var bibbase_data = {"data":"<img src=\"//bibbase.org/img/ajax-loader.gif\" id=\"spinner\"\n  style=\"display: none;\" alt=\"Loading..\" />\n\n<div id=\"bibbase\">\n\n  <script type=\"text/javascript\">\n    var bibbase = {\n      params: {\"bib\":\"https://bibbase.org/zotero/kasicamper\",\"jsonp\":\"1\",\"host\":\"bibbase.org\",\"ssl\":false},\n      data: [{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Multi-year aboveground data of minirhizotron facilities in Selhausen\",\"volume\":\"11\",\"issn\":\"2052-4463\",\"url\":\"https://www.nature.com/articles/s41597-024-03535-2\",\"doi\":\"10.1038/s41597-024-03535-2\",\"abstract\":\"Abstract Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO 2 and H 2 O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO 2 exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2025-02-18\",\"journal\":\"Scientific Data\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Nguyen\"],\"firstnames\":[\"Thuy\",\"Huu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lopez\"],\"firstnames\":[\"Gina\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Seidel\"],\"firstnames\":[\"Sabine\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lärm\"],\"firstnames\":[\"Lena\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bauer\"],\"firstnames\":[\"Felix\",\"Maximilian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Klotzsche\"],\"firstnames\":[\"Anja\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schnepf\"],\"firstnames\":[\"Andrea\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hüging\"],\"firstnames\":[\"Hubert\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ewert\"],\"firstnames\":[\"Frank\"],\"suffixes\":[]}],\"month\":\"June\",\"year\":\"2024\",\"pages\":\"674\",\"bibtex\":\"@article{nguyen_multi-year_2024,\\n\\ttitle = {Multi-year aboveground data of minirhizotron facilities in {Selhausen}},\\n\\tvolume = {11},\\n\\tissn = {2052-4463},\\n\\turl = {https://www.nature.com/articles/s41597-024-03535-2},\\n\\tdoi = {10.1038/s41597-024-03535-2},\\n\\tabstract = {Abstract\\n            \\n              Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO\\n              2\\n              and H\\n              2\\n              O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO\\n              2\\n              exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2025-02-18},\\n\\tjournal = {Scientific Data},\\n\\tauthor = {Nguyen, Thuy Huu and Lopez, Gina and Seidel, Sabine J. and Lärm, Lena and Bauer, Felix Maximilian and Klotzsche, Anja and Schnepf, Andrea and Gaiser, Thomas and Hüging, Hubert and Ewert, Frank},\\n\\tmonth = jun,\\n\\tyear = {2024},\\n\\tpages = {674},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Nguyen, T. H.\",\"Lopez, G.\",\"Seidel, S. J.\",\"Lärm, L.\",\"Bauer, F. M.\",\"Klotzsche, A.\",\"Schnepf, A.\",\"Gaiser, T.\",\"Hüging, H.\",\"Ewert, F.\"],\"key\":\"nguyen_multi-year_2024\",\"id\":\"nguyen_multi-year_2024\",\"bibbaseid\":\"nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s41597-024-03535-2\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Mechanistically derived macroscopic root water uptake functions: The <i>α</i> and <i>ω</i> of root water uptake functions\",\"volume\":\"23\",\"issn\":\"1539-1663, 1539-1663\",\"shorttitle\":\"Mechanistically derived macroscopic root water uptake functions\",\"url\":\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333\",\"doi\":\"10.1002/vzj2.20333\",\"abstract\":\"Abstract Water uptake by plant roots is an important component of the soil water balance. Predicting to what extent potential transpiration from the canopy, that is, transpiration demand, can be met by supply of water from the soil through the root system is crucial to simulate the actual transpiration and assess vegetation water stress. In models that simulate the dynamics of vertical soil water content profiles as a function of water fluxes and soil water potential gradients, the root water uptake (RWU) distribution is represented by macroscopic sink terms. We present RWU functions that calculate sink terms based on a mechanistic model of water flow in the soil–root system. Based on soil–root hydraulics, we define α ‐supply functions representing the maximal uptake by the root system from a certain soil depth when the root collar water potential equals the wilting point, ω ‐supply factors representing the maximal supply from the entire root system, and a critical ω c factor representing the potential transpiration demand. These functions and factors are subsequently used to calculate RWU distributions directly from potential transpiration or demand and the soil water potentials. Unlike currently used approaches, which define α ‐stress functions and ω factors representing ratios of actual uptake to uptake demand, the supply‐based formulations can be derived directly from soil and root hydraulic properties and can represent processes like root hydraulic redistribution and hydraulic lift. , Core Ideas Functions to calculate root water uptake (RWU) from different soil depths were derived. RWU is calculated directly using soil water potentials and the potential transpiration rate. The functions are derived using soil and root hydraulic properties. Phenomena like RWU compensation, hydraulic redistribution, and hydraulic lift are reproduced. Similarities and differences with currently used uptake functions are discussed.\",\"language\":\"en\",\"number\":\"4\",\"urldate\":\"2025-02-18\",\"journal\":\"Vadose Zone Journal\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Vanderborght\"],\"firstnames\":[\"Jan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Couvreur\"],\"firstnames\":[\"Valentin\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Javaux\"],\"firstnames\":[\"Mathieu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Leitner\"],\"firstnames\":[\"Daniel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schnepf\"],\"firstnames\":[\"Andrea\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]}],\"month\":\"July\",\"year\":\"2024\",\"pages\":\"e20333\",\"bibtex\":\"@article{vanderborght_mechanistically_2024,\\n\\ttitle = {Mechanistically derived macroscopic root water uptake functions: {The} \\\\textit{α} and \\\\textit{ω} of root water uptake functions},\\n\\tvolume = {23},\\n\\tissn = {1539-1663, 1539-1663},\\n\\tshorttitle = {Mechanistically derived macroscopic root water uptake functions},\\n\\turl = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333},\\n\\tdoi = {10.1002/vzj2.20333},\\n\\tabstract = {Abstract\\n            \\n              Water uptake by plant roots is an important component of the soil water balance. Predicting to what extent potential transpiration from the canopy, that is, transpiration demand, can be met by supply of water from the soil through the root system is crucial to simulate the actual transpiration and assess vegetation water stress. In models that simulate the dynamics of vertical soil water content profiles as a function of water fluxes and soil water potential gradients, the root water uptake (RWU) distribution is represented by macroscopic sink terms. We present RWU functions that calculate sink terms based on a mechanistic model of water flow in the soil–root system. Based on soil–root hydraulics, we define\\n              α\\n              ‐supply functions representing the maximal uptake by the root system from a certain soil depth when the root collar water potential equals the wilting point,\\n              ω\\n              ‐supply factors representing the maximal supply from the entire root system, and a critical\\n              \\n                ω\\n                c\\n              \\n              factor representing the potential transpiration demand. These functions and factors are subsequently used to calculate RWU distributions directly from potential transpiration or demand and the soil water potentials. Unlike currently used approaches, which define\\n              α\\n              ‐stress functions and\\n              ω\\n              factors representing ratios of actual uptake to uptake demand, the supply‐based formulations can be derived directly from soil and root hydraulic properties and can represent processes like root hydraulic redistribution and hydraulic lift.\\n            \\n          , \\n            Core Ideas\\n            \\n              \\n                \\n                  Functions to calculate root water uptake (RWU) from different soil depths were derived.\\n                \\n                \\n                  RWU is calculated directly using soil water potentials and the potential transpiration rate.\\n                \\n                \\n                  The functions are derived using soil and root hydraulic properties.\\n                \\n                \\n                  Phenomena like RWU compensation, hydraulic redistribution, and hydraulic lift are reproduced.\\n                \\n                \\n                  Similarities and differences with currently used uptake functions are discussed.},\\n\\tlanguage = {en},\\n\\tnumber = {4},\\n\\turldate = {2025-02-18},\\n\\tjournal = {Vadose Zone Journal},\\n\\tauthor = {Vanderborght, Jan and Couvreur, Valentin and Javaux, Mathieu and Leitner, Daniel and Schnepf, Andrea and Vereecken, Harry},\\n\\tmonth = jul,\\n\\tyear = {2024},\\n\\tpages = {e20333},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Vanderborght, J.\",\"Couvreur, V.\",\"Javaux, M.\",\"Leitner, D.\",\"Schnepf, A.\",\"Vereecken, H.\"],\"key\":\"vanderborght_mechanistically_2024\",\"id\":\"vanderborght_mechanistically_2024\",\"bibbaseid\":\"vanderborght-couvreur-javaux-leitner-schnepf-vereecken-mechanisticallyderivedmacroscopicrootwateruptakefunctionstheiiandiiofrootwateruptakefunctions-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Summer evapotranspiration-cloud feedbacks in land-atmosphere interactions over Europe\",\"volume\":\"62\",\"issn\":\"0930-7575, 1432-0894\",\"url\":\"https://link.springer.com/10.1007/s00382-024-07475-w\",\"doi\":\"10.1007/s00382-024-07475-w\",\"abstract\":\"Abstract Land-atmosphere (L-A) feedbacks are important for understanding regional climate functioning. However, the accurate quantification of feedback strength is challenging due to complex, nonlinear interactions and varying background atmospheric conditions. In particular, the role of cloud water in the terrestrial water cycle is often ignored or simplified in previous L-A feedback studies, which overlook the relationship between evapotranspiration ( ET ) and cloud water ( TQC ). This study diagnoses the interactions between $$\\\\:ET$$ , $$\\\\:TQC$$ and its dynamics ( $$\\\\:\\\\varDelta\\\\:TQC/\\\\varDelta\\\\:t$$ ) under different atmospheric conditions by conducting correlation and a novel scaling analysis, based on a coupled regional climate model simulation. Contrasting correlation relationships between $$\\\\:ET$$ , $$\\\\:TQC$$ and $$\\\\:\\\\varDelta\\\\:TQC/\\\\varDelta\\\\:t$$ were identified, indicating the positive feedback between $$\\\\:ET$$ and the dynamics in cloud water. Two types of positive scaling relationships between $$\\\\:ET$$ and $$\\\\:\\\\varDelta\\\\:TQC/\\\\varDelta\\\\:t$$ were identified by K-means clustering. The analysis shows a contrasting north-south distribution of the scaling relationship that is similar to the spatial distribution of energy-limited and water-limited $$\\\\:ET$$ regimes, highlighting the role of ET regimes in modulating the $$\\\\:ET$$ - $$\\\\:\\\\varDelta\\\\:TQC/\\\\varDelta\\\\:t$$ scaling relationships. Moreover, the feedback strength and scaling relationship are affected by atmospheric moisture flux dynamics, providing remote moisture sources and altering dry/wet conditions. Our results highlight the role of cloud water in the atmospheric part of the L-A process chain and reveal the effect of different atmospheric conditions on L-A interactions based on the new analysis framework.\",\"language\":\"en\",\"number\":\"12\",\"urldate\":\"2025-02-14\",\"journal\":\"Climate Dynamics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Zhang\"],\"firstnames\":[\"Yikui\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wagner\"],\"firstnames\":[\"Niklas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Goergen\"],\"firstnames\":[\"Klaus\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kollet\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]}],\"month\":\"December\",\"year\":\"2024\",\"pages\":\"10767–10783\",\"bibtex\":\"@article{zhang_summer_2024,\\n\\ttitle = {Summer evapotranspiration-cloud feedbacks in land-atmosphere interactions over {Europe}},\\n\\tvolume = {62},\\n\\tissn = {0930-7575, 1432-0894},\\n\\turl = {https://link.springer.com/10.1007/s00382-024-07475-w},\\n\\tdoi = {10.1007/s00382-024-07475-w},\\n\\tabstract = {Abstract\\n            \\n              Land-atmosphere (L-A) feedbacks are important for understanding regional climate functioning. However, the accurate quantification of feedback strength is challenging due to complex, nonlinear interactions and varying background atmospheric conditions. In particular, the role of cloud water in the terrestrial water cycle is often ignored or simplified in previous L-A feedback studies, which overlook the relationship between evapotranspiration (\\n              ET\\n              ) and cloud water (\\n              TQC\\n              ). This study diagnoses the interactions between\\n              \\n                \\\\$\\\\${\\\\textbackslash}:ET\\\\$\\\\$\\n              \\n              ,\\n              \\n                \\\\$\\\\${\\\\textbackslash}:TQC\\\\$\\\\$\\n              \\n              and its dynamics (\\n              \\n                \\\\$\\\\${\\\\textbackslash}:{\\\\textbackslash}varDelta{\\\\textbackslash}:TQC/{\\\\textbackslash}varDelta{\\\\textbackslash}:t\\\\$\\\\$\\n              \\n              ) under different atmospheric conditions by conducting correlation and a novel scaling analysis, based on a coupled regional climate model simulation. Contrasting correlation relationships between\\n              \\n                \\\\$\\\\${\\\\textbackslash}:ET\\\\$\\\\$\\n              \\n              ,\\n              \\n                \\\\$\\\\${\\\\textbackslash}:TQC\\\\$\\\\$\\n              \\n              and\\n              \\n                \\\\$\\\\${\\\\textbackslash}:{\\\\textbackslash}varDelta{\\\\textbackslash}:TQC/{\\\\textbackslash}varDelta{\\\\textbackslash}:t\\\\$\\\\$\\n              \\n              were identified, indicating the positive feedback between\\n              \\n                \\\\$\\\\${\\\\textbackslash}:ET\\\\$\\\\$\\n              \\n              and the dynamics in cloud water. Two types of positive scaling relationships between\\n              \\n                \\\\$\\\\${\\\\textbackslash}:ET\\\\$\\\\$\\n              \\n              and\\n              \\n                \\\\$\\\\${\\\\textbackslash}:{\\\\textbackslash}varDelta{\\\\textbackslash}:TQC/{\\\\textbackslash}varDelta{\\\\textbackslash}:t\\\\$\\\\$\\n              \\n              were identified by K-means clustering. The analysis shows a contrasting north-south distribution of the scaling relationship that is similar to the spatial distribution of energy-limited and water-limited\\n              \\n                \\\\$\\\\${\\\\textbackslash}:ET\\\\$\\\\$\\n              \\n              regimes, highlighting the role of ET regimes in modulating the\\n              \\n                \\\\$\\\\${\\\\textbackslash}:ET\\\\$\\\\$\\n              \\n              -\\n              \\n                \\\\$\\\\${\\\\textbackslash}:{\\\\textbackslash}varDelta{\\\\textbackslash}:TQC/{\\\\textbackslash}varDelta{\\\\textbackslash}:t\\\\$\\\\$\\n              \\n              scaling relationships. Moreover, the feedback strength and scaling relationship are affected by atmospheric moisture flux dynamics, providing remote moisture sources and altering dry/wet conditions. Our results highlight the role of cloud water in the atmospheric part of the L-A process chain and reveal the effect of different atmospheric conditions on L-A interactions based on the new analysis framework.},\\n\\tlanguage = {en},\\n\\tnumber = {12},\\n\\turldate = {2025-02-14},\\n\\tjournal = {Climate Dynamics},\\n\\tauthor = {Zhang, Yikui and Wagner, Niklas and Goergen, Klaus and Kollet, Stefan},\\n\\tmonth = dec,\\n\\tyear = {2024},\\n\\tpages = {10767--10783},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Zhang, Y.\",\"Wagner, N.\",\"Goergen, K.\",\"Kollet, S.\"],\"key\":\"zhang_summer_2024\",\"id\":\"zhang_summer_2024\",\"bibbaseid\":\"zhang-wagner-goergen-kollet-summerevapotranspirationcloudfeedbacksinlandatmosphereinteractionsovereurope-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://link.springer.com/10.1007/s00382-024-07475-w\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"How realistic are multi-decadal reconstructions of GRACE-like total water storage anomalies?\",\"volume\":\"645\",\"issn\":\"00221694\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762\",\"doi\":\"10.1016/j.jhydrol.2024.132180\",\"language\":\"en\",\"urldate\":\"2025-02-14\",\"journal\":\"Journal of Hydrology\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Hacker\"],\"firstnames\":[\"Charlotte\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]}],\"month\":\"December\",\"year\":\"2024\",\"pages\":\"132180\",\"bibtex\":\"@article{hacker_how_2024,\\n\\ttitle = {How realistic are multi-decadal reconstructions of {GRACE}-like total water storage anomalies?},\\n\\tvolume = {645},\\n\\tissn = {00221694},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762},\\n\\tdoi = {10.1016/j.jhydrol.2024.132180},\\n\\tlanguage = {en},\\n\\turldate = {2025-02-14},\\n\\tjournal = {Journal of Hydrology},\\n\\tauthor = {Hacker, Charlotte and Kusche, Jürgen},\\n\\tmonth = dec,\\n\\tyear = {2024},\\n\\tpages = {132180},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Hacker, C.\",\"Kusche, J.\"],\"key\":\"hacker_how_2024\",\"id\":\"hacker_how_2024\",\"bibbaseid\":\"hacker-kusche-howrealisticaremultidecadalreconstructionsofgraceliketotalwaterstorageanomalies-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe\",\"volume\":\"18\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"1991-9603\",\"url\":\"https://gmd.copernicus.org/articles/18/287/2025/\",\"doi\":\"10.5194/gmd-18-287-2025\",\"abstract\":\"Abstract. Evapotranspiration (ET) and gross primary production (GPP) are critical fluxes contributing to the energy, water, and carbon exchanges between the atmosphere and the land surface. Land surface models such as the Community Land Model v5 (CLM5) quantify these fluxes, estimate the state of carbon budgets and water resources, and contribute to a better understanding of climate change's impact on ecosystems. Past studies have shown the ability of CLM5 to model ET and GPP magnitudes well but emphasized systematic underestimations and lower variability than in the observations. Here, we evaluated CLM5's predictions of water and energy fluxes using observations from eddy covariance stations from the Integrated Carbon Observation System (ICOS), remote sensing, and reanalysis data sets. We assess simulated ET and GPP from the grid scale (CLM5grid) and the plant functional type (PFT) scale (CLM5PFT). CLM5PFT exhibited a low systematic error in simulating the ET at the ICOS sites (average bias of −4.68 %), indicating that PFT-specific ET closely matches the observations' magnitude. GPP was underestimated by CLM5PFT, especially in deciduous forests (bias of −43.76 %). The results showed an underestimation of the spatiotemporal variability in the simulated ET and GPP distribution moments across PFTs for both CLM setups compared to reanalysis data and remote-sensing products. These findings provide essential insights for improving land surface models, highlighting the need to enhance the CLM5's ability to capture the spatiotemporal variability in ET and GPP simulations across PFTs.\",\"language\":\"en\",\"number\":\"2\",\"urldate\":\"2025-02-14\",\"journal\":\"Geoscientific Model Development\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Poppe\",\"Terán\"],\"firstnames\":[\"Christian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Naz\"],\"firstnames\":[\"Bibi\",\"S.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Baatz\"],\"firstnames\":[\"Roland\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Fisher\"],\"firstnames\":[\"Rosie\",\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hendricks\",\"Franssen\"],\"firstnames\":[\"Harrie-Jan\"],\"suffixes\":[]}],\"month\":\"January\",\"year\":\"2025\",\"pages\":\"287–317\",\"bibtex\":\"@article{poppe_teran_systematic_2025,\\n\\ttitle = {Systematic underestimation of type-specific ecosystem process variability in the {Community} {Land} {Model} v5 over {Europe}},\\n\\tvolume = {18},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {1991-9603},\\n\\turl = {https://gmd.copernicus.org/articles/18/287/2025/},\\n\\tdoi = {10.5194/gmd-18-287-2025},\\n\\tabstract = {Abstract. Evapotranspiration (ET) and gross primary production (GPP) are critical fluxes contributing to the energy, water, and carbon exchanges between the atmosphere and the land surface. Land surface models such as the Community Land Model v5 (CLM5) quantify these fluxes, estimate the state of carbon budgets and water resources, and contribute to a better understanding of climate change's impact on ecosystems. Past studies have shown the ability of CLM5 to model ET and GPP magnitudes well but emphasized systematic underestimations and lower variability than in the observations. Here, we evaluated CLM5's predictions of water and energy fluxes using observations from eddy covariance stations from the Integrated Carbon Observation System (ICOS), remote sensing, and reanalysis data sets. We assess simulated ET and GPP from the grid scale (CLM5grid) and the plant functional type (PFT) scale (CLM5PFT). CLM5PFT exhibited a low systematic error in simulating the ET at the ICOS sites (average bias of −4.68 \\\\%), indicating that PFT-specific ET closely matches the observations' magnitude. GPP was underestimated by CLM5PFT, especially in deciduous forests (bias of −43.76 \\\\%). The results showed an underestimation of the spatiotemporal variability in the simulated ET and GPP distribution moments across PFTs for both CLM setups compared to reanalysis data and remote-sensing products. These findings provide essential insights for improving land surface models, highlighting the need to enhance the CLM5's ability to capture the spatiotemporal variability in ET and GPP simulations across PFTs.},\\n\\tlanguage = {en},\\n\\tnumber = {2},\\n\\turldate = {2025-02-14},\\n\\tjournal = {Geoscientific Model Development},\\n\\tauthor = {Poppe Terán, Christian and Naz, Bibi S. and Vereecken, Harry and Baatz, Roland and Fisher, Rosie A. and Hendricks Franssen, Harrie-Jan},\\n\\tmonth = jan,\\n\\tyear = {2025},\\n\\tpages = {287--317},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Poppe Terán, C.\",\"Naz, B. S.\",\"Vereecken, H.\",\"Baatz, R.\",\"Fisher, R. A.\",\"Hendricks Franssen, H.\"],\"key\":\"poppe_teran_systematic_2025\",\"id\":\"poppe_teran_systematic_2025\",\"bibbaseid\":\"poppetern-naz-vereecken-baatz-fisher-hendricksfranssen-systematicunderestimationoftypespecificecosystemprocessvariabilityinthecommunitylandmodelv5overeurope-2025\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://gmd.copernicus.org/articles/18/287/2025/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Measuring Off-nadir river water levels and slopes from altimeter Fully-Focused SAR mode\",\"volume\":\"650\",\"issn\":\"00221694\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498\",\"doi\":\"10.1016/j.jhydrol.2024.132553\",\"language\":\"en\",\"urldate\":\"2025-02-14\",\"journal\":\"Journal of Hydrology\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Chen\"],\"firstnames\":[\"Jiaming\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Fenoglio\"],\"firstnames\":[\"Luciana\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]}],\"month\":\"April\",\"year\":\"2025\",\"pages\":\"132553\",\"bibtex\":\"@article{chen_measuring_2025,\\n\\ttitle = {Measuring {Off}-nadir river water levels and slopes from altimeter {Fully}-{Focused} {SAR} mode},\\n\\tvolume = {650},\\n\\tissn = {00221694},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498},\\n\\tdoi = {10.1016/j.jhydrol.2024.132553},\\n\\tlanguage = {en},\\n\\turldate = {2025-02-14},\\n\\tjournal = {Journal of Hydrology},\\n\\tauthor = {Chen, Jiaming and Fenoglio, Luciana and Kusche, Jürgen},\\n\\tmonth = apr,\\n\\tyear = {2025},\\n\\tpages = {132553},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Chen, J.\",\"Fenoglio, L.\",\"Kusche, J.\"],\"key\":\"chen_measuring_2025\",\"id\":\"chen_measuring_2025\",\"bibbaseid\":\"chen-fenoglio-kusche-measuringoffnadirriverwaterlevelsandslopesfromaltimeterfullyfocusedsarmode-2025\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Would the 2021 Western Europe Flood Event Be Visible in Satellite Gravimetry?\",\"volume\":\"130\",\"issn\":\"2169-897X, 2169-8996\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190\",\"doi\":\"10.1029/2024JD042190\",\"abstract\":\"Abstract The primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in the Earth's gravitational field. Distance variations between the two GRACE‐FO satellites, recorded by a K‐Band Ranging system and a new Laser Ranging Interferometer (LRI), are significantly influenced by atmospheric mass redistribution. We investigate whether the sub‐monthly variations in atmospheric water mass, precipitation, and changes in total water storage during the extreme flood event in western Europe in 2021 were sufficiently large to influence the satellite gravity field measurements, if the GRACE‐FO satellites would have passed directly over the region. We use several data sets such as weather forecasts (ICON‐D2 model), hydrological simulations (ParFlow/CLM), observations as well as reanalyses, showing the high uncertainty between different estimations of the considered variables: total precipitable water, total precipitation, and total water storage. Our estimates suggest a potentially noticeable impact of the 2021 flood event on the GRACE‐FO satellites. Although it was globally seen a rather small event, even the atmospheric water mass beyond water vapor, which is not considered within the de‐aliasing process, is close to the LRI detection accuracy. This is particularly relevant for future gravity missions, which will use the LRI with potentially higher sensitivity as their main instrument. Sub‐monthly variations in the total atmospheric water mass, that is, beyond water vapor of huge extreme precipitation events should be investigated further to reduce potential future aliasing errors. , Plain Language Summary The GRACE Follow‐On (GRACE‐FO) satellite mission measures temporal changes in the Earth's gravitational field by tracking the distance between GRACE‐FO's two satellites with a K‐Band Ranging system and a new laser ranging interferometer (LRI). Sub‐monthly variations in atmospheric mass impact these measurements, so it is essential to account for these variations to minimize errors in the derived monthly gravity fields. In July 2021, western Europe experienced an extreme flood event. We investigate whether its unusually high atmospheric water masses, strong precipitation, and increased overall water storage could impact the satellite's gravity measurements. We use data from several sources, including weather forecasts, hydrological simulations, observed precipitation and reanalysis data. We estimate potential changes in the distance between the satellites if they had flown over the flooded area during the flood period from July 14 to 16, 2021. Our upper estimates suggest that the flood event could have been seen in the GRACE‐FO measurements in case of a direct overpass. To improve the accuracy of future missions, which will rely on the LRI as their primary instrument, we suggest to further investigate short‐term variations in atmospheric water mass, that is, beyond water vapor to reduce potential errors. , Key Points Simulations show that the flood event could have noticeably impacted GRACE‐FO Laser Ranging Interferometer measurements, if the satellites had flown over the event Even the instantaneous atmospheric water mass was likely large enough to have been detected Atmospheric water beyond water vapor is not considered in current de‐aliasing products, and we suggest this paradigm should be reassessed\",\"language\":\"en\",\"number\":\"3\",\"urldate\":\"2025-02-03\",\"journal\":\"Journal of Geophysical Research: Atmospheres\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Kracheletz\"],\"firstnames\":[\"Magdalena\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Liu\"],\"firstnames\":[\"Ziyu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Springer\"],\"firstnames\":[\"Anne\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Friederichs\"],\"firstnames\":[\"Petra\"],\"suffixes\":[]}],\"month\":\"February\",\"year\":\"2025\",\"pages\":\"e2024JD042190\",\"bibtex\":\"@article{kracheletz_would_2025,\\n\\ttitle = {Would the 2021 {Western} {Europe} {Flood} {Event} {Be} {Visible} in {Satellite} {Gravimetry}?},\\n\\tvolume = {130},\\n\\tissn = {2169-897X, 2169-8996},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190},\\n\\tdoi = {10.1029/2024JD042190},\\n\\tabstract = {Abstract\\n            The primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in the Earth's gravitational field. Distance variations between the two GRACE‐FO satellites, recorded by a K‐Band Ranging system and a new Laser Ranging Interferometer (LRI), are significantly influenced by atmospheric mass redistribution. We investigate whether the sub‐monthly variations in atmospheric water mass, precipitation, and changes in total water storage during the extreme flood event in western Europe in 2021 were sufficiently large to influence the satellite gravity field measurements, if the GRACE‐FO satellites would have passed directly over the region. We use several data sets such as weather forecasts (ICON‐D2 model), hydrological simulations (ParFlow/CLM), observations as well as reanalyses, showing the high uncertainty between different estimations of the considered variables: total precipitable water, total precipitation, and total water storage. Our estimates suggest a potentially noticeable impact of the 2021 flood event on the GRACE‐FO satellites. Although it was globally seen a rather small event, even the atmospheric water mass beyond water vapor, which is not considered within the de‐aliasing process, is close to the LRI detection accuracy. This is particularly relevant for future gravity missions, which will use the LRI with potentially higher sensitivity as their main instrument. Sub‐monthly variations in the total atmospheric water mass, that is, beyond water vapor of huge extreme precipitation events should be investigated further to reduce potential future aliasing errors.\\n          , \\n            Plain Language Summary\\n            The GRACE Follow‐On (GRACE‐FO) satellite mission measures temporal changes in the Earth's gravitational field by tracking the distance between GRACE‐FO's two satellites with a K‐Band Ranging system and a new laser ranging interferometer (LRI). Sub‐monthly variations in atmospheric mass impact these measurements, so it is essential to account for these variations to minimize errors in the derived monthly gravity fields. In July 2021, western Europe experienced an extreme flood event. We investigate whether its unusually high atmospheric water masses, strong precipitation, and increased overall water storage could impact the satellite's gravity measurements. We use data from several sources, including weather forecasts, hydrological simulations, observed precipitation and reanalysis data. We estimate potential changes in the distance between the satellites if they had flown over the flooded area during the flood period from July 14 to 16, 2021. Our upper estimates suggest that the flood event could have been seen in the GRACE‐FO measurements in case of a direct overpass. To improve the accuracy of future missions, which will rely on the LRI as their primary instrument, we suggest to further investigate short‐term variations in atmospheric water mass, that is, beyond water vapor to reduce potential errors.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  Simulations show that the flood event could have noticeably impacted GRACE‐FO Laser Ranging Interferometer measurements, if the satellites had flown over the event\\n                \\n                \\n                  Even the instantaneous atmospheric water mass was likely large enough to have been detected\\n                \\n                \\n                  Atmospheric water beyond water vapor is not considered in current de‐aliasing products, and we suggest this paradigm should be reassessed},\\n\\tlanguage = {en},\\n\\tnumber = {3},\\n\\turldate = {2025-02-03},\\n\\tjournal = {Journal of Geophysical Research: Atmospheres},\\n\\tauthor = {Kracheletz, Magdalena and Liu, Ziyu and Springer, Anne and Kusche, Jürgen and Friederichs, Petra},\\n\\tmonth = feb,\\n\\tyear = {2025},\\n\\tpages = {e2024JD042190},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Kracheletz, M.\",\"Liu, Z.\",\"Springer, A.\",\"Kusche, J.\",\"Friederichs, P.\"],\"key\":\"kracheletz_would_2025\",\"id\":\"kracheletz_would_2025\",\"bibbaseid\":\"kracheletz-liu-springer-kusche-friederichs-wouldthe2021westerneuropefloodeventbevisibleinsatellitegravimetry-2025\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Coastal Flooding in Asian Megadeltas: Recent Advances, Persistent Challenges, and Call for Actions Amidst Local and Global Changes\",\"volume\":\"62\",\"issn\":\"8755-1209, 1944-9208\",\"shorttitle\":\"Coastal Flooding in Asian Megadeltas\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846\",\"doi\":\"10.1029/2024RG000846\",\"abstract\":\"Abstract Asian megadeltas, specifically the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas host half of the world's deltaic population and are vital for Asian countries' ecosystems and food production. These deltas are extremely vulnerable to global change. Accelerating relative sea‐level rise, combined with rapid socio‐economic development intensifies these vulnerabilities and calls for a comprehensive understanding of current and future coastal flood dynamics. Here we provide a state‐of‐the‐art on the current knowledge and recent advances in quantifying and understanding the drivers of coastal flood‐related hazards in these deltas. We discuss the environmental and physical drivers, including climate influence, hydrology, oceanography, geomorphology, and geophysical processes and how they interact from short to long‐term changes, including during extreme events. We also jointly examine how human disturbances, with catchment interventions, land use changes and resource exploitations, contribute to coastal flooding in the deltas. Through a systems perspective, we characterize the current state of the deltaic systems and provide essential insights for shaping their sustainable future trajectories regarding the multifaceted challenges of coastal flooding. , Plain Language Summary Asian megadeltas, including the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas, are home to half of the world's deltaic population and play a critical role in Asian food production. However, these deltas are at high risk to climatic changes, with the vast majority of the world's coastal flood exposure observed in these systems. Rising sea levels and rapid socio‐economic development worsen these vulnerabilities, necessitating a comprehensive understanding of coastal flooding dynamics across the five deltas. This review provides up‐to‐date insights on the current understanding and quantification of the drivers of coastal flood‐related hazards. It examines environmental and biophysical factors, such as climate, hydrology, oceanography, geomorphology, and geophysical processes, and how these may interact during extreme events. The review also explores how human activities, like catchment interventions, land use changes, and resource exploitation, contribute to coastal flooding. By offering a systematic perspective, this review characterizes the current state of knowledge on these deltaic systems and provides valuable insights for shaping sustainable future trajectories in the face of the challenges posed by coastal flooding. , Key Points Urgent action is needed to address data gaps in monitoring coastal flooding in Asian megadeltas Integrated approaches, including in situ data, remote sensing and advanced modeling, are needed to understand coastal flooding impacts Unprecedented changes in Asian megadeltas call for integrated studies; decisions made today shape deltaic sustainability for decades\",\"language\":\"en\",\"number\":\"4\",\"urldate\":\"2025-01-06\",\"journal\":\"Reviews of Geophysics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Becker\"],\"firstnames\":[\"M.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Seeger\"],\"firstnames\":[\"K.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Paszkowski\"],\"firstnames\":[\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Marcos\"],\"firstnames\":[\"M.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Papa\"],\"firstnames\":[\"F.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Almar\"],\"firstnames\":[\"R.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bates\"],\"firstnames\":[\"P.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"France‐Lanord\"],\"firstnames\":[\"C.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hossain\"],\"firstnames\":[\"Md\",\"S.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Khan\"],\"firstnames\":[\"Md\",\"J.\",\"U.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Karegar\"],\"firstnames\":[\"M.\",\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Karpytchev\"],\"firstnames\":[\"M.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Long\"],\"firstnames\":[\"N.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Minderhoud\"],\"firstnames\":[\"P.\",\"S.\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Neal\"],\"firstnames\":[\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Nicholls\"],\"firstnames\":[\"R.\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Syvitski\"],\"firstnames\":[\"J.\"],\"suffixes\":[]}],\"month\":\"December\",\"year\":\"2024\",\"pages\":\"e2024RG000846\",\"bibtex\":\"@article{becker_coastal_2024,\\n\\ttitle = {Coastal {Flooding} in {Asian} {Megadeltas}: {Recent} {Advances}, {Persistent} {Challenges}, and {Call} for {Actions} {Amidst} {Local} and {Global} {Changes}},\\n\\tvolume = {62},\\n\\tissn = {8755-1209, 1944-9208},\\n\\tshorttitle = {Coastal {Flooding} in {Asian} {Megadeltas}},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846},\\n\\tdoi = {10.1029/2024RG000846},\\n\\tabstract = {Abstract\\n            Asian megadeltas, specifically the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas host half of the world's deltaic population and are vital for Asian countries' ecosystems and food production. These deltas are extremely vulnerable to global change. Accelerating relative sea‐level rise, combined with rapid socio‐economic development intensifies these vulnerabilities and calls for a comprehensive understanding of current and future coastal flood dynamics. Here we provide a state‐of‐the‐art on the current knowledge and recent advances in quantifying and understanding the drivers of coastal flood‐related hazards in these deltas. We discuss the environmental and physical drivers, including climate influence, hydrology, oceanography, geomorphology, and geophysical processes and how they interact from short to long‐term changes, including during extreme events. We also jointly examine how human disturbances, with catchment interventions, land use changes and resource exploitations, contribute to coastal flooding in the deltas. Through a systems perspective, we characterize the current state of the deltaic systems and provide essential insights for shaping their sustainable future trajectories regarding the multifaceted challenges of coastal flooding.\\n          , \\n            Plain Language Summary\\n            Asian megadeltas, including the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas, are home to half of the world's deltaic population and play a critical role in Asian food production. However, these deltas are at high risk to climatic changes, with the vast majority of the world's coastal flood exposure observed in these systems. Rising sea levels and rapid socio‐economic development worsen these vulnerabilities, necessitating a comprehensive understanding of coastal flooding dynamics across the five deltas. This review provides up‐to‐date insights on the current understanding and quantification of the drivers of coastal flood‐related hazards. It examines environmental and biophysical factors, such as climate, hydrology, oceanography, geomorphology, and geophysical processes, and how these may interact during extreme events. The review also explores how human activities, like catchment interventions, land use changes, and resource exploitation, contribute to coastal flooding. By offering a systematic perspective, this review characterizes the current state of knowledge on these deltaic systems and provides valuable insights for shaping sustainable future trajectories in the face of the challenges posed by coastal flooding.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  Urgent action is needed to address data gaps in monitoring coastal flooding in Asian megadeltas\\n                \\n                \\n                  Integrated approaches, including in situ data, remote sensing and advanced modeling, are needed to understand coastal flooding impacts\\n                \\n                \\n                  Unprecedented changes in Asian megadeltas call for integrated studies; decisions made today shape deltaic sustainability for decades},\\n\\tlanguage = {en},\\n\\tnumber = {4},\\n\\turldate = {2025-01-06},\\n\\tjournal = {Reviews of Geophysics},\\n\\tauthor = {Becker, M. and Seeger, K. and Paszkowski, A. and Marcos, M. and Papa, F. and Almar, R. and Bates, P. and France‐Lanord, C. and Hossain, Md S. and Khan, Md J. U. and Karegar, M. A. and Karpytchev, M. and Long, N. and Minderhoud, P. S. J. and Neal, J. and Nicholls, R. J. and Syvitski, J.},\\n\\tmonth = dec,\\n\\tyear = {2024},\\n\\tpages = {e2024RG000846},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Becker, M.\",\"Seeger, K.\",\"Paszkowski, A.\",\"Marcos, M.\",\"Papa, F.\",\"Almar, R.\",\"Bates, P.\",\"France‐Lanord, C.\",\"Hossain, M. S.\",\"Khan, M. J. U.\",\"Karegar, M. A.\",\"Karpytchev, M.\",\"Long, N.\",\"Minderhoud, P. S. J.\",\"Neal, J.\",\"Nicholls, R. J.\",\"Syvitski, J.\"],\"key\":\"becker_coastal_2024\",\"id\":\"becker_coastal_2024\",\"bibbaseid\":\"becker-seeger-paszkowski-marcos-papa-almar-bates-francelanord-etal-coastalfloodinginasianmegadeltasrecentadvancespersistentchallengesandcallforactionsamidstlocalandglobalchanges-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Exploring drought hazard, vulnerability, and related impacts on agriculture in Brandenburg\",\"volume\":\"24\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"1684-9981\",\"url\":\"https://nhess.copernicus.org/articles/24/4237/2024/\",\"doi\":\"10.5194/nhess-24-4237-2024\",\"abstract\":\"Abstract. Adaptation to an increasingly dry regional climate requires spatially explicit information about current and future risks. Existing drought risk studies often rely on expert-weighted composite indicators, while empirical evidence on impact-relevant factors is still scarce. The aim of this study is to investigate to what extent hazard and vulnerability indicators can explain observed agricultural drought impacts via data-driven methods. We focus on the German federal state of Brandenburg, 2013–2022, including several consecutive drought years. As impact indicators we use thermal–spectral anomalies (land surface temperature (LST) and the normalized difference vegetation index (NDVI)) on the field level, and empirical yield gaps from reported statistics on the county level. Empirical associations to the impact indicators on both spatial levels are compared. Extreme gradient boosting (XGBoost) models explain up to about 60 % of the variance in the yield gap data (best R2 = 0.62). Model performance is more stable for the drought years and when using all crops for training rather than individual crops. Meteorological drought in June and soil quality are selected as the strongest impact-relevant factors. Rye is empirically found to be less vulnerable to drought than wheat, even on poorer soils. LST / NDVI only weakly relates to our empirical yield gaps. We recommend comparing different impact indicators on multiple scales to proceed with the development of empirically grounded risk maps.\",\"language\":\"en\",\"number\":\"12\",\"urldate\":\"2024-12-02\",\"journal\":\"Natural Hazards and Earth System Sciences\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Brill\"],\"firstnames\":[\"Fabio\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Alencar\"],\"firstnames\":[\"Pedro\",\"Henrique\",\"Lima\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhang\"],\"firstnames\":[\"Huihui\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Boeing\"],\"firstnames\":[\"Friedrich\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hüttel\"],\"firstnames\":[\"Silke\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lakes\"],\"firstnames\":[\"Tobia\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2024\",\"pages\":\"4237–4265\",\"bibtex\":\"@article{brill_exploring_2024,\\n\\ttitle = {Exploring drought hazard, vulnerability, and related impacts on agriculture in {Brandenburg}},\\n\\tvolume = {24},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {1684-9981},\\n\\turl = {https://nhess.copernicus.org/articles/24/4237/2024/},\\n\\tdoi = {10.5194/nhess-24-4237-2024},\\n\\tabstract = {Abstract. Adaptation to an increasingly dry regional climate requires spatially explicit information about current and future risks. Existing drought risk studies often rely on expert-weighted composite indicators, while empirical evidence on impact-relevant factors is still scarce. The aim of this study is to investigate to what extent hazard and vulnerability indicators can explain observed agricultural drought impacts via data-driven methods. We focus on the German federal state of Brandenburg, 2013–2022, including several consecutive drought years. As impact indicators we use thermal–spectral anomalies (land surface temperature (LST) and the normalized difference vegetation index (NDVI)) on the field level, and empirical yield gaps from reported statistics on the county level. Empirical associations to the impact indicators on both spatial levels are compared. Extreme gradient boosting (XGBoost) models explain up to about 60 \\\\% of the variance in the yield gap data (best R2 = 0.62). Model performance is more stable for the drought years and when using all crops for training rather than individual crops. Meteorological drought in June and soil quality are selected as the strongest impact-relevant factors. Rye is empirically found to be less vulnerable to drought than wheat, even on poorer soils. LST / NDVI only weakly relates to our empirical yield gaps. We recommend comparing different impact indicators on multiple scales to proceed with the development of empirically grounded risk maps.},\\n\\tlanguage = {en},\\n\\tnumber = {12},\\n\\turldate = {2024-12-02},\\n\\tjournal = {Natural Hazards and Earth System Sciences},\\n\\tauthor = {Brill, Fabio and Alencar, Pedro Henrique Lima and Zhang, Huihui and Boeing, Friedrich and Hüttel, Silke and Lakes, Tobia},\\n\\tmonth = nov,\\n\\tyear = {2024},\\n\\tpages = {4237--4265},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Brill, F.\",\"Alencar, P. H. L.\",\"Zhang, H.\",\"Boeing, F.\",\"Hüttel, S.\",\"Lakes, T.\"],\"key\":\"brill_exploring_2024\",\"id\":\"brill_exploring_2024\",\"bibbaseid\":\"brill-alencar-zhang-boeing-httel-lakes-exploringdroughthazardvulnerabilityandrelatedimpactsonagricultureinbrandenburg-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://nhess.copernicus.org/articles/24/4237/2024/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0\",\"volume\":\"17\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"1991-9603\",\"url\":\"https://gmd.copernicus.org/articles/17/7815/2024/\",\"doi\":\"10.5194/gmd-17-7815-2024\",\"abstract\":\"Abstract. Interactions and feedback between components of the Earth system can have a significant impact on local and regional climate and its changes due to global warming. These effects can be better represented by regional Earth system models (RESMs) than by traditional stand-alone atmosphere and ocean models. Here, we present the RESM Geesthacht Coupled cOAstal model SysTem (GCOAST)-AHOI v2.0, which includes a new atmospheric component, the regional climate model Icosahedral Nonhydrostatic (ICON)-CLM, which is coupled to the Nucleus for European Modelling of the Ocean (NEMO) and the hydrological discharge model HD via the OASIS3-MCT coupler. The GCOAST-AHOI model has been developed and applied for climate simulations over the EURO-CORDEX domain. Two 11-year simulations from 2008 to 2018 of the uncoupled ICON-CLM and GCOAST-AHOI give similar results for seasonal and annual means of near-surface air temperature, precipitation, mean sea level pressure, and wind speed at a height of 10 m. However, GCOAST-AHOI has a cold sea surface temperature (SST) bias of 1–2 K over the Baltic and North seas that is most pronounced in the winter and spring seasons. A possible reason for the cold SST bias could be the underestimation of the downward shortwave radiation at the surface of ICON-CLM with the current model settings. Despite the cold SST bias, GCOAST-AHOI was able to capture other key variables well, such as those mentioned above. Therefore, GCOAST-AHOI can be a useful tool for long-term climate simulations over the EURO-CORDEX domain. Compared to the stand-alone NEMO3.6 forced by ERA5 and ORAS5 boundary forcing, GCOAST-AHOI has positive biases in sea ice fraction and salinity but negative biases in runoff, which need to be investigated further in the future to improve the coupled simulations. The new OASIS3-MCT coupling interface OMCI implemented in ICON-CLM adds the possibility of coupling ICON-CLM to an external ocean model and an external hydrological discharge model using OASIS3-MCT instead of the YAC (Yet Another Coupler). Using OMCI, it is also possible to set up a RESM with ICON-CLM and other ocean and hydrology models possessing the OASIS3-MCT interface for other regions, such as the Mediterranean Sea.\",\"language\":\"en\",\"number\":\"21\",\"urldate\":\"2024-11-27\",\"journal\":\"Geoscientific Model Development\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Ho-Hagemann\"],\"firstnames\":[\"Ha\",\"Thi\",\"Minh\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Maurer\"],\"firstnames\":[\"Vera\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Poll\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Fast\"],\"firstnames\":[\"Irina\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2024\",\"pages\":\"7815–7834\",\"bibtex\":\"@article{ho-hagemann_coupling_2024,\\n\\ttitle = {Coupling the regional climate model {ICON}-{CLM} v2.6.6 to the {Earth} system model {GCOAST}-{AHOI} v2.0 using {OASIS3}-{MCT} v4.0},\\n\\tvolume = {17},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {1991-9603},\\n\\turl = {https://gmd.copernicus.org/articles/17/7815/2024/},\\n\\tdoi = {10.5194/gmd-17-7815-2024},\\n\\tabstract = {Abstract. Interactions and feedback between components of the Earth system can have a significant impact on local and regional climate and its changes due to global warming. These effects can be better represented by regional Earth system models (RESMs) than by traditional stand-alone atmosphere and ocean models. Here, we present the RESM Geesthacht Coupled cOAstal model SysTem (GCOAST)-AHOI v2.0, which includes a new atmospheric component, the regional climate model Icosahedral Nonhydrostatic (ICON)-CLM, which is coupled to the Nucleus for European Modelling of the Ocean (NEMO) and the hydrological discharge model HD via the OASIS3-MCT coupler. The GCOAST-AHOI model has been developed and applied for climate simulations over the EURO-CORDEX domain. Two 11-year simulations from 2008 to 2018 of the uncoupled ICON-CLM and GCOAST-AHOI give similar results for seasonal and annual means of near-surface air temperature, precipitation, mean sea level pressure, and wind speed at a height of 10 m. However, GCOAST-AHOI has a cold sea surface temperature (SST) bias of 1–2 K over the Baltic and North seas that is most pronounced in the winter and spring seasons. A possible reason for the cold SST bias could be the underestimation of the downward shortwave radiation at the surface of ICON-CLM with the current model settings. Despite the cold SST bias, GCOAST-AHOI was able to capture other key variables well, such as those mentioned above. Therefore, GCOAST-AHOI can be a useful tool for long-term climate simulations over the EURO-CORDEX domain. Compared to the stand-alone NEMO3.6 forced by ERA5 and ORAS5 boundary forcing, GCOAST-AHOI has positive biases in sea ice fraction and salinity but negative biases in runoff, which need to be investigated further in the future to improve the coupled simulations. The new OASIS3-MCT coupling interface OMCI implemented in ICON-CLM adds the possibility of coupling ICON-CLM to an external ocean model and an external hydrological discharge model using OASIS3-MCT instead of the YAC (Yet Another Coupler). Using OMCI, it is also possible to set up a RESM with ICON-CLM and other ocean and hydrology models possessing the OASIS3-MCT interface for other regions, such as the Mediterranean Sea.},\\n\\tlanguage = {en},\\n\\tnumber = {21},\\n\\turldate = {2024-11-27},\\n\\tjournal = {Geoscientific Model Development},\\n\\tauthor = {Ho-Hagemann, Ha Thi Minh and Maurer, Vera and Poll, Stefan and Fast, Irina},\\n\\tmonth = nov,\\n\\tyear = {2024},\\n\\tpages = {7815--7834},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Ho-Hagemann, H. T. M.\",\"Maurer, V.\",\"Poll, S.\",\"Fast, I.\"],\"key\":\"ho-hagemann_coupling_2024\",\"id\":\"ho-hagemann_coupling_2024\",\"bibbaseid\":\"hohagemann-maurer-poll-fast-couplingtheregionalclimatemodeliconclmv266totheearthsystemmodelgcoastahoiv20usingoasis3mctv40-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://gmd.copernicus.org/articles/17/7815/2024/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"A Comparative Analysis of Remote Sensing Soil Moisture Datasets Fusion Methods: Novel LSTM Approach Versus Widely Used Triple Collocation Technique\",\"volume\":\"17\",\"copyright\":\"https://creativecommons.org/licenses/by-nc-nd/4.0/\",\"issn\":\"1939-1404, 2151-1535\",\"shorttitle\":\"A Comparative Analysis of Remote Sensing Soil Moisture Datasets Fusion Methods\",\"url\":\"https://ieeexplore.ieee.org/document/10669050/\",\"doi\":\"10.1109/JSTARS.2024.3455549\",\"urldate\":\"2024-11-21\",\"journal\":\"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Zhao\"],\"firstnames\":[\"Haojin\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Montzka\"],\"firstnames\":[\"Carsten\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Franssen\"],\"firstnames\":[\"Harrie-Jan\",\"Hendricks\"],\"suffixes\":[]}],\"year\":\"2024\",\"pages\":\"16659–16671\",\"bibtex\":\"@article{zhao_comparative_2024,\\n\\ttitle = {A {Comparative} {Analysis} of {Remote} {Sensing} {Soil} {Moisture} {Datasets} {Fusion} {Methods}: {Novel} {LSTM} {Approach} {Versus} {Widely} {Used} {Triple} {Collocation} {Technique}},\\n\\tvolume = {17},\\n\\tcopyright = {https://creativecommons.org/licenses/by-nc-nd/4.0/},\\n\\tissn = {1939-1404, 2151-1535},\\n\\tshorttitle = {A {Comparative} {Analysis} of {Remote} {Sensing} {Soil} {Moisture} {Datasets} {Fusion} {Methods}},\\n\\turl = {https://ieeexplore.ieee.org/document/10669050/},\\n\\tdoi = {10.1109/JSTARS.2024.3455549},\\n\\turldate = {2024-11-21},\\n\\tjournal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},\\n\\tauthor = {Zhao, Haojin and Montzka, Carsten and Vereecken, Harry and Franssen, Harrie-Jan Hendricks},\\n\\tyear = {2024},\\n\\tpages = {16659--16671},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Zhao, H.\",\"Montzka, C.\",\"Vereecken, H.\",\"Franssen, H. H.\"],\"key\":\"zhao_comparative_2024\",\"id\":\"zhao_comparative_2024\",\"bibbaseid\":\"zhao-montzka-vereecken-franssen-acomparativeanalysisofremotesensingsoilmoisturedatasetsfusionmethodsnovellstmapproachversuswidelyusedtriplecollocationtechnique-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://ieeexplore.ieee.org/document/10669050/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Short-Term Response of Soil Organic Carbon Indices to Different Farming Strategies and Crop Rotation Systems in a Semiarid Warm Region\",\"volume\":\"2024\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"1687-7675, 1687-7667\",\"url\":\"https://www.hindawi.com/journals/aess/2024/8594691/\",\"doi\":\"10.1155/2024/8594691\",\"abstract\":\"Several indices can be used to assess the impact of short-term conservation agriculture strategies on improving soil organic carbon (SOC). To find out how the SOC pools and the carbon lability influence the carbon management index (CMI) in response to different agricultural practices in a warm semiarid region, the carbon lability index (LI) and the carbon pool index (CPI) were measured under the interactive effect of different fertilizer applications and crop residue management (hereafter referred to as “farming strategies”) in combination with four crop rotation systems in Ahvaz, Khuzestan, Iran, over four growing seasons from 2018 to 2020. The farming strategies were as follows: (1) using the standard rate of inorganic fertilizer used in the region and removing crop residues from the soil (SIF_no-CR); (2) applying the standard rate of organic fertilizers used in the region and returning 30% of crop residues to the soil (SOF_30% CR); and (3) integrating the use of inorganic and organic fertilizers and returning 15% of crop residues to the soil (IOF_15% CR). The crop rotation systems were fallow-wheat (F-W), corn-wheat (C-W), sesame-wheat (S-W), and mung bean-wheat (B-W). No statistically significant difference was observed between the different farming strategies and rotation systems with respect to LI after two years of the experiment. The highest (1.26) and lowest (1.06) CPIs were observed for SOF_30% CR and SIF_no-CR, respectively. The magnitude of the CMI values followed the order SOF_30% CR (121) \\\\textgreater IOF_15% CR (107) ≥ SIF_no-CR (106). B-W and F-W had the highest and lowest CPI with values of 1.29 and 1.01, respectively. No statistically significant difference was found for the different crop rotation systems. Given the low impact of the common farming practices in the region, e.g., SIF_no-CR and F-W, on CPI and CMI at 24 months, our results showed that farming strategies with manure application and crop residue management and summer wheat-based rotation systems appear to be more appropriate farming strategies to improve CMI in arable land.\",\"language\":\"en\",\"urldate\":\"2024-11-15\",\"journal\":\"Applied and Environmental Soil Science\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Gorooei\"],\"firstnames\":[\"Aram\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Aynehband\"],\"firstnames\":[\"Amir\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Behrend\"],\"firstnames\":[\"Dominik\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"J.\",\"Seidel\"],\"firstnames\":[\"Sabine\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kumar\",\"Srivastava\"],\"firstnames\":[\"Amit\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Rahnama\"],\"firstnames\":[\"Afrasyab\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]}],\"editor\":[{\"propositions\":[],\"lastnames\":[\"El-Gendy\"],\"firstnames\":[\"Nour\",\"Sh.\"],\"suffixes\":[]}],\"month\":\"April\",\"year\":\"2024\",\"pages\":\"1–11\",\"bibtex\":\"@article{gorooei_short-term_2024,\\n\\ttitle = {Short-{Term} {Response} of {Soil} {Organic} {Carbon} {Indices} to {Different} {Farming} {Strategies} and {Crop} {Rotation} {Systems} in a {Semiarid} {Warm} {Region}},\\n\\tvolume = {2024},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {1687-7675, 1687-7667},\\n\\turl = {https://www.hindawi.com/journals/aess/2024/8594691/},\\n\\tdoi = {10.1155/2024/8594691},\\n\\tabstract = {Several indices can be used to assess the impact of short-term conservation agriculture strategies on improving soil organic carbon (SOC). To find out how the SOC pools and the carbon lability influence the carbon management index (CMI) in response to different agricultural practices in a warm semiarid region, the carbon lability index (LI) and the carbon pool index (CPI) were measured under the interactive effect of different fertilizer applications and crop residue management (hereafter referred to as “farming strategies”) in combination with four crop rotation systems in Ahvaz, Khuzestan, Iran, over four growing seasons from 2018 to 2020. The farming strategies were as follows: (1) using the standard rate of inorganic fertilizer used in the region and removing crop residues from the soil (SIF\\\\_no-CR); (2) applying the standard rate of organic fertilizers used in the region and returning 30\\\\% of crop residues to the soil (SOF\\\\_30\\\\% CR); and (3) integrating the use of inorganic and organic fertilizers and returning 15\\\\% of crop residues to the soil (IOF\\\\_15\\\\% CR). The crop rotation systems were fallow-wheat (F-W), corn-wheat (C-W), sesame-wheat (S-W), and mung bean-wheat (B-W). No statistically significant difference was observed between the different farming strategies and rotation systems with respect to LI after two years of the experiment. The highest (1.26) and lowest (1.06) CPIs were observed for SOF\\\\_30\\\\% CR and SIF\\\\_no-CR, respectively. The magnitude of the CMI values followed the order SOF\\\\_30\\\\% CR (121) {\\\\textgreater} IOF\\\\_15\\\\% CR (107) ≥ SIF\\\\_no-CR (106). B-W and F-W had the highest and lowest CPI with values of 1.29 and 1.01, respectively. No statistically significant difference was found for the different crop rotation systems. Given the low impact of the common farming practices in the region, e.g., SIF\\\\_no-CR and F-W, on CPI and CMI at 24 months, our results showed that farming strategies with manure application and crop residue management and summer wheat-based rotation systems appear to be more appropriate farming strategies to improve CMI in arable land.},\\n\\tlanguage = {en},\\n\\turldate = {2024-11-15},\\n\\tjournal = {Applied and Environmental Soil Science},\\n\\tauthor = {Gorooei, Aram and Aynehband, Amir and Behrend, Dominik and J. Seidel, Sabine and Kumar Srivastava, Amit and Rahnama, Afrasyab and Gaiser, Thomas},\\n\\teditor = {El-Gendy, Nour Sh.},\\n\\tmonth = apr,\\n\\tyear = {2024},\\n\\tpages = {1--11},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Gorooei, A.\",\"Aynehband, A.\",\"Behrend, D.\",\"J. Seidel, S.\",\"Kumar Srivastava, A.\",\"Rahnama, A.\",\"Gaiser, T.\"],\"editor_short\":[\"El-Gendy, N. S.\"],\"key\":\"gorooei_short-term_2024\",\"id\":\"gorooei_short-term_2024\",\"bibbaseid\":\"gorooei-aynehband-behrend-jseidel-kumarsrivastava-rahnama-gaiser-shorttermresponseofsoilorganiccarbonindicestodifferentfarmingstrategiesandcroprotationsystemsinasemiaridwarmregion-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.hindawi.com/journals/aess/2024/8594691/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Integration of UAV-sensed features using machine learning methods to assess species richness in wet grassland ecosystems\",\"volume\":\"83\",\"issn\":\"15749541\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558\",\"doi\":\"10.1016/j.ecoinf.2024.102813\",\"language\":\"en\",\"urldate\":\"2024-11-15\",\"journal\":\"Ecological Informatics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Bazzo\"],\"firstnames\":[\"Clara\",\"Oliva\",\"Gonçalves\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kamali\"],\"firstnames\":[\"Bahareh\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Dos\",\"Santos\",\"Vianna\"],\"firstnames\":[\"Murilo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Behrend\"],\"firstnames\":[\"Dominik\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hueging\"],\"firstnames\":[\"Hubert\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schleip\"],\"firstnames\":[\"Inga\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Mosebach\"],\"firstnames\":[\"Paul\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Haub\"],\"firstnames\":[\"Almut\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Behrendt\"],\"firstnames\":[\"Axel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2024\",\"pages\":\"102813\",\"bibtex\":\"@article{bazzo_integration_2024,\\n\\ttitle = {Integration of {UAV}-sensed features using machine learning methods to assess species richness in wet grassland ecosystems},\\n\\tvolume = {83},\\n\\tissn = {15749541},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558},\\n\\tdoi = {10.1016/j.ecoinf.2024.102813},\\n\\tlanguage = {en},\\n\\turldate = {2024-11-15},\\n\\tjournal = {Ecological Informatics},\\n\\tauthor = {Bazzo, Clara Oliva Gonçalves and Kamali, Bahareh and Dos Santos Vianna, Murilo and Behrend, Dominik and Hueging, Hubert and Schleip, Inga and Mosebach, Paul and Haub, Almut and Behrendt, Axel and Gaiser, Thomas},\\n\\tmonth = nov,\\n\\tyear = {2024},\\n\\tpages = {102813},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Bazzo, C. O. G.\",\"Kamali, B.\",\"Dos Santos Vianna, M.\",\"Behrend, D.\",\"Hueging, H.\",\"Schleip, I.\",\"Mosebach, P.\",\"Haub, A.\",\"Behrendt, A.\",\"Gaiser, T.\"],\"key\":\"bazzo_integration_2024\",\"id\":\"bazzo_integration_2024\",\"bibbaseid\":\"bazzo-kamali-dossantosvianna-behrend-hueging-schleip-mosebach-haub-etal-integrationofuavsensedfeaturesusingmachinelearningmethodstoassessspeciesrichnessinwetgrasslandecosystems-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Assessing the Effect of Field Disturbances On Biomass Estimation in Grasslands Using UAV-Derived Canopy Height Models\",\"issn\":\"2512-2789, 2512-2819\",\"url\":\"https://link.springer.com/10.1007/s41064-024-00322-x\",\"doi\":\"10.1007/s41064-024-00322-x\",\"abstract\":\"Abstract Accurate estimation of biomass in grasslands is essential for understanding ecosystem health and productivity. Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools for biomass estimation using canopy height models derived from high-resolution imagery. However, the impact of field disturbances, such as lodging and molehills, on the accuracy of biomass estimation using UAV-derived canopy height models remains underexplored. This study aimed to assess the relationship between UAV-derived canopy height and both reference canopy height measurements and dry biomass, accounting for different management systems and disturbance scenarios. UAV data were collected using a multispectral camera, and ground-based measurements were obtained for validation. The results revealed that UAV-derived canopy height models remained accurate in estimating vegetation height, even in the presence of disturbances. However, the relationship between UAV-derived canopy height and dry biomass was affected by disturbances, leading to overestimation or underestimation of biomass depending on disturbance type and severity. The impact of disturbances on biomass estimation varied across cutting systems. These findings highlight the potential of UAV-derived canopy height models for estimating vegetation structure, but also underscore the need for caution in relying solely on these models for accurate biomass estimation in heterogeneous grasslands. Future research should explore strategies to enhance biomass estimation accuracy by integrating additional data sources and accounting for field disturbances.\",\"language\":\"en\",\"urldate\":\"2024-11-15\",\"journal\":\"PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Bazzo\"],\"firstnames\":[\"Clara\",\"Oliva\",\"Gonçalves\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kamali\"],\"firstnames\":[\"Bahareh\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Behrend\"],\"firstnames\":[\"Dominik\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hueging\"],\"firstnames\":[\"Hubert\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schleip\"],\"firstnames\":[\"Inga\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Mosebach\"],\"firstnames\":[\"Paul\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Behrendt\"],\"firstnames\":[\"Axel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2024\",\"bibtex\":\"@article{bazzo_assessing_2024,\\n\\ttitle = {Assessing the {Effect} of {Field} {Disturbances} {On} {Biomass} {Estimation} in {Grasslands} {Using} {UAV}-{Derived} {Canopy} {Height} {Models}},\\n\\tissn = {2512-2789, 2512-2819},\\n\\turl = {https://link.springer.com/10.1007/s41064-024-00322-x},\\n\\tdoi = {10.1007/s41064-024-00322-x},\\n\\tabstract = {Abstract\\n            Accurate estimation of biomass in grasslands is essential for understanding ecosystem health and productivity. Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools for biomass estimation using canopy height models derived from high-resolution imagery. However, the impact of field disturbances, such as lodging and molehills, on the accuracy of biomass estimation using UAV-derived canopy height models remains underexplored. This study aimed to assess the relationship between UAV-derived canopy height and both reference canopy height measurements and dry biomass, accounting for different management systems and disturbance scenarios. UAV data were collected using a multispectral camera, and ground-based measurements were obtained for validation. The results revealed that UAV-derived canopy height models remained accurate in estimating vegetation height, even in the presence of disturbances. However, the relationship between UAV-derived canopy height and dry biomass was affected by disturbances, leading to overestimation or underestimation of biomass depending on disturbance type and severity. The impact of disturbances on biomass estimation varied across cutting systems. These findings highlight the potential of UAV-derived canopy height models for estimating vegetation structure, but also underscore the need for caution in relying solely on these models for accurate biomass estimation in heterogeneous grasslands. Future research should explore strategies to enhance biomass estimation accuracy by integrating additional data sources and accounting for field disturbances.},\\n\\tlanguage = {en},\\n\\turldate = {2024-11-15},\\n\\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\\n\\tauthor = {Bazzo, Clara Oliva Gonçalves and Kamali, Bahareh and Behrend, Dominik and Hueging, Hubert and Schleip, Inga and Mosebach, Paul and Behrendt, Axel and Gaiser, Thomas},\\n\\tmonth = nov,\\n\\tyear = {2024},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Bazzo, C. O. G.\",\"Kamali, B.\",\"Behrend, D.\",\"Hueging, H.\",\"Schleip, I.\",\"Mosebach, P.\",\"Behrendt, A.\",\"Gaiser, T.\"],\"key\":\"bazzo_assessing_2024\",\"id\":\"bazzo_assessing_2024\",\"bibbaseid\":\"bazzo-kamali-behrend-hueging-schleip-mosebach-behrendt-gaiser-assessingtheeffectoffielddisturbancesonbiomassestimationingrasslandsusinguavderivedcanopyheightmodels-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://link.springer.com/10.1007/s41064-024-00322-x\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models\",\"volume\":\"955\",\"issn\":\"00489697\",\"shorttitle\":\"The overlooked effects of environmental impacts on root\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955\",\"doi\":\"10.1016/j.scitotenv.2024.176738\",\"language\":\"en\",\"urldate\":\"2024-10-24\",\"journal\":\"Science of The Total Environment\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Seidel\"],\"firstnames\":[\"S.J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ahmadi\"],\"firstnames\":[\"S.H.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Weihermüller\"],\"firstnames\":[\"L.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Couëdel\"],\"firstnames\":[\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lopez\"],\"firstnames\":[\"G.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Behrend\"],\"firstnames\":[\"D.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kamali\"],\"firstnames\":[\"B.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"T.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hernández-Ochoa\"],\"firstnames\":[\"I.M.\"],\"suffixes\":[]}],\"month\":\"December\",\"year\":\"2024\",\"pages\":\"176738\",\"bibtex\":\"@article{seidel_overlooked_2024,\\n\\ttitle = {The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models},\\n\\tvolume = {955},\\n\\tissn = {00489697},\\n\\tshorttitle = {The overlooked effects of environmental impacts on root},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955},\\n\\tdoi = {10.1016/j.scitotenv.2024.176738},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-24},\\n\\tjournal = {Science of The Total Environment},\\n\\tauthor = {Seidel, S.J. and Ahmadi, S.H. and Weihermüller, L. and Couëdel, A. and Lopez, G. and Behrend, D. and Kamali, B. and Gaiser, T. and Hernández-Ochoa, I.M.},\\n\\tmonth = dec,\\n\\tyear = {2024},\\n\\tpages = {176738},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Seidel, S.\",\"Ahmadi, S.\",\"Weihermüller, L.\",\"Couëdel, A.\",\"Lopez, G.\",\"Behrend, D.\",\"Kamali, B.\",\"Gaiser, T.\",\"Hernández-Ochoa, I.\"],\"key\":\"seidel_overlooked_2024\",\"id\":\"seidel_overlooked_2024\",\"bibbaseid\":\"seidel-ahmadi-weihermller-coudel-lopez-behrend-kamali-gaiser-etal-theoverlookedeffectsofenvironmentalimpactsonrootshootratioinexperimentsandsoilcropmodels-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Soil Moisture Memory: State‐Of‐The‐Art and the Way Forward\",\"volume\":\"62\",\"issn\":\"8755-1209, 1944-9208\",\"shorttitle\":\"Soil Moisture Memory\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828\",\"doi\":\"10.1029/2023RG000828\",\"abstract\":\"Abstract Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil‐plant‐atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth‐dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM. , Plain Language Summary Our review paper takes an in‐depth look at soil moisture memory, which is how soil records its moisture history over time and space. Analogous to human psychology, which seeks to understand how a person's/society's memory influences his/her present and future behavior, understanding soil moisture memory encourages consideration of how such memory determines present state and might determine future behavior of soils exposed to environmental disturbances. Soil moisture memory can be affected by a variety of factors, both external (e.g., weather extremes) and internal (soil's unique properties). It affects everything from the air to the way our landscapes respond to disasters like droughts, wildfires, and floods. We also studied how this phenomenon affects the balance of water and energy in our environment, the health of our plants, and even how it communicates with the atmosphere. We show how it can change depending on where you are on the planet, the time of year, and how deep you dig into the soil. We offer scientists insights into how weather and land surface models can become more accurate by accounting for soil moisture memory. Its understanding not only helps us predict and manage our environment, but also provides opportunities for exciting scientific discoveries. , Key Points Atmospheric forcings, land use and management, and soil processes and mechanisms explain how and why soil moisture memory emerges in ecosystems Nonlocality of moisture memory, its spread across different regions, and its interaction with large‐scale climate phenomena are underexplored Further advances in land surface models and closer integration of model simulations and observations are needed to better characterize moisture memory\",\"language\":\"en\",\"number\":\"2\",\"urldate\":\"2024-10-23\",\"journal\":\"Reviews of Geophysics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Rahmati\"],\"firstnames\":[\"Mehdi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Amelung\"],\"firstnames\":[\"Wulf\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Brogi\"],\"firstnames\":[\"Cosimo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Dari\"],\"firstnames\":[\"Jacopo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Flammini\"],\"firstnames\":[\"Alessia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bogena\"],\"firstnames\":[\"Heye\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Brocca\"],\"firstnames\":[\"Luca\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Chen\"],\"firstnames\":[\"Hao\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Groh\"],\"firstnames\":[\"Jannis\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Koster\"],\"firstnames\":[\"Randal\",\"D.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"McColl\"],\"firstnames\":[\"Kaighin\",\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Montzka\"],\"firstnames\":[\"Carsten\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Moradi\"],\"firstnames\":[\"Shirin\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Rahi\"],\"firstnames\":[\"Arash\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Sharghi\",\"S.\"],\"firstnames\":[\"Farnaz\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]}],\"month\":\"June\",\"year\":\"2024\",\"pages\":\"e2023RG000828\",\"bibtex\":\"@article{rahmati_soil_2024,\\n\\ttitle = {Soil {Moisture} {Memory}: {State}‐{Of}‐{The}‐{Art} and the {Way} {Forward}},\\n\\tvolume = {62},\\n\\tissn = {8755-1209, 1944-9208},\\n\\tshorttitle = {Soil {Moisture} {Memory}},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828},\\n\\tdoi = {10.1029/2023RG000828},\\n\\tabstract = {Abstract\\n            Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil‐plant‐atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth‐dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM.\\n          , \\n            Plain Language Summary\\n            Our review paper takes an in‐depth look at soil moisture memory, which is how soil records its moisture history over time and space. Analogous to human psychology, which seeks to understand how a person's/society's memory influences his/her present and future behavior, understanding soil moisture memory encourages consideration of how such memory determines present state and might determine future behavior of soils exposed to environmental disturbances. Soil moisture memory can be affected by a variety of factors, both external (e.g., weather extremes) and internal (soil's unique properties). It affects everything from the air to the way our landscapes respond to disasters like droughts, wildfires, and floods. We also studied how this phenomenon affects the balance of water and energy in our environment, the health of our plants, and even how it communicates with the atmosphere. We show how it can change depending on where you are on the planet, the time of year, and how deep you dig into the soil. We offer scientists insights into how weather and land surface models can become more accurate by accounting for soil moisture memory. Its understanding not only helps us predict and manage our environment, but also provides opportunities for exciting scientific discoveries.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  Atmospheric forcings, land use and management, and soil processes and mechanisms explain how and why soil moisture memory emerges in ecosystems\\n                \\n                \\n                  Nonlocality of moisture memory, its spread across different regions, and its interaction with large‐scale climate phenomena are underexplored\\n                \\n                \\n                  Further advances in land surface models and closer integration of model simulations and observations are needed to better characterize moisture memory},\\n\\tlanguage = {en},\\n\\tnumber = {2},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Reviews of Geophysics},\\n\\tauthor = {Rahmati, Mehdi and Amelung, Wulf and Brogi, Cosimo and Dari, Jacopo and Flammini, Alessia and Bogena, Heye and Brocca, Luca and Chen, Hao and Groh, Jannis and Koster, Randal D. and McColl, Kaighin A. and Montzka, Carsten and Moradi, Shirin and Rahi, Arash and Sharghi S., Farnaz and Vereecken, Harry},\\n\\tmonth = jun,\\n\\tyear = {2024},\\n\\tpages = {e2023RG000828},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Rahmati, M.\",\"Amelung, W.\",\"Brogi, C.\",\"Dari, J.\",\"Flammini, A.\",\"Bogena, H.\",\"Brocca, L.\",\"Chen, H.\",\"Groh, J.\",\"Koster, R. D.\",\"McColl, K. A.\",\"Montzka, C.\",\"Moradi, S.\",\"Rahi, A.\",\"Sharghi S., F.\",\"Vereecken, H.\"],\"key\":\"rahmati_soil_2024\",\"id\":\"rahmati_soil_2024\",\"bibbaseid\":\"rahmati-amelung-brogi-dari-flammini-bogena-brocca-chen-etal-soilmoisturememorystateoftheartandthewayforward-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Implications for sustainable water consumption in Africa by simulating five decades (1965–2014) of groundwater recharge\",\"volume\":\"626\",\"issn\":\"00221694\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301\",\"doi\":\"10.1016/j.jhydrol.2023.130288\",\"language\":\"en\",\"urldate\":\"2024-10-23\",\"journal\":\"Journal of Hydrology\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Bayat\"],\"firstnames\":[\"Bagher\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Oloruntoba\"],\"firstnames\":[\"Bamidele\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Montzka\"],\"firstnames\":[\"Carsten\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hendricks\",\"Franssen\"],\"firstnames\":[\"Harrie-Jan\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2023\",\"pages\":\"130288\",\"bibtex\":\"@article{bayat_implications_2023,\\n\\ttitle = {Implications for sustainable water consumption in {Africa} by simulating five decades (1965–2014) of groundwater recharge},\\n\\tvolume = {626},\\n\\tissn = {00221694},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301},\\n\\tdoi = {10.1016/j.jhydrol.2023.130288},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Journal of Hydrology},\\n\\tauthor = {Bayat, Bagher and Oloruntoba, Bamidele and Montzka, Carsten and Vereecken, Harry and Hendricks Franssen, Harrie-Jan},\\n\\tmonth = nov,\\n\\tyear = {2023},\\n\\tpages = {130288},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Bayat, B.\",\"Oloruntoba, B.\",\"Montzka, C.\",\"Vereecken, H.\",\"Hendricks Franssen, H.\"],\"key\":\"bayat_implications_2023\",\"id\":\"bayat_implications_2023\",\"bibbaseid\":\"bayat-oloruntoba-montzka-vereecken-hendricksfranssen-implicationsforsustainablewaterconsumptioninafricabysimulatingfivedecades19652014ofgroundwaterrecharge-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Climate-driven interannual variability in subnational irrigation areas across Europe\",\"volume\":\"5\",\"issn\":\"2662-4435\",\"url\":\"https://www.nature.com/articles/s43247-024-01721-z\",\"doi\":\"10.1038/s43247-024-01721-z\",\"abstract\":\"Abstract Irrigation profoundly impacts ecology and agricultural productivity, with irrigated areas varying across regions and years. Interannual dynamics of irrigation extent are lacking, particularly in humid regions of Europe. We analyzed the response of irrigated areas to drought conditions in areas equipped for irrigation and used the derived relationships to estimate annual irrigated areas for 32 European countries in the period 1990–2020. Interannual variability of irrigated areas varied notably, particularly in more humid Northern and Western Europe. In most humid regions, irrigated area is larger in dry years, whereas in more arid regions like Spain, it is larger in wet years. The largest irrigated area across Europe occurred in dry years 2003 and 2018 (11.93 and 11.77 million hectares), while the smallest is estimated for the wet years 2002 and 2014 (10.71 and 10.31 million hectares). The findings of this study help to improve scenario development and water resources management.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2024-10-23\",\"journal\":\"Communications Earth & Environment\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Zhu\"],\"firstnames\":[\"Wanxue\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Siebert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"554\",\"bibtex\":\"@article{zhu_climate-driven_2024,\\n\\ttitle = {Climate-driven interannual variability in subnational irrigation areas across {Europe}},\\n\\tvolume = {5},\\n\\tissn = {2662-4435},\\n\\turl = {https://www.nature.com/articles/s43247-024-01721-z},\\n\\tdoi = {10.1038/s43247-024-01721-z},\\n\\tabstract = {Abstract\\n            Irrigation profoundly impacts ecology and agricultural productivity, with irrigated areas varying across regions and years. Interannual dynamics of irrigation extent are lacking, particularly in humid regions of Europe. We analyzed the response of irrigated areas to drought conditions in areas equipped for irrigation and used the derived relationships to estimate annual irrigated areas for 32 European countries in the period 1990–2020. Interannual variability of irrigated areas varied notably, particularly in more humid Northern and Western Europe. In most humid regions, irrigated area is larger in dry years, whereas in more arid regions like Spain, it is larger in wet years. The largest irrigated area across Europe occurred in dry years 2003 and 2018 (11.93 and 11.77 million hectares), while the smallest is estimated for the wet years 2002 and 2014 (10.71 and 10.31 million hectares). The findings of this study help to improve scenario development and water resources management.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Communications Earth \\\\& Environment},\\n\\tauthor = {Zhu, Wanxue and Siebert, Stefan},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {554},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Zhu, W.\",\"Siebert, S.\"],\"key\":\"zhu_climate-driven_2024\",\"id\":\"zhu_climate-driven_2024\",\"bibbaseid\":\"zhu-siebert-climatedriveninterannualvariabilityinsubnationalirrigationareasacrosseurope-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s43247-024-01721-z\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation\",\"volume\":\"83\",\"issn\":\"15749541\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789\",\"doi\":\"10.1016/j.ecoinf.2024.102836\",\"language\":\"en\",\"urldate\":\"2024-10-23\",\"journal\":\"Ecological Informatics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Baumert\"],\"firstnames\":[\"Josef\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Heckelei\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Storm\"],\"firstnames\":[\"Hugo\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2024\",\"pages\":\"102836\",\"bibtex\":\"@article{baumert_probabilistic_2024,\\n\\ttitle = {Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation},\\n\\tvolume = {83},\\n\\tissn = {15749541},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789},\\n\\tdoi = {10.1016/j.ecoinf.2024.102836},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Ecological Informatics},\\n\\tauthor = {Baumert, Josef and Heckelei, Thomas and Storm, Hugo},\\n\\tmonth = nov,\\n\\tyear = {2024},\\n\\tpages = {102836},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Baumert, J.\",\"Heckelei, T.\",\"Storm, H.\"],\"key\":\"baumert_probabilistic_2024\",\"id\":\"baumert_probabilistic_2024\",\"bibbaseid\":\"baumert-heckelei-storm-probabilisticcroptypemappingforexantemodellingandspatialdisaggregation-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Benefits and Pitfalls of GRACE and Streamflow Assimilation for Improving the Streamflow Simulations of the WaterGAP Global Hydrology Model\",\"volume\":\"16\",\"issn\":\"1942-2466, 1942-2466\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092\",\"doi\":\"10.1029/2023MS004092\",\"abstract\":\"Abstract Distribution and change of freshwater resources is often simulated with global hydrological models. However, owing to process representation limitations and forcing data uncertainties, these model simulations have shortcomings. Combining them with observations via data assimilation, for example, with data from the Gravity Recovery and Climate Experiment (GRACE) mission or streamflow measured at in situ stations is considered to improve the realism of the simulations. We assimilate gridded total water storage anomaly (TWSA) from GRACE into the WaterGAP Global Hydrology Model (WGHM) over the Mississippi River basin via an Ensemble Kalman Filter. Our results agree with previous studies where assimilating GRACE observations nudges TWSA simulations closer to the observations, reducing the root mean square error (RMSE) by 21% compared to an uncalibrated model. However, simulations of streamflow show degeneration at more than 90% of all gauge stations for metrics such as RMSE and correlations; only the annual phase of simulated streamflow improves at half the stations. Therefore, for the first time, we instead assimilated streamflow observations into the WGHM, which improved simulated streamflow at up to nearly 80% of the stations, with normalized RMSE showing improvements of up to 0.1, while TWSA was well‐simulated in all metrics. Combining both approaches, that is, jointly assimilating GRACE‐derived TWSA and streamflow observations, leads to a trade‐off between a good fit of both variables albeit skewed to the GRACE observations. Overall, we speculate that our findings point to limitations of process representation in WGHM hindering consistent flux simulation from the storage history, especially in dry regions. , Plain Language Summary The distribution of freshwater on Earth can be simulated by hydrological models like the WaterGAP Global Hydrology Model (WGHM). Changes of the total water storages can also be derived from satellite gravimetry, for example, with the Gravity Recovery and Climate Experiment (GRACE) mission. Model and observations do not necessarily agree and are both prone to errors. We combined the model and observations over the Mississippi River basin taking the errors into account by applying a data assimilation technique. This led to a more realistic simulation of the total water storage changes. Since simulated streamflow was found to degenerate at nearly all gauge stations, we assimilated streamflow observations (instead of GRACE data) into the WGHM. This turned out to improve simulated streamflow at up to nearly 80% of the stations. The assimilation of both data sets (GRACE and streamflow) together leads to a compromise between the TWSA and the streamflow simulations, with the GRACE data affecting the simulations more than the streamflow data. Our findings are expected to aid reducing the weaknesses of the WGHM model equations and thus contribute to improved quantification of Earth's freshwater distribution in the future. , Key Points GRACE assimilation improves the WGHM storage representation, but degrades the simulated streamflow at up to 99% of the gauge stations Assimilating streamflow data instead improves the streamflow simulations at up to 79% of the validation stations Joint assimilation leads to a trade‐off between a good fit of simulated storages and streamflow albeit skewed to the GRACE observations\",\"language\":\"en\",\"number\":\"10\",\"urldate\":\"2024-10-23\",\"journal\":\"Journal of Advances in Modeling Earth Systems\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Schulze\"],\"firstnames\":[\"K.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gerdener\"],\"firstnames\":[\"H.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Döll\"],\"firstnames\":[\"P.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Müller\",\"Schmied\"],\"firstnames\":[\"H.\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"e2023MS004092\",\"bibtex\":\"@article{schulze_benefits_2024,\\n\\ttitle = {Benefits and {Pitfalls} of {GRACE} and {Streamflow} {Assimilation} for {Improving} the {Streamflow} {Simulations} of the {WaterGAP} {Global} {Hydrology} {Model}},\\n\\tvolume = {16},\\n\\tissn = {1942-2466, 1942-2466},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092},\\n\\tdoi = {10.1029/2023MS004092},\\n\\tabstract = {Abstract\\n            Distribution and change of freshwater resources is often simulated with global hydrological models. However, owing to process representation limitations and forcing data uncertainties, these model simulations have shortcomings. Combining them with observations via data assimilation, for example, with data from the Gravity Recovery and Climate Experiment (GRACE) mission or streamflow measured at in situ stations is considered to improve the realism of the simulations. We assimilate gridded total water storage anomaly (TWSA) from GRACE into the WaterGAP Global Hydrology Model (WGHM) over the Mississippi River basin via an Ensemble Kalman Filter. Our results agree with previous studies where assimilating GRACE observations nudges TWSA simulations closer to the observations, reducing the root mean square error (RMSE) by 21\\\\% compared to an uncalibrated model. However, simulations of streamflow show degeneration at more than 90\\\\% of all gauge stations for metrics such as RMSE and correlations; only the annual phase of simulated streamflow improves at half the stations. Therefore, for the first time, we instead assimilated streamflow observations into the WGHM, which improved simulated streamflow at up to nearly 80\\\\% of the stations, with normalized RMSE showing improvements of up to 0.1, while TWSA was well‐simulated in all metrics. Combining both approaches, that is, jointly assimilating GRACE‐derived TWSA and streamflow observations, leads to a trade‐off between a good fit of both variables albeit skewed to the GRACE observations. Overall, we speculate that our findings point to limitations of process representation in WGHM hindering consistent flux simulation from the storage history, especially in dry regions.\\n          , \\n            Plain Language Summary\\n            The distribution of freshwater on Earth can be simulated by hydrological models like the WaterGAP Global Hydrology Model (WGHM). Changes of the total water storages can also be derived from satellite gravimetry, for example, with the Gravity Recovery and Climate Experiment (GRACE) mission. Model and observations do not necessarily agree and are both prone to errors. We combined the model and observations over the Mississippi River basin taking the errors into account by applying a data assimilation technique. This led to a more realistic simulation of the total water storage changes. Since simulated streamflow was found to degenerate at nearly all gauge stations, we assimilated streamflow observations (instead of GRACE data) into the WGHM. This turned out to improve simulated streamflow at up to nearly 80\\\\% of the stations. The assimilation of both data sets (GRACE and streamflow) together leads to a compromise between the TWSA and the streamflow simulations, with the GRACE data affecting the simulations more than the streamflow data. Our findings are expected to aid reducing the weaknesses of the WGHM model equations and thus contribute to improved quantification of Earth's freshwater distribution in the future.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  GRACE assimilation improves the WGHM storage representation, but degrades the simulated streamflow at up to 99\\\\% of the gauge stations\\n                \\n                \\n                  Assimilating streamflow data instead improves the streamflow simulations at up to 79\\\\% of the validation stations\\n                \\n                \\n                  Joint assimilation leads to a trade‐off between a good fit of simulated storages and streamflow albeit skewed to the GRACE observations},\\n\\tlanguage = {en},\\n\\tnumber = {10},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Journal of Advances in Modeling Earth Systems},\\n\\tauthor = {Schulze, K. and Kusche, J. and Gerdener, H. and Döll, P. and Müller Schmied, H.},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {e2023MS004092},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Schulze, K.\",\"Kusche, J.\",\"Gerdener, H.\",\"Döll, P.\",\"Müller Schmied, H.\"],\"key\":\"schulze_benefits_2024\",\"id\":\"schulze_benefits_2024\",\"bibbaseid\":\"schulze-kusche-gerdener-dll-mllerschmied-benefitsandpitfallsofgraceandstreamflowassimilationforimprovingthestreamflowsimulationsofthewatergapglobalhydrologymodel-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Separation of earthquake and hydrology signals from GRACE satellites data via independent component analysis: a case study in the Sumatra region\",\"volume\":\"239\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"0956-540X, 1365-246X\",\"shorttitle\":\"Separation of earthquake and hydrology signals from GRACE satellites data via independent component analysis\",\"url\":\"https://academic.oup.com/gji/article/239/3/1597/7778285\",\"doi\":\"10.1093/gji/ggae351\",\"abstract\":\"SUMMARY The Gravity Recovery and Climate Experiment (GRACE) satellites have observed mass migrations caused by megathrust earthquakes. Extracting earthquake-related signals from GRACE data is still a challenge due to the interference from non-earthquake sources such as terrestrial hydrology. Instead of reducing hydrological signals by potentially biased hydrological models, in this study we apply a model-free technique of independent component analysis (ICA), to separate earthquake and non-earthquake signals from non-Gaussian GRACE data. We elucidate the principles and mechanisms of ICA for the separation of earthquake and hydrology signals, employing simulated data to demonstrate the process. Our findings demonstrate that both spatial ICA and temporal ICA are highly effective in discerning earthquake related to 2004 Mw 9.2 event and hydrological signals from GRACE data in the Sumatra region. This stands in stark contrast to principal component analysis, which often encounters challenges with signal intermingling. The utility of ICA is evident in its ability to distinctly delineate coseismic and post-seismic behaviours associated with megathrust events, including the 2004 Sumatra, the 2010 Maule, and the 2011 Tohoku earthquakes. ICA effectively mitigates the potential for misestimation of earthquake signals, an issue that can carry substantial implications. Therefore, employing ICA facilitates the accurate extraction of earthquake-related data from satellite gravity observations—a critical process for refining earthquake source parameters and understanding Earth's rheological properties, especially when non-earthquake signals are significant and cannot be disregarded.\",\"language\":\"en\",\"number\":\"3\",\"urldate\":\"2024-10-23\",\"journal\":\"Geophysical Journal International\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Xiong\"],\"firstnames\":[\"Yuhao\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Feng\"],\"firstnames\":[\"Wei\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhou\"],\"firstnames\":[\"Xin\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Shen\"],\"firstnames\":[\"Yingchun\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Yang\"],\"firstnames\":[\"Meng\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wang\"],\"firstnames\":[\"Changqing\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhong\"],\"firstnames\":[\"Min\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"1597–1616\",\"bibtex\":\"@article{xiong_separation_2024,\\n\\ttitle = {Separation of earthquake and hydrology signals from {GRACE} satellites data via independent component analysis: a case study in the {Sumatra} region},\\n\\tvolume = {239},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {0956-540X, 1365-246X},\\n\\tshorttitle = {Separation of earthquake and hydrology signals from {GRACE} satellites data via independent component analysis},\\n\\turl = {https://academic.oup.com/gji/article/239/3/1597/7778285},\\n\\tdoi = {10.1093/gji/ggae351},\\n\\tabstract = {SUMMARY\\n            The Gravity Recovery and Climate Experiment (GRACE) satellites have observed mass migrations caused by megathrust earthquakes. Extracting earthquake-related signals from GRACE data is still a challenge due to the interference from non-earthquake sources such as terrestrial hydrology. Instead of reducing hydrological signals by potentially biased hydrological models, in this study we apply a model-free technique of independent component analysis (ICA), to separate earthquake and non-earthquake signals from non-Gaussian GRACE data. We elucidate the principles and mechanisms of ICA for the separation of earthquake and hydrology signals, employing simulated data to demonstrate the process. Our findings demonstrate that both spatial ICA and temporal ICA are highly effective in discerning earthquake related to 2004 Mw 9.2 event and hydrological signals from GRACE data in the Sumatra region. This stands in stark contrast to principal component analysis, which often encounters challenges with signal intermingling. The utility of ICA is evident in its ability to distinctly delineate coseismic and post-seismic behaviours associated with megathrust events, including the 2004 Sumatra, the 2010 Maule, and the 2011 Tohoku earthquakes. ICA effectively mitigates the potential for misestimation of earthquake signals, an issue that can carry substantial implications. Therefore, employing ICA facilitates the accurate extraction of earthquake-related data from satellite gravity observations—a critical process for refining earthquake source parameters and understanding Earth's rheological properties, especially when non-earthquake signals are significant and cannot be disregarded.},\\n\\tlanguage = {en},\\n\\tnumber = {3},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Geophysical Journal International},\\n\\tauthor = {Xiong, Yuhao and Feng, Wei and Zhou, Xin and Kusche, Jürgen and Shen, Yingchun and Yang, Meng and Wang, Changqing and Zhong, Min},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {1597--1616},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Xiong, Y.\",\"Feng, W.\",\"Zhou, X.\",\"Kusche, J.\",\"Shen, Y.\",\"Yang, M.\",\"Wang, C.\",\"Zhong, M.\"],\"key\":\"xiong_separation_2024\",\"id\":\"xiong_separation_2024\",\"bibbaseid\":\"xiong-feng-zhou-kusche-shen-yang-wang-zhong-separationofearthquakeandhydrologysignalsfromgracesatellitesdataviaindependentcomponentanalysisacasestudyinthesumatraregion-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://academic.oup.com/gji/article/239/3/1597/7778285\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Observations indicate regionally misleading wetting and drying trends in CMIP6\",\"volume\":\"7\",\"issn\":\"2397-3722\",\"url\":\"https://www.nature.com/articles/s41612-024-00788-x\",\"doi\":\"10.1038/s41612-024-00788-x\",\"abstract\":\"Abstract We evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against a new global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. To account for different timescales in our analysis, we select regions in which the influence of interannual variability is relatively small and observed trends are assumed to be representative of the development over longer periods. Our results reveal distinct biases in drying and wetting trends in CMIP6 models for several world regions. Specifically, we see high model consensus for drying in the Amazon, which disagrees with the observed wetting. Other regions show a high consensus of models and observations suggesting qualitatively correctly simulated trends, e.g., for the Mediterranean and parts of Central Africa. A high model agreement might therefore falsely indicate a robust trend in water storage if it is not assessed in light of the observed developments. This underlines the potential use of maintaining an adequate observational capacity of water storage for climate change assessments.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2024-10-23\",\"journal\":\"npj Climate and Atmospheric Science\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Jensen\"],\"firstnames\":[\"Laura\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gerdener\"],\"firstnames\":[\"Helena\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Eicker\"],\"firstnames\":[\"Annette\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Fiedler\"],\"firstnames\":[\"Stephanie\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"249\",\"bibtex\":\"@article{jensen_observations_2024,\\n\\ttitle = {Observations indicate regionally misleading wetting and drying trends in {CMIP6}},\\n\\tvolume = {7},\\n\\tissn = {2397-3722},\\n\\turl = {https://www.nature.com/articles/s41612-024-00788-x},\\n\\tdoi = {10.1038/s41612-024-00788-x},\\n\\tabstract = {Abstract\\n            We evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against a new global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. To account for different timescales in our analysis, we select regions in which the influence of interannual variability is relatively small and observed trends are assumed to be representative of the development over longer periods. Our results reveal distinct biases in drying and wetting trends in CMIP6 models for several world regions. Specifically, we see high model consensus for drying in the Amazon, which disagrees with the observed wetting. Other regions show a high consensus of models and observations suggesting qualitatively correctly simulated trends, e.g., for the Mediterranean and parts of Central Africa. A high model agreement might therefore falsely indicate a robust trend in water storage if it is not assessed in light of the observed developments. This underlines the potential use of maintaining an adequate observational capacity of water storage for climate change assessments.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2024-10-23},\\n\\tjournal = {npj Climate and Atmospheric Science},\\n\\tauthor = {Jensen, Laura and Gerdener, Helena and Eicker, Annette and Kusche, Jürgen and Fiedler, Stephanie},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {249},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Jensen, L.\",\"Gerdener, H.\",\"Eicker, A.\",\"Kusche, J.\",\"Fiedler, S.\"],\"key\":\"jensen_observations_2024\",\"id\":\"jensen_observations_2024\",\"bibbaseid\":\"jensen-gerdener-eicker-kusche-fiedler-observationsindicateregionallymisleadingwettinganddryingtrendsincmip6-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s41612-024-00788-x\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Towards a comprehensive analysis of agricultural land systems in the EU and US: A critical view on publicly available datasets\",\"volume\":\"147\",\"issn\":\"02648377\",\"shorttitle\":\"Towards a comprehensive analysis of agricultural land systems in the EU and US\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247\",\"doi\":\"10.1016/j.landusepol.2024.107371\",\"language\":\"en\",\"urldate\":\"2024-10-23\",\"journal\":\"Land Use Policy\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Burchfield\"],\"firstnames\":[\"Emily\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ferro\"],\"firstnames\":[\"Marco\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hüttel\"],\"firstnames\":[\"Silke\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lakes\"],\"firstnames\":[\"Tobia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Leonhardt\"],\"firstnames\":[\"Heidi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Niedermayr\"],\"firstnames\":[\"Andreas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Rissing\"],\"firstnames\":[\"Andrea\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Seifert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wesemeyer\"],\"firstnames\":[\"Maximilian\"],\"suffixes\":[]}],\"month\":\"December\",\"year\":\"2024\",\"pages\":\"107371\",\"bibtex\":\"@article{burchfield_towards_2024,\\n\\ttitle = {Towards a comprehensive analysis of agricultural land systems in the {EU} and {US}: {A} critical view on publicly available datasets},\\n\\tvolume = {147},\\n\\tissn = {02648377},\\n\\tshorttitle = {Towards a comprehensive analysis of agricultural land systems in the {EU} and {US}},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247},\\n\\tdoi = {10.1016/j.landusepol.2024.107371},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Land Use Policy},\\n\\tauthor = {Burchfield, Emily and Ferro, Marco and Hüttel, Silke and Lakes, Tobia and Leonhardt, Heidi and Niedermayr, Andreas and Rissing, Andrea and Seifert, Stefan and Wesemeyer, Maximilian},\\n\\tmonth = dec,\\n\\tyear = {2024},\\n\\tpages = {107371},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Burchfield, E.\",\"Ferro, M.\",\"Hüttel, S.\",\"Lakes, T.\",\"Leonhardt, H.\",\"Niedermayr, A.\",\"Rissing, A.\",\"Seifert, S.\",\"Wesemeyer, M.\"],\"key\":\"burchfield_towards_2024\",\"id\":\"burchfield_towards_2024\",\"bibbaseid\":\"burchfield-ferro-httel-lakes-leonhardt-niedermayr-rissing-seifert-etal-towardsacomprehensiveanalysisofagriculturallandsystemsintheeuandusacriticalviewonpubliclyavailabledatasets-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Use cases and scientific potential of land use data from the EU’s Integrated Administration and Control System: A systematic mapping review\",\"volume\":\"167\",\"issn\":\"1470160X\",\"shorttitle\":\"Use cases and scientific potential of land use data from the EU’s Integrated Administration and Control System\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X\",\"doi\":\"10.1016/j.ecolind.2024.112709\",\"language\":\"en\",\"urldate\":\"2024-10-23\",\"journal\":\"Ecological Indicators\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Leonhardt\"],\"firstnames\":[\"Heidi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wesemeyer\"],\"firstnames\":[\"Maximilian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Eder\"],\"firstnames\":[\"Andreas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hüttel\"],\"firstnames\":[\"Silke\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lakes\"],\"firstnames\":[\"Tobia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schaak\"],\"firstnames\":[\"Henning\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Seifert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wolff\"],\"firstnames\":[\"Saskia\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"112709\",\"bibtex\":\"@article{leonhardt_use_2024,\\n\\ttitle = {Use cases and scientific potential of land use data from the {EU}’s {Integrated} {Administration} and {Control} {System}: {A} systematic mapping review},\\n\\tvolume = {167},\\n\\tissn = {1470160X},\\n\\tshorttitle = {Use cases and scientific potential of land use data from the {EU}’s {Integrated} {Administration} and {Control} {System}},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X},\\n\\tdoi = {10.1016/j.ecolind.2024.112709},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Ecological Indicators},\\n\\tauthor = {Leonhardt, Heidi and Wesemeyer, Maximilian and Eder, Andreas and Hüttel, Silke and Lakes, Tobia and Schaak, Henning and Seifert, Stefan and Wolff, Saskia},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {112709},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Leonhardt, H.\",\"Wesemeyer, M.\",\"Eder, A.\",\"Hüttel, S.\",\"Lakes, T.\",\"Schaak, H.\",\"Seifert, S.\",\"Wolff, S.\"],\"key\":\"leonhardt_use_2024\",\"id\":\"leonhardt_use_2024\",\"bibbaseid\":\"leonhardt-wesemeyer-eder-httel-lakes-schaak-seifert-wolff-usecasesandscientificpotentialoflandusedatafromtheeusintegratedadministrationandcontrolsystemasystematicmappingreview-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Estimating soil moisture from environmental gamma radiation monitoring data\",\"issn\":\"1539-1663, 1539-1663\",\"url\":\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384\",\"doi\":\"10.1002/vzj2.20384\",\"abstract\":\"Abstract Soil moisture (SM) information is invaluable for a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents root‐zone SM for longer periods and larger spatial scales. One option for root‐zone SM observation is terrestrial gamma radiation (TGR), as it is inversely related to SM. Hence, the near real‐time data of more than 5000 environmental gamma radiation (EGR) monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) is a potential source to develop a root‐zone SM product for Europe without extra investments in SM sensors. This study aims to investigate to what extent the EURDEP data can be used for SM estimation. For this, two EGR monitoring stations were equipped with in situ SM sensors to measure reference SM. The terrestrial component of EGR was extracted after eliminating the contributions of rain washout and secondary cosmic radiation, and used to obtain a functional relationship with SM. We predicted the weekly volumetric SM with a root mean square error of 7%–9% from TGR measurements. Nevertheless, we believe that this technique, due to its greater penetration depth and long data legacy, can provide useful data complementary to satellite‐based remote sensing techniques to estimate root‐zone SM at the continental scale. , Core Ideas An extensive early warning monitoring network for environmental gamma radiation (EGR) is maintained in Europe. Since soil moisture influences EGR, this database could be used to derive continental soil moisture products. To test this, two monitoring stations in Germany were selected and equipped with reference soil moisture sensors. From the terrestrial component of EGR, soil moisture was determined with an error of 7–9 vol.%. , Plain Language Summary Information on the temporal dynamics of SM across a large area is vital for many sectors. An extensive network for monitoring EGR detectors that has been operated across Europe after the Chernobyl nuclear accident is a potential source for deriving continental‐scale SM information without additional costs. We investigated how accurately SM can be estimated from the data of two of such detectors. The results showed that weekly SM estimates with an accuracy of 0.07–0.09 cm 3 cm −3 are feasible after adequate data processing accounting for other factors affecting EGR. We also discussed possible sources that affected the accuracy of the SM estimates and provided directions for further research. Despite the current limitations, EGR data show potential for estimating SM across Europe.\",\"language\":\"en\",\"urldate\":\"2024-10-23\",\"journal\":\"Vadose Zone Journal\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Akter\"],\"firstnames\":[\"Sonia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Huisman\"],\"firstnames\":[\"Johan\",\"Alexander\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bogena\"],\"firstnames\":[\"Heye\",\"Reemt\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"e20384\",\"bibtex\":\"@article{akter_estimating_2024,\\n\\ttitle = {Estimating soil moisture from environmental gamma radiation monitoring data},\\n\\tissn = {1539-1663, 1539-1663},\\n\\turl = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384},\\n\\tdoi = {10.1002/vzj2.20384},\\n\\tabstract = {Abstract\\n            Soil moisture (SM) information is invaluable for a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents root‐zone SM for longer periods and larger spatial scales. One option for root‐zone SM observation is terrestrial gamma radiation (TGR), as it is inversely related to SM. Hence, the near real‐time data of more than 5000 environmental gamma radiation (EGR) monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) is a potential source to develop a root‐zone SM product for Europe without extra investments in SM sensors. This study aims to investigate to what extent the EURDEP data can be used for SM estimation. For this, two EGR monitoring stations were equipped with in situ SM sensors to measure reference SM. The terrestrial component of EGR was extracted after eliminating the contributions of rain washout and secondary cosmic radiation, and used to obtain a functional relationship with SM. We predicted the weekly volumetric SM with a root mean square error of 7\\\\%–9\\\\% from TGR measurements. Nevertheless, we believe that this technique, due to its greater penetration depth and long data legacy, can provide useful data complementary to satellite‐based remote sensing techniques to estimate root‐zone SM at the continental scale.\\n          , \\n            Core Ideas\\n            \\n              \\n                \\n                  An extensive early warning monitoring network for environmental gamma radiation (EGR) is maintained in Europe.\\n                \\n                \\n                  Since soil moisture influences EGR, this database could be used to derive continental soil moisture products.\\n                \\n                \\n                  To test this, two monitoring stations in Germany were selected and equipped with reference soil moisture sensors.\\n                \\n                \\n                  From the terrestrial component of EGR, soil moisture was determined with an error of 7–9 vol.\\\\%.\\n                \\n              \\n            \\n          , \\n            Plain Language Summary\\n            \\n              Information on the temporal dynamics of SM across a large area is vital for many sectors. An extensive network for monitoring EGR detectors that has been operated across Europe after the Chernobyl nuclear accident is a potential source for deriving continental‐scale SM information without additional costs. We investigated how accurately SM can be estimated from the data of two of such detectors. The results showed that weekly SM estimates with an accuracy of 0.07–0.09 cm\\n              3\\n              cm\\n              −3\\n              are feasible after adequate data processing accounting for other factors affecting EGR. We also discussed possible sources that affected the accuracy of the SM estimates and provided directions for further research. Despite the current limitations, EGR data show potential for estimating SM across Europe.},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-23},\\n\\tjournal = {Vadose Zone Journal},\\n\\tauthor = {Akter, Sonia and Huisman, Johan Alexander and Bogena, Heye Reemt},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {e20384},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Akter, S.\",\"Huisman, J. A.\",\"Bogena, H. R.\"],\"key\":\"akter_estimating_2024\",\"id\":\"akter_estimating_2024\",\"bibbaseid\":\"akter-huisman-bogena-estimatingsoilmoisturefromenvironmentalgammaradiationmonitoringdata-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Forecasting Next Year's Global Land Water Storage Using GRACE Data\",\"volume\":\"51\",\"issn\":\"0094-8276, 1944-8007\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101\",\"doi\":\"10.1029/2024GL109101\",\"abstract\":\"Abstract Existing approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management. , Plain Language Summary Traditional methods for predicting short‐term/seasonal variations in land total water storages rely on hydrological models. However, these models have a drawback—they are better at predicting water stored in specific parts of the land system like soil moisture than giving an accurate forecast for the overall integrated land total water storage. In this study, we demonstrate the applicability of machine learning in uncovering relationships between the de‐season and de‐linearized terms of global water storage variability as observed by the Gravity Recovery and Climate Experiment (GRACE) satellites, and the preceding hydrometeorological variables such as sea surface temperature. These relationships can then be utilized to forecast monthly changes in land total water storage up to 1 year ahead, and even to predict exceptional drought events based on near real‐time observational forcing data. The validation by actual GRACE observations, lends further credence to the effectiveness of the method developed here, showcasing its potential to forecast trends in global land total water storage for the upcoming year. The potential applications of these predictions in early warning systems are highly promising, and we anticipate that they can assist decision‐makers in enhancing current drought and water resource management practices. , Key Points We identify a stable lag relationship between hydrometeorological variables and the GRACE derived total water storage change (TWSC) Using this stable lag relationship, we are able to forecast the global TWSC up to 1 year ahead with solely observational data as inputs Our forecasts exhibit high consistency with actual GRACE data in terms of global mean land water storage trends for the following year\",\"language\":\"en\",\"number\":\"17\",\"urldate\":\"2024-10-01\",\"journal\":\"Geophysical Research Letters\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Li\"],\"firstnames\":[\"Fupeng\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Sneeuw\"],\"firstnames\":[\"Nico\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Siebert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gerdener\"],\"firstnames\":[\"Helena\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wang\"],\"firstnames\":[\"Zhengtao\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Chao\"],\"firstnames\":[\"Nengfang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Chen\"],\"firstnames\":[\"Gang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Tian\"],\"firstnames\":[\"Kunjun\"],\"suffixes\":[]}],\"month\":\"September\",\"year\":\"2024\",\"pages\":\"e2024GL109101\",\"bibtex\":\"@article{li_forecasting_2024,\\n\\ttitle = {Forecasting {Next} {Year}'s {Global} {Land} {Water} {Storage} {Using} {GRACE} {Data}},\\n\\tvolume = {51},\\n\\tissn = {0094-8276, 1944-8007},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101},\\n\\tdoi = {10.1029/2024GL109101},\\n\\tabstract = {Abstract\\n            Existing approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management.\\n          , \\n            Plain Language Summary\\n            Traditional methods for predicting short‐term/seasonal variations in land total water storages rely on hydrological models. However, these models have a drawback—they are better at predicting water stored in specific parts of the land system like soil moisture than giving an accurate forecast for the overall integrated land total water storage. In this study, we demonstrate the applicability of machine learning in uncovering relationships between the de‐season and de‐linearized terms of global water storage variability as observed by the Gravity Recovery and Climate Experiment (GRACE) satellites, and the preceding hydrometeorological variables such as sea surface temperature. These relationships can then be utilized to forecast monthly changes in land total water storage up to 1 year ahead, and even to predict exceptional drought events based on near real‐time observational forcing data. The validation by actual GRACE observations, lends further credence to the effectiveness of the method developed here, showcasing its potential to forecast trends in global land total water storage for the upcoming year. The potential applications of these predictions in early warning systems are highly promising, and we anticipate that they can assist decision‐makers in enhancing current drought and water resource management practices.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  We identify a stable lag relationship between hydrometeorological variables and the GRACE derived total water storage change (TWSC)\\n                \\n                \\n                  Using this stable lag relationship, we are able to forecast the global TWSC up to 1 year ahead with solely observational data as inputs\\n                \\n                \\n                  Our forecasts exhibit high consistency with actual GRACE data in terms of global mean land water storage trends for the following year},\\n\\tlanguage = {en},\\n\\tnumber = {17},\\n\\turldate = {2024-10-01},\\n\\tjournal = {Geophysical Research Letters},\\n\\tauthor = {Li, Fupeng and Kusche, Jürgen and Sneeuw, Nico and Siebert, Stefan and Gerdener, Helena and Wang, Zhengtao and Chao, Nengfang and Chen, Gang and Tian, Kunjun},\\n\\tmonth = sep,\\n\\tyear = {2024},\\n\\tpages = {e2024GL109101},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Li, F.\",\"Kusche, J.\",\"Sneeuw, N.\",\"Siebert, S.\",\"Gerdener, H.\",\"Wang, Z.\",\"Chao, N.\",\"Chen, G.\",\"Tian, K.\"],\"key\":\"li_forecasting_2024\",\"id\":\"li_forecasting_2024\",\"bibbaseid\":\"li-kusche-sneeuw-siebert-gerdener-wang-chao-chen-etal-forecastingnextyearsgloballandwaterstorageusinggracedata-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Are lessons being learnt from the replication crisis or will the revolution devour its children? Open Q science from the editor's perspective\",\"copyright\":\"https://creativecommons.org/licenses/by-nc/4.0/\",\"issn\":\"2633-9048\",\"shorttitle\":\"Are lessons being learnt from the replication crisis or will the revolution devour its children?\",\"url\":\"https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351\",\"doi\":\"10.1093/qopen/qoae019\",\"abstract\":\"Abstract The scientific production system is crucial in how global challenges are addressed. However, scholars have recently begun to voice concerns about structural inefficiencies within the system, as highlighted, for example, by the replication crisis, the p-value debate and various forms of publication bias. Most suggested remedies tend to address only partial aspects of the system's inefficiencies, but there is currently no unifying agenda in favour of an overall transformation of the system. Based on a critical review of the current scientific system and an exploratory pilot study about the state of student training, we argue that a unifying agenda is urgently needed, particularly given the emergence of artificial intelligence (AI) as a tool in scientific writing and the research discovery process. Without appropriate responses from academia, this trend may even compound current issues around credibility due to limited replicability and ritual-based statistical practice while amplifying all forms of existing biases. Naïve openness in the science system alone is unlikely to lead to major improvements. We contribute to the debate and call for a system reform by identifying key elements in the definition of transformation pathways towards open, democratic and conscious learning, teaching, reviewing and publishing supported by openly maintained AI tools. Roles and incentives within the review process will have to adapt and be strengthened in relation to those that apply to authors. Scientists will have to write less, learn differently and review more in the future, but need to be trained better in and for AI even today.\",\"language\":\"en\",\"urldate\":\"2024-10-01\",\"journal\":\"Q Open\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Hüttel\"],\"firstnames\":[\"Silke\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hess\"],\"firstnames\":[\"Sebastian\"],\"suffixes\":[]}],\"month\":\"July\",\"year\":\"2024\",\"pages\":\"qoae019\",\"bibtex\":\"@article{huttel_are_2024,\\n\\ttitle = {Are lessons being learnt from the replication crisis or will the revolution devour its children? {Open} {Q} science from the editor's perspective},\\n\\tcopyright = {https://creativecommons.org/licenses/by-nc/4.0/},\\n\\tissn = {2633-9048},\\n\\tshorttitle = {Are lessons being learnt from the replication crisis or will the revolution devour its children?},\\n\\turl = {https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351},\\n\\tdoi = {10.1093/qopen/qoae019},\\n\\tabstract = {Abstract\\n            The scientific production system is crucial in how global challenges are addressed. However, scholars have recently begun to voice concerns about structural inefficiencies within the system, as highlighted, for example, by the replication crisis, the p-value debate and various forms of publication bias. Most suggested remedies tend to address only partial aspects of the system's inefficiencies, but there is currently no unifying agenda in favour of an overall transformation of the system. Based on a critical review of the current scientific system and an exploratory pilot study about the state of student training, we argue that a unifying agenda is urgently needed, particularly given the emergence of artificial intelligence (AI) as a tool in scientific writing and the research discovery process. Without appropriate responses from academia, this trend may even compound current issues around credibility due to limited replicability and ritual-based statistical practice while amplifying all forms of existing biases. Naïve openness in the science system alone is unlikely to lead to major improvements. We contribute to the debate and call for a system reform by identifying key elements in the definition of transformation pathways towards open, democratic and conscious learning, teaching, reviewing and publishing supported by openly maintained AI tools. Roles and incentives within the review process will have to adapt and be strengthened in relation to those that apply to authors. Scientists will have to write less, learn differently and review more in the future, but need to be trained better in and for AI even today.},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-01},\\n\\tjournal = {Q Open},\\n\\tauthor = {Hüttel, Silke and Hess, Sebastian},\\n\\tmonth = jul,\\n\\tyear = {2024},\\n\\tpages = {qoae019},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Hüttel, S.\",\"Hess, S.\"],\"key\":\"huttel_are_2024\",\"id\":\"huttel_are_2024\",\"bibbaseid\":\"httel-hess-arelessonsbeinglearntfromthereplicationcrisisorwilltherevolutiondevouritschildrenopenqsciencefromtheeditorsperspective-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"German sugar beet farmers’ intention to use autonomous field robots for seeding and weeding\",\"volume\":\"370\",\"issn\":\"03014797\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587\",\"doi\":\"10.1016/j.jenvman.2024.122472\",\"language\":\"en\",\"urldate\":\"2024-10-01\",\"journal\":\"Journal of Environmental Management\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Uehleke\"],\"firstnames\":[\"Reinhard\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Von\",\"Plettenberg\"],\"firstnames\":[\"Lousia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Leyer\"],\"firstnames\":[\"Michael\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hüttel\"],\"firstnames\":[\"Silke\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2024\",\"pages\":\"122472\",\"bibtex\":\"@article{uehleke_german_2024,\\n\\ttitle = {German sugar beet farmers’ intention to use autonomous field robots for seeding and weeding},\\n\\tvolume = {370},\\n\\tissn = {03014797},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587},\\n\\tdoi = {10.1016/j.jenvman.2024.122472},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-01},\\n\\tjournal = {Journal of Environmental Management},\\n\\tauthor = {Uehleke, Reinhard and Von Plettenberg, Lousia and Leyer, Michael and Hüttel, Silke},\\n\\tmonth = nov,\\n\\tyear = {2024},\\n\\tpages = {122472},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Uehleke, R.\",\"Von Plettenberg, L.\",\"Leyer, M.\",\"Hüttel, S.\"],\"key\":\"uehleke_german_2024\",\"id\":\"uehleke_german_2024\",\"bibbaseid\":\"uehleke-vonplettenberg-leyer-httel-germansugarbeetfarmersintentiontouseautonomousfieldrobotsforseedingandweeding-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Eco-efficiency in the agricultural landscape of North Rhine-Westphalia, Germany\",\"volume\":\"220\",\"issn\":\"0308521X\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129\",\"doi\":\"10.1016/j.agsy.2024.104062\",\"language\":\"en\",\"urldate\":\"2024-10-01\",\"journal\":\"Agricultural Systems\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Seifert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wolff\"],\"firstnames\":[\"Saskia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hüttel\"],\"firstnames\":[\"Silke\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"104062\",\"bibtex\":\"@article{seifert_eco-efficiency_2024,\\n\\ttitle = {Eco-efficiency in the agricultural landscape of {North} {Rhine}-{Westphalia}, {Germany}},\\n\\tvolume = {220},\\n\\tissn = {0308521X},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129},\\n\\tdoi = {10.1016/j.agsy.2024.104062},\\n\\tlanguage = {en},\\n\\turldate = {2024-10-01},\\n\\tjournal = {Agricultural Systems},\\n\\tauthor = {Seifert, Stefan and Wolff, Saskia and Hüttel, Silke},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {104062},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Seifert, S.\",\"Wolff, S.\",\"Hüttel, S.\"],\"key\":\"seifert_eco-efficiency_2024\",\"id\":\"seifert_eco-efficiency_2024\",\"bibbaseid\":\"seifert-wolff-httel-ecoefficiencyintheagriculturallandscapeofnorthrhinewestphaliagermany-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Sensitivity of aridity diagnoses to land-atmosphere coupling in South America\",\"issn\":\"0930-7575, 1432-0894\",\"url\":\"https://link.springer.com/10.1007/s00382-024-07413-w\",\"doi\":\"10.1007/s00382-024-07413-w\",\"language\":\"en\",\"urldate\":\"2024-09-27\",\"journal\":\"Climate Dynamics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Eugenio\",\"Russmann\"],\"firstnames\":[\"Juan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Menéndez\"],\"firstnames\":[\"Claudio\",\"G.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Giles\"],\"firstnames\":[\"Julian\",\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Carril\"],\"firstnames\":[\"Andrea\",\"F.\"],\"suffixes\":[]}],\"month\":\"September\",\"year\":\"2024\",\"bibtex\":\"@article{eugenio_russmann_sensitivity_2024,\\n\\ttitle = {Sensitivity of aridity diagnoses to land-atmosphere coupling in {South} {America}},\\n\\tissn = {0930-7575, 1432-0894},\\n\\turl = {https://link.springer.com/10.1007/s00382-024-07413-w},\\n\\tdoi = {10.1007/s00382-024-07413-w},\\n\\tlanguage = {en},\\n\\turldate = {2024-09-27},\\n\\tjournal = {Climate Dynamics},\\n\\tauthor = {Eugenio Russmann, Juan and Menéndez, Claudio G. and Giles, Julian A. and Carril, Andrea F.},\\n\\tmonth = sep,\\n\\tyear = {2024},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Eugenio Russmann, J.\",\"Menéndez, C. G.\",\"Giles, J. A.\",\"Carril, A. F.\"],\"key\":\"eugenio_russmann_sensitivity_2024\",\"id\":\"eugenio_russmann_sensitivity_2024\",\"bibbaseid\":\"eugeniorussmann-menndez-giles-carril-sensitivityofariditydiagnosestolandatmospherecouplinginsouthamerica-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://link.springer.com/10.1007/s00382-024-07413-w\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Multi-year aboveground data of minirhizotron facilities in Selhausen\",\"volume\":\"11\",\"issn\":\"2052-4463\",\"url\":\"https://www.nature.com/articles/s41597-024-03535-2\",\"doi\":\"10.1038/s41597-024-03535-2\",\"abstract\":\"Abstract Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO 2 and H 2 O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO 2 exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2024-08-20\",\"journal\":\"Scientific Data\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Nguyen\"],\"firstnames\":[\"Thuy\",\"Huu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lopez\"],\"firstnames\":[\"Gina\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Seidel\"],\"firstnames\":[\"Sabine\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lärm\"],\"firstnames\":[\"Lena\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bauer\"],\"firstnames\":[\"Felix\",\"Maximilian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Klotzsche\"],\"firstnames\":[\"Anja\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schnepf\"],\"firstnames\":[\"Andrea\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hüging\"],\"firstnames\":[\"Hubert\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ewert\"],\"firstnames\":[\"Frank\"],\"suffixes\":[]}],\"month\":\"June\",\"year\":\"2024\",\"pages\":\"674\",\"bibtex\":\"@article{nguyen_multi-year_2024,\\n\\ttitle = {Multi-year aboveground data of minirhizotron facilities in {Selhausen}},\\n\\tvolume = {11},\\n\\tissn = {2052-4463},\\n\\turl = {https://www.nature.com/articles/s41597-024-03535-2},\\n\\tdoi = {10.1038/s41597-024-03535-2},\\n\\tabstract = {Abstract\\n            \\n              Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO\\n              2\\n              and H\\n              2\\n              O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO\\n              2\\n              exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2024-08-20},\\n\\tjournal = {Scientific Data},\\n\\tauthor = {Nguyen, Thuy Huu and Lopez, Gina and Seidel, Sabine J. and Lärm, Lena and Bauer, Felix Maximilian and Klotzsche, Anja and Schnepf, Andrea and Gaiser, Thomas and Hüging, Hubert and Ewert, Frank},\\n\\tmonth = jun,\\n\\tyear = {2024},\\n\\tpages = {674},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Nguyen, T. H.\",\"Lopez, G.\",\"Seidel, S. J.\",\"Lärm, L.\",\"Bauer, F. M.\",\"Klotzsche, A.\",\"Schnepf, A.\",\"Gaiser, T.\",\"Hüging, H.\",\"Ewert, F.\"],\"key\":\"nguyen_multi-year_2024-1\",\"id\":\"nguyen_multi-year_2024-1\",\"bibbaseid\":\"nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s41597-024-03535-2\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Gnssrefl: an open source software package in python for GNSS interferometric reflectometry applications\",\"volume\":\"28\",\"issn\":\"1080-5370, 1521-1886\",\"shorttitle\":\"Gnssrefl\",\"url\":\"https://link.springer.com/10.1007/s10291-024-01694-8\",\"doi\":\"10.1007/s10291-024-01694-8\",\"abstract\":\"Abstract An open source software package has been developed for Global Navigation Satellite Systems (GNSS) interferometric reflectometry. The gnssrefl package is written in python; it can be installed from the source code, the python packaging index website, or via a docker. It includes modules that download GNSS data and orbit data from global archives. A periodogram is used to retrieve the height of the GNSS antenna over the reflecting surface using signal to noise ratio data. Signals from the Global Positioning System, Glonass, Galileo, and Beidou constellations are supported. Modules are provided to estimate volumetric water content of soil, snow depth/accumulation, and water level. Utilities for mapping and assessing reflection zones and determining the maximum resolvable height are available.\",\"language\":\"en\",\"number\":\"4\",\"urldate\":\"2024-08-20\",\"journal\":\"GPS Solutions\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Larson\"],\"firstnames\":[\"Kristine\",\"M.\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2024\",\"pages\":\"165\",\"bibtex\":\"@article{larson_gnssrefl_2024,\\n\\ttitle = {Gnssrefl: an open source software package in python for {GNSS} interferometric reflectometry applications},\\n\\tvolume = {28},\\n\\tissn = {1080-5370, 1521-1886},\\n\\tshorttitle = {Gnssrefl},\\n\\turl = {https://link.springer.com/10.1007/s10291-024-01694-8},\\n\\tdoi = {10.1007/s10291-024-01694-8},\\n\\tabstract = {Abstract\\n            An open source software package has been developed for Global Navigation Satellite Systems (GNSS) interferometric reflectometry. The gnssrefl package is written in python; it can be installed from the source code, the python packaging index website, or via a docker. It includes modules that download GNSS data and orbit data from global archives. A periodogram is used to retrieve the height of the GNSS antenna over the reflecting surface using signal to noise ratio data. Signals from the Global Positioning System, Glonass, Galileo, and Beidou constellations are supported. Modules are provided to estimate volumetric water content of soil, snow depth/accumulation, and water level. Utilities for mapping and assessing reflection zones and determining the maximum resolvable height are available.},\\n\\tlanguage = {en},\\n\\tnumber = {4},\\n\\turldate = {2024-08-20},\\n\\tjournal = {GPS Solutions},\\n\\tauthor = {Larson, Kristine M.},\\n\\tmonth = oct,\\n\\tyear = {2024},\\n\\tpages = {165},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Larson, K. M.\"],\"key\":\"larson_gnssrefl_2024\",\"id\":\"larson_gnssrefl_2024\",\"bibbaseid\":\"larson-gnssreflanopensourcesoftwarepackageinpythonforgnssinterferometricreflectometryapplications-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://link.springer.com/10.1007/s10291-024-01694-8\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"A Regionally Refined and Mass‐Consistent Atmospheric and Hydrological De‐Aliasing Product for GRACE, GRACE‐FO and Future Gravity Missions\",\"volume\":\"129\",\"issn\":\"2169-9313, 2169-9356\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883\",\"doi\":\"10.1029/2023JB027883\",\"abstract\":\"Abstract De‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de‐aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de‐aliasing products by nesting a regional high‐resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de‐aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3‐hourly data, our investigations suggest that contributions from continental hydrology and from regional non‐hydrostatic atmospheric modeling to sub‐monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions. , Plain Language Summary Observing temporal variations in the Earth's gravity field with satellite gravimetry plays an essential role for monitoring mass transports on and underneath the Earth's surface. This is crucial for understanding the evolution of floods and droughts, the role of groundwater pumping, and to quantify the melting of ice sheets and glaciers and the resulting sea level rise. In order to isolate the target variable (e.g., terrestrial water storage changes) unwanted signals (e.g., fast mass variations in the atmosphere) need to be removed in the gravity field estimation process using background models, so‐called de‐aliasing models. This paper focuses on improving background models by incorporating regional high‐resolution models, which more specifically resolve certain processes in the atmosphere. Our hypothesis is that this will lead to better gravity fields with increased spatial resolution and less noise. Moreover, we find that considering fast hydrological variations as additional background model could improve gravity fields from the current satellite mission GRACE‐FO. For the first time, we quantify contributions from so far neglected atmospheric moisture fields, such as cloud liquid water, to enhance background models in the context of extreme events—which, however, will likely be in particular relevant for more sensitive gravity missions in the future. , Key Points We provide an atmosphere‐hydrology de‐aliasing product with regional mass‐consistent refinement over Europe Using non‐hydrostatic as opposed to hydrostatic numerical weather prediction model output significantly impacts the de‐aliasing product We found that for extreme events additional moisture fields unaccounted in present Atmosphere and Ocean De‐aliasing (AOD) models can reach magnitudes relevant for de‐aliasing\",\"language\":\"en\",\"number\":\"5\",\"urldate\":\"2024-07-23\",\"journal\":\"Journal of Geophysical Research: Solid Earth\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Springer\"],\"firstnames\":[\"Anne\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Mielke\"],\"firstnames\":[\"Christian\",\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Liu\"],\"firstnames\":[\"Ziyu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Dixit\"],\"firstnames\":[\"Shashi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Friederichs\"],\"firstnames\":[\"Petra\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]}],\"month\":\"May\",\"year\":\"2024\",\"pages\":\"e2023JB027883\",\"bibtex\":\"@article{springer_regionally_2024,\\n\\ttitle = {A {Regionally} {Refined} and {Mass}‐{Consistent} {Atmospheric} and {Hydrological} {De}‐{Aliasing} {Product} for {GRACE}, {GRACE}‐{FO} and {Future} {Gravity} {Missions}},\\n\\tvolume = {129},\\n\\tissn = {2169-9313, 2169-9356},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883},\\n\\tdoi = {10.1029/2023JB027883},\\n\\tabstract = {Abstract\\n            De‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de‐aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de‐aliasing products by nesting a regional high‐resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de‐aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3‐hourly data, our investigations suggest that contributions from continental hydrology and from regional non‐hydrostatic atmospheric modeling to sub‐monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions.\\n          , \\n            Plain Language Summary\\n            Observing temporal variations in the Earth's gravity field with satellite gravimetry plays an essential role for monitoring mass transports on and underneath the Earth's surface. This is crucial for understanding the evolution of floods and droughts, the role of groundwater pumping, and to quantify the melting of ice sheets and glaciers and the resulting sea level rise. In order to isolate the target variable (e.g., terrestrial water storage changes) unwanted signals (e.g., fast mass variations in the atmosphere) need to be removed in the gravity field estimation process using background models, so‐called de‐aliasing models. This paper focuses on improving background models by incorporating regional high‐resolution models, which more specifically resolve certain processes in the atmosphere. Our hypothesis is that this will lead to better gravity fields with increased spatial resolution and less noise. Moreover, we find that considering fast hydrological variations as additional background model could improve gravity fields from the current satellite mission GRACE‐FO. For the first time, we quantify contributions from so far neglected atmospheric moisture fields, such as cloud liquid water, to enhance background models in the context of extreme events—which, however, will likely be in particular relevant for more sensitive gravity missions in the future.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  We provide an atmosphere‐hydrology de‐aliasing product with regional mass‐consistent refinement over Europe\\n                \\n                \\n                  Using non‐hydrostatic as opposed to hydrostatic numerical weather prediction model output significantly impacts the de‐aliasing product\\n                \\n                \\n                  We found that for extreme events additional moisture fields unaccounted in present Atmosphere and Ocean De‐aliasing (AOD) models can reach magnitudes relevant for de‐aliasing},\\n\\tlanguage = {en},\\n\\tnumber = {5},\\n\\turldate = {2024-07-23},\\n\\tjournal = {Journal of Geophysical Research: Solid Earth},\\n\\tauthor = {Springer, Anne and Mielke, Christian A. and Liu, Ziyu and Dixit, Shashi and Friederichs, Petra and Kusche, Jürgen},\\n\\tmonth = may,\\n\\tyear = {2024},\\n\\tpages = {e2023JB027883},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Springer, A.\",\"Mielke, C. A.\",\"Liu, Z.\",\"Dixit, S.\",\"Friederichs, P.\",\"Kusche, J.\"],\"key\":\"springer_regionally_2024\",\"id\":\"springer_regionally_2024\",\"bibbaseid\":\"springer-mielke-liu-dixit-friederichs-kusche-aregionallyrefinedandmassconsistentatmosphericandhydrologicaldealiasingproductforgracegracefoandfuturegravitymissions-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Global needs for nitrogen fertilizer to improve wheat yield under climate change\",\"issn\":\"2055-0278\",\"url\":\"https://www.nature.com/articles/s41477-024-01739-3\",\"doi\":\"10.1038/s41477-024-01739-3\",\"language\":\"en\",\"urldate\":\"2024-07-22\",\"journal\":\"Nature Plants\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Martre\"],\"firstnames\":[\"Pierre\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Dueri\"],\"firstnames\":[\"Sibylle\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Guarin\"],\"firstnames\":[\"Jose\",\"Rafael\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ewert\"],\"firstnames\":[\"Frank\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Webber\"],\"firstnames\":[\"Heidi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Calderini\"],\"firstnames\":[\"Daniel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Molero\"],\"firstnames\":[\"Gemma\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Reynolds\"],\"firstnames\":[\"Matthew\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Miralles\"],\"firstnames\":[\"Daniel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Garcia\"],\"firstnames\":[\"Guillermo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Brown\"],\"firstnames\":[\"Hamish\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"George\"],\"firstnames\":[\"Mike\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Craigie\"],\"firstnames\":[\"Rob\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Cohan\"],\"firstnames\":[\"Jean-Pierre\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Deswarte\"],\"firstnames\":[\"Jean-Charles\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Slafer\"],\"firstnames\":[\"Gustavo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Giunta\"],\"firstnames\":[\"Francesco\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Cammarano\"],\"firstnames\":[\"Davide\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ferrise\"],\"firstnames\":[\"Roberto\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gao\"],\"firstnames\":[\"Yujing\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hochman\"],\"firstnames\":[\"Zvi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hoogenboom\"],\"firstnames\":[\"Gerrit\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hunt\"],\"firstnames\":[\"Leslie\",\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kersebaum\"],\"firstnames\":[\"Kurt\",\"C.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Nendel\"],\"firstnames\":[\"Claas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Padovan\"],\"firstnames\":[\"Gloria\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ruane\"],\"firstnames\":[\"Alex\",\"C.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Srivastava\"],\"firstnames\":[\"Amit\",\"Kumar\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Stella\"],\"firstnames\":[\"Tommaso\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Supit\"],\"firstnames\":[\"Iwan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Thorburn\"],\"firstnames\":[\"Peter\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wang\"],\"firstnames\":[\"Enli\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wolf\"],\"firstnames\":[\"Joost\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhao\"],\"firstnames\":[\"Chuang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhao\"],\"firstnames\":[\"Zhigan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Asseng\"],\"firstnames\":[\"Senthold\"],\"suffixes\":[]}],\"month\":\"July\",\"year\":\"2024\",\"bibtex\":\"@article{martre_global_2024,\\n\\ttitle = {Global needs for nitrogen fertilizer to improve wheat yield under climate change},\\n\\tissn = {2055-0278},\\n\\turl = {https://www.nature.com/articles/s41477-024-01739-3},\\n\\tdoi = {10.1038/s41477-024-01739-3},\\n\\tlanguage = {en},\\n\\turldate = {2024-07-22},\\n\\tjournal = {Nature Plants},\\n\\tauthor = {Martre, Pierre and Dueri, Sibylle and Guarin, Jose Rafael and Ewert, Frank and Webber, Heidi and Calderini, Daniel and Molero, Gemma and Reynolds, Matthew and Miralles, Daniel and Garcia, Guillermo and Brown, Hamish and George, Mike and Craigie, Rob and Cohan, Jean-Pierre and Deswarte, Jean-Charles and Slafer, Gustavo and Giunta, Francesco and Cammarano, Davide and Ferrise, Roberto and Gaiser, Thomas and Gao, Yujing and Hochman, Zvi and Hoogenboom, Gerrit and Hunt, Leslie A. and Kersebaum, Kurt C. and Nendel, Claas and Padovan, Gloria and Ruane, Alex C. and Srivastava, Amit Kumar and Stella, Tommaso and Supit, Iwan and Thorburn, Peter and Wang, Enli and Wolf, Joost and Zhao, Chuang and Zhao, Zhigan and Asseng, Senthold},\\n\\tmonth = jul,\\n\\tyear = {2024},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Martre, P.\",\"Dueri, S.\",\"Guarin, J. R.\",\"Ewert, F.\",\"Webber, H.\",\"Calderini, D.\",\"Molero, G.\",\"Reynolds, M.\",\"Miralles, D.\",\"Garcia, G.\",\"Brown, H.\",\"George, M.\",\"Craigie, R.\",\"Cohan, J.\",\"Deswarte, J.\",\"Slafer, G.\",\"Giunta, F.\",\"Cammarano, D.\",\"Ferrise, R.\",\"Gaiser, T.\",\"Gao, Y.\",\"Hochman, Z.\",\"Hoogenboom, G.\",\"Hunt, L. A.\",\"Kersebaum, K. C.\",\"Nendel, C.\",\"Padovan, G.\",\"Ruane, A. C.\",\"Srivastava, A. K.\",\"Stella, T.\",\"Supit, I.\",\"Thorburn, P.\",\"Wang, E.\",\"Wolf, J.\",\"Zhao, C.\",\"Zhao, Z.\",\"Asseng, S.\"],\"key\":\"martre_global_2024\",\"id\":\"martre_global_2024\",\"bibbaseid\":\"martre-dueri-guarin-ewert-webber-calderini-molero-reynolds-etal-globalneedsfornitrogenfertilizertoimprovewheatyieldunderclimatechange-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s41477-024-01739-3\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Convection‐Permitting ICON‐LAM Simulations for Renewable Energy Potential Estimates Over Southern Africa\",\"volume\":\"129\",\"issn\":\"2169-897X, 2169-8996\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569\",\"doi\":\"10.1029/2023JD039569\",\"abstract\":\"Abstract Renewable energy is recognized in Africa as a means for climate change mitigation, but also to provide access to electricity in sub‐Saharan Africa, where three‐quarters of the global population without electricity resides. Reliable and highly resolved renewable energy potential (REP) information is indispensable to support power plants expansion. Existing atmospheric data sets over Africa that are used for REP estimates are often characterized by data gaps, or coarse resolution. With the aim to overcome these challenges, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON‐NWP) model in its Limited Area Mode (ICON‐LAM) is implemented and run over southern Africa in a hindcast dynamical downscaling setup at a convection‐permitting 3.3 km horizontal resolution. The simulation time span covers contrasting solar and wind weather years from 2017 to 2019. To assess the suitability of the novel simulations for REP estimates, the simulated hourly 10 m wind speed (sfcWind) and hourly surface solar irradiance (rsds) are extensively evaluated against a large compilation of in situ observations, satellite, and composite data products. ICON‐LAM reproduces the spatial patterns, temporal evolution, the variability, and absolute values of sfcWind sufficiently well, albeit with a slight overestimation and a mean bias (mean error (ME)) of 1.12 m s −1 over land. Likewise the simulated rsds with an ME of 50 W m −2 well resembles the observations. This new ICON simulation data product will be the basis for ensuing REP estimates that will be compared with existing lower resolution data sets. , Plain Language Summary There are still approximately 580 million people in Africa without reliable electricity supply. Renewable energy is broadly accepted as an important solution for Africa to fill the power supply gap and to mitigate climate change. Renewable energy potential (REP) information is thereby imperative for the expansion of renewable energy power planning. With conventional REP estimates, challenges are often linked to the meteorological input data, due to either the relatively coarse spatial resolution, data gaps in space and time, or data quality in general. In this study, we implemented and ran the atmospheric model ICOsahedral Nonhydrostatic (ICON) from the German Weather Service and partners at 3 km high‐resolution. The renewable energy variables wind speed and solar irradiance from these simulations are evaluated against an extensive in situ observations data set, as well as satellite, and other composite data products. In a comparison with more than 200 stations from three different in situ observation networks, it can be shown that ICON can reproduce REP‐related variables with a level of sophistication that the data is likely to offer added value over conventional inputs to REP assessments. The study is an example on how numerical models can fill in gaps in data‐scarce regions to produce useable information. , Key Points A new convection‐permitting regional ICOsahedral Nonhydrostatic (ICON) model setup over southern Africa is presented and evaluated The spatially and temporally highly resolved ICON wind and solar fields are inputs for improved renewable energy potential estimates ICON outputs agree well with hourly in situ observations and satellite data; wind speeds are slightly overestimated\",\"language\":\"en\",\"number\":\"6\",\"urldate\":\"2024-07-10\",\"journal\":\"Journal of Geophysical Research: Atmospheres\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Chen\"],\"firstnames\":[\"Shuying\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Poll\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hendricks\",\"Franssen\"],\"firstnames\":[\"Harrie‐Jan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Heinrichs\"],\"firstnames\":[\"Heidi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Goergen\"],\"firstnames\":[\"Klaus\"],\"suffixes\":[]}],\"month\":\"March\",\"year\":\"2024\",\"pages\":\"e2023JD039569\",\"bibtex\":\"@article{chen_convectionpermitting_2024,\\n\\ttitle = {Convection‐{Permitting} {ICON}‐{LAM} {Simulations} for {Renewable} {Energy} {Potential} {Estimates} {Over} {Southern} {Africa}},\\n\\tvolume = {129},\\n\\tissn = {2169-897X, 2169-8996},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569},\\n\\tdoi = {10.1029/2023JD039569},\\n\\tabstract = {Abstract\\n            \\n              Renewable energy is recognized in Africa as a means for climate change mitigation, but also to provide access to electricity in sub‐Saharan Africa, where three‐quarters of the global population without electricity resides. Reliable and highly resolved renewable energy potential (REP) information is indispensable to support power plants expansion. Existing atmospheric data sets over Africa that are used for REP estimates are often characterized by data gaps, or coarse resolution. With the aim to overcome these challenges, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON‐NWP) model in its Limited Area Mode (ICON‐LAM) is implemented and run over southern Africa in a hindcast dynamical downscaling setup at a convection‐permitting 3.3 km horizontal resolution. The simulation time span covers contrasting solar and wind weather years from 2017 to 2019. To assess the suitability of the novel simulations for REP estimates, the simulated hourly 10 m wind speed (sfcWind) and hourly surface solar irradiance (rsds) are extensively evaluated against a large compilation of in situ observations, satellite, and composite data products. ICON‐LAM reproduces the spatial patterns, temporal evolution, the variability, and absolute values of sfcWind sufficiently well, albeit with a slight overestimation and a mean bias (mean error (ME)) of 1.12 m s\\n              −1\\n              over land. Likewise the simulated rsds with an ME of 50 W m\\n              −2\\n              well resembles the observations. This new ICON simulation data product will be the basis for ensuing REP estimates that will be compared with existing lower resolution data sets.\\n            \\n          , \\n            Plain Language Summary\\n            There are still approximately 580 million people in Africa without reliable electricity supply. Renewable energy is broadly accepted as an important solution for Africa to fill the power supply gap and to mitigate climate change. Renewable energy potential (REP) information is thereby imperative for the expansion of renewable energy power planning. With conventional REP estimates, challenges are often linked to the meteorological input data, due to either the relatively coarse spatial resolution, data gaps in space and time, or data quality in general. In this study, we implemented and ran the atmospheric model ICOsahedral Nonhydrostatic (ICON) from the German Weather Service and partners at 3 km high‐resolution. The renewable energy variables wind speed and solar irradiance from these simulations are evaluated against an extensive in situ observations data set, as well as satellite, and other composite data products. In a comparison with more than 200 stations from three different in situ observation networks, it can be shown that ICON can reproduce REP‐related variables with a level of sophistication that the data is likely to offer added value over conventional inputs to REP assessments. The study is an example on how numerical models can fill in gaps in data‐scarce regions to produce useable information.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  A new convection‐permitting regional ICOsahedral Nonhydrostatic (ICON) model setup over southern Africa is presented and evaluated\\n                \\n                \\n                  The spatially and temporally highly resolved ICON wind and solar fields are inputs for improved renewable energy potential estimates\\n                \\n                \\n                  ICON outputs agree well with hourly in situ observations and satellite data; wind speeds are slightly overestimated},\\n\\tlanguage = {en},\\n\\tnumber = {6},\\n\\turldate = {2024-07-10},\\n\\tjournal = {Journal of Geophysical Research: Atmospheres},\\n\\tauthor = {Chen, Shuying and Poll, Stefan and Hendricks Franssen, Harrie‐Jan and Heinrichs, Heidi and Vereecken, Harry and Goergen, Klaus},\\n\\tmonth = mar,\\n\\tyear = {2024},\\n\\tpages = {e2023JD039569},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Chen, S.\",\"Poll, S.\",\"Hendricks Franssen, H.\",\"Heinrichs, H.\",\"Vereecken, H.\",\"Goergen, K.\"],\"key\":\"chen_convectionpermitting_2024\",\"id\":\"chen_convectionpermitting_2024\",\"bibbaseid\":\"chen-poll-hendricksfranssen-heinrichs-vereecken-goergen-convectionpermittingiconlamsimulationsforrenewableenergypotentialestimatesoversouthernafrica-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Probabilistic programming for embedding theory and quantifying uncertainty in econometric analysis\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"0165-1587, 1464-3618\",\"url\":\"https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545\",\"doi\":\"10.1093/erae/jbae016\",\"abstract\":\"Abstract The replication crisis in empirical research calls for a more mindful approach to how we apply and report statistical models. For empirical research to have a lasting (policy) impact, these concerns are crucial. In this paper, we present Probabilistic Programming (PP) as a way forward. The PP workflow with an explicit data-generating process enhances the communication of model assumptions, code testing and consistency between theory and estimation. By simplifying Bayesian analysis, it also offers advantages for the interpretation, communication and modelling of uncertainty. We outline the advantages of PP to encourage its adoption in our community.\",\"language\":\"en\",\"urldate\":\"2024-07-10\",\"journal\":\"European Review of Agricultural Economics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Storm\"],\"firstnames\":[\"Hugo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Heckelei\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Baylis\"],\"firstnames\":[\"Kathy\"],\"suffixes\":[]}],\"month\":\"July\",\"year\":\"2024\",\"pages\":\"jbae016\",\"bibtex\":\"@article{storm_probabilistic_2024,\\n\\ttitle = {Probabilistic programming for embedding theory and quantifying uncertainty in econometric analysis},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {0165-1587, 1464-3618},\\n\\turl = {https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545},\\n\\tdoi = {10.1093/erae/jbae016},\\n\\tabstract = {Abstract\\n            The replication crisis in empirical research calls for a more mindful approach to how we apply and report statistical models. For empirical research to have a lasting (policy) impact, these concerns are crucial. In this paper, we present Probabilistic Programming (PP) as a way forward. The PP workflow with an explicit data-generating process enhances the communication of model assumptions, code testing and consistency between theory and estimation. By simplifying Bayesian analysis, it also offers advantages for the interpretation, communication and modelling of uncertainty. We outline the advantages of PP to encourage its adoption in our community.},\\n\\tlanguage = {en},\\n\\turldate = {2024-07-10},\\n\\tjournal = {European Review of Agricultural Economics},\\n\\tauthor = {Storm, Hugo and Heckelei, Thomas and Baylis, Kathy},\\n\\tmonth = jul,\\n\\tyear = {2024},\\n\\tpages = {jbae016},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Storm, H.\",\"Heckelei, T.\",\"Baylis, K.\"],\"key\":\"storm_probabilistic_2024\",\"id\":\"storm_probabilistic_2024\",\"bibbaseid\":\"storm-heckelei-baylis-probabilisticprogrammingforembeddingtheoryandquantifyinguncertaintyineconometricanalysis-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP\",\"volume\":\"17\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"1991-9603\",\"url\":\"https://gmd.copernicus.org/articles/17/2387/2024/\",\"doi\":\"10.5194/gmd-17-2387-2024\",\"abstract\":\"Abstract. The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.\",\"language\":\"en\",\"number\":\"6\",\"urldate\":\"2024-06-26\",\"journal\":\"Geoscientific Model Development\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Fiedler\"],\"firstnames\":[\"Stephanie\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Naik\"],\"firstnames\":[\"Vaishali\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"O'Connor\"],\"firstnames\":[\"Fiona\",\"M.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Smith\"],\"firstnames\":[\"Christopher\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Griffiths\"],\"firstnames\":[\"Paul\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kramer\"],\"firstnames\":[\"Ryan\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Takemura\"],\"firstnames\":[\"Toshihiko\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Allen\"],\"firstnames\":[\"Robert\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Im\"],\"firstnames\":[\"Ulas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kasoar\"],\"firstnames\":[\"Matthew\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Modak\"],\"firstnames\":[\"Angshuman\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Turnock\"],\"firstnames\":[\"Steven\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Voulgarakis\"],\"firstnames\":[\"Apostolos\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Watson-Parris\"],\"firstnames\":[\"Duncan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Westervelt\"],\"firstnames\":[\"Daniel\",\"M.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wilcox\"],\"firstnames\":[\"Laura\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhao\"],\"firstnames\":[\"Alcide\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Collins\"],\"firstnames\":[\"William\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schulz\"],\"firstnames\":[\"Michael\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Myhre\"],\"firstnames\":[\"Gunnar\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Forster\"],\"firstnames\":[\"Piers\",\"M.\"],\"suffixes\":[]}],\"month\":\"March\",\"year\":\"2024\",\"pages\":\"2387–2417\",\"bibtex\":\"@article{fiedler_interactions_2024,\\n\\ttitle = {Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from {AerChemMIP}, {PDRMIP}, and {RFMIP}},\\n\\tvolume = {17},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {1991-9603},\\n\\turl = {https://gmd.copernicus.org/articles/17/2387/2024/},\\n\\tdoi = {10.5194/gmd-17-2387-2024},\\n\\tabstract = {Abstract. The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.},\\n\\tlanguage = {en},\\n\\tnumber = {6},\\n\\turldate = {2024-06-26},\\n\\tjournal = {Geoscientific Model Development},\\n\\tauthor = {Fiedler, Stephanie and Naik, Vaishali and O'Connor, Fiona M. and Smith, Christopher J. and Griffiths, Paul and Kramer, Ryan J. and Takemura, Toshihiko and Allen, Robert J. and Im, Ulas and Kasoar, Matthew and Modak, Angshuman and Turnock, Steven and Voulgarakis, Apostolos and Watson-Parris, Duncan and Westervelt, Daniel M. and Wilcox, Laura J. and Zhao, Alcide and Collins, William J. and Schulz, Michael and Myhre, Gunnar and Forster, Piers M.},\\n\\tmonth = mar,\\n\\tyear = {2024},\\n\\tpages = {2387--2417},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Fiedler, S.\",\"Naik, V.\",\"O'Connor, F. M.\",\"Smith, C. J.\",\"Griffiths, P.\",\"Kramer, R. J.\",\"Takemura, T.\",\"Allen, R. J.\",\"Im, U.\",\"Kasoar, M.\",\"Modak, A.\",\"Turnock, S.\",\"Voulgarakis, A.\",\"Watson-Parris, D.\",\"Westervelt, D. M.\",\"Wilcox, L. J.\",\"Zhao, A.\",\"Collins, W. J.\",\"Schulz, M.\",\"Myhre, G.\",\"Forster, P. M.\"],\"key\":\"fiedler_interactions_2024\",\"id\":\"fiedler_interactions_2024\",\"bibbaseid\":\"fiedler-naik-oconnor-smith-griffiths-kramer-takemura-allen-etal-interactionsbetweenatmosphericcompositionandclimatechangeprogressinunderstandingandfutureopportunitiesfromaerchemmippdrmipandrfmip-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://gmd.copernicus.org/articles/17/2387/2024/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Root hydraulic properties: An exploration of their variability across scales\",\"volume\":\"8\",\"issn\":\"2475-4455, 2475-4455\",\"shorttitle\":\"Root hydraulic properties\",\"url\":\"https://onlinelibrary.wiley.com/doi/10.1002/pld3.582\",\"doi\":\"10.1002/pld3.582\",\"abstract\":\"Abstract Root hydraulic properties are key physiological traits that determine the capacity of root systems to take up water, at a specific evaporative demand. They can strongly vary among species, cultivars or even within the same genotype, but a systematic analysis of their variation across plant functional types (PFTs) is still missing. Here, we reviewed published empirical studies on root hydraulic properties at the segment‐, individual root‐, or root system scale and determined its variability and the main factors contributing to it. This corresponded to a total of 241 published studies, comprising 213 species, including woody and herbaceous vegetation. We observed an extremely large range of variation (of orders of magnitude) in root hydraulic properties, but this was not caused by systematic differences among PFTs. Rather, the (combined) effect of factors such as root system age, driving force used for measurement, or stress treatments shaped the results. We found a significant decrease in root hydraulic properties under stress conditions (drought and aquaporin inhibition, p  \\\\textless .001) and a significant effect of the driving force used for measurement (hydrostatic or osmotic gradients, p  \\\\textless .001). Furthermore, whole root system conductance increased significantly with root system age across several crop species ( p  \\\\textless .01), causing very large variation in the data (\\\\textgreater2 orders of magnitude). Interestingly, this relationship showed an asymptotic shape, with a steep increase during the first days of growth and a flattening out at later stages of development. We confirmed this dynamic through simulations using a state‐of‐the‐art computational model of water flow in the root system for a variety of crop species, suggesting common patterns across studies and species. These findings provide better understanding of the main causes of root hydraulic properties variations observed across empirical studies. They also open the door to better representation of hydraulic processes across multiple plant functional types and at large scales. All data collected in our analysis has been aggregated into an open access database ( https://roothydraulic-properties.shinyapps.io/database/ ), fostering scientific exchange.\",\"language\":\"en\",\"number\":\"4\",\"urldate\":\"2024-04-25\",\"journal\":\"Plant Direct\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Baca\",\"Cabrera\"],\"firstnames\":[\"Juan\",\"C.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vanderborght\"],\"firstnames\":[\"Jan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Couvreur\"],\"firstnames\":[\"Valentin\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Behrend\"],\"firstnames\":[\"Dominik\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Nguyen\"],\"firstnames\":[\"Thuy\",\"Huu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lobet\"],\"firstnames\":[\"Guillaume\"],\"suffixes\":[]}],\"month\":\"April\",\"year\":\"2024\",\"pages\":\"e582\",\"bibtex\":\"@article{baca_cabrera_root_2024,\\n\\ttitle = {Root hydraulic properties: {An} exploration of their variability across scales},\\n\\tvolume = {8},\\n\\tissn = {2475-4455, 2475-4455},\\n\\tshorttitle = {Root hydraulic properties},\\n\\turl = {https://onlinelibrary.wiley.com/doi/10.1002/pld3.582},\\n\\tdoi = {10.1002/pld3.582},\\n\\tabstract = {Abstract\\n            Root hydraulic properties are key physiological traits that determine the capacity of root systems to take up water, at a specific evaporative demand. They can strongly vary among species, cultivars or even within the same genotype, but a systematic analysis of their variation across plant functional types (PFTs) is still missing. Here, we reviewed published empirical studies on root hydraulic properties at the segment‐, individual root‐, or root system scale and determined its variability and the main factors contributing to it. This corresponded to a total of 241 published studies, comprising 213 species, including woody and herbaceous vegetation.\\n            \\n              We observed an extremely large range of variation (of orders of magnitude) in root hydraulic properties, but this was not caused by systematic differences among PFTs. Rather, the (combined) effect of factors such as root system age, driving force used for measurement, or stress treatments shaped the results. We found a significant decrease in root hydraulic properties under stress conditions (drought and aquaporin inhibition,\\n              p\\n               {\\\\textless} .001) and a significant effect of the driving force used for measurement (hydrostatic or osmotic gradients,\\n              p\\n               {\\\\textless} .001). Furthermore, whole root system conductance increased significantly with root system age across several crop species (\\n              p\\n               {\\\\textless} .01), causing very large variation in the data ({\\\\textgreater}2 orders of magnitude). Interestingly, this relationship showed an asymptotic shape, with a steep increase during the first days of growth and a flattening out at later stages of development. We confirmed this dynamic through simulations using a state‐of‐the‐art computational model of water flow in the root system for a variety of crop species, suggesting common patterns across studies and species.\\n            \\n            \\n              These findings provide better understanding of the main causes of root hydraulic properties variations observed across empirical studies. They also open the door to better representation of hydraulic processes across multiple plant functional types and at large scales. All data collected in our analysis has been aggregated into an open access database (\\n              https://roothydraulic-properties.shinyapps.io/database/\\n              ), fostering scientific exchange.},\\n\\tlanguage = {en},\\n\\tnumber = {4},\\n\\turldate = {2024-04-25},\\n\\tjournal = {Plant Direct},\\n\\tauthor = {Baca Cabrera, Juan C. and Vanderborght, Jan and Couvreur, Valentin and Behrend, Dominik and Gaiser, Thomas and Nguyen, Thuy Huu and Lobet, Guillaume},\\n\\tmonth = apr,\\n\\tyear = {2024},\\n\\tpages = {e582},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Baca Cabrera, J. C.\",\"Vanderborght, J.\",\"Couvreur, V.\",\"Behrend, D.\",\"Gaiser, T.\",\"Nguyen, T. H.\",\"Lobet, G.\"],\"key\":\"baca_cabrera_root_2024\",\"id\":\"baca_cabrera_root_2024\",\"bibbaseid\":\"bacacabrera-vanderborght-couvreur-behrend-gaiser-nguyen-lobet-roothydraulicpropertiesanexplorationoftheirvariabilityacrossscales-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://onlinelibrary.wiley.com/doi/10.1002/pld3.582\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Focal-TSMP: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation\",\"volume\":\"17\",\"copyright\":\"https://creativecommons.org/licenses/by/4.0/\",\"issn\":\"1991-9603\",\"shorttitle\":\"Focal-TSMP\",\"url\":\"https://gmd.copernicus.org/articles/17/2987/2024/\",\"doi\":\"10.5194/gmd-17-2987-2024\",\"abstract\":\"Abstract. Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model’s applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP, last access: 4 April 2024).\",\"language\":\"en\",\"number\":\"7\",\"urldate\":\"2024-04-25\",\"journal\":\"Geoscientific Model Development\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Shams\",\"Eddin\"],\"firstnames\":[\"Mohamad\",\"Hakam\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gall\"],\"firstnames\":[\"Juergen\"],\"suffixes\":[]}],\"month\":\"April\",\"year\":\"2024\",\"pages\":\"2987–3023\",\"bibtex\":\"@article{shams_eddin_focal-tsmp_2024,\\n\\ttitle = {Focal-{TSMP}: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation},\\n\\tvolume = {17},\\n\\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\\n\\tissn = {1991-9603},\\n\\tshorttitle = {Focal-{TSMP}},\\n\\turl = {https://gmd.copernicus.org/articles/17/2987/2024/},\\n\\tdoi = {10.5194/gmd-17-2987-2024},\\n\\tabstract = {Abstract. Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model’s applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP, last access: 4 April 2024).},\\n\\tlanguage = {en},\\n\\tnumber = {7},\\n\\turldate = {2024-04-25},\\n\\tjournal = {Geoscientific Model Development},\\n\\tauthor = {Shams Eddin, Mohamad Hakam and Gall, Juergen},\\n\\tmonth = apr,\\n\\tyear = {2024},\\n\\tpages = {2987--3023},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Shams Eddin, M. H.\",\"Gall, J.\"],\"key\":\"shams_eddin_focal-tsmp_2024\",\"id\":\"shams_eddin_focal-tsmp_2024\",\"bibbaseid\":\"shamseddin-gall-focaltsmpdeeplearningforvegetationhealthpredictionandagriculturaldroughtassessmentfromaregionalclimatesimulation-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://gmd.copernicus.org/articles/17/2987/2024/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"The asymmetric impacts of international agricultural trade on water use scarcity, inequality and inequity\",\"issn\":\"2731-6084\",\"url\":\"https://www.nature.com/articles/s44221-024-00224-7\",\"doi\":\"10.1038/s44221-024-00224-7\",\"language\":\"en\",\"urldate\":\"2024-04-25\",\"journal\":\"Nature Water\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Gu\"],\"firstnames\":[\"Weiyi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wang\"],\"firstnames\":[\"Fang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Siebert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kummu\"],\"firstnames\":[\"Matti\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wang\"],\"firstnames\":[\"Xuhui\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hong\"],\"firstnames\":[\"Chaopeng\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhou\"],\"firstnames\":[\"Feng\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhu\"],\"firstnames\":[\"Qing\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Liu\"],\"firstnames\":[\"Yong\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Qin\"],\"firstnames\":[\"Yue\"],\"suffixes\":[]}],\"month\":\"April\",\"year\":\"2024\",\"bibtex\":\"@article{gu_asymmetric_2024,\\n\\ttitle = {The asymmetric impacts of international agricultural trade on water use scarcity, inequality and inequity},\\n\\tissn = {2731-6084},\\n\\turl = {https://www.nature.com/articles/s44221-024-00224-7},\\n\\tdoi = {10.1038/s44221-024-00224-7},\\n\\tlanguage = {en},\\n\\turldate = {2024-04-25},\\n\\tjournal = {Nature Water},\\n\\tauthor = {Gu, Weiyi and Wang, Fang and Siebert, Stefan and Kummu, Matti and Wang, Xuhui and Hong, Chaopeng and Zhou, Feng and Zhu, Qing and Liu, Yong and Qin, Yue},\\n\\tmonth = apr,\\n\\tyear = {2024},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Gu, W.\",\"Wang, F.\",\"Siebert, S.\",\"Kummu, M.\",\"Wang, X.\",\"Hong, C.\",\"Zhou, F.\",\"Zhu, Q.\",\"Liu, Y.\",\"Qin, Y.\"],\"key\":\"gu_asymmetric_2024\",\"id\":\"gu_asymmetric_2024\",\"bibbaseid\":\"gu-wang-siebert-kummu-wang-hong-zhou-zhu-etal-theasymmetricimpactsofinternationalagriculturaltradeonwaterusescarcityinequalityandinequity-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s44221-024-00224-7\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Location-Aware Adaptive Normalization: A Deep Learning Approach for Wildfire Danger Forecasting\",\"volume\":\"61\",\"copyright\":\"https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html\",\"issn\":\"0196-2892, 1558-0644\",\"shorttitle\":\"Location-Aware Adaptive Normalization\",\"url\":\"https://ieeexplore.ieee.org/document/10149031/\",\"doi\":\"10.1109/TGRS.2023.3285401\",\"urldate\":\"2024-04-25\",\"journal\":\"IEEE Transactions on Geoscience and Remote Sensing\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Shams\",\"Eddin\"],\"firstnames\":[\"Mohamad\",\"Hakam\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Roscher\"],\"firstnames\":[\"Ribana\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gall\"],\"firstnames\":[\"Juergen\"],\"suffixes\":[]}],\"year\":\"2023\",\"pages\":\"1–18\",\"bibtex\":\"@article{shams_eddin_location-aware_2023,\\n\\ttitle = {Location-{Aware} {Adaptive} {Normalization}: {A} {Deep} {Learning} {Approach} for {Wildfire} {Danger} {Forecasting}},\\n\\tvolume = {61},\\n\\tcopyright = {https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html},\\n\\tissn = {0196-2892, 1558-0644},\\n\\tshorttitle = {Location-{Aware} {Adaptive} {Normalization}},\\n\\turl = {https://ieeexplore.ieee.org/document/10149031/},\\n\\tdoi = {10.1109/TGRS.2023.3285401},\\n\\turldate = {2024-04-25},\\n\\tjournal = {IEEE Transactions on Geoscience and Remote Sensing},\\n\\tauthor = {Shams Eddin, Mohamad Hakam and Roscher, Ribana and Gall, Juergen},\\n\\tyear = {2023},\\n\\tpages = {1--18},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Shams Eddin, M. H.\",\"Roscher, R.\",\"Gall, J.\"],\"key\":\"shams_eddin_location-aware_2023\",\"id\":\"shams_eddin_location-aware_2023\",\"bibbaseid\":\"shamseddin-roscher-gall-locationawareadaptivenormalizationadeeplearningapproachforwildfiredangerforecasting-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://ieeexplore.ieee.org/document/10149031/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Half of twenty-first century global irrigation expansion has been in water-stressed regions\",\"issn\":\"2731-6084\",\"url\":\"https://www.nature.com/articles/s44221-024-00206-9\",\"doi\":\"10.1038/s44221-024-00206-9\",\"abstract\":\"Abstract The expansion of irrigated agriculture has increased global crop production but resulted in widespread stress on freshwater resources. Ensuring that increases in irrigated production occur only in places where water is relatively abundant is a key objective of sustainable agriculture and knowledge of how irrigated land has evolved is important for measuring progress towards water sustainability. Yet, a spatially detailed understanding of the evolution of the global area equipped for irrigation (AEI) is missing. In this study, we used the latest subnational irrigation statistics (covering 17,298 administrative units) from various official sources to develop a gridded (5 arcmin resolution) global product of AEI for the years 2000, 2005, 2010 and 2015. We found that AEI increased by 11% from 2000 (297 Mha) to 2015 (330 Mha), with areas of both substantial expansion, such as northwest India and northeast China, and decline, such as Russia. Combining these outputs with information on green (that is, rainfall) and blue (that is, surface and ground) water stress, we also examined to what extent irrigation has expanded unsustainably in places already experiencing water stress. We found that more than half (52%) of the irrigation expansion has taken place in areas that were already water-stressed in the year 2000, with India alone accounting for 36% of global unsustainable expansion. These findings provide new insights into the evolving patterns of global irrigation with important implications for global water sustainability and food security.\",\"language\":\"en\",\"urldate\":\"2024-03-11\",\"journal\":\"Nature Water\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Mehta\"],\"firstnames\":[\"Piyush\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Siebert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kummu\"],\"firstnames\":[\"Matti\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Deng\"],\"firstnames\":[\"Qinyu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ali\"],\"firstnames\":[\"Tariq\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Marston\"],\"firstnames\":[\"Landon\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Xie\"],\"firstnames\":[\"Wei\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Davis\"],\"firstnames\":[\"Kyle\",\"Frankel\"],\"suffixes\":[]}],\"month\":\"March\",\"year\":\"2024\",\"bibtex\":\"@article{mehta_half_2024,\\n\\ttitle = {Half of twenty-first century global irrigation expansion has been in water-stressed regions},\\n\\tissn = {2731-6084},\\n\\turl = {https://www.nature.com/articles/s44221-024-00206-9},\\n\\tdoi = {10.1038/s44221-024-00206-9},\\n\\tabstract = {Abstract\\n            The expansion of irrigated agriculture has increased global crop production but resulted in widespread stress on freshwater resources. Ensuring that increases in irrigated production occur only in places where water is relatively abundant is a key objective of sustainable agriculture and knowledge of how irrigated land has evolved is important for measuring progress towards water sustainability. Yet, a spatially detailed understanding of the evolution of the global area equipped for irrigation (AEI) is missing. In this study, we used the latest subnational irrigation statistics (covering 17,298 administrative units) from various official sources to develop a gridded (5 arcmin resolution) global product of AEI for the years 2000, 2005, 2010 and 2015. We found that AEI increased by 11\\\\% from 2000 (297 Mha) to 2015 (330 Mha), with areas of both substantial expansion, such as northwest India and northeast China, and decline, such as Russia. Combining these outputs with information on green (that is, rainfall) and blue (that is, surface and ground) water stress, we also examined to what extent irrigation has expanded unsustainably in places already experiencing water stress. We found that more than half (52\\\\%) of the irrigation expansion has taken place in areas that were already water-stressed in the year 2000, with India alone accounting for 36\\\\% of global unsustainable expansion. These findings provide new insights into the evolving patterns of global irrigation with important implications for global water sustainability and food security.},\\n\\tlanguage = {en},\\n\\turldate = {2024-03-11},\\n\\tjournal = {Nature Water},\\n\\tauthor = {Mehta, Piyush and Siebert, Stefan and Kummu, Matti and Deng, Qinyu and Ali, Tariq and Marston, Landon and Xie, Wei and Davis, Kyle Frankel},\\n\\tmonth = mar,\\n\\tyear = {2024},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Mehta, P.\",\"Siebert, S.\",\"Kummu, M.\",\"Deng, Q.\",\"Ali, T.\",\"Marston, L.\",\"Xie, W.\",\"Davis, K. F.\"],\"key\":\"mehta_half_2024\",\"id\":\"mehta_half_2024\",\"bibbaseid\":\"mehta-siebert-kummu-deng-ali-marston-xie-davis-halfoftwentyfirstcenturyglobalirrigationexpansionhasbeeninwaterstressedregions-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s44221-024-00206-9\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data\",\"volume\":\"28\",\"issn\":\"1607-7938\",\"url\":\"https://hess.copernicus.org/articles/28/1001/2024/\",\"doi\":\"10.5194/hess-28-1001-2024\",\"abstract\":\"Abstract. Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSMs with observations, data assimilation methods and tools have been developed in the past decades. We apply the coupled Community Land Model version 5 (CLM5) and Parallel Data Assimilation Framework (PDAF) system (CLM5-PDAF) for 13 forest field sites throughout Europe covering different climate zones. The goal of this study is to assimilate in situ soil moisture measurements into CLM5 to improve the modeled evapotranspiration fluxes. The modeled fluxes will be evaluated using the predicted evapotranspiration fluxes with eddy covariance (EC) systems. Most of the sites use point-scale measurements from sensors placed in the ground; however, for three of the forest sites we use soil water content data from cosmic-ray neutron sensors, which have a measurement scale closer to the typical land surface model grid scale and EC footprint. Our results show that while data assimilation reduced the root-mean-square error for soil water content on average by 56 % to 64 %, the root-mean-square error for the evapotranspiration estimation is increased by 4 %. This finding indicates that only improving the soil water content (SWC) estimation of state-of-the-art LSMs such as CLM5 is not sufficient to improve evapotranspiration estimates for forest sites. To improve evapotranspiration estimates, it is also necessary to consider the representation of leaf area index (LAI) in magnitude and timing, as well as uncertainties in water uptake by roots and vegetation parameters.\",\"language\":\"en\",\"number\":\"4\",\"urldate\":\"2024-03-05\",\"journal\":\"Hydrology and Earth System Sciences\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Strebel\"],\"firstnames\":[\"Lukas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bogena\"],\"firstnames\":[\"Heye\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Andreasen\"],\"firstnames\":[\"Mie\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Aranda-Barranco\"],\"firstnames\":[\"Sergio\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hendricks\",\"Franssen\"],\"firstnames\":[\"Harrie-Jan\"],\"suffixes\":[]}],\"month\":\"February\",\"year\":\"2024\",\"pages\":\"1001–1026\",\"bibtex\":\"@article{strebel_evapotranspiration_2024,\\n\\ttitle = {Evapotranspiration prediction for {European} forest sites does not improve with assimilation of in situ soil water content data},\\n\\tvolume = {28},\\n\\tissn = {1607-7938},\\n\\turl = {https://hess.copernicus.org/articles/28/1001/2024/},\\n\\tdoi = {10.5194/hess-28-1001-2024},\\n\\tabstract = {Abstract. Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSMs with observations, data assimilation methods and tools have been developed in the past decades. We apply the coupled Community Land Model version 5 (CLM5) and Parallel Data Assimilation Framework (PDAF) system (CLM5-PDAF) for 13 forest field sites throughout Europe covering different climate zones. The goal of this study is to assimilate in situ soil moisture measurements into CLM5 to improve the modeled evapotranspiration fluxes. The modeled fluxes will be evaluated using the predicted evapotranspiration fluxes with eddy covariance (EC) systems. Most of the sites use point-scale measurements from sensors placed in the ground; however, for three of the forest sites we use soil water content data from cosmic-ray neutron sensors, which have a measurement scale closer to the typical land surface model grid scale and EC footprint. Our results show that while data assimilation reduced the root-mean-square error for soil water content on average by 56 \\\\% to 64 \\\\%, the root-mean-square error for the evapotranspiration estimation is increased by 4 \\\\%. This finding indicates that only improving the soil water content (SWC) estimation of state-of-the-art LSMs such as CLM5 is not sufficient to improve evapotranspiration estimates for forest sites. To improve evapotranspiration estimates, it is also necessary to consider the representation of leaf area index (LAI) in magnitude and timing, as well as uncertainties in water uptake by roots and vegetation parameters.},\\n\\tlanguage = {en},\\n\\tnumber = {4},\\n\\turldate = {2024-03-05},\\n\\tjournal = {Hydrology and Earth System Sciences},\\n\\tauthor = {Strebel, Lukas and Bogena, Heye and Vereecken, Harry and Andreasen, Mie and Aranda-Barranco, Sergio and Hendricks Franssen, Harrie-Jan},\\n\\tmonth = feb,\\n\\tyear = {2024},\\n\\tpages = {1001--1026},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Strebel, L.\",\"Bogena, H.\",\"Vereecken, H.\",\"Andreasen, M.\",\"Aranda-Barranco, S.\",\"Hendricks Franssen, H.\"],\"key\":\"strebel_evapotranspiration_2024\",\"id\":\"strebel_evapotranspiration_2024\",\"bibbaseid\":\"strebel-bogena-vereecken-andreasen-arandabarranco-hendricksfranssen-evapotranspirationpredictionforeuropeanforestsitesdoesnotimprovewithassimilationofinsitusoilwatercontentdata-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://hess.copernicus.org/articles/28/1001/2024/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"On study of the Earth topography correction for the GRACE surface mass estimation\",\"volume\":\"96\",\"issn\":\"0949-7714, 1432-1394\",\"url\":\"https://link.springer.com/10.1007/s00190-022-01683-0\",\"doi\":\"10.1007/s00190-022-01683-0\",\"language\":\"en\",\"number\":\"12\",\"urldate\":\"2024-03-05\",\"journal\":\"Journal of Geodesy\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Yang\"],\"firstnames\":[\"Fan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Luo\"],\"firstnames\":[\"ZhiCai\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhou\"],\"firstnames\":[\"Hao\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]}],\"month\":\"December\",\"year\":\"2022\",\"pages\":\"95\",\"bibtex\":\"@article{yang_study_2022,\\n\\ttitle = {On study of the {Earth} topography correction for the {GRACE} surface mass estimation},\\n\\tvolume = {96},\\n\\tissn = {0949-7714, 1432-1394},\\n\\turl = {https://link.springer.com/10.1007/s00190-022-01683-0},\\n\\tdoi = {10.1007/s00190-022-01683-0},\\n\\tlanguage = {en},\\n\\tnumber = {12},\\n\\turldate = {2024-03-05},\\n\\tjournal = {Journal of Geodesy},\\n\\tauthor = {Yang, Fan and Luo, ZhiCai and Zhou, Hao and Kusche, Jürgen},\\n\\tmonth = dec,\\n\\tyear = {2022},\\n\\tpages = {95},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Yang, F.\",\"Luo, Z.\",\"Zhou, H.\",\"Kusche, J.\"],\"key\":\"yang_study_2022\",\"id\":\"yang_study_2022\",\"bibbaseid\":\"yang-luo-zhou-kusche-onstudyoftheearthtopographycorrectionforthegracesurfacemassestimation-2022\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://link.springer.com/10.1007/s00190-022-01683-0\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Snowmelt risk telecouplings for irrigated agriculture\",\"volume\":\"12\",\"issn\":\"1758-678X, 1758-6798\",\"url\":\"https://www.nature.com/articles/s41558-022-01509-z\",\"doi\":\"10.1038/s41558-022-01509-z\",\"language\":\"en\",\"number\":\"11\",\"urldate\":\"2024-03-05\",\"journal\":\"Nature Climate Change\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Qin\"],\"firstnames\":[\"Yue\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hong\"],\"firstnames\":[\"Chaopeng\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhao\"],\"firstnames\":[\"Hongyan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Siebert\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Abatzoglou\"],\"firstnames\":[\"John\",\"T.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Huning\"],\"firstnames\":[\"Laurie\",\"S.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Sloat\"],\"firstnames\":[\"Lindsey\",\"L.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Park\"],\"firstnames\":[\"Sohyun\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Li\"],\"firstnames\":[\"Shiyu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Munroe\"],\"firstnames\":[\"Darla\",\"K.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhu\"],\"firstnames\":[\"Tong\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Davis\"],\"firstnames\":[\"Steven\",\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Mueller\"],\"firstnames\":[\"Nathaniel\",\"D.\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2022\",\"pages\":\"1007–1015\",\"bibtex\":\"@article{qin_snowmelt_2022,\\n\\ttitle = {Snowmelt risk telecouplings for irrigated agriculture},\\n\\tvolume = {12},\\n\\tissn = {1758-678X, 1758-6798},\\n\\turl = {https://www.nature.com/articles/s41558-022-01509-z},\\n\\tdoi = {10.1038/s41558-022-01509-z},\\n\\tlanguage = {en},\\n\\tnumber = {11},\\n\\turldate = {2024-03-05},\\n\\tjournal = {Nature Climate Change},\\n\\tauthor = {Qin, Yue and Hong, Chaopeng and Zhao, Hongyan and Siebert, Stefan and Abatzoglou, John T. and Huning, Laurie S. and Sloat, Lindsey L. and Park, Sohyun and Li, Shiyu and Munroe, Darla K. and Zhu, Tong and Davis, Steven J. and Mueller, Nathaniel D.},\\n\\tmonth = nov,\\n\\tyear = {2022},\\n\\tpages = {1007--1015},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Qin, Y.\",\"Hong, C.\",\"Zhao, H.\",\"Siebert, S.\",\"Abatzoglou, J. T.\",\"Huning, L. S.\",\"Sloat, L. L.\",\"Park, S.\",\"Li, S.\",\"Munroe, D. K.\",\"Zhu, T.\",\"Davis, S. J.\",\"Mueller, N. D.\"],\"key\":\"qin_snowmelt_2022\",\"id\":\"qin_snowmelt_2022\",\"bibbaseid\":\"qin-hong-zhao-siebert-abatzoglou-huning-sloat-park-etal-snowmeltrisktelecouplingsforirrigatedagriculture-2022\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s41558-022-01509-z\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Mapping land degradation risk due to land susceptibility to dust emission and water erosion\",\"volume\":\"9\",\"issn\":\"2199-398X\",\"url\":\"https://soil.copernicus.org/articles/9/411/2023/\",\"doi\":\"10.5194/soil-9-411-2023\",\"abstract\":\"Abstract. Land degradation is a cause of many social, economic, and environmental problems. Therefore identification and monitoring of high-risk areas for land degradation are necessary. Despite the importance of land degradation due to wind and water erosion in some areas of the world, the combined study of both types of erosion in the same area receives relatively little attention. The present study aims to create a land degradation map in terms of soil erosion caused by wind and water erosion of semi-dry land. We focus on the Lut watershed in Iran, encompassing the Lut Desert that is influenced by both monsoon rainfalls and dust storms. Dust sources are identified using MODIS satellite images with the help of four different indices to quantify uncertainty. The dust source maps are assessed with three machine learning algorithms encompassing the artificial neural network (ANN), random forest (RF), and flexible discriminant analysis (FDA) to map dust sources paired with soil erosion susceptibility due to water. We assess the accuracy of the maps from the machine learning results with the area under the curve (AUC) of the receiver operating characteristic (ROC) metric. The water and aeolian soil erosion maps are used to identify different classes of land degradation risks. The results show that 43 % of the watershed is prone to land degradation in terms of both aeolian and water erosion. Most regions (45 %) have a risk of water erosion and some regions (7 %) a risk of aeolian erosion. Only a small fraction (4 %) of the total area of the region had a low to very low susceptibility for land degradation. The results of this study underline the risk of land degradation for in an inhabited region in Iran. Future work should focus on land degradation associated with soil erosion from water and storms in larger regions to evaluate the risks also elsewhere.\",\"language\":\"en\",\"number\":\"2\",\"urldate\":\"2024-02-26\",\"journal\":\"SOIL\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Boroughani\"],\"firstnames\":[\"Mahdi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Mirchooli\"],\"firstnames\":[\"Fahimeh\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hadavifar\"],\"firstnames\":[\"Mojtaba\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Fiedler\"],\"firstnames\":[\"Stephanie\"],\"suffixes\":[]}],\"month\":\"July\",\"year\":\"2023\",\"pages\":\"411–423\",\"bibtex\":\"@article{boroughani_mapping_2023,\\n\\ttitle = {Mapping land degradation risk due to land susceptibility to dust emission and water erosion},\\n\\tvolume = {9},\\n\\tissn = {2199-398X},\\n\\turl = {https://soil.copernicus.org/articles/9/411/2023/},\\n\\tdoi = {10.5194/soil-9-411-2023},\\n\\tabstract = {Abstract. Land degradation is a cause of many social, economic, and environmental\\nproblems. Therefore identification and monitoring of high-risk areas for\\nland degradation are necessary. Despite the importance of land degradation\\ndue to wind and water erosion in some areas of the world, the combined study\\nof both types of erosion in the same area receives relatively little\\nattention. The present study aims to create a land degradation map in terms\\nof soil erosion caused by wind and water erosion of semi-dry land. We focus\\non the Lut watershed in Iran, encompassing the Lut Desert that is influenced\\nby both monsoon rainfalls and dust storms. Dust sources are identified using\\nMODIS satellite images with the help of four different indices to quantify\\nuncertainty. The dust source maps are assessed with three machine learning\\nalgorithms encompassing the artificial neural network (ANN), random forest (RF),\\nand flexible discriminant analysis (FDA) to map dust sources paired with\\nsoil erosion susceptibility due to water. We assess the accuracy of the maps\\nfrom the machine learning results with the area under the curve (AUC)\\nof the receiver operating characteristic (ROC) metric. The water and aeolian soil\\nerosion maps are used to identify different classes of land degradation\\nrisks. The results show that 43 \\\\% of the watershed is prone to land\\ndegradation in terms of both aeolian and water erosion. Most regions\\n(45 \\\\%) have a risk of water erosion and some regions (7 \\\\%) a risk of\\naeolian erosion. Only a small fraction (4 \\\\%) of the total area of the\\nregion had a low to very low susceptibility for land degradation. The\\nresults of this study underline the risk of land degradation for in an\\ninhabited region in Iran. Future work should focus on land degradation\\nassociated with soil erosion from water and storms in larger regions to\\nevaluate the risks also elsewhere.},\\n\\tlanguage = {en},\\n\\tnumber = {2},\\n\\turldate = {2024-02-26},\\n\\tjournal = {SOIL},\\n\\tauthor = {Boroughani, Mahdi and Mirchooli, Fahimeh and Hadavifar, Mojtaba and Fiedler, Stephanie},\\n\\tmonth = jul,\\n\\tyear = {2023},\\n\\tpages = {411--423},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Boroughani, M.\",\"Mirchooli, F.\",\"Hadavifar, M.\",\"Fiedler, S.\"],\"key\":\"boroughani_mapping_2023\",\"id\":\"boroughani_mapping_2023\",\"bibbaseid\":\"boroughani-mirchooli-hadavifar-fiedler-mappinglanddegradationriskduetolandsusceptibilitytodustemissionandwatererosion-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://soil.copernicus.org/articles/9/411/2023/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Can a Sparse Network of Cosmic Ray Neutron Sensors Improve Soil Moisture and Evapotranspiration Estimation at the Larger Catchment Scale?\",\"volume\":\"60\",\"issn\":\"0043-1397, 1944-7973\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056\",\"doi\":\"10.1029/2023WR035056\",\"abstract\":\"Abstract Cosmic‐ray neutron sensors (CRNS) fill the gap between locally measured in‐situ soil moisture (SM) and remotely sensed SM by providing accurate SM estimation at the field scale. This is promising for improving hydrologic model predictions, as CRNS can provide valuable information on SM in the root zone at the typical scale of a model grid cell. In this study, SM measurements from a network of 12 CRNS in the Rur catchment (Germany) were assimilated into the Terrestrial System Modeling Platform (TSMP) to investigate its potential for improving SM, evapotranspiration (ET) and river discharge characterization and estimating soil hydraulic parameters at the larger catchment scale. The data assimilation (DA) experiments (with and without parameter estimation) were conducted in both a wet year (2016) and a dry year (2018) with the ensemble Kalman filter (EnKF), and later verified with an independent year (2017) without DA. The results show that SM characterization was significantly improved at measurement locations (with up to 60% root mean square error (RMSE) reduction), and that joint state‐parameter estimation improved SM simulation more than state estimation alone (more than 15% additional RMSE reduction). Jackknife experiments showed that SM at verification locations had lower and different improvements in the wet and dry years (an RMSE reduction of 40% in 2016 and 16% in 2018). In addition, SM assimilation was found to improve ET characterization to a much lesser extent, with a 15% RMSE reduction of monthly ET in the wet year and 9% in the dry year. , Key Points Assimilation of soil moisture from a network of cosmic‐ray neutron sensors improves soil moisture characterization at the catchment scale Soil moisture characterization improved more in a wet year than in a very dry year Evapotranspiration and river discharge simulation are only slightly improved, despite better estimations of soil moisture\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2024-02-26\",\"journal\":\"Water Resources Research\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Li\"],\"firstnames\":[\"Fang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bogena\"],\"firstnames\":[\"Heye\",\"Reemt\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bayat\"],\"firstnames\":[\"Bagher\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kurtz\"],\"firstnames\":[\"Wolfgang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hendricks\",\"Franssen\"],\"firstnames\":[\"Harrie‐Jan\"],\"suffixes\":[]}],\"month\":\"January\",\"year\":\"2024\",\"pages\":\"e2023WR035056\",\"bibtex\":\"@article{li_can_2024,\\n\\ttitle = {Can a {Sparse} {Network} of {Cosmic} {Ray} {Neutron} {Sensors} {Improve} {Soil} {Moisture} and {Evapotranspiration} {Estimation} at the {Larger} {Catchment} {Scale}?},\\n\\tvolume = {60},\\n\\tissn = {0043-1397, 1944-7973},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056},\\n\\tdoi = {10.1029/2023WR035056},\\n\\tabstract = {Abstract\\n            Cosmic‐ray neutron sensors (CRNS) fill the gap between locally measured in‐situ soil moisture (SM) and remotely sensed SM by providing accurate SM estimation at the field scale. This is promising for improving hydrologic model predictions, as CRNS can provide valuable information on SM in the root zone at the typical scale of a model grid cell. In this study, SM measurements from a network of 12 CRNS in the Rur catchment (Germany) were assimilated into the Terrestrial System Modeling Platform (TSMP) to investigate its potential for improving SM, evapotranspiration (ET) and river discharge characterization and estimating soil hydraulic parameters at the larger catchment scale. The data assimilation (DA) experiments (with and without parameter estimation) were conducted in both a wet year (2016) and a dry year (2018) with the ensemble Kalman filter (EnKF), and later verified with an independent year (2017) without DA. The results show that SM characterization was significantly improved at measurement locations (with up to 60\\\\% root mean square error (RMSE) reduction), and that joint state‐parameter estimation improved SM simulation more than state estimation alone (more than 15\\\\% additional RMSE reduction). Jackknife experiments showed that SM at verification locations had lower and different improvements in the wet and dry years (an RMSE reduction of 40\\\\% in 2016 and 16\\\\% in 2018). In addition, SM assimilation was found to improve ET characterization to a much lesser extent, with a 15\\\\% RMSE reduction of monthly ET in the wet year and 9\\\\% in the dry year.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  Assimilation of soil moisture from a network of cosmic‐ray neutron sensors improves soil moisture characterization at the catchment scale\\n                \\n                \\n                  Soil moisture characterization improved more in a wet year than in a very dry year\\n                \\n                \\n                  Evapotranspiration and river discharge simulation are only slightly improved, despite better estimations of soil moisture},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2024-02-26},\\n\\tjournal = {Water Resources Research},\\n\\tauthor = {Li, Fang and Bogena, Heye Reemt and Bayat, Bagher and Kurtz, Wolfgang and Hendricks Franssen, Harrie‐Jan},\\n\\tmonth = jan,\\n\\tyear = {2024},\\n\\tpages = {e2023WR035056},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Li, F.\",\"Bogena, H. R.\",\"Bayat, B.\",\"Kurtz, W.\",\"Hendricks Franssen, H.\"],\"key\":\"li_can_2024\",\"id\":\"li_can_2024\",\"bibbaseid\":\"li-bogena-bayat-kurtz-hendricksfranssen-canasparsenetworkofcosmicrayneutronsensorsimprovesoilmoistureandevapotranspirationestimationatthelargercatchmentscale-2024\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056\"},\"metadata\":{\"authorlinks\":{}},\"downloads\":12,\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"A detailed analysis of stochastic models applied to temporal gravity field recovery with GRACE observations\",\"volume\":\"236\",\"issn\":\"0956-540X, 1365-246X\",\"url\":\"https://academic.oup.com/gji/article/236/1/516/7382201\",\"doi\":\"10.1093/gji/ggad441\",\"abstract\":\"SUMMARY In this study, we analysed the impacts of errors in background force models and observed non-gravitational forces on the pseudo-observations (pre-fits) during gravity field recovery based on the Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission. To reduce these effects, we introduced the stochastic parameters into the functional model of the variational equation integration approach to absorb this type of noise contribution. Simultaneously, the prior variances of observed orbits and K-band range rates used in traditional method are re-estimated with least-squares variance component estimation (LS-VCE) after considering these stochastic parameters. To improve the computing efficiency, a modified method of the calculation of sensitivity matrices related to the introduced stochastic parameters is proposed. Compared to the method of variation of constants widely used in the precise orbit determination and gravity field recovery, the modified method decreases the computational time of these matrices by about four times. Furthermore, an efficient LS-VCE algorithm is derived in a more generalized case. The efficient algorithm only costs 1 per cent of the time of the unoptimized method. With the GRACE data, we analysed the benefits of these refinements in gravity field recovery, and the results show that these improvements can mitigate the impacts of errors in background force models and accelerometer data on recovered gravity field models, especially in the high-degree signals. Furthermore, the quality of results has less dependence on parametrization.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2024-02-26\",\"journal\":\"Geophysical Journal International\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Yu\"],\"firstnames\":[\"Biao\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"You\"],\"firstnames\":[\"Wei\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Fan\"],\"firstnames\":[\"Dongming\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Su\"],\"firstnames\":[\"Yong\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhang\"],\"firstnames\":[\"Jiahui\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2023\",\"pages\":\"516–536\",\"bibtex\":\"@article{yu_detailed_2023,\\n\\ttitle = {A detailed analysis of stochastic models applied to temporal gravity field recovery with {GRACE} observations},\\n\\tvolume = {236},\\n\\tissn = {0956-540X, 1365-246X},\\n\\turl = {https://academic.oup.com/gji/article/236/1/516/7382201},\\n\\tdoi = {10.1093/gji/ggad441},\\n\\tabstract = {SUMMARY\\n            In this study, we analysed the impacts of errors in background force models and observed non-gravitational forces on the pseudo-observations (pre-fits) during gravity field recovery based on the Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission. To reduce these effects, we introduced the stochastic parameters into the functional model of the variational equation integration approach to absorb this type of noise contribution. Simultaneously, the prior variances of observed orbits and K-band range rates used in traditional method are re-estimated with least-squares variance component estimation (LS-VCE) after considering these stochastic parameters. To improve the computing efficiency, a modified method of the calculation of sensitivity matrices related to the introduced stochastic parameters is proposed. Compared to the method of variation of constants widely used in the precise orbit determination and gravity field recovery, the modified method decreases the computational time of these matrices by about four times. Furthermore, an efficient LS-VCE algorithm is derived in a more generalized case. The efficient algorithm only costs 1 per cent of the time of the unoptimized method. With the GRACE data, we analysed the benefits of these refinements in gravity field recovery, and the results show that these improvements can mitigate the impacts of errors in background force models and accelerometer data on recovered gravity field models, especially in the high-degree signals. Furthermore, the quality of results has less dependence on parametrization.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2024-02-26},\\n\\tjournal = {Geophysical Journal International},\\n\\tauthor = {Yu, Biao and You, Wei and Kusche, Jürgen and Fan, Dongming and Su, Yong and Zhang, Jiahui},\\n\\tmonth = nov,\\n\\tyear = {2023},\\n\\tpages = {516--536},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Yu, B.\",\"You, W.\",\"Kusche, J.\",\"Fan, D.\",\"Su, Y.\",\"Zhang, J.\"],\"key\":\"yu_detailed_2023\",\"id\":\"yu_detailed_2023\",\"bibbaseid\":\"yu-you-kusche-fan-su-zhang-adetailedanalysisofstochasticmodelsappliedtotemporalgravityfieldrecoverywithgraceobservations-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://academic.oup.com/gji/article/236/1/516/7382201\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Combining root and soil hydraulics in macroscopic representations of root water uptake\",\"issn\":\"1539-1663, 1539-1663\",\"url\":\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273\",\"doi\":\"10.1002/vzj2.20273\",\"abstract\":\"Abstract Plant water uptake and plant and soil water status are important for the soil water balance and plant growth. They depend on atmospheric water demand and the accessibility of soil water to plant roots, which is in turn related to the hydraulic properties of the root system and the soil around root segments. We present a simulation model that describes water flow in the soil–plant system mechanistically considering both root and soil hydraulic properties. We developed an approach to upscale three‐dimensional (3D) flow in the soil toward root segments of a 3D root architecture to a model that considers one‐dimensional flow between horizontal soil layers and radial flow to root segments in that layer. The upscaled model couples upscaled linear flow equations in the root system with an analytical solution of the nonlinear radial flow equation between the soil and roots. The upscaled model avoids simplifying assumptions about root hydraulic properties and water potential drops near roots made in, respectively, soil‐ and root‐centered models. Xylem water potentials and soil–root interface potentials are explicitly simulated and show, respectively, large variations with depth and large deviations from bulk soil water potentials under dry soil conditions. Accounting for hydraulic gradients in the soil around root segments led to an earlier but slower reduction of transpiration during a drought period and a better plant water status with higher nighttime plant water potentials. , Core Ideas Root water uptake depends on root and soil hydraulic properties. Water uptake at root element scale was upscaled to the root system scale. The upscaled model can be implemented in one‐dimensional soil water flow models. Low conductance of dry soil prevents low nighttime plant water potentials.\",\"language\":\"en\",\"urldate\":\"2024-01-29\",\"journal\":\"Vadose Zone Journal\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Vanderborght\"],\"firstnames\":[\"Jan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Leitner\"],\"firstnames\":[\"Daniel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schnepf\"],\"firstnames\":[\"Andrea\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Couvreur\"],\"firstnames\":[\"Valentin\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Javaux\"],\"firstnames\":[\"Mathieu\"],\"suffixes\":[]}],\"month\":\"July\",\"year\":\"2023\",\"pages\":\"e20273\",\"bibtex\":\"@article{vanderborght_combining_2023,\\n\\ttitle = {Combining root and soil hydraulics in macroscopic representations of root water uptake},\\n\\tissn = {1539-1663, 1539-1663},\\n\\turl = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273},\\n\\tdoi = {10.1002/vzj2.20273},\\n\\tabstract = {Abstract\\n            Plant water uptake and plant and soil water status are important for the soil water balance and plant growth. They depend on atmospheric water demand and the accessibility of soil water to plant roots, which is in turn related to the hydraulic properties of the root system and the soil around root segments. We present a simulation model that describes water flow in the soil–plant system mechanistically considering both root and soil hydraulic properties. We developed an approach to upscale three‐dimensional (3D) flow in the soil toward root segments of a 3D root architecture to a model that considers one‐dimensional flow between horizontal soil layers and radial flow to root segments in that layer. The upscaled model couples upscaled linear flow equations in the root system with an analytical solution of the nonlinear radial flow equation between the soil and roots. The upscaled model avoids simplifying assumptions about root hydraulic properties and water potential drops near roots made in, respectively, soil‐ and root‐centered models. Xylem water potentials and soil–root interface potentials are explicitly simulated and show, respectively, large variations with depth and large deviations from bulk soil water potentials under dry soil conditions. Accounting for hydraulic gradients in the soil around root segments led to an earlier but slower reduction of transpiration during a drought period and a better plant water status with higher nighttime plant water potentials.\\n          , \\n            Core Ideas\\n            \\n              \\n                \\n                  Root water uptake depends on root and soil hydraulic properties.\\n                \\n                \\n                  Water uptake at root element scale was upscaled to the root system scale.\\n                \\n                \\n                  The upscaled model can be implemented in one‐dimensional soil water flow models.\\n                \\n                \\n                  Low conductance of dry soil prevents low nighttime plant water potentials.},\\n\\tlanguage = {en},\\n\\turldate = {2024-01-29},\\n\\tjournal = {Vadose Zone Journal},\\n\\tauthor = {Vanderborght, Jan and Leitner, Daniel and Schnepf, Andrea and Couvreur, Valentin and Vereecken, Harry and Javaux, Mathieu},\\n\\tmonth = jul,\\n\\tyear = {2023},\\n\\tpages = {e20273},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Vanderborght, J.\",\"Leitner, D.\",\"Schnepf, A.\",\"Couvreur, V.\",\"Vereecken, H.\",\"Javaux, M.\"],\"key\":\"vanderborght_combining_2023\",\"id\":\"vanderborght_combining_2023\",\"bibbaseid\":\"vanderborght-leitner-schnepf-couvreur-vereecken-javaux-combiningrootandsoilhydraulicsinmacroscopicrepresentationsofrootwateruptake-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"incollection\",\"type\":\"incollection\",\"address\":\"Cham\",\"title\":\"Probabilistic Biomass Estimation with Conditional Generative Adversarial Networks\",\"volume\":\"13485\",\"isbn\":\"978-3-031-16787-4 978-3-031-16788-1\",\"url\":\"https://link.springer.com/10.1007/978-3-031-16788-1_29\",\"language\":\"en\",\"urldate\":\"2023-11-27\",\"booktitle\":\"Pattern Recognition\",\"publisher\":\"Springer International Publishing\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Leonhardt\"],\"firstnames\":[\"Johannes\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Drees\"],\"firstnames\":[\"Lukas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Jung\"],\"firstnames\":[\"Peter\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Roscher\"],\"firstnames\":[\"Ribana\"],\"suffixes\":[]}],\"editor\":[{\"propositions\":[],\"lastnames\":[\"Andres\"],\"firstnames\":[\"Björn\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bernard\"],\"firstnames\":[\"Florian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Cremers\"],\"firstnames\":[\"Daniel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Frintrop\"],\"firstnames\":[\"Simone\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Goldlücke\"],\"firstnames\":[\"Bastian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ihrke\"],\"firstnames\":[\"Ivo\"],\"suffixes\":[]}],\"year\":\"2022\",\"doi\":\"10.1007/978-3-031-16788-1_29\",\"note\":\"Series Title: Lecture Notes in Computer Science\",\"pages\":\"479–494\",\"bibtex\":\"@incollection{andres_probabilistic_2022,\\n\\taddress = {Cham},\\n\\ttitle = {Probabilistic {Biomass} {Estimation} with {Conditional} {Generative} {Adversarial} {Networks}},\\n\\tvolume = {13485},\\n\\tisbn = {978-3-031-16787-4 978-3-031-16788-1},\\n\\turl = {https://link.springer.com/10.1007/978-3-031-16788-1_29},\\n\\tlanguage = {en},\\n\\turldate = {2023-11-27},\\n\\tbooktitle = {Pattern {Recognition}},\\n\\tpublisher = {Springer International Publishing},\\n\\tauthor = {Leonhardt, Johannes and Drees, Lukas and Jung, Peter and Roscher, Ribana},\\n\\teditor = {Andres, Björn and Bernard, Florian and Cremers, Daniel and Frintrop, Simone and Goldlücke, Bastian and Ihrke, Ivo},\\n\\tyear = {2022},\\n\\tdoi = {10.1007/978-3-031-16788-1_29},\\n\\tnote = {Series Title: Lecture Notes in Computer Science},\\n\\tpages = {479--494},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Leonhardt, J.\",\"Drees, L.\",\"Jung, P.\",\"Roscher, R.\"],\"editor_short\":[\"Andres, B.\",\"Bernard, F.\",\"Cremers, D.\",\"Frintrop, S.\",\"Goldlücke, B.\",\"Ihrke, I.\"],\"key\":\"andres_probabilistic_2022\",\"id\":\"andres_probabilistic_2022\",\"bibbaseid\":\"leonhardt-drees-jung-roscher-probabilisticbiomassestimationwithconditionalgenerativeadversarialnetworks-2022\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://link.springer.com/10.1007/978-3-031-16788-1_29\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"incollection\",\"type\":\"incollection\",\"title\":\"Organic soils\",\"isbn\":\"978-0-323-95133-3\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732\",\"language\":\"en\",\"urldate\":\"2023-11-27\",\"booktitle\":\"Encyclopedia of Soils in the Environment\",\"publisher\":\"Elsevier\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Schimmel\"],\"firstnames\":[\"Heike\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Amelung\"],\"firstnames\":[\"Wulf\"],\"suffixes\":[]}],\"year\":\"2023\",\"doi\":\"10.1016/B978-0-12-822974-3.00073-2\",\"pages\":\"383–397\",\"bibtex\":\"@incollection{schimmel_organic_2023,\\n\\ttitle = {Organic soils},\\n\\tisbn = {978-0-323-95133-3},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732},\\n\\tlanguage = {en},\\n\\turldate = {2023-11-27},\\n\\tbooktitle = {Encyclopedia of {Soils} in the {Environment}},\\n\\tpublisher = {Elsevier},\\n\\tauthor = {Schimmel, Heike and Amelung, Wulf},\\n\\tyear = {2023},\\n\\tdoi = {10.1016/B978-0-12-822974-3.00073-2},\\n\\tpages = {383--397},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Schimmel, H.\",\"Amelung, W.\"],\"key\":\"schimmel_organic_2023\",\"id\":\"schimmel_organic_2023\",\"bibbaseid\":\"schimmel-amelung-organicsoils-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Evaluation of Sentinel-3A altimetry over Songhua river Basin\",\"volume\":\"618\",\"issn\":\"00221694\",\"url\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397\",\"doi\":\"10.1016/j.jhydrol.2023.129197\",\"language\":\"en\",\"urldate\":\"2023-10-31\",\"journal\":\"Journal of Hydrology\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Chen\"],\"firstnames\":[\"Jiaming\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Fenoglio\"],\"firstnames\":[\"Luciana\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Liao\"],\"firstnames\":[\"Jingjuan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Uyanik\"],\"firstnames\":[\"Hakan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Nadzir\"],\"firstnames\":[\"Zulfikar\",\"Adlan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lou\"],\"firstnames\":[\"Yanhan\"],\"suffixes\":[]}],\"month\":\"March\",\"year\":\"2023\",\"pages\":\"129197\",\"bibtex\":\"@article{chen_evaluation_2023,\\n\\ttitle = {Evaluation of {Sentinel}-{3A} altimetry over {Songhua} river {Basin}},\\n\\tvolume = {618},\\n\\tissn = {00221694},\\n\\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397},\\n\\tdoi = {10.1016/j.jhydrol.2023.129197},\\n\\tlanguage = {en},\\n\\turldate = {2023-10-31},\\n\\tjournal = {Journal of Hydrology},\\n\\tauthor = {Chen, Jiaming and Fenoglio, Luciana and Kusche, Jürgen and Liao, Jingjuan and Uyanik, Hakan and Nadzir, Zulfikar Adlan and Lou, Yanhan},\\n\\tmonth = mar,\\n\\tyear = {2023},\\n\\tpages = {129197},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Chen, J.\",\"Fenoglio, L.\",\"Kusche, J.\",\"Liao, J.\",\"Uyanik, H.\",\"Nadzir, Z. A.\",\"Lou, Y.\"],\"key\":\"chen_evaluation_2023\",\"id\":\"chen_evaluation_2023\",\"bibbaseid\":\"chen-fenoglio-kusche-liao-uyanik-nadzir-lou-evaluationofsentinel3aaltimetryoversonghuariverbasin-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Veränderungen der Wasserspeicherung in Deutschland seit 2002 aus Beobachtungen der Satellitengravimetrie – Water storage changes in Germany since 2002 from satellite gravity observations\",\"issn\":\"1439-1783\",\"url\":\"https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf\",\"doi\":\"10.5675/HYWA_2023.2_1\",\"urldate\":\"2023-10-30\",\"journal\":\"Hydrologie und Wasserbewirtschaftung\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Güntner\"],\"firstnames\":[\"Andreas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gerdener\"],\"firstnames\":[\"Helena\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Boergens\"],\"firstnames\":[\"Eva\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kollet\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Dobslaw\"],\"firstnames\":[\"Henryk\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hartick\"],\"firstnames\":[\"Carl\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Sharifi\"],\"firstnames\":[\"Ehsan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Flechtner\"],\"firstnames\":[\"Frank\"],\"suffixes\":[]}],\"year\":\"2023\",\"note\":\"Publisher: Bundesanstalt für Gewässerkunde, Koblenz\",\"bibtex\":\"@article{guntner_veranderungen_2023,\\n\\ttitle = {Veränderungen der {Wasserspeicherung} in {Deutschland} seit 2002 aus {Beobachtungen} der {Satellitengravimetrie} – {Water} storage changes in {Germany} since 2002 from satellite gravity observations},\\n\\tissn = {1439-1783},\\n\\turl = {https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf},\\n\\tdoi = {10.5675/HYWA_2023.2_1},\\n\\turldate = {2023-10-30},\\n\\tjournal = {Hydrologie und Wasserbewirtschaftung},\\n\\tauthor = {Güntner, Andreas and Gerdener, Helena and Boergens, Eva and Kusche, Jürgen and Kollet, Stefan and Dobslaw, Henryk and Hartick, Carl and Sharifi, Ehsan and Flechtner, Frank},\\n\\tyear = {2023},\\n\\tnote = {Publisher: Bundesanstalt für Gewässerkunde, Koblenz},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Güntner, A.\",\"Gerdener, H.\",\"Boergens, E.\",\"Kusche, J.\",\"Kollet, S.\",\"Dobslaw, H.\",\"Hartick, C.\",\"Sharifi, E.\",\"Flechtner, F.\"],\"key\":\"guntner_veranderungen_2023\",\"id\":\"guntner_veranderungen_2023\",\"bibbaseid\":\"gntner-gerdener-boergens-kusche-kollet-dobslaw-hartick-sharifi-etal-vernderungenderwasserspeicherungindeutschlandseit2002ausbeobachtungendersatellitengravimetriewaterstoragechangesingermanysince2002fromsatellitegravityobservations-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"SIMPLACE—a versatile modelling and simulation framework for sustainable crops and agroecosystems\",\"volume\":\"5\",\"issn\":\"2517-5025\",\"url\":\"https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223\",\"doi\":\"10.1093/insilicoplants/diad006\",\"abstract\":\"Abstract Agricultural system analysis has considerably evolved over the last years, allowing scientists to quantify complex interactions in crops and agroecosystems. Computer-based models have become a central tool for such analysis, using formulated mathematical representations (algorithms) of different biophysical processes to simulate complex system’s behaviour. Nevertheless, the current large variety of algorithms in combination with nonstandardization in their use limits rapid and rigorous model improvement and testing. This is particularly important because contextualization is a key aspect used to formulate the appropriate model structure for a specific research question, framing a clear demand for ‘next generation’ models being modular and flexible. This paper aims to describe the Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE), which has been developed over the last decade to address the various aforementioned issues and support appropriate model formulations and interoperability. We describe its main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems with high flexibility, performance and transparency. A brief review of exemplary applications of SIMPLACE is provided covering the different topics, crops and cropping systems, spatial scales and geographies. We stress that standardized documentation of modules, variables ontology and data archives are key requirements to maintain and assist model development and reproducibility. The increasing demand for more complex, diversified and integrated production systems (e.g. intercropping, livestock-grazing, agroforestry) and the associated impacts on sustainable food systems also require the strong collaboration of a multidisciplinary community of modellers and stakeholders.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2023-10-30\",\"journal\":\"in silico Plants\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Enders\"],\"firstnames\":[\"Andreas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vianna\"],\"firstnames\":[\"Murilo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gaiser\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Krauss\"],\"firstnames\":[\"Gunther\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Webber\"],\"firstnames\":[\"Heidi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Srivastava\"],\"firstnames\":[\"Amit\",\"Kumar\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Seidel\"],\"firstnames\":[\"Sabine\",\"Julia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Tewes\"],\"firstnames\":[\"Andreas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Rezaei\"],\"firstnames\":[\"Ehsan\",\"Eyshi\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ewert\"],\"firstnames\":[\"Frank\"],\"suffixes\":[]}],\"editor\":[{\"propositions\":[],\"lastnames\":[\"Marshall-Colon\"],\"firstnames\":[\"Amy\"],\"suffixes\":[]}],\"month\":\"January\",\"year\":\"2023\",\"pages\":\"diad006\",\"bibtex\":\"@article{enders_simplaceversatile_2023,\\n\\ttitle = {{SIMPLACE}—a versatile modelling and simulation framework for sustainable crops and agroecosystems},\\n\\tvolume = {5},\\n\\tissn = {2517-5025},\\n\\turl = {https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223},\\n\\tdoi = {10.1093/insilicoplants/diad006},\\n\\tabstract = {Abstract\\n            Agricultural system analysis has considerably evolved over the last years, allowing scientists to quantify complex interactions in crops and agroecosystems. Computer-based models have become a central tool for such analysis, using formulated mathematical representations (algorithms) of different biophysical processes to simulate complex system’s behaviour. Nevertheless, the current large variety of algorithms in combination with nonstandardization in their use limits rapid and rigorous model improvement and testing. This is particularly important because contextualization is a key aspect used to formulate the appropriate model structure for a specific research question, framing a clear demand for ‘next generation’ models being modular and flexible. This paper aims to describe the Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE), which has been developed over the last decade to address the various aforementioned issues and support appropriate model formulations and interoperability. We describe its main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems with high flexibility, performance and transparency. A brief review of exemplary applications of SIMPLACE is provided covering the different topics, crops and cropping systems, spatial scales and geographies. We stress that standardized documentation of modules, variables ontology and data archives are key requirements to maintain and assist model development and reproducibility. The increasing demand for more complex, diversified and integrated production systems (e.g. intercropping, livestock-grazing, agroforestry) and the associated impacts on sustainable food systems also require the strong collaboration of a multidisciplinary community of modellers and stakeholders.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2023-10-30},\\n\\tjournal = {in silico Plants},\\n\\tauthor = {Enders, Andreas and Vianna, Murilo and Gaiser, Thomas and Krauss, Gunther and Webber, Heidi and Srivastava, Amit Kumar and Seidel, Sabine Julia and Tewes, Andreas and Rezaei, Ehsan Eyshi and Ewert, Frank},\\n\\teditor = {Marshall-Colon, Amy},\\n\\tmonth = jan,\\n\\tyear = {2023},\\n\\tpages = {diad006},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Enders, A.\",\"Vianna, M.\",\"Gaiser, T.\",\"Krauss, G.\",\"Webber, H.\",\"Srivastava, A. K.\",\"Seidel, S. J.\",\"Tewes, A.\",\"Rezaei, E. E.\",\"Ewert, F.\"],\"editor_short\":[\"Marshall-Colon, A.\"],\"key\":\"enders_simplaceversatile_2023\",\"id\":\"enders_simplaceversatile_2023\",\"bibbaseid\":\"enders-vianna-gaiser-krauss-webber-srivastava-seidel-tewes-etal-simplaceaversatilemodellingandsimulationframeworkforsustainablecropsandagroecosystems-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects\",\"volume\":\"4\",\"issn\":\"2662-4435\",\"url\":\"https://www.nature.com/articles/s43247-023-00958-4\",\"doi\":\"10.1038/s43247-023-00958-4\",\"abstract\":\"Abstract Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2023-10-30\",\"journal\":\"Communications Earth & Environment\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Graf\"],\"firstnames\":[\"Alexander\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Wohlfahrt\"],\"firstnames\":[\"Georg\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Aranda-Barranco\"],\"firstnames\":[\"Sergio\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Arriga\"],\"firstnames\":[\"Nicola\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Brümmer\"],\"firstnames\":[\"Christian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ceschia\"],\"firstnames\":[\"Eric\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ciais\"],\"firstnames\":[\"Philippe\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Desai\"],\"firstnames\":[\"Ankur\",\"R.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Di\",\"Lonardo\"],\"firstnames\":[\"Sara\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gharun\"],\"firstnames\":[\"Mana\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Grünwald\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hörtnagl\"],\"firstnames\":[\"Lukas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kasak\"],\"firstnames\":[\"Kuno\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Klosterhalfen\"],\"firstnames\":[\"Anne\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Knohl\"],\"firstnames\":[\"Alexander\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kowalska\"],\"firstnames\":[\"Natalia\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Leuchner\"],\"firstnames\":[\"Michael\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lindroth\"],\"firstnames\":[\"Anders\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Mauder\"],\"firstnames\":[\"Matthias\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Migliavacca\"],\"firstnames\":[\"Mirco\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Morel\"],\"firstnames\":[\"Alexandra\",\"C.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Pfennig\"],\"firstnames\":[\"Andreas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Poorter\"],\"firstnames\":[\"Hendrik\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Terán\"],\"firstnames\":[\"Christian\",\"Poppe\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Reitz\"],\"firstnames\":[\"Oliver\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Rebmann\"],\"firstnames\":[\"Corinna\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Sanchez-Azofeifa\"],\"firstnames\":[\"Arturo\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schmidt\"],\"firstnames\":[\"Marius\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Šigut\"],\"firstnames\":[\"Ladislav\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Tomelleri\"],\"firstnames\":[\"Enrico\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Yu\"],\"firstnames\":[\"Ke\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Varlagin\"],\"firstnames\":[\"Andrej\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]}],\"month\":\"August\",\"year\":\"2023\",\"pages\":\"298\",\"bibtex\":\"@article{graf_joint_2023,\\n\\ttitle = {Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects},\\n\\tvolume = {4},\\n\\tissn = {2662-4435},\\n\\turl = {https://www.nature.com/articles/s43247-023-00958-4},\\n\\tdoi = {10.1038/s43247-023-00958-4},\\n\\tabstract = {Abstract\\n            Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2023-10-30},\\n\\tjournal = {Communications Earth \\\\& Environment},\\n\\tauthor = {Graf, Alexander and Wohlfahrt, Georg and Aranda-Barranco, Sergio and Arriga, Nicola and Brümmer, Christian and Ceschia, Eric and Ciais, Philippe and Desai, Ankur R. and Di Lonardo, Sara and Gharun, Mana and Grünwald, Thomas and Hörtnagl, Lukas and Kasak, Kuno and Klosterhalfen, Anne and Knohl, Alexander and Kowalska, Natalia and Leuchner, Michael and Lindroth, Anders and Mauder, Matthias and Migliavacca, Mirco and Morel, Alexandra C. and Pfennig, Andreas and Poorter, Hendrik and Terán, Christian Poppe and Reitz, Oliver and Rebmann, Corinna and Sanchez-Azofeifa, Arturo and Schmidt, Marius and Šigut, Ladislav and Tomelleri, Enrico and Yu, Ke and Varlagin, Andrej and Vereecken, Harry},\\n\\tmonth = aug,\\n\\tyear = {2023},\\n\\tpages = {298},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Graf, A.\",\"Wohlfahrt, G.\",\"Aranda-Barranco, S.\",\"Arriga, N.\",\"Brümmer, C.\",\"Ceschia, E.\",\"Ciais, P.\",\"Desai, A. R.\",\"Di Lonardo, S.\",\"Gharun, M.\",\"Grünwald, T.\",\"Hörtnagl, L.\",\"Kasak, K.\",\"Klosterhalfen, A.\",\"Knohl, A.\",\"Kowalska, N.\",\"Leuchner, M.\",\"Lindroth, A.\",\"Mauder, M.\",\"Migliavacca, M.\",\"Morel, A. C.\",\"Pfennig, A.\",\"Poorter, H.\",\"Terán, C. P.\",\"Reitz, O.\",\"Rebmann, C.\",\"Sanchez-Azofeifa, A.\",\"Schmidt, M.\",\"Šigut, L.\",\"Tomelleri, E.\",\"Yu, K.\",\"Varlagin, A.\",\"Vereecken, H.\"],\"key\":\"graf_joint_2023\",\"id\":\"graf_joint_2023\",\"bibbaseid\":\"graf-wohlfahrt-arandabarranco-arriga-brmmer-ceschia-ciais-desai-etal-jointoptimizationoflandcarbonuptakeandalbedocanhelpachievemoderateinstantaneousandlongtermcoolingeffects-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s43247-023-00958-4\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Water table depth assimilation in integrated terrestrial system models at the larger catchment scale\",\"volume\":\"5\",\"issn\":\"2624-9375\",\"url\":\"https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full\",\"doi\":\"10.3389/frwa.2023.1150999\",\"abstract\":\"As an important source of water for human beings, groundwater plays a significant role in human production and life. However, different sources of uncertainty may lead to unsatisfactory simulations of groundwater hydrodynamics with hydrological models. The goal of this study is to investigate the impact of assimilating groundwater data into the Terrestrial System Modeling Platform (TSMP) for improving hydrological modeling in a real-world case. Daily groundwater table depth (WTD) measurements from the year 2018 for the Rur catchment in Germany were assimilated by the Localized Ensemble Kalman Filter (LEnKF) into TSMP. The LEnKF is used with a localization radius so that the assimilated measurements only update model states in a limited radius around the measurements, in order to avoid unphysical updates related to spurious correlations. Due to the mismatch between groundwater measurements and the coarse model resolution (500 m), the measurements need careful screening before data assimilation (DA). Based on the spatial autocorrelation of the WTD deduced from the measurements, three different filter localization radii (2.5, 5, and 10 km) were evaluated for assimilation. The bias in the simulated water table and the root mean square error (RMSE) are reduced after DA, compared with runs without DA [i.e., open loop (OL) runs]. The best results at the assimilated locations are obtained for a localization radius of 10 km, with an 81% reduction of RMSE at the measurement locations, and slightly smaller RMSE reductions for the 5 and 2.5 km radius. The validation with independent WTD data showed the best results for a localization radius of 10 km, but groundwater table characterization could only be improved for sites &lt;2.5 km from measurement locations. In case of a localization radius of 10 km the RMSE-reduction was 30% for those nearby sites. Simulated soil moisture was validated against soil moisture measured by cosmic-ray neutron sensors (CRNS), but no RMSE reduction was observed for DA-runs compared to OL-run. However, in both cases, the correlation between measured and simulated soil moisture content was high (between 0.70 and 0.89, except for the Wuestebach site).\",\"urldate\":\"2023-10-30\",\"journal\":\"Frontiers in Water\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Li\"],\"firstnames\":[\"Fang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kurtz\"],\"firstnames\":[\"Wolfgang\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hung\"],\"firstnames\":[\"Ching\",\"Pui\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Hendricks\",\"Franssen\"],\"firstnames\":[\"Harrie-Jan\"],\"suffixes\":[]}],\"month\":\"March\",\"year\":\"2023\",\"pages\":\"1150999\",\"bibtex\":\"@article{li_water_2023,\\n\\ttitle = {Water table depth assimilation in integrated terrestrial system models at the larger catchment scale},\\n\\tvolume = {5},\\n\\tissn = {2624-9375},\\n\\turl = {https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full},\\n\\tdoi = {10.3389/frwa.2023.1150999},\\n\\tabstract = {As an important source of water for human beings, groundwater plays a significant role in human production and life. However, different sources of uncertainty may lead to unsatisfactory simulations of groundwater hydrodynamics with hydrological models. The goal of this study is to investigate the impact of assimilating groundwater data into the Terrestrial System Modeling Platform (TSMP) for improving hydrological modeling in a real-world case. Daily groundwater table depth (WTD) measurements from the year 2018 for the Rur catchment in Germany were assimilated by the Localized Ensemble Kalman Filter (LEnKF) into TSMP. The LEnKF is used with a localization radius so that the assimilated measurements only update model states in a limited radius around the measurements, in order to avoid unphysical updates related to spurious correlations. Due to the mismatch between groundwater measurements and the coarse model resolution (500 m), the measurements need careful screening before data assimilation (DA). Based on the spatial autocorrelation of the WTD deduced from the measurements, three different filter localization radii (2.5, 5, and 10 km) were evaluated for assimilation. The bias in the simulated water table and the root mean square error (RMSE) are reduced after DA, compared with runs without DA [i.e., open loop (OL) runs]. The best results at the assimilated locations are obtained for a localization radius of 10 km, with an 81\\\\% reduction of RMSE at the measurement locations, and slightly smaller RMSE reductions for the 5 and 2.5 km radius. The validation with independent WTD data showed the best results for a localization radius of 10 km, but groundwater table characterization could only be improved for sites \\\\&lt;2.5 km from measurement locations. In case of a localization radius of 10 km the RMSE-reduction was 30\\\\% for those nearby sites. Simulated soil moisture was validated against soil moisture measured by cosmic-ray neutron sensors (CRNS), but no RMSE reduction was observed for DA-runs compared to OL-run. However, in both cases, the correlation between measured and simulated soil moisture content was high (between 0.70 and 0.89, except for the Wuestebach site).},\\n\\turldate = {2023-10-30},\\n\\tjournal = {Frontiers in Water},\\n\\tauthor = {Li, Fang and Kurtz, Wolfgang and Hung, Ching Pui and Vereecken, Harry and Hendricks Franssen, Harrie-Jan},\\n\\tmonth = mar,\\n\\tyear = {2023},\\n\\tpages = {1150999},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Li, F.\",\"Kurtz, W.\",\"Hung, C. P.\",\"Vereecken, H.\",\"Hendricks Franssen, H.\"],\"key\":\"li_water_2023\",\"id\":\"li_water_2023\",\"bibbaseid\":\"li-kurtz-hung-vereecken-hendricksfranssen-watertabledepthassimilationinintegratedterrestrialsystemmodelsatthelargercatchmentscale-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full\"},\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Wildfire precursors show complementary predictability in different timescales\",\"volume\":\"14\",\"issn\":\"2041-1723\",\"url\":\"https://www.nature.com/articles/s41467-023-42597-5\",\"doi\":\"10.1038/s41467-023-42597-5\",\"abstract\":\"Abstract In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3% and 26.7% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.\",\"language\":\"en\",\"number\":\"1\",\"urldate\":\"2023-10-30\",\"journal\":\"Nature Communications\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Qu\"],\"firstnames\":[\"Yuquan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Miralles\"],\"firstnames\":[\"Diego\",\"G.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Veraverbeke\"],\"firstnames\":[\"Sander\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Montzka\"],\"firstnames\":[\"Carsten\"],\"suffixes\":[]}],\"month\":\"October\",\"year\":\"2023\",\"pages\":\"6829\",\"bibtex\":\"@article{qu_wildfire_2023,\\n\\ttitle = {Wildfire precursors show complementary predictability in different timescales},\\n\\tvolume = {14},\\n\\tissn = {2041-1723},\\n\\turl = {https://www.nature.com/articles/s41467-023-42597-5},\\n\\tdoi = {10.1038/s41467-023-42597-5},\\n\\tabstract = {Abstract\\n            In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3\\\\% and 26.7\\\\% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.},\\n\\tlanguage = {en},\\n\\tnumber = {1},\\n\\turldate = {2023-10-30},\\n\\tjournal = {Nature Communications},\\n\\tauthor = {Qu, Yuquan and Miralles, Diego G. and Veraverbeke, Sander and Vereecken, Harry and Montzka, Carsten},\\n\\tmonth = oct,\\n\\tyear = {2023},\\n\\tpages = {6829},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Qu, Y.\",\"Miralles, D. G.\",\"Veraverbeke, S.\",\"Vereecken, H.\",\"Montzka, C.\"],\"key\":\"qu_wildfire_2023\",\"id\":\"qu_wildfire_2023\",\"bibbaseid\":\"qu-miralles-veraverbeke-vereecken-montzka-wildfireprecursorsshowcomplementarypredictabilityindifferenttimescales-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s41467-023-42597-5\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"The synergies of SMAP enhanced and MODIS products in a random forest regression for estimating 1 km soil moisture over Africa using Google Earth Engine\",\"issn\":\"2096-4471, 2574-5417\",\"url\":\"https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905\",\"doi\":\"10.1080/20964471.2023.2257905\",\"language\":\"en\",\"urldate\":\"2023-10-30\",\"journal\":\"Big Earth Data\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Mohseni\"],\"firstnames\":[\"Farzane\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ahrari\"],\"firstnames\":[\"Amirhossein\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Haunert\"],\"firstnames\":[\"Jan-Henrik\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Montzka\"],\"firstnames\":[\"Carsten\"],\"suffixes\":[]}],\"month\":\"September\",\"year\":\"2023\",\"pages\":\"1–25\",\"bibtex\":\"@article{mohseni_synergies_2023,\\n\\ttitle = {The synergies of {SMAP} enhanced and {MODIS} products in a random forest regression for estimating 1 km soil moisture over {Africa} using {Google} {Earth} {Engine}},\\n\\tissn = {2096-4471, 2574-5417},\\n\\turl = {https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905},\\n\\tdoi = {10.1080/20964471.2023.2257905},\\n\\tlanguage = {en},\\n\\turldate = {2023-10-30},\\n\\tjournal = {Big Earth Data},\\n\\tauthor = {Mohseni, Farzane and Ahrari, Amirhossein and Haunert, Jan-Henrik and Montzka, Carsten},\\n\\tmonth = sep,\\n\\tyear = {2023},\\n\\tpages = {1--25},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Mohseni, F.\",\"Ahrari, A.\",\"Haunert, J.\",\"Montzka, C.\"],\"key\":\"mohseni_synergies_2023\",\"id\":\"mohseni_synergies_2023\",\"bibbaseid\":\"mohseni-ahrari-haunert-montzka-thesynergiesofsmapenhancedandmodisproductsinarandomforestregressionforestimating1kmsoilmoistureoverafricausinggoogleearthengine-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Introducing the Idea of Classifying Sets of Permanent GNSS Stations as Benchmarks for Hydrogeodesy\",\"volume\":\"128\",\"issn\":\"2169-9313, 2169-9356\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988\",\"doi\":\"10.1029/2023JB026988\",\"abstract\":\"Abstract We propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal‐scales: short‐term, seasonal and long‐term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998–2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre‐defined temporal‐scales of short‐term, seasonal and long‐term, using non‐parametric wavelet analysis. For each temporal‐scale, correlation coefficients are computed between GNSS‐measured and GRACE‐derived/GLWS‐predicted displacements. We present the benefits of applying high‐resolution GRACE‐assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15% for short‐term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake‐affected sites and those where a possible poroelastic response is observed. , Plain Language Summary Displacements of the Earth's crust measured by permanent Global Navigation Satellite System (GNSS) ground stations are used for many geophysical interpretations. However, it is common to omit the evaluation of the sensitivity of the system to the measurement of displacements from different sources, assuming in advance 100% sensitivity of the system to a given effect. Consequently, the fact that at a given station several effects can be recorded simultaneously is overlooked. This is particularly evident in earthquake‐affected areas, where GNSS stations are excluded from most analyses of non‐tectonic effects. We solve this problem and propose to divide GNSS stations into trusted sets, which we call benchmarks. Benchmarking is performed by indicating the stations that are certain to register a given effect in three pre‐defined temporal‐scales: short‐term, seasonal and long‐term. We present the analysis for the Amazon area, known for its large hydrosphere‐related signal, and demonstrate that the benchmarking allows for the inclusion of GNSS stations that were previously omitted in analyses of this type. , Key Points Displacements measured by Global Positioning System (GPS) correlate well with surface water levels derived from radar altimetry missions Trusted sets of GPS stations are classified at the three pre‐defined temporal‐scales: short‐term, seasonal and long‐term Benchmarking allows to include more GPS stations in hydrogeodetic analyses\",\"language\":\"en\",\"number\":\"9\",\"urldate\":\"2023-10-30\",\"journal\":\"Journal of Geophysical Research: Solid Earth\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Klos\"],\"firstnames\":[\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"J.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Leszczuk\"],\"firstnames\":[\"G.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Gerdener\"],\"firstnames\":[\"H.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schulze\"],\"firstnames\":[\"K.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lenczuk\"],\"firstnames\":[\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bogusz\"],\"firstnames\":[\"J.\"],\"suffixes\":[]}],\"month\":\"September\",\"year\":\"2023\",\"pages\":\"e2023JB026988\",\"bibtex\":\"@article{klos_introducing_2023,\\n\\ttitle = {Introducing the {Idea} of {Classifying} {Sets} of {Permanent} {GNSS} {Stations} as {Benchmarks} for {Hydrogeodesy}},\\n\\tvolume = {128},\\n\\tissn = {2169-9313, 2169-9356},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988},\\n\\tdoi = {10.1029/2023JB026988},\\n\\tabstract = {Abstract\\n            We propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal‐scales: short‐term, seasonal and long‐term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998–2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre‐defined temporal‐scales of short‐term, seasonal and long‐term, using non‐parametric wavelet analysis. For each temporal‐scale, correlation coefficients are computed between GNSS‐measured and GRACE‐derived/GLWS‐predicted displacements. We present the benefits of applying high‐resolution GRACE‐assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15\\\\% for short‐term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake‐affected sites and those where a possible poroelastic response is observed.\\n          , \\n            Plain Language Summary\\n            Displacements of the Earth's crust measured by permanent Global Navigation Satellite System (GNSS) ground stations are used for many geophysical interpretations. However, it is common to omit the evaluation of the sensitivity of the system to the measurement of displacements from different sources, assuming in advance 100\\\\% sensitivity of the system to a given effect. Consequently, the fact that at a given station several effects can be recorded simultaneously is overlooked. This is particularly evident in earthquake‐affected areas, where GNSS stations are excluded from most analyses of non‐tectonic effects. We solve this problem and propose to divide GNSS stations into trusted sets, which we call benchmarks. Benchmarking is performed by indicating the stations that are certain to register a given effect in three pre‐defined temporal‐scales: short‐term, seasonal and long‐term. We present the analysis for the Amazon area, known for its large hydrosphere‐related signal, and demonstrate that the benchmarking allows for the inclusion of GNSS stations that were previously omitted in analyses of this type.\\n          , \\n            Key Points\\n            \\n              \\n                \\n                  Displacements measured by Global Positioning System (GPS) correlate well with surface water levels derived from radar altimetry missions\\n                \\n                \\n                  Trusted sets of GPS stations are classified at the three pre‐defined temporal‐scales: short‐term, seasonal and long‐term\\n                \\n                \\n                  Benchmarking allows to include more GPS stations in hydrogeodetic analyses},\\n\\tlanguage = {en},\\n\\tnumber = {9},\\n\\turldate = {2023-10-30},\\n\\tjournal = {Journal of Geophysical Research: Solid Earth},\\n\\tauthor = {Klos, A. and Kusche, J. and Leszczuk, G. and Gerdener, H. and Schulze, K. and Lenczuk, A. and Bogusz, J.},\\n\\tmonth = sep,\\n\\tyear = {2023},\\n\\tpages = {e2023JB026988},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Klos, A.\",\"Kusche, J.\",\"Leszczuk, G.\",\"Gerdener, H.\",\"Schulze, K.\",\"Lenczuk, A.\",\"Bogusz, J.\"],\"key\":\"klos_introducing_2023\",\"id\":\"klos_introducing_2023\",\"bibbaseid\":\"klos-kusche-leszczuk-gerdener-schulze-lenczuk-bogusz-introducingtheideaofclassifyingsetsofpermanentgnssstationsasbenchmarksforhydrogeodesy-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"The global land water storage data set release 2 (GLWS2.0) derived via assimilating GRACE and GRACE-FO data into a global hydrological model\",\"volume\":\"97\",\"issn\":\"0949-7714, 1432-1394\",\"url\":\"https://link.springer.com/10.1007/s00190-023-01763-9\",\"doi\":\"10.1007/s00190-023-01763-9\",\"abstract\":\"Abstract We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5 $$\\\\textasciicircum\\\\circ $$ ∘ , covering the time frame 2003 to 2019 without gaps, and including monthly uncertainty quantification. GLWS2.0 was derived by assimilating monthly GRACE/-FO mass change maps into the WaterGAP global hydrology model via the ensemble Kalman filter, taking data and model uncertainty into account. TWSA in GLWS2.0 is then accumulated over several hydrological storage variables. In this article, we describe the methods and data sets that went into GLWS2.0, how it compares to GRACE/-FO data in terms of representing TWSA trends, seasonal signals, and extremes, as well as its validation via comparing to GNSS-derived vertical loading and its comparison with a version of the NASA Catchment Land Surface Model GRACE Data Assimilation (CLSM-DA). We find that, in the average over more than 1000 stations globally, GLWS2.0 correlates better with GNSS observations of vertical loading at short-term, seasonal, and long-term temporal bands than GRACE/-FO. While some differences exist, overall GLWS2.0 agrees reasonably well with CLSM-DA in terms of TWSA trends and annual amplitudes and phases. Highlights We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies over the global land with a spatial resolution of 0.5 $$\\\\textasciicircum\\\\circ $$ ∘ , covering the period 2003 to 2019 without gaps, and including uncertainty quantification. GLWS2.0 synthesizes monthly GRACE/-FO mass change maps with daily precipitation and radiation data via the WaterGAP model framework, taking data and model uncertainty into account. Here we describe the methods and data sets that went into GLWS2.0 and its validation from a geodetic applications perspective. We find that, in the global average, GLWS2.0 fits better than GRACE/-FO to GNSS observations of vertical loading.\",\"language\":\"en\",\"number\":\"7\",\"urldate\":\"2023-10-30\",\"journal\":\"Journal of Geodesy\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Gerdener\"],\"firstnames\":[\"Helena\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schulze\"],\"firstnames\":[\"Kerstin\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Döll\"],\"firstnames\":[\"Petra\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Klos\"],\"firstnames\":[\"Anna\"],\"suffixes\":[]}],\"month\":\"July\",\"year\":\"2023\",\"pages\":\"73\",\"bibtex\":\"@article{gerdener_global_2023,\\n\\ttitle = {The global land water storage data set release 2 ({GLWS2}.0) derived via assimilating {GRACE} and {GRACE}-{FO} data into a global hydrological model},\\n\\tvolume = {97},\\n\\tissn = {0949-7714, 1432-1394},\\n\\turl = {https://link.springer.com/10.1007/s00190-023-01763-9},\\n\\tdoi = {10.1007/s00190-023-01763-9},\\n\\tabstract = {Abstract\\n            \\n              We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5\\n              \\n                \\n                  \\\\$\\\\${\\\\textasciicircum}{\\\\textbackslash}circ \\\\$\\\\$\\n                  \\n                    \\n                      \\n                      ∘\\n                    \\n                  \\n                \\n              \\n              , covering the time frame 2003 to 2019 without gaps, and including monthly uncertainty quantification. GLWS2.0 was derived by assimilating monthly GRACE/-FO mass change maps into the WaterGAP global hydrology model via the ensemble Kalman filter, taking data and model uncertainty into account. TWSA in GLWS2.0 is then accumulated over several hydrological storage variables. In this article, we describe the methods and data sets that went into GLWS2.0, how it compares to GRACE/-FO data in terms of representing TWSA trends, seasonal signals, and extremes, as well as its validation via comparing to GNSS-derived vertical loading and its comparison with a version of the NASA Catchment Land Surface Model GRACE Data Assimilation (CLSM-DA). We find that, in the average over more than 1000 stations globally, GLWS2.0 correlates better with GNSS observations of vertical loading at short-term, seasonal, and long-term temporal bands than GRACE/-FO. While some differences exist, overall GLWS2.0 agrees reasonably well with CLSM-DA in terms of TWSA trends and annual amplitudes and phases.\\n              Highlights\\n              \\n                \\n                  \\n                    We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies over the global land with a spatial resolution of 0.5\\n                    \\n                      \\n                        \\\\$\\\\${\\\\textasciicircum}{\\\\textbackslash}circ \\\\$\\\\$\\n                        \\n                          \\n                            \\n                            ∘\\n                          \\n                        \\n                      \\n                    \\n                    , covering the period 2003 to 2019 without gaps, and including uncertainty quantification.\\n                  \\n                \\n                \\n                  GLWS2.0 synthesizes monthly GRACE/-FO mass change maps with daily precipitation and radiation data via the WaterGAP model framework, taking data and model uncertainty into account.\\n                \\n                \\n                  Here we describe the methods and data sets that went into GLWS2.0 and its validation from a geodetic applications perspective. We find that, in the global average, GLWS2.0 fits better than GRACE/-FO to GNSS observations of vertical loading.},\\n\\tlanguage = {en},\\n\\tnumber = {7},\\n\\turldate = {2023-10-30},\\n\\tjournal = {Journal of Geodesy},\\n\\tauthor = {Gerdener, Helena and Kusche, Jürgen and Schulze, Kerstin and Döll, Petra and Klos, Anna},\\n\\tmonth = jul,\\n\\tyear = {2023},\\n\\tpages = {73},\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\"author_short\":[\"Gerdener, H.\",\"Kusche, J.\",\"Schulze, K.\",\"Döll, P.\",\"Klos, A.\"],\"key\":\"gerdener_global_2023\",\"id\":\"gerdener_global_2023\",\"bibbaseid\":\"gerdener-kusche-schulze-dll-klos-thegloballandwaterstoragedatasetrelease2glws20derivedviaassimilatinggraceandgracefodataintoaglobalhydrologicalmodel-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://link.springer.com/10.1007/s00190-023-01763-9\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Soil water status shapes nutrient cycling in agroecosystems from micrometer to landscape scales\",\"volume\":\"185\",\"issn\":\"1436-8730, 1522-2624\",\"url\":\"https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357\",\"doi\":\"10.1002/jpln.202200357\",\"language\":\"en\",\"number\":\"6\",\"urldate\":\"2023-06-02\",\"journal\":\"Journal of Plant Nutrition and Soil Science\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Bauke\"],\"firstnames\":[\"Sara\",\"L.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Amelung\"],\"firstnames\":[\"Wulf\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bol\"],\"firstnames\":[\"Roland\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Brandt\"],\"firstnames\":[\"Luise\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Brüggemann\"],\"firstnames\":[\"Nicolas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kandeler\"],\"firstnames\":[\"Ellen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Meyer\"],\"firstnames\":[\"Nele\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Or\"],\"firstnames\":[\"Dani\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schnepf\"],\"firstnames\":[\"Andrea\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schloter\"],\"firstnames\":[\"Michael\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Schulz\"],\"firstnames\":[\"Stefanie\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Siebers\"],\"firstnames\":[\"Nina\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Von\",\"Sperber\"],\"firstnames\":[\"Christian\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]}],\"month\":\"December\",\"year\":\"2022\",\"pages\":\"773–792\",\"bibtex\":\"@article{bauke_soil_2022,\\n\\ttitle = {Soil water status shapes nutrient cycling in agroecosystems from micrometer to landscape scales},\\n\\tvolume = {185},\\n\\tissn = {1436-8730, 1522-2624},\\n\\turl = {https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357},\\n\\tdoi = {10.1002/jpln.202200357},\\n\\tlanguage = {en},\\n\\tnumber = {6},\\n\\turldate = {2023-06-02},\\n\\tjournal = {Journal of Plant Nutrition and Soil Science},\\n\\tauthor = {Bauke, Sara L. and Amelung, Wulf and Bol, Roland and Brandt, Luise and Brüggemann, Nicolas and Kandeler, Ellen and Meyer, Nele and Or, Dani and Schnepf, Andrea and Schloter, Michael and Schulz, Stefanie and Siebers, Nina and Von Sperber, Christian and Vereecken, Harry},\\n\\tmonth = dec,\\n\\tyear = {2022},\\n\\tpages = {773--792},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Bauke, S. L.\",\"Amelung, W.\",\"Bol, R.\",\"Brandt, L.\",\"Brüggemann, N.\",\"Kandeler, E.\",\"Meyer, N.\",\"Or, D.\",\"Schnepf, A.\",\"Schloter, M.\",\"Schulz, S.\",\"Siebers, N.\",\"Von Sperber, C.\",\"Vereecken, H.\"],\"key\":\"bauke_soil_2022\",\"id\":\"bauke_soil_2022\",\"bibbaseid\":\"bauke-amelung-bol-brandt-brggemann-kandeler-meyer-or-etal-soilwaterstatusshapesnutrientcyclinginagroecosystemsfrommicrometertolandscapescales-2022\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe\",\"volume\":\"16\",\"issn\":\"1991-9603\",\"url\":\"https://gmd.copernicus.org/articles/16/1617/2023/\",\"doi\":\"10.5194/gmd-16-1617-2023\",\"abstract\":\"Abstract. High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically based coupled land surface groundwater model, ParFlow-CLM version 3.6.0, over a pan-European model domain at 0.0275∘ (∼3 km) resolution. The model simulates a three-dimensional variably saturated groundwater-flow-solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of multiple hydrologic variables including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent (SWE), total water storage (TWS), and water table depth (WTD) resulting from a 10-year (1997–2006) model simulation was performed using in situ and remote sensing (RS) observations. Overall, the uncalibrated ParFlow-CLM model showed good agreement in simulating river discharge for 176 gauging stations across Europe (average Spearman's rank correlation (R) of 0.77). At the local scale, ParFlow-CLM model performed well for ET (R\\\\textgreater0.94) against eddy covariance observations but showed relatively large differences for SM and WTD (median R values of 0.7 and 0.50, respectively) when compared with soil moisture networks and groundwater-monitoring-well data. However, model performance varied between hydroclimate regions, with the best agreement to RS datasets being shown in semi-arid and arid regions for most variables. Conversely, the largest differences between modeled and RS datasets (e.g., for SM, SWE, and TWS) are shown in humid and cold regions. Our findings highlight the importance of including multiple variables using both local-scale and large-scale RS datasets in model evaluations for a better understanding of physically based fully distributed hydrologic model performance and uncertainties in water and energy fluxes over continental scales and across different hydroclimate regions. The large-scale, high-resolution setup also forms a basis for future studies and provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting considering the effects of lateral surface and groundwater flows.\",\"language\":\"en\",\"number\":\"6\",\"urldate\":\"2023-03-31\",\"journal\":\"Geoscientific Model Development\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Naz\"],\"firstnames\":[\"Bibi\",\"S.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Sharples\"],\"firstnames\":[\"Wendy\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Ma\"],\"firstnames\":[\"Yueling\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Goergen\"],\"firstnames\":[\"Klaus\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kollet\"],\"firstnames\":[\"Stefan\"],\"suffixes\":[]}],\"month\":\"March\",\"year\":\"2023\",\"pages\":\"1617–1639\",\"bibtex\":\"@article{naz_continental-scale_2023,\\n\\ttitle = {Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, {ParFlow}-{CLM} (v3.6.0), over {Europe}},\\n\\tvolume = {16},\\n\\tissn = {1991-9603},\\n\\turl = {https://gmd.copernicus.org/articles/16/1617/2023/},\\n\\tdoi = {10.5194/gmd-16-1617-2023},\\n\\tabstract = {Abstract. High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically based coupled land surface groundwater model, ParFlow-CLM version 3.6.0, over a pan-European model domain at 0.0275∘ (∼3 km) resolution. The model simulates a three-dimensional variably saturated groundwater-flow-solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of multiple hydrologic variables including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent (SWE), total water storage (TWS), and water table depth (WTD) resulting from a 10-year (1997–2006) model simulation was performed using in situ and remote sensing (RS) observations. Overall, the uncalibrated ParFlow-CLM model showed good agreement in simulating river discharge for 176 gauging stations across Europe (average Spearman's rank correlation (R) of 0.77). At the local scale, ParFlow-CLM model performed well for ET (R{\\\\textgreater}0.94) against eddy covariance observations but showed relatively large differences for SM and WTD (median R values of 0.7 and 0.50, respectively) when compared with soil moisture networks and groundwater-monitoring-well data. However, model performance varied between hydroclimate regions, with the best agreement to RS datasets being shown in semi-arid and arid regions for most variables. Conversely, the largest differences between modeled and RS datasets (e.g., for SM, SWE, and TWS) are shown in humid and cold regions. Our findings highlight the importance of including multiple variables using both local-scale and large-scale RS datasets in model evaluations for a better understanding of physically based fully distributed hydrologic model performance and uncertainties in water and energy fluxes over continental scales and across different hydroclimate regions. The large-scale, high-resolution setup also forms a basis for future studies and provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting considering the effects of lateral surface and groundwater flows.},\\n\\tlanguage = {en},\\n\\tnumber = {6},\\n\\turldate = {2023-03-31},\\n\\tjournal = {Geoscientific Model Development},\\n\\tauthor = {Naz, Bibi S. and Sharples, Wendy and Ma, Yueling and Goergen, Klaus and Kollet, Stefan},\\n\\tmonth = mar,\\n\\tyear = {2023},\\n\\tpages = {1617--1639},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Naz, B. S.\",\"Sharples, W.\",\"Ma, Y.\",\"Goergen, K.\",\"Kollet, S.\"],\"key\":\"naz_continental-scale_2023\",\"id\":\"naz_continental-scale_2023\",\"bibbaseid\":\"naz-sharples-ma-goergen-kollet-continentalscaleevaluationofafullydistributedcoupledlandsurfaceandgroundwatermodelparflowclmv360overeurope-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://gmd.copernicus.org/articles/16/1617/2023/\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"A review on irrigation parameterizations in Earth system models\",\"volume\":\"4\",\"issn\":\"2624-9375\",\"url\":\"https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full\",\"doi\":\"10.3389/frwa.2022.906664\",\"abstract\":\"Irrigation is the process of artificially providing water to agricultural lands in order to provide crops with the necessary water supply to ensure or foster the growth of the plants. However, its implications reach beyond the agro-economic aspect as irrigation affects the soil-land-atmosphere interactions and thus influences the water and energy cycles in the Earth system. Past studies have shown how through these interactions, an increase in soil moisture due to irrigation also affects the atmospheric state and its dynamics. Thus, the lack of representation of irrigation in numerical Earth system models—be it for reanalysis, weather forecasting or climate prediction—can lead to significant errors and biases in various parameters of the system including but not limited to surface temperature and precipitation. In this study, we aim to summarize and discuss currently available irrigation parameterizations across different numerical models. This provides a reference framework to understand the impact of irrigation on the various components of Earth system models. Specifically, we discuss the impact of these parameterizations in the context of their spatio-temporal scale representation and point out the benefits and limitations of the various approaches. In fact, most of the parameterizations use irrigation as a direct modification of soil moisture with just a few implementations add irrigation as a form of surface water. While the former method might be suitable for coarse spatio-temporal scales, the latter better resembles the range of employed irrigation techniques. From the analysis, we find that not only the method or the spatio-temporal scales but the actual amount of water used is of great importance to the response of the Earth system model.\",\"urldate\":\"2023-01-30\",\"journal\":\"Frontiers in Water\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Valmassoi\"],\"firstnames\":[\"Arianna\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Keller\"],\"firstnames\":[\"Jan\",\"D.\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2022\",\"pages\":\"906664\",\"bibtex\":\"@article{valmassoi_review_2022,\\n\\ttitle = {A review on irrigation parameterizations in {Earth} system models},\\n\\tvolume = {4},\\n\\tissn = {2624-9375},\\n\\turl = {https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full},\\n\\tdoi = {10.3389/frwa.2022.906664},\\n\\tabstract = {Irrigation is the process of artificially providing water to agricultural lands in order to provide crops with the necessary water supply to ensure or foster the growth of the plants. However, its implications reach beyond the agro-economic aspect as irrigation affects the soil-land-atmosphere interactions and thus influences the water and energy cycles in the Earth system. Past studies have shown how through these interactions, an increase in soil moisture due to irrigation also affects the atmospheric state and its dynamics. Thus, the lack of representation of irrigation in numerical Earth system models—be it for reanalysis, weather forecasting or climate prediction—can lead to significant errors and biases in various parameters of the system including but not limited to surface temperature and precipitation. In this study, we aim to summarize and discuss currently available irrigation parameterizations across different numerical models. This provides a reference framework to understand the impact of irrigation on the various components of Earth system models. Specifically, we discuss the impact of these parameterizations in the context of their spatio-temporal scale representation and point out the benefits and limitations of the various approaches. In fact, most of the parameterizations use irrigation as a direct modification of soil moisture with just a few implementations add irrigation as a form of surface water. While the former method might be suitable for coarse spatio-temporal scales, the latter better resembles the range of employed irrigation techniques. From the analysis, we find that not only the method or the spatio-temporal scales but the actual amount of water used is of great importance to the response of the Earth system model.},\\n\\turldate = {2023-01-30},\\n\\tjournal = {Frontiers in Water},\\n\\tauthor = {Valmassoi, Arianna and Keller, Jan D.},\\n\\tmonth = nov,\\n\\tyear = {2022},\\n\\tpages = {906664},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Valmassoi, A.\",\"Keller, J. D.\"],\"key\":\"valmassoi_review_2022\",\"id\":\"valmassoi_review_2022\",\"bibbaseid\":\"valmassoi-keller-areviewonirrigationparameterizationsinearthsystemmodels-2022\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"The Role of Space-Based Observations for Groundwater Resource Monitoring over Africa\",\"issn\":\"1573-0956\",\"url\":\"https://doi.org/10.1007/s10712-022-09759-4\",\"doi\":\"10.1007/s10712-022-09759-4\",\"abstract\":\"Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent.\",\"journal\":\"Surveys in Geophysics\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Springer\"],\"firstnames\":[\"Anne\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Lopez\"],\"firstnames\":[\"Teodolina\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Owor\"],\"firstnames\":[\"Michael\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Frappart\"],\"firstnames\":[\"Frédéric\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Stieglitz\"],\"firstnames\":[\"Thomas\"],\"suffixes\":[]}],\"month\":\"January\",\"year\":\"2023\",\"bibtex\":\"@article{springer_role_2023,\\n\\ttitle = {The {Role} of {Space}-{Based} {Observations} for {Groundwater} {Resource} {Monitoring} over {Africa}},\\n\\tissn = {1573-0956},\\n\\turl = {https://doi.org/10.1007/s10712-022-09759-4},\\n\\tdoi = {10.1007/s10712-022-09759-4},\\n\\tabstract = {Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent.},\\n\\tjournal = {Surveys in Geophysics},\\n\\tauthor = {Springer, Anne and Lopez, Teodolina and Owor, Michael and Frappart, Frédéric and Stieglitz, Thomas},\\n\\tmonth = jan,\\n\\tyear = {2023},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Springer, A.\",\"Lopez, T.\",\"Owor, M.\",\"Frappart, F.\",\"Stieglitz, T.\"],\"key\":\"springer_role_2023\",\"id\":\"springer_role_2023\",\"bibbaseid\":\"springer-lopez-owor-frappart-stieglitz-theroleofspacebasedobservationsforgroundwaterresourcemonitoringoverafrica-2023\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://doi.org/10.1007/s10712-022-09759-4\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Raspberry Pi Reflector (RPR): A Low‐cost Water‐level Monitoring System based on GNSS Interferometric Reflectometry\",\"issn\":\"0043-1397, 1944-7973\",\"shorttitle\":\"Raspberry Pi Reflector (RPR)\",\"url\":\"https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713\",\"doi\":\"10.1029/2021WR031713\",\"language\":\"en\",\"urldate\":\"2022-11-24\",\"journal\":\"Water Resources Research\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Karegar\"],\"firstnames\":[\"Makan\",\"A.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Geremia‐Nievinski\"],\"firstnames\":[\"Felipe\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Larson\"],\"firstnames\":[\"Kristine\",\"M.\"],\"suffixes\":[]}],\"month\":\"November\",\"year\":\"2022\",\"bibtex\":\"@article{karegar_raspberry_2022,\\n\\ttitle = {Raspberry {Pi} {Reflector} ({RPR}): {A} {Low}‐cost {Water}‐level {Monitoring} {System} based on {GNSS} {Interferometric} {Reflectometry}},\\n\\tissn = {0043-1397, 1944-7973},\\n\\tshorttitle = {Raspberry {Pi} {Reflector} ({RPR})},\\n\\turl = {https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713},\\n\\tdoi = {10.1029/2021WR031713},\\n\\tlanguage = {en},\\n\\turldate = {2022-11-24},\\n\\tjournal = {Water Resources Research},\\n\\tauthor = {Karegar, Makan A. and Kusche, Jürgen and Geremia‐Nievinski, Felipe and Larson, Kristine M.},\\n\\tmonth = nov,\\n\\tyear = {2022},\\n}\\n\\n\\n\\n\",\"author_short\":[\"Karegar, M. A.\",\"Kusche, J.\",\"Geremia‐Nievinski, F.\",\"Larson, K. M.\"],\"key\":\"karegar_raspberry_2022\",\"id\":\"karegar_raspberry_2022\",\"bibbaseid\":\"karegar-kusche-geremianievinski-larson-raspberrypireflectorrpralowcostwaterlevelmonitoringsystembasedongnssinterferometricreflectometry-2022\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713\"},\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"bibtype\":\"article\",\"type\":\"article\",\"title\":\"Soil hydrology in the Earth system\",\"volume\":\"3\",\"issn\":\"2662-138X\",\"url\":\"https://www.nature.com/articles/s43017-022-00324-6\",\"doi\":\"10.1038/s43017-022-00324-6\",\"language\":\"en\",\"number\":\"9\",\"urldate\":\"2023-01-26\",\"journal\":\"Nature Reviews Earth & Environment\",\"author\":[{\"propositions\":[],\"lastnames\":[\"Vereecken\"],\"firstnames\":[\"Harry\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Amelung\"],\"firstnames\":[\"Wulf\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bauke\"],\"firstnames\":[\"Sara\",\"L.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bogena\"],\"firstnames\":[\"Heye\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Brüggemann\"],\"firstnames\":[\"Nicolas\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Montzka\"],\"firstnames\":[\"Carsten\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Vanderborght\"],\"firstnames\":[\"Jan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Bechtold\"],\"firstnames\":[\"Michel\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Blöschl\"],\"firstnames\":[\"Günter\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Carminati\"],\"firstnames\":[\"Andrea\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Javaux\"],\"firstnames\":[\"Mathieu\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Konings\"],\"firstnames\":[\"Alexandra\",\"G.\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Kusche\"],\"firstnames\":[\"Jürgen\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Neuweiler\"],\"firstnames\":[\"Insa\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Or\"],\"firstnames\":[\"Dani\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Steele-Dunne\"],\"firstnames\":[\"Susan\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Verhoef\"],\"firstnames\":[\"Anne\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Young\"],\"firstnames\":[\"Michael\"],\"suffixes\":[]},{\"propositions\":[],\"lastnames\":[\"Zhang\"],\"firstnames\":[\"Yonggen\"],\"suffixes\":[]}],\"month\":\"August\",\"year\":\"2022\",\"pages\":\"573–587\",\"bibtex\":\"@article{vereecken_soil_2022,\\n\\ttitle = {Soil hydrology in the {Earth} system},\\n\\tvolume = {3},\\n\\tissn = {2662-138X},\\n\\turl = {https://www.nature.com/articles/s43017-022-00324-6},\\n\\tdoi = {10.1038/s43017-022-00324-6},\\n\\tlanguage = {en},\\n\\tnumber = {9},\\n\\turldate = {2023-01-26},\\n\\tjournal = {Nature Reviews Earth \\\\& Environment},\\n\\tauthor = {Vereecken, Harry and Amelung, Wulf and Bauke, Sara L. and Bogena, Heye and Brüggemann, Nicolas and Montzka, Carsten and Vanderborght, Jan and Bechtold, Michel and Blöschl, Günter and Carminati, Andrea and Javaux, Mathieu and Konings, Alexandra G. and Kusche, Jürgen and Neuweiler, Insa and Or, Dani and Steele-Dunne, Susan and Verhoef, Anne and Young, Michael and Zhang, Yonggen},\\n\\tmonth = aug,\\n\\tyear = {2022},\\n\\tpages = {573--587},\\n}\\n\",\"author_short\":[\"Vereecken, H.\",\"Amelung, W.\",\"Bauke, S. L.\",\"Bogena, H.\",\"Brüggemann, N.\",\"Montzka, C.\",\"Vanderborght, J.\",\"Bechtold, M.\",\"Blöschl, G.\",\"Carminati, A.\",\"Javaux, M.\",\"Konings, A. G.\",\"Kusche, J.\",\"Neuweiler, I.\",\"Or, D.\",\"Steele-Dunne, S.\",\"Verhoef, A.\",\"Young, M.\",\"Zhang, Y.\"],\"key\":\"vereecken_soil_2022\",\"id\":\"vereecken_soil_2022\",\"bibbaseid\":\"vereecken-amelung-bauke-bogena-brggemann-montzka-vanderborght-bechtold-etal-soilhydrologyintheearthsystem-2022\",\"role\":\"author\",\"urls\":{\"Paper\":\"https://www.nature.com/articles/s43017-022-00324-6\"},\"metadata\":{\"authorlinks\":{}},\"downloads\":7,\"html\":\"\"}],\n      metadata: {\"authorlinks\":{}},\n      ownerID: undefined\n    };\n  </script>\n\n  <script type=\"text/javascript\">\n  var site$;\n  if (typeof $ != 'undefined') {\n    console.log('existing jquery: storing and then restoring');\n    site$ = $;\n    $ = null;\n  }\n  </script>\n\n  <script src=\"https://ajax.googleapis.com/ajax/libs/jquery/2.2.4/jquery.min.js\">\n  </script>\n  <script type=\"text/javascript\">\n  if (site$) {\n    console.log('existing jquery: avoiding conflict and restoring');\n    bb$ = $.noConflict(true);\n    $ = site$;\n  } else {\n    bb$ = $;\n  }\n  </script>\n\n  <script src=\"//bibbase.org/js/bibbase.min.js\"\n          type=\"text/javascript\">\n  </script>\n\n  <script type=\"text/javascript\"\n          src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML\">\n  </script>\n  <script type=\"text/x-mathjax-config\">\n    MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\\\(','\\\\)']]},\n                        skipTags: [\"body\"],\n                        processClass: \"bibbase_paper\"});\n  </script>\n\n  <style>\n  @media print {\n    .dontprint {\n        display: none !important;\n    }\n\n  .bibbase_group {\n    background-color: #E0E0E0;\n    font-style: italic;\n    font-size: larger;\n    text-shadow: 0px 0px 3px #FFFFFF;\n    border-radius: 4px 4px 4px 4px;\n    -moz-border-radius: 4px 4px 4px 4px;\n    -webkit-border-radius: 4px;\n    padding: 5px 40px 5px;\n    margin-top: 10px;\n    margin-bottom: 5px;\n    cursor: pointer;\n  }\n\n  .bibbase_paper {\n    margin-bottom: 5px;\n  }\n\n  }\n  </style>\n\n  \n  <div style=\"float: right; margin-right: 10px; margin-top: 10px; text-align: right; font-size: 12px\">\n    generated by\n    <a href=\"//bibbase.org\"\n       onclick=\"trackOutboundLink('bibbase', 'logo clicked', window.location.href, '//bibbase.org'); return false;\">\n      <img src=\"//bibbase.org/img/logo.svg\"\n           style=\"vertical-align: middle; margin-left: 3px; height: 16px;\"/\n           alt=\"bibbase.org\"\n           title=\"BibBase – The easiest way to maintain your publications page.\"\n        ></a>\n    \n  </div>\n  \n\n  <div id=\"bibbase_header\" class=\"dontprint\" style=\"\">\n\n    <ul class=\"nav nav-pills\" style=\"margin: 0px;\">\n\n      <li class=\"dropdown\" id=\"groupby_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\">\n          Group by\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li class=\"groupby year\"><a onclick=\"groupby('year')\">\n            Year</a>\n        </li>\n        <li class=\"groupby author\"><a onclick=\"groupby('author_short')\">\n            Author</a>\n        </li>\n        <li class=\"groupby type\"><a onclick=\"groupby('type')\">\n            Type</a>\n        </li>\n        <li class=\"groupby keyword\"><a onclick=\"groupby('keyword')\">\n            Keyword</a>\n        </li>\n        <li class=\"groupby downloads\"><a onclick=\"groupby('downloads')\">\n            Downloads</a>\n        </li>\n      </ul>\n      </li>\n\n\n      <li class=\"dropdown\" id=\"menu_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\" alt=\"controls\">\n          <i class=\"fa fa-reorder\" alt=\"controls\"></i>\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li>\n          <a onclick=\"toggleAll()\">\n            <i class=\"fa fa-chevron-down fa-fw\"></i> Expand/Collapse All\n          </a>\n        </li>\n        <li>\n          <a download=\"kasicamper\" href=\"data:text/bibtex;base64,@article{nguyen_multi-year_2024,
	title = {Multi-year aboveground data of minirhizotron facilities in {Selhausen}},
	volume = {11},
	issn = {2052-4463},
	url = {https://www.nature.com/articles/s41597-024-03535-2},
	doi = {10.1038/s41597-024-03535-2},
	abstract = {Abstract
            
              Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO
              2
              and H
              2
              O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO
              2
              exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.},
	language = {en},
	number = {1},
	urldate = {2025-02-18},
	journal = {Scientific Data},
	author = {Nguyen, Thuy Huu and Lopez, Gina and Seidel, Sabine J. and Lärm, Lena and Bauer, Felix Maximilian and Klotzsche, Anja and Schnepf, Andrea and Gaiser, Thomas and Hüging, Hubert and Ewert, Frank},
	month = jun,
	year = {2024},
	pages = {674},
}









@article{vanderborght_mechanistically_2024,
	title = {Mechanistically derived macroscopic root water uptake functions: {The} \textit{α} and \textit{ω} of root water uptake functions},
	volume = {23},
	issn = {1539-1663, 1539-1663},
	shorttitle = {Mechanistically derived macroscopic root water uptake functions},
	url = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333},
	doi = {10.1002/vzj2.20333},
	abstract = {Abstract
            
              Water uptake by plant roots is an important component of the soil water balance. Predicting to what extent potential transpiration from the canopy, that is, transpiration demand, can be met by supply of water from the soil through the root system is crucial to simulate the actual transpiration and assess vegetation water stress. In models that simulate the dynamics of vertical soil water content profiles as a function of water fluxes and soil water potential gradients, the root water uptake (RWU) distribution is represented by macroscopic sink terms. We present RWU functions that calculate sink terms based on a mechanistic model of water flow in the soil–root system. Based on soil–root hydraulics, we define
              α
              ‐supply functions representing the maximal uptake by the root system from a certain soil depth when the root collar water potential equals the wilting point,
              ω
              ‐supply factors representing the maximal supply from the entire root system, and a critical
              
                ω
                c
              
              factor representing the potential transpiration demand. These functions and factors are subsequently used to calculate RWU distributions directly from potential transpiration or demand and the soil water potentials. Unlike currently used approaches, which define
              α
              ‐stress functions and
              ω
              factors representing ratios of actual uptake to uptake demand, the supply‐based formulations can be derived directly from soil and root hydraulic properties and can represent processes like root hydraulic redistribution and hydraulic lift.
            
          , 
            Core Ideas
            
              
                
                  Functions to calculate root water uptake (RWU) from different soil depths were derived.
                
                
                  RWU is calculated directly using soil water potentials and the potential transpiration rate.
                
                
                  The functions are derived using soil and root hydraulic properties.
                
                
                  Phenomena like RWU compensation, hydraulic redistribution, and hydraulic lift are reproduced.
                
                
                  Similarities and differences with currently used uptake functions are discussed.},
	language = {en},
	number = {4},
	urldate = {2025-02-18},
	journal = {Vadose Zone Journal},
	author = {Vanderborght, Jan and Couvreur, Valentin and Javaux, Mathieu and Leitner, Daniel and Schnepf, Andrea and Vereecken, Harry},
	month = jul,
	year = {2024},
	pages = {e20333},
}





@article{zhang_summer_2024,
	title = {Summer evapotranspiration-cloud feedbacks in land-atmosphere interactions over {Europe}},
	volume = {62},
	issn = {0930-7575, 1432-0894},
	url = {https://link.springer.com/10.1007/s00382-024-07475-w},
	doi = {10.1007/s00382-024-07475-w},
	abstract = {Abstract
            
              Land-atmosphere (L-A) feedbacks are important for understanding regional climate functioning. However, the accurate quantification of feedback strength is challenging due to complex, nonlinear interactions and varying background atmospheric conditions. In particular, the role of cloud water in the terrestrial water cycle is often ignored or simplified in previous L-A feedback studies, which overlook the relationship between evapotranspiration (
              ET
              ) and cloud water (
              TQC
              ). This study diagnoses the interactions between
              
                \$\${\textbackslash}:ET\$\$
              
              ,
              
                \$\${\textbackslash}:TQC\$\$
              
              and its dynamics (
              
                \$\${\textbackslash}:{\textbackslash}varDelta{\textbackslash}:TQC/{\textbackslash}varDelta{\textbackslash}:t\$\$
              
              ) under different atmospheric conditions by conducting correlation and a novel scaling analysis, based on a coupled regional climate model simulation. Contrasting correlation relationships between
              
                \$\${\textbackslash}:ET\$\$
              
              ,
              
                \$\${\textbackslash}:TQC\$\$
              
              and
              
                \$\${\textbackslash}:{\textbackslash}varDelta{\textbackslash}:TQC/{\textbackslash}varDelta{\textbackslash}:t\$\$
              
              were identified, indicating the positive feedback between
              
                \$\${\textbackslash}:ET\$\$
              
              and the dynamics in cloud water. Two types of positive scaling relationships between
              
                \$\${\textbackslash}:ET\$\$
              
              and
              
                \$\${\textbackslash}:{\textbackslash}varDelta{\textbackslash}:TQC/{\textbackslash}varDelta{\textbackslash}:t\$\$
              
              were identified by K-means clustering. The analysis shows a contrasting north-south distribution of the scaling relationship that is similar to the spatial distribution of energy-limited and water-limited
              
                \$\${\textbackslash}:ET\$\$
              
              regimes, highlighting the role of ET regimes in modulating the
              
                \$\${\textbackslash}:ET\$\$
              
              -
              
                \$\${\textbackslash}:{\textbackslash}varDelta{\textbackslash}:TQC/{\textbackslash}varDelta{\textbackslash}:t\$\$
              
              scaling relationships. Moreover, the feedback strength and scaling relationship are affected by atmospheric moisture flux dynamics, providing remote moisture sources and altering dry/wet conditions. Our results highlight the role of cloud water in the atmospheric part of the L-A process chain and reveal the effect of different atmospheric conditions on L-A interactions based on the new analysis framework.},
	language = {en},
	number = {12},
	urldate = {2025-02-14},
	journal = {Climate Dynamics},
	author = {Zhang, Yikui and Wagner, Niklas and Goergen, Klaus and Kollet, Stefan},
	month = dec,
	year = {2024},
	pages = {10767--10783},
}









@article{hacker_how_2024,
	title = {How realistic are multi-decadal reconstructions of {GRACE}-like total water storage anomalies?},
	volume = {645},
	issn = {00221694},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762},
	doi = {10.1016/j.jhydrol.2024.132180},
	language = {en},
	urldate = {2025-02-14},
	journal = {Journal of Hydrology},
	author = {Hacker, Charlotte and Kusche, Jürgen},
	month = dec,
	year = {2024},
	pages = {132180},
}





@article{poppe_teran_systematic_2025,
	title = {Systematic underestimation of type-specific ecosystem process variability in the {Community} {Land} {Model} v5 over {Europe}},
	volume = {18},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {1991-9603},
	url = {https://gmd.copernicus.org/articles/18/287/2025/},
	doi = {10.5194/gmd-18-287-2025},
	abstract = {Abstract. Evapotranspiration (ET) and gross primary production (GPP) are critical fluxes contributing to the energy, water, and carbon exchanges between the atmosphere and the land surface. Land surface models such as the Community Land Model v5 (CLM5) quantify these fluxes, estimate the state of carbon budgets and water resources, and contribute to a better understanding of climate change's impact on ecosystems. Past studies have shown the ability of CLM5 to model ET and GPP magnitudes well but emphasized systematic underestimations and lower variability than in the observations. Here, we evaluated CLM5's predictions of water and energy fluxes using observations from eddy covariance stations from the Integrated Carbon Observation System (ICOS), remote sensing, and reanalysis data sets. We assess simulated ET and GPP from the grid scale (CLM5grid) and the plant functional type (PFT) scale (CLM5PFT). CLM5PFT exhibited a low systematic error in simulating the ET at the ICOS sites (average bias of −4.68 \%), indicating that PFT-specific ET closely matches the observations' magnitude. GPP was underestimated by CLM5PFT, especially in deciduous forests (bias of −43.76 \%). The results showed an underestimation of the spatiotemporal variability in the simulated ET and GPP distribution moments across PFTs for both CLM setups compared to reanalysis data and remote-sensing products. These findings provide essential insights for improving land surface models, highlighting the need to enhance the CLM5's ability to capture the spatiotemporal variability in ET and GPP simulations across PFTs.},
	language = {en},
	number = {2},
	urldate = {2025-02-14},
	journal = {Geoscientific Model Development},
	author = {Poppe Terán, Christian and Naz, Bibi S. and Vereecken, Harry and Baatz, Roland and Fisher, Rosie A. and Hendricks Franssen, Harrie-Jan},
	month = jan,
	year = {2025},
	pages = {287--317},
}





@article{chen_measuring_2025,
	title = {Measuring {Off}-nadir river water levels and slopes from altimeter {Fully}-{Focused} {SAR} mode},
	volume = {650},
	issn = {00221694},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498},
	doi = {10.1016/j.jhydrol.2024.132553},
	language = {en},
	urldate = {2025-02-14},
	journal = {Journal of Hydrology},
	author = {Chen, Jiaming and Fenoglio, Luciana and Kusche, Jürgen},
	month = apr,
	year = {2025},
	pages = {132553},
}





@article{kracheletz_would_2025,
	title = {Would the 2021 {Western} {Europe} {Flood} {Event} {Be} {Visible} in {Satellite} {Gravimetry}?},
	volume = {130},
	issn = {2169-897X, 2169-8996},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190},
	doi = {10.1029/2024JD042190},
	abstract = {Abstract
            The primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in the Earth's gravitational field. Distance variations between the two GRACE‐FO satellites, recorded by a K‐Band Ranging system and a new Laser Ranging Interferometer (LRI), are significantly influenced by atmospheric mass redistribution. We investigate whether the sub‐monthly variations in atmospheric water mass, precipitation, and changes in total water storage during the extreme flood event in western Europe in 2021 were sufficiently large to influence the satellite gravity field measurements, if the GRACE‐FO satellites would have passed directly over the region. We use several data sets such as weather forecasts (ICON‐D2 model), hydrological simulations (ParFlow/CLM), observations as well as reanalyses, showing the high uncertainty between different estimations of the considered variables: total precipitable water, total precipitation, and total water storage. Our estimates suggest a potentially noticeable impact of the 2021 flood event on the GRACE‐FO satellites. Although it was globally seen a rather small event, even the atmospheric water mass beyond water vapor, which is not considered within the de‐aliasing process, is close to the LRI detection accuracy. This is particularly relevant for future gravity missions, which will use the LRI with potentially higher sensitivity as their main instrument. Sub‐monthly variations in the total atmospheric water mass, that is, beyond water vapor of huge extreme precipitation events should be investigated further to reduce potential future aliasing errors.
          , 
            Plain Language Summary
            The GRACE Follow‐On (GRACE‐FO) satellite mission measures temporal changes in the Earth's gravitational field by tracking the distance between GRACE‐FO's two satellites with a K‐Band Ranging system and a new laser ranging interferometer (LRI). Sub‐monthly variations in atmospheric mass impact these measurements, so it is essential to account for these variations to minimize errors in the derived monthly gravity fields. In July 2021, western Europe experienced an extreme flood event. We investigate whether its unusually high atmospheric water masses, strong precipitation, and increased overall water storage could impact the satellite's gravity measurements. We use data from several sources, including weather forecasts, hydrological simulations, observed precipitation and reanalysis data. We estimate potential changes in the distance between the satellites if they had flown over the flooded area during the flood period from July 14 to 16, 2021. Our upper estimates suggest that the flood event could have been seen in the GRACE‐FO measurements in case of a direct overpass. To improve the accuracy of future missions, which will rely on the LRI as their primary instrument, we suggest to further investigate short‐term variations in atmospheric water mass, that is, beyond water vapor to reduce potential errors.
          , 
            Key Points
            
              
                
                  Simulations show that the flood event could have noticeably impacted GRACE‐FO Laser Ranging Interferometer measurements, if the satellites had flown over the event
                
                
                  Even the instantaneous atmospheric water mass was likely large enough to have been detected
                
                
                  Atmospheric water beyond water vapor is not considered in current de‐aliasing products, and we suggest this paradigm should be reassessed},
	language = {en},
	number = {3},
	urldate = {2025-02-03},
	journal = {Journal of Geophysical Research: Atmospheres},
	author = {Kracheletz, Magdalena and Liu, Ziyu and Springer, Anne and Kusche, Jürgen and Friederichs, Petra},
	month = feb,
	year = {2025},
	pages = {e2024JD042190},
}





@article{becker_coastal_2024,
	title = {Coastal {Flooding} in {Asian} {Megadeltas}: {Recent} {Advances}, {Persistent} {Challenges}, and {Call} for {Actions} {Amidst} {Local} and {Global} {Changes}},
	volume = {62},
	issn = {8755-1209, 1944-9208},
	shorttitle = {Coastal {Flooding} in {Asian} {Megadeltas}},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846},
	doi = {10.1029/2024RG000846},
	abstract = {Abstract
            Asian megadeltas, specifically the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas host half of the world's deltaic population and are vital for Asian countries' ecosystems and food production. These deltas are extremely vulnerable to global change. Accelerating relative sea‐level rise, combined with rapid socio‐economic development intensifies these vulnerabilities and calls for a comprehensive understanding of current and future coastal flood dynamics. Here we provide a state‐of‐the‐art on the current knowledge and recent advances in quantifying and understanding the drivers of coastal flood‐related hazards in these deltas. We discuss the environmental and physical drivers, including climate influence, hydrology, oceanography, geomorphology, and geophysical processes and how they interact from short to long‐term changes, including during extreme events. We also jointly examine how human disturbances, with catchment interventions, land use changes and resource exploitations, contribute to coastal flooding in the deltas. Through a systems perspective, we characterize the current state of the deltaic systems and provide essential insights for shaping their sustainable future trajectories regarding the multifaceted challenges of coastal flooding.
          , 
            Plain Language Summary
            Asian megadeltas, including the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas, are home to half of the world's deltaic population and play a critical role in Asian food production. However, these deltas are at high risk to climatic changes, with the vast majority of the world's coastal flood exposure observed in these systems. Rising sea levels and rapid socio‐economic development worsen these vulnerabilities, necessitating a comprehensive understanding of coastal flooding dynamics across the five deltas. This review provides up‐to‐date insights on the current understanding and quantification of the drivers of coastal flood‐related hazards. It examines environmental and biophysical factors, such as climate, hydrology, oceanography, geomorphology, and geophysical processes, and how these may interact during extreme events. The review also explores how human activities, like catchment interventions, land use changes, and resource exploitation, contribute to coastal flooding. By offering a systematic perspective, this review characterizes the current state of knowledge on these deltaic systems and provides valuable insights for shaping sustainable future trajectories in the face of the challenges posed by coastal flooding.
          , 
            Key Points
            
              
                
                  Urgent action is needed to address data gaps in monitoring coastal flooding in Asian megadeltas
                
                
                  Integrated approaches, including in situ data, remote sensing and advanced modeling, are needed to understand coastal flooding impacts
                
                
                  Unprecedented changes in Asian megadeltas call for integrated studies; decisions made today shape deltaic sustainability for decades},
	language = {en},
	number = {4},
	urldate = {2025-01-06},
	journal = {Reviews of Geophysics},
	author = {Becker, M. and Seeger, K. and Paszkowski, A. and Marcos, M. and Papa, F. and Almar, R. and Bates, P. and France‐Lanord, C. and Hossain, Md S. and Khan, Md J. U. and Karegar, M. A. and Karpytchev, M. and Long, N. and Minderhoud, P. S. J. and Neal, J. and Nicholls, R. J. and Syvitski, J.},
	month = dec,
	year = {2024},
	pages = {e2024RG000846},
}





@article{brill_exploring_2024,
	title = {Exploring drought hazard, vulnerability, and related impacts on agriculture in {Brandenburg}},
	volume = {24},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {1684-9981},
	url = {https://nhess.copernicus.org/articles/24/4237/2024/},
	doi = {10.5194/nhess-24-4237-2024},
	abstract = {Abstract. Adaptation to an increasingly dry regional climate requires spatially explicit information about current and future risks. Existing drought risk studies often rely on expert-weighted composite indicators, while empirical evidence on impact-relevant factors is still scarce. The aim of this study is to investigate to what extent hazard and vulnerability indicators can explain observed agricultural drought impacts via data-driven methods. We focus on the German federal state of Brandenburg, 2013–2022, including several consecutive drought years. As impact indicators we use thermal–spectral anomalies (land surface temperature (LST) and the normalized difference vegetation index (NDVI)) on the field level, and empirical yield gaps from reported statistics on the county level. Empirical associations to the impact indicators on both spatial levels are compared. Extreme gradient boosting (XGBoost) models explain up to about 60 \% of the variance in the yield gap data (best R2 = 0.62). Model performance is more stable for the drought years and when using all crops for training rather than individual crops. Meteorological drought in June and soil quality are selected as the strongest impact-relevant factors. Rye is empirically found to be less vulnerable to drought than wheat, even on poorer soils. LST / NDVI only weakly relates to our empirical yield gaps. We recommend comparing different impact indicators on multiple scales to proceed with the development of empirically grounded risk maps.},
	language = {en},
	number = {12},
	urldate = {2024-12-02},
	journal = {Natural Hazards and Earth System Sciences},
	author = {Brill, Fabio and Alencar, Pedro Henrique Lima and Zhang, Huihui and Boeing, Friedrich and Hüttel, Silke and Lakes, Tobia},
	month = nov,
	year = {2024},
	pages = {4237--4265},
}





@article{ho-hagemann_coupling_2024,
	title = {Coupling the regional climate model {ICON}-{CLM} v2.6.6 to the {Earth} system model {GCOAST}-{AHOI} v2.0 using {OASIS3}-{MCT} v4.0},
	volume = {17},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {1991-9603},
	url = {https://gmd.copernicus.org/articles/17/7815/2024/},
	doi = {10.5194/gmd-17-7815-2024},
	abstract = {Abstract. Interactions and feedback between components of the Earth system can have a significant impact on local and regional climate and its changes due to global warming. These effects can be better represented by regional Earth system models (RESMs) than by traditional stand-alone atmosphere and ocean models. Here, we present the RESM Geesthacht Coupled cOAstal model SysTem (GCOAST)-AHOI v2.0, which includes a new atmospheric component, the regional climate model Icosahedral Nonhydrostatic (ICON)-CLM, which is coupled to the Nucleus for European Modelling of the Ocean (NEMO) and the hydrological discharge model HD via the OASIS3-MCT coupler. The GCOAST-AHOI model has been developed and applied for climate simulations over the EURO-CORDEX domain. Two 11-year simulations from 2008 to 2018 of the uncoupled ICON-CLM and GCOAST-AHOI give similar results for seasonal and annual means of near-surface air temperature, precipitation, mean sea level pressure, and wind speed at a height of 10 m. However, GCOAST-AHOI has a cold sea surface temperature (SST) bias of 1–2 K over the Baltic and North seas that is most pronounced in the winter and spring seasons. A possible reason for the cold SST bias could be the underestimation of the downward shortwave radiation at the surface of ICON-CLM with the current model settings. Despite the cold SST bias, GCOAST-AHOI was able to capture other key variables well, such as those mentioned above. Therefore, GCOAST-AHOI can be a useful tool for long-term climate simulations over the EURO-CORDEX domain. Compared to the stand-alone NEMO3.6 forced by ERA5 and ORAS5 boundary forcing, GCOAST-AHOI has positive biases in sea ice fraction and salinity but negative biases in runoff, which need to be investigated further in the future to improve the coupled simulations. The new OASIS3-MCT coupling interface OMCI implemented in ICON-CLM adds the possibility of coupling ICON-CLM to an external ocean model and an external hydrological discharge model using OASIS3-MCT instead of the YAC (Yet Another Coupler). Using OMCI, it is also possible to set up a RESM with ICON-CLM and other ocean and hydrology models possessing the OASIS3-MCT interface for other regions, such as the Mediterranean Sea.},
	language = {en},
	number = {21},
	urldate = {2024-11-27},
	journal = {Geoscientific Model Development},
	author = {Ho-Hagemann, Ha Thi Minh and Maurer, Vera and Poll, Stefan and Fast, Irina},
	month = nov,
	year = {2024},
	pages = {7815--7834},
}









@article{zhao_comparative_2024,
	title = {A {Comparative} {Analysis} of {Remote} {Sensing} {Soil} {Moisture} {Datasets} {Fusion} {Methods}: {Novel} {LSTM} {Approach} {Versus} {Widely} {Used} {Triple} {Collocation} {Technique}},
	volume = {17},
	copyright = {https://creativecommons.org/licenses/by-nc-nd/4.0/},
	issn = {1939-1404, 2151-1535},
	shorttitle = {A {Comparative} {Analysis} of {Remote} {Sensing} {Soil} {Moisture} {Datasets} {Fusion} {Methods}},
	url = {https://ieeexplore.ieee.org/document/10669050/},
	doi = {10.1109/JSTARS.2024.3455549},
	urldate = {2024-11-21},
	journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
	author = {Zhao, Haojin and Montzka, Carsten and Vereecken, Harry and Franssen, Harrie-Jan Hendricks},
	year = {2024},
	pages = {16659--16671},
}









@article{gorooei_short-term_2024,
	title = {Short-{Term} {Response} of {Soil} {Organic} {Carbon} {Indices} to {Different} {Farming} {Strategies} and {Crop} {Rotation} {Systems} in a {Semiarid} {Warm} {Region}},
	volume = {2024},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {1687-7675, 1687-7667},
	url = {https://www.hindawi.com/journals/aess/2024/8594691/},
	doi = {10.1155/2024/8594691},
	abstract = {Several indices can be used to assess the impact of short-term conservation agriculture strategies on improving soil organic carbon (SOC). To find out how the SOC pools and the carbon lability influence the carbon management index (CMI) in response to different agricultural practices in a warm semiarid region, the carbon lability index (LI) and the carbon pool index (CPI) were measured under the interactive effect of different fertilizer applications and crop residue management (hereafter referred to as “farming strategies”) in combination with four crop rotation systems in Ahvaz, Khuzestan, Iran, over four growing seasons from 2018 to 2020. The farming strategies were as follows: (1) using the standard rate of inorganic fertilizer used in the region and removing crop residues from the soil (SIF\_no-CR); (2) applying the standard rate of organic fertilizers used in the region and returning 30\% of crop residues to the soil (SOF\_30\% CR); and (3) integrating the use of inorganic and organic fertilizers and returning 15\% of crop residues to the soil (IOF\_15\% CR). The crop rotation systems were fallow-wheat (F-W), corn-wheat (C-W), sesame-wheat (S-W), and mung bean-wheat (B-W). No statistically significant difference was observed between the different farming strategies and rotation systems with respect to LI after two years of the experiment. The highest (1.26) and lowest (1.06) CPIs were observed for SOF\_30\% CR and SIF\_no-CR, respectively. The magnitude of the CMI values followed the order SOF\_30\% CR (121) {\textgreater} IOF\_15\% CR (107) ≥ SIF\_no-CR (106). B-W and F-W had the highest and lowest CPI with values of 1.29 and 1.01, respectively. No statistically significant difference was found for the different crop rotation systems. Given the low impact of the common farming practices in the region, e.g., SIF\_no-CR and F-W, on CPI and CMI at 24 months, our results showed that farming strategies with manure application and crop residue management and summer wheat-based rotation systems appear to be more appropriate farming strategies to improve CMI in arable land.},
	language = {en},
	urldate = {2024-11-15},
	journal = {Applied and Environmental Soil Science},
	author = {Gorooei, Aram and Aynehband, Amir and Behrend, Dominik and J. Seidel, Sabine and Kumar Srivastava, Amit and Rahnama, Afrasyab and Gaiser, Thomas},
	editor = {El-Gendy, Nour Sh.},
	month = apr,
	year = {2024},
	pages = {1--11},
}





@article{bazzo_integration_2024,
	title = {Integration of {UAV}-sensed features using machine learning methods to assess species richness in wet grassland ecosystems},
	volume = {83},
	issn = {15749541},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558},
	doi = {10.1016/j.ecoinf.2024.102813},
	language = {en},
	urldate = {2024-11-15},
	journal = {Ecological Informatics},
	author = {Bazzo, Clara Oliva Gonçalves and Kamali, Bahareh and Dos Santos Vianna, Murilo and Behrend, Dominik and Hueging, Hubert and Schleip, Inga and Mosebach, Paul and Haub, Almut and Behrendt, Axel and Gaiser, Thomas},
	month = nov,
	year = {2024},
	pages = {102813},
}





@article{bazzo_assessing_2024,
	title = {Assessing the {Effect} of {Field} {Disturbances} {On} {Biomass} {Estimation} in {Grasslands} {Using} {UAV}-{Derived} {Canopy} {Height} {Models}},
	issn = {2512-2789, 2512-2819},
	url = {https://link.springer.com/10.1007/s41064-024-00322-x},
	doi = {10.1007/s41064-024-00322-x},
	abstract = {Abstract
            Accurate estimation of biomass in grasslands is essential for understanding ecosystem health and productivity. Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools for biomass estimation using canopy height models derived from high-resolution imagery. However, the impact of field disturbances, such as lodging and molehills, on the accuracy of biomass estimation using UAV-derived canopy height models remains underexplored. This study aimed to assess the relationship between UAV-derived canopy height and both reference canopy height measurements and dry biomass, accounting for different management systems and disturbance scenarios. UAV data were collected using a multispectral camera, and ground-based measurements were obtained for validation. The results revealed that UAV-derived canopy height models remained accurate in estimating vegetation height, even in the presence of disturbances. However, the relationship between UAV-derived canopy height and dry biomass was affected by disturbances, leading to overestimation or underestimation of biomass depending on disturbance type and severity. The impact of disturbances on biomass estimation varied across cutting systems. These findings highlight the potential of UAV-derived canopy height models for estimating vegetation structure, but also underscore the need for caution in relying solely on these models for accurate biomass estimation in heterogeneous grasslands. Future research should explore strategies to enhance biomass estimation accuracy by integrating additional data sources and accounting for field disturbances.},
	language = {en},
	urldate = {2024-11-15},
	journal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},
	author = {Bazzo, Clara Oliva Gonçalves and Kamali, Bahareh and Behrend, Dominik and Hueging, Hubert and Schleip, Inga and Mosebach, Paul and Behrendt, Axel and Gaiser, Thomas},
	month = nov,
	year = {2024},
}





@article{seidel_overlooked_2024,
	title = {The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models},
	volume = {955},
	issn = {00489697},
	shorttitle = {The overlooked effects of environmental impacts on root},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955},
	doi = {10.1016/j.scitotenv.2024.176738},
	language = {en},
	urldate = {2024-10-24},
	journal = {Science of The Total Environment},
	author = {Seidel, S.J. and Ahmadi, S.H. and Weihermüller, L. and Couëdel, A. and Lopez, G. and Behrend, D. and Kamali, B. and Gaiser, T. and Hernández-Ochoa, I.M.},
	month = dec,
	year = {2024},
	pages = {176738},
}









@article{rahmati_soil_2024,
	title = {Soil {Moisture} {Memory}: {State}‐{Of}‐{The}‐{Art} and the {Way} {Forward}},
	volume = {62},
	issn = {8755-1209, 1944-9208},
	shorttitle = {Soil {Moisture} {Memory}},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828},
	doi = {10.1029/2023RG000828},
	abstract = {Abstract
            Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil‐plant‐atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth‐dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM.
          , 
            Plain Language Summary
            Our review paper takes an in‐depth look at soil moisture memory, which is how soil records its moisture history over time and space. Analogous to human psychology, which seeks to understand how a person's/society's memory influences his/her present and future behavior, understanding soil moisture memory encourages consideration of how such memory determines present state and might determine future behavior of soils exposed to environmental disturbances. Soil moisture memory can be affected by a variety of factors, both external (e.g., weather extremes) and internal (soil's unique properties). It affects everything from the air to the way our landscapes respond to disasters like droughts, wildfires, and floods. We also studied how this phenomenon affects the balance of water and energy in our environment, the health of our plants, and even how it communicates with the atmosphere. We show how it can change depending on where you are on the planet, the time of year, and how deep you dig into the soil. We offer scientists insights into how weather and land surface models can become more accurate by accounting for soil moisture memory. Its understanding not only helps us predict and manage our environment, but also provides opportunities for exciting scientific discoveries.
          , 
            Key Points
            
              
                
                  Atmospheric forcings, land use and management, and soil processes and mechanisms explain how and why soil moisture memory emerges in ecosystems
                
                
                  Nonlocality of moisture memory, its spread across different regions, and its interaction with large‐scale climate phenomena are underexplored
                
                
                  Further advances in land surface models and closer integration of model simulations and observations are needed to better characterize moisture memory},
	language = {en},
	number = {2},
	urldate = {2024-10-23},
	journal = {Reviews of Geophysics},
	author = {Rahmati, Mehdi and Amelung, Wulf and Brogi, Cosimo and Dari, Jacopo and Flammini, Alessia and Bogena, Heye and Brocca, Luca and Chen, Hao and Groh, Jannis and Koster, Randal D. and McColl, Kaighin A. and Montzka, Carsten and Moradi, Shirin and Rahi, Arash and Sharghi S., Farnaz and Vereecken, Harry},
	month = jun,
	year = {2024},
	pages = {e2023RG000828},
}





@article{bayat_implications_2023,
	title = {Implications for sustainable water consumption in {Africa} by simulating five decades (1965–2014) of groundwater recharge},
	volume = {626},
	issn = {00221694},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301},
	doi = {10.1016/j.jhydrol.2023.130288},
	language = {en},
	urldate = {2024-10-23},
	journal = {Journal of Hydrology},
	author = {Bayat, Bagher and Oloruntoba, Bamidele and Montzka, Carsten and Vereecken, Harry and Hendricks Franssen, Harrie-Jan},
	month = nov,
	year = {2023},
	pages = {130288},
}





@article{zhu_climate-driven_2024,
	title = {Climate-driven interannual variability in subnational irrigation areas across {Europe}},
	volume = {5},
	issn = {2662-4435},
	url = {https://www.nature.com/articles/s43247-024-01721-z},
	doi = {10.1038/s43247-024-01721-z},
	abstract = {Abstract
            Irrigation profoundly impacts ecology and agricultural productivity, with irrigated areas varying across regions and years. Interannual dynamics of irrigation extent are lacking, particularly in humid regions of Europe. We analyzed the response of irrigated areas to drought conditions in areas equipped for irrigation and used the derived relationships to estimate annual irrigated areas for 32 European countries in the period 1990–2020. Interannual variability of irrigated areas varied notably, particularly in more humid Northern and Western Europe. In most humid regions, irrigated area is larger in dry years, whereas in more arid regions like Spain, it is larger in wet years. The largest irrigated area across Europe occurred in dry years 2003 and 2018 (11.93 and 11.77 million hectares), while the smallest is estimated for the wet years 2002 and 2014 (10.71 and 10.31 million hectares). The findings of this study help to improve scenario development and water resources management.},
	language = {en},
	number = {1},
	urldate = {2024-10-23},
	journal = {Communications Earth \& Environment},
	author = {Zhu, Wanxue and Siebert, Stefan},
	month = oct,
	year = {2024},
	pages = {554},
}





@article{baumert_probabilistic_2024,
	title = {Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation},
	volume = {83},
	issn = {15749541},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789},
	doi = {10.1016/j.ecoinf.2024.102836},
	language = {en},
	urldate = {2024-10-23},
	journal = {Ecological Informatics},
	author = {Baumert, Josef and Heckelei, Thomas and Storm, Hugo},
	month = nov,
	year = {2024},
	pages = {102836},
}





@article{schulze_benefits_2024,
	title = {Benefits and {Pitfalls} of {GRACE} and {Streamflow} {Assimilation} for {Improving} the {Streamflow} {Simulations} of the {WaterGAP} {Global} {Hydrology} {Model}},
	volume = {16},
	issn = {1942-2466, 1942-2466},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092},
	doi = {10.1029/2023MS004092},
	abstract = {Abstract
            Distribution and change of freshwater resources is often simulated with global hydrological models. However, owing to process representation limitations and forcing data uncertainties, these model simulations have shortcomings. Combining them with observations via data assimilation, for example, with data from the Gravity Recovery and Climate Experiment (GRACE) mission or streamflow measured at in situ stations is considered to improve the realism of the simulations. We assimilate gridded total water storage anomaly (TWSA) from GRACE into the WaterGAP Global Hydrology Model (WGHM) over the Mississippi River basin via an Ensemble Kalman Filter. Our results agree with previous studies where assimilating GRACE observations nudges TWSA simulations closer to the observations, reducing the root mean square error (RMSE) by 21\% compared to an uncalibrated model. However, simulations of streamflow show degeneration at more than 90\% of all gauge stations for metrics such as RMSE and correlations; only the annual phase of simulated streamflow improves at half the stations. Therefore, for the first time, we instead assimilated streamflow observations into the WGHM, which improved simulated streamflow at up to nearly 80\% of the stations, with normalized RMSE showing improvements of up to 0.1, while TWSA was well‐simulated in all metrics. Combining both approaches, that is, jointly assimilating GRACE‐derived TWSA and streamflow observations, leads to a trade‐off between a good fit of both variables albeit skewed to the GRACE observations. Overall, we speculate that our findings point to limitations of process representation in WGHM hindering consistent flux simulation from the storage history, especially in dry regions.
          , 
            Plain Language Summary
            The distribution of freshwater on Earth can be simulated by hydrological models like the WaterGAP Global Hydrology Model (WGHM). Changes of the total water storages can also be derived from satellite gravimetry, for example, with the Gravity Recovery and Climate Experiment (GRACE) mission. Model and observations do not necessarily agree and are both prone to errors. We combined the model and observations over the Mississippi River basin taking the errors into account by applying a data assimilation technique. This led to a more realistic simulation of the total water storage changes. Since simulated streamflow was found to degenerate at nearly all gauge stations, we assimilated streamflow observations (instead of GRACE data) into the WGHM. This turned out to improve simulated streamflow at up to nearly 80\% of the stations. The assimilation of both data sets (GRACE and streamflow) together leads to a compromise between the TWSA and the streamflow simulations, with the GRACE data affecting the simulations more than the streamflow data. Our findings are expected to aid reducing the weaknesses of the WGHM model equations and thus contribute to improved quantification of Earth's freshwater distribution in the future.
          , 
            Key Points
            
              
                
                  GRACE assimilation improves the WGHM storage representation, but degrades the simulated streamflow at up to 99\% of the gauge stations
                
                
                  Assimilating streamflow data instead improves the streamflow simulations at up to 79\% of the validation stations
                
                
                  Joint assimilation leads to a trade‐off between a good fit of simulated storages and streamflow albeit skewed to the GRACE observations},
	language = {en},
	number = {10},
	urldate = {2024-10-23},
	journal = {Journal of Advances in Modeling Earth Systems},
	author = {Schulze, K. and Kusche, J. and Gerdener, H. and Döll, P. and Müller Schmied, H.},
	month = oct,
	year = {2024},
	pages = {e2023MS004092},
}





@article{xiong_separation_2024,
	title = {Separation of earthquake and hydrology signals from {GRACE} satellites data via independent component analysis: a case study in the {Sumatra} region},
	volume = {239},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {0956-540X, 1365-246X},
	shorttitle = {Separation of earthquake and hydrology signals from {GRACE} satellites data via independent component analysis},
	url = {https://academic.oup.com/gji/article/239/3/1597/7778285},
	doi = {10.1093/gji/ggae351},
	abstract = {SUMMARY
            The Gravity Recovery and Climate Experiment (GRACE) satellites have observed mass migrations caused by megathrust earthquakes. Extracting earthquake-related signals from GRACE data is still a challenge due to the interference from non-earthquake sources such as terrestrial hydrology. Instead of reducing hydrological signals by potentially biased hydrological models, in this study we apply a model-free technique of independent component analysis (ICA), to separate earthquake and non-earthquake signals from non-Gaussian GRACE data. We elucidate the principles and mechanisms of ICA for the separation of earthquake and hydrology signals, employing simulated data to demonstrate the process. Our findings demonstrate that both spatial ICA and temporal ICA are highly effective in discerning earthquake related to 2004 Mw 9.2 event and hydrological signals from GRACE data in the Sumatra region. This stands in stark contrast to principal component analysis, which often encounters challenges with signal intermingling. The utility of ICA is evident in its ability to distinctly delineate coseismic and post-seismic behaviours associated with megathrust events, including the 2004 Sumatra, the 2010 Maule, and the 2011 Tohoku earthquakes. ICA effectively mitigates the potential for misestimation of earthquake signals, an issue that can carry substantial implications. Therefore, employing ICA facilitates the accurate extraction of earthquake-related data from satellite gravity observations—a critical process for refining earthquake source parameters and understanding Earth's rheological properties, especially when non-earthquake signals are significant and cannot be disregarded.},
	language = {en},
	number = {3},
	urldate = {2024-10-23},
	journal = {Geophysical Journal International},
	author = {Xiong, Yuhao and Feng, Wei and Zhou, Xin and Kusche, Jürgen and Shen, Yingchun and Yang, Meng and Wang, Changqing and Zhong, Min},
	month = oct,
	year = {2024},
	pages = {1597--1616},
}





@article{jensen_observations_2024,
	title = {Observations indicate regionally misleading wetting and drying trends in {CMIP6}},
	volume = {7},
	issn = {2397-3722},
	url = {https://www.nature.com/articles/s41612-024-00788-x},
	doi = {10.1038/s41612-024-00788-x},
	abstract = {Abstract
            We evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against a new global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. To account for different timescales in our analysis, we select regions in which the influence of interannual variability is relatively small and observed trends are assumed to be representative of the development over longer periods. Our results reveal distinct biases in drying and wetting trends in CMIP6 models for several world regions. Specifically, we see high model consensus for drying in the Amazon, which disagrees with the observed wetting. Other regions show a high consensus of models and observations suggesting qualitatively correctly simulated trends, e.g., for the Mediterranean and parts of Central Africa. A high model agreement might therefore falsely indicate a robust trend in water storage if it is not assessed in light of the observed developments. This underlines the potential use of maintaining an adequate observational capacity of water storage for climate change assessments.},
	language = {en},
	number = {1},
	urldate = {2024-10-23},
	journal = {npj Climate and Atmospheric Science},
	author = {Jensen, Laura and Gerdener, Helena and Eicker, Annette and Kusche, Jürgen and Fiedler, Stephanie},
	month = oct,
	year = {2024},
	pages = {249},
}





@article{burchfield_towards_2024,
	title = {Towards a comprehensive analysis of agricultural land systems in the {EU} and {US}: {A} critical view on publicly available datasets},
	volume = {147},
	issn = {02648377},
	shorttitle = {Towards a comprehensive analysis of agricultural land systems in the {EU} and {US}},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247},
	doi = {10.1016/j.landusepol.2024.107371},
	language = {en},
	urldate = {2024-10-23},
	journal = {Land Use Policy},
	author = {Burchfield, Emily and Ferro, Marco and Hüttel, Silke and Lakes, Tobia and Leonhardt, Heidi and Niedermayr, Andreas and Rissing, Andrea and Seifert, Stefan and Wesemeyer, Maximilian},
	month = dec,
	year = {2024},
	pages = {107371},
}





@article{leonhardt_use_2024,
	title = {Use cases and scientific potential of land use data from the {EU}’s {Integrated} {Administration} and {Control} {System}: {A} systematic mapping review},
	volume = {167},
	issn = {1470160X},
	shorttitle = {Use cases and scientific potential of land use data from the {EU}’s {Integrated} {Administration} and {Control} {System}},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X},
	doi = {10.1016/j.ecolind.2024.112709},
	language = {en},
	urldate = {2024-10-23},
	journal = {Ecological Indicators},
	author = {Leonhardt, Heidi and Wesemeyer, Maximilian and Eder, Andreas and Hüttel, Silke and Lakes, Tobia and Schaak, Henning and Seifert, Stefan and Wolff, Saskia},
	month = oct,
	year = {2024},
	pages = {112709},
}





@article{akter_estimating_2024,
	title = {Estimating soil moisture from environmental gamma radiation monitoring data},
	issn = {1539-1663, 1539-1663},
	url = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384},
	doi = {10.1002/vzj2.20384},
	abstract = {Abstract
            Soil moisture (SM) information is invaluable for a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents root‐zone SM for longer periods and larger spatial scales. One option for root‐zone SM observation is terrestrial gamma radiation (TGR), as it is inversely related to SM. Hence, the near real‐time data of more than 5000 environmental gamma radiation (EGR) monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) is a potential source to develop a root‐zone SM product for Europe without extra investments in SM sensors. This study aims to investigate to what extent the EURDEP data can be used for SM estimation. For this, two EGR monitoring stations were equipped with in situ SM sensors to measure reference SM. The terrestrial component of EGR was extracted after eliminating the contributions of rain washout and secondary cosmic radiation, and used to obtain a functional relationship with SM. We predicted the weekly volumetric SM with a root mean square error of 7\%–9\% from TGR measurements. Nevertheless, we believe that this technique, due to its greater penetration depth and long data legacy, can provide useful data complementary to satellite‐based remote sensing techniques to estimate root‐zone SM at the continental scale.
          , 
            Core Ideas
            
              
                
                  An extensive early warning monitoring network for environmental gamma radiation (EGR) is maintained in Europe.
                
                
                  Since soil moisture influences EGR, this database could be used to derive continental soil moisture products.
                
                
                  To test this, two monitoring stations in Germany were selected and equipped with reference soil moisture sensors.
                
                
                  From the terrestrial component of EGR, soil moisture was determined with an error of 7–9 vol.\%.
                
              
            
          , 
            Plain Language Summary
            
              Information on the temporal dynamics of SM across a large area is vital for many sectors. An extensive network for monitoring EGR detectors that has been operated across Europe after the Chernobyl nuclear accident is a potential source for deriving continental‐scale SM information without additional costs. We investigated how accurately SM can be estimated from the data of two of such detectors. The results showed that weekly SM estimates with an accuracy of 0.07–0.09 cm
              3
              cm
              −3
              are feasible after adequate data processing accounting for other factors affecting EGR. We also discussed possible sources that affected the accuracy of the SM estimates and provided directions for further research. Despite the current limitations, EGR data show potential for estimating SM across Europe.},
	language = {en},
	urldate = {2024-10-23},
	journal = {Vadose Zone Journal},
	author = {Akter, Sonia and Huisman, Johan Alexander and Bogena, Heye Reemt},
	month = oct,
	year = {2024},
	pages = {e20384},
}





@article{li_forecasting_2024,
	title = {Forecasting {Next} {Year}'s {Global} {Land} {Water} {Storage} {Using} {GRACE} {Data}},
	volume = {51},
	issn = {0094-8276, 1944-8007},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101},
	doi = {10.1029/2024GL109101},
	abstract = {Abstract
            Existing approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management.
          , 
            Plain Language Summary
            Traditional methods for predicting short‐term/seasonal variations in land total water storages rely on hydrological models. However, these models have a drawback—they are better at predicting water stored in specific parts of the land system like soil moisture than giving an accurate forecast for the overall integrated land total water storage. In this study, we demonstrate the applicability of machine learning in uncovering relationships between the de‐season and de‐linearized terms of global water storage variability as observed by the Gravity Recovery and Climate Experiment (GRACE) satellites, and the preceding hydrometeorological variables such as sea surface temperature. These relationships can then be utilized to forecast monthly changes in land total water storage up to 1 year ahead, and even to predict exceptional drought events based on near real‐time observational forcing data. The validation by actual GRACE observations, lends further credence to the effectiveness of the method developed here, showcasing its potential to forecast trends in global land total water storage for the upcoming year. The potential applications of these predictions in early warning systems are highly promising, and we anticipate that they can assist decision‐makers in enhancing current drought and water resource management practices.
          , 
            Key Points
            
              
                
                  We identify a stable lag relationship between hydrometeorological variables and the GRACE derived total water storage change (TWSC)
                
                
                  Using this stable lag relationship, we are able to forecast the global TWSC up to 1 year ahead with solely observational data as inputs
                
                
                  Our forecasts exhibit high consistency with actual GRACE data in terms of global mean land water storage trends for the following year},
	language = {en},
	number = {17},
	urldate = {2024-10-01},
	journal = {Geophysical Research Letters},
	author = {Li, Fupeng and Kusche, Jürgen and Sneeuw, Nico and Siebert, Stefan and Gerdener, Helena and Wang, Zhengtao and Chao, Nengfang and Chen, Gang and Tian, Kunjun},
	month = sep,
	year = {2024},
	pages = {e2024GL109101},
}





@article{huttel_are_2024,
	title = {Are lessons being learnt from the replication crisis or will the revolution devour its children? {Open} {Q} science from the editor's perspective},
	copyright = {https://creativecommons.org/licenses/by-nc/4.0/},
	issn = {2633-9048},
	shorttitle = {Are lessons being learnt from the replication crisis or will the revolution devour its children?},
	url = {https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351},
	doi = {10.1093/qopen/qoae019},
	abstract = {Abstract
            The scientific production system is crucial in how global challenges are addressed. However, scholars have recently begun to voice concerns about structural inefficiencies within the system, as highlighted, for example, by the replication crisis, the p-value debate and various forms of publication bias. Most suggested remedies tend to address only partial aspects of the system's inefficiencies, but there is currently no unifying agenda in favour of an overall transformation of the system. Based on a critical review of the current scientific system and an exploratory pilot study about the state of student training, we argue that a unifying agenda is urgently needed, particularly given the emergence of artificial intelligence (AI) as a tool in scientific writing and the research discovery process. Without appropriate responses from academia, this trend may even compound current issues around credibility due to limited replicability and ritual-based statistical practice while amplifying all forms of existing biases. Naïve openness in the science system alone is unlikely to lead to major improvements. We contribute to the debate and call for a system reform by identifying key elements in the definition of transformation pathways towards open, democratic and conscious learning, teaching, reviewing and publishing supported by openly maintained AI tools. Roles and incentives within the review process will have to adapt and be strengthened in relation to those that apply to authors. Scientists will have to write less, learn differently and review more in the future, but need to be trained better in and for AI even today.},
	language = {en},
	urldate = {2024-10-01},
	journal = {Q Open},
	author = {Hüttel, Silke and Hess, Sebastian},
	month = jul,
	year = {2024},
	pages = {qoae019},
}





@article{uehleke_german_2024,
	title = {German sugar beet farmers’ intention to use autonomous field robots for seeding and weeding},
	volume = {370},
	issn = {03014797},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587},
	doi = {10.1016/j.jenvman.2024.122472},
	language = {en},
	urldate = {2024-10-01},
	journal = {Journal of Environmental Management},
	author = {Uehleke, Reinhard and Von Plettenberg, Lousia and Leyer, Michael and Hüttel, Silke},
	month = nov,
	year = {2024},
	pages = {122472},
}





@article{seifert_eco-efficiency_2024,
	title = {Eco-efficiency in the agricultural landscape of {North} {Rhine}-{Westphalia}, {Germany}},
	volume = {220},
	issn = {0308521X},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129},
	doi = {10.1016/j.agsy.2024.104062},
	language = {en},
	urldate = {2024-10-01},
	journal = {Agricultural Systems},
	author = {Seifert, Stefan and Wolff, Saskia and Hüttel, Silke},
	month = oct,
	year = {2024},
	pages = {104062},
}





@article{eugenio_russmann_sensitivity_2024,
	title = {Sensitivity of aridity diagnoses to land-atmosphere coupling in {South} {America}},
	issn = {0930-7575, 1432-0894},
	url = {https://link.springer.com/10.1007/s00382-024-07413-w},
	doi = {10.1007/s00382-024-07413-w},
	language = {en},
	urldate = {2024-09-27},
	journal = {Climate Dynamics},
	author = {Eugenio Russmann, Juan and Menéndez, Claudio G. and Giles, Julian A. and Carril, Andrea F.},
	month = sep,
	year = {2024},
}





@article{nguyen_multi-year_2024,
	title = {Multi-year aboveground data of minirhizotron facilities in {Selhausen}},
	volume = {11},
	issn = {2052-4463},
	url = {https://www.nature.com/articles/s41597-024-03535-2},
	doi = {10.1038/s41597-024-03535-2},
	abstract = {Abstract
            
              Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO
              2
              and H
              2
              O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO
              2
              exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.},
	language = {en},
	number = {1},
	urldate = {2024-08-20},
	journal = {Scientific Data},
	author = {Nguyen, Thuy Huu and Lopez, Gina and Seidel, Sabine J. and Lärm, Lena and Bauer, Felix Maximilian and Klotzsche, Anja and Schnepf, Andrea and Gaiser, Thomas and Hüging, Hubert and Ewert, Frank},
	month = jun,
	year = {2024},
	pages = {674},
}





@article{larson_gnssrefl_2024,
	title = {Gnssrefl: an open source software package in python for {GNSS} interferometric reflectometry applications},
	volume = {28},
	issn = {1080-5370, 1521-1886},
	shorttitle = {Gnssrefl},
	url = {https://link.springer.com/10.1007/s10291-024-01694-8},
	doi = {10.1007/s10291-024-01694-8},
	abstract = {Abstract
            An open source software package has been developed for Global Navigation Satellite Systems (GNSS) interferometric reflectometry. The gnssrefl package is written in python; it can be installed from the source code, the python packaging index website, or via a docker. It includes modules that download GNSS data and orbit data from global archives. A periodogram is used to retrieve the height of the GNSS antenna over the reflecting surface using signal to noise ratio data. Signals from the Global Positioning System, Glonass, Galileo, and Beidou constellations are supported. Modules are provided to estimate volumetric water content of soil, snow depth/accumulation, and water level. Utilities for mapping and assessing reflection zones and determining the maximum resolvable height are available.},
	language = {en},
	number = {4},
	urldate = {2024-08-20},
	journal = {GPS Solutions},
	author = {Larson, Kristine M.},
	month = oct,
	year = {2024},
	pages = {165},
}









@article{springer_regionally_2024,
	title = {A {Regionally} {Refined} and {Mass}‐{Consistent} {Atmospheric} and {Hydrological} {De}‐{Aliasing} {Product} for {GRACE}, {GRACE}‐{FO} and {Future} {Gravity} {Missions}},
	volume = {129},
	issn = {2169-9313, 2169-9356},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883},
	doi = {10.1029/2023JB027883},
	abstract = {Abstract
            De‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de‐aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de‐aliasing products by nesting a regional high‐resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de‐aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3‐hourly data, our investigations suggest that contributions from continental hydrology and from regional non‐hydrostatic atmospheric modeling to sub‐monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions.
          , 
            Plain Language Summary
            Observing temporal variations in the Earth's gravity field with satellite gravimetry plays an essential role for monitoring mass transports on and underneath the Earth's surface. This is crucial for understanding the evolution of floods and droughts, the role of groundwater pumping, and to quantify the melting of ice sheets and glaciers and the resulting sea level rise. In order to isolate the target variable (e.g., terrestrial water storage changes) unwanted signals (e.g., fast mass variations in the atmosphere) need to be removed in the gravity field estimation process using background models, so‐called de‐aliasing models. This paper focuses on improving background models by incorporating regional high‐resolution models, which more specifically resolve certain processes in the atmosphere. Our hypothesis is that this will lead to better gravity fields with increased spatial resolution and less noise. Moreover, we find that considering fast hydrological variations as additional background model could improve gravity fields from the current satellite mission GRACE‐FO. For the first time, we quantify contributions from so far neglected atmospheric moisture fields, such as cloud liquid water, to enhance background models in the context of extreme events—which, however, will likely be in particular relevant for more sensitive gravity missions in the future.
          , 
            Key Points
            
              
                
                  We provide an atmosphere‐hydrology de‐aliasing product with regional mass‐consistent refinement over Europe
                
                
                  Using non‐hydrostatic as opposed to hydrostatic numerical weather prediction model output significantly impacts the de‐aliasing product
                
                
                  We found that for extreme events additional moisture fields unaccounted in present Atmosphere and Ocean De‐aliasing (AOD) models can reach magnitudes relevant for de‐aliasing},
	language = {en},
	number = {5},
	urldate = {2024-07-23},
	journal = {Journal of Geophysical Research: Solid Earth},
	author = {Springer, Anne and Mielke, Christian A. and Liu, Ziyu and Dixit, Shashi and Friederichs, Petra and Kusche, Jürgen},
	month = may,
	year = {2024},
	pages = {e2023JB027883},
}





@article{martre_global_2024,
	title = {Global needs for nitrogen fertilizer to improve wheat yield under climate change},
	issn = {2055-0278},
	url = {https://www.nature.com/articles/s41477-024-01739-3},
	doi = {10.1038/s41477-024-01739-3},
	language = {en},
	urldate = {2024-07-22},
	journal = {Nature Plants},
	author = {Martre, Pierre and Dueri, Sibylle and Guarin, Jose Rafael and Ewert, Frank and Webber, Heidi and Calderini, Daniel and Molero, Gemma and Reynolds, Matthew and Miralles, Daniel and Garcia, Guillermo and Brown, Hamish and George, Mike and Craigie, Rob and Cohan, Jean-Pierre and Deswarte, Jean-Charles and Slafer, Gustavo and Giunta, Francesco and Cammarano, Davide and Ferrise, Roberto and Gaiser, Thomas and Gao, Yujing and Hochman, Zvi and Hoogenboom, Gerrit and Hunt, Leslie A. and Kersebaum, Kurt C. and Nendel, Claas and Padovan, Gloria and Ruane, Alex C. and Srivastava, Amit Kumar and Stella, Tommaso and Supit, Iwan and Thorburn, Peter and Wang, Enli and Wolf, Joost and Zhao, Chuang and Zhao, Zhigan and Asseng, Senthold},
	month = jul,
	year = {2024},
}









@article{chen_convectionpermitting_2024,
	title = {Convection‐{Permitting} {ICON}‐{LAM} {Simulations} for {Renewable} {Energy} {Potential} {Estimates} {Over} {Southern} {Africa}},
	volume = {129},
	issn = {2169-897X, 2169-8996},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569},
	doi = {10.1029/2023JD039569},
	abstract = {Abstract
            
              Renewable energy is recognized in Africa as a means for climate change mitigation, but also to provide access to electricity in sub‐Saharan Africa, where three‐quarters of the global population without electricity resides. Reliable and highly resolved renewable energy potential (REP) information is indispensable to support power plants expansion. Existing atmospheric data sets over Africa that are used for REP estimates are often characterized by data gaps, or coarse resolution. With the aim to overcome these challenges, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON‐NWP) model in its Limited Area Mode (ICON‐LAM) is implemented and run over southern Africa in a hindcast dynamical downscaling setup at a convection‐permitting 3.3 km horizontal resolution. The simulation time span covers contrasting solar and wind weather years from 2017 to 2019. To assess the suitability of the novel simulations for REP estimates, the simulated hourly 10 m wind speed (sfcWind) and hourly surface solar irradiance (rsds) are extensively evaluated against a large compilation of in situ observations, satellite, and composite data products. ICON‐LAM reproduces the spatial patterns, temporal evolution, the variability, and absolute values of sfcWind sufficiently well, albeit with a slight overestimation and a mean bias (mean error (ME)) of 1.12 m s
              −1
              over land. Likewise the simulated rsds with an ME of 50 W m
              −2
              well resembles the observations. This new ICON simulation data product will be the basis for ensuing REP estimates that will be compared with existing lower resolution data sets.
            
          , 
            Plain Language Summary
            There are still approximately 580 million people in Africa without reliable electricity supply. Renewable energy is broadly accepted as an important solution for Africa to fill the power supply gap and to mitigate climate change. Renewable energy potential (REP) information is thereby imperative for the expansion of renewable energy power planning. With conventional REP estimates, challenges are often linked to the meteorological input data, due to either the relatively coarse spatial resolution, data gaps in space and time, or data quality in general. In this study, we implemented and ran the atmospheric model ICOsahedral Nonhydrostatic (ICON) from the German Weather Service and partners at 3 km high‐resolution. The renewable energy variables wind speed and solar irradiance from these simulations are evaluated against an extensive in situ observations data set, as well as satellite, and other composite data products. In a comparison with more than 200 stations from three different in situ observation networks, it can be shown that ICON can reproduce REP‐related variables with a level of sophistication that the data is likely to offer added value over conventional inputs to REP assessments. The study is an example on how numerical models can fill in gaps in data‐scarce regions to produce useable information.
          , 
            Key Points
            
              
                
                  A new convection‐permitting regional ICOsahedral Nonhydrostatic (ICON) model setup over southern Africa is presented and evaluated
                
                
                  The spatially and temporally highly resolved ICON wind and solar fields are inputs for improved renewable energy potential estimates
                
                
                  ICON outputs agree well with hourly in situ observations and satellite data; wind speeds are slightly overestimated},
	language = {en},
	number = {6},
	urldate = {2024-07-10},
	journal = {Journal of Geophysical Research: Atmospheres},
	author = {Chen, Shuying and Poll, Stefan and Hendricks Franssen, Harrie‐Jan and Heinrichs, Heidi and Vereecken, Harry and Goergen, Klaus},
	month = mar,
	year = {2024},
	pages = {e2023JD039569},
}





@article{storm_probabilistic_2024,
	title = {Probabilistic programming for embedding theory and quantifying uncertainty in econometric analysis},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {0165-1587, 1464-3618},
	url = {https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545},
	doi = {10.1093/erae/jbae016},
	abstract = {Abstract
            The replication crisis in empirical research calls for a more mindful approach to how we apply and report statistical models. For empirical research to have a lasting (policy) impact, these concerns are crucial. In this paper, we present Probabilistic Programming (PP) as a way forward. The PP workflow with an explicit data-generating process enhances the communication of model assumptions, code testing and consistency between theory and estimation. By simplifying Bayesian analysis, it also offers advantages for the interpretation, communication and modelling of uncertainty. We outline the advantages of PP to encourage its adoption in our community.},
	language = {en},
	urldate = {2024-07-10},
	journal = {European Review of Agricultural Economics},
	author = {Storm, Hugo and Heckelei, Thomas and Baylis, Kathy},
	month = jul,
	year = {2024},
	pages = {jbae016},
}









@article{fiedler_interactions_2024,
	title = {Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from {AerChemMIP}, {PDRMIP}, and {RFMIP}},
	volume = {17},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {1991-9603},
	url = {https://gmd.copernicus.org/articles/17/2387/2024/},
	doi = {10.5194/gmd-17-2387-2024},
	abstract = {Abstract. The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.},
	language = {en},
	number = {6},
	urldate = {2024-06-26},
	journal = {Geoscientific Model Development},
	author = {Fiedler, Stephanie and Naik, Vaishali and O'Connor, Fiona M. and Smith, Christopher J. and Griffiths, Paul and Kramer, Ryan J. and Takemura, Toshihiko and Allen, Robert J. and Im, Ulas and Kasoar, Matthew and Modak, Angshuman and Turnock, Steven and Voulgarakis, Apostolos and Watson-Parris, Duncan and Westervelt, Daniel M. and Wilcox, Laura J. and Zhao, Alcide and Collins, William J. and Schulz, Michael and Myhre, Gunnar and Forster, Piers M.},
	month = mar,
	year = {2024},
	pages = {2387--2417},
}









@article{baca_cabrera_root_2024,
	title = {Root hydraulic properties: {An} exploration of their variability across scales},
	volume = {8},
	issn = {2475-4455, 2475-4455},
	shorttitle = {Root hydraulic properties},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/pld3.582},
	doi = {10.1002/pld3.582},
	abstract = {Abstract
            Root hydraulic properties are key physiological traits that determine the capacity of root systems to take up water, at a specific evaporative demand. They can strongly vary among species, cultivars or even within the same genotype, but a systematic analysis of their variation across plant functional types (PFTs) is still missing. Here, we reviewed published empirical studies on root hydraulic properties at the segment‐, individual root‐, or root system scale and determined its variability and the main factors contributing to it. This corresponded to a total of 241 published studies, comprising 213 species, including woody and herbaceous vegetation.
            
              We observed an extremely large range of variation (of orders of magnitude) in root hydraulic properties, but this was not caused by systematic differences among PFTs. Rather, the (combined) effect of factors such as root system age, driving force used for measurement, or stress treatments shaped the results. We found a significant decrease in root hydraulic properties under stress conditions (drought and aquaporin inhibition,
              p
               {\textless} .001) and a significant effect of the driving force used for measurement (hydrostatic or osmotic gradients,
              p
               {\textless} .001). Furthermore, whole root system conductance increased significantly with root system age across several crop species (
              p
               {\textless} .01), causing very large variation in the data ({\textgreater}2 orders of magnitude). Interestingly, this relationship showed an asymptotic shape, with a steep increase during the first days of growth and a flattening out at later stages of development. We confirmed this dynamic through simulations using a state‐of‐the‐art computational model of water flow in the root system for a variety of crop species, suggesting common patterns across studies and species.
            
            
              These findings provide better understanding of the main causes of root hydraulic properties variations observed across empirical studies. They also open the door to better representation of hydraulic processes across multiple plant functional types and at large scales. All data collected in our analysis has been aggregated into an open access database (
              https://roothydraulic-properties.shinyapps.io/database/
              ), fostering scientific exchange.},
	language = {en},
	number = {4},
	urldate = {2024-04-25},
	journal = {Plant Direct},
	author = {Baca Cabrera, Juan C. and Vanderborght, Jan and Couvreur, Valentin and Behrend, Dominik and Gaiser, Thomas and Nguyen, Thuy Huu and Lobet, Guillaume},
	month = apr,
	year = {2024},
	pages = {e582},
}









@article{shams_eddin_focal-tsmp_2024,
	title = {Focal-{TSMP}: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation},
	volume = {17},
	copyright = {https://creativecommons.org/licenses/by/4.0/},
	issn = {1991-9603},
	shorttitle = {Focal-{TSMP}},
	url = {https://gmd.copernicus.org/articles/17/2987/2024/},
	doi = {10.5194/gmd-17-2987-2024},
	abstract = {Abstract. Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model’s applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP, last access: 4 April 2024).},
	language = {en},
	number = {7},
	urldate = {2024-04-25},
	journal = {Geoscientific Model Development},
	author = {Shams Eddin, Mohamad Hakam and Gall, Juergen},
	month = apr,
	year = {2024},
	pages = {2987--3023},
}





@article{gu_asymmetric_2024,
	title = {The asymmetric impacts of international agricultural trade on water use scarcity, inequality and inequity},
	issn = {2731-6084},
	url = {https://www.nature.com/articles/s44221-024-00224-7},
	doi = {10.1038/s44221-024-00224-7},
	language = {en},
	urldate = {2024-04-25},
	journal = {Nature Water},
	author = {Gu, Weiyi and Wang, Fang and Siebert, Stefan and Kummu, Matti and Wang, Xuhui and Hong, Chaopeng and Zhou, Feng and Zhu, Qing and Liu, Yong and Qin, Yue},
	month = apr,
	year = {2024},
}









@article{shams_eddin_location-aware_2023,
	title = {Location-{Aware} {Adaptive} {Normalization}: {A} {Deep} {Learning} {Approach} for {Wildfire} {Danger} {Forecasting}},
	volume = {61},
	copyright = {https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html},
	issn = {0196-2892, 1558-0644},
	shorttitle = {Location-{Aware} {Adaptive} {Normalization}},
	url = {https://ieeexplore.ieee.org/document/10149031/},
	doi = {10.1109/TGRS.2023.3285401},
	urldate = {2024-04-25},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	author = {Shams Eddin, Mohamad Hakam and Roscher, Ribana and Gall, Juergen},
	year = {2023},
	pages = {1--18},
}





@article{mehta_half_2024,
	title = {Half of twenty-first century global irrigation expansion has been in water-stressed regions},
	issn = {2731-6084},
	url = {https://www.nature.com/articles/s44221-024-00206-9},
	doi = {10.1038/s44221-024-00206-9},
	abstract = {Abstract
            The expansion of irrigated agriculture has increased global crop production but resulted in widespread stress on freshwater resources. Ensuring that increases in irrigated production occur only in places where water is relatively abundant is a key objective of sustainable agriculture and knowledge of how irrigated land has evolved is important for measuring progress towards water sustainability. Yet, a spatially detailed understanding of the evolution of the global area equipped for irrigation (AEI) is missing. In this study, we used the latest subnational irrigation statistics (covering 17,298 administrative units) from various official sources to develop a gridded (5 arcmin resolution) global product of AEI for the years 2000, 2005, 2010 and 2015. We found that AEI increased by 11\% from 2000 (297 Mha) to 2015 (330 Mha), with areas of both substantial expansion, such as northwest India and northeast China, and decline, such as Russia. Combining these outputs with information on green (that is, rainfall) and blue (that is, surface and ground) water stress, we also examined to what extent irrigation has expanded unsustainably in places already experiencing water stress. We found that more than half (52\%) of the irrigation expansion has taken place in areas that were already water-stressed in the year 2000, with India alone accounting for 36\% of global unsustainable expansion. These findings provide new insights into the evolving patterns of global irrigation with important implications for global water sustainability and food security.},
	language = {en},
	urldate = {2024-03-11},
	journal = {Nature Water},
	author = {Mehta, Piyush and Siebert, Stefan and Kummu, Matti and Deng, Qinyu and Ali, Tariq and Marston, Landon and Xie, Wei and Davis, Kyle Frankel},
	month = mar,
	year = {2024},
}





@article{strebel_evapotranspiration_2024,
	title = {Evapotranspiration prediction for {European} forest sites does not improve with assimilation of in situ soil water content data},
	volume = {28},
	issn = {1607-7938},
	url = {https://hess.copernicus.org/articles/28/1001/2024/},
	doi = {10.5194/hess-28-1001-2024},
	abstract = {Abstract. Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSMs with observations, data assimilation methods and tools have been developed in the past decades. We apply the coupled Community Land Model version 5 (CLM5) and Parallel Data Assimilation Framework (PDAF) system (CLM5-PDAF) for 13 forest field sites throughout Europe covering different climate zones. The goal of this study is to assimilate in situ soil moisture measurements into CLM5 to improve the modeled evapotranspiration fluxes. The modeled fluxes will be evaluated using the predicted evapotranspiration fluxes with eddy covariance (EC) systems. Most of the sites use point-scale measurements from sensors placed in the ground; however, for three of the forest sites we use soil water content data from cosmic-ray neutron sensors, which have a measurement scale closer to the typical land surface model grid scale and EC footprint. Our results show that while data assimilation reduced the root-mean-square error for soil water content on average by 56 \% to 64 \%, the root-mean-square error for the evapotranspiration estimation is increased by 4 \%. This finding indicates that only improving the soil water content (SWC) estimation of state-of-the-art LSMs such as CLM5 is not sufficient to improve evapotranspiration estimates for forest sites. To improve evapotranspiration estimates, it is also necessary to consider the representation of leaf area index (LAI) in magnitude and timing, as well as uncertainties in water uptake by roots and vegetation parameters.},
	language = {en},
	number = {4},
	urldate = {2024-03-05},
	journal = {Hydrology and Earth System Sciences},
	author = {Strebel, Lukas and Bogena, Heye and Vereecken, Harry and Andreasen, Mie and Aranda-Barranco, Sergio and Hendricks Franssen, Harrie-Jan},
	month = feb,
	year = {2024},
	pages = {1001--1026},
}





@article{yang_study_2022,
	title = {On study of the {Earth} topography correction for the {GRACE} surface mass estimation},
	volume = {96},
	issn = {0949-7714, 1432-1394},
	url = {https://link.springer.com/10.1007/s00190-022-01683-0},
	doi = {10.1007/s00190-022-01683-0},
	language = {en},
	number = {12},
	urldate = {2024-03-05},
	journal = {Journal of Geodesy},
	author = {Yang, Fan and Luo, ZhiCai and Zhou, Hao and Kusche, Jürgen},
	month = dec,
	year = {2022},
	pages = {95},
}









@article{qin_snowmelt_2022,
	title = {Snowmelt risk telecouplings for irrigated agriculture},
	volume = {12},
	issn = {1758-678X, 1758-6798},
	url = {https://www.nature.com/articles/s41558-022-01509-z},
	doi = {10.1038/s41558-022-01509-z},
	language = {en},
	number = {11},
	urldate = {2024-03-05},
	journal = {Nature Climate Change},
	author = {Qin, Yue and Hong, Chaopeng and Zhao, Hongyan and Siebert, Stefan and Abatzoglou, John T. and Huning, Laurie S. and Sloat, Lindsey L. and Park, Sohyun and Li, Shiyu and Munroe, Darla K. and Zhu, Tong and Davis, Steven J. and Mueller, Nathaniel D.},
	month = nov,
	year = {2022},
	pages = {1007--1015},
}









@article{boroughani_mapping_2023,
	title = {Mapping land degradation risk due to land susceptibility to dust emission and water erosion},
	volume = {9},
	issn = {2199-398X},
	url = {https://soil.copernicus.org/articles/9/411/2023/},
	doi = {10.5194/soil-9-411-2023},
	abstract = {Abstract. Land degradation is a cause of many social, economic, and environmental
problems. Therefore identification and monitoring of high-risk areas for
land degradation are necessary. Despite the importance of land degradation
due to wind and water erosion in some areas of the world, the combined study
of both types of erosion in the same area receives relatively little
attention. The present study aims to create a land degradation map in terms
of soil erosion caused by wind and water erosion of semi-dry land. We focus
on the Lut watershed in Iran, encompassing the Lut Desert that is influenced
by both monsoon rainfalls and dust storms. Dust sources are identified using
MODIS satellite images with the help of four different indices to quantify
uncertainty. The dust source maps are assessed with three machine learning
algorithms encompassing the artificial neural network (ANN), random forest (RF),
and flexible discriminant analysis (FDA) to map dust sources paired with
soil erosion susceptibility due to water. We assess the accuracy of the maps
from the machine learning results with the area under the curve (AUC)
of the receiver operating characteristic (ROC) metric. The water and aeolian soil
erosion maps are used to identify different classes of land degradation
risks. The results show that 43 \% of the watershed is prone to land
degradation in terms of both aeolian and water erosion. Most regions
(45 \%) have a risk of water erosion and some regions (7 \%) a risk of
aeolian erosion. Only a small fraction (4 \%) of the total area of the
region had a low to very low susceptibility for land degradation. The
results of this study underline the risk of land degradation for in an
inhabited region in Iran. Future work should focus on land degradation
associated with soil erosion from water and storms in larger regions to
evaluate the risks also elsewhere.},
	language = {en},
	number = {2},
	urldate = {2024-02-26},
	journal = {SOIL},
	author = {Boroughani, Mahdi and Mirchooli, Fahimeh and Hadavifar, Mojtaba and Fiedler, Stephanie},
	month = jul,
	year = {2023},
	pages = {411--423},
}









@article{li_can_2024,
	title = {Can a {Sparse} {Network} of {Cosmic} {Ray} {Neutron} {Sensors} {Improve} {Soil} {Moisture} and {Evapotranspiration} {Estimation} at the {Larger} {Catchment} {Scale}?},
	volume = {60},
	issn = {0043-1397, 1944-7973},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056},
	doi = {10.1029/2023WR035056},
	abstract = {Abstract
            Cosmic‐ray neutron sensors (CRNS) fill the gap between locally measured in‐situ soil moisture (SM) and remotely sensed SM by providing accurate SM estimation at the field scale. This is promising for improving hydrologic model predictions, as CRNS can provide valuable information on SM in the root zone at the typical scale of a model grid cell. In this study, SM measurements from a network of 12 CRNS in the Rur catchment (Germany) were assimilated into the Terrestrial System Modeling Platform (TSMP) to investigate its potential for improving SM, evapotranspiration (ET) and river discharge characterization and estimating soil hydraulic parameters at the larger catchment scale. The data assimilation (DA) experiments (with and without parameter estimation) were conducted in both a wet year (2016) and a dry year (2018) with the ensemble Kalman filter (EnKF), and later verified with an independent year (2017) without DA. The results show that SM characterization was significantly improved at measurement locations (with up to 60\% root mean square error (RMSE) reduction), and that joint state‐parameter estimation improved SM simulation more than state estimation alone (more than 15\% additional RMSE reduction). Jackknife experiments showed that SM at verification locations had lower and different improvements in the wet and dry years (an RMSE reduction of 40\% in 2016 and 16\% in 2018). In addition, SM assimilation was found to improve ET characterization to a much lesser extent, with a 15\% RMSE reduction of monthly ET in the wet year and 9\% in the dry year.
          , 
            Key Points
            
              
                
                  Assimilation of soil moisture from a network of cosmic‐ray neutron sensors improves soil moisture characterization at the catchment scale
                
                
                  Soil moisture characterization improved more in a wet year than in a very dry year
                
                
                  Evapotranspiration and river discharge simulation are only slightly improved, despite better estimations of soil moisture},
	language = {en},
	number = {1},
	urldate = {2024-02-26},
	journal = {Water Resources Research},
	author = {Li, Fang and Bogena, Heye Reemt and Bayat, Bagher and Kurtz, Wolfgang and Hendricks Franssen, Harrie‐Jan},
	month = jan,
	year = {2024},
	pages = {e2023WR035056},
}









@article{yu_detailed_2023,
	title = {A detailed analysis of stochastic models applied to temporal gravity field recovery with {GRACE} observations},
	volume = {236},
	issn = {0956-540X, 1365-246X},
	url = {https://academic.oup.com/gji/article/236/1/516/7382201},
	doi = {10.1093/gji/ggad441},
	abstract = {SUMMARY
            In this study, we analysed the impacts of errors in background force models and observed non-gravitational forces on the pseudo-observations (pre-fits) during gravity field recovery based on the Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission. To reduce these effects, we introduced the stochastic parameters into the functional model of the variational equation integration approach to absorb this type of noise contribution. Simultaneously, the prior variances of observed orbits and K-band range rates used in traditional method are re-estimated with least-squares variance component estimation (LS-VCE) after considering these stochastic parameters. To improve the computing efficiency, a modified method of the calculation of sensitivity matrices related to the introduced stochastic parameters is proposed. Compared to the method of variation of constants widely used in the precise orbit determination and gravity field recovery, the modified method decreases the computational time of these matrices by about four times. Furthermore, an efficient LS-VCE algorithm is derived in a more generalized case. The efficient algorithm only costs 1 per cent of the time of the unoptimized method. With the GRACE data, we analysed the benefits of these refinements in gravity field recovery, and the results show that these improvements can mitigate the impacts of errors in background force models and accelerometer data on recovered gravity field models, especially in the high-degree signals. Furthermore, the quality of results has less dependence on parametrization.},
	language = {en},
	number = {1},
	urldate = {2024-02-26},
	journal = {Geophysical Journal International},
	author = {Yu, Biao and You, Wei and Kusche, Jürgen and Fan, Dongming and Su, Yong and Zhang, Jiahui},
	month = nov,
	year = {2023},
	pages = {516--536},
}









@article{vanderborght_combining_2023,
	title = {Combining root and soil hydraulics in macroscopic representations of root water uptake},
	issn = {1539-1663, 1539-1663},
	url = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273},
	doi = {10.1002/vzj2.20273},
	abstract = {Abstract
            Plant water uptake and plant and soil water status are important for the soil water balance and plant growth. They depend on atmospheric water demand and the accessibility of soil water to plant roots, which is in turn related to the hydraulic properties of the root system and the soil around root segments. We present a simulation model that describes water flow in the soil–plant system mechanistically considering both root and soil hydraulic properties. We developed an approach to upscale three‐dimensional (3D) flow in the soil toward root segments of a 3D root architecture to a model that considers one‐dimensional flow between horizontal soil layers and radial flow to root segments in that layer. The upscaled model couples upscaled linear flow equations in the root system with an analytical solution of the nonlinear radial flow equation between the soil and roots. The upscaled model avoids simplifying assumptions about root hydraulic properties and water potential drops near roots made in, respectively, soil‐ and root‐centered models. Xylem water potentials and soil–root interface potentials are explicitly simulated and show, respectively, large variations with depth and large deviations from bulk soil water potentials under dry soil conditions. Accounting for hydraulic gradients in the soil around root segments led to an earlier but slower reduction of transpiration during a drought period and a better plant water status with higher nighttime plant water potentials.
          , 
            Core Ideas
            
              
                
                  Root water uptake depends on root and soil hydraulic properties.
                
                
                  Water uptake at root element scale was upscaled to the root system scale.
                
                
                  The upscaled model can be implemented in one‐dimensional soil water flow models.
                
                
                  Low conductance of dry soil prevents low nighttime plant water potentials.},
	language = {en},
	urldate = {2024-01-29},
	journal = {Vadose Zone Journal},
	author = {Vanderborght, Jan and Leitner, Daniel and Schnepf, Andrea and Couvreur, Valentin and Vereecken, Harry and Javaux, Mathieu},
	month = jul,
	year = {2023},
	pages = {e20273},
}





@incollection{andres_probabilistic_2022,
	address = {Cham},
	title = {Probabilistic {Biomass} {Estimation} with {Conditional} {Generative} {Adversarial} {Networks}},
	volume = {13485},
	isbn = {978-3-031-16787-4 978-3-031-16788-1},
	url = {https://link.springer.com/10.1007/978-3-031-16788-1_29},
	language = {en},
	urldate = {2023-11-27},
	booktitle = {Pattern {Recognition}},
	publisher = {Springer International Publishing},
	author = {Leonhardt, Johannes and Drees, Lukas and Jung, Peter and Roscher, Ribana},
	editor = {Andres, Björn and Bernard, Florian and Cremers, Daniel and Frintrop, Simone and Goldlücke, Bastian and Ihrke, Ivo},
	year = {2022},
	doi = {10.1007/978-3-031-16788-1_29},
	note = {Series Title: Lecture Notes in Computer Science},
	pages = {479--494},
}





@incollection{schimmel_organic_2023,
	title = {Organic soils},
	isbn = {978-0-323-95133-3},
	url = {https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732},
	language = {en},
	urldate = {2023-11-27},
	booktitle = {Encyclopedia of {Soils} in the {Environment}},
	publisher = {Elsevier},
	author = {Schimmel, Heike and Amelung, Wulf},
	year = {2023},
	doi = {10.1016/B978-0-12-822974-3.00073-2},
	pages = {383--397},
}





@article{chen_evaluation_2023,
	title = {Evaluation of {Sentinel}-{3A} altimetry over {Songhua} river {Basin}},
	volume = {618},
	issn = {00221694},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397},
	doi = {10.1016/j.jhydrol.2023.129197},
	language = {en},
	urldate = {2023-10-31},
	journal = {Journal of Hydrology},
	author = {Chen, Jiaming and Fenoglio, Luciana and Kusche, Jürgen and Liao, Jingjuan and Uyanik, Hakan and Nadzir, Zulfikar Adlan and Lou, Yanhan},
	month = mar,
	year = {2023},
	pages = {129197},
}





@article{guntner_veranderungen_2023,
	title = {Veränderungen der {Wasserspeicherung} in {Deutschland} seit 2002 aus {Beobachtungen} der {Satellitengravimetrie} – {Water} storage changes in {Germany} since 2002 from satellite gravity observations},
	issn = {1439-1783},
	url = {https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf},
	doi = {10.5675/HYWA_2023.2_1},
	urldate = {2023-10-30},
	journal = {Hydrologie und Wasserbewirtschaftung},
	author = {Güntner, Andreas and Gerdener, Helena and Boergens, Eva and Kusche, Jürgen and Kollet, Stefan and Dobslaw, Henryk and Hartick, Carl and Sharifi, Ehsan and Flechtner, Frank},
	year = {2023},
	note = {Publisher: Bundesanstalt für Gewässerkunde, Koblenz},
}









@article{enders_simplaceversatile_2023,
	title = {{SIMPLACE}—a versatile modelling and simulation framework for sustainable crops and agroecosystems},
	volume = {5},
	issn = {2517-5025},
	url = {https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223},
	doi = {10.1093/insilicoplants/diad006},
	abstract = {Abstract
            Agricultural system analysis has considerably evolved over the last years, allowing scientists to quantify complex interactions in crops and agroecosystems. Computer-based models have become a central tool for such analysis, using formulated mathematical representations (algorithms) of different biophysical processes to simulate complex system’s behaviour. Nevertheless, the current large variety of algorithms in combination with nonstandardization in their use limits rapid and rigorous model improvement and testing. This is particularly important because contextualization is a key aspect used to formulate the appropriate model structure for a specific research question, framing a clear demand for ‘next generation’ models being modular and flexible. This paper aims to describe the Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE), which has been developed over the last decade to address the various aforementioned issues and support appropriate model formulations and interoperability. We describe its main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems with high flexibility, performance and transparency. A brief review of exemplary applications of SIMPLACE is provided covering the different topics, crops and cropping systems, spatial scales and geographies. We stress that standardized documentation of modules, variables ontology and data archives are key requirements to maintain and assist model development and reproducibility. The increasing demand for more complex, diversified and integrated production systems (e.g. intercropping, livestock-grazing, agroforestry) and the associated impacts on sustainable food systems also require the strong collaboration of a multidisciplinary community of modellers and stakeholders.},
	language = {en},
	number = {1},
	urldate = {2023-10-30},
	journal = {in silico Plants},
	author = {Enders, Andreas and Vianna, Murilo and Gaiser, Thomas and Krauss, Gunther and Webber, Heidi and Srivastava, Amit Kumar and Seidel, Sabine Julia and Tewes, Andreas and Rezaei, Ehsan Eyshi and Ewert, Frank},
	editor = {Marshall-Colon, Amy},
	month = jan,
	year = {2023},
	pages = {diad006},
}









@article{graf_joint_2023,
	title = {Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects},
	volume = {4},
	issn = {2662-4435},
	url = {https://www.nature.com/articles/s43247-023-00958-4},
	doi = {10.1038/s43247-023-00958-4},
	abstract = {Abstract
            Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.},
	language = {en},
	number = {1},
	urldate = {2023-10-30},
	journal = {Communications Earth \& Environment},
	author = {Graf, Alexander and Wohlfahrt, Georg and Aranda-Barranco, Sergio and Arriga, Nicola and Brümmer, Christian and Ceschia, Eric and Ciais, Philippe and Desai, Ankur R. and Di Lonardo, Sara and Gharun, Mana and Grünwald, Thomas and Hörtnagl, Lukas and Kasak, Kuno and Klosterhalfen, Anne and Knohl, Alexander and Kowalska, Natalia and Leuchner, Michael and Lindroth, Anders and Mauder, Matthias and Migliavacca, Mirco and Morel, Alexandra C. and Pfennig, Andreas and Poorter, Hendrik and Terán, Christian Poppe and Reitz, Oliver and Rebmann, Corinna and Sanchez-Azofeifa, Arturo and Schmidt, Marius and Šigut, Ladislav and Tomelleri, Enrico and Yu, Ke and Varlagin, Andrej and Vereecken, Harry},
	month = aug,
	year = {2023},
	pages = {298},
}









@article{li_water_2023,
	title = {Water table depth assimilation in integrated terrestrial system models at the larger catchment scale},
	volume = {5},
	issn = {2624-9375},
	url = {https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full},
	doi = {10.3389/frwa.2023.1150999},
	abstract = {As an important source of water for human beings, groundwater plays a significant role in human production and life. However, different sources of uncertainty may lead to unsatisfactory simulations of groundwater hydrodynamics with hydrological models. The goal of this study is to investigate the impact of assimilating groundwater data into the Terrestrial System Modeling Platform (TSMP) for improving hydrological modeling in a real-world case. Daily groundwater table depth (WTD) measurements from the year 2018 for the Rur catchment in Germany were assimilated by the Localized Ensemble Kalman Filter (LEnKF) into TSMP. The LEnKF is used with a localization radius so that the assimilated measurements only update model states in a limited radius around the measurements, in order to avoid unphysical updates related to spurious correlations. Due to the mismatch between groundwater measurements and the coarse model resolution (500 m), the measurements need careful screening before data assimilation (DA). Based on the spatial autocorrelation of the WTD deduced from the measurements, three different filter localization radii (2.5, 5, and 10 km) were evaluated for assimilation. The bias in the simulated water table and the root mean square error (RMSE) are reduced after DA, compared with runs without DA [i.e., open loop (OL) runs]. The best results at the assimilated locations are obtained for a localization radius of 10 km, with an 81\% reduction of RMSE at the measurement locations, and slightly smaller RMSE reductions for the 5 and 2.5 km radius. The validation with independent WTD data showed the best results for a localization radius of 10 km, but groundwater table characterization could only be improved for sites \&lt;2.5 km from measurement locations. In case of a localization radius of 10 km the RMSE-reduction was 30\% for those nearby sites. Simulated soil moisture was validated against soil moisture measured by cosmic-ray neutron sensors (CRNS), but no RMSE reduction was observed for DA-runs compared to OL-run. However, in both cases, the correlation between measured and simulated soil moisture content was high (between 0.70 and 0.89, except for the Wuestebach site).},
	urldate = {2023-10-30},
	journal = {Frontiers in Water},
	author = {Li, Fang and Kurtz, Wolfgang and Hung, Ching Pui and Vereecken, Harry and Hendricks Franssen, Harrie-Jan},
	month = mar,
	year = {2023},
	pages = {1150999},
}





@article{qu_wildfire_2023,
	title = {Wildfire precursors show complementary predictability in different timescales},
	volume = {14},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-023-42597-5},
	doi = {10.1038/s41467-023-42597-5},
	abstract = {Abstract
            In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3\% and 26.7\% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.},
	language = {en},
	number = {1},
	urldate = {2023-10-30},
	journal = {Nature Communications},
	author = {Qu, Yuquan and Miralles, Diego G. and Veraverbeke, Sander and Vereecken, Harry and Montzka, Carsten},
	month = oct,
	year = {2023},
	pages = {6829},
}









@article{mohseni_synergies_2023,
	title = {The synergies of {SMAP} enhanced and {MODIS} products in a random forest regression for estimating 1 km soil moisture over {Africa} using {Google} {Earth} {Engine}},
	issn = {2096-4471, 2574-5417},
	url = {https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905},
	doi = {10.1080/20964471.2023.2257905},
	language = {en},
	urldate = {2023-10-30},
	journal = {Big Earth Data},
	author = {Mohseni, Farzane and Ahrari, Amirhossein and Haunert, Jan-Henrik and Montzka, Carsten},
	month = sep,
	year = {2023},
	pages = {1--25},
}





@article{klos_introducing_2023,
	title = {Introducing the {Idea} of {Classifying} {Sets} of {Permanent} {GNSS} {Stations} as {Benchmarks} for {Hydrogeodesy}},
	volume = {128},
	issn = {2169-9313, 2169-9356},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988},
	doi = {10.1029/2023JB026988},
	abstract = {Abstract
            We propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal‐scales: short‐term, seasonal and long‐term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998–2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre‐defined temporal‐scales of short‐term, seasonal and long‐term, using non‐parametric wavelet analysis. For each temporal‐scale, correlation coefficients are computed between GNSS‐measured and GRACE‐derived/GLWS‐predicted displacements. We present the benefits of applying high‐resolution GRACE‐assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15\% for short‐term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake‐affected sites and those where a possible poroelastic response is observed.
          , 
            Plain Language Summary
            Displacements of the Earth's crust measured by permanent Global Navigation Satellite System (GNSS) ground stations are used for many geophysical interpretations. However, it is common to omit the evaluation of the sensitivity of the system to the measurement of displacements from different sources, assuming in advance 100\% sensitivity of the system to a given effect. Consequently, the fact that at a given station several effects can be recorded simultaneously is overlooked. This is particularly evident in earthquake‐affected areas, where GNSS stations are excluded from most analyses of non‐tectonic effects. We solve this problem and propose to divide GNSS stations into trusted sets, which we call benchmarks. Benchmarking is performed by indicating the stations that are certain to register a given effect in three pre‐defined temporal‐scales: short‐term, seasonal and long‐term. We present the analysis for the Amazon area, known for its large hydrosphere‐related signal, and demonstrate that the benchmarking allows for the inclusion of GNSS stations that were previously omitted in analyses of this type.
          , 
            Key Points
            
              
                
                  Displacements measured by Global Positioning System (GPS) correlate well with surface water levels derived from radar altimetry missions
                
                
                  Trusted sets of GPS stations are classified at the three pre‐defined temporal‐scales: short‐term, seasonal and long‐term
                
                
                  Benchmarking allows to include more GPS stations in hydrogeodetic analyses},
	language = {en},
	number = {9},
	urldate = {2023-10-30},
	journal = {Journal of Geophysical Research: Solid Earth},
	author = {Klos, A. and Kusche, J. and Leszczuk, G. and Gerdener, H. and Schulze, K. and Lenczuk, A. and Bogusz, J.},
	month = sep,
	year = {2023},
	pages = {e2023JB026988},
}









@article{gerdener_global_2023,
	title = {The global land water storage data set release 2 ({GLWS2}.0) derived via assimilating {GRACE} and {GRACE}-{FO} data into a global hydrological model},
	volume = {97},
	issn = {0949-7714, 1432-1394},
	url = {https://link.springer.com/10.1007/s00190-023-01763-9},
	doi = {10.1007/s00190-023-01763-9},
	abstract = {Abstract
            
              We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5
              
                
                  \$\${\textasciicircum}{\textbackslash}circ \$\$
                  
                    
                      
                      ∘
                    
                  
                
              
              , covering the time frame 2003 to 2019 without gaps, and including monthly uncertainty quantification. GLWS2.0 was derived by assimilating monthly GRACE/-FO mass change maps into the WaterGAP global hydrology model via the ensemble Kalman filter, taking data and model uncertainty into account. TWSA in GLWS2.0 is then accumulated over several hydrological storage variables. In this article, we describe the methods and data sets that went into GLWS2.0, how it compares to GRACE/-FO data in terms of representing TWSA trends, seasonal signals, and extremes, as well as its validation via comparing to GNSS-derived vertical loading and its comparison with a version of the NASA Catchment Land Surface Model GRACE Data Assimilation (CLSM-DA). We find that, in the average over more than 1000 stations globally, GLWS2.0 correlates better with GNSS observations of vertical loading at short-term, seasonal, and long-term temporal bands than GRACE/-FO. While some differences exist, overall GLWS2.0 agrees reasonably well with CLSM-DA in terms of TWSA trends and annual amplitudes and phases.
              Highlights
              
                
                  
                    We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies over the global land with a spatial resolution of 0.5
                    
                      
                        \$\${\textasciicircum}{\textbackslash}circ \$\$
                        
                          
                            
                            ∘
                          
                        
                      
                    
                    , covering the period 2003 to 2019 without gaps, and including uncertainty quantification.
                  
                
                
                  GLWS2.0 synthesizes monthly GRACE/-FO mass change maps with daily precipitation and radiation data via the WaterGAP model framework, taking data and model uncertainty into account.
                
                
                  Here we describe the methods and data sets that went into GLWS2.0 and its validation from a geodetic applications perspective. We find that, in the global average, GLWS2.0 fits better than GRACE/-FO to GNSS observations of vertical loading.},
	language = {en},
	number = {7},
	urldate = {2023-10-30},
	journal = {Journal of Geodesy},
	author = {Gerdener, Helena and Kusche, Jürgen and Schulze, Kerstin and Döll, Petra and Klos, Anna},
	month = jul,
	year = {2023},
	pages = {73},
}









@article{bauke_soil_2022,
	title = {Soil water status shapes nutrient cycling in agroecosystems from micrometer to landscape scales},
	volume = {185},
	issn = {1436-8730, 1522-2624},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357},
	doi = {10.1002/jpln.202200357},
	language = {en},
	number = {6},
	urldate = {2023-06-02},
	journal = {Journal of Plant Nutrition and Soil Science},
	author = {Bauke, Sara L. and Amelung, Wulf and Bol, Roland and Brandt, Luise and Brüggemann, Nicolas and Kandeler, Ellen and Meyer, Nele and Or, Dani and Schnepf, Andrea and Schloter, Michael and Schulz, Stefanie and Siebers, Nina and Von Sperber, Christian and Vereecken, Harry},
	month = dec,
	year = {2022},
	pages = {773--792},
}





@article{naz_continental-scale_2023,
	title = {Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, {ParFlow}-{CLM} (v3.6.0), over {Europe}},
	volume = {16},
	issn = {1991-9603},
	url = {https://gmd.copernicus.org/articles/16/1617/2023/},
	doi = {10.5194/gmd-16-1617-2023},
	abstract = {Abstract. High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically based coupled land surface groundwater model, ParFlow-CLM version 3.6.0, over a pan-European model domain at 0.0275∘ (∼3 km) resolution. The model simulates a three-dimensional variably saturated groundwater-flow-solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of multiple hydrologic variables including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent (SWE), total water storage (TWS), and water table depth (WTD) resulting from a 10-year (1997–2006) model simulation was performed using in situ and remote sensing (RS) observations. Overall, the uncalibrated ParFlow-CLM model showed good agreement in simulating river discharge for 176 gauging stations across Europe (average Spearman's rank correlation (R) of 0.77). At the local scale, ParFlow-CLM model performed well for ET (R{\textgreater}0.94) against eddy covariance observations but showed relatively large differences for SM and WTD (median R values of 0.7 and 0.50, respectively) when compared with soil moisture networks and groundwater-monitoring-well data. However, model performance varied between hydroclimate regions, with the best agreement to RS datasets being shown in semi-arid and arid regions for most variables. Conversely, the largest differences between modeled and RS datasets (e.g., for SM, SWE, and TWS) are shown in humid and cold regions. Our findings highlight the importance of including multiple variables using both local-scale and large-scale RS datasets in model evaluations for a better understanding of physically based fully distributed hydrologic model performance and uncertainties in water and energy fluxes over continental scales and across different hydroclimate regions. The large-scale, high-resolution setup also forms a basis for future studies and provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting considering the effects of lateral surface and groundwater flows.},
	language = {en},
	number = {6},
	urldate = {2023-03-31},
	journal = {Geoscientific Model Development},
	author = {Naz, Bibi S. and Sharples, Wendy and Ma, Yueling and Goergen, Klaus and Kollet, Stefan},
	month = mar,
	year = {2023},
	pages = {1617--1639},
}





@article{valmassoi_review_2022,
	title = {A review on irrigation parameterizations in {Earth} system models},
	volume = {4},
	issn = {2624-9375},
	url = {https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full},
	doi = {10.3389/frwa.2022.906664},
	abstract = {Irrigation is the process of artificially providing water to agricultural lands in order to provide crops with the necessary water supply to ensure or foster the growth of the plants. However, its implications reach beyond the agro-economic aspect as irrigation affects the soil-land-atmosphere interactions and thus influences the water and energy cycles in the Earth system. Past studies have shown how through these interactions, an increase in soil moisture due to irrigation also affects the atmospheric state and its dynamics. Thus, the lack of representation of irrigation in numerical Earth system models—be it for reanalysis, weather forecasting or climate prediction—can lead to significant errors and biases in various parameters of the system including but not limited to surface temperature and precipitation. In this study, we aim to summarize and discuss currently available irrigation parameterizations across different numerical models. This provides a reference framework to understand the impact of irrigation on the various components of Earth system models. Specifically, we discuss the impact of these parameterizations in the context of their spatio-temporal scale representation and point out the benefits and limitations of the various approaches. In fact, most of the parameterizations use irrigation as a direct modification of soil moisture with just a few implementations add irrigation as a form of surface water. While the former method might be suitable for coarse spatio-temporal scales, the latter better resembles the range of employed irrigation techniques. From the analysis, we find that not only the method or the spatio-temporal scales but the actual amount of water used is of great importance to the response of the Earth system model.},
	urldate = {2023-01-30},
	journal = {Frontiers in Water},
	author = {Valmassoi, Arianna and Keller, Jan D.},
	month = nov,
	year = {2022},
	pages = {906664},
}





@article{springer_role_2023,
	title = {The {Role} of {Space}-{Based} {Observations} for {Groundwater} {Resource} {Monitoring} over {Africa}},
	issn = {1573-0956},
	url = {https://doi.org/10.1007/s10712-022-09759-4},
	doi = {10.1007/s10712-022-09759-4},
	abstract = {Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent.},
	journal = {Surveys in Geophysics},
	author = {Springer, Anne and Lopez, Teodolina and Owor, Michael and Frappart, Frédéric and Stieglitz, Thomas},
	month = jan,
	year = {2023},
}





@article{karegar_raspberry_2022,
	title = {Raspberry {Pi} {Reflector} ({RPR}): {A} {Low}‐cost {Water}‐level {Monitoring} {System} based on {GNSS} {Interferometric} {Reflectometry}},
	issn = {0043-1397, 1944-7973},
	shorttitle = {Raspberry {Pi} {Reflector} ({RPR})},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713},
	doi = {10.1029/2021WR031713},
	language = {en},
	urldate = {2022-11-24},
	journal = {Water Resources Research},
	author = {Karegar, Makan A. and Kusche, Jürgen and Geremia‐Nievinski, Felipe and Larson, Kristine M.},
	month = nov,
	year = {2022},
}





@article{vereecken_soil_2022,
	title = {Soil hydrology in the {Earth} system},
	volume = {3},
	issn = {2662-138X},
	url = {https://www.nature.com/articles/s43017-022-00324-6},
	doi = {10.1038/s43017-022-00324-6},
	language = {en},
	number = {9},
	urldate = {2023-01-26},
	journal = {Nature Reviews Earth \& Environment},
	author = {Vereecken, Harry and Amelung, Wulf and Bauke, Sara L. and Bogena, Heye and Brüggemann, Nicolas and Montzka, Carsten and Vanderborght, Jan and Bechtold, Michel and Blöschl, Günter and Carminati, Andrea and Javaux, Mathieu and Konings, Alexandra G. and Kusche, Jürgen and Neuweiler, Insa and Or, Dani and Steele-Dunne, Susan and Verhoef, Anne and Young, Michael and Zhang, Yonggen},
	month = aug,
	year = {2022},
	pages = {573--587},
}
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In order to keep using Mendeley with BibBase past April\n        14th, you need to:\n        <ol>\n          <li>renew the authorization for BibBase on Mendeley, and</li>\n          <li>update the BibBase URL\n            in your page the same way you did when you initially set up\n            this page.\n          </li>\n        </ol>\n      </p>\n\n      <p>\n        <a href=\"http://bibbase.org/cgi-bin/mendeley2/get.py\">\n          <i class=\"fa fa-angle-double-right\"></i>\n          Fix it now</a>\n      </p>\n    </div>\n\n  </div>\n\n\n  <div id=\"bibbase_body\">\n    \n  \n  <div class=\"bibbase_group_whole\" id=\"group_2025\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2025')\"\n      onkeypress=\"toggleGroup('group_2025')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2025</span>\n      <span class=\"bibbase_group_count\">\n        \n        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"poppetern-naz-vereecken-baatz-fisher-hendricksfranssen-systematicunderestimationoftypespecificecosystemprocessvariabilityinthecommunitylandmodelv5overeurope-2025\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://gmd.copernicus.org/articles/18/287/2025/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'poppetern-naz-vereecken-baatz-fisher-hendricksfranssen-systematicunderestimationoftypespecificecosystemprocessvariabilityinthecommunitylandmodelv5overeurope-2025', 'https://gmd.copernicus.org/articles/18/287/2025/', event);\">\n    Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Poppe Terán, C.; Naz, B. S.; Vereecken, H.; Baatz, R.; Fisher, R. A.;  and Hendricks Franssen, H.\n</span>\n\n  \n\n</span>\n\n  <i>Geoscientific Model Development</i>, 18(2): 287–317. January 2025.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://gmd.copernicus.org/articles/18/287/2025/\"\n     onclick=\"log_download('poppetern-naz-vereecken-baatz-fisher-hendricksfranssen-systematicunderestimationoftypespecificecosystemprocessvariabilityinthecommunitylandmodelv5overeurope-2025', 'https://gmd.copernicus.org/articles/18/287/2025/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/gmd-18-287-2025\"\n     onclick=\"log_download('poppetern-naz-vereecken-baatz-fisher-hendricksfranssen-systematicunderestimationoftypespecificecosystemprocessvariabilityinthecommunitylandmodelv5overeurope-2025', 'http://doi.org/10.5194/gmd-18-287-2025', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/poppetern-naz-vereecken-baatz-fisher-hendricksfranssen-systematicunderestimationoftypespecificecosystemprocessvariabilityinthecommunitylandmodelv5overeurope-2025\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('poppetern-naz-vereecken-baatz-fisher-hendricksfranssen-systematicunderestimationoftypespecificecosystemprocessvariabilityinthecommunitylandmodelv5overeurope-2025')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{poppe_teran_systematic_2025,\n\ttitle = {Systematic underestimation of type-specific ecosystem process variability in the {Community} {Land} {Model} v5 over {Europe}},\n\tvolume = {18},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1991-9603},\n\turl = {https://gmd.copernicus.org/articles/18/287/2025/},\n\tdoi = {10.5194/gmd-18-287-2025},\n\tabstract = {Abstract. Evapotranspiration (ET) and gross primary production (GPP) are critical fluxes contributing to the energy, water, and carbon exchanges between the atmosphere and the land surface. Land surface models such as the Community Land Model v5 (CLM5) quantify these fluxes, estimate the state of carbon budgets and water resources, and contribute to a better understanding of climate change&#x27;s impact on ecosystems. Past studies have shown the ability of CLM5 to model ET and GPP magnitudes well but emphasized systematic underestimations and lower variability than in the observations. Here, we evaluated CLM5&#x27;s predictions of water and energy fluxes using observations from eddy covariance stations from the Integrated Carbon Observation System (ICOS), remote sensing, and reanalysis data sets. We assess simulated ET and GPP from the grid scale (CLM5grid) and the plant functional type (PFT) scale (CLM5PFT). CLM5PFT exhibited a low systematic error in simulating the ET at the ICOS sites (average bias of −4.68 \\%), indicating that PFT-specific ET closely matches the observations&#x27; magnitude. GPP was underestimated by CLM5PFT, especially in deciduous forests (bias of −43.76 \\%). The results showed an underestimation of the spatiotemporal variability in the simulated ET and GPP distribution moments across PFTs for both CLM setups compared to reanalysis data and remote-sensing products. These findings provide essential insights for improving land surface models, highlighting the need to enhance the CLM5&#x27;s ability to capture the spatiotemporal variability in ET and GPP simulations across PFTs.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2025-02-14},\n\tjournal = {Geoscientific Model Development},\n\tauthor = {Poppe Terán, Christian and Naz, Bibi S. and Vereecken, Harry and Baatz, Roland and Fisher, Rosie A. and Hendricks Franssen, Harrie-Jan},\n\tmonth = jan,\n\tyear = {2025},\n\tpages = {287--317},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. Evapotranspiration (ET) and gross primary production (GPP) are critical fluxes contributing to the energy, water, and carbon exchanges between the atmosphere and the land surface. Land surface models such as the Community Land Model v5 (CLM5) quantify these fluxes, estimate the state of carbon budgets and water resources, and contribute to a better understanding of climate change's impact on ecosystems. Past studies have shown the ability of CLM5 to model ET and GPP magnitudes well but emphasized systematic underestimations and lower variability than in the observations. Here, we evaluated CLM5's predictions of water and energy fluxes using observations from eddy covariance stations from the Integrated Carbon Observation System (ICOS), remote sensing, and reanalysis data sets. We assess simulated ET and GPP from the grid scale (CLM5grid) and the plant functional type (PFT) scale (CLM5PFT). CLM5PFT exhibited a low systematic error in simulating the ET at the ICOS sites (average bias of −4.68 %), indicating that PFT-specific ET closely matches the observations' magnitude. GPP was underestimated by CLM5PFT, especially in deciduous forests (bias of −43.76 %). The results showed an underestimation of the spatiotemporal variability in the simulated ET and GPP distribution moments across PFTs for both CLM setups compared to reanalysis data and remote-sensing products. These findings provide essential insights for improving land surface models, highlighting the need to enhance the CLM5's ability to capture the spatiotemporal variability in ET and GPP simulations across PFTs.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-fenoglio-kusche-measuringoffnadirriverwaterlevelsandslopesfromaltimeterfullyfocusedsarmode-2025\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chen-fenoglio-kusche-measuringoffnadirriverwaterlevelsandslopesfromaltimeterfullyfocusedsarmode-2025', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498', event);\">\n    Measuring Off-nadir river water levels and slopes from altimeter Fully-Focused SAR mode.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen, J.; Fenoglio, L.;  and Kusche, J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Hydrology</i>, 650: 132553. April 2025.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498\"\n     onclick=\"log_download('chen-fenoglio-kusche-measuringoffnadirriverwaterlevelsandslopesfromaltimeterfullyfocusedsarmode-2025', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Measuring Off-nadir river water levels and slopes from altimeter Fully-Focused SAR mode [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jhydrol.2024.132553\"\n     onclick=\"log_download('chen-fenoglio-kusche-measuringoffnadirriverwaterlevelsandslopesfromaltimeterfullyfocusedsarmode-2025', 'http://doi.org/10.1016/j.jhydrol.2024.132553', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-fenoglio-kusche-measuringoffnadirriverwaterlevelsandslopesfromaltimeterfullyfocusedsarmode-2025\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-fenoglio-kusche-measuringoffnadirriverwaterlevelsandslopesfromaltimeterfullyfocusedsarmode-2025')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{chen_measuring_2025,\n\ttitle = {Measuring {Off}-nadir river water levels and slopes from altimeter {Fully}-{Focused} {SAR} mode},\n\tvolume = {650},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169424019498},\n\tdoi = {10.1016/j.jhydrol.2024.132553},\n\tlanguage = {en},\n\turldate = {2025-02-14},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Chen, Jiaming and Fenoglio, Luciana and Kusche, Jürgen},\n\tmonth = apr,\n\tyear = {2025},\n\tpages = {132553},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kracheletz-liu-springer-kusche-friederichs-wouldthe2021westerneuropefloodeventbevisibleinsatellitegravimetry-2025\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kracheletz-liu-springer-kusche-friederichs-wouldthe2021westerneuropefloodeventbevisibleinsatellitegravimetry-2025', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190', event);\">\n    Would the 2021 Western Europe Flood Event Be Visible in Satellite Gravimetry?.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kracheletz, M.; Liu, Z.; Springer, A.; Kusche, J.;  and Friederichs, P.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Geophysical Research: Atmospheres</i>, 130(3): e2024JD042190. February 2025.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190\"\n     onclick=\"log_download('kracheletz-liu-springer-kusche-friederichs-wouldthe2021westerneuropefloodeventbevisibleinsatellitegravimetry-2025', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Would the 2021 Western Europe Flood Event Be Visible in Satellite Gravimetry? [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2024JD042190\"\n     onclick=\"log_download('kracheletz-liu-springer-kusche-friederichs-wouldthe2021westerneuropefloodeventbevisibleinsatellitegravimetry-2025', 'http://doi.org/10.1029/2024JD042190', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kracheletz-liu-springer-kusche-friederichs-wouldthe2021westerneuropefloodeventbevisibleinsatellitegravimetry-2025\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kracheletz-liu-springer-kusche-friederichs-wouldthe2021westerneuropefloodeventbevisibleinsatellitegravimetry-2025')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{kracheletz_would_2025,\n\ttitle = {Would the 2021 {Western} {Europe} {Flood} {Event} {Be} {Visible} in {Satellite} {Gravimetry}?},\n\tvolume = {130},\n\tissn = {2169-897X, 2169-8996},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JD042190},\n\tdoi = {10.1029/2024JD042190},\n\tabstract = {Abstract\n            The primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in the Earth&#x27;s gravitational field. Distance variations between the two GRACE‐FO satellites, recorded by a K‐Band Ranging system and a new Laser Ranging Interferometer (LRI), are significantly influenced by atmospheric mass redistribution. We investigate whether the sub‐monthly variations in atmospheric water mass, precipitation, and changes in total water storage during the extreme flood event in western Europe in 2021 were sufficiently large to influence the satellite gravity field measurements, if the GRACE‐FO satellites would have passed directly over the region. We use several data sets such as weather forecasts (ICON‐D2 model), hydrological simulations (ParFlow/CLM), observations as well as reanalyses, showing the high uncertainty between different estimations of the considered variables: total precipitable water, total precipitation, and total water storage. Our estimates suggest a potentially noticeable impact of the 2021 flood event on the GRACE‐FO satellites. Although it was globally seen a rather small event, even the atmospheric water mass beyond water vapor, which is not considered within the de‐aliasing process, is close to the LRI detection accuracy. This is particularly relevant for future gravity missions, which will use the LRI with potentially higher sensitivity as their main instrument. Sub‐monthly variations in the total atmospheric water mass, that is, beyond water vapor of huge extreme precipitation events should be investigated further to reduce potential future aliasing errors.\n          , \n            Plain Language Summary\n            The GRACE Follow‐On (GRACE‐FO) satellite mission measures temporal changes in the Earth&#x27;s gravitational field by tracking the distance between GRACE‐FO&#x27;s two satellites with a K‐Band Ranging system and a new laser ranging interferometer (LRI). Sub‐monthly variations in atmospheric mass impact these measurements, so it is essential to account for these variations to minimize errors in the derived monthly gravity fields. In July 2021, western Europe experienced an extreme flood event. We investigate whether its unusually high atmospheric water masses, strong precipitation, and increased overall water storage could impact the satellite&#x27;s gravity measurements. We use data from several sources, including weather forecasts, hydrological simulations, observed precipitation and reanalysis data. We estimate potential changes in the distance between the satellites if they had flown over the flooded area during the flood period from July 14 to 16, 2021. Our upper estimates suggest that the flood event could have been seen in the GRACE‐FO measurements in case of a direct overpass. To improve the accuracy of future missions, which will rely on the LRI as their primary instrument, we suggest to further investigate short‐term variations in atmospheric water mass, that is, beyond water vapor to reduce potential errors.\n          , \n            Key Points\n            \n              \n                \n                  Simulations show that the flood event could have noticeably impacted GRACE‐FO Laser Ranging Interferometer measurements, if the satellites had flown over the event\n                \n                \n                  Even the instantaneous atmospheric water mass was likely large enough to have been detected\n                \n                \n                  Atmospheric water beyond water vapor is not considered in current de‐aliasing products, and we suggest this paradigm should be reassessed},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2025-02-03},\n\tjournal = {Journal of Geophysical Research: Atmospheres},\n\tauthor = {Kracheletz, Magdalena and Liu, Ziyu and Springer, Anne and Kusche, Jürgen and Friederichs, Petra},\n\tmonth = feb,\n\tyear = {2025},\n\tpages = {e2024JD042190},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract The primary objective of the GRACE Follow‐On satellite mission is to measure temporal changes in the Earth's gravitational field. Distance variations between the two GRACE‐FO satellites, recorded by a K‐Band Ranging system and a new Laser Ranging Interferometer (LRI), are significantly influenced by atmospheric mass redistribution. We investigate whether the sub‐monthly variations in atmospheric water mass, precipitation, and changes in total water storage during the extreme flood event in western Europe in 2021 were sufficiently large to influence the satellite gravity field measurements, if the GRACE‐FO satellites would have passed directly over the region. We use several data sets such as weather forecasts (ICON‐D2 model), hydrological simulations (ParFlow/CLM), observations as well as reanalyses, showing the high uncertainty between different estimations of the considered variables: total precipitable water, total precipitation, and total water storage. Our estimates suggest a potentially noticeable impact of the 2021 flood event on the GRACE‐FO satellites. Although it was globally seen a rather small event, even the atmospheric water mass beyond water vapor, which is not considered within the de‐aliasing process, is close to the LRI detection accuracy. This is particularly relevant for future gravity missions, which will use the LRI with potentially higher sensitivity as their main instrument. Sub‐monthly variations in the total atmospheric water mass, that is, beyond water vapor of huge extreme precipitation events should be investigated further to reduce potential future aliasing errors. , Plain Language Summary The GRACE Follow‐On (GRACE‐FO) satellite mission measures temporal changes in the Earth's gravitational field by tracking the distance between GRACE‐FO's two satellites with a K‐Band Ranging system and a new laser ranging interferometer (LRI). Sub‐monthly variations in atmospheric mass impact these measurements, so it is essential to account for these variations to minimize errors in the derived monthly gravity fields. In July 2021, western Europe experienced an extreme flood event. We investigate whether its unusually high atmospheric water masses, strong precipitation, and increased overall water storage could impact the satellite's gravity measurements. We use data from several sources, including weather forecasts, hydrological simulations, observed precipitation and reanalysis data. We estimate potential changes in the distance between the satellites if they had flown over the flooded area during the flood period from July 14 to 16, 2021. Our upper estimates suggest that the flood event could have been seen in the GRACE‐FO measurements in case of a direct overpass. To improve the accuracy of future missions, which will rely on the LRI as their primary instrument, we suggest to further investigate short‐term variations in atmospheric water mass, that is, beyond water vapor to reduce potential errors. , Key Points Simulations show that the flood event could have noticeably impacted GRACE‐FO Laser Ranging Interferometer measurements, if the satellites had flown over the event Even the instantaneous atmospheric water mass was likely large enough to have been detected Atmospheric water beyond water vapor is not considered in current de‐aliasing products, and we suggest this paradigm should be reassessed\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2024\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2024')\"\n      onkeypress=\"toggleGroup('group_2024')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2024</span>\n      <span class=\"bibbase_group_count\">\n        \n        (39)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s41597-024-03535-2\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024', 'https://www.nature.com/articles/s41597-024-03535-2', event);\">\n    Multi-year aboveground data of minirhizotron facilities in Selhausen.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nguyen, T. H.; Lopez, G.; Seidel, S. J.; Lärm, L.; Bauer, F. M.; Klotzsche, A.; Schnepf, A.; Gaiser, T.; Hüging, H.;  and Ewert, F.\n</span>\n\n  \n\n</span>\n\n  <i>Scientific Data</i>, 11(1): 674. June 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s41597-024-03535-2\"\n     onclick=\"log_download('nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024', 'https://www.nature.com/articles/s41597-024-03535-2', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Multi-year aboveground data of minirhizotron facilities in Selhausen [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s41597-024-03535-2\"\n     onclick=\"log_download('nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024', 'http://doi.org/10.1038/s41597-024-03535-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{nguyen_multi-year_2024,\n\ttitle = {Multi-year aboveground data of minirhizotron facilities in {Selhausen}},\n\tvolume = {11},\n\tissn = {2052-4463},\n\turl = {https://www.nature.com/articles/s41597-024-03535-2},\n\tdoi = {10.1038/s41597-024-03535-2},\n\tabstract = {Abstract\n            \n              Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO\n              2\n              and H\n              2\n              O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO\n              2\n              exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2025-02-18},\n\tjournal = {Scientific Data},\n\tauthor = {Nguyen, Thuy Huu and Lopez, Gina and Seidel, Sabine J. and Lärm, Lena and Bauer, Felix Maximilian and Klotzsche, Anja and Schnepf, Andrea and Gaiser, Thomas and Hüging, Hubert and Ewert, Frank},\n\tmonth = jun,\n\tyear = {2024},\n\tpages = {674},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO 2 and H 2 O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO 2 exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"vanderborght-couvreur-javaux-leitner-schnepf-vereecken-mechanisticallyderivedmacroscopicrootwateruptakefunctionstheiiandiiofrootwateruptakefunctions-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vanderborght-couvreur-javaux-leitner-schnepf-vereecken-mechanisticallyderivedmacroscopicrootwateruptakefunctionstheiiandiiofrootwateruptakefunctions-2024', 'https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333', event);\">\n    Mechanistically derived macroscopic root water uptake functions: The <i>α</i> and <i>ω</i> of root water uptake functions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Vanderborght, J.; Couvreur, V.; Javaux, M.; Leitner, D.; Schnepf, A.;  and Vereecken, H.\n</span>\n\n  \n\n</span>\n\n  <i>Vadose Zone Journal</i>, 23(4): e20333. July 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333\"\n     onclick=\"log_download('vanderborght-couvreur-javaux-leitner-schnepf-vereecken-mechanisticallyderivedmacroscopicrootwateruptakefunctionstheiiandiiofrootwateruptakefunctions-2024', 'https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Mechanistically derived macroscopic root water uptake functions: The &lt;i&gt;α&lt;/i&gt; and &lt;i&gt;ω&lt;/i&gt; of root water uptake functions [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/vzj2.20333\"\n     onclick=\"log_download('vanderborght-couvreur-javaux-leitner-schnepf-vereecken-mechanisticallyderivedmacroscopicrootwateruptakefunctionstheiiandiiofrootwateruptakefunctions-2024', 'http://doi.org/10.1002/vzj2.20333', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vanderborght-couvreur-javaux-leitner-schnepf-vereecken-mechanisticallyderivedmacroscopicrootwateruptakefunctionstheiiandiiofrootwateruptakefunctions-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vanderborght-couvreur-javaux-leitner-schnepf-vereecken-mechanisticallyderivedmacroscopicrootwateruptakefunctionstheiiandiiofrootwateruptakefunctions-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{vanderborght_mechanistically_2024,\n\ttitle = {Mechanistically derived macroscopic root water uptake functions: {The} \\textit{α} and \\textit{ω} of root water uptake functions},\n\tvolume = {23},\n\tissn = {1539-1663, 1539-1663},\n\tshorttitle = {Mechanistically derived macroscopic root water uptake functions},\n\turl = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20333},\n\tdoi = {10.1002/vzj2.20333},\n\tabstract = {Abstract\n            \n              Water uptake by plant roots is an important component of the soil water balance. Predicting to what extent potential transpiration from the canopy, that is, transpiration demand, can be met by supply of water from the soil through the root system is crucial to simulate the actual transpiration and assess vegetation water stress. In models that simulate the dynamics of vertical soil water content profiles as a function of water fluxes and soil water potential gradients, the root water uptake (RWU) distribution is represented by macroscopic sink terms. We present RWU functions that calculate sink terms based on a mechanistic model of water flow in the soil–root system. Based on soil–root hydraulics, we define\n              α\n              ‐supply functions representing the maximal uptake by the root system from a certain soil depth when the root collar water potential equals the wilting point,\n              ω\n              ‐supply factors representing the maximal supply from the entire root system, and a critical\n              \n                ω\n                c\n              \n              factor representing the potential transpiration demand. These functions and factors are subsequently used to calculate RWU distributions directly from potential transpiration or demand and the soil water potentials. Unlike currently used approaches, which define\n              α\n              ‐stress functions and\n              ω\n              factors representing ratios of actual uptake to uptake demand, the supply‐based formulations can be derived directly from soil and root hydraulic properties and can represent processes like root hydraulic redistribution and hydraulic lift.\n            \n          , \n            Core Ideas\n            \n              \n                \n                  Functions to calculate root water uptake (RWU) from different soil depths were derived.\n                \n                \n                  RWU is calculated directly using soil water potentials and the potential transpiration rate.\n                \n                \n                  The functions are derived using soil and root hydraulic properties.\n                \n                \n                  Phenomena like RWU compensation, hydraulic redistribution, and hydraulic lift are reproduced.\n                \n                \n                  Similarities and differences with currently used uptake functions are discussed.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2025-02-18},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Vanderborght, Jan and Couvreur, Valentin and Javaux, Mathieu and Leitner, Daniel and Schnepf, Andrea and Vereecken, Harry},\n\tmonth = jul,\n\tyear = {2024},\n\tpages = {e20333},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Water uptake by plant roots is an important component of the soil water balance. Predicting to what extent potential transpiration from the canopy, that is, transpiration demand, can be met by supply of water from the soil through the root system is crucial to simulate the actual transpiration and assess vegetation water stress. In models that simulate the dynamics of vertical soil water content profiles as a function of water fluxes and soil water potential gradients, the root water uptake (RWU) distribution is represented by macroscopic sink terms. We present RWU functions that calculate sink terms based on a mechanistic model of water flow in the soil–root system. Based on soil–root hydraulics, we define α ‐supply functions representing the maximal uptake by the root system from a certain soil depth when the root collar water potential equals the wilting point, ω ‐supply factors representing the maximal supply from the entire root system, and a critical ω c factor representing the potential transpiration demand. These functions and factors are subsequently used to calculate RWU distributions directly from potential transpiration or demand and the soil water potentials. Unlike currently used approaches, which define α ‐stress functions and ω factors representing ratios of actual uptake to uptake demand, the supply‐based formulations can be derived directly from soil and root hydraulic properties and can represent processes like root hydraulic redistribution and hydraulic lift. , Core Ideas Functions to calculate root water uptake (RWU) from different soil depths were derived. RWU is calculated directly using soil water potentials and the potential transpiration rate. The functions are derived using soil and root hydraulic properties. Phenomena like RWU compensation, hydraulic redistribution, and hydraulic lift are reproduced. Similarities and differences with currently used uptake functions are discussed.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhang-wagner-goergen-kollet-summerevapotranspirationcloudfeedbacksinlandatmosphereinteractionsovereurope-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/10.1007/s00382-024-07475-w\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'zhang-wagner-goergen-kollet-summerevapotranspirationcloudfeedbacksinlandatmosphereinteractionsovereurope-2024', 'https://link.springer.com/10.1007/s00382-024-07475-w', event);\">\n    Summer evapotranspiration-cloud feedbacks in land-atmosphere interactions over Europe.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhang, Y.; Wagner, N.; Goergen, K.;  and Kollet, S.\n</span>\n\n  \n\n</span>\n\n  <i>Climate Dynamics</i>, 62(12): 10767–10783. December 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/10.1007/s00382-024-07475-w\"\n     onclick=\"log_download('zhang-wagner-goergen-kollet-summerevapotranspirationcloudfeedbacksinlandatmosphereinteractionsovereurope-2024', 'https://link.springer.com/10.1007/s00382-024-07475-w', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Summer evapotranspiration-cloud feedbacks in land-atmosphere interactions over Europe [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00382-024-07475-w\"\n     onclick=\"log_download('zhang-wagner-goergen-kollet-summerevapotranspirationcloudfeedbacksinlandatmosphereinteractionsovereurope-2024', 'http://doi.org/10.1007/s00382-024-07475-w', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhang-wagner-goergen-kollet-summerevapotranspirationcloudfeedbacksinlandatmosphereinteractionsovereurope-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhang-wagner-goergen-kollet-summerevapotranspirationcloudfeedbacksinlandatmosphereinteractionsovereurope-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{zhang_summer_2024,\n\ttitle = {Summer evapotranspiration-cloud feedbacks in land-atmosphere interactions over {Europe}},\n\tvolume = {62},\n\tissn = {0930-7575, 1432-0894},\n\turl = {https://link.springer.com/10.1007/s00382-024-07475-w},\n\tdoi = {10.1007/s00382-024-07475-w},\n\tabstract = {Abstract\n            \n              Land-atmosphere (L-A) feedbacks are important for understanding regional climate functioning. However, the accurate quantification of feedback strength is challenging due to complex, nonlinear interactions and varying background atmospheric conditions. In particular, the role of cloud water in the terrestrial water cycle is often ignored or simplified in previous L-A feedback studies, which overlook the relationship between evapotranspiration (\n              ET\n              ) and cloud water (\n              TQC\n              ). This study diagnoses the interactions between\n              \n                \\$\\${\\textbackslash}:ET\\$\\$\n              \n              ,\n              \n                \\$\\${\\textbackslash}:TQC\\$\\$\n              \n              and its dynamics (\n              \n                \\$\\${\\textbackslash}:{\\textbackslash}varDelta{\\textbackslash}:TQC/{\\textbackslash}varDelta{\\textbackslash}:t\\$\\$\n              \n              ) under different atmospheric conditions by conducting correlation and a novel scaling analysis, based on a coupled regional climate model simulation. Contrasting correlation relationships between\n              \n                \\$\\${\\textbackslash}:ET\\$\\$\n              \n              ,\n              \n                \\$\\${\\textbackslash}:TQC\\$\\$\n              \n              and\n              \n                \\$\\${\\textbackslash}:{\\textbackslash}varDelta{\\textbackslash}:TQC/{\\textbackslash}varDelta{\\textbackslash}:t\\$\\$\n              \n              were identified, indicating the positive feedback between\n              \n                \\$\\${\\textbackslash}:ET\\$\\$\n              \n              and the dynamics in cloud water. Two types of positive scaling relationships between\n              \n                \\$\\${\\textbackslash}:ET\\$\\$\n              \n              and\n              \n                \\$\\${\\textbackslash}:{\\textbackslash}varDelta{\\textbackslash}:TQC/{\\textbackslash}varDelta{\\textbackslash}:t\\$\\$\n              \n              were identified by K-means clustering. The analysis shows a contrasting north-south distribution of the scaling relationship that is similar to the spatial distribution of energy-limited and water-limited\n              \n                \\$\\${\\textbackslash}:ET\\$\\$\n              \n              regimes, highlighting the role of ET regimes in modulating the\n              \n                \\$\\${\\textbackslash}:ET\\$\\$\n              \n              -\n              \n                \\$\\${\\textbackslash}:{\\textbackslash}varDelta{\\textbackslash}:TQC/{\\textbackslash}varDelta{\\textbackslash}:t\\$\\$\n              \n              scaling relationships. Moreover, the feedback strength and scaling relationship are affected by atmospheric moisture flux dynamics, providing remote moisture sources and altering dry/wet conditions. Our results highlight the role of cloud water in the atmospheric part of the L-A process chain and reveal the effect of different atmospheric conditions on L-A interactions based on the new analysis framework.},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2025-02-14},\n\tjournal = {Climate Dynamics},\n\tauthor = {Zhang, Yikui and Wagner, Niklas and Goergen, Klaus and Kollet, Stefan},\n\tmonth = dec,\n\tyear = {2024},\n\tpages = {10767--10783},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Land-atmosphere (L-A) feedbacks are important for understanding regional climate functioning. However, the accurate quantification of feedback strength is challenging due to complex, nonlinear interactions and varying background atmospheric conditions. In particular, the role of cloud water in the terrestrial water cycle is often ignored or simplified in previous L-A feedback studies, which overlook the relationship between evapotranspiration ( ET ) and cloud water ( TQC ). This study diagnoses the interactions between $$\\:ET$$ , $$\\:TQC$$ and its dynamics ( $$\\:\\varDelta\\:TQC/\\varDelta\\:t$$ ) under different atmospheric conditions by conducting correlation and a novel scaling analysis, based on a coupled regional climate model simulation. Contrasting correlation relationships between $$\\:ET$$ , $$\\:TQC$$ and $$\\:\\varDelta\\:TQC/\\varDelta\\:t$$ were identified, indicating the positive feedback between $$\\:ET$$ and the dynamics in cloud water. Two types of positive scaling relationships between $$\\:ET$$ and $$\\:\\varDelta\\:TQC/\\varDelta\\:t$$ were identified by K-means clustering. The analysis shows a contrasting north-south distribution of the scaling relationship that is similar to the spatial distribution of energy-limited and water-limited $$\\:ET$$ regimes, highlighting the role of ET regimes in modulating the $$\\:ET$$ - $$\\:\\varDelta\\:TQC/\\varDelta\\:t$$ scaling relationships. Moreover, the feedback strength and scaling relationship are affected by atmospheric moisture flux dynamics, providing remote moisture sources and altering dry/wet conditions. Our results highlight the role of cloud water in the atmospheric part of the L-A process chain and reveal the effect of different atmospheric conditions on L-A interactions based on the new analysis framework.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hacker-kusche-howrealisticaremultidecadalreconstructionsofgraceliketotalwaterstorageanomalies-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hacker-kusche-howrealisticaremultidecadalreconstructionsofgraceliketotalwaterstorageanomalies-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762', event);\">\n    How realistic are multi-decadal reconstructions of GRACE-like total water storage anomalies?.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hacker, C.;  and Kusche, J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Hydrology</i>, 645: 132180. December 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762\"\n     onclick=\"log_download('hacker-kusche-howrealisticaremultidecadalreconstructionsofgraceliketotalwaterstorageanomalies-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"How realistic are multi-decadal reconstructions of GRACE-like total water storage anomalies? [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jhydrol.2024.132180\"\n     onclick=\"log_download('hacker-kusche-howrealisticaremultidecadalreconstructionsofgraceliketotalwaterstorageanomalies-2024', 'http://doi.org/10.1016/j.jhydrol.2024.132180', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hacker-kusche-howrealisticaremultidecadalreconstructionsofgraceliketotalwaterstorageanomalies-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hacker-kusche-howrealisticaremultidecadalreconstructionsofgraceliketotalwaterstorageanomalies-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{hacker_how_2024,\n\ttitle = {How realistic are multi-decadal reconstructions of {GRACE}-like total water storage anomalies?},\n\tvolume = {645},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169424015762},\n\tdoi = {10.1016/j.jhydrol.2024.132180},\n\tlanguage = {en},\n\turldate = {2025-02-14},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Hacker, Charlotte and Kusche, Jürgen},\n\tmonth = dec,\n\tyear = {2024},\n\tpages = {132180},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"becker-seeger-paszkowski-marcos-papa-almar-bates-francelanord-etal-coastalfloodinginasianmegadeltasrecentadvancespersistentchallengesandcallforactionsamidstlocalandglobalchanges-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'becker-seeger-paszkowski-marcos-papa-almar-bates-francelanord-etal-coastalfloodinginasianmegadeltasrecentadvancespersistentchallengesandcallforactionsamidstlocalandglobalchanges-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846', event);\">\n    Coastal Flooding in Asian Megadeltas: Recent Advances, Persistent Challenges, and Call for Actions Amidst Local and Global Changes.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Becker, M.; Seeger, K.; Paszkowski, A.; Marcos, M.; Papa, F.; Almar, R.; Bates, P.; France‐Lanord, C.; Hossain, M. S.; Khan, M. J. U.; Karegar, M. A.; Karpytchev, M.; Long, N.; Minderhoud, P. S. J.; Neal, J.; Nicholls, R. J.;  and Syvitski, J.\n</span>\n\n  \n\n</span>\n\n  <i>Reviews of Geophysics</i>, 62(4): e2024RG000846. December 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846\"\n     onclick=\"log_download('becker-seeger-paszkowski-marcos-papa-almar-bates-francelanord-etal-coastalfloodinginasianmegadeltasrecentadvancespersistentchallengesandcallforactionsamidstlocalandglobalchanges-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Coastal Flooding in Asian Megadeltas: Recent Advances, Persistent Challenges, and Call for Actions Amidst Local and Global Changes [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2024RG000846\"\n     onclick=\"log_download('becker-seeger-paszkowski-marcos-papa-almar-bates-francelanord-etal-coastalfloodinginasianmegadeltasrecentadvancespersistentchallengesandcallforactionsamidstlocalandglobalchanges-2024', 'http://doi.org/10.1029/2024RG000846', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/becker-seeger-paszkowski-marcos-papa-almar-bates-francelanord-etal-coastalfloodinginasianmegadeltasrecentadvancespersistentchallengesandcallforactionsamidstlocalandglobalchanges-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('becker-seeger-paszkowski-marcos-papa-almar-bates-francelanord-etal-coastalfloodinginasianmegadeltasrecentadvancespersistentchallengesandcallforactionsamidstlocalandglobalchanges-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{becker_coastal_2024,\n\ttitle = {Coastal {Flooding} in {Asian} {Megadeltas}: {Recent} {Advances}, {Persistent} {Challenges}, and {Call} for {Actions} {Amidst} {Local} and {Global} {Changes}},\n\tvolume = {62},\n\tissn = {8755-1209, 1944-9208},\n\tshorttitle = {Coastal {Flooding} in {Asian} {Megadeltas}},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024RG000846},\n\tdoi = {10.1029/2024RG000846},\n\tabstract = {Abstract\n            Asian megadeltas, specifically the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas host half of the world&#x27;s deltaic population and are vital for Asian countries&#x27; ecosystems and food production. These deltas are extremely vulnerable to global change. Accelerating relative sea‐level rise, combined with rapid socio‐economic development intensifies these vulnerabilities and calls for a comprehensive understanding of current and future coastal flood dynamics. Here we provide a state‐of‐the‐art on the current knowledge and recent advances in quantifying and understanding the drivers of coastal flood‐related hazards in these deltas. We discuss the environmental and physical drivers, including climate influence, hydrology, oceanography, geomorphology, and geophysical processes and how they interact from short to long‐term changes, including during extreme events. We also jointly examine how human disturbances, with catchment interventions, land use changes and resource exploitations, contribute to coastal flooding in the deltas. Through a systems perspective, we characterize the current state of the deltaic systems and provide essential insights for shaping their sustainable future trajectories regarding the multifaceted challenges of coastal flooding.\n          , \n            Plain Language Summary\n            Asian megadeltas, including the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas, are home to half of the world&#x27;s deltaic population and play a critical role in Asian food production. However, these deltas are at high risk to climatic changes, with the vast majority of the world&#x27;s coastal flood exposure observed in these systems. Rising sea levels and rapid socio‐economic development worsen these vulnerabilities, necessitating a comprehensive understanding of coastal flooding dynamics across the five deltas. This review provides up‐to‐date insights on the current understanding and quantification of the drivers of coastal flood‐related hazards. It examines environmental and biophysical factors, such as climate, hydrology, oceanography, geomorphology, and geophysical processes, and how these may interact during extreme events. The review also explores how human activities, like catchment interventions, land use changes, and resource exploitation, contribute to coastal flooding. By offering a systematic perspective, this review characterizes the current state of knowledge on these deltaic systems and provides valuable insights for shaping sustainable future trajectories in the face of the challenges posed by coastal flooding.\n          , \n            Key Points\n            \n              \n                \n                  Urgent action is needed to address data gaps in monitoring coastal flooding in Asian megadeltas\n                \n                \n                  Integrated approaches, including in situ data, remote sensing and advanced modeling, are needed to understand coastal flooding impacts\n                \n                \n                  Unprecedented changes in Asian megadeltas call for integrated studies; decisions made today shape deltaic sustainability for decades},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2025-01-06},\n\tjournal = {Reviews of Geophysics},\n\tauthor = {Becker, M. and Seeger, K. and Paszkowski, A. and Marcos, M. and Papa, F. and Almar, R. and Bates, P. and France‐Lanord, C. and Hossain, Md S. and Khan, Md J. U. and Karegar, M. A. and Karpytchev, M. and Long, N. and Minderhoud, P. S. J. and Neal, J. and Nicholls, R. J. and Syvitski, J.},\n\tmonth = dec,\n\tyear = {2024},\n\tpages = {e2024RG000846},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Asian megadeltas, specifically the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas host half of the world's deltaic population and are vital for Asian countries' ecosystems and food production. These deltas are extremely vulnerable to global change. Accelerating relative sea‐level rise, combined with rapid socio‐economic development intensifies these vulnerabilities and calls for a comprehensive understanding of current and future coastal flood dynamics. Here we provide a state‐of‐the‐art on the current knowledge and recent advances in quantifying and understanding the drivers of coastal flood‐related hazards in these deltas. We discuss the environmental and physical drivers, including climate influence, hydrology, oceanography, geomorphology, and geophysical processes and how they interact from short to long‐term changes, including during extreme events. We also jointly examine how human disturbances, with catchment interventions, land use changes and resource exploitations, contribute to coastal flooding in the deltas. Through a systems perspective, we characterize the current state of the deltaic systems and provide essential insights for shaping their sustainable future trajectories regarding the multifaceted challenges of coastal flooding. , Plain Language Summary Asian megadeltas, including the Ganges‐Brahmaputra‐Meghna, Irrawaddy, Chao Phraya, Mekong, and Red River deltas, are home to half of the world's deltaic population and play a critical role in Asian food production. However, these deltas are at high risk to climatic changes, with the vast majority of the world's coastal flood exposure observed in these systems. Rising sea levels and rapid socio‐economic development worsen these vulnerabilities, necessitating a comprehensive understanding of coastal flooding dynamics across the five deltas. This review provides up‐to‐date insights on the current understanding and quantification of the drivers of coastal flood‐related hazards. It examines environmental and biophysical factors, such as climate, hydrology, oceanography, geomorphology, and geophysical processes, and how these may interact during extreme events. The review also explores how human activities, like catchment interventions, land use changes, and resource exploitation, contribute to coastal flooding. By offering a systematic perspective, this review characterizes the current state of knowledge on these deltaic systems and provides valuable insights for shaping sustainable future trajectories in the face of the challenges posed by coastal flooding. , Key Points Urgent action is needed to address data gaps in monitoring coastal flooding in Asian megadeltas Integrated approaches, including in situ data, remote sensing and advanced modeling, are needed to understand coastal flooding impacts Unprecedented changes in Asian megadeltas call for integrated studies; decisions made today shape deltaic sustainability for decades\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"brill-alencar-zhang-boeing-httel-lakes-exploringdroughthazardvulnerabilityandrelatedimpactsonagricultureinbrandenburg-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://nhess.copernicus.org/articles/24/4237/2024/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'brill-alencar-zhang-boeing-httel-lakes-exploringdroughthazardvulnerabilityandrelatedimpactsonagricultureinbrandenburg-2024', 'https://nhess.copernicus.org/articles/24/4237/2024/', event);\">\n    Exploring drought hazard, vulnerability, and related impacts on agriculture in Brandenburg.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Brill, F.; Alencar, P. H. L.; Zhang, H.; Boeing, F.; Hüttel, S.;  and Lakes, T.\n</span>\n\n  \n\n</span>\n\n  <i>Natural Hazards and Earth System Sciences</i>, 24(12): 4237–4265. November 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://nhess.copernicus.org/articles/24/4237/2024/\"\n     onclick=\"log_download('brill-alencar-zhang-boeing-httel-lakes-exploringdroughthazardvulnerabilityandrelatedimpactsonagricultureinbrandenburg-2024', 'https://nhess.copernicus.org/articles/24/4237/2024/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Exploring drought hazard, vulnerability, and related impacts on agriculture in Brandenburg [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/nhess-24-4237-2024\"\n     onclick=\"log_download('brill-alencar-zhang-boeing-httel-lakes-exploringdroughthazardvulnerabilityandrelatedimpactsonagricultureinbrandenburg-2024', 'http://doi.org/10.5194/nhess-24-4237-2024', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/brill-alencar-zhang-boeing-httel-lakes-exploringdroughthazardvulnerabilityandrelatedimpactsonagricultureinbrandenburg-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('brill-alencar-zhang-boeing-httel-lakes-exploringdroughthazardvulnerabilityandrelatedimpactsonagricultureinbrandenburg-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{brill_exploring_2024,\n\ttitle = {Exploring drought hazard, vulnerability, and related impacts on agriculture in {Brandenburg}},\n\tvolume = {24},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1684-9981},\n\turl = {https://nhess.copernicus.org/articles/24/4237/2024/},\n\tdoi = {10.5194/nhess-24-4237-2024},\n\tabstract = {Abstract. Adaptation to an increasingly dry regional climate requires spatially explicit information about current and future risks. Existing drought risk studies often rely on expert-weighted composite indicators, while empirical evidence on impact-relevant factors is still scarce. The aim of this study is to investigate to what extent hazard and vulnerability indicators can explain observed agricultural drought impacts via data-driven methods. We focus on the German federal state of Brandenburg, 2013–2022, including several consecutive drought years. As impact indicators we use thermal–spectral anomalies (land surface temperature (LST) and the normalized difference vegetation index (NDVI)) on the field level, and empirical yield gaps from reported statistics on the county level. Empirical associations to the impact indicators on both spatial levels are compared. Extreme gradient boosting (XGBoost) models explain up to about 60 \\% of the variance in the yield gap data (best R2 = 0.62). Model performance is more stable for the drought years and when using all crops for training rather than individual crops. Meteorological drought in June and soil quality are selected as the strongest impact-relevant factors. Rye is empirically found to be less vulnerable to drought than wheat, even on poorer soils. LST / NDVI only weakly relates to our empirical yield gaps. We recommend comparing different impact indicators on multiple scales to proceed with the development of empirically grounded risk maps.},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2024-12-02},\n\tjournal = {Natural Hazards and Earth System Sciences},\n\tauthor = {Brill, Fabio and Alencar, Pedro Henrique Lima and Zhang, Huihui and Boeing, Friedrich and Hüttel, Silke and Lakes, Tobia},\n\tmonth = nov,\n\tyear = {2024},\n\tpages = {4237--4265},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. Adaptation to an increasingly dry regional climate requires spatially explicit information about current and future risks. Existing drought risk studies often rely on expert-weighted composite indicators, while empirical evidence on impact-relevant factors is still scarce. The aim of this study is to investigate to what extent hazard and vulnerability indicators can explain observed agricultural drought impacts via data-driven methods. We focus on the German federal state of Brandenburg, 2013–2022, including several consecutive drought years. As impact indicators we use thermal–spectral anomalies (land surface temperature (LST) and the normalized difference vegetation index (NDVI)) on the field level, and empirical yield gaps from reported statistics on the county level. Empirical associations to the impact indicators on both spatial levels are compared. Extreme gradient boosting (XGBoost) models explain up to about 60 % of the variance in the yield gap data (best R2 = 0.62). Model performance is more stable for the drought years and when using all crops for training rather than individual crops. Meteorological drought in June and soil quality are selected as the strongest impact-relevant factors. Rye is empirically found to be less vulnerable to drought than wheat, even on poorer soils. LST / NDVI only weakly relates to our empirical yield gaps. We recommend comparing different impact indicators on multiple scales to proceed with the development of empirically grounded risk maps.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hohagemann-maurer-poll-fast-couplingtheregionalclimatemodeliconclmv266totheearthsystemmodelgcoastahoiv20usingoasis3mctv40-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://gmd.copernicus.org/articles/17/7815/2024/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hohagemann-maurer-poll-fast-couplingtheregionalclimatemodeliconclmv266totheearthsystemmodelgcoastahoiv20usingoasis3mctv40-2024', 'https://gmd.copernicus.org/articles/17/7815/2024/', event);\">\n    Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ho-Hagemann, H. T. M.; Maurer, V.; Poll, S.;  and Fast, I.\n</span>\n\n  \n\n</span>\n\n  <i>Geoscientific Model Development</i>, 17(21): 7815–7834. November 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://gmd.copernicus.org/articles/17/7815/2024/\"\n     onclick=\"log_download('hohagemann-maurer-poll-fast-couplingtheregionalclimatemodeliconclmv266totheearthsystemmodelgcoastahoiv20usingoasis3mctv40-2024', 'https://gmd.copernicus.org/articles/17/7815/2024/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0 [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/gmd-17-7815-2024\"\n     onclick=\"log_download('hohagemann-maurer-poll-fast-couplingtheregionalclimatemodeliconclmv266totheearthsystemmodelgcoastahoiv20usingoasis3mctv40-2024', 'http://doi.org/10.5194/gmd-17-7815-2024', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hohagemann-maurer-poll-fast-couplingtheregionalclimatemodeliconclmv266totheearthsystemmodelgcoastahoiv20usingoasis3mctv40-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hohagemann-maurer-poll-fast-couplingtheregionalclimatemodeliconclmv266totheearthsystemmodelgcoastahoiv20usingoasis3mctv40-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{ho-hagemann_coupling_2024,\n\ttitle = {Coupling the regional climate model {ICON}-{CLM} v2.6.6 to the {Earth} system model {GCOAST}-{AHOI} v2.0 using {OASIS3}-{MCT} v4.0},\n\tvolume = {17},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1991-9603},\n\turl = {https://gmd.copernicus.org/articles/17/7815/2024/},\n\tdoi = {10.5194/gmd-17-7815-2024},\n\tabstract = {Abstract. Interactions and feedback between components of the Earth system can have a significant impact on local and regional climate and its changes due to global warming. These effects can be better represented by regional Earth system models (RESMs) than by traditional stand-alone atmosphere and ocean models. Here, we present the RESM Geesthacht Coupled cOAstal model SysTem (GCOAST)-AHOI v2.0, which includes a new atmospheric component, the regional climate model Icosahedral Nonhydrostatic (ICON)-CLM, which is coupled to the Nucleus for European Modelling of the Ocean (NEMO) and the hydrological discharge model HD via the OASIS3-MCT coupler. The GCOAST-AHOI model has been developed and applied for climate simulations over the EURO-CORDEX domain. Two 11-year simulations from 2008 to 2018 of the uncoupled ICON-CLM and GCOAST-AHOI give similar results for seasonal and annual means of near-surface air temperature, precipitation, mean sea level pressure, and wind speed at a height of 10 m. However, GCOAST-AHOI has a cold sea surface temperature (SST) bias of 1–2 K over the Baltic and North seas that is most pronounced in the winter and spring seasons. A possible reason for the cold SST bias could be the underestimation of the downward shortwave radiation at the surface of ICON-CLM with the current model settings. Despite the cold SST bias, GCOAST-AHOI was able to capture other key variables well, such as those mentioned above. Therefore, GCOAST-AHOI can be a useful tool for long-term climate simulations over the EURO-CORDEX domain. Compared to the stand-alone NEMO3.6 forced by ERA5 and ORAS5 boundary forcing, GCOAST-AHOI has positive biases in sea ice fraction and salinity but negative biases in runoff, which need to be investigated further in the future to improve the coupled simulations. The new OASIS3-MCT coupling interface OMCI implemented in ICON-CLM adds the possibility of coupling ICON-CLM to an external ocean model and an external hydrological discharge model using OASIS3-MCT instead of the YAC (Yet Another Coupler). Using OMCI, it is also possible to set up a RESM with ICON-CLM and other ocean and hydrology models possessing the OASIS3-MCT interface for other regions, such as the Mediterranean Sea.},\n\tlanguage = {en},\n\tnumber = {21},\n\turldate = {2024-11-27},\n\tjournal = {Geoscientific Model Development},\n\tauthor = {Ho-Hagemann, Ha Thi Minh and Maurer, Vera and Poll, Stefan and Fast, Irina},\n\tmonth = nov,\n\tyear = {2024},\n\tpages = {7815--7834},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. Interactions and feedback between components of the Earth system can have a significant impact on local and regional climate and its changes due to global warming. These effects can be better represented by regional Earth system models (RESMs) than by traditional stand-alone atmosphere and ocean models. Here, we present the RESM Geesthacht Coupled cOAstal model SysTem (GCOAST)-AHOI v2.0, which includes a new atmospheric component, the regional climate model Icosahedral Nonhydrostatic (ICON)-CLM, which is coupled to the Nucleus for European Modelling of the Ocean (NEMO) and the hydrological discharge model HD via the OASIS3-MCT coupler. The GCOAST-AHOI model has been developed and applied for climate simulations over the EURO-CORDEX domain. Two 11-year simulations from 2008 to 2018 of the uncoupled ICON-CLM and GCOAST-AHOI give similar results for seasonal and annual means of near-surface air temperature, precipitation, mean sea level pressure, and wind speed at a height of 10 m. However, GCOAST-AHOI has a cold sea surface temperature (SST) bias of 1–2 K over the Baltic and North seas that is most pronounced in the winter and spring seasons. A possible reason for the cold SST bias could be the underestimation of the downward shortwave radiation at the surface of ICON-CLM with the current model settings. Despite the cold SST bias, GCOAST-AHOI was able to capture other key variables well, such as those mentioned above. Therefore, GCOAST-AHOI can be a useful tool for long-term climate simulations over the EURO-CORDEX domain. Compared to the stand-alone NEMO3.6 forced by ERA5 and ORAS5 boundary forcing, GCOAST-AHOI has positive biases in sea ice fraction and salinity but negative biases in runoff, which need to be investigated further in the future to improve the coupled simulations. The new OASIS3-MCT coupling interface OMCI implemented in ICON-CLM adds the possibility of coupling ICON-CLM to an external ocean model and an external hydrological discharge model using OASIS3-MCT instead of the YAC (Yet Another Coupler). Using OMCI, it is also possible to set up a RESM with ICON-CLM and other ocean and hydrology models possessing the OASIS3-MCT interface for other regions, such as the Mediterranean Sea.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhao-montzka-vereecken-franssen-acomparativeanalysisofremotesensingsoilmoisturedatasetsfusionmethodsnovellstmapproachversuswidelyusedtriplecollocationtechnique-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/10669050/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'zhao-montzka-vereecken-franssen-acomparativeanalysisofremotesensingsoilmoisturedatasetsfusionmethodsnovellstmapproachversuswidelyusedtriplecollocationtechnique-2024', 'https://ieeexplore.ieee.org/document/10669050/', event);\">\n    A Comparative Analysis of Remote Sensing Soil Moisture Datasets Fusion Methods: Novel LSTM Approach Versus Widely Used Triple Collocation Technique.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhao, H.; Montzka, C.; Vereecken, H.;  and Franssen, H. H.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</i>, 17: 16659–16671.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/10669050/\"\n     onclick=\"log_download('zhao-montzka-vereecken-franssen-acomparativeanalysisofremotesensingsoilmoisturedatasetsfusionmethodsnovellstmapproachversuswidelyusedtriplecollocationtechnique-2024', 'https://ieeexplore.ieee.org/document/10669050/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Comparative Analysis of Remote Sensing Soil Moisture Datasets Fusion Methods: Novel LSTM Approach Versus Widely Used Triple Collocation Technique [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/JSTARS.2024.3455549\"\n     onclick=\"log_download('zhao-montzka-vereecken-franssen-acomparativeanalysisofremotesensingsoilmoisturedatasetsfusionmethodsnovellstmapproachversuswidelyusedtriplecollocationtechnique-2024', 'http://doi.org/10.1109/JSTARS.2024.3455549', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhao-montzka-vereecken-franssen-acomparativeanalysisofremotesensingsoilmoisturedatasetsfusionmethodsnovellstmapproachversuswidelyusedtriplecollocationtechnique-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhao-montzka-vereecken-franssen-acomparativeanalysisofremotesensingsoilmoisturedatasetsfusionmethodsnovellstmapproachversuswidelyusedtriplecollocationtechnique-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{zhao_comparative_2024,\n\ttitle = {A {Comparative} {Analysis} of {Remote} {Sensing} {Soil} {Moisture} {Datasets} {Fusion} {Methods}: {Novel} {LSTM} {Approach} {Versus} {Widely} {Used} {Triple} {Collocation} {Technique}},\n\tvolume = {17},\n\tcopyright = {https://creativecommons.org/licenses/by-nc-nd/4.0/},\n\tissn = {1939-1404, 2151-1535},\n\tshorttitle = {A {Comparative} {Analysis} of {Remote} {Sensing} {Soil} {Moisture} {Datasets} {Fusion} {Methods}},\n\turl = {https://ieeexplore.ieee.org/document/10669050/},\n\tdoi = {10.1109/JSTARS.2024.3455549},\n\turldate = {2024-11-21},\n\tjournal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},\n\tauthor = {Zhao, Haojin and Montzka, Carsten and Vereecken, Harry and Franssen, Harrie-Jan Hendricks},\n\tyear = {2024},\n\tpages = {16659--16671},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gorooei-aynehband-behrend-jseidel-kumarsrivastava-rahnama-gaiser-shorttermresponseofsoilorganiccarbonindicestodifferentfarmingstrategiesandcroprotationsystemsinasemiaridwarmregion-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.hindawi.com/journals/aess/2024/8594691/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gorooei-aynehband-behrend-jseidel-kumarsrivastava-rahnama-gaiser-shorttermresponseofsoilorganiccarbonindicestodifferentfarmingstrategiesandcroprotationsystemsinasemiaridwarmregion-2024', 'https://www.hindawi.com/journals/aess/2024/8594691/', event);\">\n    Short-Term Response of Soil Organic Carbon Indices to Different Farming Strategies and Crop Rotation Systems in a Semiarid Warm Region.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gorooei, A.; Aynehband, A.; Behrend, D.; J. Seidel, S.; Kumar Srivastava, A.; Rahnama, A.;  and Gaiser, T.\n</span>\n\n  \n\n</span>\n\n  <i>Applied and Environmental Soil Science</i>, 2024: 1–11. April 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.hindawi.com/journals/aess/2024/8594691/\"\n     onclick=\"log_download('gorooei-aynehband-behrend-jseidel-kumarsrivastava-rahnama-gaiser-shorttermresponseofsoilorganiccarbonindicestodifferentfarmingstrategiesandcroprotationsystemsinasemiaridwarmregion-2024', 'https://www.hindawi.com/journals/aess/2024/8594691/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Short-Term Response of Soil Organic Carbon Indices to Different Farming Strategies and Crop Rotation Systems in a Semiarid Warm Region [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1155/2024/8594691\"\n     onclick=\"log_download('gorooei-aynehband-behrend-jseidel-kumarsrivastava-rahnama-gaiser-shorttermresponseofsoilorganiccarbonindicestodifferentfarmingstrategiesandcroprotationsystemsinasemiaridwarmregion-2024', 'http://doi.org/10.1155/2024/8594691', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gorooei-aynehband-behrend-jseidel-kumarsrivastava-rahnama-gaiser-shorttermresponseofsoilorganiccarbonindicestodifferentfarmingstrategiesandcroprotationsystemsinasemiaridwarmregion-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gorooei-aynehband-behrend-jseidel-kumarsrivastava-rahnama-gaiser-shorttermresponseofsoilorganiccarbonindicestodifferentfarmingstrategiesandcroprotationsystemsinasemiaridwarmregion-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{gorooei_short-term_2024,\n\ttitle = {Short-{Term} {Response} of {Soil} {Organic} {Carbon} {Indices} to {Different} {Farming} {Strategies} and {Crop} {Rotation} {Systems} in a {Semiarid} {Warm} {Region}},\n\tvolume = {2024},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1687-7675, 1687-7667},\n\turl = {https://www.hindawi.com/journals/aess/2024/8594691/},\n\tdoi = {10.1155/2024/8594691},\n\tabstract = {Several indices can be used to assess the impact of short-term conservation agriculture strategies on improving soil organic carbon (SOC). To find out how the SOC pools and the carbon lability influence the carbon management index (CMI) in response to different agricultural practices in a warm semiarid region, the carbon lability index (LI) and the carbon pool index (CPI) were measured under the interactive effect of different fertilizer applications and crop residue management (hereafter referred to as “farming strategies”) in combination with four crop rotation systems in Ahvaz, Khuzestan, Iran, over four growing seasons from 2018 to 2020. The farming strategies were as follows: (1) using the standard rate of inorganic fertilizer used in the region and removing crop residues from the soil (SIF\\_no-CR); (2) applying the standard rate of organic fertilizers used in the region and returning 30\\% of crop residues to the soil (SOF\\_30\\% CR); and (3) integrating the use of inorganic and organic fertilizers and returning 15\\% of crop residues to the soil (IOF\\_15\\% CR). The crop rotation systems were fallow-wheat (F-W), corn-wheat (C-W), sesame-wheat (S-W), and mung bean-wheat (B-W). No statistically significant difference was observed between the different farming strategies and rotation systems with respect to LI after two years of the experiment. The highest (1.26) and lowest (1.06) CPIs were observed for SOF\\_30\\% CR and SIF\\_no-CR, respectively. The magnitude of the CMI values followed the order SOF\\_30\\% CR (121) {\\textgreater} IOF\\_15\\% CR (107) ≥ SIF\\_no-CR (106). B-W and F-W had the highest and lowest CPI with values of 1.29 and 1.01, respectively. No statistically significant difference was found for the different crop rotation systems. Given the low impact of the common farming practices in the region, e.g., SIF\\_no-CR and F-W, on CPI and CMI at 24 months, our results showed that farming strategies with manure application and crop residue management and summer wheat-based rotation systems appear to be more appropriate farming strategies to improve CMI in arable land.},\n\tlanguage = {en},\n\turldate = {2024-11-15},\n\tjournal = {Applied and Environmental Soil Science},\n\tauthor = {Gorooei, Aram and Aynehband, Amir and Behrend, Dominik and J. Seidel, Sabine and Kumar Srivastava, Amit and Rahnama, Afrasyab and Gaiser, Thomas},\n\teditor = {El-Gendy, Nour Sh.},\n\tmonth = apr,\n\tyear = {2024},\n\tpages = {1--11},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Several indices can be used to assess the impact of short-term conservation agriculture strategies on improving soil organic carbon (SOC). To find out how the SOC pools and the carbon lability influence the carbon management index (CMI) in response to different agricultural practices in a warm semiarid region, the carbon lability index (LI) and the carbon pool index (CPI) were measured under the interactive effect of different fertilizer applications and crop residue management (hereafter referred to as “farming strategies”) in combination with four crop rotation systems in Ahvaz, Khuzestan, Iran, over four growing seasons from 2018 to 2020. The farming strategies were as follows: (1) using the standard rate of inorganic fertilizer used in the region and removing crop residues from the soil (SIF_no-CR); (2) applying the standard rate of organic fertilizers used in the region and returning 30% of crop residues to the soil (SOF_30% CR); and (3) integrating the use of inorganic and organic fertilizers and returning 15% of crop residues to the soil (IOF_15% CR). The crop rotation systems were fallow-wheat (F-W), corn-wheat (C-W), sesame-wheat (S-W), and mung bean-wheat (B-W). No statistically significant difference was observed between the different farming strategies and rotation systems with respect to LI after two years of the experiment. The highest (1.26) and lowest (1.06) CPIs were observed for SOF_30% CR and SIF_no-CR, respectively. The magnitude of the CMI values followed the order SOF_30% CR (121) \\textgreater IOF_15% CR (107) ≥ SIF_no-CR (106). B-W and F-W had the highest and lowest CPI with values of 1.29 and 1.01, respectively. No statistically significant difference was found for the different crop rotation systems. Given the low impact of the common farming practices in the region, e.g., SIF_no-CR and F-W, on CPI and CMI at 24 months, our results showed that farming strategies with manure application and crop residue management and summer wheat-based rotation systems appear to be more appropriate farming strategies to improve CMI in arable land.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bazzo-kamali-dossantosvianna-behrend-hueging-schleip-mosebach-haub-etal-integrationofuavsensedfeaturesusingmachinelearningmethodstoassessspeciesrichnessinwetgrasslandecosystems-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bazzo-kamali-dossantosvianna-behrend-hueging-schleip-mosebach-haub-etal-integrationofuavsensedfeaturesusingmachinelearningmethodstoassessspeciesrichnessinwetgrasslandecosystems-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558', event);\">\n    Integration of UAV-sensed features using machine learning methods to assess species richness in wet grassland ecosystems.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bazzo, C. O. G.; Kamali, B.; Dos Santos Vianna, M.; Behrend, D.; Hueging, H.; Schleip, I.; Mosebach, P.; Haub, A.; Behrendt, A.;  and Gaiser, T.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Informatics</i>, 83: 102813. November 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558\"\n     onclick=\"log_download('bazzo-kamali-dossantosvianna-behrend-hueging-schleip-mosebach-haub-etal-integrationofuavsensedfeaturesusingmachinelearningmethodstoassessspeciesrichnessinwetgrasslandecosystems-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Integration of UAV-sensed features using machine learning methods to assess species richness in wet grassland ecosystems [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecoinf.2024.102813\"\n     onclick=\"log_download('bazzo-kamali-dossantosvianna-behrend-hueging-schleip-mosebach-haub-etal-integrationofuavsensedfeaturesusingmachinelearningmethodstoassessspeciesrichnessinwetgrasslandecosystems-2024', 'http://doi.org/10.1016/j.ecoinf.2024.102813', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bazzo-kamali-dossantosvianna-behrend-hueging-schleip-mosebach-haub-etal-integrationofuavsensedfeaturesusingmachinelearningmethodstoassessspeciesrichnessinwetgrasslandecosystems-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bazzo-kamali-dossantosvianna-behrend-hueging-schleip-mosebach-haub-etal-integrationofuavsensedfeaturesusingmachinelearningmethodstoassessspeciesrichnessinwetgrasslandecosystems-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{bazzo_integration_2024,\n\ttitle = {Integration of {UAV}-sensed features using machine learning methods to assess species richness in wet grassland ecosystems},\n\tvolume = {83},\n\tissn = {15749541},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1574954124003558},\n\tdoi = {10.1016/j.ecoinf.2024.102813},\n\tlanguage = {en},\n\turldate = {2024-11-15},\n\tjournal = {Ecological Informatics},\n\tauthor = {Bazzo, Clara Oliva Gonçalves and Kamali, Bahareh and Dos Santos Vianna, Murilo and Behrend, Dominik and Hueging, Hubert and Schleip, Inga and Mosebach, Paul and Haub, Almut and Behrendt, Axel and Gaiser, Thomas},\n\tmonth = nov,\n\tyear = {2024},\n\tpages = {102813},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bazzo-kamali-behrend-hueging-schleip-mosebach-behrendt-gaiser-assessingtheeffectoffielddisturbancesonbiomassestimationingrasslandsusinguavderivedcanopyheightmodels-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/10.1007/s41064-024-00322-x\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bazzo-kamali-behrend-hueging-schleip-mosebach-behrendt-gaiser-assessingtheeffectoffielddisturbancesonbiomassestimationingrasslandsusinguavderivedcanopyheightmodels-2024', 'https://link.springer.com/10.1007/s41064-024-00322-x', event);\">\n    Assessing the Effect of Field Disturbances On Biomass Estimation in Grasslands Using UAV-Derived Canopy Height Models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bazzo, C. O. G.; Kamali, B.; Behrend, D.; Hueging, H.; Schleip, I.; Mosebach, P.; Behrendt, A.;  and Gaiser, T.\n</span>\n\n  \n\n</span>\n\n  <i>PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science</i>. November 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/10.1007/s41064-024-00322-x\"\n     onclick=\"log_download('bazzo-kamali-behrend-hueging-schleip-mosebach-behrendt-gaiser-assessingtheeffectoffielddisturbancesonbiomassestimationingrasslandsusinguavderivedcanopyheightmodels-2024', 'https://link.springer.com/10.1007/s41064-024-00322-x', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Assessing the Effect of Field Disturbances On Biomass Estimation in Grasslands Using UAV-Derived Canopy Height Models [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s41064-024-00322-x\"\n     onclick=\"log_download('bazzo-kamali-behrend-hueging-schleip-mosebach-behrendt-gaiser-assessingtheeffectoffielddisturbancesonbiomassestimationingrasslandsusinguavderivedcanopyheightmodels-2024', 'http://doi.org/10.1007/s41064-024-00322-x', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bazzo-kamali-behrend-hueging-schleip-mosebach-behrendt-gaiser-assessingtheeffectoffielddisturbancesonbiomassestimationingrasslandsusinguavderivedcanopyheightmodels-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bazzo-kamali-behrend-hueging-schleip-mosebach-behrendt-gaiser-assessingtheeffectoffielddisturbancesonbiomassestimationingrasslandsusinguavderivedcanopyheightmodels-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{bazzo_assessing_2024,\n\ttitle = {Assessing the {Effect} of {Field} {Disturbances} {On} {Biomass} {Estimation} in {Grasslands} {Using} {UAV}-{Derived} {Canopy} {Height} {Models}},\n\tissn = {2512-2789, 2512-2819},\n\turl = {https://link.springer.com/10.1007/s41064-024-00322-x},\n\tdoi = {10.1007/s41064-024-00322-x},\n\tabstract = {Abstract\n            Accurate estimation of biomass in grasslands is essential for understanding ecosystem health and productivity. Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools for biomass estimation using canopy height models derived from high-resolution imagery. However, the impact of field disturbances, such as lodging and molehills, on the accuracy of biomass estimation using UAV-derived canopy height models remains underexplored. This study aimed to assess the relationship between UAV-derived canopy height and both reference canopy height measurements and dry biomass, accounting for different management systems and disturbance scenarios. UAV data were collected using a multispectral camera, and ground-based measurements were obtained for validation. The results revealed that UAV-derived canopy height models remained accurate in estimating vegetation height, even in the presence of disturbances. However, the relationship between UAV-derived canopy height and dry biomass was affected by disturbances, leading to overestimation or underestimation of biomass depending on disturbance type and severity. The impact of disturbances on biomass estimation varied across cutting systems. These findings highlight the potential of UAV-derived canopy height models for estimating vegetation structure, but also underscore the need for caution in relying solely on these models for accurate biomass estimation in heterogeneous grasslands. Future research should explore strategies to enhance biomass estimation accuracy by integrating additional data sources and accounting for field disturbances.},\n\tlanguage = {en},\n\turldate = {2024-11-15},\n\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\n\tauthor = {Bazzo, Clara Oliva Gonçalves and Kamali, Bahareh and Behrend, Dominik and Hueging, Hubert and Schleip, Inga and Mosebach, Paul and Behrendt, Axel and Gaiser, Thomas},\n\tmonth = nov,\n\tyear = {2024},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Accurate estimation of biomass in grasslands is essential for understanding ecosystem health and productivity. Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools for biomass estimation using canopy height models derived from high-resolution imagery. However, the impact of field disturbances, such as lodging and molehills, on the accuracy of biomass estimation using UAV-derived canopy height models remains underexplored. This study aimed to assess the relationship between UAV-derived canopy height and both reference canopy height measurements and dry biomass, accounting for different management systems and disturbance scenarios. UAV data were collected using a multispectral camera, and ground-based measurements were obtained for validation. The results revealed that UAV-derived canopy height models remained accurate in estimating vegetation height, even in the presence of disturbances. However, the relationship between UAV-derived canopy height and dry biomass was affected by disturbances, leading to overestimation or underestimation of biomass depending on disturbance type and severity. The impact of disturbances on biomass estimation varied across cutting systems. These findings highlight the potential of UAV-derived canopy height models for estimating vegetation structure, but also underscore the need for caution in relying solely on these models for accurate biomass estimation in heterogeneous grasslands. Future research should explore strategies to enhance biomass estimation accuracy by integrating additional data sources and accounting for field disturbances.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"seidel-ahmadi-weihermller-coudel-lopez-behrend-kamali-gaiser-etal-theoverlookedeffectsofenvironmentalimpactsonrootshootratioinexperimentsandsoilcropmodels-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'seidel-ahmadi-weihermller-coudel-lopez-behrend-kamali-gaiser-etal-theoverlookedeffectsofenvironmentalimpactsonrootshootratioinexperimentsandsoilcropmodels-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955', event);\">\n    The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Seidel, S.; Ahmadi, S.; Weihermüller, L.; Couëdel, A.; Lopez, G.; Behrend, D.; Kamali, B.; Gaiser, T.;  and Hernández-Ochoa, I.\n</span>\n\n  \n\n</span>\n\n  <i>Science of The Total Environment</i>, 955: 176738. December 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955\"\n     onclick=\"log_download('seidel-ahmadi-weihermller-coudel-lopez-behrend-kamali-gaiser-etal-theoverlookedeffectsofenvironmentalimpactsonrootshootratioinexperimentsandsoilcropmodels-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.scitotenv.2024.176738\"\n     onclick=\"log_download('seidel-ahmadi-weihermller-coudel-lopez-behrend-kamali-gaiser-etal-theoverlookedeffectsofenvironmentalimpactsonrootshootratioinexperimentsandsoilcropmodels-2024', 'http://doi.org/10.1016/j.scitotenv.2024.176738', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/seidel-ahmadi-weihermller-coudel-lopez-behrend-kamali-gaiser-etal-theoverlookedeffectsofenvironmentalimpactsonrootshootratioinexperimentsandsoilcropmodels-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('seidel-ahmadi-weihermller-coudel-lopez-behrend-kamali-gaiser-etal-theoverlookedeffectsofenvironmentalimpactsonrootshootratioinexperimentsandsoilcropmodels-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{seidel_overlooked_2024,\n\ttitle = {The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models},\n\tvolume = {955},\n\tissn = {00489697},\n\tshorttitle = {The overlooked effects of environmental impacts on root},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969724068955},\n\tdoi = {10.1016/j.scitotenv.2024.176738},\n\tlanguage = {en},\n\turldate = {2024-10-24},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Seidel, S.J. and Ahmadi, S.H. and Weihermüller, L. and Couëdel, A. and Lopez, G. and Behrend, D. and Kamali, B. and Gaiser, T. and Hernández-Ochoa, I.M.},\n\tmonth = dec,\n\tyear = {2024},\n\tpages = {176738},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"rahmati-amelung-brogi-dari-flammini-bogena-brocca-chen-etal-soilmoisturememorystateoftheartandthewayforward-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'rahmati-amelung-brogi-dari-flammini-bogena-brocca-chen-etal-soilmoisturememorystateoftheartandthewayforward-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828', event);\">\n    Soil Moisture Memory: State‐Of‐The‐Art and the Way Forward.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rahmati, M.; Amelung, W.; Brogi, C.; Dari, J.; Flammini, A.; Bogena, H.; Brocca, L.; Chen, H.; Groh, J.; Koster, R. D.; McColl, K. A.; Montzka, C.; Moradi, S.; Rahi, A.; Sharghi S., F.;  and Vereecken, H.\n</span>\n\n  \n\n</span>\n\n  <i>Reviews of Geophysics</i>, 62(2): e2023RG000828. June 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828\"\n     onclick=\"log_download('rahmati-amelung-brogi-dari-flammini-bogena-brocca-chen-etal-soilmoisturememorystateoftheartandthewayforward-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Soil Moisture Memory: State‐Of‐The‐Art and the Way Forward [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2023RG000828\"\n     onclick=\"log_download('rahmati-amelung-brogi-dari-flammini-bogena-brocca-chen-etal-soilmoisturememorystateoftheartandthewayforward-2024', 'http://doi.org/10.1029/2023RG000828', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/rahmati-amelung-brogi-dari-flammini-bogena-brocca-chen-etal-soilmoisturememorystateoftheartandthewayforward-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('rahmati-amelung-brogi-dari-flammini-bogena-brocca-chen-etal-soilmoisturememorystateoftheartandthewayforward-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{rahmati_soil_2024,\n\ttitle = {Soil {Moisture} {Memory}: {State}‐{Of}‐{The}‐{Art} and the {Way} {Forward}},\n\tvolume = {62},\n\tissn = {8755-1209, 1944-9208},\n\tshorttitle = {Soil {Moisture} {Memory}},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023RG000828},\n\tdoi = {10.1029/2023RG000828},\n\tabstract = {Abstract\n            Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil‐plant‐atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth‐dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM.\n          , \n            Plain Language Summary\n            Our review paper takes an in‐depth look at soil moisture memory, which is how soil records its moisture history over time and space. Analogous to human psychology, which seeks to understand how a person&#x27;s/society&#x27;s memory influences his/her present and future behavior, understanding soil moisture memory encourages consideration of how such memory determines present state and might determine future behavior of soils exposed to environmental disturbances. Soil moisture memory can be affected by a variety of factors, both external (e.g., weather extremes) and internal (soil&#x27;s unique properties). It affects everything from the air to the way our landscapes respond to disasters like droughts, wildfires, and floods. We also studied how this phenomenon affects the balance of water and energy in our environment, the health of our plants, and even how it communicates with the atmosphere. We show how it can change depending on where you are on the planet, the time of year, and how deep you dig into the soil. We offer scientists insights into how weather and land surface models can become more accurate by accounting for soil moisture memory. Its understanding not only helps us predict and manage our environment, but also provides opportunities for exciting scientific discoveries.\n          , \n            Key Points\n            \n              \n                \n                  Atmospheric forcings, land use and management, and soil processes and mechanisms explain how and why soil moisture memory emerges in ecosystems\n                \n                \n                  Nonlocality of moisture memory, its spread across different regions, and its interaction with large‐scale climate phenomena are underexplored\n                \n                \n                  Further advances in land surface models and closer integration of model simulations and observations are needed to better characterize moisture memory},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-10-23},\n\tjournal = {Reviews of Geophysics},\n\tauthor = {Rahmati, Mehdi and Amelung, Wulf and Brogi, Cosimo and Dari, Jacopo and Flammini, Alessia and Bogena, Heye and Brocca, Luca and Chen, Hao and Groh, Jannis and Koster, Randal D. and McColl, Kaighin A. and Montzka, Carsten and Moradi, Shirin and Rahi, Arash and Sharghi S., Farnaz and Vereecken, Harry},\n\tmonth = jun,\n\tyear = {2024},\n\tpages = {e2023RG000828},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil‐plant‐atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth‐dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM. , Plain Language Summary Our review paper takes an in‐depth look at soil moisture memory, which is how soil records its moisture history over time and space. Analogous to human psychology, which seeks to understand how a person's/society's memory influences his/her present and future behavior, understanding soil moisture memory encourages consideration of how such memory determines present state and might determine future behavior of soils exposed to environmental disturbances. Soil moisture memory can be affected by a variety of factors, both external (e.g., weather extremes) and internal (soil's unique properties). It affects everything from the air to the way our landscapes respond to disasters like droughts, wildfires, and floods. We also studied how this phenomenon affects the balance of water and energy in our environment, the health of our plants, and even how it communicates with the atmosphere. We show how it can change depending on where you are on the planet, the time of year, and how deep you dig into the soil. We offer scientists insights into how weather and land surface models can become more accurate by accounting for soil moisture memory. Its understanding not only helps us predict and manage our environment, but also provides opportunities for exciting scientific discoveries. , Key Points Atmospheric forcings, land use and management, and soil processes and mechanisms explain how and why soil moisture memory emerges in ecosystems Nonlocality of moisture memory, its spread across different regions, and its interaction with large‐scale climate phenomena are underexplored Further advances in land surface models and closer integration of model simulations and observations are needed to better characterize moisture memory\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhu-siebert-climatedriveninterannualvariabilityinsubnationalirrigationareasacrosseurope-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s43247-024-01721-z\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'zhu-siebert-climatedriveninterannualvariabilityinsubnationalirrigationareasacrosseurope-2024', 'https://www.nature.com/articles/s43247-024-01721-z', event);\">\n    Climate-driven interannual variability in subnational irrigation areas across Europe.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhu, W.;  and Siebert, S.\n</span>\n\n  \n\n</span>\n\n  <i>Communications Earth & Environment</i>, 5(1): 554. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s43247-024-01721-z\"\n     onclick=\"log_download('zhu-siebert-climatedriveninterannualvariabilityinsubnationalirrigationareasacrosseurope-2024', 'https://www.nature.com/articles/s43247-024-01721-z', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Climate-driven interannual variability in subnational irrigation areas across Europe [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s43247-024-01721-z\"\n     onclick=\"log_download('zhu-siebert-climatedriveninterannualvariabilityinsubnationalirrigationareasacrosseurope-2024', 'http://doi.org/10.1038/s43247-024-01721-z', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhu-siebert-climatedriveninterannualvariabilityinsubnationalirrigationareasacrosseurope-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhu-siebert-climatedriveninterannualvariabilityinsubnationalirrigationareasacrosseurope-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{zhu_climate-driven_2024,\n\ttitle = {Climate-driven interannual variability in subnational irrigation areas across {Europe}},\n\tvolume = {5},\n\tissn = {2662-4435},\n\turl = {https://www.nature.com/articles/s43247-024-01721-z},\n\tdoi = {10.1038/s43247-024-01721-z},\n\tabstract = {Abstract\n            Irrigation profoundly impacts ecology and agricultural productivity, with irrigated areas varying across regions and years. Interannual dynamics of irrigation extent are lacking, particularly in humid regions of Europe. We analyzed the response of irrigated areas to drought conditions in areas equipped for irrigation and used the derived relationships to estimate annual irrigated areas for 32 European countries in the period 1990–2020. Interannual variability of irrigated areas varied notably, particularly in more humid Northern and Western Europe. In most humid regions, irrigated area is larger in dry years, whereas in more arid regions like Spain, it is larger in wet years. The largest irrigated area across Europe occurred in dry years 2003 and 2018 (11.93 and 11.77 million hectares), while the smallest is estimated for the wet years 2002 and 2014 (10.71 and 10.31 million hectares). The findings of this study help to improve scenario development and water resources management.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-10-23},\n\tjournal = {Communications Earth \\&amp; Environment},\n\tauthor = {Zhu, Wanxue and Siebert, Stefan},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {554},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Irrigation profoundly impacts ecology and agricultural productivity, with irrigated areas varying across regions and years. Interannual dynamics of irrigation extent are lacking, particularly in humid regions of Europe. We analyzed the response of irrigated areas to drought conditions in areas equipped for irrigation and used the derived relationships to estimate annual irrigated areas for 32 European countries in the period 1990–2020. Interannual variability of irrigated areas varied notably, particularly in more humid Northern and Western Europe. In most humid regions, irrigated area is larger in dry years, whereas in more arid regions like Spain, it is larger in wet years. The largest irrigated area across Europe occurred in dry years 2003 and 2018 (11.93 and 11.77 million hectares), while the smallest is estimated for the wet years 2002 and 2014 (10.71 and 10.31 million hectares). The findings of this study help to improve scenario development and water resources management.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"baumert-heckelei-storm-probabilisticcroptypemappingforexantemodellingandspatialdisaggregation-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'baumert-heckelei-storm-probabilisticcroptypemappingforexantemodellingandspatialdisaggregation-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789', event);\">\n    Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Baumert, J.; Heckelei, T.;  and Storm, H.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Informatics</i>, 83: 102836. November 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789\"\n     onclick=\"log_download('baumert-heckelei-storm-probabilisticcroptypemappingforexantemodellingandspatialdisaggregation-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecoinf.2024.102836\"\n     onclick=\"log_download('baumert-heckelei-storm-probabilisticcroptypemappingforexantemodellingandspatialdisaggregation-2024', 'http://doi.org/10.1016/j.ecoinf.2024.102836', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/baumert-heckelei-storm-probabilisticcroptypemappingforexantemodellingandspatialdisaggregation-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('baumert-heckelei-storm-probabilisticcroptypemappingforexantemodellingandspatialdisaggregation-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{baumert_probabilistic_2024,\n\ttitle = {Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation},\n\tvolume = {83},\n\tissn = {15749541},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1574954124003789},\n\tdoi = {10.1016/j.ecoinf.2024.102836},\n\tlanguage = {en},\n\turldate = {2024-10-23},\n\tjournal = {Ecological Informatics},\n\tauthor = {Baumert, Josef and Heckelei, Thomas and Storm, Hugo},\n\tmonth = nov,\n\tyear = {2024},\n\tpages = {102836},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"schulze-kusche-gerdener-dll-mllerschmied-benefitsandpitfallsofgraceandstreamflowassimilationforimprovingthestreamflowsimulationsofthewatergapglobalhydrologymodel-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'schulze-kusche-gerdener-dll-mllerschmied-benefitsandpitfallsofgraceandstreamflowassimilationforimprovingthestreamflowsimulationsofthewatergapglobalhydrologymodel-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092', event);\">\n    Benefits and Pitfalls of GRACE and Streamflow Assimilation for Improving the Streamflow Simulations of the WaterGAP Global Hydrology Model.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Schulze, K.; Kusche, J.; Gerdener, H.; Döll, P.;  and Müller Schmied, H.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Advances in Modeling Earth Systems</i>, 16(10): e2023MS004092. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092\"\n     onclick=\"log_download('schulze-kusche-gerdener-dll-mllerschmied-benefitsandpitfallsofgraceandstreamflowassimilationforimprovingthestreamflowsimulationsofthewatergapglobalhydrologymodel-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Benefits and Pitfalls of GRACE and Streamflow Assimilation for Improving the Streamflow Simulations of the WaterGAP Global Hydrology Model [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2023MS004092\"\n     onclick=\"log_download('schulze-kusche-gerdener-dll-mllerschmied-benefitsandpitfallsofgraceandstreamflowassimilationforimprovingthestreamflowsimulationsofthewatergapglobalhydrologymodel-2024', 'http://doi.org/10.1029/2023MS004092', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/schulze-kusche-gerdener-dll-mllerschmied-benefitsandpitfallsofgraceandstreamflowassimilationforimprovingthestreamflowsimulationsofthewatergapglobalhydrologymodel-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('schulze-kusche-gerdener-dll-mllerschmied-benefitsandpitfallsofgraceandstreamflowassimilationforimprovingthestreamflowsimulationsofthewatergapglobalhydrologymodel-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{schulze_benefits_2024,\n\ttitle = {Benefits and {Pitfalls} of {GRACE} and {Streamflow} {Assimilation} for {Improving} the {Streamflow} {Simulations} of the {WaterGAP} {Global} {Hydrology} {Model}},\n\tvolume = {16},\n\tissn = {1942-2466, 1942-2466},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023MS004092},\n\tdoi = {10.1029/2023MS004092},\n\tabstract = {Abstract\n            Distribution and change of freshwater resources is often simulated with global hydrological models. However, owing to process representation limitations and forcing data uncertainties, these model simulations have shortcomings. Combining them with observations via data assimilation, for example, with data from the Gravity Recovery and Climate Experiment (GRACE) mission or streamflow measured at in situ stations is considered to improve the realism of the simulations. We assimilate gridded total water storage anomaly (TWSA) from GRACE into the WaterGAP Global Hydrology Model (WGHM) over the Mississippi River basin via an Ensemble Kalman Filter. Our results agree with previous studies where assimilating GRACE observations nudges TWSA simulations closer to the observations, reducing the root mean square error (RMSE) by 21\\% compared to an uncalibrated model. However, simulations of streamflow show degeneration at more than 90\\% of all gauge stations for metrics such as RMSE and correlations; only the annual phase of simulated streamflow improves at half the stations. Therefore, for the first time, we instead assimilated streamflow observations into the WGHM, which improved simulated streamflow at up to nearly 80\\% of the stations, with normalized RMSE showing improvements of up to 0.1, while TWSA was well‐simulated in all metrics. Combining both approaches, that is, jointly assimilating GRACE‐derived TWSA and streamflow observations, leads to a trade‐off between a good fit of both variables albeit skewed to the GRACE observations. Overall, we speculate that our findings point to limitations of process representation in WGHM hindering consistent flux simulation from the storage history, especially in dry regions.\n          , \n            Plain Language Summary\n            The distribution of freshwater on Earth can be simulated by hydrological models like the WaterGAP Global Hydrology Model (WGHM). Changes of the total water storages can also be derived from satellite gravimetry, for example, with the Gravity Recovery and Climate Experiment (GRACE) mission. Model and observations do not necessarily agree and are both prone to errors. We combined the model and observations over the Mississippi River basin taking the errors into account by applying a data assimilation technique. This led to a more realistic simulation of the total water storage changes. Since simulated streamflow was found to degenerate at nearly all gauge stations, we assimilated streamflow observations (instead of GRACE data) into the WGHM. This turned out to improve simulated streamflow at up to nearly 80\\% of the stations. The assimilation of both data sets (GRACE and streamflow) together leads to a compromise between the TWSA and the streamflow simulations, with the GRACE data affecting the simulations more than the streamflow data. Our findings are expected to aid reducing the weaknesses of the WGHM model equations and thus contribute to improved quantification of Earth&#x27;s freshwater distribution in the future.\n          , \n            Key Points\n            \n              \n                \n                  GRACE assimilation improves the WGHM storage representation, but degrades the simulated streamflow at up to 99\\% of the gauge stations\n                \n                \n                  Assimilating streamflow data instead improves the streamflow simulations at up to 79\\% of the validation stations\n                \n                \n                  Joint assimilation leads to a trade‐off between a good fit of simulated storages and streamflow albeit skewed to the GRACE observations},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2024-10-23},\n\tjournal = {Journal of Advances in Modeling Earth Systems},\n\tauthor = {Schulze, K. and Kusche, J. and Gerdener, H. and Döll, P. and Müller Schmied, H.},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {e2023MS004092},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Distribution and change of freshwater resources is often simulated with global hydrological models. However, owing to process representation limitations and forcing data uncertainties, these model simulations have shortcomings. Combining them with observations via data assimilation, for example, with data from the Gravity Recovery and Climate Experiment (GRACE) mission or streamflow measured at in situ stations is considered to improve the realism of the simulations. We assimilate gridded total water storage anomaly (TWSA) from GRACE into the WaterGAP Global Hydrology Model (WGHM) over the Mississippi River basin via an Ensemble Kalman Filter. Our results agree with previous studies where assimilating GRACE observations nudges TWSA simulations closer to the observations, reducing the root mean square error (RMSE) by 21% compared to an uncalibrated model. However, simulations of streamflow show degeneration at more than 90% of all gauge stations for metrics such as RMSE and correlations; only the annual phase of simulated streamflow improves at half the stations. Therefore, for the first time, we instead assimilated streamflow observations into the WGHM, which improved simulated streamflow at up to nearly 80% of the stations, with normalized RMSE showing improvements of up to 0.1, while TWSA was well‐simulated in all metrics. Combining both approaches, that is, jointly assimilating GRACE‐derived TWSA and streamflow observations, leads to a trade‐off between a good fit of both variables albeit skewed to the GRACE observations. Overall, we speculate that our findings point to limitations of process representation in WGHM hindering consistent flux simulation from the storage history, especially in dry regions. , Plain Language Summary The distribution of freshwater on Earth can be simulated by hydrological models like the WaterGAP Global Hydrology Model (WGHM). Changes of the total water storages can also be derived from satellite gravimetry, for example, with the Gravity Recovery and Climate Experiment (GRACE) mission. Model and observations do not necessarily agree and are both prone to errors. We combined the model and observations over the Mississippi River basin taking the errors into account by applying a data assimilation technique. This led to a more realistic simulation of the total water storage changes. Since simulated streamflow was found to degenerate at nearly all gauge stations, we assimilated streamflow observations (instead of GRACE data) into the WGHM. This turned out to improve simulated streamflow at up to nearly 80% of the stations. The assimilation of both data sets (GRACE and streamflow) together leads to a compromise between the TWSA and the streamflow simulations, with the GRACE data affecting the simulations more than the streamflow data. Our findings are expected to aid reducing the weaknesses of the WGHM model equations and thus contribute to improved quantification of Earth's freshwater distribution in the future. , Key Points GRACE assimilation improves the WGHM storage representation, but degrades the simulated streamflow at up to 99% of the gauge stations Assimilating streamflow data instead improves the streamflow simulations at up to 79% of the validation stations Joint assimilation leads to a trade‐off between a good fit of simulated storages and streamflow albeit skewed to the GRACE observations\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xiong-feng-zhou-kusche-shen-yang-wang-zhong-separationofearthquakeandhydrologysignalsfromgracesatellitesdataviaindependentcomponentanalysisacasestudyinthesumatraregion-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://academic.oup.com/gji/article/239/3/1597/7778285\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'xiong-feng-zhou-kusche-shen-yang-wang-zhong-separationofearthquakeandhydrologysignalsfromgracesatellitesdataviaindependentcomponentanalysisacasestudyinthesumatraregion-2024', 'https://academic.oup.com/gji/article/239/3/1597/7778285', event);\">\n    Separation of earthquake and hydrology signals from GRACE satellites data via independent component analysis: a case study in the Sumatra region.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xiong, Y.; Feng, W.; Zhou, X.; Kusche, J.; Shen, Y.; Yang, M.; Wang, C.;  and Zhong, M.\n</span>\n\n  \n\n</span>\n\n  <i>Geophysical Journal International</i>, 239(3): 1597–1616. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://academic.oup.com/gji/article/239/3/1597/7778285\"\n     onclick=\"log_download('xiong-feng-zhou-kusche-shen-yang-wang-zhong-separationofearthquakeandhydrologysignalsfromgracesatellitesdataviaindependentcomponentanalysisacasestudyinthesumatraregion-2024', 'https://academic.oup.com/gji/article/239/3/1597/7778285', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Separation of earthquake and hydrology signals from GRACE satellites data via independent component analysis: a case study in the Sumatra region [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1093/gji/ggae351\"\n     onclick=\"log_download('xiong-feng-zhou-kusche-shen-yang-wang-zhong-separationofearthquakeandhydrologysignalsfromgracesatellitesdataviaindependentcomponentanalysisacasestudyinthesumatraregion-2024', 'http://doi.org/10.1093/gji/ggae351', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xiong-feng-zhou-kusche-shen-yang-wang-zhong-separationofearthquakeandhydrologysignalsfromgracesatellitesdataviaindependentcomponentanalysisacasestudyinthesumatraregion-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xiong-feng-zhou-kusche-shen-yang-wang-zhong-separationofearthquakeandhydrologysignalsfromgracesatellitesdataviaindependentcomponentanalysisacasestudyinthesumatraregion-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{xiong_separation_2024,\n\ttitle = {Separation of earthquake and hydrology signals from {GRACE} satellites data via independent component analysis: a case study in the {Sumatra} region},\n\tvolume = {239},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {0956-540X, 1365-246X},\n\tshorttitle = {Separation of earthquake and hydrology signals from {GRACE} satellites data via independent component analysis},\n\turl = {https://academic.oup.com/gji/article/239/3/1597/7778285},\n\tdoi = {10.1093/gji/ggae351},\n\tabstract = {SUMMARY\n            The Gravity Recovery and Climate Experiment (GRACE) satellites have observed mass migrations caused by megathrust earthquakes. Extracting earthquake-related signals from GRACE data is still a challenge due to the interference from non-earthquake sources such as terrestrial hydrology. Instead of reducing hydrological signals by potentially biased hydrological models, in this study we apply a model-free technique of independent component analysis (ICA), to separate earthquake and non-earthquake signals from non-Gaussian GRACE data. We elucidate the principles and mechanisms of ICA for the separation of earthquake and hydrology signals, employing simulated data to demonstrate the process. Our findings demonstrate that both spatial ICA and temporal ICA are highly effective in discerning earthquake related to 2004 Mw 9.2 event and hydrological signals from GRACE data in the Sumatra region. This stands in stark contrast to principal component analysis, which often encounters challenges with signal intermingling. The utility of ICA is evident in its ability to distinctly delineate coseismic and post-seismic behaviours associated with megathrust events, including the 2004 Sumatra, the 2010 Maule, and the 2011 Tohoku earthquakes. ICA effectively mitigates the potential for misestimation of earthquake signals, an issue that can carry substantial implications. Therefore, employing ICA facilitates the accurate extraction of earthquake-related data from satellite gravity observations—a critical process for refining earthquake source parameters and understanding Earth&#x27;s rheological properties, especially when non-earthquake signals are significant and cannot be disregarded.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2024-10-23},\n\tjournal = {Geophysical Journal International},\n\tauthor = {Xiong, Yuhao and Feng, Wei and Zhou, Xin and Kusche, Jürgen and Shen, Yingchun and Yang, Meng and Wang, Changqing and Zhong, Min},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {1597--1616},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  SUMMARY The Gravity Recovery and Climate Experiment (GRACE) satellites have observed mass migrations caused by megathrust earthquakes. Extracting earthquake-related signals from GRACE data is still a challenge due to the interference from non-earthquake sources such as terrestrial hydrology. Instead of reducing hydrological signals by potentially biased hydrological models, in this study we apply a model-free technique of independent component analysis (ICA), to separate earthquake and non-earthquake signals from non-Gaussian GRACE data. We elucidate the principles and mechanisms of ICA for the separation of earthquake and hydrology signals, employing simulated data to demonstrate the process. Our findings demonstrate that both spatial ICA and temporal ICA are highly effective in discerning earthquake related to 2004 Mw 9.2 event and hydrological signals from GRACE data in the Sumatra region. This stands in stark contrast to principal component analysis, which often encounters challenges with signal intermingling. The utility of ICA is evident in its ability to distinctly delineate coseismic and post-seismic behaviours associated with megathrust events, including the 2004 Sumatra, the 2010 Maule, and the 2011 Tohoku earthquakes. ICA effectively mitigates the potential for misestimation of earthquake signals, an issue that can carry substantial implications. Therefore, employing ICA facilitates the accurate extraction of earthquake-related data from satellite gravity observations—a critical process for refining earthquake source parameters and understanding Earth's rheological properties, especially when non-earthquake signals are significant and cannot be disregarded.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jensen-gerdener-eicker-kusche-fiedler-observationsindicateregionallymisleadingwettinganddryingtrendsincmip6-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s41612-024-00788-x\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jensen-gerdener-eicker-kusche-fiedler-observationsindicateregionallymisleadingwettinganddryingtrendsincmip6-2024', 'https://www.nature.com/articles/s41612-024-00788-x', event);\">\n    Observations indicate regionally misleading wetting and drying trends in CMIP6.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jensen, L.; Gerdener, H.; Eicker, A.; Kusche, J.;  and Fiedler, S.\n</span>\n\n  \n\n</span>\n\n  <i>npj Climate and Atmospheric Science</i>, 7(1): 249. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s41612-024-00788-x\"\n     onclick=\"log_download('jensen-gerdener-eicker-kusche-fiedler-observationsindicateregionallymisleadingwettinganddryingtrendsincmip6-2024', 'https://www.nature.com/articles/s41612-024-00788-x', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Observations indicate regionally misleading wetting and drying trends in CMIP6 [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s41612-024-00788-x\"\n     onclick=\"log_download('jensen-gerdener-eicker-kusche-fiedler-observationsindicateregionallymisleadingwettinganddryingtrendsincmip6-2024', 'http://doi.org/10.1038/s41612-024-00788-x', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jensen-gerdener-eicker-kusche-fiedler-observationsindicateregionallymisleadingwettinganddryingtrendsincmip6-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jensen-gerdener-eicker-kusche-fiedler-observationsindicateregionallymisleadingwettinganddryingtrendsincmip6-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{jensen_observations_2024,\n\ttitle = {Observations indicate regionally misleading wetting and drying trends in {CMIP6}},\n\tvolume = {7},\n\tissn = {2397-3722},\n\turl = {https://www.nature.com/articles/s41612-024-00788-x},\n\tdoi = {10.1038/s41612-024-00788-x},\n\tabstract = {Abstract\n            We evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against a new global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. To account for different timescales in our analysis, we select regions in which the influence of interannual variability is relatively small and observed trends are assumed to be representative of the development over longer periods. Our results reveal distinct biases in drying and wetting trends in CMIP6 models for several world regions. Specifically, we see high model consensus for drying in the Amazon, which disagrees with the observed wetting. Other regions show a high consensus of models and observations suggesting qualitatively correctly simulated trends, e.g., for the Mediterranean and parts of Central Africa. A high model agreement might therefore falsely indicate a robust trend in water storage if it is not assessed in light of the observed developments. This underlines the potential use of maintaining an adequate observational capacity of water storage for climate change assessments.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-10-23},\n\tjournal = {npj Climate and Atmospheric Science},\n\tauthor = {Jensen, Laura and Gerdener, Helena and Eicker, Annette and Kusche, Jürgen and Fiedler, Stephanie},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {249},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract We evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against a new global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. To account for different timescales in our analysis, we select regions in which the influence of interannual variability is relatively small and observed trends are assumed to be representative of the development over longer periods. Our results reveal distinct biases in drying and wetting trends in CMIP6 models for several world regions. Specifically, we see high model consensus for drying in the Amazon, which disagrees with the observed wetting. Other regions show a high consensus of models and observations suggesting qualitatively correctly simulated trends, e.g., for the Mediterranean and parts of Central Africa. A high model agreement might therefore falsely indicate a robust trend in water storage if it is not assessed in light of the observed developments. This underlines the potential use of maintaining an adequate observational capacity of water storage for climate change assessments.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"burchfield-ferro-httel-lakes-leonhardt-niedermayr-rissing-seifert-etal-towardsacomprehensiveanalysisofagriculturallandsystemsintheeuandusacriticalviewonpubliclyavailabledatasets-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'burchfield-ferro-httel-lakes-leonhardt-niedermayr-rissing-seifert-etal-towardsacomprehensiveanalysisofagriculturallandsystemsintheeuandusacriticalviewonpubliclyavailabledatasets-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247', event);\">\n    Towards a comprehensive analysis of agricultural land systems in the EU and US: A critical view on publicly available datasets.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Burchfield, E.; Ferro, M.; Hüttel, S.; Lakes, T.; Leonhardt, H.; Niedermayr, A.; Rissing, A.; Seifert, S.;  and Wesemeyer, M.\n</span>\n\n  \n\n</span>\n\n  <i>Land Use Policy</i>, 147: 107371. December 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247\"\n     onclick=\"log_download('burchfield-ferro-httel-lakes-leonhardt-niedermayr-rissing-seifert-etal-towardsacomprehensiveanalysisofagriculturallandsystemsintheeuandusacriticalviewonpubliclyavailabledatasets-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Towards a comprehensive analysis of agricultural land systems in the EU and US: A critical view on publicly available datasets [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.landusepol.2024.107371\"\n     onclick=\"log_download('burchfield-ferro-httel-lakes-leonhardt-niedermayr-rissing-seifert-etal-towardsacomprehensiveanalysisofagriculturallandsystemsintheeuandusacriticalviewonpubliclyavailabledatasets-2024', 'http://doi.org/10.1016/j.landusepol.2024.107371', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/burchfield-ferro-httel-lakes-leonhardt-niedermayr-rissing-seifert-etal-towardsacomprehensiveanalysisofagriculturallandsystemsintheeuandusacriticalviewonpubliclyavailabledatasets-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('burchfield-ferro-httel-lakes-leonhardt-niedermayr-rissing-seifert-etal-towardsacomprehensiveanalysisofagriculturallandsystemsintheeuandusacriticalviewonpubliclyavailabledatasets-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{burchfield_towards_2024,\n\ttitle = {Towards a comprehensive analysis of agricultural land systems in the {EU} and {US}: {A} critical view on publicly available datasets},\n\tvolume = {147},\n\tissn = {02648377},\n\tshorttitle = {Towards a comprehensive analysis of agricultural land systems in the {EU} and {US}},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0264837724003247},\n\tdoi = {10.1016/j.landusepol.2024.107371},\n\tlanguage = {en},\n\turldate = {2024-10-23},\n\tjournal = {Land Use Policy},\n\tauthor = {Burchfield, Emily and Ferro, Marco and Hüttel, Silke and Lakes, Tobia and Leonhardt, Heidi and Niedermayr, Andreas and Rissing, Andrea and Seifert, Stefan and Wesemeyer, Maximilian},\n\tmonth = dec,\n\tyear = {2024},\n\tpages = {107371},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"leonhardt-wesemeyer-eder-httel-lakes-schaak-seifert-wolff-usecasesandscientificpotentialoflandusedatafromtheeusintegratedadministrationandcontrolsystemasystematicmappingreview-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'leonhardt-wesemeyer-eder-httel-lakes-schaak-seifert-wolff-usecasesandscientificpotentialoflandusedatafromtheeusintegratedadministrationandcontrolsystemasystematicmappingreview-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X', event);\">\n    Use cases and scientific potential of land use data from the EU’s Integrated Administration and Control System: A systematic mapping review.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Leonhardt, H.; Wesemeyer, M.; Eder, A.; Hüttel, S.; Lakes, T.; Schaak, H.; Seifert, S.;  and Wolff, S.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Indicators</i>, 167: 112709. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X\"\n     onclick=\"log_download('leonhardt-wesemeyer-eder-httel-lakes-schaak-seifert-wolff-usecasesandscientificpotentialoflandusedatafromtheeusintegratedadministrationandcontrolsystemasystematicmappingreview-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Use cases and scientific potential of land use data from the EU’s Integrated Administration and Control System: A systematic mapping review [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolind.2024.112709\"\n     onclick=\"log_download('leonhardt-wesemeyer-eder-httel-lakes-schaak-seifert-wolff-usecasesandscientificpotentialoflandusedatafromtheeusintegratedadministrationandcontrolsystemasystematicmappingreview-2024', 'http://doi.org/10.1016/j.ecolind.2024.112709', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/leonhardt-wesemeyer-eder-httel-lakes-schaak-seifert-wolff-usecasesandscientificpotentialoflandusedatafromtheeusintegratedadministrationandcontrolsystemasystematicmappingreview-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('leonhardt-wesemeyer-eder-httel-lakes-schaak-seifert-wolff-usecasesandscientificpotentialoflandusedatafromtheeusintegratedadministrationandcontrolsystemasystematicmappingreview-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{leonhardt_use_2024,\n\ttitle = {Use cases and scientific potential of land use data from the {EU}’s {Integrated} {Administration} and {Control} {System}: {A} systematic mapping review},\n\tvolume = {167},\n\tissn = {1470160X},\n\tshorttitle = {Use cases and scientific potential of land use data from the {EU}’s {Integrated} {Administration} and {Control} {System}},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X2401166X},\n\tdoi = {10.1016/j.ecolind.2024.112709},\n\tlanguage = {en},\n\turldate = {2024-10-23},\n\tjournal = {Ecological Indicators},\n\tauthor = {Leonhardt, Heidi and Wesemeyer, Maximilian and Eder, Andreas and Hüttel, Silke and Lakes, Tobia and Schaak, Henning and Seifert, Stefan and Wolff, Saskia},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {112709},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"akter-huisman-bogena-estimatingsoilmoisturefromenvironmentalgammaradiationmonitoringdata-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'akter-huisman-bogena-estimatingsoilmoisturefromenvironmentalgammaradiationmonitoringdata-2024', 'https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384', event);\">\n    Estimating soil moisture from environmental gamma radiation monitoring data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Akter, S.; Huisman, J. A.;  and Bogena, H. R.\n</span>\n\n  \n\n</span>\n\n  <i>Vadose Zone Journal</i>,e20384. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384\"\n     onclick=\"log_download('akter-huisman-bogena-estimatingsoilmoisturefromenvironmentalgammaradiationmonitoringdata-2024', 'https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Estimating soil moisture from environmental gamma radiation monitoring data [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/vzj2.20384\"\n     onclick=\"log_download('akter-huisman-bogena-estimatingsoilmoisturefromenvironmentalgammaradiationmonitoringdata-2024', 'http://doi.org/10.1002/vzj2.20384', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/akter-huisman-bogena-estimatingsoilmoisturefromenvironmentalgammaradiationmonitoringdata-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('akter-huisman-bogena-estimatingsoilmoisturefromenvironmentalgammaradiationmonitoringdata-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{akter_estimating_2024,\n\ttitle = {Estimating soil moisture from environmental gamma radiation monitoring data},\n\tissn = {1539-1663, 1539-1663},\n\turl = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20384},\n\tdoi = {10.1002/vzj2.20384},\n\tabstract = {Abstract\n            Soil moisture (SM) information is invaluable for a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents root‐zone SM for longer periods and larger spatial scales. One option for root‐zone SM observation is terrestrial gamma radiation (TGR), as it is inversely related to SM. Hence, the near real‐time data of more than 5000 environmental gamma radiation (EGR) monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) is a potential source to develop a root‐zone SM product for Europe without extra investments in SM sensors. This study aims to investigate to what extent the EURDEP data can be used for SM estimation. For this, two EGR monitoring stations were equipped with in situ SM sensors to measure reference SM. The terrestrial component of EGR was extracted after eliminating the contributions of rain washout and secondary cosmic radiation, and used to obtain a functional relationship with SM. We predicted the weekly volumetric SM with a root mean square error of 7\\%–9\\% from TGR measurements. Nevertheless, we believe that this technique, due to its greater penetration depth and long data legacy, can provide useful data complementary to satellite‐based remote sensing techniques to estimate root‐zone SM at the continental scale.\n          , \n            Core Ideas\n            \n              \n                \n                  An extensive early warning monitoring network for environmental gamma radiation (EGR) is maintained in Europe.\n                \n                \n                  Since soil moisture influences EGR, this database could be used to derive continental soil moisture products.\n                \n                \n                  To test this, two monitoring stations in Germany were selected and equipped with reference soil moisture sensors.\n                \n                \n                  From the terrestrial component of EGR, soil moisture was determined with an error of 7–9 vol.\\%.\n                \n              \n            \n          , \n            Plain Language Summary\n            \n              Information on the temporal dynamics of SM across a large area is vital for many sectors. An extensive network for monitoring EGR detectors that has been operated across Europe after the Chernobyl nuclear accident is a potential source for deriving continental‐scale SM information without additional costs. We investigated how accurately SM can be estimated from the data of two of such detectors. The results showed that weekly SM estimates with an accuracy of 0.07–0.09 cm\n              3\n              cm\n              −3\n              are feasible after adequate data processing accounting for other factors affecting EGR. We also discussed possible sources that affected the accuracy of the SM estimates and provided directions for further research. Despite the current limitations, EGR data show potential for estimating SM across Europe.},\n\tlanguage = {en},\n\turldate = {2024-10-23},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Akter, Sonia and Huisman, Johan Alexander and Bogena, Heye Reemt},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {e20384},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Soil moisture (SM) information is invaluable for a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents root‐zone SM for longer periods and larger spatial scales. One option for root‐zone SM observation is terrestrial gamma radiation (TGR), as it is inversely related to SM. Hence, the near real‐time data of more than 5000 environmental gamma radiation (EGR) monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) is a potential source to develop a root‐zone SM product for Europe without extra investments in SM sensors. This study aims to investigate to what extent the EURDEP data can be used for SM estimation. For this, two EGR monitoring stations were equipped with in situ SM sensors to measure reference SM. The terrestrial component of EGR was extracted after eliminating the contributions of rain washout and secondary cosmic radiation, and used to obtain a functional relationship with SM. We predicted the weekly volumetric SM with a root mean square error of 7%–9% from TGR measurements. Nevertheless, we believe that this technique, due to its greater penetration depth and long data legacy, can provide useful data complementary to satellite‐based remote sensing techniques to estimate root‐zone SM at the continental scale. , Core Ideas An extensive early warning monitoring network for environmental gamma radiation (EGR) is maintained in Europe. Since soil moisture influences EGR, this database could be used to derive continental soil moisture products. To test this, two monitoring stations in Germany were selected and equipped with reference soil moisture sensors. From the terrestrial component of EGR, soil moisture was determined with an error of 7–9 vol.%. , Plain Language Summary Information on the temporal dynamics of SM across a large area is vital for many sectors. An extensive network for monitoring EGR detectors that has been operated across Europe after the Chernobyl nuclear accident is a potential source for deriving continental‐scale SM information without additional costs. We investigated how accurately SM can be estimated from the data of two of such detectors. The results showed that weekly SM estimates with an accuracy of 0.07–0.09 cm 3 cm −3 are feasible after adequate data processing accounting for other factors affecting EGR. We also discussed possible sources that affected the accuracy of the SM estimates and provided directions for further research. Despite the current limitations, EGR data show potential for estimating SM across Europe.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-kusche-sneeuw-siebert-gerdener-wang-chao-chen-etal-forecastingnextyearsgloballandwaterstorageusinggracedata-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'li-kusche-sneeuw-siebert-gerdener-wang-chao-chen-etal-forecastingnextyearsgloballandwaterstorageusinggracedata-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101', event);\">\n    Forecasting Next Year's Global Land Water Storage Using GRACE Data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li, F.; Kusche, J.; Sneeuw, N.; Siebert, S.; Gerdener, H.; Wang, Z.; Chao, N.; Chen, G.;  and Tian, K.\n</span>\n\n  \n\n</span>\n\n  <i>Geophysical Research Letters</i>, 51(17): e2024GL109101. September 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101\"\n     onclick=\"log_download('li-kusche-sneeuw-siebert-gerdener-wang-chao-chen-etal-forecastingnextyearsgloballandwaterstorageusinggracedata-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Forecasting Next Year&#x27;s Global Land Water Storage Using GRACE Data [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2024GL109101\"\n     onclick=\"log_download('li-kusche-sneeuw-siebert-gerdener-wang-chao-chen-etal-forecastingnextyearsgloballandwaterstorageusinggracedata-2024', 'http://doi.org/10.1029/2024GL109101', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-kusche-sneeuw-siebert-gerdener-wang-chao-chen-etal-forecastingnextyearsgloballandwaterstorageusinggracedata-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-kusche-sneeuw-siebert-gerdener-wang-chao-chen-etal-forecastingnextyearsgloballandwaterstorageusinggracedata-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{li_forecasting_2024,\n\ttitle = {Forecasting {Next} {Year}&#x27;s {Global} {Land} {Water} {Storage} {Using} {GRACE} {Data}},\n\tvolume = {51},\n\tissn = {0094-8276, 1944-8007},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024GL109101},\n\tdoi = {10.1029/2024GL109101},\n\tabstract = {Abstract\n            Existing approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management.\n          , \n            Plain Language Summary\n            Traditional methods for predicting short‐term/seasonal variations in land total water storages rely on hydrological models. However, these models have a drawback—they are better at predicting water stored in specific parts of the land system like soil moisture than giving an accurate forecast for the overall integrated land total water storage. In this study, we demonstrate the applicability of machine learning in uncovering relationships between the de‐season and de‐linearized terms of global water storage variability as observed by the Gravity Recovery and Climate Experiment (GRACE) satellites, and the preceding hydrometeorological variables such as sea surface temperature. These relationships can then be utilized to forecast monthly changes in land total water storage up to 1 year ahead, and even to predict exceptional drought events based on near real‐time observational forcing data. The validation by actual GRACE observations, lends further credence to the effectiveness of the method developed here, showcasing its potential to forecast trends in global land total water storage for the upcoming year. The potential applications of these predictions in early warning systems are highly promising, and we anticipate that they can assist decision‐makers in enhancing current drought and water resource management practices.\n          , \n            Key Points\n            \n              \n                \n                  We identify a stable lag relationship between hydrometeorological variables and the GRACE derived total water storage change (TWSC)\n                \n                \n                  Using this stable lag relationship, we are able to forecast the global TWSC up to 1 year ahead with solely observational data as inputs\n                \n                \n                  Our forecasts exhibit high consistency with actual GRACE data in terms of global mean land water storage trends for the following year},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2024-10-01},\n\tjournal = {Geophysical Research Letters},\n\tauthor = {Li, Fupeng and Kusche, Jürgen and Sneeuw, Nico and Siebert, Stefan and Gerdener, Helena and Wang, Zhengtao and Chao, Nengfang and Chen, Gang and Tian, Kunjun},\n\tmonth = sep,\n\tyear = {2024},\n\tpages = {e2024GL109101},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Existing approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management. , Plain Language Summary Traditional methods for predicting short‐term/seasonal variations in land total water storages rely on hydrological models. However, these models have a drawback—they are better at predicting water stored in specific parts of the land system like soil moisture than giving an accurate forecast for the overall integrated land total water storage. In this study, we demonstrate the applicability of machine learning in uncovering relationships between the de‐season and de‐linearized terms of global water storage variability as observed by the Gravity Recovery and Climate Experiment (GRACE) satellites, and the preceding hydrometeorological variables such as sea surface temperature. These relationships can then be utilized to forecast monthly changes in land total water storage up to 1 year ahead, and even to predict exceptional drought events based on near real‐time observational forcing data. The validation by actual GRACE observations, lends further credence to the effectiveness of the method developed here, showcasing its potential to forecast trends in global land total water storage for the upcoming year. The potential applications of these predictions in early warning systems are highly promising, and we anticipate that they can assist decision‐makers in enhancing current drought and water resource management practices. , Key Points We identify a stable lag relationship between hydrometeorological variables and the GRACE derived total water storage change (TWSC) Using this stable lag relationship, we are able to forecast the global TWSC up to 1 year ahead with solely observational data as inputs Our forecasts exhibit high consistency with actual GRACE data in terms of global mean land water storage trends for the following year\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"httel-hess-arelessonsbeinglearntfromthereplicationcrisisorwilltherevolutiondevouritschildrenopenqsciencefromtheeditorsperspective-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'httel-hess-arelessonsbeinglearntfromthereplicationcrisisorwilltherevolutiondevouritschildrenopenqsciencefromtheeditorsperspective-2024', 'https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351', event);\">\n    Are lessons being learnt from the replication crisis or will the revolution devour its children? Open Q science from the editor's perspective.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hüttel, S.;  and Hess, S.\n</span>\n\n  \n\n</span>\n\n  <i>Q Open</i>,qoae019. July 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351\"\n     onclick=\"log_download('httel-hess-arelessonsbeinglearntfromthereplicationcrisisorwilltherevolutiondevouritschildrenopenqsciencefromtheeditorsperspective-2024', 'https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Are lessons being learnt from the replication crisis or will the revolution devour its children? Open Q science from the editor&#x27;s perspective [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1093/qopen/qoae019\"\n     onclick=\"log_download('httel-hess-arelessonsbeinglearntfromthereplicationcrisisorwilltherevolutiondevouritschildrenopenqsciencefromtheeditorsperspective-2024', 'http://doi.org/10.1093/qopen/qoae019', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/httel-hess-arelessonsbeinglearntfromthereplicationcrisisorwilltherevolutiondevouritschildrenopenqsciencefromtheeditorsperspective-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('httel-hess-arelessonsbeinglearntfromthereplicationcrisisorwilltherevolutiondevouritschildrenopenqsciencefromtheeditorsperspective-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{huttel_are_2024,\n\ttitle = {Are lessons being learnt from the replication crisis or will the revolution devour its children? {Open} {Q} science from the editor&#x27;s perspective},\n\tcopyright = {https://creativecommons.org/licenses/by-nc/4.0/},\n\tissn = {2633-9048},\n\tshorttitle = {Are lessons being learnt from the replication crisis or will the revolution devour its children?},\n\turl = {https://academic.oup.com/qopen/advance-article/doi/10.1093/qopen/qoae019/7708351},\n\tdoi = {10.1093/qopen/qoae019},\n\tabstract = {Abstract\n            The scientific production system is crucial in how global challenges are addressed. However, scholars have recently begun to voice concerns about structural inefficiencies within the system, as highlighted, for example, by the replication crisis, the p-value debate and various forms of publication bias. Most suggested remedies tend to address only partial aspects of the system&#x27;s inefficiencies, but there is currently no unifying agenda in favour of an overall transformation of the system. Based on a critical review of the current scientific system and an exploratory pilot study about the state of student training, we argue that a unifying agenda is urgently needed, particularly given the emergence of artificial intelligence (AI) as a tool in scientific writing and the research discovery process. Without appropriate responses from academia, this trend may even compound current issues around credibility due to limited replicability and ritual-based statistical practice while amplifying all forms of existing biases. Naïve openness in the science system alone is unlikely to lead to major improvements. We contribute to the debate and call for a system reform by identifying key elements in the definition of transformation pathways towards open, democratic and conscious learning, teaching, reviewing and publishing supported by openly maintained AI tools. Roles and incentives within the review process will have to adapt and be strengthened in relation to those that apply to authors. Scientists will have to write less, learn differently and review more in the future, but need to be trained better in and for AI even today.},\n\tlanguage = {en},\n\turldate = {2024-10-01},\n\tjournal = {Q Open},\n\tauthor = {Hüttel, Silke and Hess, Sebastian},\n\tmonth = jul,\n\tyear = {2024},\n\tpages = {qoae019},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract The scientific production system is crucial in how global challenges are addressed. However, scholars have recently begun to voice concerns about structural inefficiencies within the system, as highlighted, for example, by the replication crisis, the p-value debate and various forms of publication bias. Most suggested remedies tend to address only partial aspects of the system's inefficiencies, but there is currently no unifying agenda in favour of an overall transformation of the system. Based on a critical review of the current scientific system and an exploratory pilot study about the state of student training, we argue that a unifying agenda is urgently needed, particularly given the emergence of artificial intelligence (AI) as a tool in scientific writing and the research discovery process. Without appropriate responses from academia, this trend may even compound current issues around credibility due to limited replicability and ritual-based statistical practice while amplifying all forms of existing biases. Naïve openness in the science system alone is unlikely to lead to major improvements. We contribute to the debate and call for a system reform by identifying key elements in the definition of transformation pathways towards open, democratic and conscious learning, teaching, reviewing and publishing supported by openly maintained AI tools. Roles and incentives within the review process will have to adapt and be strengthened in relation to those that apply to authors. Scientists will have to write less, learn differently and review more in the future, but need to be trained better in and for AI even today.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"uehleke-vonplettenberg-leyer-httel-germansugarbeetfarmersintentiontouseautonomousfieldrobotsforseedingandweeding-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'uehleke-vonplettenberg-leyer-httel-germansugarbeetfarmersintentiontouseautonomousfieldrobotsforseedingandweeding-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587', event);\">\n    German sugar beet farmers’ intention to use autonomous field robots for seeding and weeding.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Uehleke, R.; Von Plettenberg, L.; Leyer, M.;  and Hüttel, S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Environmental Management</i>, 370: 122472. November 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587\"\n     onclick=\"log_download('uehleke-vonplettenberg-leyer-httel-germansugarbeetfarmersintentiontouseautonomousfieldrobotsforseedingandweeding-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"German sugar beet farmers’ intention to use autonomous field robots for seeding and weeding [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2024.122472\"\n     onclick=\"log_download('uehleke-vonplettenberg-leyer-httel-germansugarbeetfarmersintentiontouseautonomousfieldrobotsforseedingandweeding-2024', 'http://doi.org/10.1016/j.jenvman.2024.122472', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/uehleke-vonplettenberg-leyer-httel-germansugarbeetfarmersintentiontouseautonomousfieldrobotsforseedingandweeding-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('uehleke-vonplettenberg-leyer-httel-germansugarbeetfarmersintentiontouseautonomousfieldrobotsforseedingandweeding-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{uehleke_german_2024,\n\ttitle = {German sugar beet farmers’ intention to use autonomous field robots for seeding and weeding},\n\tvolume = {370},\n\tissn = {03014797},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0301479724024587},\n\tdoi = {10.1016/j.jenvman.2024.122472},\n\tlanguage = {en},\n\turldate = {2024-10-01},\n\tjournal = {Journal of Environmental Management},\n\tauthor = {Uehleke, Reinhard and Von Plettenberg, Lousia and Leyer, Michael and Hüttel, Silke},\n\tmonth = nov,\n\tyear = {2024},\n\tpages = {122472},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"seifert-wolff-httel-ecoefficiencyintheagriculturallandscapeofnorthrhinewestphaliagermany-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'seifert-wolff-httel-ecoefficiencyintheagriculturallandscapeofnorthrhinewestphaliagermany-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129', event);\">\n    Eco-efficiency in the agricultural landscape of North Rhine-Westphalia, Germany.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Seifert, S.; Wolff, S.;  and Hüttel, S.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Systems</i>, 220: 104062. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129\"\n     onclick=\"log_download('seifert-wolff-httel-ecoefficiencyintheagriculturallandscapeofnorthrhinewestphaliagermany-2024', 'https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Eco-efficiency in the agricultural landscape of North Rhine-Westphalia, Germany [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agsy.2024.104062\"\n     onclick=\"log_download('seifert-wolff-httel-ecoefficiencyintheagriculturallandscapeofnorthrhinewestphaliagermany-2024', 'http://doi.org/10.1016/j.agsy.2024.104062', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/seifert-wolff-httel-ecoefficiencyintheagriculturallandscapeofnorthrhinewestphaliagermany-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('seifert-wolff-httel-ecoefficiencyintheagriculturallandscapeofnorthrhinewestphaliagermany-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{seifert_eco-efficiency_2024,\n\ttitle = {Eco-efficiency in the agricultural landscape of {North} {Rhine}-{Westphalia}, {Germany}},\n\tvolume = {220},\n\tissn = {0308521X},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0308521X24002129},\n\tdoi = {10.1016/j.agsy.2024.104062},\n\tlanguage = {en},\n\turldate = {2024-10-01},\n\tjournal = {Agricultural Systems},\n\tauthor = {Seifert, Stefan and Wolff, Saskia and Hüttel, Silke},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {104062},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"eugeniorussmann-menndez-giles-carril-sensitivityofariditydiagnosestolandatmospherecouplinginsouthamerica-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/10.1007/s00382-024-07413-w\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'eugeniorussmann-menndez-giles-carril-sensitivityofariditydiagnosestolandatmospherecouplinginsouthamerica-2024', 'https://link.springer.com/10.1007/s00382-024-07413-w', event);\">\n    Sensitivity of aridity diagnoses to land-atmosphere coupling in South America.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Eugenio Russmann, J.; Menéndez, C. G.; Giles, J. A.;  and Carril, A. F.\n</span>\n\n  \n\n</span>\n\n  <i>Climate Dynamics</i>. September 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/10.1007/s00382-024-07413-w\"\n     onclick=\"log_download('eugeniorussmann-menndez-giles-carril-sensitivityofariditydiagnosestolandatmospherecouplinginsouthamerica-2024', 'https://link.springer.com/10.1007/s00382-024-07413-w', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Sensitivity of aridity diagnoses to land-atmosphere coupling in South America [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00382-024-07413-w\"\n     onclick=\"log_download('eugeniorussmann-menndez-giles-carril-sensitivityofariditydiagnosestolandatmospherecouplinginsouthamerica-2024', 'http://doi.org/10.1007/s00382-024-07413-w', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/eugeniorussmann-menndez-giles-carril-sensitivityofariditydiagnosestolandatmospherecouplinginsouthamerica-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('eugeniorussmann-menndez-giles-carril-sensitivityofariditydiagnosestolandatmospherecouplinginsouthamerica-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{eugenio_russmann_sensitivity_2024,\n\ttitle = {Sensitivity of aridity diagnoses to land-atmosphere coupling in {South} {America}},\n\tissn = {0930-7575, 1432-0894},\n\turl = {https://link.springer.com/10.1007/s00382-024-07413-w},\n\tdoi = {10.1007/s00382-024-07413-w},\n\tlanguage = {en},\n\turldate = {2024-09-27},\n\tjournal = {Climate Dynamics},\n\tauthor = {Eugenio Russmann, Juan and Menéndez, Claudio G. and Giles, Julian A. and Carril, Andrea F.},\n\tmonth = sep,\n\tyear = {2024},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s41597-024-03535-2\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024', 'https://www.nature.com/articles/s41597-024-03535-2', event);\">\n    Multi-year aboveground data of minirhizotron facilities in Selhausen.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nguyen, T. H.; Lopez, G.; Seidel, S. J.; Lärm, L.; Bauer, F. M.; Klotzsche, A.; Schnepf, A.; Gaiser, T.; Hüging, H.;  and Ewert, F.\n</span>\n\n  \n\n</span>\n\n  <i>Scientific Data</i>, 11(1): 674. June 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s41597-024-03535-2\"\n     onclick=\"log_download('nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024', 'https://www.nature.com/articles/s41597-024-03535-2', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Multi-year aboveground data of minirhizotron facilities in Selhausen [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s41597-024-03535-2\"\n     onclick=\"log_download('nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024', 'http://doi.org/10.1038/s41597-024-03535-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nguyen-lopez-seidel-lrm-bauer-klotzsche-schnepf-gaiser-etal-multiyearabovegrounddataofminirhizotronfacilitiesinselhausen-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{nguyen_multi-year_2024,\n\ttitle = {Multi-year aboveground data of minirhizotron facilities in {Selhausen}},\n\tvolume = {11},\n\tissn = {2052-4463},\n\turl = {https://www.nature.com/articles/s41597-024-03535-2},\n\tdoi = {10.1038/s41597-024-03535-2},\n\tabstract = {Abstract\n            \n              Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO\n              2\n              and H\n              2\n              O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO\n              2\n              exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-08-20},\n\tjournal = {Scientific Data},\n\tauthor = {Nguyen, Thuy Huu and Lopez, Gina and Seidel, Sabine J. and Lärm, Lena and Bauer, Felix Maximilian and Klotzsche, Anja and Schnepf, Andrea and Gaiser, Thomas and Hüging, Hubert and Ewert, Frank},\n\tmonth = jun,\n\tyear = {2024},\n\tpages = {674},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Improved understanding of crops’ response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO 2 and H 2 O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO 2 exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"larson-gnssreflanopensourcesoftwarepackageinpythonforgnssinterferometricreflectometryapplications-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/10.1007/s10291-024-01694-8\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'larson-gnssreflanopensourcesoftwarepackageinpythonforgnssinterferometricreflectometryapplications-2024', 'https://link.springer.com/10.1007/s10291-024-01694-8', event);\">\n    Gnssrefl: an open source software package in python for GNSS interferometric reflectometry applications.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Larson, K. M.\n</span>\n\n  \n\n</span>\n\n  <i>GPS Solutions</i>, 28(4): 165. October 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/10.1007/s10291-024-01694-8\"\n     onclick=\"log_download('larson-gnssreflanopensourcesoftwarepackageinpythonforgnssinterferometricreflectometryapplications-2024', 'https://link.springer.com/10.1007/s10291-024-01694-8', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Gnssrefl: an open source software package in python for GNSS interferometric reflectometry applications [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10291-024-01694-8\"\n     onclick=\"log_download('larson-gnssreflanopensourcesoftwarepackageinpythonforgnssinterferometricreflectometryapplications-2024', 'http://doi.org/10.1007/s10291-024-01694-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/larson-gnssreflanopensourcesoftwarepackageinpythonforgnssinterferometricreflectometryapplications-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('larson-gnssreflanopensourcesoftwarepackageinpythonforgnssinterferometricreflectometryapplications-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{larson_gnssrefl_2024,\n\ttitle = {Gnssrefl: an open source software package in python for {GNSS} interferometric reflectometry applications},\n\tvolume = {28},\n\tissn = {1080-5370, 1521-1886},\n\tshorttitle = {Gnssrefl},\n\turl = {https://link.springer.com/10.1007/s10291-024-01694-8},\n\tdoi = {10.1007/s10291-024-01694-8},\n\tabstract = {Abstract\n            An open source software package has been developed for Global Navigation Satellite Systems (GNSS) interferometric reflectometry. The gnssrefl package is written in python; it can be installed from the source code, the python packaging index website, or via a docker. It includes modules that download GNSS data and orbit data from global archives. A periodogram is used to retrieve the height of the GNSS antenna over the reflecting surface using signal to noise ratio data. Signals from the Global Positioning System, Glonass, Galileo, and Beidou constellations are supported. Modules are provided to estimate volumetric water content of soil, snow depth/accumulation, and water level. Utilities for mapping and assessing reflection zones and determining the maximum resolvable height are available.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-08-20},\n\tjournal = {GPS Solutions},\n\tauthor = {Larson, Kristine M.},\n\tmonth = oct,\n\tyear = {2024},\n\tpages = {165},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract An open source software package has been developed for Global Navigation Satellite Systems (GNSS) interferometric reflectometry. The gnssrefl package is written in python; it can be installed from the source code, the python packaging index website, or via a docker. It includes modules that download GNSS data and orbit data from global archives. A periodogram is used to retrieve the height of the GNSS antenna over the reflecting surface using signal to noise ratio data. Signals from the Global Positioning System, Glonass, Galileo, and Beidou constellations are supported. Modules are provided to estimate volumetric water content of soil, snow depth/accumulation, and water level. Utilities for mapping and assessing reflection zones and determining the maximum resolvable height are available.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"springer-mielke-liu-dixit-friederichs-kusche-aregionallyrefinedandmassconsistentatmosphericandhydrologicaldealiasingproductforgracegracefoandfuturegravitymissions-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'springer-mielke-liu-dixit-friederichs-kusche-aregionallyrefinedandmassconsistentatmosphericandhydrologicaldealiasingproductforgracegracefoandfuturegravitymissions-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883', event);\">\n    A Regionally Refined and Mass‐Consistent Atmospheric and Hydrological De‐Aliasing Product for GRACE, GRACE‐FO and Future Gravity Missions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Springer, A.; Mielke, C. A.; Liu, Z.; Dixit, S.; Friederichs, P.;  and Kusche, J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Geophysical Research: Solid Earth</i>, 129(5): e2023JB027883. May 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883\"\n     onclick=\"log_download('springer-mielke-liu-dixit-friederichs-kusche-aregionallyrefinedandmassconsistentatmosphericandhydrologicaldealiasingproductforgracegracefoandfuturegravitymissions-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Regionally Refined and Mass‐Consistent Atmospheric and Hydrological De‐Aliasing Product for GRACE, GRACE‐FO and Future Gravity Missions [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2023JB027883\"\n     onclick=\"log_download('springer-mielke-liu-dixit-friederichs-kusche-aregionallyrefinedandmassconsistentatmosphericandhydrologicaldealiasingproductforgracegracefoandfuturegravitymissions-2024', 'http://doi.org/10.1029/2023JB027883', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/springer-mielke-liu-dixit-friederichs-kusche-aregionallyrefinedandmassconsistentatmosphericandhydrologicaldealiasingproductforgracegracefoandfuturegravitymissions-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('springer-mielke-liu-dixit-friederichs-kusche-aregionallyrefinedandmassconsistentatmosphericandhydrologicaldealiasingproductforgracegracefoandfuturegravitymissions-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{springer_regionally_2024,\n\ttitle = {A {Regionally} {Refined} and {Mass}‐{Consistent} {Atmospheric} and {Hydrological} {De}‐{Aliasing} {Product} for {GRACE}, {GRACE}‐{FO} and {Future} {Gravity} {Missions}},\n\tvolume = {129},\n\tissn = {2169-9313, 2169-9356},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB027883},\n\tdoi = {10.1029/2023JB027883},\n\tabstract = {Abstract\n            De‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de‐aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de‐aliasing products by nesting a regional high‐resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de‐aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3‐hourly data, our investigations suggest that contributions from continental hydrology and from regional non‐hydrostatic atmospheric modeling to sub‐monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions.\n          , \n            Plain Language Summary\n            Observing temporal variations in the Earth&#x27;s gravity field with satellite gravimetry plays an essential role for monitoring mass transports on and underneath the Earth&#x27;s surface. This is crucial for understanding the evolution of floods and droughts, the role of groundwater pumping, and to quantify the melting of ice sheets and glaciers and the resulting sea level rise. In order to isolate the target variable (e.g., terrestrial water storage changes) unwanted signals (e.g., fast mass variations in the atmosphere) need to be removed in the gravity field estimation process using background models, so‐called de‐aliasing models. This paper focuses on improving background models by incorporating regional high‐resolution models, which more specifically resolve certain processes in the atmosphere. Our hypothesis is that this will lead to better gravity fields with increased spatial resolution and less noise. Moreover, we find that considering fast hydrological variations as additional background model could improve gravity fields from the current satellite mission GRACE‐FO. For the first time, we quantify contributions from so far neglected atmospheric moisture fields, such as cloud liquid water, to enhance background models in the context of extreme events—which, however, will likely be in particular relevant for more sensitive gravity missions in the future.\n          , \n            Key Points\n            \n              \n                \n                  We provide an atmosphere‐hydrology de‐aliasing product with regional mass‐consistent refinement over Europe\n                \n                \n                  Using non‐hydrostatic as opposed to hydrostatic numerical weather prediction model output significantly impacts the de‐aliasing product\n                \n                \n                  We found that for extreme events additional moisture fields unaccounted in present Atmosphere and Ocean De‐aliasing (AOD) models can reach magnitudes relevant for de‐aliasing},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2024-07-23},\n\tjournal = {Journal of Geophysical Research: Solid Earth},\n\tauthor = {Springer, Anne and Mielke, Christian A. and Liu, Ziyu and Dixit, Shashi and Friederichs, Petra and Kusche, Jürgen},\n\tmonth = may,\n\tyear = {2024},\n\tpages = {e2023JB027883},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract De‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de‐aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de‐aliasing products by nesting a regional high‐resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de‐aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3‐hourly data, our investigations suggest that contributions from continental hydrology and from regional non‐hydrostatic atmospheric modeling to sub‐monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions. , Plain Language Summary Observing temporal variations in the Earth's gravity field with satellite gravimetry plays an essential role for monitoring mass transports on and underneath the Earth's surface. This is crucial for understanding the evolution of floods and droughts, the role of groundwater pumping, and to quantify the melting of ice sheets and glaciers and the resulting sea level rise. In order to isolate the target variable (e.g., terrestrial water storage changes) unwanted signals (e.g., fast mass variations in the atmosphere) need to be removed in the gravity field estimation process using background models, so‐called de‐aliasing models. This paper focuses on improving background models by incorporating regional high‐resolution models, which more specifically resolve certain processes in the atmosphere. Our hypothesis is that this will lead to better gravity fields with increased spatial resolution and less noise. Moreover, we find that considering fast hydrological variations as additional background model could improve gravity fields from the current satellite mission GRACE‐FO. For the first time, we quantify contributions from so far neglected atmospheric moisture fields, such as cloud liquid water, to enhance background models in the context of extreme events—which, however, will likely be in particular relevant for more sensitive gravity missions in the future. , Key Points We provide an atmosphere‐hydrology de‐aliasing product with regional mass‐consistent refinement over Europe Using non‐hydrostatic as opposed to hydrostatic numerical weather prediction model output significantly impacts the de‐aliasing product We found that for extreme events additional moisture fields unaccounted in present Atmosphere and Ocean De‐aliasing (AOD) models can reach magnitudes relevant for de‐aliasing\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"martre-dueri-guarin-ewert-webber-calderini-molero-reynolds-etal-globalneedsfornitrogenfertilizertoimprovewheatyieldunderclimatechange-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s41477-024-01739-3\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'martre-dueri-guarin-ewert-webber-calderini-molero-reynolds-etal-globalneedsfornitrogenfertilizertoimprovewheatyieldunderclimatechange-2024', 'https://www.nature.com/articles/s41477-024-01739-3', event);\">\n    Global needs for nitrogen fertilizer to improve wheat yield under climate change.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Martre, P.; Dueri, S.; Guarin, J. R.; Ewert, F.; Webber, H.; Calderini, D.; Molero, G.; Reynolds, M.; Miralles, D.; Garcia, G.; Brown, H.; George, M.; Craigie, R.; Cohan, J.; Deswarte, J.; Slafer, G.; Giunta, F.; Cammarano, D.; Ferrise, R.; Gaiser, T.; Gao, Y.; Hochman, Z.; Hoogenboom, G.; Hunt, L. A.; Kersebaum, K. C.; Nendel, C.; Padovan, G.; Ruane, A. C.; Srivastava, A. K.; Stella, T.; Supit, I.; Thorburn, P.; Wang, E.; Wolf, J.; Zhao, C.; Zhao, Z.;  and Asseng, S.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Plants</i>. July 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s41477-024-01739-3\"\n     onclick=\"log_download('martre-dueri-guarin-ewert-webber-calderini-molero-reynolds-etal-globalneedsfornitrogenfertilizertoimprovewheatyieldunderclimatechange-2024', 'https://www.nature.com/articles/s41477-024-01739-3', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Global needs for nitrogen fertilizer to improve wheat yield under climate change [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s41477-024-01739-3\"\n     onclick=\"log_download('martre-dueri-guarin-ewert-webber-calderini-molero-reynolds-etal-globalneedsfornitrogenfertilizertoimprovewheatyieldunderclimatechange-2024', 'http://doi.org/10.1038/s41477-024-01739-3', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/martre-dueri-guarin-ewert-webber-calderini-molero-reynolds-etal-globalneedsfornitrogenfertilizertoimprovewheatyieldunderclimatechange-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('martre-dueri-guarin-ewert-webber-calderini-molero-reynolds-etal-globalneedsfornitrogenfertilizertoimprovewheatyieldunderclimatechange-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{martre_global_2024,\n\ttitle = {Global needs for nitrogen fertilizer to improve wheat yield under climate change},\n\tissn = {2055-0278},\n\turl = {https://www.nature.com/articles/s41477-024-01739-3},\n\tdoi = {10.1038/s41477-024-01739-3},\n\tlanguage = {en},\n\turldate = {2024-07-22},\n\tjournal = {Nature Plants},\n\tauthor = {Martre, Pierre and Dueri, Sibylle and Guarin, Jose Rafael and Ewert, Frank and Webber, Heidi and Calderini, Daniel and Molero, Gemma and Reynolds, Matthew and Miralles, Daniel and Garcia, Guillermo and Brown, Hamish and George, Mike and Craigie, Rob and Cohan, Jean-Pierre and Deswarte, Jean-Charles and Slafer, Gustavo and Giunta, Francesco and Cammarano, Davide and Ferrise, Roberto and Gaiser, Thomas and Gao, Yujing and Hochman, Zvi and Hoogenboom, Gerrit and Hunt, Leslie A. and Kersebaum, Kurt C. and Nendel, Claas and Padovan, Gloria and Ruane, Alex C. and Srivastava, Amit Kumar and Stella, Tommaso and Supit, Iwan and Thorburn, Peter and Wang, Enli and Wolf, Joost and Zhao, Chuang and Zhao, Zhigan and Asseng, Senthold},\n\tmonth = jul,\n\tyear = {2024},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-poll-hendricksfranssen-heinrichs-vereecken-goergen-convectionpermittingiconlamsimulationsforrenewableenergypotentialestimatesoversouthernafrica-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chen-poll-hendricksfranssen-heinrichs-vereecken-goergen-convectionpermittingiconlamsimulationsforrenewableenergypotentialestimatesoversouthernafrica-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569', event);\">\n    Convection‐Permitting ICON‐LAM Simulations for Renewable Energy Potential Estimates Over Southern Africa.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen, S.; Poll, S.; Hendricks Franssen, H.; Heinrichs, H.; Vereecken, H.;  and Goergen, K.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Geophysical Research: Atmospheres</i>, 129(6): e2023JD039569. March 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569\"\n     onclick=\"log_download('chen-poll-hendricksfranssen-heinrichs-vereecken-goergen-convectionpermittingiconlamsimulationsforrenewableenergypotentialestimatesoversouthernafrica-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Convection‐Permitting ICON‐LAM Simulations for Renewable Energy Potential Estimates Over Southern Africa [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2023JD039569\"\n     onclick=\"log_download('chen-poll-hendricksfranssen-heinrichs-vereecken-goergen-convectionpermittingiconlamsimulationsforrenewableenergypotentialestimatesoversouthernafrica-2024', 'http://doi.org/10.1029/2023JD039569', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-poll-hendricksfranssen-heinrichs-vereecken-goergen-convectionpermittingiconlamsimulationsforrenewableenergypotentialestimatesoversouthernafrica-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-poll-hendricksfranssen-heinrichs-vereecken-goergen-convectionpermittingiconlamsimulationsforrenewableenergypotentialestimatesoversouthernafrica-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{chen_convectionpermitting_2024,\n\ttitle = {Convection‐{Permitting} {ICON}‐{LAM} {Simulations} for {Renewable} {Energy} {Potential} {Estimates} {Over} {Southern} {Africa}},\n\tvolume = {129},\n\tissn = {2169-897X, 2169-8996},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD039569},\n\tdoi = {10.1029/2023JD039569},\n\tabstract = {Abstract\n            \n              Renewable energy is recognized in Africa as a means for climate change mitigation, but also to provide access to electricity in sub‐Saharan Africa, where three‐quarters of the global population without electricity resides. Reliable and highly resolved renewable energy potential (REP) information is indispensable to support power plants expansion. Existing atmospheric data sets over Africa that are used for REP estimates are often characterized by data gaps, or coarse resolution. With the aim to overcome these challenges, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON‐NWP) model in its Limited Area Mode (ICON‐LAM) is implemented and run over southern Africa in a hindcast dynamical downscaling setup at a convection‐permitting 3.3 km horizontal resolution. The simulation time span covers contrasting solar and wind weather years from 2017 to 2019. To assess the suitability of the novel simulations for REP estimates, the simulated hourly 10 m wind speed (sfcWind) and hourly surface solar irradiance (rsds) are extensively evaluated against a large compilation of in situ observations, satellite, and composite data products. ICON‐LAM reproduces the spatial patterns, temporal evolution, the variability, and absolute values of sfcWind sufficiently well, albeit with a slight overestimation and a mean bias (mean error (ME)) of 1.12 m s\n              −1\n              over land. Likewise the simulated rsds with an ME of 50 W m\n              −2\n              well resembles the observations. This new ICON simulation data product will be the basis for ensuing REP estimates that will be compared with existing lower resolution data sets.\n            \n          , \n            Plain Language Summary\n            There are still approximately 580 million people in Africa without reliable electricity supply. Renewable energy is broadly accepted as an important solution for Africa to fill the power supply gap and to mitigate climate change. Renewable energy potential (REP) information is thereby imperative for the expansion of renewable energy power planning. With conventional REP estimates, challenges are often linked to the meteorological input data, due to either the relatively coarse spatial resolution, data gaps in space and time, or data quality in general. In this study, we implemented and ran the atmospheric model ICOsahedral Nonhydrostatic (ICON) from the German Weather Service and partners at 3 km high‐resolution. The renewable energy variables wind speed and solar irradiance from these simulations are evaluated against an extensive in situ observations data set, as well as satellite, and other composite data products. In a comparison with more than 200 stations from three different in situ observation networks, it can be shown that ICON can reproduce REP‐related variables with a level of sophistication that the data is likely to offer added value over conventional inputs to REP assessments. The study is an example on how numerical models can fill in gaps in data‐scarce regions to produce useable information.\n          , \n            Key Points\n            \n              \n                \n                  A new convection‐permitting regional ICOsahedral Nonhydrostatic (ICON) model setup over southern Africa is presented and evaluated\n                \n                \n                  The spatially and temporally highly resolved ICON wind and solar fields are inputs for improved renewable energy potential estimates\n                \n                \n                  ICON outputs agree well with hourly in situ observations and satellite data; wind speeds are slightly overestimated},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2024-07-10},\n\tjournal = {Journal of Geophysical Research: Atmospheres},\n\tauthor = {Chen, Shuying and Poll, Stefan and Hendricks Franssen, Harrie‐Jan and Heinrichs, Heidi and Vereecken, Harry and Goergen, Klaus},\n\tmonth = mar,\n\tyear = {2024},\n\tpages = {e2023JD039569},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Renewable energy is recognized in Africa as a means for climate change mitigation, but also to provide access to electricity in sub‐Saharan Africa, where three‐quarters of the global population without electricity resides. Reliable and highly resolved renewable energy potential (REP) information is indispensable to support power plants expansion. Existing atmospheric data sets over Africa that are used for REP estimates are often characterized by data gaps, or coarse resolution. With the aim to overcome these challenges, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON‐NWP) model in its Limited Area Mode (ICON‐LAM) is implemented and run over southern Africa in a hindcast dynamical downscaling setup at a convection‐permitting 3.3 km horizontal resolution. The simulation time span covers contrasting solar and wind weather years from 2017 to 2019. To assess the suitability of the novel simulations for REP estimates, the simulated hourly 10 m wind speed (sfcWind) and hourly surface solar irradiance (rsds) are extensively evaluated against a large compilation of in situ observations, satellite, and composite data products. ICON‐LAM reproduces the spatial patterns, temporal evolution, the variability, and absolute values of sfcWind sufficiently well, albeit with a slight overestimation and a mean bias (mean error (ME)) of 1.12 m s −1 over land. Likewise the simulated rsds with an ME of 50 W m −2 well resembles the observations. This new ICON simulation data product will be the basis for ensuing REP estimates that will be compared with existing lower resolution data sets. , Plain Language Summary There are still approximately 580 million people in Africa without reliable electricity supply. Renewable energy is broadly accepted as an important solution for Africa to fill the power supply gap and to mitigate climate change. Renewable energy potential (REP) information is thereby imperative for the expansion of renewable energy power planning. With conventional REP estimates, challenges are often linked to the meteorological input data, due to either the relatively coarse spatial resolution, data gaps in space and time, or data quality in general. In this study, we implemented and ran the atmospheric model ICOsahedral Nonhydrostatic (ICON) from the German Weather Service and partners at 3 km high‐resolution. The renewable energy variables wind speed and solar irradiance from these simulations are evaluated against an extensive in situ observations data set, as well as satellite, and other composite data products. In a comparison with more than 200 stations from three different in situ observation networks, it can be shown that ICON can reproduce REP‐related variables with a level of sophistication that the data is likely to offer added value over conventional inputs to REP assessments. The study is an example on how numerical models can fill in gaps in data‐scarce regions to produce useable information. , Key Points A new convection‐permitting regional ICOsahedral Nonhydrostatic (ICON) model setup over southern Africa is presented and evaluated The spatially and temporally highly resolved ICON wind and solar fields are inputs for improved renewable energy potential estimates ICON outputs agree well with hourly in situ observations and satellite data; wind speeds are slightly overestimated\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"storm-heckelei-baylis-probabilisticprogrammingforembeddingtheoryandquantifyinguncertaintyineconometricanalysis-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'storm-heckelei-baylis-probabilisticprogrammingforembeddingtheoryandquantifyinguncertaintyineconometricanalysis-2024', 'https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545', event);\">\n    Probabilistic programming for embedding theory and quantifying uncertainty in econometric analysis.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Storm, H.; Heckelei, T.;  and Baylis, K.\n</span>\n\n  \n\n</span>\n\n  <i>European Review of Agricultural Economics</i>,jbae016. July 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545\"\n     onclick=\"log_download('storm-heckelei-baylis-probabilisticprogrammingforembeddingtheoryandquantifyinguncertaintyineconometricanalysis-2024', 'https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Probabilistic programming for embedding theory and quantifying uncertainty in econometric analysis [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1093/erae/jbae016\"\n     onclick=\"log_download('storm-heckelei-baylis-probabilisticprogrammingforembeddingtheoryandquantifyinguncertaintyineconometricanalysis-2024', 'http://doi.org/10.1093/erae/jbae016', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/storm-heckelei-baylis-probabilisticprogrammingforembeddingtheoryandquantifyinguncertaintyineconometricanalysis-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('storm-heckelei-baylis-probabilisticprogrammingforembeddingtheoryandquantifyinguncertaintyineconometricanalysis-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{storm_probabilistic_2024,\n\ttitle = {Probabilistic programming for embedding theory and quantifying uncertainty in econometric analysis},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {0165-1587, 1464-3618},\n\turl = {https://academic.oup.com/erae/advance-article/doi/10.1093/erae/jbae016/7704545},\n\tdoi = {10.1093/erae/jbae016},\n\tabstract = {Abstract\n            The replication crisis in empirical research calls for a more mindful approach to how we apply and report statistical models. For empirical research to have a lasting (policy) impact, these concerns are crucial. In this paper, we present Probabilistic Programming (PP) as a way forward. The PP workflow with an explicit data-generating process enhances the communication of model assumptions, code testing and consistency between theory and estimation. By simplifying Bayesian analysis, it also offers advantages for the interpretation, communication and modelling of uncertainty. We outline the advantages of PP to encourage its adoption in our community.},\n\tlanguage = {en},\n\turldate = {2024-07-10},\n\tjournal = {European Review of Agricultural Economics},\n\tauthor = {Storm, Hugo and Heckelei, Thomas and Baylis, Kathy},\n\tmonth = jul,\n\tyear = {2024},\n\tpages = {jbae016},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract The replication crisis in empirical research calls for a more mindful approach to how we apply and report statistical models. For empirical research to have a lasting (policy) impact, these concerns are crucial. In this paper, we present Probabilistic Programming (PP) as a way forward. The PP workflow with an explicit data-generating process enhances the communication of model assumptions, code testing and consistency between theory and estimation. By simplifying Bayesian analysis, it also offers advantages for the interpretation, communication and modelling of uncertainty. We outline the advantages of PP to encourage its adoption in our community.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fiedler-naik-oconnor-smith-griffiths-kramer-takemura-allen-etal-interactionsbetweenatmosphericcompositionandclimatechangeprogressinunderstandingandfutureopportunitiesfromaerchemmippdrmipandrfmip-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://gmd.copernicus.org/articles/17/2387/2024/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fiedler-naik-oconnor-smith-griffiths-kramer-takemura-allen-etal-interactionsbetweenatmosphericcompositionandclimatechangeprogressinunderstandingandfutureopportunitiesfromaerchemmippdrmipandrfmip-2024', 'https://gmd.copernicus.org/articles/17/2387/2024/', event);\">\n    Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fiedler, S.; Naik, V.; O'Connor, F. M.; Smith, C. J.; Griffiths, P.; Kramer, R. J.; Takemura, T.; Allen, R. J.; Im, U.; Kasoar, M.; Modak, A.; Turnock, S.; Voulgarakis, A.; Watson-Parris, D.; Westervelt, D. M.; Wilcox, L. J.; Zhao, A.; Collins, W. J.; Schulz, M.; Myhre, G.;  and Forster, P. M.\n</span>\n\n  \n\n</span>\n\n  <i>Geoscientific Model Development</i>, 17(6): 2387–2417. March 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://gmd.copernicus.org/articles/17/2387/2024/\"\n     onclick=\"log_download('fiedler-naik-oconnor-smith-griffiths-kramer-takemura-allen-etal-interactionsbetweenatmosphericcompositionandclimatechangeprogressinunderstandingandfutureopportunitiesfromaerchemmippdrmipandrfmip-2024', 'https://gmd.copernicus.org/articles/17/2387/2024/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/gmd-17-2387-2024\"\n     onclick=\"log_download('fiedler-naik-oconnor-smith-griffiths-kramer-takemura-allen-etal-interactionsbetweenatmosphericcompositionandclimatechangeprogressinunderstandingandfutureopportunitiesfromaerchemmippdrmipandrfmip-2024', 'http://doi.org/10.5194/gmd-17-2387-2024', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fiedler-naik-oconnor-smith-griffiths-kramer-takemura-allen-etal-interactionsbetweenatmosphericcompositionandclimatechangeprogressinunderstandingandfutureopportunitiesfromaerchemmippdrmipandrfmip-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fiedler-naik-oconnor-smith-griffiths-kramer-takemura-allen-etal-interactionsbetweenatmosphericcompositionandclimatechangeprogressinunderstandingandfutureopportunitiesfromaerchemmippdrmipandrfmip-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{fiedler_interactions_2024,\n\ttitle = {Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from {AerChemMIP}, {PDRMIP}, and {RFMIP}},\n\tvolume = {17},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1991-9603},\n\turl = {https://gmd.copernicus.org/articles/17/2387/2024/},\n\tdoi = {10.5194/gmd-17-2387-2024},\n\tabstract = {Abstract. The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth&#x27;s surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2024-06-26},\n\tjournal = {Geoscientific Model Development},\n\tauthor = {Fiedler, Stephanie and Naik, Vaishali and O&#x27;Connor, Fiona M. and Smith, Christopher J. and Griffiths, Paul and Kramer, Ryan J. and Takemura, Toshihiko and Allen, Robert J. and Im, Ulas and Kasoar, Matthew and Modak, Angshuman and Turnock, Steven and Voulgarakis, Apostolos and Watson-Parris, Duncan and Westervelt, Daniel M. and Wilcox, Laura J. and Zhao, Alcide and Collins, William J. and Schulz, Michael and Myhre, Gunnar and Forster, Piers M.},\n\tmonth = mar,\n\tyear = {2024},\n\tpages = {2387--2417},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bacacabrera-vanderborght-couvreur-behrend-gaiser-nguyen-lobet-roothydraulicpropertiesanexplorationoftheirvariabilityacrossscales-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/10.1002/pld3.582\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bacacabrera-vanderborght-couvreur-behrend-gaiser-nguyen-lobet-roothydraulicpropertiesanexplorationoftheirvariabilityacrossscales-2024', 'https://onlinelibrary.wiley.com/doi/10.1002/pld3.582', event);\">\n    Root hydraulic properties: An exploration of their variability across scales.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Baca Cabrera, J. C.; Vanderborght, J.; Couvreur, V.; Behrend, D.; Gaiser, T.; Nguyen, T. H.;  and Lobet, G.\n</span>\n\n  \n\n</span>\n\n  <i>Plant Direct</i>, 8(4): e582. April 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/10.1002/pld3.582\"\n     onclick=\"log_download('bacacabrera-vanderborght-couvreur-behrend-gaiser-nguyen-lobet-roothydraulicpropertiesanexplorationoftheirvariabilityacrossscales-2024', 'https://onlinelibrary.wiley.com/doi/10.1002/pld3.582', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Root hydraulic properties: An exploration of their variability across scales [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/pld3.582\"\n     onclick=\"log_download('bacacabrera-vanderborght-couvreur-behrend-gaiser-nguyen-lobet-roothydraulicpropertiesanexplorationoftheirvariabilityacrossscales-2024', 'http://doi.org/10.1002/pld3.582', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bacacabrera-vanderborght-couvreur-behrend-gaiser-nguyen-lobet-roothydraulicpropertiesanexplorationoftheirvariabilityacrossscales-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bacacabrera-vanderborght-couvreur-behrend-gaiser-nguyen-lobet-roothydraulicpropertiesanexplorationoftheirvariabilityacrossscales-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{baca_cabrera_root_2024,\n\ttitle = {Root hydraulic properties: {An} exploration of their variability across scales},\n\tvolume = {8},\n\tissn = {2475-4455, 2475-4455},\n\tshorttitle = {Root hydraulic properties},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/pld3.582},\n\tdoi = {10.1002/pld3.582},\n\tabstract = {Abstract\n            Root hydraulic properties are key physiological traits that determine the capacity of root systems to take up water, at a specific evaporative demand. They can strongly vary among species, cultivars or even within the same genotype, but a systematic analysis of their variation across plant functional types (PFTs) is still missing. Here, we reviewed published empirical studies on root hydraulic properties at the segment‐, individual root‐, or root system scale and determined its variability and the main factors contributing to it. This corresponded to a total of 241 published studies, comprising 213 species, including woody and herbaceous vegetation.\n            \n              We observed an extremely large range of variation (of orders of magnitude) in root hydraulic properties, but this was not caused by systematic differences among PFTs. Rather, the (combined) effect of factors such as root system age, driving force used for measurement, or stress treatments shaped the results. We found a significant decrease in root hydraulic properties under stress conditions (drought and aquaporin inhibition,\n              p\n               {\\textless} .001) and a significant effect of the driving force used for measurement (hydrostatic or osmotic gradients,\n              p\n               {\\textless} .001). Furthermore, whole root system conductance increased significantly with root system age across several crop species (\n              p\n               {\\textless} .01), causing very large variation in the data ({\\textgreater}2 orders of magnitude). Interestingly, this relationship showed an asymptotic shape, with a steep increase during the first days of growth and a flattening out at later stages of development. We confirmed this dynamic through simulations using a state‐of‐the‐art computational model of water flow in the root system for a variety of crop species, suggesting common patterns across studies and species.\n            \n            \n              These findings provide better understanding of the main causes of root hydraulic properties variations observed across empirical studies. They also open the door to better representation of hydraulic processes across multiple plant functional types and at large scales. All data collected in our analysis has been aggregated into an open access database (\n              https://roothydraulic-properties.shinyapps.io/database/\n              ), fostering scientific exchange.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-04-25},\n\tjournal = {Plant Direct},\n\tauthor = {Baca Cabrera, Juan C. and Vanderborght, Jan and Couvreur, Valentin and Behrend, Dominik and Gaiser, Thomas and Nguyen, Thuy Huu and Lobet, Guillaume},\n\tmonth = apr,\n\tyear = {2024},\n\tpages = {e582},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Root hydraulic properties are key physiological traits that determine the capacity of root systems to take up water, at a specific evaporative demand. They can strongly vary among species, cultivars or even within the same genotype, but a systematic analysis of their variation across plant functional types (PFTs) is still missing. Here, we reviewed published empirical studies on root hydraulic properties at the segment‐, individual root‐, or root system scale and determined its variability and the main factors contributing to it. This corresponded to a total of 241 published studies, comprising 213 species, including woody and herbaceous vegetation. We observed an extremely large range of variation (of orders of magnitude) in root hydraulic properties, but this was not caused by systematic differences among PFTs. Rather, the (combined) effect of factors such as root system age, driving force used for measurement, or stress treatments shaped the results. We found a significant decrease in root hydraulic properties under stress conditions (drought and aquaporin inhibition, p  \\textless .001) and a significant effect of the driving force used for measurement (hydrostatic or osmotic gradients, p  \\textless .001). Furthermore, whole root system conductance increased significantly with root system age across several crop species ( p  \\textless .01), causing very large variation in the data (\\textgreater2 orders of magnitude). Interestingly, this relationship showed an asymptotic shape, with a steep increase during the first days of growth and a flattening out at later stages of development. We confirmed this dynamic through simulations using a state‐of‐the‐art computational model of water flow in the root system for a variety of crop species, suggesting common patterns across studies and species. These findings provide better understanding of the main causes of root hydraulic properties variations observed across empirical studies. They also open the door to better representation of hydraulic processes across multiple plant functional types and at large scales. All data collected in our analysis has been aggregated into an open access database ( https://roothydraulic-properties.shinyapps.io/database/ ), fostering scientific exchange.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shamseddin-gall-focaltsmpdeeplearningforvegetationhealthpredictionandagriculturaldroughtassessmentfromaregionalclimatesimulation-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://gmd.copernicus.org/articles/17/2987/2024/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'shamseddin-gall-focaltsmpdeeplearningforvegetationhealthpredictionandagriculturaldroughtassessmentfromaregionalclimatesimulation-2024', 'https://gmd.copernicus.org/articles/17/2987/2024/', event);\">\n    Focal-TSMP: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shams Eddin, M. H.;  and Gall, J.\n</span>\n\n  \n\n</span>\n\n  <i>Geoscientific Model Development</i>, 17(7): 2987–3023. April 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://gmd.copernicus.org/articles/17/2987/2024/\"\n     onclick=\"log_download('shamseddin-gall-focaltsmpdeeplearningforvegetationhealthpredictionandagriculturaldroughtassessmentfromaregionalclimatesimulation-2024', 'https://gmd.copernicus.org/articles/17/2987/2024/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Focal-TSMP: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/gmd-17-2987-2024\"\n     onclick=\"log_download('shamseddin-gall-focaltsmpdeeplearningforvegetationhealthpredictionandagriculturaldroughtassessmentfromaregionalclimatesimulation-2024', 'http://doi.org/10.5194/gmd-17-2987-2024', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shamseddin-gall-focaltsmpdeeplearningforvegetationhealthpredictionandagriculturaldroughtassessmentfromaregionalclimatesimulation-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shamseddin-gall-focaltsmpdeeplearningforvegetationhealthpredictionandagriculturaldroughtassessmentfromaregionalclimatesimulation-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{shams_eddin_focal-tsmp_2024,\n\ttitle = {Focal-{TSMP}: deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation},\n\tvolume = {17},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1991-9603},\n\tshorttitle = {Focal-{TSMP}},\n\turl = {https://gmd.copernicus.org/articles/17/2987/2024/},\n\tdoi = {10.5194/gmd-17-2987-2024},\n\tabstract = {Abstract. Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model’s applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP, last access: 4 April 2024).},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2024-04-25},\n\tjournal = {Geoscientific Model Development},\n\tauthor = {Shams Eddin, Mohamad Hakam and Gall, Juergen},\n\tmonth = apr,\n\tyear = {2024},\n\tpages = {2987--3023},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model’s applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP, last access: 4 April 2024).\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gu-wang-siebert-kummu-wang-hong-zhou-zhu-etal-theasymmetricimpactsofinternationalagriculturaltradeonwaterusescarcityinequalityandinequity-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s44221-024-00224-7\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gu-wang-siebert-kummu-wang-hong-zhou-zhu-etal-theasymmetricimpactsofinternationalagriculturaltradeonwaterusescarcityinequalityandinequity-2024', 'https://www.nature.com/articles/s44221-024-00224-7', event);\">\n    The asymmetric impacts of international agricultural trade on water use scarcity, inequality and inequity.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gu, W.; Wang, F.; Siebert, S.; Kummu, M.; Wang, X.; Hong, C.; Zhou, F.; Zhu, Q.; Liu, Y.;  and Qin, Y.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Water</i>. April 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s44221-024-00224-7\"\n     onclick=\"log_download('gu-wang-siebert-kummu-wang-hong-zhou-zhu-etal-theasymmetricimpactsofinternationalagriculturaltradeonwaterusescarcityinequalityandinequity-2024', 'https://www.nature.com/articles/s44221-024-00224-7', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The asymmetric impacts of international agricultural trade on water use scarcity, inequality and inequity [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s44221-024-00224-7\"\n     onclick=\"log_download('gu-wang-siebert-kummu-wang-hong-zhou-zhu-etal-theasymmetricimpactsofinternationalagriculturaltradeonwaterusescarcityinequalityandinequity-2024', 'http://doi.org/10.1038/s44221-024-00224-7', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gu-wang-siebert-kummu-wang-hong-zhou-zhu-etal-theasymmetricimpactsofinternationalagriculturaltradeonwaterusescarcityinequalityandinequity-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gu-wang-siebert-kummu-wang-hong-zhou-zhu-etal-theasymmetricimpactsofinternationalagriculturaltradeonwaterusescarcityinequalityandinequity-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{gu_asymmetric_2024,\n\ttitle = {The asymmetric impacts of international agricultural trade on water use scarcity, inequality and inequity},\n\tissn = {2731-6084},\n\turl = {https://www.nature.com/articles/s44221-024-00224-7},\n\tdoi = {10.1038/s44221-024-00224-7},\n\tlanguage = {en},\n\turldate = {2024-04-25},\n\tjournal = {Nature Water},\n\tauthor = {Gu, Weiyi and Wang, Fang and Siebert, Stefan and Kummu, Matti and Wang, Xuhui and Hong, Chaopeng and Zhou, Feng and Zhu, Qing and Liu, Yong and Qin, Yue},\n\tmonth = apr,\n\tyear = {2024},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mehta-siebert-kummu-deng-ali-marston-xie-davis-halfoftwentyfirstcenturyglobalirrigationexpansionhasbeeninwaterstressedregions-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s44221-024-00206-9\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mehta-siebert-kummu-deng-ali-marston-xie-davis-halfoftwentyfirstcenturyglobalirrigationexpansionhasbeeninwaterstressedregions-2024', 'https://www.nature.com/articles/s44221-024-00206-9', event);\">\n    Half of twenty-first century global irrigation expansion has been in water-stressed regions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mehta, P.; Siebert, S.; Kummu, M.; Deng, Q.; Ali, T.; Marston, L.; Xie, W.;  and Davis, K. F.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Water</i>. March 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s44221-024-00206-9\"\n     onclick=\"log_download('mehta-siebert-kummu-deng-ali-marston-xie-davis-halfoftwentyfirstcenturyglobalirrigationexpansionhasbeeninwaterstressedregions-2024', 'https://www.nature.com/articles/s44221-024-00206-9', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Half of twenty-first century global irrigation expansion has been in water-stressed regions [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s44221-024-00206-9\"\n     onclick=\"log_download('mehta-siebert-kummu-deng-ali-marston-xie-davis-halfoftwentyfirstcenturyglobalirrigationexpansionhasbeeninwaterstressedregions-2024', 'http://doi.org/10.1038/s44221-024-00206-9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mehta-siebert-kummu-deng-ali-marston-xie-davis-halfoftwentyfirstcenturyglobalirrigationexpansionhasbeeninwaterstressedregions-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mehta-siebert-kummu-deng-ali-marston-xie-davis-halfoftwentyfirstcenturyglobalirrigationexpansionhasbeeninwaterstressedregions-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{mehta_half_2024,\n\ttitle = {Half of twenty-first century global irrigation expansion has been in water-stressed regions},\n\tissn = {2731-6084},\n\turl = {https://www.nature.com/articles/s44221-024-00206-9},\n\tdoi = {10.1038/s44221-024-00206-9},\n\tabstract = {Abstract\n            The expansion of irrigated agriculture has increased global crop production but resulted in widespread stress on freshwater resources. Ensuring that increases in irrigated production occur only in places where water is relatively abundant is a key objective of sustainable agriculture and knowledge of how irrigated land has evolved is important for measuring progress towards water sustainability. Yet, a spatially detailed understanding of the evolution of the global area equipped for irrigation (AEI) is missing. In this study, we used the latest subnational irrigation statistics (covering 17,298 administrative units) from various official sources to develop a gridded (5 arcmin resolution) global product of AEI for the years 2000, 2005, 2010 and 2015. We found that AEI increased by 11\\% from 2000 (297 Mha) to 2015 (330 Mha), with areas of both substantial expansion, such as northwest India and northeast China, and decline, such as Russia. Combining these outputs with information on green (that is, rainfall) and blue (that is, surface and ground) water stress, we also examined to what extent irrigation has expanded unsustainably in places already experiencing water stress. We found that more than half (52\\%) of the irrigation expansion has taken place in areas that were already water-stressed in the year 2000, with India alone accounting for 36\\% of global unsustainable expansion. These findings provide new insights into the evolving patterns of global irrigation with important implications for global water sustainability and food security.},\n\tlanguage = {en},\n\turldate = {2024-03-11},\n\tjournal = {Nature Water},\n\tauthor = {Mehta, Piyush and Siebert, Stefan and Kummu, Matti and Deng, Qinyu and Ali, Tariq and Marston, Landon and Xie, Wei and Davis, Kyle Frankel},\n\tmonth = mar,\n\tyear = {2024},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract The expansion of irrigated agriculture has increased global crop production but resulted in widespread stress on freshwater resources. Ensuring that increases in irrigated production occur only in places where water is relatively abundant is a key objective of sustainable agriculture and knowledge of how irrigated land has evolved is important for measuring progress towards water sustainability. Yet, a spatially detailed understanding of the evolution of the global area equipped for irrigation (AEI) is missing. In this study, we used the latest subnational irrigation statistics (covering 17,298 administrative units) from various official sources to develop a gridded (5 arcmin resolution) global product of AEI for the years 2000, 2005, 2010 and 2015. We found that AEI increased by 11% from 2000 (297 Mha) to 2015 (330 Mha), with areas of both substantial expansion, such as northwest India and northeast China, and decline, such as Russia. Combining these outputs with information on green (that is, rainfall) and blue (that is, surface and ground) water stress, we also examined to what extent irrigation has expanded unsustainably in places already experiencing water stress. We found that more than half (52%) of the irrigation expansion has taken place in areas that were already water-stressed in the year 2000, with India alone accounting for 36% of global unsustainable expansion. These findings provide new insights into the evolving patterns of global irrigation with important implications for global water sustainability and food security.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"strebel-bogena-vereecken-andreasen-arandabarranco-hendricksfranssen-evapotranspirationpredictionforeuropeanforestsitesdoesnotimprovewithassimilationofinsitusoilwatercontentdata-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://hess.copernicus.org/articles/28/1001/2024/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'strebel-bogena-vereecken-andreasen-arandabarranco-hendricksfranssen-evapotranspirationpredictionforeuropeanforestsitesdoesnotimprovewithassimilationofinsitusoilwatercontentdata-2024', 'https://hess.copernicus.org/articles/28/1001/2024/', event);\">\n    Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Strebel, L.; Bogena, H.; Vereecken, H.; Andreasen, M.; Aranda-Barranco, S.;  and Hendricks Franssen, H.\n</span>\n\n  \n\n</span>\n\n  <i>Hydrology and Earth System Sciences</i>, 28(4): 1001–1026. February 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://hess.copernicus.org/articles/28/1001/2024/\"\n     onclick=\"log_download('strebel-bogena-vereecken-andreasen-arandabarranco-hendricksfranssen-evapotranspirationpredictionforeuropeanforestsitesdoesnotimprovewithassimilationofinsitusoilwatercontentdata-2024', 'https://hess.copernicus.org/articles/28/1001/2024/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/hess-28-1001-2024\"\n     onclick=\"log_download('strebel-bogena-vereecken-andreasen-arandabarranco-hendricksfranssen-evapotranspirationpredictionforeuropeanforestsitesdoesnotimprovewithassimilationofinsitusoilwatercontentdata-2024', 'http://doi.org/10.5194/hess-28-1001-2024', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/strebel-bogena-vereecken-andreasen-arandabarranco-hendricksfranssen-evapotranspirationpredictionforeuropeanforestsitesdoesnotimprovewithassimilationofinsitusoilwatercontentdata-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('strebel-bogena-vereecken-andreasen-arandabarranco-hendricksfranssen-evapotranspirationpredictionforeuropeanforestsitesdoesnotimprovewithassimilationofinsitusoilwatercontentdata-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{strebel_evapotranspiration_2024,\n\ttitle = {Evapotranspiration prediction for {European} forest sites does not improve with assimilation of in situ soil water content data},\n\tvolume = {28},\n\tissn = {1607-7938},\n\turl = {https://hess.copernicus.org/articles/28/1001/2024/},\n\tdoi = {10.5194/hess-28-1001-2024},\n\tabstract = {Abstract. Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSMs with observations, data assimilation methods and tools have been developed in the past decades. We apply the coupled Community Land Model version 5 (CLM5) and Parallel Data Assimilation Framework (PDAF) system (CLM5-PDAF) for 13 forest field sites throughout Europe covering different climate zones. The goal of this study is to assimilate in situ soil moisture measurements into CLM5 to improve the modeled evapotranspiration fluxes. The modeled fluxes will be evaluated using the predicted evapotranspiration fluxes with eddy covariance (EC) systems. Most of the sites use point-scale measurements from sensors placed in the ground; however, for three of the forest sites we use soil water content data from cosmic-ray neutron sensors, which have a measurement scale closer to the typical land surface model grid scale and EC footprint. Our results show that while data assimilation reduced the root-mean-square error for soil water content on average by 56 \\% to 64 \\%, the root-mean-square error for the evapotranspiration estimation is increased by 4 \\%. This finding indicates that only improving the soil water content (SWC) estimation of state-of-the-art LSMs such as CLM5 is not sufficient to improve evapotranspiration estimates for forest sites. To improve evapotranspiration estimates, it is also necessary to consider the representation of leaf area index (LAI) in magnitude and timing, as well as uncertainties in water uptake by roots and vegetation parameters.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-03-05},\n\tjournal = {Hydrology and Earth System Sciences},\n\tauthor = {Strebel, Lukas and Bogena, Heye and Vereecken, Harry and Andreasen, Mie and Aranda-Barranco, Sergio and Hendricks Franssen, Harrie-Jan},\n\tmonth = feb,\n\tyear = {2024},\n\tpages = {1001--1026},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSMs with observations, data assimilation methods and tools have been developed in the past decades. We apply the coupled Community Land Model version 5 (CLM5) and Parallel Data Assimilation Framework (PDAF) system (CLM5-PDAF) for 13 forest field sites throughout Europe covering different climate zones. The goal of this study is to assimilate in situ soil moisture measurements into CLM5 to improve the modeled evapotranspiration fluxes. The modeled fluxes will be evaluated using the predicted evapotranspiration fluxes with eddy covariance (EC) systems. Most of the sites use point-scale measurements from sensors placed in the ground; however, for three of the forest sites we use soil water content data from cosmic-ray neutron sensors, which have a measurement scale closer to the typical land surface model grid scale and EC footprint. Our results show that while data assimilation reduced the root-mean-square error for soil water content on average by 56 % to 64 %, the root-mean-square error for the evapotranspiration estimation is increased by 4 %. This finding indicates that only improving the soil water content (SWC) estimation of state-of-the-art LSMs such as CLM5 is not sufficient to improve evapotranspiration estimates for forest sites. To improve evapotranspiration estimates, it is also necessary to consider the representation of leaf area index (LAI) in magnitude and timing, as well as uncertainties in water uptake by roots and vegetation parameters.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-bogena-bayat-kurtz-hendricksfranssen-canasparsenetworkofcosmicrayneutronsensorsimprovesoilmoistureandevapotranspirationestimationatthelargercatchmentscale-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'li-bogena-bayat-kurtz-hendricksfranssen-canasparsenetworkofcosmicrayneutronsensorsimprovesoilmoistureandevapotranspirationestimationatthelargercatchmentscale-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056', event);\">\n    Can a Sparse Network of Cosmic Ray Neutron Sensors Improve Soil Moisture and Evapotranspiration Estimation at the Larger Catchment Scale?.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li, F.; Bogena, H. R.; Bayat, B.; Kurtz, W.;  and Hendricks Franssen, H.\n</span>\n\n  \n\n</span>\n\n  <i>Water Resources Research</i>, 60(1): e2023WR035056. January 2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056\"\n     onclick=\"log_download('li-bogena-bayat-kurtz-hendricksfranssen-canasparsenetworkofcosmicrayneutronsensorsimprovesoilmoistureandevapotranspirationestimationatthelargercatchmentscale-2024', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Can a Sparse Network of Cosmic Ray Neutron Sensors Improve Soil Moisture and Evapotranspiration Estimation at the Larger Catchment Scale? [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2023WR035056\"\n     onclick=\"log_download('li-bogena-bayat-kurtz-hendricksfranssen-canasparsenetworkofcosmicrayneutronsensorsimprovesoilmoistureandevapotranspirationestimationatthelargercatchmentscale-2024', 'http://doi.org/10.1029/2023WR035056', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-bogena-bayat-kurtz-hendricksfranssen-canasparsenetworkofcosmicrayneutronsensorsimprovesoilmoistureandevapotranspirationestimationatthelargercatchmentscale-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>12 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-bogena-bayat-kurtz-hendricksfranssen-canasparsenetworkofcosmicrayneutronsensorsimprovesoilmoistureandevapotranspirationestimationatthelargercatchmentscale-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{li_can_2024,\n\ttitle = {Can a {Sparse} {Network} of {Cosmic} {Ray} {Neutron} {Sensors} {Improve} {Soil} {Moisture} and {Evapotranspiration} {Estimation} at the {Larger} {Catchment} {Scale}?},\n\tvolume = {60},\n\tissn = {0043-1397, 1944-7973},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR035056},\n\tdoi = {10.1029/2023WR035056},\n\tabstract = {Abstract\n            Cosmic‐ray neutron sensors (CRNS) fill the gap between locally measured in‐situ soil moisture (SM) and remotely sensed SM by providing accurate SM estimation at the field scale. This is promising for improving hydrologic model predictions, as CRNS can provide valuable information on SM in the root zone at the typical scale of a model grid cell. In this study, SM measurements from a network of 12 CRNS in the Rur catchment (Germany) were assimilated into the Terrestrial System Modeling Platform (TSMP) to investigate its potential for improving SM, evapotranspiration (ET) and river discharge characterization and estimating soil hydraulic parameters at the larger catchment scale. The data assimilation (DA) experiments (with and without parameter estimation) were conducted in both a wet year (2016) and a dry year (2018) with the ensemble Kalman filter (EnKF), and later verified with an independent year (2017) without DA. The results show that SM characterization was significantly improved at measurement locations (with up to 60\\% root mean square error (RMSE) reduction), and that joint state‐parameter estimation improved SM simulation more than state estimation alone (more than 15\\% additional RMSE reduction). Jackknife experiments showed that SM at verification locations had lower and different improvements in the wet and dry years (an RMSE reduction of 40\\% in 2016 and 16\\% in 2018). In addition, SM assimilation was found to improve ET characterization to a much lesser extent, with a 15\\% RMSE reduction of monthly ET in the wet year and 9\\% in the dry year.\n          , \n            Key Points\n            \n              \n                \n                  Assimilation of soil moisture from a network of cosmic‐ray neutron sensors improves soil moisture characterization at the catchment scale\n                \n                \n                  Soil moisture characterization improved more in a wet year than in a very dry year\n                \n                \n                  Evapotranspiration and river discharge simulation are only slightly improved, despite better estimations of soil moisture},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-02-26},\n\tjournal = {Water Resources Research},\n\tauthor = {Li, Fang and Bogena, Heye Reemt and Bayat, Bagher and Kurtz, Wolfgang and Hendricks Franssen, Harrie‐Jan},\n\tmonth = jan,\n\tyear = {2024},\n\tpages = {e2023WR035056},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Cosmic‐ray neutron sensors (CRNS) fill the gap between locally measured in‐situ soil moisture (SM) and remotely sensed SM by providing accurate SM estimation at the field scale. This is promising for improving hydrologic model predictions, as CRNS can provide valuable information on SM in the root zone at the typical scale of a model grid cell. In this study, SM measurements from a network of 12 CRNS in the Rur catchment (Germany) were assimilated into the Terrestrial System Modeling Platform (TSMP) to investigate its potential for improving SM, evapotranspiration (ET) and river discharge characterization and estimating soil hydraulic parameters at the larger catchment scale. The data assimilation (DA) experiments (with and without parameter estimation) were conducted in both a wet year (2016) and a dry year (2018) with the ensemble Kalman filter (EnKF), and later verified with an independent year (2017) without DA. The results show that SM characterization was significantly improved at measurement locations (with up to 60% root mean square error (RMSE) reduction), and that joint state‐parameter estimation improved SM simulation more than state estimation alone (more than 15% additional RMSE reduction). Jackknife experiments showed that SM at verification locations had lower and different improvements in the wet and dry years (an RMSE reduction of 40% in 2016 and 16% in 2018). In addition, SM assimilation was found to improve ET characterization to a much lesser extent, with a 15% RMSE reduction of monthly ET in the wet year and 9% in the dry year. , Key Points Assimilation of soil moisture from a network of cosmic‐ray neutron sensors improves soil moisture characterization at the catchment scale Soil moisture characterization improved more in a wet year than in a very dry year Evapotranspiration and river discharge simulation are only slightly improved, despite better estimations of soil moisture\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2023\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2023')\"\n      onkeypress=\"toggleGroup('group_2023')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2023</span>\n      <span class=\"bibbase_group_count\">\n        \n        (17)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"bayat-oloruntoba-montzka-vereecken-hendricksfranssen-implicationsforsustainablewaterconsumptioninafricabysimulatingfivedecades19652014ofgroundwaterrecharge-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bayat-oloruntoba-montzka-vereecken-hendricksfranssen-implicationsforsustainablewaterconsumptioninafricabysimulatingfivedecades19652014ofgroundwaterrecharge-2023', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301', event);\">\n    Implications for sustainable water consumption in Africa by simulating five decades (1965–2014) of groundwater recharge.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bayat, B.; Oloruntoba, B.; Montzka, C.; Vereecken, H.;  and Hendricks Franssen, H.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Hydrology</i>, 626: 130288. November 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301\"\n     onclick=\"log_download('bayat-oloruntoba-montzka-vereecken-hendricksfranssen-implicationsforsustainablewaterconsumptioninafricabysimulatingfivedecades19652014ofgroundwaterrecharge-2023', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Implications for sustainable water consumption in Africa by simulating five decades (1965–2014) of groundwater recharge [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jhydrol.2023.130288\"\n     onclick=\"log_download('bayat-oloruntoba-montzka-vereecken-hendricksfranssen-implicationsforsustainablewaterconsumptioninafricabysimulatingfivedecades19652014ofgroundwaterrecharge-2023', 'http://doi.org/10.1016/j.jhydrol.2023.130288', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bayat-oloruntoba-montzka-vereecken-hendricksfranssen-implicationsforsustainablewaterconsumptioninafricabysimulatingfivedecades19652014ofgroundwaterrecharge-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bayat-oloruntoba-montzka-vereecken-hendricksfranssen-implicationsforsustainablewaterconsumptioninafricabysimulatingfivedecades19652014ofgroundwaterrecharge-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{bayat_implications_2023,\n\ttitle = {Implications for sustainable water consumption in {Africa} by simulating five decades (1965–2014) of groundwater recharge},\n\tvolume = {626},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169423012301},\n\tdoi = {10.1016/j.jhydrol.2023.130288},\n\tlanguage = {en},\n\turldate = {2024-10-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Bayat, Bagher and Oloruntoba, Bamidele and Montzka, Carsten and Vereecken, Harry and Hendricks Franssen, Harrie-Jan},\n\tmonth = nov,\n\tyear = {2023},\n\tpages = {130288},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shamseddin-roscher-gall-locationawareadaptivenormalizationadeeplearningapproachforwildfiredangerforecasting-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/10149031/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'shamseddin-roscher-gall-locationawareadaptivenormalizationadeeplearningapproachforwildfiredangerforecasting-2023', 'https://ieeexplore.ieee.org/document/10149031/', event);\">\n    Location-Aware Adaptive Normalization: A Deep Learning Approach for Wildfire Danger Forecasting.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shams Eddin, M. H.; Roscher, R.;  and Gall, J.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Geoscience and Remote Sensing</i>, 61: 1–18.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/10149031/\"\n     onclick=\"log_download('shamseddin-roscher-gall-locationawareadaptivenormalizationadeeplearningapproachforwildfiredangerforecasting-2023', 'https://ieeexplore.ieee.org/document/10149031/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Location-Aware Adaptive Normalization: A Deep Learning Approach for Wildfire Danger Forecasting [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TGRS.2023.3285401\"\n     onclick=\"log_download('shamseddin-roscher-gall-locationawareadaptivenormalizationadeeplearningapproachforwildfiredangerforecasting-2023', 'http://doi.org/10.1109/TGRS.2023.3285401', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shamseddin-roscher-gall-locationawareadaptivenormalizationadeeplearningapproachforwildfiredangerforecasting-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shamseddin-roscher-gall-locationawareadaptivenormalizationadeeplearningapproachforwildfiredangerforecasting-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{shams_eddin_location-aware_2023,\n\ttitle = {Location-{Aware} {Adaptive} {Normalization}: {A} {Deep} {Learning} {Approach} for {Wildfire} {Danger} {Forecasting}},\n\tvolume = {61},\n\tcopyright = {https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html},\n\tissn = {0196-2892, 1558-0644},\n\tshorttitle = {Location-{Aware} {Adaptive} {Normalization}},\n\turl = {https://ieeexplore.ieee.org/document/10149031/},\n\tdoi = {10.1109/TGRS.2023.3285401},\n\turldate = {2024-04-25},\n\tjournal = {IEEE Transactions on Geoscience and Remote Sensing},\n\tauthor = {Shams Eddin, Mohamad Hakam and Roscher, Ribana and Gall, Juergen},\n\tyear = {2023},\n\tpages = {1--18},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"boroughani-mirchooli-hadavifar-fiedler-mappinglanddegradationriskduetolandsusceptibilitytodustemissionandwatererosion-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://soil.copernicus.org/articles/9/411/2023/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'boroughani-mirchooli-hadavifar-fiedler-mappinglanddegradationriskduetolandsusceptibilitytodustemissionandwatererosion-2023', 'https://soil.copernicus.org/articles/9/411/2023/', event);\">\n    Mapping land degradation risk due to land susceptibility to dust emission and water erosion.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Boroughani, M.; Mirchooli, F.; Hadavifar, M.;  and Fiedler, S.\n</span>\n\n  \n\n</span>\n\n  <i>SOIL</i>, 9(2): 411–423. July 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://soil.copernicus.org/articles/9/411/2023/\"\n     onclick=\"log_download('boroughani-mirchooli-hadavifar-fiedler-mappinglanddegradationriskduetolandsusceptibilitytodustemissionandwatererosion-2023', 'https://soil.copernicus.org/articles/9/411/2023/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Mapping land degradation risk due to land susceptibility to dust emission and water erosion [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/soil-9-411-2023\"\n     onclick=\"log_download('boroughani-mirchooli-hadavifar-fiedler-mappinglanddegradationriskduetolandsusceptibilitytodustemissionandwatererosion-2023', 'http://doi.org/10.5194/soil-9-411-2023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/boroughani-mirchooli-hadavifar-fiedler-mappinglanddegradationriskduetolandsusceptibilitytodustemissionandwatererosion-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('boroughani-mirchooli-hadavifar-fiedler-mappinglanddegradationriskduetolandsusceptibilitytodustemissionandwatererosion-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{boroughani_mapping_2023,\n\ttitle = {Mapping land degradation risk due to land susceptibility to dust emission and water erosion},\n\tvolume = {9},\n\tissn = {2199-398X},\n\turl = {https://soil.copernicus.org/articles/9/411/2023/},\n\tdoi = {10.5194/soil-9-411-2023},\n\tabstract = {Abstract. Land degradation is a cause of many social, economic, and environmental\nproblems. Therefore identification and monitoring of high-risk areas for\nland degradation are necessary. Despite the importance of land degradation\ndue to wind and water erosion in some areas of the world, the combined study\nof both types of erosion in the same area receives relatively little\nattention. The present study aims to create a land degradation map in terms\nof soil erosion caused by wind and water erosion of semi-dry land. We focus\non the Lut watershed in Iran, encompassing the Lut Desert that is influenced\nby both monsoon rainfalls and dust storms. Dust sources are identified using\nMODIS satellite images with the help of four different indices to quantify\nuncertainty. The dust source maps are assessed with three machine learning\nalgorithms encompassing the artificial neural network (ANN), random forest (RF),\nand flexible discriminant analysis (FDA) to map dust sources paired with\nsoil erosion susceptibility due to water. We assess the accuracy of the maps\nfrom the machine learning results with the area under the curve (AUC)\nof the receiver operating characteristic (ROC) metric. The water and aeolian soil\nerosion maps are used to identify different classes of land degradation\nrisks. The results show that 43 \\% of the watershed is prone to land\ndegradation in terms of both aeolian and water erosion. Most regions\n(45 \\%) have a risk of water erosion and some regions (7 \\%) a risk of\naeolian erosion. Only a small fraction (4 \\%) of the total area of the\nregion had a low to very low susceptibility for land degradation. The\nresults of this study underline the risk of land degradation for in an\ninhabited region in Iran. Future work should focus on land degradation\nassociated with soil erosion from water and storms in larger regions to\nevaluate the risks also elsewhere.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-02-26},\n\tjournal = {SOIL},\n\tauthor = {Boroughani, Mahdi and Mirchooli, Fahimeh and Hadavifar, Mojtaba and Fiedler, Stephanie},\n\tmonth = jul,\n\tyear = {2023},\n\tpages = {411--423},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. Land degradation is a cause of many social, economic, and environmental problems. Therefore identification and monitoring of high-risk areas for land degradation are necessary. Despite the importance of land degradation due to wind and water erosion in some areas of the world, the combined study of both types of erosion in the same area receives relatively little attention. The present study aims to create a land degradation map in terms of soil erosion caused by wind and water erosion of semi-dry land. We focus on the Lut watershed in Iran, encompassing the Lut Desert that is influenced by both monsoon rainfalls and dust storms. Dust sources are identified using MODIS satellite images with the help of four different indices to quantify uncertainty. The dust source maps are assessed with three machine learning algorithms encompassing the artificial neural network (ANN), random forest (RF), and flexible discriminant analysis (FDA) to map dust sources paired with soil erosion susceptibility due to water. We assess the accuracy of the maps from the machine learning results with the area under the curve (AUC) of the receiver operating characteristic (ROC) metric. The water and aeolian soil erosion maps are used to identify different classes of land degradation risks. The results show that 43 % of the watershed is prone to land degradation in terms of both aeolian and water erosion. Most regions (45 %) have a risk of water erosion and some regions (7 %) a risk of aeolian erosion. Only a small fraction (4 %) of the total area of the region had a low to very low susceptibility for land degradation. The results of this study underline the risk of land degradation for in an inhabited region in Iran. Future work should focus on land degradation associated with soil erosion from water and storms in larger regions to evaluate the risks also elsewhere.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-you-kusche-fan-su-zhang-adetailedanalysisofstochasticmodelsappliedtotemporalgravityfieldrecoverywithgraceobservations-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://academic.oup.com/gji/article/236/1/516/7382201\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yu-you-kusche-fan-su-zhang-adetailedanalysisofstochasticmodelsappliedtotemporalgravityfieldrecoverywithgraceobservations-2023', 'https://academic.oup.com/gji/article/236/1/516/7382201', event);\">\n    A detailed analysis of stochastic models applied to temporal gravity field recovery with GRACE observations.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu, B.; You, W.; Kusche, J.; Fan, D.; Su, Y.;  and Zhang, J.\n</span>\n\n  \n\n</span>\n\n  <i>Geophysical Journal International</i>, 236(1): 516–536. November 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://academic.oup.com/gji/article/236/1/516/7382201\"\n     onclick=\"log_download('yu-you-kusche-fan-su-zhang-adetailedanalysisofstochasticmodelsappliedtotemporalgravityfieldrecoverywithgraceobservations-2023', 'https://academic.oup.com/gji/article/236/1/516/7382201', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A detailed analysis of stochastic models applied to temporal gravity field recovery with GRACE observations [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1093/gji/ggad441\"\n     onclick=\"log_download('yu-you-kusche-fan-su-zhang-adetailedanalysisofstochasticmodelsappliedtotemporalgravityfieldrecoverywithgraceobservations-2023', 'http://doi.org/10.1093/gji/ggad441', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-you-kusche-fan-su-zhang-adetailedanalysisofstochasticmodelsappliedtotemporalgravityfieldrecoverywithgraceobservations-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-you-kusche-fan-su-zhang-adetailedanalysisofstochasticmodelsappliedtotemporalgravityfieldrecoverywithgraceobservations-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{yu_detailed_2023,\n\ttitle = {A detailed analysis of stochastic models applied to temporal gravity field recovery with {GRACE} observations},\n\tvolume = {236},\n\tissn = {0956-540X, 1365-246X},\n\turl = {https://academic.oup.com/gji/article/236/1/516/7382201},\n\tdoi = {10.1093/gji/ggad441},\n\tabstract = {SUMMARY\n            In this study, we analysed the impacts of errors in background force models and observed non-gravitational forces on the pseudo-observations (pre-fits) during gravity field recovery based on the Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission. To reduce these effects, we introduced the stochastic parameters into the functional model of the variational equation integration approach to absorb this type of noise contribution. Simultaneously, the prior variances of observed orbits and K-band range rates used in traditional method are re-estimated with least-squares variance component estimation (LS-VCE) after considering these stochastic parameters. To improve the computing efficiency, a modified method of the calculation of sensitivity matrices related to the introduced stochastic parameters is proposed. Compared to the method of variation of constants widely used in the precise orbit determination and gravity field recovery, the modified method decreases the computational time of these matrices by about four times. Furthermore, an efficient LS-VCE algorithm is derived in a more generalized case. The efficient algorithm only costs 1 per cent of the time of the unoptimized method. With the GRACE data, we analysed the benefits of these refinements in gravity field recovery, and the results show that these improvements can mitigate the impacts of errors in background force models and accelerometer data on recovered gravity field models, especially in the high-degree signals. Furthermore, the quality of results has less dependence on parametrization.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-02-26},\n\tjournal = {Geophysical Journal International},\n\tauthor = {Yu, Biao and You, Wei and Kusche, Jürgen and Fan, Dongming and Su, Yong and Zhang, Jiahui},\n\tmonth = nov,\n\tyear = {2023},\n\tpages = {516--536},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  SUMMARY In this study, we analysed the impacts of errors in background force models and observed non-gravitational forces on the pseudo-observations (pre-fits) during gravity field recovery based on the Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission. To reduce these effects, we introduced the stochastic parameters into the functional model of the variational equation integration approach to absorb this type of noise contribution. Simultaneously, the prior variances of observed orbits and K-band range rates used in traditional method are re-estimated with least-squares variance component estimation (LS-VCE) after considering these stochastic parameters. To improve the computing efficiency, a modified method of the calculation of sensitivity matrices related to the introduced stochastic parameters is proposed. Compared to the method of variation of constants widely used in the precise orbit determination and gravity field recovery, the modified method decreases the computational time of these matrices by about four times. Furthermore, an efficient LS-VCE algorithm is derived in a more generalized case. The efficient algorithm only costs 1 per cent of the time of the unoptimized method. With the GRACE data, we analysed the benefits of these refinements in gravity field recovery, and the results show that these improvements can mitigate the impacts of errors in background force models and accelerometer data on recovered gravity field models, especially in the high-degree signals. Furthermore, the quality of results has less dependence on parametrization.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"vanderborght-leitner-schnepf-couvreur-vereecken-javaux-combiningrootandsoilhydraulicsinmacroscopicrepresentationsofrootwateruptake-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vanderborght-leitner-schnepf-couvreur-vereecken-javaux-combiningrootandsoilhydraulicsinmacroscopicrepresentationsofrootwateruptake-2023', 'https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273', event);\">\n    Combining root and soil hydraulics in macroscopic representations of root water uptake.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Vanderborght, J.; Leitner, D.; Schnepf, A.; Couvreur, V.; Vereecken, H.;  and Javaux, M.\n</span>\n\n  \n\n</span>\n\n  <i>Vadose Zone Journal</i>,e20273. July 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273\"\n     onclick=\"log_download('vanderborght-leitner-schnepf-couvreur-vereecken-javaux-combiningrootandsoilhydraulicsinmacroscopicrepresentationsofrootwateruptake-2023', 'https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Combining root and soil hydraulics in macroscopic representations of root water uptake [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/vzj2.20273\"\n     onclick=\"log_download('vanderborght-leitner-schnepf-couvreur-vereecken-javaux-combiningrootandsoilhydraulicsinmacroscopicrepresentationsofrootwateruptake-2023', 'http://doi.org/10.1002/vzj2.20273', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vanderborght-leitner-schnepf-couvreur-vereecken-javaux-combiningrootandsoilhydraulicsinmacroscopicrepresentationsofrootwateruptake-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vanderborght-leitner-schnepf-couvreur-vereecken-javaux-combiningrootandsoilhydraulicsinmacroscopicrepresentationsofrootwateruptake-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{vanderborght_combining_2023,\n\ttitle = {Combining root and soil hydraulics in macroscopic representations of root water uptake},\n\tissn = {1539-1663, 1539-1663},\n\turl = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/vzj2.20273},\n\tdoi = {10.1002/vzj2.20273},\n\tabstract = {Abstract\n            Plant water uptake and plant and soil water status are important for the soil water balance and plant growth. They depend on atmospheric water demand and the accessibility of soil water to plant roots, which is in turn related to the hydraulic properties of the root system and the soil around root segments. We present a simulation model that describes water flow in the soil–plant system mechanistically considering both root and soil hydraulic properties. We developed an approach to upscale three‐dimensional (3D) flow in the soil toward root segments of a 3D root architecture to a model that considers one‐dimensional flow between horizontal soil layers and radial flow to root segments in that layer. The upscaled model couples upscaled linear flow equations in the root system with an analytical solution of the nonlinear radial flow equation between the soil and roots. The upscaled model avoids simplifying assumptions about root hydraulic properties and water potential drops near roots made in, respectively, soil‐ and root‐centered models. Xylem water potentials and soil–root interface potentials are explicitly simulated and show, respectively, large variations with depth and large deviations from bulk soil water potentials under dry soil conditions. Accounting for hydraulic gradients in the soil around root segments led to an earlier but slower reduction of transpiration during a drought period and a better plant water status with higher nighttime plant water potentials.\n          , \n            Core Ideas\n            \n              \n                \n                  Root water uptake depends on root and soil hydraulic properties.\n                \n                \n                  Water uptake at root element scale was upscaled to the root system scale.\n                \n                \n                  The upscaled model can be implemented in one‐dimensional soil water flow models.\n                \n                \n                  Low conductance of dry soil prevents low nighttime plant water potentials.},\n\tlanguage = {en},\n\turldate = {2024-01-29},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Vanderborght, Jan and Leitner, Daniel and Schnepf, Andrea and Couvreur, Valentin and Vereecken, Harry and Javaux, Mathieu},\n\tmonth = jul,\n\tyear = {2023},\n\tpages = {e20273},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Plant water uptake and plant and soil water status are important for the soil water balance and plant growth. They depend on atmospheric water demand and the accessibility of soil water to plant roots, which is in turn related to the hydraulic properties of the root system and the soil around root segments. We present a simulation model that describes water flow in the soil–plant system mechanistically considering both root and soil hydraulic properties. We developed an approach to upscale three‐dimensional (3D) flow in the soil toward root segments of a 3D root architecture to a model that considers one‐dimensional flow between horizontal soil layers and radial flow to root segments in that layer. The upscaled model couples upscaled linear flow equations in the root system with an analytical solution of the nonlinear radial flow equation between the soil and roots. The upscaled model avoids simplifying assumptions about root hydraulic properties and water potential drops near roots made in, respectively, soil‐ and root‐centered models. Xylem water potentials and soil–root interface potentials are explicitly simulated and show, respectively, large variations with depth and large deviations from bulk soil water potentials under dry soil conditions. Accounting for hydraulic gradients in the soil around root segments led to an earlier but slower reduction of transpiration during a drought period and a better plant water status with higher nighttime plant water potentials. , Core Ideas Root water uptake depends on root and soil hydraulic properties. Water uptake at root element scale was upscaled to the root system scale. The upscaled model can be implemented in one‐dimensional soil water flow models. Low conductance of dry soil prevents low nighttime plant water potentials.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"schimmel-amelung-organicsoils-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'schimmel-amelung-organicsoils-2023', 'https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732', event);\">\n    Organic soils.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Schimmel, H.;  and Amelung, W.\n</span>\n\n  \n\n</span>\n\n  In <i>Encyclopedia of Soils in the Environment</i>, pages 383–397. Elsevier,  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732\"\n     onclick=\"log_download('schimmel-amelung-organicsoils-2023', 'https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Organic soils [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/B978-0-12-822974-3.00073-2\"\n     onclick=\"log_download('schimmel-amelung-organicsoils-2023', 'http://doi.org/10.1016/B978-0-12-822974-3.00073-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/schimmel-amelung-organicsoils-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('schimmel-amelung-organicsoils-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@incollection{schimmel_organic_2023,\n\ttitle = {Organic soils},\n\tisbn = {978-0-323-95133-3},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/B9780128229743000732},\n\tlanguage = {en},\n\turldate = {2023-11-27},\n\tbooktitle = {Encyclopedia of {Soils} in the {Environment}},\n\tpublisher = {Elsevier},\n\tauthor = {Schimmel, Heike and Amelung, Wulf},\n\tyear = {2023},\n\tdoi = {10.1016/B978-0-12-822974-3.00073-2},\n\tpages = {383--397},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-fenoglio-kusche-liao-uyanik-nadzir-lou-evaluationofsentinel3aaltimetryoversonghuariverbasin-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chen-fenoglio-kusche-liao-uyanik-nadzir-lou-evaluationofsentinel3aaltimetryoversonghuariverbasin-2023', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397', event);\">\n    Evaluation of Sentinel-3A altimetry over Songhua river Basin.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen, J.; Fenoglio, L.; Kusche, J.; Liao, J.; Uyanik, H.; Nadzir, Z. A.;  and Lou, Y.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Hydrology</i>, 618: 129197. March 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397\"\n     onclick=\"log_download('chen-fenoglio-kusche-liao-uyanik-nadzir-lou-evaluationofsentinel3aaltimetryoversonghuariverbasin-2023', 'https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evaluation of Sentinel-3A altimetry over Songhua river Basin [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jhydrol.2023.129197\"\n     onclick=\"log_download('chen-fenoglio-kusche-liao-uyanik-nadzir-lou-evaluationofsentinel3aaltimetryoversonghuariverbasin-2023', 'http://doi.org/10.1016/j.jhydrol.2023.129197', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-fenoglio-kusche-liao-uyanik-nadzir-lou-evaluationofsentinel3aaltimetryoversonghuariverbasin-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-fenoglio-kusche-liao-uyanik-nadzir-lou-evaluationofsentinel3aaltimetryoversonghuariverbasin-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{chen_evaluation_2023,\n\ttitle = {Evaluation of {Sentinel}-{3A} altimetry over {Songhua} river {Basin}},\n\tvolume = {618},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169423001397},\n\tdoi = {10.1016/j.jhydrol.2023.129197},\n\tlanguage = {en},\n\turldate = {2023-10-31},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Chen, Jiaming and Fenoglio, Luciana and Kusche, Jürgen and Liao, Jingjuan and Uyanik, Hakan and Nadzir, Zulfikar Adlan and Lou, Yanhan},\n\tmonth = mar,\n\tyear = {2023},\n\tpages = {129197},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gntner-gerdener-boergens-kusche-kollet-dobslaw-hartick-sharifi-etal-vernderungenderwasserspeicherungindeutschlandseit2002ausbeobachtungendersatellitengravimetriewaterstoragechangesingermanysince2002fromsatellitegravityobservations-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gntner-gerdener-boergens-kusche-kollet-dobslaw-hartick-sharifi-etal-vernderungenderwasserspeicherungindeutschlandseit2002ausbeobachtungendersatellitengravimetriewaterstoragechangesingermanysince2002fromsatellitegravityobservations-2023', 'https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf', event);\">\n    Veränderungen der Wasserspeicherung in Deutschland seit 2002 aus Beobachtungen der Satellitengravimetrie – Water storage changes in Germany since 2002 from satellite gravity observations.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Güntner, A.; Gerdener, H.; Boergens, E.; Kusche, J.; Kollet, S.; Dobslaw, H.; Hartick, C.; Sharifi, E.;  and Flechtner, F.\n</span>\n\n  \n\n</span>\n\n  <i>Hydrologie und Wasserbewirtschaftung</i>.  2023.\n  <span class=\"note\">Publisher: Bundesanstalt für Gewässerkunde, Koblenz</span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf\"\n     onclick=\"log_download('gntner-gerdener-boergens-kusche-kollet-dobslaw-hartick-sharifi-etal-vernderungenderwasserspeicherungindeutschlandseit2002ausbeobachtungendersatellitengravimetriewaterstoragechangesingermanysince2002fromsatellitegravityobservations-2023', 'https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Veränderungen der Wasserspeicherung in Deutschland seit 2002 aus Beobachtungen der Satellitengravimetrie – Water storage changes in Germany since 2002 from satellite gravity observations [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5675/HYWA_2023.2_1\"\n     onclick=\"log_download('gntner-gerdener-boergens-kusche-kollet-dobslaw-hartick-sharifi-etal-vernderungenderwasserspeicherungindeutschlandseit2002ausbeobachtungendersatellitengravimetriewaterstoragechangesingermanysince2002fromsatellitegravityobservations-2023', 'http://doi.org/10.5675/HYWA_2023.2_1', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gntner-gerdener-boergens-kusche-kollet-dobslaw-hartick-sharifi-etal-vernderungenderwasserspeicherungindeutschlandseit2002ausbeobachtungendersatellitengravimetriewaterstoragechangesingermanysince2002fromsatellitegravityobservations-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gntner-gerdener-boergens-kusche-kollet-dobslaw-hartick-sharifi-etal-vernderungenderwasserspeicherungindeutschlandseit2002ausbeobachtungendersatellitengravimetriewaterstoragechangesingermanysince2002fromsatellitegravityobservations-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{guntner_veranderungen_2023,\n\ttitle = {Veränderungen der {Wasserspeicherung} in {Deutschland} seit 2002 aus {Beobachtungen} der {Satellitengravimetrie} – {Water} storage changes in {Germany} since 2002 from satellite gravity observations},\n\tissn = {1439-1783},\n\turl = {https://doi.bafg.de/HyWa/2023/HyWa_2023.2_1.pdf},\n\tdoi = {10.5675/HYWA_2023.2_1},\n\turldate = {2023-10-30},\n\tjournal = {Hydrologie und Wasserbewirtschaftung},\n\tauthor = {Güntner, Andreas and Gerdener, Helena and Boergens, Eva and Kusche, Jürgen and Kollet, Stefan and Dobslaw, Henryk and Hartick, Carl and Sharifi, Ehsan and Flechtner, Frank},\n\tyear = {2023},\n\tnote = {Publisher: Bundesanstalt für Gewässerkunde, Koblenz},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"enders-vianna-gaiser-krauss-webber-srivastava-seidel-tewes-etal-simplaceaversatilemodellingandsimulationframeworkforsustainablecropsandagroecosystems-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'enders-vianna-gaiser-krauss-webber-srivastava-seidel-tewes-etal-simplaceaversatilemodellingandsimulationframeworkforsustainablecropsandagroecosystems-2023', 'https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223', event);\">\n    SIMPLACE—a versatile modelling and simulation framework for sustainable crops and agroecosystems.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Enders, A.; Vianna, M.; Gaiser, T.; Krauss, G.; Webber, H.; Srivastava, A. K.; Seidel, S. J.; Tewes, A.; Rezaei, E. E.;  and Ewert, F.\n</span>\n\n  \n\n</span>\n\n  <i>in silico Plants</i>, 5(1): diad006. January 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223\"\n     onclick=\"log_download('enders-vianna-gaiser-krauss-webber-srivastava-seidel-tewes-etal-simplaceaversatilemodellingandsimulationframeworkforsustainablecropsandagroecosystems-2023', 'https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"SIMPLACE—a versatile modelling and simulation framework for sustainable crops and agroecosystems [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1093/insilicoplants/diad006\"\n     onclick=\"log_download('enders-vianna-gaiser-krauss-webber-srivastava-seidel-tewes-etal-simplaceaversatilemodellingandsimulationframeworkforsustainablecropsandagroecosystems-2023', 'http://doi.org/10.1093/insilicoplants/diad006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/enders-vianna-gaiser-krauss-webber-srivastava-seidel-tewes-etal-simplaceaversatilemodellingandsimulationframeworkforsustainablecropsandagroecosystems-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('enders-vianna-gaiser-krauss-webber-srivastava-seidel-tewes-etal-simplaceaversatilemodellingandsimulationframeworkforsustainablecropsandagroecosystems-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{enders_simplaceversatile_2023,\n\ttitle = {{SIMPLACE}—a versatile modelling and simulation framework for sustainable crops and agroecosystems},\n\tvolume = {5},\n\tissn = {2517-5025},\n\turl = {https://academic.oup.com/insilicoplants/article/doi/10.1093/insilicoplants/diad006/7176223},\n\tdoi = {10.1093/insilicoplants/diad006},\n\tabstract = {Abstract\n            Agricultural system analysis has considerably evolved over the last years, allowing scientists to quantify complex interactions in crops and agroecosystems. Computer-based models have become a central tool for such analysis, using formulated mathematical representations (algorithms) of different biophysical processes to simulate complex system’s behaviour. Nevertheless, the current large variety of algorithms in combination with nonstandardization in their use limits rapid and rigorous model improvement and testing. This is particularly important because contextualization is a key aspect used to formulate the appropriate model structure for a specific research question, framing a clear demand for ‘next generation’ models being modular and flexible. This paper aims to describe the Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE), which has been developed over the last decade to address the various aforementioned issues and support appropriate model formulations and interoperability. We describe its main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems with high flexibility, performance and transparency. A brief review of exemplary applications of SIMPLACE is provided covering the different topics, crops and cropping systems, spatial scales and geographies. We stress that standardized documentation of modules, variables ontology and data archives are key requirements to maintain and assist model development and reproducibility. The increasing demand for more complex, diversified and integrated production systems (e.g. intercropping, livestock-grazing, agroforestry) and the associated impacts on sustainable food systems also require the strong collaboration of a multidisciplinary community of modellers and stakeholders.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-10-30},\n\tjournal = {in silico Plants},\n\tauthor = {Enders, Andreas and Vianna, Murilo and Gaiser, Thomas and Krauss, Gunther and Webber, Heidi and Srivastava, Amit Kumar and Seidel, Sabine Julia and Tewes, Andreas and Rezaei, Ehsan Eyshi and Ewert, Frank},\n\teditor = {Marshall-Colon, Amy},\n\tmonth = jan,\n\tyear = {2023},\n\tpages = {diad006},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Agricultural system analysis has considerably evolved over the last years, allowing scientists to quantify complex interactions in crops and agroecosystems. Computer-based models have become a central tool for such analysis, using formulated mathematical representations (algorithms) of different biophysical processes to simulate complex system’s behaviour. Nevertheless, the current large variety of algorithms in combination with nonstandardization in their use limits rapid and rigorous model improvement and testing. This is particularly important because contextualization is a key aspect used to formulate the appropriate model structure for a specific research question, framing a clear demand for ‘next generation’ models being modular and flexible. This paper aims to describe the Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE), which has been developed over the last decade to address the various aforementioned issues and support appropriate model formulations and interoperability. We describe its main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems with high flexibility, performance and transparency. A brief review of exemplary applications of SIMPLACE is provided covering the different topics, crops and cropping systems, spatial scales and geographies. We stress that standardized documentation of modules, variables ontology and data archives are key requirements to maintain and assist model development and reproducibility. The increasing demand for more complex, diversified and integrated production systems (e.g. intercropping, livestock-grazing, agroforestry) and the associated impacts on sustainable food systems also require the strong collaboration of a multidisciplinary community of modellers and stakeholders.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"graf-wohlfahrt-arandabarranco-arriga-brmmer-ceschia-ciais-desai-etal-jointoptimizationoflandcarbonuptakeandalbedocanhelpachievemoderateinstantaneousandlongtermcoolingeffects-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s43247-023-00958-4\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'graf-wohlfahrt-arandabarranco-arriga-brmmer-ceschia-ciais-desai-etal-jointoptimizationoflandcarbonuptakeandalbedocanhelpachievemoderateinstantaneousandlongtermcoolingeffects-2023', 'https://www.nature.com/articles/s43247-023-00958-4', event);\">\n    Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Graf, A.; Wohlfahrt, G.; Aranda-Barranco, S.; Arriga, N.; Brümmer, C.; Ceschia, E.; Ciais, P.; Desai, A. R.; Di Lonardo, S.; Gharun, M.; Grünwald, T.; Hörtnagl, L.; Kasak, K.; Klosterhalfen, A.; Knohl, A.; Kowalska, N.; Leuchner, M.; Lindroth, A.; Mauder, M.; Migliavacca, M.; Morel, A. C.; Pfennig, A.; Poorter, H.; Terán, C. P.; Reitz, O.; Rebmann, C.; Sanchez-Azofeifa, A.; Schmidt, M.; Šigut, L.; Tomelleri, E.; Yu, K.; Varlagin, A.;  and Vereecken, H.\n</span>\n\n  \n\n</span>\n\n  <i>Communications Earth & Environment</i>, 4(1): 298. August 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s43247-023-00958-4\"\n     onclick=\"log_download('graf-wohlfahrt-arandabarranco-arriga-brmmer-ceschia-ciais-desai-etal-jointoptimizationoflandcarbonuptakeandalbedocanhelpachievemoderateinstantaneousandlongtermcoolingeffects-2023', 'https://www.nature.com/articles/s43247-023-00958-4', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s43247-023-00958-4\"\n     onclick=\"log_download('graf-wohlfahrt-arandabarranco-arriga-brmmer-ceschia-ciais-desai-etal-jointoptimizationoflandcarbonuptakeandalbedocanhelpachievemoderateinstantaneousandlongtermcoolingeffects-2023', 'http://doi.org/10.1038/s43247-023-00958-4', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/graf-wohlfahrt-arandabarranco-arriga-brmmer-ceschia-ciais-desai-etal-jointoptimizationoflandcarbonuptakeandalbedocanhelpachievemoderateinstantaneousandlongtermcoolingeffects-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('graf-wohlfahrt-arandabarranco-arriga-brmmer-ceschia-ciais-desai-etal-jointoptimizationoflandcarbonuptakeandalbedocanhelpachievemoderateinstantaneousandlongtermcoolingeffects-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{graf_joint_2023,\n\ttitle = {Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects},\n\tvolume = {4},\n\tissn = {2662-4435},\n\turl = {https://www.nature.com/articles/s43247-023-00958-4},\n\tdoi = {10.1038/s43247-023-00958-4},\n\tabstract = {Abstract\n            Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-10-30},\n\tjournal = {Communications Earth \\&amp; Environment},\n\tauthor = {Graf, Alexander and Wohlfahrt, Georg and Aranda-Barranco, Sergio and Arriga, Nicola and Brümmer, Christian and Ceschia, Eric and Ciais, Philippe and Desai, Ankur R. and Di Lonardo, Sara and Gharun, Mana and Grünwald, Thomas and Hörtnagl, Lukas and Kasak, Kuno and Klosterhalfen, Anne and Knohl, Alexander and Kowalska, Natalia and Leuchner, Michael and Lindroth, Anders and Mauder, Matthias and Migliavacca, Mirco and Morel, Alexandra C. and Pfennig, Andreas and Poorter, Hendrik and Terán, Christian Poppe and Reitz, Oliver and Rebmann, Corinna and Sanchez-Azofeifa, Arturo and Schmidt, Marius and Šigut, Ladislav and Tomelleri, Enrico and Yu, Ke and Varlagin, Andrej and Vereecken, Harry},\n\tmonth = aug,\n\tyear = {2023},\n\tpages = {298},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-kurtz-hung-vereecken-hendricksfranssen-watertabledepthassimilationinintegratedterrestrialsystemmodelsatthelargercatchmentscale-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'li-kurtz-hung-vereecken-hendricksfranssen-watertabledepthassimilationinintegratedterrestrialsystemmodelsatthelargercatchmentscale-2023', 'https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full', event);\">\n    Water table depth assimilation in integrated terrestrial system models at the larger catchment scale.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li, F.; Kurtz, W.; Hung, C. P.; Vereecken, H.;  and Hendricks Franssen, H.\n</span>\n\n  \n\n</span>\n\n  <i>Frontiers in Water</i>, 5: 1150999. March 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full\"\n     onclick=\"log_download('li-kurtz-hung-vereecken-hendricksfranssen-watertabledepthassimilationinintegratedterrestrialsystemmodelsatthelargercatchmentscale-2023', 'https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Water table depth assimilation in integrated terrestrial system models at the larger catchment scale [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3389/frwa.2023.1150999\"\n     onclick=\"log_download('li-kurtz-hung-vereecken-hendricksfranssen-watertabledepthassimilationinintegratedterrestrialsystemmodelsatthelargercatchmentscale-2023', 'http://doi.org/10.3389/frwa.2023.1150999', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-kurtz-hung-vereecken-hendricksfranssen-watertabledepthassimilationinintegratedterrestrialsystemmodelsatthelargercatchmentscale-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-kurtz-hung-vereecken-hendricksfranssen-watertabledepthassimilationinintegratedterrestrialsystemmodelsatthelargercatchmentscale-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{li_water_2023,\n\ttitle = {Water table depth assimilation in integrated terrestrial system models at the larger catchment scale},\n\tvolume = {5},\n\tissn = {2624-9375},\n\turl = {https://www.frontiersin.org/articles/10.3389/frwa.2023.1150999/full},\n\tdoi = {10.3389/frwa.2023.1150999},\n\tabstract = {As an important source of water for human beings, groundwater plays a significant role in human production and life. However, different sources of uncertainty may lead to unsatisfactory simulations of groundwater hydrodynamics with hydrological models. The goal of this study is to investigate the impact of assimilating groundwater data into the Terrestrial System Modeling Platform (TSMP) for improving hydrological modeling in a real-world case. Daily groundwater table depth (WTD) measurements from the year 2018 for the Rur catchment in Germany were assimilated by the Localized Ensemble Kalman Filter (LEnKF) into TSMP. The LEnKF is used with a localization radius so that the assimilated measurements only update model states in a limited radius around the measurements, in order to avoid unphysical updates related to spurious correlations. Due to the mismatch between groundwater measurements and the coarse model resolution (500 m), the measurements need careful screening before data assimilation (DA). Based on the spatial autocorrelation of the WTD deduced from the measurements, three different filter localization radii (2.5, 5, and 10 km) were evaluated for assimilation. The bias in the simulated water table and the root mean square error (RMSE) are reduced after DA, compared with runs without DA [i.e., open loop (OL) runs]. The best results at the assimilated locations are obtained for a localization radius of 10 km, with an 81\\% reduction of RMSE at the measurement locations, and slightly smaller RMSE reductions for the 5 and 2.5 km radius. The validation with independent WTD data showed the best results for a localization radius of 10 km, but groundwater table characterization could only be improved for sites \\&amp;lt;2.5 km from measurement locations. In case of a localization radius of 10 km the RMSE-reduction was 30\\% for those nearby sites. Simulated soil moisture was validated against soil moisture measured by cosmic-ray neutron sensors (CRNS), but no RMSE reduction was observed for DA-runs compared to OL-run. However, in both cases, the correlation between measured and simulated soil moisture content was high (between 0.70 and 0.89, except for the Wuestebach site).},\n\turldate = {2023-10-30},\n\tjournal = {Frontiers in Water},\n\tauthor = {Li, Fang and Kurtz, Wolfgang and Hung, Ching Pui and Vereecken, Harry and Hendricks Franssen, Harrie-Jan},\n\tmonth = mar,\n\tyear = {2023},\n\tpages = {1150999},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  As an important source of water for human beings, groundwater plays a significant role in human production and life. However, different sources of uncertainty may lead to unsatisfactory simulations of groundwater hydrodynamics with hydrological models. The goal of this study is to investigate the impact of assimilating groundwater data into the Terrestrial System Modeling Platform (TSMP) for improving hydrological modeling in a real-world case. Daily groundwater table depth (WTD) measurements from the year 2018 for the Rur catchment in Germany were assimilated by the Localized Ensemble Kalman Filter (LEnKF) into TSMP. The LEnKF is used with a localization radius so that the assimilated measurements only update model states in a limited radius around the measurements, in order to avoid unphysical updates related to spurious correlations. Due to the mismatch between groundwater measurements and the coarse model resolution (500 m), the measurements need careful screening before data assimilation (DA). Based on the spatial autocorrelation of the WTD deduced from the measurements, three different filter localization radii (2.5, 5, and 10 km) were evaluated for assimilation. The bias in the simulated water table and the root mean square error (RMSE) are reduced after DA, compared with runs without DA [i.e., open loop (OL) runs]. The best results at the assimilated locations are obtained for a localization radius of 10 km, with an 81% reduction of RMSE at the measurement locations, and slightly smaller RMSE reductions for the 5 and 2.5 km radius. The validation with independent WTD data showed the best results for a localization radius of 10 km, but groundwater table characterization could only be improved for sites &lt;2.5 km from measurement locations. In case of a localization radius of 10 km the RMSE-reduction was 30% for those nearby sites. Simulated soil moisture was validated against soil moisture measured by cosmic-ray neutron sensors (CRNS), but no RMSE reduction was observed for DA-runs compared to OL-run. However, in both cases, the correlation between measured and simulated soil moisture content was high (between 0.70 and 0.89, except for the Wuestebach site).\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"qu-miralles-veraverbeke-vereecken-montzka-wildfireprecursorsshowcomplementarypredictabilityindifferenttimescales-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s41467-023-42597-5\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'qu-miralles-veraverbeke-vereecken-montzka-wildfireprecursorsshowcomplementarypredictabilityindifferenttimescales-2023', 'https://www.nature.com/articles/s41467-023-42597-5', event);\">\n    Wildfire precursors show complementary predictability in different timescales.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Qu, Y.; Miralles, D. G.; Veraverbeke, S.; Vereecken, H.;  and Montzka, C.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Communications</i>, 14(1): 6829. October 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s41467-023-42597-5\"\n     onclick=\"log_download('qu-miralles-veraverbeke-vereecken-montzka-wildfireprecursorsshowcomplementarypredictabilityindifferenttimescales-2023', 'https://www.nature.com/articles/s41467-023-42597-5', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Wildfire precursors show complementary predictability in different timescales [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s41467-023-42597-5\"\n     onclick=\"log_download('qu-miralles-veraverbeke-vereecken-montzka-wildfireprecursorsshowcomplementarypredictabilityindifferenttimescales-2023', 'http://doi.org/10.1038/s41467-023-42597-5', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/qu-miralles-veraverbeke-vereecken-montzka-wildfireprecursorsshowcomplementarypredictabilityindifferenttimescales-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('qu-miralles-veraverbeke-vereecken-montzka-wildfireprecursorsshowcomplementarypredictabilityindifferenttimescales-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{qu_wildfire_2023,\n\ttitle = {Wildfire precursors show complementary predictability in different timescales},\n\tvolume = {14},\n\tissn = {2041-1723},\n\turl = {https://www.nature.com/articles/s41467-023-42597-5},\n\tdoi = {10.1038/s41467-023-42597-5},\n\tabstract = {Abstract\n            In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3\\% and 26.7\\% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-10-30},\n\tjournal = {Nature Communications},\n\tauthor = {Qu, Yuquan and Miralles, Diego G. and Veraverbeke, Sander and Vereecken, Harry and Montzka, Carsten},\n\tmonth = oct,\n\tyear = {2023},\n\tpages = {6829},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3% and 26.7% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mohseni-ahrari-haunert-montzka-thesynergiesofsmapenhancedandmodisproductsinarandomforestregressionforestimating1kmsoilmoistureoverafricausinggoogleearthengine-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mohseni-ahrari-haunert-montzka-thesynergiesofsmapenhancedandmodisproductsinarandomforestregressionforestimating1kmsoilmoistureoverafricausinggoogleearthengine-2023', 'https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905', event);\">\n    The synergies of SMAP enhanced and MODIS products in a random forest regression for estimating 1 km soil moisture over Africa using Google Earth Engine.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mohseni, F.; Ahrari, A.; Haunert, J.;  and Montzka, C.\n</span>\n\n  \n\n</span>\n\n  <i>Big Earth Data</i>,1–25. September 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905\"\n     onclick=\"log_download('mohseni-ahrari-haunert-montzka-thesynergiesofsmapenhancedandmodisproductsinarandomforestregressionforestimating1kmsoilmoistureoverafricausinggoogleearthengine-2023', 'https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The synergies of SMAP enhanced and MODIS products in a random forest regression for estimating 1 km soil moisture over Africa using Google Earth Engine [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/20964471.2023.2257905\"\n     onclick=\"log_download('mohseni-ahrari-haunert-montzka-thesynergiesofsmapenhancedandmodisproductsinarandomforestregressionforestimating1kmsoilmoistureoverafricausinggoogleearthengine-2023', 'http://doi.org/10.1080/20964471.2023.2257905', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mohseni-ahrari-haunert-montzka-thesynergiesofsmapenhancedandmodisproductsinarandomforestregressionforestimating1kmsoilmoistureoverafricausinggoogleearthengine-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mohseni-ahrari-haunert-montzka-thesynergiesofsmapenhancedandmodisproductsinarandomforestregressionforestimating1kmsoilmoistureoverafricausinggoogleearthengine-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{mohseni_synergies_2023,\n\ttitle = {The synergies of {SMAP} enhanced and {MODIS} products in a random forest regression for estimating 1 km soil moisture over {Africa} using {Google} {Earth} {Engine}},\n\tissn = {2096-4471, 2574-5417},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/20964471.2023.2257905},\n\tdoi = {10.1080/20964471.2023.2257905},\n\tlanguage = {en},\n\turldate = {2023-10-30},\n\tjournal = {Big Earth Data},\n\tauthor = {Mohseni, Farzane and Ahrari, Amirhossein and Haunert, Jan-Henrik and Montzka, Carsten},\n\tmonth = sep,\n\tyear = {2023},\n\tpages = {1--25},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"klos-kusche-leszczuk-gerdener-schulze-lenczuk-bogusz-introducingtheideaofclassifyingsetsofpermanentgnssstationsasbenchmarksforhydrogeodesy-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'klos-kusche-leszczuk-gerdener-schulze-lenczuk-bogusz-introducingtheideaofclassifyingsetsofpermanentgnssstationsasbenchmarksforhydrogeodesy-2023', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988', event);\">\n    Introducing the Idea of Classifying Sets of Permanent GNSS Stations as Benchmarks for Hydrogeodesy.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Klos, A.; Kusche, J.; Leszczuk, G.; Gerdener, H.; Schulze, K.; Lenczuk, A.;  and Bogusz, J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Geophysical Research: Solid Earth</i>, 128(9): e2023JB026988. September 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988\"\n     onclick=\"log_download('klos-kusche-leszczuk-gerdener-schulze-lenczuk-bogusz-introducingtheideaofclassifyingsetsofpermanentgnssstationsasbenchmarksforhydrogeodesy-2023', 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Introducing the Idea of Classifying Sets of Permanent GNSS Stations as Benchmarks for Hydrogeodesy [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2023JB026988\"\n     onclick=\"log_download('klos-kusche-leszczuk-gerdener-schulze-lenczuk-bogusz-introducingtheideaofclassifyingsetsofpermanentgnssstationsasbenchmarksforhydrogeodesy-2023', 'http://doi.org/10.1029/2023JB026988', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/klos-kusche-leszczuk-gerdener-schulze-lenczuk-bogusz-introducingtheideaofclassifyingsetsofpermanentgnssstationsasbenchmarksforhydrogeodesy-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('klos-kusche-leszczuk-gerdener-schulze-lenczuk-bogusz-introducingtheideaofclassifyingsetsofpermanentgnssstationsasbenchmarksforhydrogeodesy-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{klos_introducing_2023,\n\ttitle = {Introducing the {Idea} of {Classifying} {Sets} of {Permanent} {GNSS} {Stations} as {Benchmarks} for {Hydrogeodesy}},\n\tvolume = {128},\n\tissn = {2169-9313, 2169-9356},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JB026988},\n\tdoi = {10.1029/2023JB026988},\n\tabstract = {Abstract\n            We propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal‐scales: short‐term, seasonal and long‐term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998–2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre‐defined temporal‐scales of short‐term, seasonal and long‐term, using non‐parametric wavelet analysis. For each temporal‐scale, correlation coefficients are computed between GNSS‐measured and GRACE‐derived/GLWS‐predicted displacements. We present the benefits of applying high‐resolution GRACE‐assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15\\% for short‐term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake‐affected sites and those where a possible poroelastic response is observed.\n          , \n            Plain Language Summary\n            Displacements of the Earth&#x27;s crust measured by permanent Global Navigation Satellite System (GNSS) ground stations are used for many geophysical interpretations. However, it is common to omit the evaluation of the sensitivity of the system to the measurement of displacements from different sources, assuming in advance 100\\% sensitivity of the system to a given effect. Consequently, the fact that at a given station several effects can be recorded simultaneously is overlooked. This is particularly evident in earthquake‐affected areas, where GNSS stations are excluded from most analyses of non‐tectonic effects. We solve this problem and propose to divide GNSS stations into trusted sets, which we call benchmarks. Benchmarking is performed by indicating the stations that are certain to register a given effect in three pre‐defined temporal‐scales: short‐term, seasonal and long‐term. We present the analysis for the Amazon area, known for its large hydrosphere‐related signal, and demonstrate that the benchmarking allows for the inclusion of GNSS stations that were previously omitted in analyses of this type.\n          , \n            Key Points\n            \n              \n                \n                  Displacements measured by Global Positioning System (GPS) correlate well with surface water levels derived from radar altimetry missions\n                \n                \n                  Trusted sets of GPS stations are classified at the three pre‐defined temporal‐scales: short‐term, seasonal and long‐term\n                \n                \n                  Benchmarking allows to include more GPS stations in hydrogeodetic analyses},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2023-10-30},\n\tjournal = {Journal of Geophysical Research: Solid Earth},\n\tauthor = {Klos, A. and Kusche, J. and Leszczuk, G. and Gerdener, H. and Schulze, K. and Lenczuk, A. and Bogusz, J.},\n\tmonth = sep,\n\tyear = {2023},\n\tpages = {e2023JB026988},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract We propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal‐scales: short‐term, seasonal and long‐term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998–2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre‐defined temporal‐scales of short‐term, seasonal and long‐term, using non‐parametric wavelet analysis. For each temporal‐scale, correlation coefficients are computed between GNSS‐measured and GRACE‐derived/GLWS‐predicted displacements. We present the benefits of applying high‐resolution GRACE‐assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15% for short‐term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake‐affected sites and those where a possible poroelastic response is observed. , Plain Language Summary Displacements of the Earth's crust measured by permanent Global Navigation Satellite System (GNSS) ground stations are used for many geophysical interpretations. However, it is common to omit the evaluation of the sensitivity of the system to the measurement of displacements from different sources, assuming in advance 100% sensitivity of the system to a given effect. Consequently, the fact that at a given station several effects can be recorded simultaneously is overlooked. This is particularly evident in earthquake‐affected areas, where GNSS stations are excluded from most analyses of non‐tectonic effects. We solve this problem and propose to divide GNSS stations into trusted sets, which we call benchmarks. Benchmarking is performed by indicating the stations that are certain to register a given effect in three pre‐defined temporal‐scales: short‐term, seasonal and long‐term. We present the analysis for the Amazon area, known for its large hydrosphere‐related signal, and demonstrate that the benchmarking allows for the inclusion of GNSS stations that were previously omitted in analyses of this type. , Key Points Displacements measured by Global Positioning System (GPS) correlate well with surface water levels derived from radar altimetry missions Trusted sets of GPS stations are classified at the three pre‐defined temporal‐scales: short‐term, seasonal and long‐term Benchmarking allows to include more GPS stations in hydrogeodetic analyses\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gerdener-kusche-schulze-dll-klos-thegloballandwaterstoragedatasetrelease2glws20derivedviaassimilatinggraceandgracefodataintoaglobalhydrologicalmodel-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/10.1007/s00190-023-01763-9\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gerdener-kusche-schulze-dll-klos-thegloballandwaterstoragedatasetrelease2glws20derivedviaassimilatinggraceandgracefodataintoaglobalhydrologicalmodel-2023', 'https://link.springer.com/10.1007/s00190-023-01763-9', event);\">\n    The global land water storage data set release 2 (GLWS2.0) derived via assimilating GRACE and GRACE-FO data into a global hydrological model.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gerdener, H.; Kusche, J.; Schulze, K.; Döll, P.;  and Klos, A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Geodesy</i>, 97(7): 73. July 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/10.1007/s00190-023-01763-9\"\n     onclick=\"log_download('gerdener-kusche-schulze-dll-klos-thegloballandwaterstoragedatasetrelease2glws20derivedviaassimilatinggraceandgracefodataintoaglobalhydrologicalmodel-2023', 'https://link.springer.com/10.1007/s00190-023-01763-9', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The global land water storage data set release 2 (GLWS2.0) derived via assimilating GRACE and GRACE-FO data into a global hydrological model [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00190-023-01763-9\"\n     onclick=\"log_download('gerdener-kusche-schulze-dll-klos-thegloballandwaterstoragedatasetrelease2glws20derivedviaassimilatinggraceandgracefodataintoaglobalhydrologicalmodel-2023', 'http://doi.org/10.1007/s00190-023-01763-9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gerdener-kusche-schulze-dll-klos-thegloballandwaterstoragedatasetrelease2glws20derivedviaassimilatinggraceandgracefodataintoaglobalhydrologicalmodel-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gerdener-kusche-schulze-dll-klos-thegloballandwaterstoragedatasetrelease2glws20derivedviaassimilatinggraceandgracefodataintoaglobalhydrologicalmodel-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{gerdener_global_2023,\n\ttitle = {The global land water storage data set release 2 ({GLWS2}.0) derived via assimilating {GRACE} and {GRACE}-{FO} data into a global hydrological model},\n\tvolume = {97},\n\tissn = {0949-7714, 1432-1394},\n\turl = {https://link.springer.com/10.1007/s00190-023-01763-9},\n\tdoi = {10.1007/s00190-023-01763-9},\n\tabstract = {Abstract\n            \n              We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5\n              \n                \n                  \\$\\${\\textasciicircum}{\\textbackslash}circ \\$\\$\n                  \n                    \n                      \n                      ∘\n                    \n                  \n                \n              \n              , covering the time frame 2003 to 2019 without gaps, and including monthly uncertainty quantification. GLWS2.0 was derived by assimilating monthly GRACE/-FO mass change maps into the WaterGAP global hydrology model via the ensemble Kalman filter, taking data and model uncertainty into account. TWSA in GLWS2.0 is then accumulated over several hydrological storage variables. In this article, we describe the methods and data sets that went into GLWS2.0, how it compares to GRACE/-FO data in terms of representing TWSA trends, seasonal signals, and extremes, as well as its validation via comparing to GNSS-derived vertical loading and its comparison with a version of the NASA Catchment Land Surface Model GRACE Data Assimilation (CLSM-DA). We find that, in the average over more than 1000 stations globally, GLWS2.0 correlates better with GNSS observations of vertical loading at short-term, seasonal, and long-term temporal bands than GRACE/-FO. While some differences exist, overall GLWS2.0 agrees reasonably well with CLSM-DA in terms of TWSA trends and annual amplitudes and phases.\n              Highlights\n              \n                \n                  \n                    We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies over the global land with a spatial resolution of 0.5\n                    \n                      \n                        \\$\\${\\textasciicircum}{\\textbackslash}circ \\$\\$\n                        \n                          \n                            \n                            ∘\n                          \n                        \n                      \n                    \n                    , covering the period 2003 to 2019 without gaps, and including uncertainty quantification.\n                  \n                \n                \n                  GLWS2.0 synthesizes monthly GRACE/-FO mass change maps with daily precipitation and radiation data via the WaterGAP model framework, taking data and model uncertainty into account.\n                \n                \n                  Here we describe the methods and data sets that went into GLWS2.0 and its validation from a geodetic applications perspective. We find that, in the global average, GLWS2.0 fits better than GRACE/-FO to GNSS observations of vertical loading.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-10-30},\n\tjournal = {Journal of Geodesy},\n\tauthor = {Gerdener, Helena and Kusche, Jürgen and Schulze, Kerstin and Döll, Petra and Klos, Anna},\n\tmonth = jul,\n\tyear = {2023},\n\tpages = {73},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5 $$\\textasciicircum\\circ $$ ∘ , covering the time frame 2003 to 2019 without gaps, and including monthly uncertainty quantification. GLWS2.0 was derived by assimilating monthly GRACE/-FO mass change maps into the WaterGAP global hydrology model via the ensemble Kalman filter, taking data and model uncertainty into account. TWSA in GLWS2.0 is then accumulated over several hydrological storage variables. In this article, we describe the methods and data sets that went into GLWS2.0, how it compares to GRACE/-FO data in terms of representing TWSA trends, seasonal signals, and extremes, as well as its validation via comparing to GNSS-derived vertical loading and its comparison with a version of the NASA Catchment Land Surface Model GRACE Data Assimilation (CLSM-DA). We find that, in the average over more than 1000 stations globally, GLWS2.0 correlates better with GNSS observations of vertical loading at short-term, seasonal, and long-term temporal bands than GRACE/-FO. While some differences exist, overall GLWS2.0 agrees reasonably well with CLSM-DA in terms of TWSA trends and annual amplitudes and phases. Highlights We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies over the global land with a spatial resolution of 0.5 $$\\textasciicircum\\circ $$ ∘ , covering the period 2003 to 2019 without gaps, and including uncertainty quantification. GLWS2.0 synthesizes monthly GRACE/-FO mass change maps with daily precipitation and radiation data via the WaterGAP model framework, taking data and model uncertainty into account. Here we describe the methods and data sets that went into GLWS2.0 and its validation from a geodetic applications perspective. We find that, in the global average, GLWS2.0 fits better than GRACE/-FO to GNSS observations of vertical loading.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"naz-sharples-ma-goergen-kollet-continentalscaleevaluationofafullydistributedcoupledlandsurfaceandgroundwatermodelparflowclmv360overeurope-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://gmd.copernicus.org/articles/16/1617/2023/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'naz-sharples-ma-goergen-kollet-continentalscaleevaluationofafullydistributedcoupledlandsurfaceandgroundwatermodelparflowclmv360overeurope-2023', 'https://gmd.copernicus.org/articles/16/1617/2023/', event);\">\n    Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Naz, B. S.; Sharples, W.; Ma, Y.; Goergen, K.;  and Kollet, S.\n</span>\n\n  \n\n</span>\n\n  <i>Geoscientific Model Development</i>, 16(6): 1617–1639. March 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://gmd.copernicus.org/articles/16/1617/2023/\"\n     onclick=\"log_download('naz-sharples-ma-goergen-kollet-continentalscaleevaluationofafullydistributedcoupledlandsurfaceandgroundwatermodelparflowclmv360overeurope-2023', 'https://gmd.copernicus.org/articles/16/1617/2023/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/gmd-16-1617-2023\"\n     onclick=\"log_download('naz-sharples-ma-goergen-kollet-continentalscaleevaluationofafullydistributedcoupledlandsurfaceandgroundwatermodelparflowclmv360overeurope-2023', 'http://doi.org/10.5194/gmd-16-1617-2023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/naz-sharples-ma-goergen-kollet-continentalscaleevaluationofafullydistributedcoupledlandsurfaceandgroundwatermodelparflowclmv360overeurope-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('naz-sharples-ma-goergen-kollet-continentalscaleevaluationofafullydistributedcoupledlandsurfaceandgroundwatermodelparflowclmv360overeurope-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{naz_continental-scale_2023,\n\ttitle = {Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, {ParFlow}-{CLM} (v3.6.0), over {Europe}},\n\tvolume = {16},\n\tissn = {1991-9603},\n\turl = {https://gmd.copernicus.org/articles/16/1617/2023/},\n\tdoi = {10.5194/gmd-16-1617-2023},\n\tabstract = {Abstract. High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically based coupled land surface groundwater model, ParFlow-CLM version 3.6.0, over a pan-European model domain at 0.0275∘ (∼3 km) resolution. The model simulates a three-dimensional variably saturated groundwater-flow-solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of multiple hydrologic variables including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent (SWE), total water storage (TWS), and water table depth (WTD) resulting from a 10-year (1997–2006) model simulation was performed using in situ and remote sensing (RS) observations. Overall, the uncalibrated ParFlow-CLM model showed good agreement in simulating river discharge for 176 gauging stations across Europe (average Spearman&#x27;s rank correlation (R) of 0.77). At the local scale, ParFlow-CLM model performed well for ET (R{\\textgreater}0.94) against eddy covariance observations but showed relatively large differences for SM and WTD (median R values of 0.7 and 0.50, respectively) when compared with soil moisture networks and groundwater-monitoring-well data. However, model performance varied between hydroclimate regions, with the best agreement to RS datasets being shown in semi-arid and arid regions for most variables. Conversely, the largest differences between modeled and RS datasets (e.g., for SM, SWE, and TWS) are shown in humid and cold regions. Our findings highlight the importance of including multiple variables using both local-scale and large-scale RS datasets in model evaluations for a better understanding of physically based fully distributed hydrologic model performance and uncertainties in water and energy fluxes over continental scales and across different hydroclimate regions. The large-scale, high-resolution setup also forms a basis for future studies and provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting considering the effects of lateral surface and groundwater flows.},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2023-03-31},\n\tjournal = {Geoscientific Model Development},\n\tauthor = {Naz, Bibi S. and Sharples, Wendy and Ma, Yueling and Goergen, Klaus and Kollet, Stefan},\n\tmonth = mar,\n\tyear = {2023},\n\tpages = {1617--1639},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically based coupled land surface groundwater model, ParFlow-CLM version 3.6.0, over a pan-European model domain at 0.0275∘ (∼3 km) resolution. The model simulates a three-dimensional variably saturated groundwater-flow-solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of multiple hydrologic variables including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent (SWE), total water storage (TWS), and water table depth (WTD) resulting from a 10-year (1997–2006) model simulation was performed using in situ and remote sensing (RS) observations. Overall, the uncalibrated ParFlow-CLM model showed good agreement in simulating river discharge for 176 gauging stations across Europe (average Spearman's rank correlation (R) of 0.77). At the local scale, ParFlow-CLM model performed well for ET (R\\textgreater0.94) against eddy covariance observations but showed relatively large differences for SM and WTD (median R values of 0.7 and 0.50, respectively) when compared with soil moisture networks and groundwater-monitoring-well data. However, model performance varied between hydroclimate regions, with the best agreement to RS datasets being shown in semi-arid and arid regions for most variables. Conversely, the largest differences between modeled and RS datasets (e.g., for SM, SWE, and TWS) are shown in humid and cold regions. Our findings highlight the importance of including multiple variables using both local-scale and large-scale RS datasets in model evaluations for a better understanding of physically based fully distributed hydrologic model performance and uncertainties in water and energy fluxes over continental scales and across different hydroclimate regions. The large-scale, high-resolution setup also forms a basis for future studies and provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting considering the effects of lateral surface and groundwater flows.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"springer-lopez-owor-frappart-stieglitz-theroleofspacebasedobservationsforgroundwaterresourcemonitoringoverafrica-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://doi.org/10.1007/s10712-022-09759-4\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'springer-lopez-owor-frappart-stieglitz-theroleofspacebasedobservationsforgroundwaterresourcemonitoringoverafrica-2023', 'https://doi.org/10.1007/s10712-022-09759-4', event);\">\n    The Role of Space-Based Observations for Groundwater Resource Monitoring over Africa.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Springer, A.; Lopez, T.; Owor, M.; Frappart, F.;  and Stieglitz, T.\n</span>\n\n  \n\n</span>\n\n  <i>Surveys in Geophysics</i>. January 2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://doi.org/10.1007/s10712-022-09759-4\"\n     onclick=\"log_download('springer-lopez-owor-frappart-stieglitz-theroleofspacebasedobservationsforgroundwaterresourcemonitoringoverafrica-2023', 'https://doi.org/10.1007/s10712-022-09759-4', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The Role of Space-Based Observations for Groundwater Resource Monitoring over Africa [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10712-022-09759-4\"\n     onclick=\"log_download('springer-lopez-owor-frappart-stieglitz-theroleofspacebasedobservationsforgroundwaterresourcemonitoringoverafrica-2023', 'http://doi.org/10.1007/s10712-022-09759-4', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/springer-lopez-owor-frappart-stieglitz-theroleofspacebasedobservationsforgroundwaterresourcemonitoringoverafrica-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('springer-lopez-owor-frappart-stieglitz-theroleofspacebasedobservationsforgroundwaterresourcemonitoringoverafrica-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{springer_role_2023,\n\ttitle = {The {Role} of {Space}-{Based} {Observations} for {Groundwater} {Resource} {Monitoring} over {Africa}},\n\tissn = {1573-0956},\n\turl = {https://doi.org/10.1007/s10712-022-09759-4},\n\tdoi = {10.1007/s10712-022-09759-4},\n\tabstract = {Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent.},\n\tjournal = {Surveys in Geophysics},\n\tauthor = {Springer, Anne and Lopez, Teodolina and Owor, Michael and Frappart, Frédéric and Stieglitz, Thomas},\n\tmonth = jan,\n\tyear = {2023},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2022\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2022')\"\n      onkeypress=\"toggleGroup('group_2022')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2022</span>\n      <span class=\"bibbase_group_count\">\n        \n        (7)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"yang-luo-zhou-kusche-onstudyoftheearthtopographycorrectionforthegracesurfacemassestimation-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/10.1007/s00190-022-01683-0\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yang-luo-zhou-kusche-onstudyoftheearthtopographycorrectionforthegracesurfacemassestimation-2022', 'https://link.springer.com/10.1007/s00190-022-01683-0', event);\">\n    On study of the Earth topography correction for the GRACE surface mass estimation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yang, F.; Luo, Z.; Zhou, H.;  and Kusche, J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Geodesy</i>, 96(12): 95. December 2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/10.1007/s00190-022-01683-0\"\n     onclick=\"log_download('yang-luo-zhou-kusche-onstudyoftheearthtopographycorrectionforthegracesurfacemassestimation-2022', 'https://link.springer.com/10.1007/s00190-022-01683-0', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On study of the Earth topography correction for the GRACE surface mass estimation [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00190-022-01683-0\"\n     onclick=\"log_download('yang-luo-zhou-kusche-onstudyoftheearthtopographycorrectionforthegracesurfacemassestimation-2022', 'http://doi.org/10.1007/s00190-022-01683-0', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yang-luo-zhou-kusche-onstudyoftheearthtopographycorrectionforthegracesurfacemassestimation-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yang-luo-zhou-kusche-onstudyoftheearthtopographycorrectionforthegracesurfacemassestimation-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{yang_study_2022,\n\ttitle = {On study of the {Earth} topography correction for the {GRACE} surface mass estimation},\n\tvolume = {96},\n\tissn = {0949-7714, 1432-1394},\n\turl = {https://link.springer.com/10.1007/s00190-022-01683-0},\n\tdoi = {10.1007/s00190-022-01683-0},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2024-03-05},\n\tjournal = {Journal of Geodesy},\n\tauthor = {Yang, Fan and Luo, ZhiCai and Zhou, Hao and Kusche, Jürgen},\n\tmonth = dec,\n\tyear = {2022},\n\tpages = {95},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"qin-hong-zhao-siebert-abatzoglou-huning-sloat-park-etal-snowmeltrisktelecouplingsforirrigatedagriculture-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s41558-022-01509-z\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'qin-hong-zhao-siebert-abatzoglou-huning-sloat-park-etal-snowmeltrisktelecouplingsforirrigatedagriculture-2022', 'https://www.nature.com/articles/s41558-022-01509-z', event);\">\n    Snowmelt risk telecouplings for irrigated agriculture.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Qin, Y.; Hong, C.; Zhao, H.; Siebert, S.; Abatzoglou, J. T.; Huning, L. S.; Sloat, L. L.; Park, S.; Li, S.; Munroe, D. K.; Zhu, T.; Davis, S. J.;  and Mueller, N. D.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Climate Change</i>, 12(11): 1007–1015. November 2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s41558-022-01509-z\"\n     onclick=\"log_download('qin-hong-zhao-siebert-abatzoglou-huning-sloat-park-etal-snowmeltrisktelecouplingsforirrigatedagriculture-2022', 'https://www.nature.com/articles/s41558-022-01509-z', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Snowmelt risk telecouplings for irrigated agriculture [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s41558-022-01509-z\"\n     onclick=\"log_download('qin-hong-zhao-siebert-abatzoglou-huning-sloat-park-etal-snowmeltrisktelecouplingsforirrigatedagriculture-2022', 'http://doi.org/10.1038/s41558-022-01509-z', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/qin-hong-zhao-siebert-abatzoglou-huning-sloat-park-etal-snowmeltrisktelecouplingsforirrigatedagriculture-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('qin-hong-zhao-siebert-abatzoglou-huning-sloat-park-etal-snowmeltrisktelecouplingsforirrigatedagriculture-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{qin_snowmelt_2022,\n\ttitle = {Snowmelt risk telecouplings for irrigated agriculture},\n\tvolume = {12},\n\tissn = {1758-678X, 1758-6798},\n\turl = {https://www.nature.com/articles/s41558-022-01509-z},\n\tdoi = {10.1038/s41558-022-01509-z},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2024-03-05},\n\tjournal = {Nature Climate Change},\n\tauthor = {Qin, Yue and Hong, Chaopeng and Zhao, Hongyan and Siebert, Stefan and Abatzoglou, John T. and Huning, Laurie S. and Sloat, Lindsey L. and Park, Sohyun and Li, Shiyu and Munroe, Darla K. and Zhu, Tong and Davis, Steven J. and Mueller, Nathaniel D.},\n\tmonth = nov,\n\tyear = {2022},\n\tpages = {1007--1015},\n}\n\n\n\n\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"leonhardt-drees-jung-roscher-probabilisticbiomassestimationwithconditionalgenerativeadversarialnetworks-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.springer.com/10.1007/978-3-031-16788-1_29\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'leonhardt-drees-jung-roscher-probabilisticbiomassestimationwithconditionalgenerativeadversarialnetworks-2022', 'https://link.springer.com/10.1007/978-3-031-16788-1_29', event);\">\n    Probabilistic Biomass Estimation with Conditional Generative Adversarial Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Leonhardt, J.; Drees, L.; Jung, P.;  and Roscher, R.\n</span>\n\n  \n\n</span>\n\n  In Andres, B.; Bernard, F.; Cremers, D.; Frintrop, S.; Goldlücke, B.;  and Ihrke, I., editor(s), <i>Pattern Recognition</i>, volume 13485, pages 479–494. Springer International Publishing, Cham,  2022.\n  <span class=\"note\">Series Title: Lecture Notes in Computer Science</span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.springer.com/10.1007/978-3-031-16788-1_29\"\n     onclick=\"log_download('leonhardt-drees-jung-roscher-probabilisticbiomassestimationwithconditionalgenerativeadversarialnetworks-2022', 'https://link.springer.com/10.1007/978-3-031-16788-1_29', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Probabilistic Biomass Estimation with Conditional Generative Adversarial Networks [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-031-16788-1_29\"\n     onclick=\"log_download('leonhardt-drees-jung-roscher-probabilisticbiomassestimationwithconditionalgenerativeadversarialnetworks-2022', 'http://doi.org/10.1007/978-3-031-16788-1_29', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/leonhardt-drees-jung-roscher-probabilisticbiomassestimationwithconditionalgenerativeadversarialnetworks-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('leonhardt-drees-jung-roscher-probabilisticbiomassestimationwithconditionalgenerativeadversarialnetworks-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@incollection{andres_probabilistic_2022,\n\taddress = {Cham},\n\ttitle = {Probabilistic {Biomass} {Estimation} with {Conditional} {Generative} {Adversarial} {Networks}},\n\tvolume = {13485},\n\tisbn = {978-3-031-16787-4 978-3-031-16788-1},\n\turl = {https://link.springer.com/10.1007/978-3-031-16788-1_29},\n\tlanguage = {en},\n\turldate = {2023-11-27},\n\tbooktitle = {Pattern {Recognition}},\n\tpublisher = {Springer International Publishing},\n\tauthor = {Leonhardt, Johannes and Drees, Lukas and Jung, Peter and Roscher, Ribana},\n\teditor = {Andres, Björn and Bernard, Florian and Cremers, Daniel and Frintrop, Simone and Goldlücke, Bastian and Ihrke, Ivo},\n\tyear = {2022},\n\tdoi = {10.1007/978-3-031-16788-1_29},\n\tnote = {Series Title: Lecture Notes in Computer Science},\n\tpages = {479--494},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bauke-amelung-bol-brandt-brggemann-kandeler-meyer-or-etal-soilwaterstatusshapesnutrientcyclinginagroecosystemsfrommicrometertolandscapescales-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bauke-amelung-bol-brandt-brggemann-kandeler-meyer-or-etal-soilwaterstatusshapesnutrientcyclinginagroecosystemsfrommicrometertolandscapescales-2022', 'https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357', event);\">\n    Soil water status shapes nutrient cycling in agroecosystems from micrometer to landscape scales.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bauke, S. L.; Amelung, W.; Bol, R.; Brandt, L.; Brüggemann, N.; Kandeler, E.; Meyer, N.; Or, D.; Schnepf, A.; Schloter, M.; Schulz, S.; Siebers, N.; Von Sperber, C.;  and Vereecken, H.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Plant Nutrition and Soil Science</i>, 185(6): 773–792. December 2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357\"\n     onclick=\"log_download('bauke-amelung-bol-brandt-brggemann-kandeler-meyer-or-etal-soilwaterstatusshapesnutrientcyclinginagroecosystemsfrommicrometertolandscapescales-2022', 'https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Soil water status shapes nutrient cycling in agroecosystems from micrometer to landscape scales [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/jpln.202200357\"\n     onclick=\"log_download('bauke-amelung-bol-brandt-brggemann-kandeler-meyer-or-etal-soilwaterstatusshapesnutrientcyclinginagroecosystemsfrommicrometertolandscapescales-2022', 'http://doi.org/10.1002/jpln.202200357', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bauke-amelung-bol-brandt-brggemann-kandeler-meyer-or-etal-soilwaterstatusshapesnutrientcyclinginagroecosystemsfrommicrometertolandscapescales-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bauke-amelung-bol-brandt-brggemann-kandeler-meyer-or-etal-soilwaterstatusshapesnutrientcyclinginagroecosystemsfrommicrometertolandscapescales-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{bauke_soil_2022,\n\ttitle = {Soil water status shapes nutrient cycling in agroecosystems from micrometer to landscape scales},\n\tvolume = {185},\n\tissn = {1436-8730, 1522-2624},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/jpln.202200357},\n\tdoi = {10.1002/jpln.202200357},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2023-06-02},\n\tjournal = {Journal of Plant Nutrition and Soil Science},\n\tauthor = {Bauke, Sara L. and Amelung, Wulf and Bol, Roland and Brandt, Luise and Brüggemann, Nicolas and Kandeler, Ellen and Meyer, Nele and Or, Dani and Schnepf, Andrea and Schloter, Michael and Schulz, Stefanie and Siebers, Nina and Von Sperber, Christian and Vereecken, Harry},\n\tmonth = dec,\n\tyear = {2022},\n\tpages = {773--792},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"valmassoi-keller-areviewonirrigationparameterizationsinearthsystemmodels-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'valmassoi-keller-areviewonirrigationparameterizationsinearthsystemmodels-2022', 'https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full', event);\">\n    A review on irrigation parameterizations in Earth system models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Valmassoi, A.;  and Keller, J. D.\n</span>\n\n  \n\n</span>\n\n  <i>Frontiers in Water</i>, 4: 906664. November 2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full\"\n     onclick=\"log_download('valmassoi-keller-areviewonirrigationparameterizationsinearthsystemmodels-2022', 'https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A review on irrigation parameterizations in Earth system models [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3389/frwa.2022.906664\"\n     onclick=\"log_download('valmassoi-keller-areviewonirrigationparameterizationsinearthsystemmodels-2022', 'http://doi.org/10.3389/frwa.2022.906664', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/valmassoi-keller-areviewonirrigationparameterizationsinearthsystemmodels-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('valmassoi-keller-areviewonirrigationparameterizationsinearthsystemmodels-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{valmassoi_review_2022,\n\ttitle = {A review on irrigation parameterizations in {Earth} system models},\n\tvolume = {4},\n\tissn = {2624-9375},\n\turl = {https://www.frontiersin.org/articles/10.3389/frwa.2022.906664/full},\n\tdoi = {10.3389/frwa.2022.906664},\n\tabstract = {Irrigation is the process of artificially providing water to agricultural lands in order to provide crops with the necessary water supply to ensure or foster the growth of the plants. However, its implications reach beyond the agro-economic aspect as irrigation affects the soil-land-atmosphere interactions and thus influences the water and energy cycles in the Earth system. Past studies have shown how through these interactions, an increase in soil moisture due to irrigation also affects the atmospheric state and its dynamics. Thus, the lack of representation of irrigation in numerical Earth system models—be it for reanalysis, weather forecasting or climate prediction—can lead to significant errors and biases in various parameters of the system including but not limited to surface temperature and precipitation. In this study, we aim to summarize and discuss currently available irrigation parameterizations across different numerical models. This provides a reference framework to understand the impact of irrigation on the various components of Earth system models. Specifically, we discuss the impact of these parameterizations in the context of their spatio-temporal scale representation and point out the benefits and limitations of the various approaches. In fact, most of the parameterizations use irrigation as a direct modification of soil moisture with just a few implementations add irrigation as a form of surface water. While the former method might be suitable for coarse spatio-temporal scales, the latter better resembles the range of employed irrigation techniques. From the analysis, we find that not only the method or the spatio-temporal scales but the actual amount of water used is of great importance to the response of the Earth system model.},\n\turldate = {2023-01-30},\n\tjournal = {Frontiers in Water},\n\tauthor = {Valmassoi, Arianna and Keller, Jan D.},\n\tmonth = nov,\n\tyear = {2022},\n\tpages = {906664},\n}\n\n\n\n</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Irrigation is the process of artificially providing water to agricultural lands in order to provide crops with the necessary water supply to ensure or foster the growth of the plants. However, its implications reach beyond the agro-economic aspect as irrigation affects the soil-land-atmosphere interactions and thus influences the water and energy cycles in the Earth system. Past studies have shown how through these interactions, an increase in soil moisture due to irrigation also affects the atmospheric state and its dynamics. Thus, the lack of representation of irrigation in numerical Earth system models—be it for reanalysis, weather forecasting or climate prediction—can lead to significant errors and biases in various parameters of the system including but not limited to surface temperature and precipitation. In this study, we aim to summarize and discuss currently available irrigation parameterizations across different numerical models. This provides a reference framework to understand the impact of irrigation on the various components of Earth system models. Specifically, we discuss the impact of these parameterizations in the context of their spatio-temporal scale representation and point out the benefits and limitations of the various approaches. In fact, most of the parameterizations use irrigation as a direct modification of soil moisture with just a few implementations add irrigation as a form of surface water. While the former method might be suitable for coarse spatio-temporal scales, the latter better resembles the range of employed irrigation techniques. From the analysis, we find that not only the method or the spatio-temporal scales but the actual amount of water used is of great importance to the response of the Earth system model.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"karegar-kusche-geremianievinski-larson-raspberrypireflectorrpralowcostwaterlevelmonitoringsystembasedongnssinterferometricreflectometry-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'karegar-kusche-geremianievinski-larson-raspberrypireflectorrpralowcostwaterlevelmonitoringsystembasedongnssinterferometricreflectometry-2022', 'https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713', event);\">\n    Raspberry Pi Reflector (RPR): A Low‐cost Water‐level Monitoring System based on GNSS Interferometric Reflectometry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Karegar, M. A.; Kusche, J.; Geremia‐Nievinski, F.;  and Larson, K. M.\n</span>\n\n  \n\n</span>\n\n  <i>Water Resources Research</i>. November 2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713\"\n     onclick=\"log_download('karegar-kusche-geremianievinski-larson-raspberrypireflectorrpralowcostwaterlevelmonitoringsystembasedongnssinterferometricreflectometry-2022', 'https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Raspberry Pi Reflector (RPR): A Low‐cost Water‐level Monitoring System based on GNSS Interferometric Reflectometry [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2021WR031713\"\n     onclick=\"log_download('karegar-kusche-geremianievinski-larson-raspberrypireflectorrpralowcostwaterlevelmonitoringsystembasedongnssinterferometricreflectometry-2022', 'http://doi.org/10.1029/2021WR031713', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/karegar-kusche-geremianievinski-larson-raspberrypireflectorrpralowcostwaterlevelmonitoringsystembasedongnssinterferometricreflectometry-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('karegar-kusche-geremianievinski-larson-raspberrypireflectorrpralowcostwaterlevelmonitoringsystembasedongnssinterferometricreflectometry-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{karegar_raspberry_2022,\n\ttitle = {Raspberry {Pi} {Reflector} ({RPR}): {A} {Low}‐cost {Water}‐level {Monitoring} {System} based on {GNSS} {Interferometric} {Reflectometry}},\n\tissn = {0043-1397, 1944-7973},\n\tshorttitle = {Raspberry {Pi} {Reflector} ({RPR})},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR031713},\n\tdoi = {10.1029/2021WR031713},\n\tlanguage = {en},\n\turldate = {2022-11-24},\n\tjournal = {Water Resources Research},\n\tauthor = {Karegar, Makan A. and Kusche, Jürgen and Geremia‐Nievinski, Felipe and Larson, Kristine M.},\n\tmonth = nov,\n\tyear = {2022},\n}\n\n\n\n</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"vereecken-amelung-bauke-bogena-brggemann-montzka-vanderborght-bechtold-etal-soilhydrologyintheearthsystem-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nature.com/articles/s43017-022-00324-6\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vereecken-amelung-bauke-bogena-brggemann-montzka-vanderborght-bechtold-etal-soilhydrologyintheearthsystem-2022', 'https://www.nature.com/articles/s43017-022-00324-6', event);\">\n    Soil hydrology in the Earth system.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Vereecken, H.; Amelung, W.; Bauke, S. L.; Bogena, H.; Brüggemann, N.; Montzka, C.; Vanderborght, J.; Bechtold, M.; Blöschl, G.; Carminati, A.; Javaux, M.; Konings, A. G.; Kusche, J.; Neuweiler, I.; Or, D.; Steele-Dunne, S.; Verhoef, A.; Young, M.;  and Zhang, Y.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Reviews Earth & Environment</i>, 3(9): 573–587. August 2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nature.com/articles/s43017-022-00324-6\"\n     onclick=\"log_download('vereecken-amelung-bauke-bogena-brggemann-montzka-vanderborght-bechtold-etal-soilhydrologyintheearthsystem-2022', 'https://www.nature.com/articles/s43017-022-00324-6', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Soil hydrology in the Earth system [link]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s43017-022-00324-6\"\n     onclick=\"log_download('vereecken-amelung-bauke-bogena-brggemann-montzka-vanderborght-bechtold-etal-soilhydrologyintheearthsystem-2022', 'http://doi.org/10.1038/s43017-022-00324-6', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vereecken-amelung-bauke-bogena-brggemann-montzka-vanderborght-bechtold-etal-soilhydrologyintheearthsystem-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>7 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vereecken-amelung-bauke-bogena-brggemann-montzka-vanderborght-bechtold-etal-soilhydrologyintheearthsystem-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{vereecken_soil_2022,\n\ttitle = {Soil hydrology in the {Earth} system},\n\tvolume = {3},\n\tissn = {2662-138X},\n\turl = {https://www.nature.com/articles/s43017-022-00324-6},\n\tdoi = {10.1038/s43017-022-00324-6},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2023-01-26},\n\tjournal = {Nature Reviews Earth \\&amp; Environment},\n\tauthor = {Vereecken, Harry and Amelung, Wulf and Bauke, Sara L. and Bogena, Heye and Brüggemann, Nicolas and Montzka, Carsten and Vanderborght, Jan and Bechtold, Michel and Blöschl, Günter and Carminati, Andrea and Javaux, Mathieu and Konings, Alexandra G. and Kusche, Jürgen and Neuweiler, Insa and Or, Dani and Steele-Dunne, Susan and Verhoef, Anne and Young, Michael and Zhang, Yonggen},\n\tmonth = aug,\n\tyear = {2022},\n\tpages = {573--587},\n}\n</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n\n\n\n  </div>\n\n\n  <!-- Modal -->\n\n  <!-- <iframe id=\"bibbase_network_frame\" -->\n  <!--         src=\"//bibbase.org/network/control\" -->\n  <!--         style=\"display: none;\"> -->\n  <!-- </iframe> -->\n\n</div>\n"}; document.write(bibbase_data.data);