\n \n\n \n \n Alemohammad, S. H.; Kolassa, J.; Prigent, C.; Aires, F.; and Gentine, P.\n\n\n \n \n \n \n \n Global downscaling of remotely sensed soil moisture using neural networks.\n \n \n \n \n\n\n \n\n\n\n Hydrology and Earth System Sciences, 22(10): 5341–5356. October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Global$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{alemohammad_global_2018,\n\ttitle = {Global downscaling of remotely sensed soil moisture using neural networks},\n\tvolume = {22},\n\tissn = {1607-7938},\n\turl = {https://hess.copernicus.org/articles/22/5341/2018/},\n\tdoi = {10.5194/hess-22-5341-2018},\n\tabstract = {Abstract. Characterizing soil moisture at spatiotemporal scales relevant to land surface processes (i.e.,\nof the order of 1 km) is necessary in order to quantify its role in regional\nfeedbacks between the land surface and the atmospheric boundary layer.\nMoreover, several applications such as agricultural management can benefit\nfrom soil moisture information at fine spatial scales. Soil moisture\nestimates from current satellite missions have a reasonably good temporal\nrevisit over the globe (2–3-day repeat time); however, their finest spatial\nresolution is 9 km. NASA's Soil Moisture Active Passive (SMAP) satellite has\nestimated soil moisture at two different spatial scales of 36 and 9 km since\nApril 2015. In this study, we develop a neural-network-based downscaling\nalgorithm using SMAP observations and disaggregate soil moisture to 2.25 km\nspatial resolution. Our approach uses the mean monthly Normalized Differenced\nVegetation Index (NDVI) as ancillary data to quantify the subpixel\nheterogeneity of soil moisture. Evaluation of the downscaled soil moisture\nestimates against in situ observations shows that their accuracy is better\nthan or equal to the SMAP 9 km soil moisture estimates.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2022-11-04},\n\tjournal = {Hydrology and Earth System Sciences},\n\tauthor = {Alemohammad, Seyed Hamed and Kolassa, Jana and Prigent, Catherine and Aires, Filipe and Gentine, Pierre},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {5341--5356},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Baatz, R.; Sullivan, P. L.; Li, L.; Weintraub, S. R.; Loescher, H. W.; Mirtl, M.; Groffman, P. M.; Wall, D. H.; Young, M.; White, T.; Wen, H.; Zacharias, S.; Kühn, I.; Tang, J.; Gaillardet, J.; Braud, I.; Flores, A. N.; Kumar, P.; Lin, H.; Ghezzehei, T.; Jones, J.; Gholz, H. L.; Vereecken, H.; and Van Looy, K.\n\n\n \n \n \n \n \n Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling.\n \n \n \n \n\n\n \n\n\n\n Earth System Dynamics, 9(2): 593–609. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Steering$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{baatz_steering_2018,\n\ttitle = {Steering operational synergies in terrestrial observation networks: opportunity for advancing {Earth} system dynamics modelling},\n\tvolume = {9},\n\tissn = {2190-4987},\n\tshorttitle = {Steering operational synergies in terrestrial observation networks},\n\turl = {https://esd.copernicus.org/articles/9/593/2018/},\n\tdoi = {10.5194/esd-9-593-2018},\n\tabstract = {Abstract. Advancing our understanding of Earth system dynamics (ESD) depends on the\ndevelopment of models and other analytical tools that apply physical,\nbiological, and chemical data. This ambition to increase understanding and\ndevelop models of ESD based on site observations was the stimulus for\ncreating the networks of Long-Term Ecological Research (LTER), Critical Zone\nObservatories (CZOs), and others. We organized a survey, the results of which\nidentified pressing gaps in data availability from these networks, in\nparticular for the future development and evaluation of models that represent\nESD processes, and provide insights for improvement in both data collection\nand model integration. From this survey overview of data applications in the context of LTER and\nCZO research, we identified three challenges: (1) widen application of\nterrestrial observation network data in Earth system modelling,\n(2) develop integrated Earth system models that incorporate process\nrepresentation and data of multiple disciplines, and (3) identify\ncomplementarity in measured variables and spatial extent, and promoting\nsynergies in the existing observational networks. These challenges lead to\nperspectives and recommendations for an improved dialogue between the\nobservation networks and the ESD modelling community, including co-location\nof sites in the existing networks and further formalizing these\nrecommendations among these communities. Developing these synergies will\nenable cross-site and cross-network comparison and synthesis studies, which\nwill help produce insights around organizing principles, classifications,\nand general rules of coupling processes with environmental conditions.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-04},\n\tjournal = {Earth System Dynamics},\n\tauthor = {Baatz, Roland and Sullivan, Pamela L. and Li, Li and Weintraub, Samantha R. and Loescher, Henry W. and Mirtl, Michael and Groffman, Peter M. and Wall, Diana H. and Young, Michael and White, Tim and Wen, Hang and Zacharias, Steffen and Kühn, Ingolf and Tang, Jianwu and Gaillardet, Jérôme and Braud, Isabelle and Flores, Alejandro N. and Kumar, Praveen and Lin, Henry and Ghezzehei, Teamrat and Jones, Julia and Gholz, Henry L. and Vereecken, Harry and Van Looy, Kris},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {593--609},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Balanzategui, D.; Knorr, A.; Heussner, K.; Wazny, T.; Beck, W.; Słowiński, M.; Helle, G.; Buras, A.; Wilmking, M.; Van Der Maaten, E.; Scharnweber, T.; Dorado-Liñán, I.; and Heinrich, I.\n\n\n \n \n \n \n \n An 810-year history of cold season temperature variability for northern Poland.\n \n \n \n \n\n\n \n\n\n\n Boreas, 47(2): 443–453. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"An$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{balanzategui_810-year_2018,\n\ttitle = {An 810-year history of cold season temperature variability for northern {Poland}},\n\tvolume = {47},\n\tissn = {03009483},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/bor.12274},\n\tdoi = {10.1111/bor.12274},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-18},\n\tjournal = {Boreas},\n\tauthor = {Balanzategui, Daniel and Knorr, Antje and Heussner, Karl-Uwe and Wazny, Tomasz and Beck, Wolfgang and Słowiński, Michał and Helle, Gerhard and Buras, Allan and Wilmking, Martin and Van Der Maaten, Ernst and Scharnweber, Tobias and Dorado-Liñán, Isabel and Heinrich, Ingo},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {443--453},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Banerjee, T.; Brugger, P.; De Roo, F.; Kröniger, K.; Yakir, D.; Rotenberg, E.; and Mauder, M.\n\n\n \n \n \n \n \n Turbulent transport of energy across a forest and a semiarid shrubland.\n \n \n \n \n\n\n \n\n\n\n Atmospheric Chemistry and Physics, 18(13): 10025–10038. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Turbulent$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{banerjee_turbulent_2018,\n\ttitle = {Turbulent transport of energy across a forest and a semiarid shrubland},\n\tvolume = {18},\n\tissn = {1680-7324},\n\turl = {https://acp.copernicus.org/articles/18/10025/2018/},\n\tdoi = {10.5194/acp-18-10025-2018},\n\tabstract = {Abstract. The role of secondary circulations has recently been studied in the context of well-defined surface heterogeneity in a semiarid ecosystem where it was found that energy balance closure over a desert–forest system and the structure of the boundary layer was impacted by advection and flux divergence. As a part of the CliFF (“Climate feedbacks and benefits of semi-arid forests”, a collaboration between KIT, Germany, and the Weizmann Institute, Israel) campaign, we studied the boundary layer dynamics and turbulent transport of energy corresponding to this effect in Yatir Forest situated in the Negev Desert in Israel. The forest surrounded by small shrubs presents a distinct feature of surface heterogeneity, allowing us to study the differences between their interactions with the atmosphere above by conducting measurements with two eddy covariance (EC) stations and two Doppler lidars. As expected, the turbulence intensity and vertical fluxes of momentum and sensible heat are found to be higher above the forest compared to the shrubland. Turbulent statistics indicative of nonlocal motions are also found to differ over the forest and shrubland and also display a strong diurnal cycle. The production of turbulent kinetic energy (TKE) over the forest is strongly mechanical, while buoyancy effects generate most of the TKE over the shrubland. Overall TKE production is much higher above the forest compared to the shrubland. The forest is also found to be more efficient in dissipating TKE. The TKE budget appears to be balanced on average both for the forest and shrubland, although the imbalance of the TKE budget, which includes the role of TKE transport, is found to be quite different in terms of diurnal cycles for the forest and shrubland. The difference in turbulent quantities and the relationships between the components of TKE budget are used to infer the characteristics of the turbulent transport of energy between the desert and the forest.},\n\tlanguage = {en},\n\tnumber = {13},\n\turldate = {2022-11-04},\n\tjournal = {Atmospheric Chemistry and Physics},\n\tauthor = {Banerjee, Tirtha and Brugger, Peter and De Roo, Frederik and Kröniger, Konstantin and Yakir, Dan and Rotenberg, Eyal and Mauder, Matthias},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {10025--10038},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Baroni, G.; Scheiffele, L.; Schrön, M.; Ingwersen, J.; and Oswald, S.\n\n\n \n \n \n \n \n Uncertainty, sensitivity and improvements in soil moisture estimation with cosmic-ray neutron sensing.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 564: 873–887. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Uncertainty,$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{baroni_uncertainty_2018,\n\ttitle = {Uncertainty, sensitivity and improvements in soil moisture estimation with cosmic-ray neutron sensing},\n\tvolume = {564},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169418305675},\n\tdoi = {10.1016/j.jhydrol.2018.07.053},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Baroni, G. and Scheiffele, L.M. and Schrön, M. and Ingwersen, J. and Oswald, S.E.},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {873--887},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Barrios, J. M.; Ghilain, N.; Arboleda, A.; Sachs, T.; and Gellens-Meulenberghs, F.\n\n\n \n \n \n \n \n Daily evapotranspiration at sub-kilometre spatial resolution by combining observations from geostationary and polar-orbit satellites.\n \n \n \n \n\n\n \n\n\n\n International Journal of Remote Sensing, 39(23): 8984–9003. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Daily$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{barrios_daily_2018,\n\ttitle = {Daily evapotranspiration at sub-kilometre spatial resolution by combining observations from geostationary and polar-orbit satellites},\n\tvolume = {39},\n\tissn = {0143-1161, 1366-5901},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/01431161.2018.1504340},\n\tdoi = {10.1080/01431161.2018.1504340},\n\tlanguage = {en},\n\tnumber = {23},\n\turldate = {2022-11-04},\n\tjournal = {International Journal of Remote Sensing},\n\tauthor = {Barrios, J. M. and Ghilain, N. and Arboleda, A. and Sachs, T. and Gellens-Meulenberghs, F.},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {8984--9003},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Beckers, L.; Busch, W.; Krauss, M.; Schulze, T.; and Brack, W.\n\n\n \n \n \n \n \n Characterization and risk assessment of seasonal and weather dynamics in organic pollutant mixtures from discharge of a separate sewer system.\n \n \n \n \n\n\n \n\n\n\n Water Research, 135: 122–133. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Characterization$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{beckers_characterization_2018,\n\ttitle = {Characterization and risk assessment of seasonal and weather dynamics in organic pollutant mixtures from discharge of a separate sewer system},\n\tvolume = {135},\n\tissn = {00431354},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0043135418301015},\n\tdoi = {10.1016/j.watres.2018.02.002},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Water Research},\n\tauthor = {Beckers, Liza-Marie and Busch, Wibke and Krauss, Martin and Schulze, Tobias and Brack, Werner},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {122--133},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Beriozkin, A.; and Mualem, Y.\n\n\n \n \n \n \n \n Comparative analysis of the apparent saturation hysteresis approach and the domain theory of hysteresis in respect of prediction of scanning curves and air entrapment.\n \n \n \n \n\n\n \n\n\n\n Advances in Water Resources, 115: 253–263. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Comparative$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{beriozkin_comparative_2018,\n\ttitle = {Comparative analysis of the apparent saturation hysteresis approach and the domain theory of hysteresis in respect of prediction of scanning curves and air entrapment},\n\tvolume = {115},\n\tissn = {03091708},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0309170817301586},\n\tdoi = {10.1016/j.advwatres.2018.01.016},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Advances in Water Resources},\n\tauthor = {Beriozkin, A. and Mualem, Y.},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {253--263},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Berns, A. E.; Flath, A.; Mehmood, K.; Hofmann, D.; Jacques, D.; Sauter, M.; Vereecken, H.; and Engelhardt, I.\n\n\n \n \n \n \n \n Numerical and Experimental Investigations of Cesium and Strontium Sorption and Transport in Agricultural Soils.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 170126. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Numerical$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{berns_numerical_2018,\n\ttitle = {Numerical and {Experimental} {Investigations} of {Cesium} and {Strontium} {Sorption} and {Transport} in {Agricultural} {Soils}},\n\tvolume = {17},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2017.06.0126},\n\tdoi = {10.2136/vzj2017.06.0126},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Berns, Anne E. and Flath, Alexander and Mehmood, Khalid and Hofmann, Diana and Jacques, Diederik and Sauter, Martin and Vereecken, Harry and Engelhardt, Irina},\n\tyear = {2018},\n\tpages = {170126},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Beylich, M.; Pöhlein, F.; and Reinstorf, F.\n\n\n \n \n \n \n Das hydrologische Versuchsgebiet Schäferbach - Referenzgebiet für Klima-Simulationen.\n \n \n \n\n\n \n\n\n\n Wasserwirtschaft, 108(1): S.30–34. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{beylich_marcus_hydrologische_2018,\n\ttitle = {Das hydrologische {Versuchsgebiet} {Schäferbach} - {Referenzgebiet} für {Klima}-{Simulationen}},\n\tvolume = {108},\n\tissn = {0043-0978},\n\tnumber = {1},\n\tjournal = {Wasserwirtschaft},\n\tauthor = {Beylich, Marcus and Pöhlein, Florian and Reinstorf, Frido},\n\tyear = {2018},\n\tpages = {S.30--34},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Blume, T.; van Meerveld, I.; and Weiler, M.\n\n\n \n \n \n \n \n Why and when it is useful to publish and share inconclusive results and failures: reply to “Reporting negative results to stimulate experimental hydrology”.\n \n \n \n \n\n\n \n\n\n\n Hydrological Sciences Journal, 63(8): 1273–1274. June 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Why$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{blume_why_2018,\n\ttitle = {Why and when it is useful to publish and share inconclusive results and failures: reply to “{Reporting} negative results to stimulate experimental hydrology”},\n\tvolume = {63},\n\tissn = {0262-6667, 2150-3435},\n\tshorttitle = {Why and when it is useful to publish and share inconclusive results and failures},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/02626667.2018.1493204},\n\tdoi = {10.1080/02626667.2018.1493204},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2022-11-04},\n\tjournal = {Hydrological Sciences Journal},\n\tauthor = {Blume, Theresa and van Meerveld, Ilja and Weiler, Markus},\n\tmonth = jun,\n\tyear = {2018},\n\tpages = {1273--1274},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Blume, T.; van Meerveld, I.; and Weiler, M.\n\n\n \n \n \n \n \n Incentives for field hydrology and data sharing: collaboration and compensation: reply to “A need for incentivizing field hydrology, especially in an era of open data”*.\n \n \n \n \n\n\n \n\n\n\n Hydrological Sciences Journal, 63(8): 1266–1268. June 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Incentives$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{blume_incentives_2018,\n\ttitle = {Incentives for field hydrology and data sharing: collaboration and compensation: reply to “{A} need for incentivizing field hydrology, especially in an era of open data”*},\n\tvolume = {63},\n\tissn = {0262-6667, 2150-3435},\n\tshorttitle = {Incentives for field hydrology and data sharing},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/02626667.2018.1495839},\n\tdoi = {10.1080/02626667.2018.1495839},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2022-11-04},\n\tjournal = {Hydrological Sciences Journal},\n\tauthor = {Blume, Theresa and van Meerveld, Ilja and Weiler, Markus},\n\tmonth = jun,\n\tyear = {2018},\n\tpages = {1266--1268},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Bogena, H.; Montzka, C.; Huisman, J.; Graf, A.; Schmidt, M.; Stockinger, M.; von Hebel, C.; Hendricks-Franssen, H.; van der Kruk, J.; Tappe, W.; Lücke, A.; Baatz, R.; Bol, R.; Groh, J.; Pütz, T.; Jakobi, J.; Kunkel, R.; Sorg, J.; and Vereecken, H.\n\n\n \n \n \n \n \n The TERENO-Rur Hydrological Observatory: A Multiscale Multi-Compartment Research Platform for the Advancement of Hydrological Science.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 180055. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{bogena_tereno-rur_2018,\n\ttitle = {The {TERENO}-{Rur} {Hydrological} {Observatory}: {A} {Multiscale} {Multi}-{Compartment} {Research} {Platform} for the {Advancement} of {Hydrological} {Science}},\n\tvolume = {17},\n\tissn = {15391663},\n\tshorttitle = {The {TERENO}-{Rur} {Hydrological} {Observatory}},\n\turl = {http://doi.wiley.com/10.2136/vzj2018.03.0055},\n\tdoi = {10.2136/vzj2018.03.0055},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Bogena, H.R. and Montzka, C. and Huisman, J.A. and Graf, A. and Schmidt, M. and Stockinger, M. and von Hebel, C. and Hendricks-Franssen, H.J. and van der Kruk, J. and Tappe, W. and Lücke, A. and Baatz, R. and Bol, R. and Groh, J. and Pütz, T. and Jakobi, J. and Kunkel, R. and Sorg, J. and Vereecken, H.},\n\tyear = {2018},\n\tpages = {180055},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Bogena, H.; White, T.; Bour, O.; Li, X.; and Jensen, K.\n\n\n \n \n \n \n \n Toward Better Understanding of Terrestrial Processes through Long-Term Hydrological Observatories.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 180194. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Toward$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{bogena_toward_2018,\n\ttitle = {Toward {Better} {Understanding} of {Terrestrial} {Processes} through {Long}-{Term} {Hydrological} {Observatories}},\n\tvolume = {17},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2018.10.0194},\n\tdoi = {10.2136/vzj2018.10.0194},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Bogena, H.R. and White, T. and Bour, O. and Li, X. and Jensen, K.H.},\n\tyear = {2018},\n\tpages = {180194},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Brase, L.; Sanders, T.; and Dähnke, K.\n\n\n \n \n \n \n \n Anthropogenic changes of nitrogen loads in a small river: external nutrient sources vs. internal turnover processes.\n \n \n \n \n\n\n \n\n\n\n Isotopes in Environmental and Health Studies, 54(2): 168–184. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Anthropogenic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{brase_anthropogenic_2018,\n\ttitle = {Anthropogenic changes of nitrogen loads in a small river: external nutrient sources vs. internal turnover processes},\n\tvolume = {54},\n\tissn = {1025-6016, 1477-2639},\n\tshorttitle = {Anthropogenic changes of nitrogen loads in a small river},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/10256016.2018.1428580},\n\tdoi = {10.1080/10256016.2018.1428580},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-04},\n\tjournal = {Isotopes in Environmental and Health Studies},\n\tauthor = {Brase, Lisa and Sanders, Tina and Dähnke, Kirstin},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {168--184},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Brenner, C.; Zeeman, M.; Bernhardt, M.; and Schulz, K.\n\n\n \n \n \n \n \n Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems.\n \n \n \n \n\n\n \n\n\n\n International Journal of Remote Sensing, 39(15-16): 5141–5174. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Estimation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{brenner_estimation_2018,\n\ttitle = {Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems},\n\tvolume = {39},\n\tissn = {0143-1161, 1366-5901},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/01431161.2018.1471550},\n\tdoi = {10.1080/01431161.2018.1471550},\n\tlanguage = {en},\n\tnumber = {15-16},\n\turldate = {2022-11-04},\n\tjournal = {International Journal of Remote Sensing},\n\tauthor = {Brenner, Claire and Zeeman, Matthias and Bernhardt, Matthias and Schulz, Karsten},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {5141--5174},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Bruce, L. C.; Frassl, M. A.; Arhonditsis, G. B.; Gal, G.; Hamilton, D. P.; Hanson, P. C.; Hetherington, A. L.; Melack, J. M.; Read, J. S.; Rinke, K.; Rigosi, A.; Trolle, D.; Winslow, L.; Adrian, R.; Ayala, A. I.; Bocaniov, S. A.; Boehrer, B.; Boon, C.; Brookes, J. D.; Bueche, T.; Busch, B. D.; Copetti, D.; Cortés, A.; de Eyto, E.; Elliott, J. A.; Gallina, N.; Gilboa, Y.; Guyennon, N.; Huang, L.; Kerimoglu, O.; Lenters, J. D.; MacIntyre, S.; Makler-Pick, V.; McBride, C. G.; Moreira, S.; Özkundakci, D.; Pilotti, M.; Rueda, F. J.; Rusak, J. A.; Samal, N. R.; Schmid, M.; Shatwell, T.; Snorthheim, C.; Soulignac, F.; Valerio, G.; van der Linden, L.; Vetter, M.; Vinçon-Leite, B.; Wang, J.; Weber, M.; Wickramaratne, C.; Woolway, R. I.; Yao, H.; and Hipsey, M. R.\n\n\n \n \n \n \n \n A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network.\n \n \n \n \n\n\n \n\n\n\n Environmental Modelling & Software, 102: 274–291. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{bruce_multi-lake_2018,\n\ttitle = {A multi-lake comparative analysis of the {General} {Lake} {Model} ({GLM}): {Stress}-testing across a global observatory network},\n\tvolume = {102},\n\tissn = {13648152},\n\tshorttitle = {A multi-lake comparative analysis of the {General} {Lake} {Model} ({GLM})},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1364815216311562},\n\tdoi = {10.1016/j.envsoft.2017.11.016},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Environmental Modelling \\& Software},\n\tauthor = {Bruce, Louise C. and Frassl, Marieke A. and Arhonditsis, George B. and Gal, Gideon and Hamilton, David P. and Hanson, Paul C. and Hetherington, Amy L. and Melack, John M. and Read, Jordan S. and Rinke, Karsten and Rigosi, Anna and Trolle, Dennis and Winslow, Luke and Adrian, Rita and Ayala, Ana I. and Bocaniov, Serghei A. and Boehrer, Bertram and Boon, Casper and Brookes, Justin D. and Bueche, Thomas and Busch, Brendan D. and Copetti, Diego and Cortés, Alicia and de Eyto, Elvira and Elliott, J. Alex and Gallina, Nicole and Gilboa, Yael and Guyennon, Nicolas and Huang, Lei and Kerimoglu, Onur and Lenters, John D. and MacIntyre, Sally and Makler-Pick, Vardit and McBride, Chris G. and Moreira, Santiago and Özkundakci, Deniz and Pilotti, Marco and Rueda, Francisco J. and Rusak, James A. and Samal, Nihar R. and Schmid, Martin and Shatwell, Tom and Snorthheim, Craig and Soulignac, Frédéric and Valerio, Giulia and van der Linden, Leon and Vetter, Mark and Vinçon-Leite, Brigitte and Wang, Junbo and Weber, Michael and Wickramaratne, Chaturangi and Woolway, R. Iestyn and Yao, Huaxia and Hipsey, Matthew R.},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {274--291},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Brugger, P.; Katul, G. G.; De Roo, F.; Kröniger, K.; Rotenberg, E.; Rohatyn, S.; and Mauder, M.\n\n\n \n \n \n \n \n Scalewise invariant analysis of the anisotropic Reynolds stress tensor for atmospheric surface layer and canopy sublayer turbulent flows.\n \n \n \n \n\n\n \n\n\n\n Physical Review Fluids, 3(5): 054608. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Scalewise$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{brugger_scalewise_2018,\n\ttitle = {Scalewise invariant analysis of the anisotropic {Reynolds} stress tensor for atmospheric surface layer and canopy sublayer turbulent flows},\n\tvolume = {3},\n\tissn = {2469-990X},\n\turl = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.054608},\n\tdoi = {10.1103/PhysRevFluids.3.054608},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2022-11-04},\n\tjournal = {Physical Review Fluids},\n\tauthor = {Brugger, Peter and Katul, Gabriel G. and De Roo, Frederik and Kröniger, Konstantin and Rotenberg, Eyal and Rohatyn, Shani and Mauder, Matthias},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {054608},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Cai, G.; Vanderborght, J.; Couvreur, V.; Mboh, C. M.; and Vereecken, H.\n\n\n \n \n \n \n \n Parameterization of Root Water Uptake Models Considering Dynamic Root Distributions and Water Uptake Compensation.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 160125. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Parameterization$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{cai_parameterization_2018,\n\ttitle = {Parameterization of {Root} {Water} {Uptake} {Models} {Considering} {Dynamic} {Root} {Distributions} and {Water} {Uptake} {Compensation}},\n\tvolume = {17},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2016.12.0125},\n\tdoi = {10.2136/vzj2016.12.0125},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Cai, Gaochao and Vanderborght, Jan and Couvreur, Valentin and Mboh, Cho Miltin and Vereecken, Harry},\n\tyear = {2018},\n\tpages = {160125},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Cai, G.; Vanderborght, J.; Langensiepen, M.; Schnepf, A.; Hüging, H.; and Vereecken, H.\n\n\n \n \n \n \n \n Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions.\n \n \n \n \n\n\n \n\n\n\n Hydrology and Earth System Sciences, 22(4): 2449–2470. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Root$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{cai_root_2018,\n\ttitle = {Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions},\n\tvolume = {22},\n\tissn = {1607-7938},\n\turl = {https://hess.copernicus.org/articles/22/2449/2018/},\n\tdoi = {10.5194/hess-22-2449-2018},\n\tabstract = {Abstract. How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are\nimportant questions that need to be answered to describe water fluxes in the soil–plant–atmosphere\nsystem. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water\npotential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU\nof winter wheat using the empirical Feddes–Jarvis (FJ) model and the physically based Couvreur (C) model for different soil\nwater conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root\ndevelopment were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil\ntextures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters\nof the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for\nvalidation. The different soil types and water treatments resulted in different crop biomass, root densities, and root\ndistributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was\nalso lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all\ntreatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model\npredicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root\nhydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ\nmodel. This was attributed to differences in root densities between the different soils and treatments which are accounted\nfor by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root\ndensity on RWU could be accounted for directly by the physically based RWU model but not by empirical models that use\nnormalized root density functions.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2022-11-04},\n\tjournal = {Hydrology and Earth System Sciences},\n\tauthor = {Cai, Gaochao and Vanderborght, Jan and Langensiepen, Matthias and Schnepf, Andrea and Hüging, Hubert and Vereecken, Harry},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {2449--2470},\n}\n\n

\n

\n\n\n

\n Abstract. How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are important questions that need to be answered to describe water fluxes in the soil–plant–atmosphere system. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU of winter wheat using the empirical Feddes–Jarvis (FJ) model and the physically based Couvreur (C) model for different soil water conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities, and root distributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and treatments which are accounted for by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWU could be accounted for directly by the physically based RWU model but not by empirical models that use normalized root density functions.\n

\n\n\n

\n \n\n \n \n Carrara, A.; Kolari, P.; de Beeck, M. O.; Arriga, N.; Berveiller, D.; Dengel, S.; Ibrom, A.; Merbold, L.; Rebmann, C.; Sabbatini, S.; Serrano-Ortíz, P.; and Biraud, S. C.\n\n\n \n \n \n \n \n Radiation measurements at ICOS ecosystem stations.\n \n \n \n \n\n\n \n\n\n\n International Agrophysics, 32(4): 589–605. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Radiation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{carrara_radiation_2018,\n\ttitle = {Radiation measurements at {ICOS} ecosystem stations},\n\tvolume = {32},\n\tissn = {2300-8725},\n\turl = {http://archive.sciendo.com/INTAG/intag.2017.32.issue-4/intag-2017-0049/intag-2017-0049.pdf},\n\tdoi = {10.1515/intag-2017-0049},\n\tabstract = {Abstract \n            Solar radiation is a key driver of energy and carbon fluxes in natural ecosystems. Radiation measurements are essential for interpreting ecosystem scale greenhouse gases and energy fluxes as well as many other observations performed at ecosystem stations of the Integrated Carbon Observation System (ICOS). We describe and explain the relevance of the radiation variables that are monitored continuously at ICOS ecosystem stations and define recommendations to perform these measurements with consistent and comparable accuracy. The measurement methodology and instruments are described including detailed technical specifications. Guidelines for instrumental set up as well as for operation, maintenance and data collection are defined considering both ICOS scientific objectives and practical operational constraints. For measurements of short-wave (solar) and long wave (infrared) radiation components, requirements for the ICOS network are based on available well-defined state-of-the art standards (World Meteorological Organization, International Organization for Standardization). For photosynthetically active radiation measurements, some basic instrumental requirements are based on the performance of commercially available sensors. Since site specific conditions and practical constraints at individual ICOS ecosystem stations may hamper the applicability of standard requirements, we recommend that ICOS develops mid-term coordinated actions to assess the effective level of uncertainties in radiation measurements at the network scale.},\n\tnumber = {4},\n\turldate = {2022-11-04},\n\tjournal = {International Agrophysics},\n\tauthor = {Carrara, Arnaud and Kolari, Pasi and de Beeck, Maarten Op and Arriga, Nicola and Berveiller, Daniel and Dengel, Sigrid and Ibrom, Andreas and Merbold, Lutz and Rebmann, Corinna and Sabbatini, Simone and Serrano-Ortíz, Penelope and Biraud, Sébastien C.},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {589--605},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Czymzik, M.; Muscheler, R.; Adolphi, F.; Mekhaldi, F.; Dräger, N.; Ott, F.; Słowinski, M.; Błaszkiewicz, M.; Aldahan, A.; Possnert, G.; and Brauer, A.\n\n\n \n \n \n \n \n Synchronizing 10Be in two varved lake sediment records to IntCal13 14C during three grand solar minima.\n \n \n \n \n\n\n \n\n\n\n Climate of the Past, 14(5): 687–696. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Synchronizing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{czymzik_synchronizing_2018,\n\ttitle = {Synchronizing {10Be} in two varved lake sediment records to {IntCal13} {14C} during three grand solar minima},\n\tvolume = {14},\n\tissn = {1814-9332},\n\turl = {https://cp.copernicus.org/articles/14/687/2018/},\n\tdoi = {10.5194/cp-14-687-2018},\n\tabstract = {Abstract. Timescale uncertainties between paleoclimate reconstructions often inhibit studying the exact timing, spatial expression and driving mechanisms of climate variations. Detecting and aligning the globally common cosmogenic radionuclide production signal via a curve fitting method provides a tool for the quasi-continuous synchronization of paleoclimate archives. In this study, we apply this approach to synchronize 10Be records from varved sediments of Tiefer See and Lake Czechowskie covering the Maunder, Homeric and 5500 a BP grand solar minima with 14C production rates inferred from the IntCal13 calibration curve. Our analyses indicate best fits with 14C production rates when the 10Be records from Tiefer See were shifted for 8 (−12∕ + 4) (Maunder Minimum), 31 (−16∕ + 12) (Homeric Minimum) and 86 (−22∕ + 18) years (5500 a BP grand solar minimum) towards the past. The best fit between the Lake Czechowskie 10Be record for the 5500 a BP grand solar minimum and 14C production was obtained when the 10Be time series was shifted 29 (−8∕ + 7) years towards present. No significant fits were detected between the Lake Czechowskie 10Be records for the Maunder and Homeric minima and 14C production, likely due to intensified in-lake sediment resuspension since about 2800 a BP, transporting old 10Be to the coring location. Our results provide a proof of concept for facilitating 10Be in varved lake sediments as a novel synchronization tool required for investigating leads and lags of proxy responses to climate variability. However, they also point to some limitations of 10Be in these archives, mainly connected to in-lake sediment resuspension processes.},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2022-11-04},\n\tjournal = {Climate of the Past},\n\tauthor = {Czymzik, Markus and Muscheler, Raimund and Adolphi, Florian and Mekhaldi, Florian and Dräger, Nadine and Ott, Florian and Słowinski, Michał and Błaszkiewicz, Mirosław and Aldahan, Ala and Possnert, Göran and Brauer, Achim},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {687--696},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n De Roo, F.; and Mauder, M.\n\n\n \n \n \n \n \n The influence of idealized surface heterogeneity on virtual turbulent flux measurements.\n \n \n \n \n\n\n \n\n\n\n Atmospheric Chemistry and Physics, 18(7): 5059–5074. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{de_roo_influence_2018,\n\ttitle = {The influence of idealized surface heterogeneity on virtual turbulent flux measurements},\n\tvolume = {18},\n\tissn = {1680-7324},\n\turl = {https://acp.copernicus.org/articles/18/5059/2018/},\n\tdoi = {10.5194/acp-18-5059-2018},\n\tabstract = {Abstract. The imbalance of the surface energy budget in eddy-covariance measurements is still an unsolved problem. A possible cause is the presence of land surface heterogeneity, which affects the boundary-layer turbulence. To investigate the impact of surface variables on the partitioning of the energy budget of flux measurements in the surface layer under convective conditions, we set up a systematic parameter study by means of large-eddy simulation. For the study we use a virtual control volume approach, which allows the determination of advection by the mean flow, flux-divergence and storage terms of the energy budget at the virtual measurement site, in addition to the standard turbulent flux. We focus on the heterogeneity of the surface fluxes and keep the topography flat. The surface fluxes vary locally in intensity and these patches have different length scales. Intensity and length scales can vary for the two horizontal dimensions but follow an idealized chessboard pattern. Our main focus lies on surface heterogeneity of the kilometer scale, and one order of magnitude smaller. For these two length scales, we investigate the average response of the fluxes at a number of virtual towers, when varying the heterogeneity length within the length scale and when varying the contrast between the different patches. For each simulation, virtual measurement towers were positioned at functionally different positions (e.g., downdraft region, updraft region, at border between domains, etc.). As the storage term is always small, the non-closure is given by the sum of the advection by the mean flow and the flux-divergence. Remarkably, the missing flux can be described by either the advection by the mean flow or the flux-divergence separately, because the latter two have a high correlation with each other. For kilometer scale heterogeneity, we notice a clear dependence of the updrafts and downdrafts on the surface heterogeneity and likewise we also see a dependence of the energy partitioning on the tower location. For the hectometer scale, we do not notice such a clear dependence. Finally, we seek correlators for the energy balance ratio in the simulations. The correlation with the friction velocity is less pronounced than previously found, but this is likely due to our concentration on effectively strongly to freely convective conditions.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2022-11-04},\n\tjournal = {Atmospheric Chemistry and Physics},\n\tauthor = {De Roo, Frederik and Mauder, Matthias},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {5059--5074},\n}\n\n

\n

\n\n\n

\n Abstract. The imbalance of the surface energy budget in eddy-covariance measurements is still an unsolved problem. A possible cause is the presence of land surface heterogeneity, which affects the boundary-layer turbulence. To investigate the impact of surface variables on the partitioning of the energy budget of flux measurements in the surface layer under convective conditions, we set up a systematic parameter study by means of large-eddy simulation. For the study we use a virtual control volume approach, which allows the determination of advection by the mean flow, flux-divergence and storage terms of the energy budget at the virtual measurement site, in addition to the standard turbulent flux. We focus on the heterogeneity of the surface fluxes and keep the topography flat. The surface fluxes vary locally in intensity and these patches have different length scales. Intensity and length scales can vary for the two horizontal dimensions but follow an idealized chessboard pattern. Our main focus lies on surface heterogeneity of the kilometer scale, and one order of magnitude smaller. For these two length scales, we investigate the average response of the fluxes at a number of virtual towers, when varying the heterogeneity length within the length scale and when varying the contrast between the different patches. For each simulation, virtual measurement towers were positioned at functionally different positions (e.g., downdraft region, updraft region, at border between domains, etc.). As the storage term is always small, the non-closure is given by the sum of the advection by the mean flow and the flux-divergence. Remarkably, the missing flux can be described by either the advection by the mean flow or the flux-divergence separately, because the latter two have a high correlation with each other. For kilometer scale heterogeneity, we notice a clear dependence of the updrafts and downdrafts on the surface heterogeneity and likewise we also see a dependence of the energy partitioning on the tower location. For the hectometer scale, we do not notice such a clear dependence. Finally, we seek correlators for the energy balance ratio in the simulations. The correlation with the friction velocity is less pronounced than previously found, but this is likely due to our concentration on effectively strongly to freely convective conditions.\n

\n\n\n

\n \n\n \n \n De Roo, F.; Zhang, S.; Huq, S.; and Mauder, M.\n\n\n \n \n \n \n \n A semi-empirical model of the energy balance closure in the surface layer.\n \n \n \n \n\n\n \n\n\n\n PLOS ONE, 13(12): e0209022. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{de_roo_semi-empirical_2018,\n\ttitle = {A semi-empirical model of the energy balance closure in the surface layer},\n\tvolume = {13},\n\tissn = {1932-6203},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0209022},\n\tdoi = {10.1371/journal.pone.0209022},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2022-11-04},\n\tjournal = {PLOS ONE},\n\tauthor = {De Roo, Frederik and Zhang, Sha and Huq, Sadiq and Mauder, Matthias},\n\teditor = {Sihi, Debjani},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {e0209022},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Djukic, I.; Kepfer-Rojas, S.; Schmidt, I. K.; Larsen, K. S.; Beier, C.; Berg, B.; Verheyen, K.; Caliman, A.; Paquette, A.; Gutiérrez-Girón, A.; Humber, A.; Valdecantos, A.; Petraglia, A.; Alexander, H.; Augustaitis, A.; Saillard, A.; Fernández, A. C. R.; Sousa, A. I.; Lillebø, A. I.; da Rocha Gripp, A.; Francez, A.; Fischer, A.; Bohner, A.; Malyshev, A.; Andrić, A.; Smith, A.; Stanisci, A.; Seres, A.; Schmidt, A.; Avila, A.; Probst, A.; Ouin, A.; Khuroo, A. A.; Verstraeten, A.; Palabral-Aguilera, A. N.; Stefanski, A.; Gaxiola, A.; Muys, B.; Bosman, B.; Ahrends, B.; Parker, B.; Sattler, B.; Yang, B.; Juráni, B.; Erschbamer, B.; Ortiz, C. E. R.; Christiansen, C. T.; Carol Adair, E.; Meredieu, C.; Mony, C.; Nock, C. A.; Chen, C.; Wang, C.; Baum, C.; Rixen, C.; Delire, C.; Piscart, C.; Andrews, C.; Rebmann, C.; Branquinho, C.; Polyanskaya, D.; Delgado, D. F.; Wundram, D.; Radeideh, D.; Ordóñez-Regil, E.; Crawford, E.; Preda, E.; Tropina, E.; Groner, E.; Lucot, E.; Hornung, E.; Gacia, E.; Lévesque, E.; Benedito, E.; Davydov, E. A.; Ampoorter, E.; Bolzan, F. P.; Varela, F.; Kristöfel, F.; Maestre, F. T.; Maunoury-Danger, F.; Hofhansl, F.; Kitz, F.; Sutter, F.; Cuesta, F.; de Almeida Lobo, F.; de Souza, F. L.; Berninger, F.; Zehetner, F.; Wohlfahrt, G.; Vourlitis, G.; Carreño-Rocabado, G.; Arena, G.; Pinha, G. D.; González, G.; Canut, G.; Lee, H.; Verbeeck, H.; Auge, H.; Pauli, H.; Nacro, H. B.; Bahamonde, H. A.; Feldhaar, H.; Jäger, H.; Serrano, H. C.; Verheyden, H.; Bruelheide, H.; Meesenburg, H.; Jungkunst, H.; Jactel, H.; Shibata, H.; Kurokawa, H.; Rosas, H. L.; Rojas Villalobos, H. L.; Yesilonis, I.; Melece, I.; Van Halder, I.; Quirós, I. G.; Makelele, I.; Senou, I.; Fekete, I.; Mihal, I.; Ostonen, I.; Borovská, J.; Roales, J.; Shoqeir, J.; Lata, J.; Theurillat, J.; Probst, J.; Zimmerman, J.; Vijayanathan, J.; Tang, J.; Thompson, J.; Doležal, J.; Sanchez-Cabeza, J.; Merlet, J.; Henschel, J.; Neirynck, J.; Knops, J.; Loehr, J.; von Oppen, J.; Þorláksdóttir, J. S.; Löffler, J.; Cardoso-Mohedano, J.; Benito-Alonso, J.; Torezan, J. M.; Morina, J. C.; Jiménez, J. J.; Quinde, J. D.; Alatalo, J.; Seeber, J.; Stadler, J.; Kriiska, K.; Coulibaly, K.; Fukuzawa, K.; Szlavecz, K.; Gerhátová, K.; Lajtha, K.; Käppeler, K.; Jennings, K. A.; Tielbörger, K.; Hoshizaki, K.; Green, K.; Yé, L.; Pazianoto, L. H. R.; Dienstbach, L.; Williams, L.; Yahdjian, L.; Brigham, L. M.; van den Brink, L.; Rustad, L.; Zhang, L.; Morillas, L.; Xiankai, L.; Carneiro, L. S.; Di Martino, L.; Villar, L.; Bader, M. Y.; Morley, M.; Lebouvier, M.; Tomaselli, M.; Sternberg, M.; Schaub, M.; Santos-Reis, M.; Glushkova, M.; Torres, M. G. A.; Giroux, M.; de Graaff, M.; Pons, M.; Bauters, M.; Mazón, M.; Frenzel, M.; Didion, M.; Wagner, M.; Hamid, M.; Lopes, M. L.; Apple, M.; Schädler, M.; Weih, M.; Gualmini, M.; Vadeboncoeur, M. A.; Bierbaumer, M.; Danger, M.; Liddell, M.; Mirtl, M.; Scherer-Lorenzen, M.; Růžek, M.; Carbognani, M.; Di Musciano, M.; Matsushita, M.; Zhiyanski, M.; Pușcaș, M.; Barna, M.; Ataka, M.; Jiangming, M.; Alsafran, M.; Carnol, M.; Barsoum, N.; Tokuchi, N.; Eisenhauer, N.; Lecomte, N.; Filippova, N.; Hölzel, N.; Ferlian, O.; Romero, O.; Pinto, O. B.; Peri, P.; Weber, P.; Vittoz, P.; Turtureanu, P. D.; Fleischer, P.; Macreadie, P.; Haase, P.; Reich, P.; Petřík, P.; Choler, P.; Marmonier, P.; Muriel, P.; Ponette, Q.; Guariento, R. D.; Canessa, R.; Kiese, R.; Hewitt, R.; Rønn, R.; Adrian, R.; Kanka, R.; Weigel, R.; Gatti, R. C.; Martins, R. L.; Georges, R.; Meneses, R. I.; Gavilán, R. G.; Dasgupta, S.; Wittlinger, S.; Puijalon, S.; Freda, S.; Suzuki, S.; Charles, S.; Gogo, S.; Drollinger, S.; Mereu, S.; Wipf, S.; Trevathan-Tackett, S.; Löfgren, S.; Stoll, S.; Trogisch, S.; Hoeber, S.; Seitz, S.; Glatzel, S.; Milton, S. J.; Dousset, S.; Mori, T.; Sato, T.; Ise, T.; Hishi, T.; Kenta, T.; Nakaji, T.; Michelan, T. S.; Camboulive, T.; Mozdzer, T. J.; Scholten, T.; Spiegelberger, T.; Zechmeister, T.; Kleinebecker, T.; Hiura, T.; Enoki, T.; Ursu, T.; di Cella, U. M.; Hamer, U.; Klaus, V. H.; Rêgo, V. M.; Di Cecco, V.; Busch, V.; Fontana, V.; Piscová, V.; Carbonell, V.; Ochoa, V.; Bretagnolle, V.; Maire, V.; Farjalla, V.; Zhou, W.; Luo, W.; McDowell, W. H.; Hu, Y.; Utsumi, Y.; Kominami, Y.; Zaika, Y.; Rozhkov, Y.; Kotroczó, Z.; and Tóth, Z.\n\n\n \n \n \n \n \n Early stage litter decomposition across biomes.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 628-629: 1369–1394. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Early$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{djukic_early_2018,\n\ttitle = {Early stage litter decomposition across biomes},\n\tvolume = {628-629},\n\tissn = {00489697},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969718300123},\n\tdoi = {10.1016/j.scitotenv.2018.01.012},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Djukic, Ika and Kepfer-Rojas, Sebastian and Schmidt, Inger Kappel and Larsen, Klaus Steenberg and Beier, Claus and Berg, Björn and Verheyen, Kris and Caliman, Adriano and Paquette, Alain and Gutiérrez-Girón, Alba and Humber, Alberto and Valdecantos, Alejandro and Petraglia, Alessandro and Alexander, Heather and Augustaitis, Algirdas and Saillard, Amélie and Fernández, Ana Carolina Ruiz and Sousa, Ana I. and Lillebø, Ana I. and da Rocha Gripp, Anderson and Francez, André-Jean and Fischer, Andrea and Bohner, Andreas and Malyshev, Andrey and Andrić, Andrijana and Smith, Andy and Stanisci, Angela and Seres, Anikó and Schmidt, Anja and Avila, Anna and Probst, Anne and Ouin, Annie and Khuroo, Anzar A. and Verstraeten, Arne and Palabral-Aguilera, Arely N. and Stefanski, Artur and Gaxiola, Aurora and Muys, Bart and Bosman, Bernard and Ahrends, Bernd and Parker, Bill and Sattler, Birgit and Yang, Bo and Juráni, Bohdan and Erschbamer, Brigitta and Ortiz, Carmen Eugenia Rodriguez and Christiansen, Casper T. and Carol Adair, E. and Meredieu, Céline and Mony, Cendrine and Nock, Charles A. and Chen, Chi-Ling and Wang, Chiao-Ping and Baum, Christel and Rixen, Christian and Delire, Christine and Piscart, Christophe and Andrews, Christopher and Rebmann, Corinna and Branquinho, Cristina and Polyanskaya, Dana and Delgado, David Fuentes and Wundram, Dirk and Radeideh, Diyaa and Ordóñez-Regil, Eduardo and Crawford, Edward and Preda, Elena and Tropina, Elena and Groner, Elli and Lucot, Eric and Hornung, Erzsébet and Gacia, Esperança and Lévesque, Esther and Benedito, Evanilde and Davydov, Evgeny A. and Ampoorter, Evy and Bolzan, Fabio Padilha and Varela, Felipe and Kristöfel, Ferdinand and Maestre, Fernando T. and Maunoury-Danger, Florence and Hofhansl, Florian and Kitz, Florian and Sutter, Flurin and Cuesta, Francisco and de Almeida Lobo, Francisco and de Souza, Franco Leandro and Berninger, Frank and Zehetner, Franz and Wohlfahrt, Georg and Vourlitis, George and Carreño-Rocabado, Geovana and Arena, Gina and Pinha, Gisele Daiane and González, Grizelle and Canut, Guylaine and Lee, Hanna and Verbeeck, Hans and Auge, Harald and Pauli, Harald and Nacro, Hassan Bismarck and Bahamonde, Héctor A. and Feldhaar, Heike and Jäger, Heinke and Serrano, Helena C. and Verheyden, Hélène and Bruelheide, Helge and Meesenburg, Henning and Jungkunst, Hermann and Jactel, Hervé and Shibata, Hideaki and Kurokawa, Hiroko and Rosas, Hugo López and Rojas Villalobos, Hugo L. and Yesilonis, Ian and Melece, Inara and Van Halder, Inge and Quirós, Inmaculada García and Makelele, Isaac and Senou, Issaka and Fekete, István and Mihal, Ivan and Ostonen, Ivika and Borovská, Jana and Roales, Javier and Shoqeir, Jawad and Lata, Jean-Christophe and Theurillat, Jean-Paul and Probst, Jean-Luc and Zimmerman, Jess and Vijayanathan, Jeyanny and Tang, Jianwu and Thompson, Jill and Doležal, Jiří and Sanchez-Cabeza, Joan-Albert and Merlet, Joël and Henschel, Joh and Neirynck, Johan and Knops, Johannes and Loehr, John and von Oppen, Jonathan and Þorláksdóttir, Jónína Sigríður and Löffler, Jörg and Cardoso-Mohedano, José-Gilberto and Benito-Alonso, José-Luis and Torezan, Jose Marcelo and Morina, Joseph C. and Jiménez, Juan J. and Quinde, Juan Dario and Alatalo, Juha and Seeber, Julia and Stadler, Jutta and Kriiska, Kaie and Coulibaly, Kalifa and Fukuzawa, Karibu and Szlavecz, Katalin and Gerhátová, Katarína and Lajtha, Kate and Käppeler, Kathrin and Jennings, Katie A. and Tielbörger, Katja and Hoshizaki, Kazuhiko and Green, Ken and Yé, Lambiénou and Pazianoto, Laryssa Helena Ribeiro and Dienstbach, Laura and Williams, Laura and Yahdjian, Laura and Brigham, Laurel M. and van den Brink, Liesbeth and Rustad, Lindsey and Zhang, Lipeng and Morillas, Lourdes and Xiankai, Lu and Carneiro, Luciana Silva and Di Martino, Luciano and Villar, Luis and Bader, Maaike Y. and Morley, Madison and Lebouvier, Marc and Tomaselli, Marcello and Sternberg, Marcelo and Schaub, Marcus and Santos-Reis, Margarida and Glushkova, Maria and Torres, María Guadalupe Almazán and Giroux, Marie-Andrée and de Graaff, Marie-Anne and Pons, Marie-Noëlle and Bauters, Marijn and Mazón, Marina and Frenzel, Mark and Didion, Markus and Wagner, Markus and Hamid, Maroof and Lopes, Marta L. and Apple, Martha and Schädler, Martin and Weih, Martin and Gualmini, Matteo and Vadeboncoeur, Matthew A. and Bierbaumer, Michael and Danger, Michael and Liddell, Michael and Mirtl, Michael and Scherer-Lorenzen, Michael and Růžek, Michal and Carbognani, Michele and Di Musciano, Michele and Matsushita, Michinari and Zhiyanski, Miglena and Pușcaș, Mihai and Barna, Milan and Ataka, Mioko and Jiangming, Mo and Alsafran, Mohammed and Carnol, Monique and Barsoum, Nadia and Tokuchi, Naoko and Eisenhauer, Nico and Lecomte, Nicolas and Filippova, Nina and Hölzel, Norbert and Ferlian, Olga and Romero, Oscar and Pinto, Osvaldo B. and Peri, Pablo and Weber, Paige and Vittoz, Pascal and Turtureanu, Pavel Dan and Fleischer, Peter and Macreadie, Peter and Haase, Peter and Reich, Peter and Petřík, Petr and Choler, Philippe and Marmonier, Pierre and Muriel, Priscilla and Ponette, Quentin and Guariento, Rafael Dettogni and Canessa, Rafaella and Kiese, Ralf and Hewitt, Rebecca and Rønn, Regin and Adrian, Rita and Kanka, Róbert and Weigel, Robert and Gatti, Roberto Cazzolla and Martins, Rodrigo Lemes and Georges, Romain and Meneses, Rosa Isela and Gavilán, Rosario G. and Dasgupta, Sabyasachi and Wittlinger, Sally and Puijalon, Sara and Freda, Sarah and Suzuki, Satoshi and Charles, Sean and Gogo, Sébastien and Drollinger, Simon and Mereu, Simone and Wipf, Sonja and Trevathan-Tackett, Stacey and Löfgren, Stefan and Stoll, Stefan and Trogisch, Stefan and Hoeber, Stefanie and Seitz, Steffen and Glatzel, Stephan and Milton, Sue J. and Dousset, Sylvie and Mori, Taiki and Sato, Takanori and Ise, Takeshi and Hishi, Takuo and Kenta, Tanaka and Nakaji, Tatsuro and Michelan, Thaisa Sala and Camboulive, Thierry and Mozdzer, Thomas J. and Scholten, Thomas and Spiegelberger, Thomas and Zechmeister, Thomas and Kleinebecker, Till and Hiura, Tsutom and Enoki, Tsutomu and Ursu, Tudor-Mihai and di Cella, Umberto Morra and Hamer, Ute and Klaus, Valentin H. and Rêgo, Vanessa Mendes and Di Cecco, Valter and Busch, Verena and Fontana, Veronika and Piscová, Veronika and Carbonell, Victoria and Ochoa, Victoria and Bretagnolle, Vincent and Maire, Vincent and Farjalla, Vinicius and Zhou, Wenjun and Luo, Wentao and McDowell, William H. and Hu, Yalin and Utsumi, Yasuhiro and Kominami, Yuji and Zaika, Yulia and Rozhkov, Yury and Kotroczó, Zsolt and Tóth, Zsolt},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {1369--1394},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Dupas, R.; Tittel, J.; Jordan, P.; Musolff, A.; and Rode, M.\n\n\n \n \n \n \n \n Non-domestic phosphorus release in rivers during low-flow: Mechanisms and implications for sources identification.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 560: 141–149. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Non-domestic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{dupas_non-domestic_2018,\n\ttitle = {Non-domestic phosphorus release in rivers during low-flow: {Mechanisms} and implications for sources identification},\n\tvolume = {560},\n\tissn = {00221694},\n\tshorttitle = {Non-domestic phosphorus release in rivers during low-flow},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169418301896},\n\tdoi = {10.1016/j.jhydrol.2018.03.023},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Dupas, Rémi and Tittel, Jörg and Jordan, Phil and Musolff, Andreas and Rode, Michael},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {141--149},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Dörnhöfer, K.; Scholze, J.; Stelzer, K.; and Oppelt, N.\n\n\n \n \n \n \n \n Water Colour Analysis of Lake Kummerow Using Time Series of Remote Sensing and In Situ Data.\n \n \n \n \n\n\n \n\n\n\n PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 86(2): 103–120. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Water$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{dornhofer_water_2018,\n\ttitle = {Water {Colour} {Analysis} of {Lake} {Kummerow} {Using} {Time} {Series} of {Remote} {Sensing} and {In} {Situ} {Data}},\n\tvolume = {86},\n\tissn = {2512-2789, 2512-2819},\n\turl = {http://link.springer.com/10.1007/s41064-018-0046-3},\n\tdoi = {10.1007/s41064-018-0046-3},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-04},\n\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\n\tauthor = {Dörnhöfer, K. and Scholze, J. and Stelzer, K. and Oppelt, N.},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {103--120},\n}\n\n

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\n \n\n \n \n Ebrahimi-Khusfi, M.; Alavipanah, S. K.; Hamzeh, S.; Amiraslani, F.; Neysani Samany, N.; and Wigneron, J.\n\n\n \n \n \n \n \n Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC.\n \n \n \n \n\n\n \n\n\n\n International Journal of Applied Earth Observation and Geoinformation, 67: 148–160. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Comparison$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ebrahimi-khusfi_comparison_2018,\n\ttitle = {Comparison of soil moisture retrieval algorithms based on the synergy between {SMAP} and {SMOS}-{IC}},\n\tvolume = {67},\n\tissn = {15698432},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0303243417302945},\n\tdoi = {10.1016/j.jag.2017.12.005},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {International Journal of Applied Earth Observation and Geoinformation},\n\tauthor = {Ebrahimi-Khusfi, Mohsen and Alavipanah, Seyed Kazem and Hamzeh, Saeid and Amiraslani, Farshad and Neysani Samany, Najmeh and Wigneron, Jean-Pierre},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {148--160},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Ehrhardt, S.; Kumar, R.; Fleckenstein, J. H.; Attinger, S.; and Musolff, A.\n\n\n \n \n \n \n \n Decadal trajectories of nitrate input and output in three nested catchments along a land use gradient.\n \n \n \n \n\n\n \n\n\n\n Technical Report Catchment hydrology/Theory development, October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Decadal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@techreport{ehrhardt_decadal_2018,\n\ttype = {preprint},\n\ttitle = {Decadal trajectories of nitrate input and output in three nested catchments along a land use gradient},\n\turl = {https://hess.copernicus.org/preprints/hess-2018-475/hess-2018-475.pdf},\n\tabstract = {Abstract. Increased anthropogenic inputs of nitrogen (N) to the biosphere during the last decades have resulted in increased groundwater and surface water concentrations of N (primarily as nitrate) posing a global problem. Although measures have been implemented to reduce N-inputs especially from agricultural sources, they have not always led to decreasing riverine nitrate concentrations and loads. The limited response to the measures can either be caused by the accumulation of slowly mineralized organic N in the soils acting as a biogeochemical legacy or by long travel times (TTs) of inorganic N to the streams forming a hydrological legacy. Both types of legacy are hard to distinguish from the TTs and N budgets alone. Here we jointly analyze atmospheric and agricultural N inputs with long-term observations of nitrate concentrations and discharge in a mesoscale catchment in Central Germany. For three nested sub-catchments with increasing agricultural land use, we assess the catchment scale N budget, the effective TT of N. In combination with long-term trajectories of C-Q relationships we finally evaluate the potential for and the characteristics of an N-legacy. We show that in the 42-year-long observation period, the catchment received an N-input of 42 758 t, of which 97 \\% derived from agricultural sources. The riverine N-export sums up to 6 592 t indicating that the catchment retained 85 \\% of the N-input. Removal of N by denitrification could not fully explain this imbalance. Log-normal travel time distributions (TTD) for N that link the input history to the riverine export differed seasonally, with modes spanning 8–17 years. Under low-flow conditions, TTs were found to be systematically longer than during high discharges. Systematic shifts in the C-Q relationships could be attributed to significant changes in N-inputs resulting from agricultural intensification and the break-down of the East German agriculture after 1989 and to the longer travel times of nitrate during low flows compared to high flows. A chemostatic export regime of nitrate was only found after several years of stabilized N-inputs. We explain these observations by the vertical migration of the N-input and the seasonally changing contribution of subsurface flow paths with differing ages and thus differing N-loads. The changes in C-Q relationships suggest a dominance of hydrological N-legacy rather than a biogeochemical N-fixation in the soils, which should result in a stronger and even increasing dampening of riverine N-concentrations after sustained high N-inputs. Despite the strong N-legacy, a chemostatic nitrate export regime is not necessarily a persistent endpoint of intense agricultural land use, but rather depends on a steady replenishment of the mass of N propagating through the catchments subsurface. The input-output imbalance, the long time-lags and the lack of significant denitrification in the catchment let us conclude that catchment management needs to address both, a longer-term reduction of N-inputs and shorter-term mitigation of today’s high N-loads.},\n\turldate = {2022-11-17},\n\tinstitution = {Catchment hydrology/Theory development},\n\tauthor = {Ehrhardt, Sophie and Kumar, Rohini and Fleckenstein, Jan H. and Attinger, Sabine and Musolff, Andreas},\n\tmonth = oct,\n\tyear = {2018},\n\tdoi = {10.5194/hess-2018-475},\n}\n\n

\n

\n\n\n

\n Abstract. Increased anthropogenic inputs of nitrogen (N) to the biosphere during the last decades have resulted in increased groundwater and surface water concentrations of N (primarily as nitrate) posing a global problem. Although measures have been implemented to reduce N-inputs especially from agricultural sources, they have not always led to decreasing riverine nitrate concentrations and loads. The limited response to the measures can either be caused by the accumulation of slowly mineralized organic N in the soils acting as a biogeochemical legacy or by long travel times (TTs) of inorganic N to the streams forming a hydrological legacy. Both types of legacy are hard to distinguish from the TTs and N budgets alone. Here we jointly analyze atmospheric and agricultural N inputs with long-term observations of nitrate concentrations and discharge in a mesoscale catchment in Central Germany. For three nested sub-catchments with increasing agricultural land use, we assess the catchment scale N budget, the effective TT of N. In combination with long-term trajectories of C-Q relationships we finally evaluate the potential for and the characteristics of an N-legacy. We show that in the 42-year-long observation period, the catchment received an N-input of 42 758 t, of which 97 % derived from agricultural sources. The riverine N-export sums up to 6 592 t indicating that the catchment retained 85 % of the N-input. Removal of N by denitrification could not fully explain this imbalance. Log-normal travel time distributions (TTD) for N that link the input history to the riverine export differed seasonally, with modes spanning 8–17 years. Under low-flow conditions, TTs were found to be systematically longer than during high discharges. Systematic shifts in the C-Q relationships could be attributed to significant changes in N-inputs resulting from agricultural intensification and the break-down of the East German agriculture after 1989 and to the longer travel times of nitrate during low flows compared to high flows. A chemostatic export regime of nitrate was only found after several years of stabilized N-inputs. We explain these observations by the vertical migration of the N-input and the seasonally changing contribution of subsurface flow paths with differing ages and thus differing N-loads. The changes in C-Q relationships suggest a dominance of hydrological N-legacy rather than a biogeochemical N-fixation in the soils, which should result in a stronger and even increasing dampening of riverine N-concentrations after sustained high N-inputs. Despite the strong N-legacy, a chemostatic nitrate export regime is not necessarily a persistent endpoint of intense agricultural land use, but rather depends on a steady replenishment of the mass of N propagating through the catchments subsurface. The input-output imbalance, the long time-lags and the lack of significant denitrification in the catchment let us conclude that catchment management needs to address both, a longer-term reduction of N-inputs and shorter-term mitigation of today’s high N-loads.\n

\n\n\n

\n \n\n \n \n Emeis, S.; Kalthoff, N.; Adler, B.; Pardyjak, E.; Paci, A.; and Junkermann, W.\n\n\n \n \n \n \n \n High-Resolution Observations of Transport and Exchange Processes in Mountainous Terrain.\n \n \n \n \n\n\n \n\n\n\n Atmosphere, 9(12): 457. November 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"High-Resolution$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{emeis_high-resolution_2018,\n\ttitle = {High-{Resolution} {Observations} of {Transport} and {Exchange} {Processes} in {Mountainous} {Terrain}},\n\tvolume = {9},\n\tissn = {2073-4433},\n\turl = {http://www.mdpi.com/2073-4433/9/12/457},\n\tdoi = {10.3390/atmos9120457},\n\tabstract = {Mountainous areas require appropriate measurement strategies to cover the full spectrum of details concerning the energy exchange at the Earth’s surface and to capture the spatiotemporal distribution of atmospheric dynamic and thermodynamic fields over them. This includes the range from turbulence to mesoscale processes and its interaction. The surface energy balance needs appropriate measurement strategies as well. In this paper, we present an overview of important experiments performed over mountainous terrain and summarize the available techniques for flow and energy measurements in complex terrain. The description includes ground-based and airborne in situ observations as well as ground-based and airborne remote sensing (passive and active) observations. Emphasis is placed on systems which retrieve spatiotemporal information on mesoscale and smaller scales, fitting mountainous terrain research needs. Finally, we conclude with a short list summarizing challenges and gaps one faces when dealing with measurements over complex terrain.},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2022-11-04},\n\tjournal = {Atmosphere},\n\tauthor = {Emeis, Stefan and Kalthoff, Norbert and Adler, Bianca and Pardyjak, Eric and Paci, Alexandre and Junkermann, Wolfgang},\n\tmonth = nov,\n\tyear = {2018},\n\tpages = {457},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Fersch, B.; Jagdhuber, T.; Schrön, M.; Völksch, I.; and Jäger, M.\n\n\n \n \n \n \n \n Synergies for Soil Moisture Retrieval Across Scales From Airborne Polarimetric SAR, Cosmic Ray Neutron Roving, and an In Situ Sensor Network.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 54(11): 9364–9383. November 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Synergies$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{fersch_synergies_2018,\n\ttitle = {Synergies for {Soil} {Moisture} {Retrieval} {Across} {Scales} {From} {Airborne} {Polarimetric} {SAR}, {Cosmic} {Ray} {Neutron} {Roving}, and an {In} {Situ} {Sensor} {Network}},\n\tvolume = {54},\n\tissn = {0043-1397, 1944-7973},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2018WR023337},\n\tdoi = {10.1029/2018WR023337},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2022-11-04},\n\tjournal = {Water Resources Research},\n\tauthor = {Fersch, B. and Jagdhuber, T. and Schrön, M. and Völksch, I. and Jäger, M.},\n\tmonth = nov,\n\tyear = {2018},\n\tpages = {9364--9383},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Fiener, P.; Wilken, F.; Aldana-Jague, E.; Deumlich, D.; Gómez, J.; Guzmán, G.; Hardy, R.; Quinton, J.; Sommer, M.; Van Oost, K.; and Wexler, R.\n\n\n \n \n \n \n \n Uncertainties in assessing tillage erosion – How appropriate are our measuring techniques?.\n \n \n \n \n\n\n \n\n\n\n Geomorphology, 304: 214–225. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Uncertainties$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{fiener_uncertainties_2018,\n\ttitle = {Uncertainties in assessing tillage erosion – {How} appropriate are our measuring techniques?},\n\tvolume = {304},\n\tissn = {0169555X},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0169555X17305391},\n\tdoi = {10.1016/j.geomorph.2017.12.031},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Geomorphology},\n\tauthor = {Fiener, P. and Wilken, F. and Aldana-Jague, E. and Deumlich, D. and Gómez, J.A. and Guzmán, G. and Hardy, R.A. and Quinton, J.N. and Sommer, M. and Van Oost, K. and Wexler, R.},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {214--225},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Filipović, V.; Gerke, H. H.; Filipović, L.; and Sommer, M.\n\n\n \n \n \n \n \n Quantifying Subsurface Lateral Flow along Sloping Horizon Boundaries in Soil Profiles of a Hummocky Ground Moraine.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 170106. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Quantifying$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{filipovic_quantifying_2018,\n\ttitle = {Quantifying {Subsurface} {Lateral} {Flow} along {Sloping} {Horizon} {Boundaries} in {Soil} {Profiles} of a {Hummocky} {Ground} {Moraine}},\n\tvolume = {17},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2017.05.0106},\n\tdoi = {10.2136/vzj2017.05.0106},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Filipović, Vilim and Gerke, Horst H. and Filipović, Lana and Sommer, Michael},\n\tyear = {2018},\n\tpages = {170106},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Franz, D.; Acosta, M.; Altimir, N.; Arriga, N.; Arrouays, D.; Aubinet, M.; Aurela, M.; Ayres, E.; López-Ballesteros, A.; Barbaste, M.; Berveiller, D.; Biraud, S.; Boukir, H.; Brown, T.; Brümmer, C.; Buchmann, N.; Burba, G.; Carrara, A.; Cescatti, A.; Ceschia, E.; Clement, R.; Cremonese, E.; Crill, P.; Darenova, E.; Dengel, S.; D’Odorico, P.; Filippa, G.; Fleck, S.; Fratini, G.; Fuß, R.; Gielen, B.; Gogo, S.; Grace, J.; Graf, A.; Grelle, A.; Gross, P.; Grünwald, T.; Haapanala, S.; Hehn, M.; Heinesch, B.; Heiskanen, J.; Herbst, M.; Herschlein, C.; Hörtnagl, L.; Hufkens, K.; Ibrom, A.; Jolivet, C.; Joly, L.; Jones, M.; Kiese, R.; Klemedtsson, L.; Kljun, N.; Klumpp, K.; Kolari, P.; Kolle, O.; Kowalski, A.; Kutsch, W.; Laurila, T.; de Ligne, A.; Linder, S.; Lindroth, A.; Lohila, A.; Longdoz, B.; Mammarella, I.; Manise, T.; Jiménez, S. M.; Matteucci, G.; Mauder, M.; Meier, P.; Merbold, L.; Mereu, S.; Metzger, S.; Migliavacca, M.; Mölder, M.; Montagnani, L.; Moureaux, C.; Nelson, D.; Nemitz, E.; Nicolini, G.; Nilsson, M. B.; de Beeck, M. O.; Osborne, B.; Löfvenius, M. O.; Pavelka, M.; Peichl, M.; Peltola, O.; Pihlatie, M.; Pitacco, A.; Pokorný, R.; Pumpanen, J.; Ratié, C.; Rebmann, C.; Roland, M.; Sabbatini, S.; Saby, N. P.; Saunders, M.; Schmid, H. P.; Schrumpf, M.; Sedlák, P.; Ortiz, P. S.; Siebicke, L.; Šigut, L.; Silvennoinen, H.; Simioni, G.; Skiba, U.; Sonnentag, O.; Soudani, K.; Soulé, P.; Steinbrecher, R.; Tallec, T.; Thimonier, A.; Tuittila, E.; Tuovinen, J.; Vestin, P.; Vincent, G.; Vincke, C.; Vitale, D.; Waldner, P.; Weslien, P.; Wingate, L.; Wohlfahrt, G.; Zahniser, M.; and Vesala, T.\n\n\n \n \n \n \n \n Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: a review.\n \n \n \n \n\n\n \n\n\n\n International Agrophysics, 32(4): 439–455. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{franz_towards_2018,\n\ttitle = {Towards long-term standardised carbon and greenhouse gas observations for monitoring {Europe}’s terrestrial ecosystems: a review},\n\tvolume = {32},\n\tissn = {2300-8725},\n\tshorttitle = {Towards long-term standardised carbon and greenhouse gas observations for monitoring {Europe}’s terrestrial ecosystems},\n\turl = {http://archive.sciendo.com/INTAG/intag.2017.32.issue-4/intag-2017-0039/intag-2017-0039.pdf},\n\tdoi = {10.1515/intag-2017-0039},\n\tabstract = {Abstract \n             \n              Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO \n              2 \n              , CH \n              4 \n              , N \n              2 \n              O, H \n              2 \n              O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.},\n\tnumber = {4},\n\turldate = {2022-11-04},\n\tjournal = {International Agrophysics},\n\tauthor = {Franz, Daniela and Acosta, Manuel and Altimir, Núria and Arriga, Nicola and Arrouays, Dominique and Aubinet, Marc and Aurela, Mika and Ayres, Edward and López-Ballesteros, Ana and Barbaste, Mireille and Berveiller, Daniel and Biraud, Sébastien and Boukir, Hakima and Brown, Timothy and Brümmer, Christian and Buchmann, Nina and Burba, George and Carrara, Arnaud and Cescatti, Allessandro and Ceschia, Eric and Clement, Robert and Cremonese, Edoardo and Crill, Patrick and Darenova, Eva and Dengel, Sigrid and D’Odorico, Petra and Filippa, Gianluca and Fleck, Stefan and Fratini, Gerardo and Fuß, Roland and Gielen, Bert and Gogo, Sébastien and Grace, John and Graf, Alexander and Grelle, Achim and Gross, Patrick and Grünwald, Thomas and Haapanala, Sami and Hehn, Markus and Heinesch, Bernard and Heiskanen, Jouni and Herbst, Mathias and Herschlein, Christine and Hörtnagl, Lukas and Hufkens, Koen and Ibrom, Andreas and Jolivet, Claudy and Joly, Lilian and Jones, Michael and Kiese, Ralf and Klemedtsson, Leif and Kljun, Natascha and Klumpp, Katja and Kolari, Pasi and Kolle, Olaf and Kowalski, Andrew and Kutsch, Werner and Laurila, Tuomas and de Ligne, Anne and Linder, Sune and Lindroth, Anders and Lohila, Annalea and Longdoz, Bernhard and Mammarella, Ivan and Manise, Tanguy and Jiménez, Sara Maraňón and Matteucci, Giorgio and Mauder, Matthias and Meier, Philip and Merbold, Lutz and Mereu, Simone and Metzger, Stefan and Migliavacca, Mirco and Mölder, Meelis and Montagnani, Leonardo and Moureaux, Christine and Nelson, David and Nemitz, Eiko and Nicolini, Giacomo and Nilsson, Mats B. and de Beeck, Maarten Op and Osborne, Bruce and Löfvenius, Mikaell Ottosson and Pavelka, Marian and Peichl, Matthias and Peltola, Olli and Pihlatie, Mari and Pitacco, Andrea and Pokorný, Radek and Pumpanen, Jukka and Ratié, Céline and Rebmann, Corinna and Roland, Marilyn and Sabbatini, Simone and Saby, Nicolas P.A. and Saunders, Matthew and Schmid, Hans Peter and Schrumpf, Marion and Sedlák, Pavel and Ortiz, Penelope Serrano and Siebicke, Lukas and Šigut, Ladislav and Silvennoinen, Hanna and Simioni, Guillaume and Skiba, Ute and Sonnentag, Oliver and Soudani, Kamel and Soulé, Patrice and Steinbrecher, Rainer and Tallec, Tiphaine and Thimonier, Anne and Tuittila, Eeva-Stiina and Tuovinen, Juha-Pekka and Vestin, Patrik and Vincent, Gaëlle and Vincke, Caroline and Vitale, Domenico and Waldner, Peter and Weslien, Per and Wingate, Lisa and Wohlfahrt, Georg and Zahniser, Mark and Vesala, Timo},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {439--455},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Frenck, G.; Leitinger, G.; Obojes, N.; Hofmann, M.; Newesely, C.; Deutschmann, M.; Tappeiner, U.; and Tasser, E.\n\n\n \n \n \n \n \n Community-specific hydraulic conductance potential of soil water decomposed for two Alpine grasslands by small-scale lysimetry.\n \n \n \n \n\n\n \n\n\n\n Biogeosciences, 15(4): 1065–1078. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Community-specific$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{frenck_community-specific_2018,\n\ttitle = {Community-specific hydraulic conductance potential of soil water decomposed for two {Alpine} grasslands by small-scale lysimetry},\n\tvolume = {15},\n\tissn = {1726-4189},\n\turl = {https://bg.copernicus.org/articles/15/1065/2018/},\n\tdoi = {10.5194/bg-15-1065-2018},\n\tabstract = {Abstract. For central Europe in addition to rising temperatures an increasing\nvariability in precipitation is predicted. This will increase the probability\nof drought periods in the Alps, where water supply has been sufficient in\nmost areas so far. For Alpine grasslands, community-specific imprints on\ndrought responses are poorly analyzed so far due to the sufficient natural\nwater supply. In a replicated mesocosm experiment we compared\nevapotranspiration (ET) and biomass productivity of two differently\ndrought-adapted Alpine grassland communities during two artificial drought\nperiods divided by extreme precipitation events using high-precision small\nlysimeters. The drought-adapted vegetation type showed a high potential to\nutilize even scarce water resources. This is combined with a low potential to\ntranslate atmospheric deficits into higher water conductance and a lower\nbiomass production as those measured for the non-drought-adapted type. The\nnon-drought-adapted type, in contrast, showed high water conductance\npotential and a strong increase in ET rates when environmental conditions\nbecame less constraining. With high rates even at dry conditions, this\ncommunity appears not to be optimized to save water and might experience\ndrought effects earlier and probably more strongly. As a result, the water\nuse efficiency of the drought-adapted plant community is with\n2.6 gDW kg−1 of water much higher than that of the\nnon-drought-adapted plant community (0.16 gDW kg−1). In\nsummary, the vegetation's reaction to two covarying gradients of potential\nevapotranspiration and soil water content revealed a clear difference in\nvegetation development and between water-saving and water-spending strategies\nregarding evapotranspiration.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2022-11-04},\n\tjournal = {Biogeosciences},\n\tauthor = {Frenck, Georg and Leitinger, Georg and Obojes, Nikolaus and Hofmann, Magdalena and Newesely, Christian and Deutschmann, Mario and Tappeiner, Ulrike and Tasser, Erich},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {1065--1078},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Georgi, C.; Spengler, D.; Itzerott, S.; and Kleinschmit, B.\n\n\n \n \n \n \n \n Automatic delineation algorithm for site-specific management zones based on satellite remote sensing data.\n \n \n \n \n\n\n \n\n\n\n Precision Agriculture, 19(4): 684–707. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Automatic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{georgi_automatic_2018,\n\ttitle = {Automatic delineation algorithm for site-specific management zones based on satellite remote sensing data},\n\tvolume = {19},\n\tissn = {1385-2256, 1573-1618},\n\turl = {http://link.springer.com/10.1007/s11119-017-9549-y},\n\tdoi = {10.1007/s11119-017-9549-y},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2022-11-16},\n\tjournal = {Precision Agriculture},\n\tauthor = {Georgi, Claudia and Spengler, Daniel and Itzerott, Sibylle and Kleinschmit, Birgit},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {684--707},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Gerstmann, H.; Gläßer, C.; Thürkow, D.; and Möller, M.\n\n\n \n \n \n \n \n Detection of Phenology-Defined Data Acquisition Time Frames For Crop Type Mapping.\n \n \n \n \n\n\n \n\n\n\n PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 86(1): 15–27. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Detection$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{gerstmann_detection_2018,\n\ttitle = {Detection of {Phenology}-{Defined} {Data} {Acquisition} {Time} {Frames} {For} {Crop} {Type} {Mapping}},\n\tvolume = {86},\n\tissn = {2512-2789, 2512-2819},\n\turl = {http://link.springer.com/10.1007/s41064-018-0043-6},\n\tdoi = {10.1007/s41064-018-0043-6},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\n\tauthor = {Gerstmann, Henning and Gläßer, Cornelia and Thürkow, Detlef and Möller, Markus},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {15--27},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Groh, J.; Slawitsch, V.; Herndl, M.; Graf, A.; Vereecken, H.; and Pütz, T.\n\n\n \n \n \n \n \n Determining dew and hoar frost formation for a low mountain range and alpine grassland site by weighable lysimeter.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 563: 372–381. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Determining$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{groh_determining_2018,\n\ttitle = {Determining dew and hoar frost formation for a low mountain range and alpine grassland site by weighable lysimeter},\n\tvolume = {563},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169418304153},\n\tdoi = {10.1016/j.jhydrol.2018.06.009},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Groh, Jannis and Slawitsch, Veronika and Herndl, Markus and Graf, Alexander and Vereecken, Harry and Pütz, Thomas},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {372--381},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Groh, J.; Stumpp, C.; Lücke, A.; Pütz, T.; Vanderborght, J.; and Vereecken, H.\n\n\n \n \n \n \n \n Inverse Estimation of Soil Hydraulic and Transport Parameters of Layered Soils from Water Stable Isotope and Lysimeter Data.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 170168. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Inverse$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{groh_inverse_2018,\n\ttitle = {Inverse {Estimation} of {Soil} {Hydraulic} and {Transport} {Parameters} of {Layered} {Soils} from {Water} {Stable} {Isotope} and {Lysimeter} {Data}},\n\tvolume = {17},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2017.09.0168},\n\tdoi = {10.2136/vzj2017.09.0168},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Groh, Jannis and Stumpp, Christine and Lücke, Andreas and Pütz, Thomas and Vanderborght, Jan and Vereecken, Harry},\n\tyear = {2018},\n\tpages = {170168},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Gueting, N.; Caers, J.; Comunian, A.; Vanderborght, J.; and Englert, A.\n\n\n \n \n \n \n \n Reconstruction of Three-Dimensional Aquifer Heterogeneity from Two-Dimensional Geophysical Data.\n \n \n \n \n\n\n \n\n\n\n Mathematical Geosciences, 50(1): 53–75. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Reconstruction$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{gueting_reconstruction_2018,\n\ttitle = {Reconstruction of {Three}-{Dimensional} {Aquifer} {Heterogeneity} from {Two}-{Dimensional} {Geophysical} {Data}},\n\tvolume = {50},\n\tissn = {1874-8961, 1874-8953},\n\turl = {http://link.springer.com/10.1007/s11004-017-9694-x},\n\tdoi = {10.1007/s11004-017-9694-x},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Mathematical Geosciences},\n\tauthor = {Gueting, Nils and Caers, Jef and Comunian, Alessandro and Vanderborght, Jan and Englert, Andreas},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {53--75},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Haase, P.; Tonkin, J. D.; Stoll, S.; Burkhard, B.; Frenzel, M.; Geijzendorffer, I. R.; Häuser, C.; Klotz, S.; Kühn, I.; McDowell, W. H.; Mirtl, M.; Müller, F.; Musche, M.; Penner, J.; Zacharias, S.; and Schmeller, D. S.\n\n\n \n \n \n \n \n The next generation of site-based long-term ecological monitoring: Linking essential biodiversity variables and ecosystem integrity.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 613-614: 1376–1384. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{haase_next_2018,\n\ttitle = {The next generation of site-based long-term ecological monitoring: {Linking} essential biodiversity variables and ecosystem integrity},\n\tvolume = {613-614},\n\tissn = {00489697},\n\tshorttitle = {The next generation of site-based long-term ecological monitoring},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969717321095},\n\tdoi = {10.1016/j.scitotenv.2017.08.111},\n\tlanguage = {en},\n\turldate = {2022-11-04},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Haase, Peter and Tonkin, Jonathan D. and Stoll, Stefan and Burkhard, Benjamin and Frenzel, Mark and Geijzendorffer, Ilse R. and Häuser, Christoph and Klotz, Stefan and Kühn, Ingolf and McDowell, William H. and Mirtl, Michael and Müller, Felix and Musche, Martin and Penner, Johannes and Zacharias, Steffen and Schmeller, Dirk S.},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {1376--1384},\n}\n\n

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\n \n\n \n \n Hassler, S. K.; Weiler, M.; and Blume, T.\n\n\n \n \n \n \n \n Tree-, stand- and site-specific controls on landscape-scale patterns of transpiration.\n \n \n \n \n\n\n \n\n\n\n Hydrology and Earth System Sciences, 22(1): 13–30. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Tree-,$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{hassler_tree-_2018,\n\ttitle = {Tree-, stand- and site-specific controls on landscape-scale patterns of transpiration},\n\tvolume = {22},\n\tissn = {1607-7938},\n\turl = {https://hess.copernicus.org/articles/22/13/2018/},\n\tdoi = {10.5194/hess-22-13-2018},\n\tabstract = {Abstract. Transpiration is a key process in the hydrological cycle,\nand a sound understanding and quantification of transpiration and its\nspatial variability is essential for management decisions as well as for\nimproving the parameterisation and evaluation of hydrological and\nsoil–vegetation–atmosphere transfer models. For individual trees,\ntranspiration is commonly estimated by measuring sap flow. Besides\nevaporative demand and water availability, tree-specific characteristics\nsuch as species, size or social status control sap flow amounts of\nindividual trees. Within forest stands, properties such as species\ncomposition, basal area or stand density additionally affect sap flow, for\nexample via competition mechanisms. Finally, sap flow patterns might also be\ninfluenced by landscape-scale characteristics such as geology and soils,\nslope position or aspect because they affect water and energy availability;\nhowever, little is known about the dynamic interplay of these controls. We studied the relative importance of various tree-, stand- and\nsite-specific characteristics with multiple linear regression models to\nexplain the variability of sap velocity measurements in 61 beech and oak\ntrees, located at 24 sites across a 290 km2 catchment in\nLuxembourg. For each of 132 consecutive days of the growing season of 2014\nwe modelled the daily sap velocity and derived sap flow patterns of these 61\ntrees, and we determined the importance of the different controls. Results indicate that a combination of mainly tree- and site-specific\nfactors controls sap velocity patterns in the landscape, namely tree\nspecies, tree diameter, geology and aspect. For sap flow we included only\nthe stand- and site-specific predictors in the models to ensure variable\nindependence. Of those, geology and aspect were most important. Compared to\nthese predictors, spatial variability of atmospheric demand and soil\nmoisture explains only a small fraction of the variability in the daily\ndatasets. However, the temporal dynamics of the explanatory power of the\ntree-specific characteristics, especially species, are correlated to the\ntemporal dynamics of potential evaporation. We conclude that transpiration\nestimates on the landscape scale would benefit from not only consideration of\nhydro-meteorological drivers, but also tree, stand and site characteristics\nin order to improve the spatial and temporal representation of transpiration\nfor hydrological and soil–vegetation–atmosphere transfer models.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Hydrology and Earth System Sciences},\n\tauthor = {Hassler, Sibylle Kathrin and Weiler, Markus and Blume, Theresa},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {13--30},\n}\n\n

\n

\n\n\n

\n Abstract. Transpiration is a key process in the hydrological cycle, and a sound understanding and quantification of transpiration and its spatial variability is essential for management decisions as well as for improving the parameterisation and evaluation of hydrological and soil–vegetation–atmosphere transfer models. For individual trees, transpiration is commonly estimated by measuring sap flow. Besides evaporative demand and water availability, tree-specific characteristics such as species, size or social status control sap flow amounts of individual trees. Within forest stands, properties such as species composition, basal area or stand density additionally affect sap flow, for example via competition mechanisms. Finally, sap flow patterns might also be influenced by landscape-scale characteristics such as geology and soils, slope position or aspect because they affect water and energy availability; however, little is known about the dynamic interplay of these controls. We studied the relative importance of various tree-, stand- and site-specific characteristics with multiple linear regression models to explain the variability of sap velocity measurements in 61 beech and oak trees, located at 24 sites across a 290 km2 catchment in Luxembourg. For each of 132 consecutive days of the growing season of 2014 we modelled the daily sap velocity and derived sap flow patterns of these 61 trees, and we determined the importance of the different controls. Results indicate that a combination of mainly tree- and site-specific factors controls sap velocity patterns in the landscape, namely tree species, tree diameter, geology and aspect. For sap flow we included only the stand- and site-specific predictors in the models to ensure variable independence. Of those, geology and aspect were most important. Compared to these predictors, spatial variability of atmospheric demand and soil moisture explains only a small fraction of the variability in the daily datasets. However, the temporal dynamics of the explanatory power of the tree-specific characteristics, especially species, are correlated to the temporal dynamics of potential evaporation. We conclude that transpiration estimates on the landscape scale would benefit from not only consideration of hydro-meteorological drivers, but also tree, stand and site characteristics in order to improve the spatial and temporal representation of transpiration for hydrological and soil–vegetation–atmosphere transfer models.\n

\n\n\n

\n \n\n \n \n Heinrich, I.; Balanzategui, D.; Bens, O.; Blasch, G.; Blume, T.; Böttcher, F.; Borg, E.; Brademann, B.; Brauer, A.; Conrad, C.; Dietze, E.; Dräger, N.; Fiener, P.; Gerke, H. H.; Güntner, A.; Heine, I.; Helle, G.; Herbrich, M.; Harfenmeister, K.; Heußner, K.; Hohmann, C.; Itzerott, S.; Jurasinski, G.; Kaiser, K.; Kappler, C.; Koebsch, F.; Liebner, S.; Lischeid, G.; Merz, B.; Missling, K. D.; Morgner, M.; Pinkerneil, S.; Plessen, B.; Raab, T.; Ruhtz, T.; Sachs, T.; Sommer, M.; Spengler, D.; Stender, V.; Stüve, P.; and Wilken, F.\n\n\n \n \n \n \n \n Interdisciplinary Geo-ecological Research across Time Scales in the Northeast German Lowland Observatory (TERENO-NE).\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 180116. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Interdisciplinary$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{heinrich_interdisciplinary_2018,\n\ttitle = {Interdisciplinary {Geo}-ecological {Research} across {Time} {Scales} in the {Northeast} {German} {Lowland} {Observatory} ({TERENO}-{NE})},\n\tvolume = {17},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2018.06.0116},\n\tdoi = {10.2136/vzj2018.06.0116},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-04},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Heinrich, Ingo and Balanzategui, Daniel and Bens, Oliver and Blasch, Gerald and Blume, Theresa and Böttcher, Falk and Borg, Erik and Brademann, Brian and Brauer, Achim and Conrad, Christopher and Dietze, Elisabeth and Dräger, Nadine and Fiener, Peter and Gerke, Horst H. and Güntner, Andreas and Heine, Iris and Helle, Gerhard and Herbrich, Marcus and Harfenmeister, Katharina and Heußner, Karl-Uwe and Hohmann, Christian and Itzerott, Sibylle and Jurasinski, Gerald and Kaiser, Knut and Kappler, Christoph and Koebsch, Franziska and Liebner, Susanne and Lischeid, Gunnar and Merz, Bruno and Missling, Klaus Dieter and Morgner, Markus and Pinkerneil, Sylvia and Plessen, Birgit and Raab, Thomas and Ruhtz, Thomas and Sachs, Torsten and Sommer, Michael and Spengler, Daniel and Stender, Vivien and Stüve, Peter and Wilken, Florian},\n\tyear = {2018},\n\tpages = {180116},\n}\n\n

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\n \n\n \n \n Herbrich, M.; Gerke, H. H.; and Sommer, M.\n\n\n \n \n \n \n \n Root development of winter wheat in erosion‐affected soils depending on the position in a hummocky ground moraine soil landscape.\n \n \n \n \n\n\n \n\n\n\n Journal of Plant Nutrition and Soil Science, 181(2): 147–157. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Root$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{herbrich_root_2018,\n\ttitle = {Root development of winter wheat in erosion‐affected soils depending on the position in a hummocky ground moraine soil landscape},\n\tvolume = {181},\n\tissn = {1436-8730, 1522-2624},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/jpln.201600536},\n\tdoi = {10.1002/jpln.201600536},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-04},\n\tjournal = {Journal of Plant Nutrition and Soil Science},\n\tauthor = {Herbrich, Marcus and Gerke, Horst H. and Sommer, Michael},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {147--157},\n}\n\n

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\n \n\n \n \n Heupel, K.; Spengler, D.; and Itzerott, S.\n\n\n \n \n \n \n \n A Progressive Crop-Type Classification Using Multitemporal Remote Sensing Data and Phenological Information.\n \n \n \n \n\n\n \n\n\n\n PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 86(2): 53–69. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{heupel_progressive_2018,\n\ttitle = {A {Progressive} {Crop}-{Type} {Classification} {Using} {Multitemporal} {Remote} {Sensing} {Data} and {Phenological} {Information}},\n\tvolume = {86},\n\tissn = {2512-2789, 2512-2819},\n\turl = {http://link.springer.com/10.1007/s41064-018-0050-7},\n\tdoi = {10.1007/s41064-018-0050-7},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-04},\n\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\n\tauthor = {Heupel, Katharina and Spengler, Daniel and Itzerott, Sibylle},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {53--69},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Holtgrave, A.; Förster, M.; Greifeneder, F.; Notarnicola, C.; and Kleinschmit, B.\n\n\n \n \n \n \n \n Estimation of Soil Moisture in Vegetation-Covered Floodplains with Sentinel-1 SAR Data Using Support Vector Regression.\n \n \n \n \n\n\n \n\n\n\n PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 86(2): 85–101. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Estimation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{holtgrave_estimation_2018,\n\ttitle = {Estimation of {Soil} {Moisture} in {Vegetation}-{Covered} {Floodplains} with {Sentinel}-1 {SAR} {Data} {Using} {Support} {Vector} {Regression}},\n\tvolume = {86},\n\tissn = {2512-2789, 2512-2819},\n\turl = {http://link.springer.com/10.1007/s41064-018-0045-4},\n\tdoi = {10.1007/s41064-018-0045-4},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-04},\n\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\n\tauthor = {Holtgrave, Ann-Kathrin and Förster, Michael and Greifeneder, Felix and Notarnicola, Claudia and Kleinschmit, Birgit},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {85--101},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Hörtnagl, L.; Barthel, M.; Buchmann, N.; Eugster, W.; Butterbach-Bahl, K.; Díaz-Pinés, E.; Zeeman, M.; Klumpp, K.; Kiese, R.; Bahn, M.; Hammerle, A.; Lu, H.; Ladreiter-Knauss, T.; Burri, S.; and Merbold, L.\n\n\n \n \n \n \n \n Greenhouse gas fluxes over managed grasslands in Central Europe.\n \n \n \n \n\n\n \n\n\n\n Global Change Biology, 24(5): 1843–1872. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Greenhouse$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{hortnagl_greenhouse_2018,\n\ttitle = {Greenhouse gas fluxes over managed grasslands in {Central} {Europe}},\n\tvolume = {24},\n\tissn = {13541013},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/gcb.14079},\n\tdoi = {10.1111/gcb.14079},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2022-11-04},\n\tjournal = {Global Change Biology},\n\tauthor = {Hörtnagl, Lukas and Barthel, Matti and Buchmann, Nina and Eugster, Werner and Butterbach-Bahl, Klaus and Díaz-Pinés, Eugenio and Zeeman, Matthias and Klumpp, Katja and Kiese, Ralf and Bahn, Michael and Hammerle, Albin and Lu, Haiyan and Ladreiter-Knauss, Thomas and Burri, Susanne and Merbold, Lutz},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {1843--1872},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Inostroza, P. A.; Vera-Escalona, I.; Wild, R.; Norf, H.; and Brauns, M.\n\n\n \n \n \n \n \n Tandem Action of Natural and Chemical Stressors in Stream Ecosystems: Insights from a Population Genetic Perspective.\n \n \n \n \n\n\n \n\n\n\n Environmental Science & Technology, 52(14): 7962–7971. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Tandem$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{inostroza_tandem_2018,\n\ttitle = {Tandem {Action} of {Natural} and {Chemical} {Stressors} in {Stream} {Ecosystems}: {Insights} from a {Population} {Genetic} {Perspective}},\n\tvolume = {52},\n\tissn = {0013-936X, 1520-5851},\n\tshorttitle = {Tandem {Action} of {Natural} and {Chemical} {Stressors} in {Stream} {Ecosystems}},\n\turl = {https://pubs.acs.org/doi/10.1021/acs.est.8b01259},\n\tdoi = {10.1021/acs.est.8b01259},\n\tlanguage = {en},\n\tnumber = {14},\n\turldate = {2022-11-04},\n\tjournal = {Environmental Science \\& Technology},\n\tauthor = {Inostroza, Pedro A. and Vera-Escalona, Iván and Wild, Romy and Norf, Helge and Brauns, Mario},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {7962--7971},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Jagdhuber, T.; Fersch, B.; Schron, M.; Jager, M.; Voormansik, K.; and Lopez-Martinez, C.\n\n\n \n \n \n \n \n Field-Scale Assessment of Multi-Sensor Soil Moisture Retrieval Under Grassland.\n \n \n \n \n\n\n \n\n\n\n In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, pages 6111–6114, Valencia, July 2018. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Field-Scale$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{jagdhuber_field-scale_2018,\n\taddress = {Valencia},\n\ttitle = {Field-{Scale} {Assessment} of {Multi}-{Sensor} {Soil} {Moisture} {Retrieval} {Under} {Grassland}},\n\tisbn = {9781538671504},\n\turl = {https://ieeexplore.ieee.org/document/8517560/},\n\tdoi = {10.1109/IGARSS.2018.8517560},\n\turldate = {2022-11-04},\n\tbooktitle = {{IGARSS} 2018 - 2018 {IEEE} {International} {Geoscience} and {Remote} {Sensing} {Symposium}},\n\tpublisher = {IEEE},\n\tauthor = {Jagdhuber, T. and Fersch, B. and Schron, M. and Jager, M. and Voormansik, K. and Lopez-Martinez, C.},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {6111--6114},\n}\n\n

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\n \n\n \n \n Jagdhuber, T.; Link, M.; Meyer, T.; Soebjaerg, S.; Dill, S.; and Peichl, M.\n\n\n \n \n \n \n Fully Polarimetric Radiometer Signatures of Azimuthal Permittivity Patterns: Ground-Based L-band Brightness Temperature Observations and Model Simulations.\n \n \n \n\n\n \n\n\n\n In March 2018. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{jagdhuber_fully_2018,\n\ttitle = {Fully {Polarimetric} {Radiometer} {Signatures} of {Azimuthal} {Permittivity} {Patterns}: {Ground}-{Based} {L}-band {Brightness} {Temperature} {Observations} and {Model} {Simulations}},\n\tauthor = {Jagdhuber, Thomas and Link, Moritz and Meyer, Thomas and Soebjaerg, Sten and Dill, Stephan and Peichl, Markus},\n\tmonth = mar,\n\tyear = {2018},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Jakobi, J.; Huisman, J. A.; Vereecken, H.; Diekkrüger, B.; and Bogena, H. R.\n\n\n \n \n \n \n \n Cosmic Ray Neutron Sensing for Simultaneous Soil Water Content and Biomass Quantification in Drought Conditions.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 54(10): 7383–7402. October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Cosmic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{jakobi_cosmic_2018,\n\ttitle = {Cosmic {Ray} {Neutron} {Sensing} for {Simultaneous} {Soil} {Water} {Content} and {Biomass} {Quantification} in {Drought} {Conditions}},\n\tvolume = {54},\n\tissn = {0043-1397, 1944-7973},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2018WR022692},\n\tdoi = {10.1029/2018WR022692},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2022-11-16},\n\tjournal = {Water Resources Research},\n\tauthor = {Jakobi, J. and Huisman, J. A. and Vereecken, H. and Diekkrüger, B. and Bogena, H. R.},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {7383--7402},\n}\n\n

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\n \n\n \n \n Jonard, F.; Bircher, S.; Demontoux, F.; Weihermüller, L.; Razafindratsima, S.; Wigneron, J.; and Vereecken, H.\n\n\n \n \n \n \n \n Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 10(2): 304. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Passive$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{jonard_passive_2018,\n\ttitle = {Passive {L}-{Band} {Microwave} {Remote} {Sensing} of {Organic} {Soil} {Surface} {Layers}: {A} {Tower}-{Based} {Experiment}},\n\tvolume = {10},\n\tissn = {2072-4292},\n\tshorttitle = {Passive {L}-{Band} {Microwave} {Remote} {Sensing} of {Organic} {Soil} {Surface} {Layers}},\n\turl = {http://www.mdpi.com/2072-4292/10/2/304},\n\tdoi = {10.3390/rs10020304},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing},\n\tauthor = {Jonard, François and Bircher, Simone and Demontoux, François and Weihermüller, Lutz and Razafindratsima, Stephen and Wigneron, Jean-Pierre and Vereecken, Harry},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {304},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Jonard, F.; Bogena, H.; Caterina, D.; Garré, S.; Klotzsche, A.; Monerris, A.; Schwank, M.; and von Hebel, C.\n\n\n \n \n \n \n \n Ground-Based Soil Moisture Determination.\n \n \n \n \n\n\n \n\n\n\n In Li, X.; and Vereecken, H., editor(s), Observation and Measurement, pages 1–42. Springer Berlin Heidelberg, Berlin, Heidelberg, 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Ground-Based$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@incollection{li_ground-based_2018,\n\taddress = {Berlin, Heidelberg},\n\ttitle = {Ground-{Based} {Soil} {Moisture} {Determination}},\n\tisbn = {9783662478714},\n\turl = {http://link.springer.com/10.1007/978-3-662-47871-4_2-1},\n\turldate = {2022-11-16},\n\tbooktitle = {Observation and {Measurement}},\n\tpublisher = {Springer Berlin Heidelberg},\n\tauthor = {Jonard, François and Bogena, Heye and Caterina, David and Garré, Sarah and Klotzsche, Anja and Monerris, Alessandra and Schwank, Mike and von Hebel, Christian},\n\teditor = {Li, Xin and Vereecken, Harry},\n\tyear = {2018},\n\tdoi = {10.1007/978-3-662-47871-4_2-1},\n\tpages = {1--42},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Kaiser, K.; Keller, N.; Brande, A.; Dalitz, S.; Hensel, N.; Heußner, K.; Kappler, C.; Michas, U.; Müller, J.; Schwalbe, G.; Weiße, R.; and Bens, O.\n\n\n \n \n \n \n \n A large-scale medieval dam-lake cascade in central Europe: Water level dynamics of the Havel River, Berlin-Brandenburg region, Germany.\n \n \n \n \n\n\n \n\n\n\n Geoarchaeology, 33(2): 237–259. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kaiser_large-scale_2018,\n\ttitle = {A large-scale medieval dam-lake cascade in central {Europe}: {Water} level dynamics of the {Havel} {River}, {Berlin}-{Brandenburg} region, {Germany}},\n\tvolume = {33},\n\tissn = {08836353},\n\tshorttitle = {A large-scale medieval dam-lake cascade in central {Europe}},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/gea.21649},\n\tdoi = {10.1002/gea.21649},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-16},\n\tjournal = {Geoarchaeology},\n\tauthor = {Kaiser, Knut and Keller, Nora and Brande, Arthur and Dalitz, Stefan and Hensel, Nicola and Heußner, Karl-Uwe and Kappler, Christoph and Michas, Uwe and Müller, Joachim and Schwalbe, Grit and Weiße, Roland and Bens, Oliver},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {237--259},\n}\n\n

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\n \n\n \n \n Kaiser, K.; Oldorff, S.; Breitbach, C.; Kappler, C.; Theuerkauf, M.; Scharnweber, T.; Schult, M.; Küster, M.; Engelhardt, C.; Heinrich, I.; Hupfer, M.; Schwalbe, G.; Kirschey, T.; and Bens, O.\n\n\n \n \n \n \n \n A submerged pine forest from the early Holocene in the Mecklenburg Lake District, northern Germany.\n \n \n \n \n\n\n \n\n\n\n Boreas, 47(3): 910–925. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kaiser_submerged_2018,\n\ttitle = {A submerged pine forest from the early {Holocene} in the {Mecklenburg} {Lake} {District}, northern {Germany}},\n\tvolume = {47},\n\tissn = {03009483},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/bor.12314},\n\tdoi = {10.1111/bor.12314},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Boreas},\n\tauthor = {Kaiser, Knut and Oldorff, Silke and Breitbach, Carsten and Kappler, Christoph and Theuerkauf, Martin and Scharnweber, Tobias and Schult, Manuela and Küster, Mathias and Engelhardt, Christof and Heinrich, Ingo and Hupfer, Michael and Schwalbe, Grit and Kirschey, Tom and Bens, Oliver},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {910--925},\n}\n\n

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\n \n\n \n \n Kappler, C.; Kaiser, K.; Tanski, P.; Klos, F.; Fülling, A.; Mrotzek, A.; Sommer, M.; and Bens, O.\n\n\n \n \n \n \n \n Stratigraphy and age of colluvial deposits indicating Late Holocene soil erosion in northeastern Germany.\n \n \n \n \n\n\n \n\n\n\n CATENA, 170: 224–245. November 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Stratigraphy$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{kappler_stratigraphy_2018,\n\ttitle = {Stratigraphy and age of colluvial deposits indicating {Late} {Holocene} soil erosion in northeastern {Germany}},\n\tvolume = {170},\n\tissn = {03418162},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S034181621830242X},\n\tdoi = {10.1016/j.catena.2018.06.010},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {CATENA},\n\tauthor = {Kappler, Christoph and Kaiser, Knut and Tanski, Phillipp and Klos, Friederike and Fülling, Alexander and Mrotzek, Almut and Sommer, Michael and Bens, Oliver},\n\tmonth = nov,\n\tyear = {2018},\n\tpages = {224--245},\n}\n\n

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\n \n\n \n \n Kaufmann, M. S.; Klotzsche, A.; Vereecken, H; and van der Kruk, J.\n\n\n \n \n \n \n \n Simultaneous multi-channel GPR measurements for soil characterization.\n \n \n \n \n\n\n \n\n\n\n In 2018 17th International Conference on Ground Penetrating Radar (GPR), pages 1–4, Rapperswil, June 2018. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Simultaneous$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{kaufmann_simultaneous_2018,\n\taddress = {Rapperswil},\n\ttitle = {Simultaneous multi-channel {GPR} measurements for soil characterization},\n\tisbn = {9781538657775},\n\turl = {https://ieeexplore.ieee.org/document/8441602/},\n\tdoi = {10.1109/ICGPR.2018.8441602},\n\turldate = {2022-11-16},\n\tbooktitle = {2018 17th {International} {Conference} on {Ground} {Penetrating} {Radar} ({GPR})},\n\tpublisher = {IEEE},\n\tauthor = {Kaufmann, M. S. and Klotzsche, A. and Vereecken, H and van der Kruk, J.},\n\tmonth = jun,\n\tyear = {2018},\n\tpages = {1--4},\n}\n\n

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\n \n\n \n \n Kiese, R.; Fersch, B.; Baessler, C.; Brosy, C.; Butterbach-Bahl, K.; Chwala, C.; Dannenmann, M.; Fu, J.; Gasche, R.; Grote, R.; Jahn, C.; Klatt, J.; Kunstmann, H.; Mauder, M.; Rödiger, T.; Smiatek, G.; Soltani, M.; Steinbrecher, R.; Völksch, I.; Werhahn, J.; Wolf, B.; Zeeman, M.; and Schmid, H.\n\n\n \n \n \n \n \n The TERENO Pre‐Alpine Observatory: Integrating Meteorological, Hydrological, and Biogeochemical Measurements and Modeling.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 1–17. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{kiese_tereno_2018,\n\ttitle = {The {TERENO} {Pre}‐{Alpine} {Observatory}: {Integrating} {Meteorological}, {Hydrological}, and {Biogeochemical} {Measurements} and {Modeling}},\n\tvolume = {17},\n\tissn = {1539-1663, 1539-1663},\n\tshorttitle = {The {TERENO} {Pre}‐{Alpine} {Observatory}},\n\turl = {https://onlinelibrary.wiley.com/doi/10.2136/vzj2018.03.0060},\n\tdoi = {10.2136/vzj2018.03.0060},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Kiese, R. and Fersch, B. and Baessler, C. and Brosy, C. and Butterbach-Bahl, K. and Chwala, C. and Dannenmann, M. and Fu, J. and Gasche, R. and Grote, R. and Jahn, C. and Klatt, J. and Kunstmann, H. and Mauder, M. and Rödiger, T. and Smiatek, G. and Soltani, M. and Steinbrecher, R. and Völksch, I. and Werhahn, J. and Wolf, B. and Zeeman, M. and Schmid, H.P.},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {1--17},\n}\n\n

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\n \n\n \n \n Klinke, R.; Kuechly, H.; Frick, A.; Förster, M.; Schmidt, T.; Holtgrave, A.; Kleinschmit, B.; Spengler, D.; and Neumann, C.\n\n\n \n \n \n \n \n Indicator-Based Soil Moisture Monitoring of Wetlands by Utilizing Sentinel and Landsat Remote Sensing Data.\n \n \n \n \n\n\n \n\n\n\n PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 86(2): 71–84. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Indicator-Based$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{klinke_indicator-based_2018,\n\ttitle = {Indicator-{Based} {Soil} {Moisture} {Monitoring} of {Wetlands} by {Utilizing} {Sentinel} and {Landsat} {Remote} {Sensing} {Data}},\n\tvolume = {86},\n\tissn = {2512-2789, 2512-2819},\n\turl = {http://link.springer.com/10.1007/s41064-018-0044-5},\n\tdoi = {10.1007/s41064-018-0044-5},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-16},\n\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\n\tauthor = {Klinke, Randolf and Kuechly, Helga and Frick, Annett and Förster, Michael and Schmidt, Tobias and Holtgrave, Ann-Kathrin and Kleinschmit, Birgit and Spengler, Daniel and Neumann, Carsten},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {71--84},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Klotzsche, A.; Lärm, L.; Weihermüller, L.; Vanderborght, J.; Vereecken, H.; and van der Kruk, J.\n\n\n \n \n \n \n \n Time-lapse horizontal borehole GPR measurements to investigate spatial and temporal soil-water content changes.\n \n \n \n \n\n\n \n\n\n\n In SEG Technical Program Expanded Abstracts 2018, pages 4904–4908, Anaheim, California, August 2018. Society of Exploration Geophysicists\n \n\n\n\n
\n\n\n\n \n \n $\"Time-lapse$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{klotzsche_time-lapse_2018,\n\taddress = {Anaheim, California},\n\ttitle = {Time-lapse horizontal borehole {GPR} measurements to investigate spatial and temporal soil-water content changes},\n\turl = {https://library.seg.org/doi/10.1190/segam2018-2995843.1},\n\tdoi = {10.1190/segam2018-2995843.1},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tbooktitle = {{SEG} {Technical} {Program} {Expanded} {Abstracts} 2018},\n\tpublisher = {Society of Exploration Geophysicists},\n\tauthor = {Klotzsche, Anja and Lärm, Lena and Weihermüller, Lutz and Vanderborght, Jan and Vereecken, Harry and van der Kruk, Jan},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {4904--4908},\n}\n\n

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\n \n\n \n \n Knillmann, S.; Orlinskiy, P.; Kaske, O.; Foit, K.; and Liess, M.\n\n\n \n \n \n \n \n Indication of pesticide effects and recolonization in streams.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 630: 1619–1627. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Indication$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{knillmann_indication_2018,\n\ttitle = {Indication of pesticide effects and recolonization in streams},\n\tvolume = {630},\n\tissn = {00489697},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969718304443},\n\tdoi = {10.1016/j.scitotenv.2018.02.056},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Knillmann, Saskia and Orlinskiy, Polina and Kaske, Oliver and Foit, Kaarina and Liess, Matthias},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {1619--1627},\n}\n\n

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\n \n\n \n \n Kollet, S.; Gasper, F.; Brdar, S.; Goergen, K.; Hendricks-Franssen, H.; Keune, J.; Kurtz, W.; Küll, V.; Pappenberger, F.; Poll, S.; Trömel, S.; Shrestha, P.; Simmer, C.; and Sulis, M.\n\n\n \n \n \n \n \n Introduction of an Experimental Terrestrial Forecasting/Monitoring System at Regional to Continental Scales Based on the Terrestrial System Modeling Platform (v1.1.0).\n \n \n \n \n\n\n \n\n\n\n Technical Report EARTH SCIENCES, October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Introduction$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@techreport{kollet_introduction_2018,\n\ttype = {preprint},\n\ttitle = {Introduction of an {Experimental} {Terrestrial} {Forecasting}/{Monitoring} {System} at {Regional} to {Continental} {Scales} {Based} on the {Terrestrial} {System} {Modeling} {Platform} (v1.1.0)},\n\turl = {https://www.preprints.org/manuscript/201810.0625/v1},\n\tabstract = {Operational weather and also flood forecasting has been performed successfully for decades and is of great socioeconomic importance. Up to now, forecast products focus on atmospheric variables, such as precipitation, air temperature and, in hydrology, on river discharge. Considering the full terrestrial system from groundwater across the land surface into the atmosphere, a number of important hydrologic variables are missing especially with regard to the shallow and deeper subsurface (e.g. groundwater), which are gaining considerable attention in the context of global change. In this study, we propose a terrestrial monitoring/forecasting system using the Terrestrial Systems Modeling Platform (TSMP) that predicts all essential states and fluxes of the terrestrial hydrologic and energy cycles from groundwater into the atmosphere. Closure of the terrestrial cycles provides a physically consistent picture of the terrestrial system in TSMP. TSMP has been implemented over a regional domain over North Rhine-Westphalia and a continental domain over European in a real-time forecast/monitoring workflow. Applying a real-time forecasting/monitoring workflow over both domains, experimental forecasts are being produced with different lead times since the beginning of 2016. Real-time forecast/monitoring products encompass all compartments of the terrestrial system including additional hydrologic variables, such as plant available soil water, groundwater table depth, and groundwater recharge and storage.},\n\turldate = {2022-11-16},\n\tinstitution = {EARTH SCIENCES},\n\tauthor = {Kollet, Stefan and Gasper, Fabian and Brdar, Slavko and Goergen, Klaus and Hendricks-Franssen, Harrie-Jan and Keune, Jessica and Kurtz, Wolfgang and Küll, Volker and Pappenberger, Florian and Poll, Stefan and Trömel, Silke and Shrestha, Prabhakar and Simmer, Clemens and Sulis, Mauro},\n\tmonth = oct,\n\tyear = {2018},\n\tdoi = {10.20944/preprints201810.0625.v1},\n}\n\n

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\n\n\n\n\n\n

\n \n\n \n \n Kröniger, K.; Banerjee, T.; De Roo, F.; and Mauder, M.\n\n\n \n \n \n \n \n Flow adjustment inside homogeneous canopies after a leading edge – An analytical approach backed by LES.\n \n \n \n \n\n\n \n\n\n\n Agricultural and Forest Meteorology, 255: 17–30. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Flow$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{kroniger_flow_2018,\n\ttitle = {Flow adjustment inside homogeneous canopies after a leading edge – {An} analytical approach backed by {LES}},\n\tvolume = {255},\n\tissn = {01681923},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0168192317303143},\n\tdoi = {10.1016/j.agrformet.2017.09.019},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Agricultural and Forest Meteorology},\n\tauthor = {Kröniger, Konstantin and Banerjee, Tirtha and De Roo, Frederik and Mauder, Matthias},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {17--30},\n}\n\n

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\n \n\n \n \n Köhli, M.; Schrön, M.; and Schmidt, U.\n\n\n \n \n \n \n \n Response functions for detectors in cosmic ray neutron sensing.\n \n \n \n \n\n\n \n\n\n\n Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 902: 184–189. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Response$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{kohli_response_2018,\n\ttitle = {Response functions for detectors in cosmic ray neutron sensing},\n\tvolume = {902},\n\tissn = {01689002},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0168900218307745},\n\tdoi = {10.1016/j.nima.2018.06.052},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment},\n\tauthor = {Köhli, M. and Schrön, M. and Schmidt, U.},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {184--189},\n}\n\n

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\n \n\n \n \n Lausch, A.; Bastian, O.; Klotz, S.; Leitão, P. J.; Jung, A.; Rocchini, D.; Schaepman, M. E.; Skidmore, A. K.; Tischendorf, L.; and Knapp, S.\n\n\n \n \n \n \n \n Understanding and assessing vegetation health by in situ species and remote‐sensing approaches.\n \n \n \n \n\n\n \n\n\n\n Methods in Ecology and Evolution, 9(8): 1799–1809. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Understanding$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{lausch_understanding_2018,\n\ttitle = {Understanding and assessing vegetation health by in situ species and remote‐sensing approaches},\n\tvolume = {9},\n\tissn = {2041-210X, 2041-210X},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/2041-210X.13025},\n\tdoi = {10.1111/2041-210X.13025},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2022-11-16},\n\tjournal = {Methods in Ecology and Evolution},\n\tauthor = {Lausch, Angela and Bastian, Olaf and Klotz, Stefan and Leitão, Pedro J. and Jung, András and Rocchini, Duccio and Schaepman, Michael E. and Skidmore, Andrew K. and Tischendorf, Lutz and Knapp, Sonja},\n\teditor = {Vihervaara, Petteri},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {1799--1809},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Lausch, A.; Borg, E.; Bumberger, J.; Dietrich, P.; Heurich, M.; Huth, A.; Jung, A.; Klenke, R.; Knapp, S.; Mollenhauer, H.; Paasche, H.; Paulheim, H.; Pause, M.; Schweitzer, C.; Schmulius, C.; Settele, J.; Skidmore, A.; Wegmann, M.; Zacharias, S.; Kirsten, T.; and Schaepman, M.\n\n\n \n \n \n \n \n Understanding Forest Health with Remote Sensing, Part III: Requirements for a Scalable Multi-Source Forest Health Monitoring Network Based on Data Science Approaches.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 10(7): 1120. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Understanding$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{lausch_understanding_2018-1,\n\ttitle = {Understanding {Forest} {Health} with {Remote} {Sensing}, {Part} {III}: {Requirements} for a {Scalable} {Multi}-{Source} {Forest} {Health} {Monitoring} {Network} {Based} on {Data} {Science} {Approaches}},\n\tvolume = {10},\n\tissn = {2072-4292},\n\tshorttitle = {Understanding {Forest} {Health} with {Remote} {Sensing}, {Part} {III}},\n\turl = {http://www.mdpi.com/2072-4292/10/7/1120},\n\tdoi = {10.3390/rs10071120},\n\tabstract = {Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing},\n\tauthor = {Lausch, Angela and Borg, Erik and Bumberger, Jan and Dietrich, Peter and Heurich, Marco and Huth, Andreas and Jung, András and Klenke, Reinhard and Knapp, Sonja and Mollenhauer, Hannes and Paasche, Hendrik and Paulheim, Heiko and Pause, Marion and Schweitzer, Christian and Schmulius, Christiane and Settele, Josef and Skidmore, Andrew and Wegmann, Martin and Zacharias, Steffen and Kirsten, Toralf and Schaepman, Michael},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {1120},\n}\n\n

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\n Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.\n

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\n \n\n \n \n Lehr, C.; Dannowski, R.; Kalettka, T.; Merz, C.; Schröder, B.; Steidl, J.; and Lischeid, G.\n\n\n \n \n \n \n \n Detecting dominant changes in irregularly sampled multivariate water quality data sets.\n \n \n \n \n\n\n \n\n\n\n Hydrology and Earth System Sciences, 22(8): 4401–4424. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Detecting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{lehr_detecting_2018,\n\ttitle = {Detecting dominant changes in irregularly sampled multivariate water quality data sets},\n\tvolume = {22},\n\tissn = {1607-7938},\n\turl = {https://hess.copernicus.org/articles/22/4401/2018/},\n\tdoi = {10.5194/hess-22-4401-2018},\n\tabstract = {Abstract. Time series of groundwater and stream water quality often exhibit substantial\ntemporal and spatial variability, whereas typical existing monitoring data\nsets, e.g. from environmental agencies, are usually characterized by\nrelatively low sampling frequency and irregular sampling in space and/or\ntime. This complicates the differentiation between anthropogenic influence\nand natural variability as well as the detection of changes in water quality\nwhich indicate changes in single drivers. We suggest the new term “dominant\nchanges” for changes in multivariate water quality data which concern\n(1) multiple variables, (2) multiple sites and (3) long-term patterns and\npresent an exploratory framework for the detection of such dominant changes\nin data sets with irregular sampling in space and time. Firstly, a non-linear\ndimension-reduction technique was used to summarize the dominant\nspatiotemporal dynamics in the multivariate water quality data set in a few\ncomponents. Those were used to derive hypotheses on the dominant drivers\ninfluencing water quality. Secondly, different sampling sites were compared\nwith respect to median component values. Thirdly, time series of the\ncomponents at single sites were analysed for long-term patterns. We tested\nthe approach with a joint stream water and groundwater data set quality\nconsisting of 1572 samples, each comprising sixteen variables, sampled with a\nspatially and temporally irregular sampling scheme at 29 sites in northeast\nGermany from 1998 to 2009. The first four components were interpreted as\n(1) an agriculturally induced enhancement of the natural background level of\nsolute concentration, (2) a redox sequence from reducing conditions in deep\ngroundwater to post-oxic conditions in shallow groundwater and oxic\nconditions in stream water, (3) a mixing ratio of deep and shallow\ngroundwater to the streamflow and (4) sporadic events of slurry application\nin the agricultural practice. Dominant changes were observed for the first\ntwo components. The changing intensity of the first component was interpreted\nas response to the temporal variability of the thickness of the unsaturated\nzone. A steady increase in the second component at most stream water sites\npointed towards progressing depletion of the denitrification capacity of the\ndeep aquifer.},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2022-11-16},\n\tjournal = {Hydrology and Earth System Sciences},\n\tauthor = {Lehr, Christian and Dannowski, Ralf and Kalettka, Thomas and Merz, Christoph and Schröder, Boris and Steidl, Jörg and Lischeid, Gunnar},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {4401--4424},\n}\n\n

\n

\n\n\n

\n Abstract. Time series of groundwater and stream water quality often exhibit substantial temporal and spatial variability, whereas typical existing monitoring data sets, e.g. from environmental agencies, are usually characterized by relatively low sampling frequency and irregular sampling in space and/or time. This complicates the differentiation between anthropogenic influence and natural variability as well as the detection of changes in water quality which indicate changes in single drivers. We suggest the new term “dominant changes” for changes in multivariate water quality data which concern (1) multiple variables, (2) multiple sites and (3) long-term patterns and present an exploratory framework for the detection of such dominant changes in data sets with irregular sampling in space and time. Firstly, a non-linear dimension-reduction technique was used to summarize the dominant spatiotemporal dynamics in the multivariate water quality data set in a few components. Those were used to derive hypotheses on the dominant drivers influencing water quality. Secondly, different sampling sites were compared with respect to median component values. Thirdly, time series of the components at single sites were analysed for long-term patterns. We tested the approach with a joint stream water and groundwater data set quality consisting of 1572 samples, each comprising sixteen variables, sampled with a spatially and temporally irregular sampling scheme at 29 sites in northeast Germany from 1998 to 2009. The first four components were interpreted as (1) an agriculturally induced enhancement of the natural background level of solute concentration, (2) a redox sequence from reducing conditions in deep groundwater to post-oxic conditions in shallow groundwater and oxic conditions in stream water, (3) a mixing ratio of deep and shallow groundwater to the streamflow and (4) sporadic events of slurry application in the agricultural practice. Dominant changes were observed for the first two components. The changing intensity of the first component was interpreted as response to the temporal variability of the thickness of the unsaturated zone. A steady increase in the second component at most stream water sites pointed towards progressing depletion of the denitrification capacity of the deep aquifer.\n

\n\n\n

\n \n\n \n \n Lischeid, G.; Kalettka, T.; Holländer, M.; Steidl, J.; Merz, C.; Dannowski, R.; Hohenbrink, T.; Lehr, C.; Onandia, G.; Reverey, F.; and Pätzig, M.\n\n\n \n \n \n \n \n Natural ponds in an agricultural landscape: External drivers, internal processes, and the role of the terrestrial-aquatic interface.\n \n \n \n \n\n\n \n\n\n\n Limnologica, 68: 5–16. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Natural$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{lischeid_natural_2018,\n\ttitle = {Natural ponds in an agricultural landscape: {External} drivers, internal processes, and the role of the terrestrial-aquatic interface},\n\tvolume = {68},\n\tissn = {00759511},\n\tshorttitle = {Natural ponds in an agricultural landscape},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0075951116300524},\n\tdoi = {10.1016/j.limno.2017.01.003},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Limnologica},\n\tauthor = {Lischeid, Gunnar and Kalettka, Thomas and Holländer, Matthias and Steidl, Jörg and Merz, Christoph and Dannowski, Ralf and Hohenbrink, Tobias and Lehr, Christian and Onandia, Gabriela and Reverey, Florian and Pätzig, Marlene},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {5--16},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Liu, S.; Schloter, M.; and Brüggemann, N.\n\n\n \n \n \n \n \n Accumulation of NO $_{\\textrm{2}}$ $^{\\textrm{−}}$ during periods of drying stimulates soil N $_{\\textrm{2}}$ O emissions during subsequent rewetting: Nitrite stimulates N $_{\\textrm{2}}$ O emissions during rewetting.\n \n \n \n \n\n\n \n\n\n\n European Journal of Soil Science, 69(5): 936–946. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Accumulation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{liu_accumulation_2018,\n\ttitle = {Accumulation of {NO} $_{\\textrm{2}}$ $^{\\textrm{−}}$ during periods of drying stimulates soil {N} $_{\\textrm{2}}$ {O} emissions during subsequent rewetting: {Nitrite} stimulates {N} $_{\\textrm{2}}$ {O} emissions during rewetting},\n\tvolume = {69},\n\tissn = {13510754},\n\tshorttitle = {Accumulation of {NO} $_{\\textrm{2}}$ $^{\\textrm{−}}$ during periods of drying stimulates soil {N} $_{\\textrm{2}}$ {O} emissions during subsequent rewetting},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/ejss.12683},\n\tdoi = {10.1111/ejss.12683},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2022-11-16},\n\tjournal = {European Journal of Soil Science},\n\tauthor = {Liu, S. and Schloter, M. and Brüggemann, N.},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {936--946},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Lutz, S. R.; Krieg, R.; Müller, C.; Zink, M.; Knöller, K.; Samaniego, L.; and Merz, R.\n\n\n \n \n \n \n \n Spatial Patterns of Water Age: Using Young Water Fractions to Improve the Characterization of Transit Times in Contrasting Catchments.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 54(7): 4767–4784. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{lutz_spatial_2018,\n\ttitle = {Spatial {Patterns} of {Water} {Age}: {Using} {Young} {Water} {Fractions} to {Improve} the {Characterization} of {Transit} {Times} in {Contrasting} {Catchments}},\n\tvolume = {54},\n\tissn = {0043-1397, 1944-7973},\n\tshorttitle = {Spatial {Patterns} of {Water} {Age}},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2017WR022216},\n\tdoi = {10.1029/2017WR022216},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2022-11-16},\n\tjournal = {Water Resources Research},\n\tauthor = {Lutz, S. R. and Krieg, R. and Müller, C. and Zink, M. and Knöller, K. and Samaniego, L. and Merz, R.},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {4767--4784},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Mader, M.; Roberts, A. M.; Porst, D.; Schmidt, C.; Trauth, N.; van Geldern, R.; and Barth, J. A.\n\n\n \n \n \n \n \n River recharge versus O2 supply from the unsaturated zone in shallow riparian groundwater: A case study from the Selke River (Germany).\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 634: 374–381. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"River$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{mader_river_2018,\n\ttitle = {River recharge versus {O2} supply from the unsaturated zone in shallow riparian groundwater: {A} case study from the {Selke} {River} ({Germany})},\n\tvolume = {634},\n\tissn = {00489697},\n\tshorttitle = {River recharge versus {O2} supply from the unsaturated zone in shallow riparian groundwater},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969718309896},\n\tdoi = {10.1016/j.scitotenv.2018.03.230},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Mader, Michael and Roberts, André M. and Porst, David and Schmidt, Christian and Trauth, Nico and van Geldern, Robert and Barth, Johannes A.C.},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {374--381},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Makselon, J.; Siebers, N.; Meier, F.; Vereecken, H.; and Klumpp, E.\n\n\n \n \n \n \n \n Role of rain intensity and soil colloids in the retention of surfactant-stabilized silver nanoparticles in soil.\n \n \n \n \n\n\n \n\n\n\n Environmental Pollution, 238: 1027–1034. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Role$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{makselon_role_2018,\n\ttitle = {Role of rain intensity and soil colloids in the retention of surfactant-stabilized silver nanoparticles in soil},\n\tvolume = {238},\n\tissn = {02697491},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0269749117346201},\n\tdoi = {10.1016/j.envpol.2018.02.025},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Environmental Pollution},\n\tauthor = {Makselon, Joanna and Siebers, Nina and Meier, Florian and Vereecken, Harry and Klumpp, Erwin},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {1027--1034},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Marke, T.; Crewell, S.; Schemann, V.; Schween, J. H.; and Tuononen, M.\n\n\n \n \n \n \n \n Long-Term Observations and High-Resolution Modeling of Midlatitude Nocturnal Boundary Layer Processes Connected to Low-Level Jets.\n \n \n \n \n\n\n \n\n\n\n Journal of Applied Meteorology and Climatology, 57(5): 1155–1170. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Long-Term$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{marke_long-term_2018,\n\ttitle = {Long-{Term} {Observations} and {High}-{Resolution} {Modeling} of {Midlatitude} {Nocturnal} {Boundary} {Layer} {Processes} {Connected} to {Low}-{Level} {Jets}},\n\tvolume = {57},\n\tissn = {1558-8424, 1558-8432},\n\turl = {https://journals.ametsoc.org/view/journals/apme/57/5/jamc-d-17-0341.1.xml},\n\tdoi = {10.1175/JAMC-D-17-0341.1},\n\tabstract = {Abstract \n             \n              Low-level-jet (LLJ) periods are investigated by exploiting a long-term record of ground-based remote sensing Doppler wind lidar measurements supported by tower observations and surface flux measurements at the Jülich Observatory for Cloud Evolution (JOYCE), a midlatitude site in western Germany. LLJs were found 13\\% of the time during continuous observations over more than 4 yr. The climatological behavior of the LLJs shows a prevailing nighttime appearance of the jets, with a median height of 375 m and a median wind speed of 8.8 m s \n              −1 \n              at the jet nose. Significant turbulence below the jet nose only occurs for high bulk wind shear, which is an important parameter for describing the turbulent characteristics of the jets. The numerous LLJs (16\\% of all jets) in the range of wind-turbine rotor heights below 200 m demonstrate the importance of LLJs and the associated intermittent turbulence for wind-energy applications. Also, a decrease in surface fluxes and an accumulation of carbon dioxide are observed if LLJs are present. A comprehensive analysis of an LLJ case shows the influence of the surrounding topography, dominated by an open pit mine and a 200-m-high hill, on the wind observed at JOYCE. High-resolution large-eddy simulations that complement the observations show that the spatial distribution of the wind field exhibits variations connected with the orographic flow depending on the wind direction, causing high variability in the long-term measurements of the vertical velocity.},\n\tnumber = {5},\n\turldate = {2022-11-16},\n\tjournal = {Journal of Applied Meteorology and Climatology},\n\tauthor = {Marke, Tobias and Crewell, Susanne and Schemann, Vera and Schween, Jan H. and Tuononen, Minttu},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {1155--1170},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Martens, B.; de Jeu, R.; Verhoest, N.; Schuurmans, H.; Kleijer, J.; and Miralles, D.\n\n\n \n \n \n \n \n Towards Estimating Land Evaporation at Field Scales Using GLEAM.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 10(11): 1720. October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{martens_towards_2018,\n\ttitle = {Towards {Estimating} {Land} {Evaporation} at {Field} {Scales} {Using} {GLEAM}},\n\tvolume = {10},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/10/11/1720},\n\tdoi = {10.3390/rs10111720},\n\tabstract = {The evaporation of water from land into the atmosphere is a key component of the hydrological cycle. Accurate estimates of this flux are essential for proper water management and irrigation scheduling. However, continuous and qualitative information on land evaporation is currently not available at the required spatio-temporal scales for agricultural applications and regional-scale water management. Here, we apply the Global Land Evaporation Amsterdam Model (GLEAM) at 100 m spatial resolution and daily time steps to provide estimates of land evaporation over The Netherlands, Flanders, and western Germany for the period 2013–2017. By making extensive use of microwave-based geophysical observations, we are able to provide data under all weather conditions. The soil moisture estimates from GLEAM at high resolution compare well with in situ measurements of surface soil moisture, resulting in a median temporal correlation coefficient of 0.76 across 29 sites. Estimates of terrestrial evaporation are also evaluated using in situ eddy-covariance measurements from five sites, and compared to estimates from the coarse-scale GLEAM v3.2b, land evaporation from the Satellite Application Facility on Land Surface Analysis (LSA-SAF), and reference grass evaporation based on Makkink’s equation. All datasets compare similarly with in situ measurements and differences in the temporal statistics are small, with correlation coefficients against in situ data ranging from 0.65 to 0.95, depending on the site. Evaporation estimates from GLEAM-HR are typically bounded by the high values of the Makkink evaporation and the low values from LSA-SAF. While GLEAM-HR and LSA-SAF show the highest spatial detail, their geographical patterns diverge strongly due to differences in model assumptions, model parameterizations, and forcing data. The separate consideration of rainfall interception loss by tall vegetation in GLEAM-HR is a key cause of this divergence: while LSA-SAF reports maximum annual evaporation volumes in the Green Heart of The Netherlands, an area dominated by shrubs and grasses, GLEAM-HR shows its maximum in the national parks of the Veluwe and Heuvelrug, both densely-forested regions where rainfall interception loss is a dominant process. The pioneering dataset presented here is unique in that it provides observational-based estimates at high resolution under all weather conditions, and represents a viable alternative to traditional visible and infrared models to retrieve evaporation at field scales.},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing},\n\tauthor = {Martens, Brecht and de Jeu, Richard and Verhoest, Niko and Schuurmans, Hanneke and Kleijer, Jonne and Miralles, Diego},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {1720},\n}\n\n

\n

\n\n\n

\n The evaporation of water from land into the atmosphere is a key component of the hydrological cycle. Accurate estimates of this flux are essential for proper water management and irrigation scheduling. However, continuous and qualitative information on land evaporation is currently not available at the required spatio-temporal scales for agricultural applications and regional-scale water management. Here, we apply the Global Land Evaporation Amsterdam Model (GLEAM) at 100 m spatial resolution and daily time steps to provide estimates of land evaporation over The Netherlands, Flanders, and western Germany for the period 2013–2017. By making extensive use of microwave-based geophysical observations, we are able to provide data under all weather conditions. The soil moisture estimates from GLEAM at high resolution compare well with in situ measurements of surface soil moisture, resulting in a median temporal correlation coefficient of 0.76 across 29 sites. Estimates of terrestrial evaporation are also evaluated using in situ eddy-covariance measurements from five sites, and compared to estimates from the coarse-scale GLEAM v3.2b, land evaporation from the Satellite Application Facility on Land Surface Analysis (LSA-SAF), and reference grass evaporation based on Makkink’s equation. All datasets compare similarly with in situ measurements and differences in the temporal statistics are small, with correlation coefficients against in situ data ranging from 0.65 to 0.95, depending on the site. Evaporation estimates from GLEAM-HR are typically bounded by the high values of the Makkink evaporation and the low values from LSA-SAF. While GLEAM-HR and LSA-SAF show the highest spatial detail, their geographical patterns diverge strongly due to differences in model assumptions, model parameterizations, and forcing data. The separate consideration of rainfall interception loss by tall vegetation in GLEAM-HR is a key cause of this divergence: while LSA-SAF reports maximum annual evaporation volumes in the Green Heart of The Netherlands, an area dominated by shrubs and grasses, GLEAM-HR shows its maximum in the national parks of the Veluwe and Heuvelrug, both densely-forested regions where rainfall interception loss is a dominant process. The pioneering dataset presented here is unique in that it provides observational-based estimates at high resolution under all weather conditions, and represents a viable alternative to traditional visible and infrared models to retrieve evaporation at field scales.\n

\n\n\n

\n \n\n \n \n Martínez, B.; Sanchez-Ruiz, S.; Gilabert, M.; Moreno, A.; Campos-Taberner, M.; García-Haro, F.; Trigo, I.; Aurela, M.; Brümmer, C.; Carrara, A.; De Ligne, A.; Gianelle, D.; Grünwald, T.; Limousin, J.; Lohila, A.; Mammarella, I.; Sottocornola, M.; Steinbrecher, R.; and Tagesson, T.\n\n\n \n \n \n \n \n Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products.\n \n \n \n \n\n\n \n\n\n\n International Journal of Applied Earth Observation and Geoinformation, 65: 124–136. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Retrieval$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{martinez_retrieval_2018,\n\ttitle = {Retrieval of daily gross primary production over {Europe} and {Africa} from an ensemble of {SEVIRI}/{MSG} products},\n\tvolume = {65},\n\tissn = {15698432},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0303243417302301},\n\tdoi = {10.1016/j.jag.2017.10.011},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {International Journal of Applied Earth Observation and Geoinformation},\n\tauthor = {Martínez, B. and Sanchez-Ruiz, S. and Gilabert, M.A. and Moreno, A. and Campos-Taberner, M. and García-Haro, F.J. and Trigo, I.F. and Aurela, M. and Brümmer, C. and Carrara, A. and De Ligne, A. and Gianelle, D. and Grünwald, T. and Limousin, J.M. and Lohila, A. and Mammarella, I. and Sottocornola, M. and Steinbrecher, R. and Tagesson, T.},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {124--136},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Massei, R.; Byers, H.; Beckers, L.; Prothmann, J.; Brack, W.; Schulze, T.; and Krauss, M.\n\n\n \n \n \n \n \n A sediment extraction and cleanup method for wide-scope multitarget screening by liquid chromatography–high-resolution mass spectrometry.\n \n \n \n \n\n\n \n\n\n\n Analytical and Bioanalytical Chemistry, 410(1): 177–188. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{massei_sediment_2018,\n\ttitle = {A sediment extraction and cleanup method for wide-scope multitarget screening by liquid chromatography–high-resolution mass spectrometry},\n\tvolume = {410},\n\tissn = {1618-2642, 1618-2650},\n\turl = {http://link.springer.com/10.1007/s00216-017-0708-9},\n\tdoi = {10.1007/s00216-017-0708-9},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Analytical and Bioanalytical Chemistry},\n\tauthor = {Massei, Riccardo and Byers, Harry and Beckers, Liza-Marie and Prothmann, Jens and Brack, Werner and Schulze, Tobias and Krauss, Martin},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {177--188},\n}\n\n

\n

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\n \n\n \n \n Mauder, M.; Genzel, S.; Fu, J.; Kiese, R.; Soltani, M.; Steinbrecher, R.; Zeeman, M.; Banerjee, T.; De Roo, F.; and Kunstmann, H.\n\n\n \n \n \n \n \n Evaluation of energy balance closure adjustment methods by independent evapotranspiration estimates from lysimeters and hydrological simulations.\n \n \n \n \n\n\n \n\n\n\n Hydrological Processes, 32(1): 39–50. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{mauder_evaluation_2018,\n\ttitle = {Evaluation of energy balance closure adjustment methods by independent evapotranspiration estimates from lysimeters and hydrological simulations},\n\tvolume = {32},\n\tissn = {08856087},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/hyp.11397},\n\tdoi = {10.1002/hyp.11397},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Hydrological Processes},\n\tauthor = {Mauder, Matthias and Genzel, Sandra and Fu, Jin and Kiese, Ralf and Soltani, Mohsen and Steinbrecher, Rainer and Zeeman, Matthias and Banerjee, Tirtha and De Roo, Frederik and Kunstmann, Harald},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {39--50},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Mauder, M.; and Zeeman, M. J.\n\n\n \n \n \n \n \n Field intercomparison of prevailing sonic anemometers.\n \n \n \n \n\n\n \n\n\n\n Atmospheric Measurement Techniques, 11(1): 249–263. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Field$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{mauder_field_2018,\n\ttitle = {Field intercomparison of prevailing sonic anemometers},\n\tvolume = {11},\n\tissn = {1867-8548},\n\turl = {https://amt.copernicus.org/articles/11/249/2018/},\n\tdoi = {10.5194/amt-11-249-2018},\n\tabstract = {Abstract. Three-dimensional sonic anemometers are the core component of eddy covariance systems, which are widely used for micrometeorological and ecological research. In order to characterize the measurement uncertainty of these instruments we present and analyse the results from a field intercomparison experiment of six commonly used sonic anemometer models from four major manufacturers. These models include Campbell CSAT3, Gill HS-50 and R3, METEK uSonic-3 Omni, R. M. Young 81000 and 81000RE. The experiment was conducted over a meadow at the TERENO/ICOS site DE-Fen in southern Germany over a period of 16 days in June of 2016 as part of the ScaleX campaign. The measurement height was 3 m for all sensors, which were separated by 9 m from each other, each on its own tripod, in order to limit contamination of the turbulence measurements by adjacent structures as much as possible. Moreover, the high-frequency data from all instruments were treated with the same post-processing algorithm. In this study, we compare the results for various turbulence statistics, which include mean horizontal wind speed, standard deviations of vertical wind velocity and sonic temperature, friction velocity, and the buoyancy flux. Quantitative measures of uncertainty, such as bias and comparability, are derived from these results. We find that biases are generally very small for all sensors and all computed variables, except for the sonic temperature measurements of the two Gill sonic anemometers (HS and R3), confirming a known transducer-temperature dependence of the sonic temperature measurement. The best overall agreement between the different instruments was found for the mean wind speed and the buoyancy flux.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Atmospheric Measurement Techniques},\n\tauthor = {Mauder, Matthias and Zeeman, Matthias J.},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {249--263},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Meyer, M.; Krabel, D.; Kniesel, B.; and Helle, G.\n\n\n \n \n \n \n \n Inter-annual variation of tree-ring width, δ13C and δ18O in juvenile trees of five plantation poplar cultivars (Populus spp.).\n \n \n \n \n\n\n \n\n\n\n Dendrochronologia, 51: 32–39. October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Inter-annual$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{meyer_inter-annual_2018,\n\ttitle = {Inter-annual variation of tree-ring width, δ{13C} and δ{18O} in juvenile trees of five plantation poplar cultivars ({Populus} spp.)},\n\tvolume = {51},\n\tissn = {11257865},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1125786517301832},\n\tdoi = {10.1016/j.dendro.2018.07.002},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Dendrochronologia},\n\tauthor = {Meyer, Matthias and Krabel, Doris and Kniesel, Britt and Helle, Gerhard},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {32--39},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Meyer, N.; Meyer, H.; Welp, G.; and Amelung, W.\n\n\n \n \n \n \n \n Soil respiration and its temperature sensitivity (Q10): Rapid acquisition using mid-infrared spectroscopy.\n \n \n \n \n\n\n \n\n\n\n Geoderma, 323: 31–40. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Soil$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{meyer_soil_2018,\n\ttitle = {Soil respiration and its temperature sensitivity ({Q10}): {Rapid} acquisition using mid-infrared spectroscopy},\n\tvolume = {323},\n\tissn = {00167061},\n\tshorttitle = {Soil respiration and its temperature sensitivity ({Q10})},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0016706117311242},\n\tdoi = {10.1016/j.geoderma.2018.02.031},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Geoderma},\n\tauthor = {Meyer, Nele and Meyer, Hanna and Welp, Gerhard and Amelung, Wulf},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {31--40},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Meyer, T.; Weihermüller, L.; Vereecken, H.; and Jonard, F.\n\n\n \n \n \n \n \n Vegetation Optical Depth and Soil Moisture Retrieved from L-Band Radiometry over the Growth Cycle of a Winter Wheat.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 10(10): 1637. October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Vegetation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{meyer_vegetation_2018,\n\ttitle = {Vegetation {Optical} {Depth} and {Soil} {Moisture} {Retrieved} from {L}-{Band} {Radiometry} over the {Growth} {Cycle} of a {Winter} {Wheat}},\n\tvolume = {10},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/10/10/1637},\n\tdoi = {10.3390/rs10101637},\n\tabstract = {L-band radiometer measurements were performed at the Selhausen remote sensing field laboratory (Germany) over the entire growing season of a winter wheat stand. L-band microwave observations were collected over two different footprints within a homogenous winter wheat stand in order to disentangle the emissions originating from the soil and from the vegetation. Based on brightness temperature (TB) measurements performed over an area consisting of a soil surface covered by a reflector (i.e., to block the radiation from the soil surface), vegetation optical depth (τ) information was retrieved using the tau-omega (τ-ω) radiative transfer model. The retrieved τ appeared to be clearly polarization dependent, with lower values for horizontal (H) and higher values for vertical (V) polarization. Additionally, a strong dependency of τ on incidence angle for the V polarization was observed. Furthermore, τ indicated a bell-shaped temporal evolution, with lowest values during the tillering and senescence stages, and highest values during flowering of the wheat plants. The latter corresponded to the highest amounts of vegetation water content (VWC) and largest leaf area index (LAI). To show that the time, polarization, and angle dependence is also highly dependent on the observed vegetation species, white mustard was grown during a short experiment, and radiometer measurements were performed using the same experimental setup. These results showed that the mustard canopy is more isotropic compared to the wheat vegetation (i.e., the τ parameter is less dependent on incidence angle and polarization). In a next step, the relationship between τ and in situ measured vegetation properties (VWC, LAI, total of aboveground vegetation biomass, and vegetation height) was investigated, showing a strong correlation between τ over the entire growing season and the VWC as well as between τ and LAI. Finally, the soil moisture was retrieved from TB observations over a second plot without a reflector on the ground. The retrievals were significantly improved compared to in situ measurements by using the time, polarization, and angle dependent τ as a priori information. This improvement can be explained by the better representation of the vegetation layer effect on the measured TB.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing},\n\tauthor = {Meyer, Thomas and Weihermüller, Lutz and Vereecken, Harry and Jonard, François},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {1637},\n}\n\n

\n

\n\n\n

\n L-band radiometer measurements were performed at the Selhausen remote sensing field laboratory (Germany) over the entire growing season of a winter wheat stand. L-band microwave observations were collected over two different footprints within a homogenous winter wheat stand in order to disentangle the emissions originating from the soil and from the vegetation. Based on brightness temperature (TB) measurements performed over an area consisting of a soil surface covered by a reflector (i.e., to block the radiation from the soil surface), vegetation optical depth (τ) information was retrieved using the tau-omega (τ-ω) radiative transfer model. The retrieved τ appeared to be clearly polarization dependent, with lower values for horizontal (H) and higher values for vertical (V) polarization. Additionally, a strong dependency of τ on incidence angle for the V polarization was observed. Furthermore, τ indicated a bell-shaped temporal evolution, with lowest values during the tillering and senescence stages, and highest values during flowering of the wheat plants. The latter corresponded to the highest amounts of vegetation water content (VWC) and largest leaf area index (LAI). To show that the time, polarization, and angle dependence is also highly dependent on the observed vegetation species, white mustard was grown during a short experiment, and radiometer measurements were performed using the same experimental setup. These results showed that the mustard canopy is more isotropic compared to the wheat vegetation (i.e., the τ parameter is less dependent on incidence angle and polarization). In a next step, the relationship between τ and in situ measured vegetation properties (VWC, LAI, total of aboveground vegetation biomass, and vegetation height) was investigated, showing a strong correlation between τ over the entire growing season and the VWC as well as between τ and LAI. Finally, the soil moisture was retrieved from TB observations over a second plot without a reflector on the ground. The retrievals were significantly improved compared to in situ measurements by using the time, polarization, and angle dependent τ as a priori information. This improvement can be explained by the better representation of the vegetation layer effect on the measured TB.\n

\n\n\n

\n \n\n \n \n Mi, C.; Frassl, M. A.; Boehrer, B.; and Rinke, K.\n\n\n \n \n \n \n \n Episodic wind events induce persistent shifts in the thermal stratification of a reservoir (Rappbode Reservoir, Germany).\n \n \n \n \n\n\n \n\n\n\n International Review of Hydrobiology, 103(3-4): 71–82. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Episodic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{mi_episodic_2018,\n\ttitle = {Episodic wind events induce persistent shifts in the thermal stratification of a reservoir ({Rappbode} {Reservoir}, {Germany})},\n\tvolume = {103},\n\tissn = {14342944},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/iroh.201701916},\n\tdoi = {10.1002/iroh.201701916},\n\tlanguage = {en},\n\tnumber = {3-4},\n\turldate = {2022-11-16},\n\tjournal = {International Review of Hydrobiology},\n\tauthor = {Mi, Chenxi and Frassl, Marieke A. and Boehrer, Bertram and Rinke, Karsten},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {71--82},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Missong, A.; Bol, R.; Nischwitz, V.; Krüger, J.; Lang, F.; Siemens, J.; and Klumpp, E.\n\n\n \n \n \n \n \n Phosphorus in water dispersible-colloids of forest soil profiles.\n \n \n \n \n\n\n \n\n\n\n Plant and Soil, 427(1-2): 71–86. June 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Phosphorus$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{missong_phosphorus_2018,\n\ttitle = {Phosphorus in water dispersible-colloids of forest soil profiles},\n\tvolume = {427},\n\tissn = {0032-079X, 1573-5036},\n\turl = {http://link.springer.com/10.1007/s11104-017-3430-7},\n\tdoi = {10.1007/s11104-017-3430-7},\n\tlanguage = {en},\n\tnumber = {1-2},\n\turldate = {2022-11-16},\n\tjournal = {Plant and Soil},\n\tauthor = {Missong, Anna and Bol, Roland and Nischwitz, Volker and Krüger, Jaane and Lang, Friederike and Siemens, Jan and Klumpp, Erwin},\n\tmonth = jun,\n\tyear = {2018},\n\tpages = {71--86},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Missong, A.; Holzmann, S.; Bol, R.; Nischwitz, V.; Puhlmann, H.; v. Wilpert, K.; Siemens, J.; and Klumpp, E.\n\n\n \n \n \n \n \n Leaching of natural colloids from forest topsoils and their relevance for phosphorus mobility.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 634: 305–315. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Leaching$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{missong_leaching_2018,\n\ttitle = {Leaching of natural colloids from forest topsoils and their relevance for phosphorus mobility},\n\tvolume = {634},\n\tissn = {00489697},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969718310246},\n\tdoi = {10.1016/j.scitotenv.2018.03.265},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Missong, Anna and Holzmann, Stefan and Bol, Roland and Nischwitz, Volker and Puhlmann, Heike and v. Wilpert, Klaus and Siemens, Jan and Klumpp, Erwin},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {305--315},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Mollenhauer, H.; Kasner, M.; Haase, P.; Peterseil, J.; Wohner, C.; Frenzel, M.; Mirtl, M.; Schima, R.; Bumberger, J.; and Zacharias, S.\n\n\n \n \n \n \n \n Long-term environmental monitoring infrastructures in Europe: observations, measurements, scales, and socio-ecological representativeness.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 624: 968–978. May 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Long-term$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{mollenhauer_long-term_2018,\n\ttitle = {Long-term environmental monitoring infrastructures in {Europe}: observations, measurements, scales, and socio-ecological representativeness},\n\tvolume = {624},\n\tissn = {00489697},\n\tshorttitle = {Long-term environmental monitoring infrastructures in {Europe}},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969717335210},\n\tdoi = {10.1016/j.scitotenv.2017.12.095},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Mollenhauer, Hannes and Kasner, Max and Haase, Peter and Peterseil, Johannes and Wohner, Christoph and Frenzel, Mark and Mirtl, Michael and Schima, Robert and Bumberger, Jan and Zacharias, Steffen},\n\tmonth = may,\n\tyear = {2018},\n\tpages = {968--978},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Montzka, C.; Rötzer, K.; Bogena, H.; Sanchez, N.; and Vereecken, H.\n\n\n \n \n \n \n \n A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 10(3): 427. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{montzka_new_2018,\n\ttitle = {A {New} {Soil} {Moisture} {Downscaling} {Approach} for {SMAP}, {SMOS}, and {ASCAT} by {Predicting} {Sub}-{Grid} {Variability}},\n\tvolume = {10},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/10/3/427},\n\tdoi = {10.3390/rs10030427},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing},\n\tauthor = {Montzka, Carsten and Rötzer, Kathrina and Bogena, Heye and Sanchez, Nilda and Vereecken, Harry},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {427},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Musolff, A.; Fleckenstein, J.; Opitz, M.; Büttner, O.; Kumar, R.; and Tittel, J.\n\n\n \n \n \n \n \n Spatio-temporal controls of dissolved organic carbon stream water concentrations.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 566: 205–215. November 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatio-temporal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{musolff_spatio-temporal_2018,\n\ttitle = {Spatio-temporal controls of dissolved organic carbon stream water concentrations},\n\tvolume = {566},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169418306978},\n\tdoi = {10.1016/j.jhydrol.2018.09.011},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Musolff, A. and Fleckenstein, J.H. and Opitz, M. and Büttner, O. and Kumar, R. and Tittel, J.},\n\tmonth = nov,\n\tyear = {2018},\n\tpages = {205--215},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Müller, C.; Musolff, A.; Strachauer, U.; Brauns, M.; Tarasova, L.; Merz, R.; and Knöller, K.\n\n\n \n \n \n \n \n Tomography of anthropogenic nitrate contribution along a mesoscale river.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 615: 773–783. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Tomography$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{muller_tomography_2018,\n\ttitle = {Tomography of anthropogenic nitrate contribution along a mesoscale river},\n\tvolume = {615},\n\tissn = {00489697},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969717326487},\n\tdoi = {10.1016/j.scitotenv.2017.09.297},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Müller, Christin and Musolff, Andreas and Strachauer, Ulrike and Brauns, Mario and Tarasova, Larisa and Merz, Ralf and Knöller, Kay},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {773--783},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Naderpour, R.; and Schwank, M.\n\n\n \n \n \n \n \n Snow Wetness Retrieved from L-Band Radiometry.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 10(3): 359. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Snow$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{naderpour_snow_2018,\n\ttitle = {Snow {Wetness} {Retrieved} from {L}-{Band} {Radiometry}},\n\tvolume = {10},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/10/3/359},\n\tdoi = {10.3390/rs10030359},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing},\n\tauthor = {Naderpour, Reza and Schwank, Mike},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {359},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Ney, P.; and Graf, A.\n\n\n \n \n \n \n \n High-Resolution Vertical Profile Measurements for Carbon Dioxide and Water Vapour Concentrations Within and Above Crop Canopies.\n \n \n \n \n\n\n \n\n\n\n Boundary-Layer Meteorology, 166(3): 449–473. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"High-Resolution$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{ney_high-resolution_2018,\n\ttitle = {High-{Resolution} {Vertical} {Profile} {Measurements} for {Carbon} {Dioxide} and {Water} {Vapour} {Concentrations} {Within} and {Above} {Crop} {Canopies}},\n\tvolume = {166},\n\tissn = {0006-8314, 1573-1472},\n\turl = {http://link.springer.com/10.1007/s10546-017-0316-4},\n\tdoi = {10.1007/s10546-017-0316-4},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Boundary-Layer Meteorology},\n\tauthor = {Ney, Patrizia and Graf, Alexander},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {449--473},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Nixdorf, E.; and Trauth, N.\n\n\n \n \n \n \n \n Evaluating the reliability of time series analysis to estimate variable riparian travel times by numerical groundwater modelling.\n \n \n \n \n\n\n \n\n\n\n Hydrological Processes, 32(3): 408–420. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluating$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{nixdorf_evaluating_2018,\n\ttitle = {Evaluating the reliability of time series analysis to estimate variable riparian travel times by numerical groundwater modelling},\n\tvolume = {32},\n\tissn = {08856087},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/hyp.11428},\n\tdoi = {10.1002/hyp.11428},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Hydrological Processes},\n\tauthor = {Nixdorf, Erik and Trauth, Nico},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {408--420},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Pauly, M.; Helle, G.; Miramont, C.; Büntgen, U.; Treydte, K.; Reinig, F.; Guibal, F.; Sivan, O.; Heinrich, I.; Riedel, F.; Kromer, B.; Balanzategui, D.; Wacker, L.; Sookdeo, A.; and Brauer, A.\n\n\n \n \n \n \n \n Subfossil trees suggest enhanced Mediterranean hydroclimate variability at the onset of the Younger Dryas.\n \n \n \n \n\n\n \n\n\n\n Scientific Reports, 8(1): 13980. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Subfossil$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{pauly_subfossil_2018,\n\ttitle = {Subfossil trees suggest enhanced {Mediterranean} hydroclimate variability at the onset of the {Younger} {Dryas}},\n\tvolume = {8},\n\tissn = {2045-2322},\n\turl = {http://www.nature.com/articles/s41598-018-32251-2},\n\tdoi = {10.1038/s41598-018-32251-2},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Scientific Reports},\n\tauthor = {Pauly, Maren and Helle, Gerhard and Miramont, Cécile and Büntgen, Ulf and Treydte, Kerstin and Reinig, Frederick and Guibal, Frédéric and Sivan, Olivier and Heinrich, Ingo and Riedel, Frank and Kromer, Bernd and Balanzategui, Daniel and Wacker, Lukas and Sookdeo, Adam and Brauer, Achim},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {13980},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Pavelka, M.; Acosta, M.; Kiese, R.; Altimir, N.; Brümmer, C.; Crill, P.; Darenova, E.; Fuß, R.; Gielen, B.; Graf, A.; Klemedtsson, L.; Lohila, A.; Longdoz, B.; Lindroth, A.; Nilsson, M.; Jiménez, S. M.; Merbold, L.; Montagnani, L.; Peichl, M.; Pihlatie, M.; Pumpanen, J.; Ortiz, P. S.; Silvennoinen, H.; Skiba, U.; Vestin, P.; Weslien, P.; Janous, D.; and Kutsch, W.\n\n\n \n \n \n \n \n Standardisation of chamber technique for CO2, N2O and CH4 fluxes measurements from terrestrial ecosystems.\n \n \n \n \n\n\n \n\n\n\n International Agrophysics, 32(4): 569–587. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Standardisation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{pavelka_standardisation_2018,\n\ttitle = {Standardisation of chamber technique for {CO2}, {N2O} and {CH4} fluxes measurements from terrestrial ecosystems},\n\tvolume = {32},\n\tissn = {2300-8725},\n\turl = {http://archive.sciendo.com/INTAG/intag.2017.32.issue-4/intag-2017-0045/intag-2017-0045.pdf},\n\tdoi = {10.1515/intag-2017-0045},\n\tabstract = {Abstract \n             \n              Chamber measurements of trace gas fluxes between the land surface and the atmosphere have been conducted for almost a century. Different chamber techniques, including static and dynamic, have been used with varying degrees of success in estimating greenhouse gases (CO \n              2 \n              , CH \n              4 \n              , N \n              2 \n              O) fluxes. However, all of these have certain disadvantages which have either prevented them from providing an adequate estimate of greenhouse gas exchange or restricted them to be used under limited conditions. Generally, chamber methods are relatively low in cost and simple to operate. In combination with the appropriate sample allocations, chamber methods are adaptable for a wide variety of studies from local to global spatial scales, and they are particularly well suited for in situ and laboratory-based studies. Consequently, chamber measurements will play an important role in the portfolio of the Pan-European long-term research infrastructure Integrated Carbon Observation System. The respective working group of the Integrated Carbon Observation System Ecosystem Monitoring Station Assembly has decided to ascertain standards and quality checks for automated and manual chamber systems instead of defining one or several standard systems provided by commercial manufacturers in order to define minimum requirements for chamber measurements. The defined requirements and recommendations related to chamber measurements are described here.},\n\tnumber = {4},\n\turldate = {2022-11-16},\n\tjournal = {International Agrophysics},\n\tauthor = {Pavelka, Marian and Acosta, Manuel and Kiese, Ralf and Altimir, Núria and Brümmer, Christian and Crill, Patrick and Darenova, Eva and Fuß, Roland and Gielen, Bert and Graf, Alexander and Klemedtsson, Leif and Lohila, Annalea and Longdoz, Bernhard and Lindroth, Anders and Nilsson, Mats and Jiménez, Sara Maraňón and Merbold, Lutz and Montagnani, Leonardo and Peichl, Matthias and Pihlatie, Mari and Pumpanen, Jukka and Ortiz, Penelope Serrano and Silvennoinen, Hanna and Skiba, Ute and Vestin, Patrik and Weslien, Per and Janous, Dalibor and Kutsch, Werner},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {569--587},\n}\n\n

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\n\n\n\n\n\n

\n \n\n \n \n Peters, R. L.; Balanzategui, D.; Hurley, A. G.; von Arx, G.; Prendin, A. L.; Cuny, H. E.; Björklund, J.; Frank, D. C.; and Fonti, P.\n\n\n \n \n \n \n \n RAPTOR: Row and position tracheid organizer in R.\n \n \n \n \n\n\n \n\n\n\n Dendrochronologia, 47: 10–16. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"RAPTOR:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{peters_raptor_2018,\n\ttitle = {{RAPTOR}: {Row} and position tracheid organizer in {R}},\n\tvolume = {47},\n\tissn = {11257865},\n\tshorttitle = {{RAPTOR}},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1125786517301236},\n\tdoi = {10.1016/j.dendro.2017.10.003},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Dendrochronologia},\n\tauthor = {Peters, Richard L. and Balanzategui, Daniel and Hurley, Alexander G. and von Arx, Georg and Prendin, Angela Luisa and Cuny, Henri E. and Björklund, Jesper and Frank, David C. and Fonti, Patrick},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {10--16},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Peters, R. L.; Fonti, P.; Frank, D. C.; Poyatos, R.; Pappas, C.; Kahmen, A.; Carraro, V.; Prendin, A. L.; Schneider, L.; Baltzer, J. L.; Baron‐Gafford, G. A.; Dietrich, L.; Heinrich, I.; Minor, R. L.; Sonnentag, O.; Matheny, A. M.; Wightman, M. G.; and Steppe, K.\n\n\n \n \n \n \n \n Quantification of uncertainties in conifer sap flow measured with the thermal dissipation method.\n \n \n \n \n\n\n \n\n\n\n New Phytologist, 219(4): 1283–1299. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Quantification$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{peters_quantification_2018,\n\ttitle = {Quantification of uncertainties in conifer sap flow measured with the thermal dissipation method},\n\tvolume = {219},\n\tissn = {0028-646X, 1469-8137},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/nph.15241},\n\tdoi = {10.1111/nph.15241},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2022-11-16},\n\tjournal = {New Phytologist},\n\tauthor = {Peters, Richard L. and Fonti, Patrick and Frank, David C. and Poyatos, Rafael and Pappas, Christoforos and Kahmen, Ansgar and Carraro, Vinicio and Prendin, Angela Luisa and Schneider, Loïc and Baltzer, Jennifer L. and Baron‐Gafford, Greg A. and Dietrich, Lars and Heinrich, Ingo and Minor, Rebecca L. and Sonnentag, Oliver and Matheny, Ashley M. and Wightman, Maxwell G. and Steppe, Kathy},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {1283--1299},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Polst, B. H.; Anlanger, C.; Risse-Buhl, U.; Larras, F.; Hein, T.; Weitere, M.; and Schmitt-Jansen, M.\n\n\n \n \n \n \n \n Hydrodynamics Alter the Tolerance of Autotrophic Biofilm Communities Toward Herbicides.\n \n \n \n \n\n\n \n\n\n\n Frontiers in Microbiology, 9: 2884. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Hydrodynamics$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{polst_hydrodynamics_2018,\n\ttitle = {Hydrodynamics {Alter} the {Tolerance} of {Autotrophic} {Biofilm} {Communities} {Toward} {Herbicides}},\n\tvolume = {9},\n\tissn = {1664-302X},\n\turl = {https://www.frontiersin.org/article/10.3389/fmicb.2018.02884/full},\n\tdoi = {10.3389/fmicb.2018.02884},\n\turldate = {2022-11-16},\n\tjournal = {Frontiers in Microbiology},\n\tauthor = {Polst, Bastian H. and Anlanger, Christine and Risse-Buhl, Ute and Larras, Floriane and Hein, Thomas and Weitere, Markus and Schmitt-Jansen, Mechthild},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {2884},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Post, H.; Hendricks Franssen, H.; Han, X.; Baatz, R.; Montzka, C.; Schmidt, M.; and Vereecken, H.\n\n\n \n \n \n \n \n Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates.\n \n \n \n \n\n\n \n\n\n\n Biogeosciences, 15(1): 187–208. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{post_evaluation_2018,\n\ttitle = {Evaluation and uncertainty analysis of regional-scale {CLM4}.5 net carbon flux estimates},\n\tvolume = {15},\n\tissn = {1726-4189},\n\turl = {https://bg.copernicus.org/articles/15/187/2018/},\n\tdoi = {10.5194/bg-15-187-2018},\n\tabstract = {Abstract. Modeling net ecosystem exchange (NEE) at the regional scale with land surface models (LSMs) is relevant for the estimation of regional carbon balances, but studies on it are very limited. Furthermore, it is essential to better understand and quantify the uncertainty of LSMs in order to improve them. An important key variable in this respect is the prognostic leaf area index (LAI), which is very sensitive to forcing data and strongly affects the modeled NEE. We applied the Community Land Model (CLM4.5-BGC) to the Rur catchment in western Germany and compared estimated and default ecological key parameters for modeling carbon fluxes and LAI. The parameter estimates were previously estimated with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) for four of the most widespread plant functional types in the catchment. It was found that the catchment-scale annual NEE was strongly positive with default parameter values but negative (and closer to observations) with the estimated values. Thus, the estimation of CLM parameters with local NEE observations can be highly relevant when determining regional carbon balances. To obtain a more comprehensive picture of model uncertainty, CLM ensembles were set up with perturbed meteorological input and uncertain initial states in addition to uncertain parameters. C3 grass and C3 crops were particularly sensitive to the perturbed meteorological input, which resulted in a strong increase in the standard deviation of the annual NEE sum (σ ∑ NEE) for the different ensemble members from  ∼ 2 to 3 g C m−2 yr−1 (with uncertain parameters) to  ∼ 45 g C m−2 yr−1 (C3 grass) and  ∼ 75 g C m−2 yr−1 (C3 crops) with perturbed forcings. This increase in uncertainty is related to the impact of the meteorological forcings on leaf onset and senescence, and enhanced/reduced drought stress related to perturbation of precipitation. The NEE uncertainty for the forest plant functional type (PFT) was considerably lower (σ ∑ NEE ∼ 4.0–13.5 g C m−2 yr−1 with perturbed parameters, meteorological forcings and initial states). We conclude that LAI and NEE uncertainty with CLM is clearly underestimated if uncertain meteorological forcings and initial states are not taken into account.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Biogeosciences},\n\tauthor = {Post, Hanna and Hendricks Franssen, Harrie-Jan and Han, Xujun and Baatz, Roland and Montzka, Carsten and Schmidt, Marius and Vereecken, Harry},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {187--208},\n}\n\n

\n

\n\n\n

\n Abstract. Modeling net ecosystem exchange (NEE) at the regional scale with land surface models (LSMs) is relevant for the estimation of regional carbon balances, but studies on it are very limited. Furthermore, it is essential to better understand and quantify the uncertainty of LSMs in order to improve them. An important key variable in this respect is the prognostic leaf area index (LAI), which is very sensitive to forcing data and strongly affects the modeled NEE. We applied the Community Land Model (CLM4.5-BGC) to the Rur catchment in western Germany and compared estimated and default ecological key parameters for modeling carbon fluxes and LAI. The parameter estimates were previously estimated with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) for four of the most widespread plant functional types in the catchment. It was found that the catchment-scale annual NEE was strongly positive with default parameter values but negative (and closer to observations) with the estimated values. Thus, the estimation of CLM parameters with local NEE observations can be highly relevant when determining regional carbon balances. To obtain a more comprehensive picture of model uncertainty, CLM ensembles were set up with perturbed meteorological input and uncertain initial states in addition to uncertain parameters. C3 grass and C3 crops were particularly sensitive to the perturbed meteorological input, which resulted in a strong increase in the standard deviation of the annual NEE sum (σ ∑ NEE) for the different ensemble members from ∼ 2 to 3 g C m−2 yr−1 (with uncertain parameters) to ∼ 45 g C m−2 yr−1 (C3 grass) and ∼ 75 g C m−2 yr−1 (C3 crops) with perturbed forcings. This increase in uncertainty is related to the impact of the meteorological forcings on leaf onset and senescence, and enhanced/reduced drought stress related to perturbation of precipitation. The NEE uncertainty for the forest plant functional type (PFT) was considerably lower (σ ∑ NEE ∼ 4.0–13.5 g C m−2 yr−1 with perturbed parameters, meteorological forcings and initial states). We conclude that LAI and NEE uncertainty with CLM is clearly underestimated if uncertain meteorological forcings and initial states are not taken into account.\n

\n\n\n

\n \n\n \n \n Pütz, T.; Fank, J.; and Flury, M.\n\n\n \n \n \n \n \n Lysimeters in Vadose Zone Research.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 1–4. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Lysimeters$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{putz_lysimeters_2018,\n\ttitle = {Lysimeters in {Vadose} {Zone} {Research}},\n\tvolume = {17},\n\tissn = {1539-1663, 1539-1663},\n\turl = {https://onlinelibrary.wiley.com/doi/10.2136/vzj2018.02.0035},\n\tdoi = {10.2136/vzj2018.02.0035},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Pütz, Thomas and Fank, Johann and Flury, Markus},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {1--4},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Qiu, C.; Zhu, D.; Ciais, P.; Guenet, B.; Krinner, G.; Peng, S.; Aurela, M.; Bernhofer, C.; Brümmer, C.; Bret-Harte, S.; Chu, H.; Chen, J.; Desai, A. R.; Dušek, J.; Euskirchen, E. S.; Fortuniak, K.; Flanagan, L. B.; Friborg, T.; Grygoruk, M.; Gogo, S.; Grünwald, T.; Hansen, B. U.; Holl, D.; Humphreys, E.; Hurkuck, M.; Kiely, G.; Klatt, J.; Kutzbach, L.; Largeron, C.; Laggoun-Défarge, F.; Lund, M.; Lafleur, P. M.; Li, X.; Mammarella, I.; Merbold, L.; Nilsson, M. B.; Olejnik, J.; Ottosson-Löfvenius, M.; Oechel, W.; Parmentier, F. W.; Peichl, M.; Pirk, N.; Peltola, O.; Pawlak, W.; Rasse, D.; Rinne, J.; Shaver, G.; Schmid, H. P.; Sottocornola, M.; Steinbrecher, R.; Sachs, T.; Urbaniak, M.; Zona, D.; and Ziemblinska, K.\n\n\n \n \n \n \n \n ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO$_{\\textrm{2}}$, water, and energy fluxes on daily to annual scales.\n \n \n \n \n\n\n \n\n\n\n Geoscientific Model Development, 11(2): 497–519. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"ORCHIDEE-PEAT$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{qiu_orchidee-peat_2018,\n\ttitle = {{ORCHIDEE}-{PEAT} (revision 4596), a model for northern peatland {CO}$_{\\textrm{2}}$, water, and energy fluxes on daily to annual scales},\n\tvolume = {11},\n\tissn = {1991-9603},\n\turl = {https://gmd.copernicus.org/articles/11/497/2018/},\n\tdoi = {10.5194/gmd-11-497-2018},\n\tabstract = {Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 {\\textless} 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-16},\n\tjournal = {Geoscientific Model Development},\n\tauthor = {Qiu, Chunjing and Zhu, Dan and Ciais, Philippe and Guenet, Bertrand and Krinner, Gerhard and Peng, Shushi and Aurela, Mika and Bernhofer, Christian and Brümmer, Christian and Bret-Harte, Syndonia and Chu, Housen and Chen, Jiquan and Desai, Ankur R. and Dušek, Jiří and Euskirchen, Eugénie S. and Fortuniak, Krzysztof and Flanagan, Lawrence B. and Friborg, Thomas and Grygoruk, Mateusz and Gogo, Sébastien and Grünwald, Thomas and Hansen, Birger U. and Holl, David and Humphreys, Elyn and Hurkuck, Miriam and Kiely, Gerard and Klatt, Janina and Kutzbach, Lars and Largeron, Chloé and Laggoun-Défarge, Fatima and Lund, Magnus and Lafleur, Peter M. and Li, Xuefei and Mammarella, Ivan and Merbold, Lutz and Nilsson, Mats B. and Olejnik, Janusz and Ottosson-Löfvenius, Mikaell and Oechel, Walter and Parmentier, Frans-Jan W. and Peichl, Matthias and Pirk, Norbert and Peltola, Olli and Pawlak, Włodzimierz and Rasse, Daniel and Rinne, Janne and Shaver, Gaius and Schmid, Hans Peter and Sottocornola, Matteo and Steinbrecher, Rainer and Sachs, Torsten and Urbaniak, Marek and Zona, Donatella and Ziemblinska, Klaudia},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {497--519},\n}\n\n

\n

\n\n\n

\n Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 \\textless 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.\n

\n\n\n

\n \n\n \n \n Rabbel, I.; Bogena, H.; Neuwirth, B.; and Diekkrüger, B.\n\n\n \n \n \n \n \n Using Sap Flow Data to Parameterize the Feddes Water Stress Model for Norway Spruce.\n \n \n \n \n\n\n \n\n\n\n Water, 10(3): 279. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{rabbel_using_2018,\n\ttitle = {Using {Sap} {Flow} {Data} to {Parameterize} the {Feddes} {Water} {Stress} {Model} for {Norway} {Spruce}},\n\tvolume = {10},\n\tissn = {2073-4441},\n\turl = {http://www.mdpi.com/2073-4441/10/3/279},\n\tdoi = {10.3390/w10030279},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Water},\n\tauthor = {Rabbel, Inken and Bogena, Heye and Neuwirth, Burkhard and Diekkrüger, Bernd},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {279},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Rabbel, I.; Neuwirth, B.; Bogena, H.; and Diekkrüger, B.\n\n\n \n \n \n \n \n Exploring the growth response of Norway spruce (Picea abies) along a small-scale gradient of soil water supply.\n \n \n \n \n\n\n \n\n\n\n Dendrochronologia, 52: 123–130. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{rabbel_exploring_2018,\n\ttitle = {Exploring the growth response of {Norway} spruce ({Picea} abies) along a small-scale gradient of soil water supply},\n\tvolume = {52},\n\tissn = {11257865},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1125786518301425},\n\tdoi = {10.1016/j.dendro.2018.10.007},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Dendrochronologia},\n\tauthor = {Rabbel, Inken and Neuwirth, Burkhard and Bogena, Heye and Diekkrüger, Bernd},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {123--130},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Rahmati, M.; Weihermüller, L.; Vanderborght, J.; Pachepsky, Y. A.; Mao, L.; Sadeghi, S. H.; Moosavi, N.; Kheirfam, H.; Montzka, C.; Van Looy, K.; Toth, B.; Hazbavi, Z.; Al Yamani, W.; Albalasmeh, A. A.; Alghzawi, M. Z.; Angulo-Jaramillo, R.; Antonino, A. C. D.; Arampatzis, G.; Armindo, R. A.; Asadi, H.; Bamutaze, Y.; Batlle-Aguilar, J.; Béchet, B.; Becker, F.; Blöschl, G.; Bohne, K.; Braud, I.; Castellano, C.; Cerdà, A.; Chalhoub, M.; Cichota, R.; Císlerová, M.; Clothier, B.; Coquet, Y.; Cornelis, W.; Corradini, C.; Coutinho, A. P.; de Oliveira, M. B.; de Macedo, J. R.; Durães, M. F.; Emami, H.; Eskandari, I.; Farajnia, A.; Flammini, A.; Fodor, N.; Gharaibeh, M.; Ghavimipanah, M. H.; Ghezzehei, T. A.; Giertz, S.; Hatzigiannakis, E. G.; Horn, R.; Jiménez, J. J.; Jacques, D.; Keesstra, S. D.; Kelishadi, H.; Kiani-Harchegani, M.; Kouselou, M.; Kumar Jha, M.; Lassabatere, L.; Li, X.; Liebig, M. A.; Lichner, L.; López, M. V.; Machiwal, D.; Mallants, D.; Mallmann, M. S.; de Oliveira Marques, J. D.; Marshall, M. R.; Mertens, J.; Meunier, F.; Mohammadi, M. H.; Mohanty, B. P.; Pulido-Moncada, M.; Montenegro, S.; Morbidelli, R.; Moret-Fernández, D.; Moosavi, A. A.; Mosaddeghi, M. R.; Mousavi, S. B.; Mozaffari, H.; Nabiollahi, K.; Neyshabouri, M. R.; Ottoni, M. V.; Ottoni Filho, T. B.; Pahlavan-Rad, M. R.; Panagopoulos, A.; Peth, S.; Peyneau, P.; Picciafuoco, T.; Poesen, J.; Pulido, M.; Reinert, D. J.; Reinsch, S.; Rezaei, M.; Roberts, F. P.; Robinson, D.; Rodrigo-Comino, J.; Rotunno Filho, O. C.; Saito, T.; Suganuma, H.; Saltalippi, C.; Sándor, R.; Schütt, B.; Seeger, M.; Sepehrnia, N.; Sharifi Moghaddam, E.; Shukla, M.; Shutaro, S.; Sorando, R.; Stanley, A. A.; Strauss, P.; Su, Z.; Taghizadeh-Mehrjardi, R.; Taguas, E.; Teixeira, W. G.; Vaezi, A. R.; Vafakhah, M.; Vogel, T.; Vogeler, I.; Votrubova, J.; Werner, S.; Winarski, T.; Yilmaz, D.; Young, M. H.; Zacharias, S.; Zeng, Y.; Zhao, Y.; Zhao, H.; and Vereecken, H.\n\n\n \n \n \n \n \n Development and analysis of the Soil Water Infiltration Global database.\n \n \n \n \n\n\n \n\n\n\n Earth System Science Data, 10(3): 1237–1263. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Development$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{rahmati_development_2018,\n\ttitle = {Development and analysis of the {Soil} {Water} {Infiltration} {Global} database},\n\tvolume = {10},\n\tissn = {1866-3516},\n\turl = {https://essd.copernicus.org/articles/10/1237/2018/},\n\tdoi = {10.5194/essd-10-1237-2018},\n\tabstract = {Abstract. In this paper, we present and analyze a novel global database of\nsoil infiltration measurements, the Soil Water Infiltration Global (SWIG)\ndatabase. In total, 5023 infiltration curves were collected across all\ncontinents in the SWIG database. These data were either provided and quality\nchecked by the scientists who performed the experiments or they were\ndigitized from published articles. Data from 54 different countries were\nincluded in the database with major contributions from Iran, China, and the USA.\nIn addition to its extensive geographical coverage, the collected\ninfiltration curves cover research from 1976 to late 2017. Basic information\non measurement location and method, soil properties, and land use was\ngathered along with the infiltration data, making the database valuable for\nthe development of pedotransfer functions (PTFs) for estimating soil hydraulic\nproperties, for the evaluation of infiltration measurement methods, and for\ndeveloping and validating infiltration models. Soil textural information\n(clay, silt, and sand content) is available for 3842 out of 5023 infiltration\nmeasurements (∼ 76\\%) covering nearly all soil USDA textural classes\nexcept for the sandy clay and silt classes. Information on land use is\navailable for 76 \\% of the experimental sites with agricultural land use as\nthe dominant type (∼ 40\\%). We are convinced that the SWIG database\nwill allow for a better parameterization of the infiltration process in land\nsurface models and for testing infiltration models. All collected data and\nrelated soil characteristics are provided online in\n*.xlsx and *.csv formats for reference, and we add a disclaimer that the\ndatabase is for public domain use only and can be copied freely by\nreferencing it. Supplementary data are available at\nhttps://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data\nquality assessment is strongly advised prior to any use of this database.\nFinally, we would like to encourage scientists to extend and update the SWIG database\nby uploading new data to it.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Earth System Science Data},\n\tauthor = {Rahmati, Mehdi and Weihermüller, Lutz and Vanderborght, Jan and Pachepsky, Yakov A. and Mao, Lili and Sadeghi, Seyed Hamidreza and Moosavi, Niloofar and Kheirfam, Hossein and Montzka, Carsten and Van Looy, Kris and Toth, Brigitta and Hazbavi, Zeinab and Al Yamani, Wafa and Albalasmeh, Ammar A. and Alghzawi, Ma'in Z. and Angulo-Jaramillo, Rafael and Antonino, Antônio Celso Dantas and Arampatzis, George and Armindo, Robson André and Asadi, Hossein and Bamutaze, Yazidhi and Batlle-Aguilar, Jordi and Béchet, Béatrice and Becker, Fabian and Blöschl, Günter and Bohne, Klaus and Braud, Isabelle and Castellano, Clara and Cerdà, Artemi and Chalhoub, Maha and Cichota, Rogerio and Císlerová, Milena and Clothier, Brent and Coquet, Yves and Cornelis, Wim and Corradini, Corrado and Coutinho, Artur Paiva and de Oliveira, Muriel Bastista and de Macedo, José Ronaldo and Durães, Matheus Fonseca and Emami, Hojat and Eskandari, Iraj and Farajnia, Asghar and Flammini, Alessia and Fodor, Nándor and Gharaibeh, Mamoun and Ghavimipanah, Mohamad Hossein and Ghezzehei, Teamrat A. and Giertz, Simone and Hatzigiannakis, Evangelos G. and Horn, Rainer and Jiménez, Juan José and Jacques, Diederik and Keesstra, Saskia Deborah and Kelishadi, Hamid and Kiani-Harchegani, Mahboobeh and Kouselou, Mehdi and Kumar Jha, Madan and Lassabatere, Laurent and Li, Xiaoyan and Liebig, Mark A. and Lichner, Lubomír and López, María Victoria and Machiwal, Deepesh and Mallants, Dirk and Mallmann, Micael Stolben and de Oliveira Marques, Jean Dalmo and Marshall, Miles R. and Mertens, Jan and Meunier, Félicien and Mohammadi, Mohammad Hossein and Mohanty, Binayak P. and Pulido-Moncada, Mansonia and Montenegro, Suzana and Morbidelli, Renato and Moret-Fernández, David and Moosavi, Ali Akbar and Mosaddeghi, Mohammad Reza and Mousavi, Seyed Bahman and Mozaffari, Hasan and Nabiollahi, Kamal and Neyshabouri, Mohammad Reza and Ottoni, Marta Vasconcelos and Ottoni Filho, Theophilo Benedicto and Pahlavan-Rad, Mohammad Reza and Panagopoulos, Andreas and Peth, Stephan and Peyneau, Pierre-Emmanuel and Picciafuoco, Tommaso and Poesen, Jean and Pulido, Manuel and Reinert, Dalvan José and Reinsch, Sabine and Rezaei, Meisam and Roberts, Francis Parry and Robinson, David and Rodrigo-Comino, Jesús and Rotunno Filho, Otto Corrêa and Saito, Tadaomi and Suganuma, Hideki and Saltalippi, Carla and Sándor, Renáta and Schütt, Brigitta and Seeger, Manuel and Sepehrnia, Nasrollah and Sharifi Moghaddam, Ehsan and Shukla, Manoj and Shutaro, Shiraki and Sorando, Ricardo and Stanley, Ajayi Asishana and Strauss, Peter and Su, Zhongbo and Taghizadeh-Mehrjardi, Ruhollah and Taguas, Encarnación and Teixeira, Wenceslau Geraldes and Vaezi, Ali Reza and Vafakhah, Mehdi and Vogel, Tomas and Vogeler, Iris and Votrubova, Jana and Werner, Steffen and Winarski, Thierry and Yilmaz, Deniz and Young, Michael H. and Zacharias, Steffen and Zeng, Yijian and Zhao, Ying and Zhao, Hong and Vereecken, Harry},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {1237--1263},\n}\n\n

\n

\n\n\n

\n Abstract. In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76 % of the experimental sites with agricultural land use as the dominant type (∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.\n

\n\n\n

\n \n\n \n \n Rebmann, C.; Aubinet, M.; Schmid, H.; Arriga, N.; Aurela, M.; Burba, G.; Clement, R.; De Ligne, A.; Fratini, G.; Gielen, B.; Grace, J.; Graf, A.; Gross, P.; Haapanala, S.; Herbst, M.; Hörtnagl, L.; Ibrom, A.; Joly, L.; Kljun, N.; Kolle, O.; Kowalski, A.; Lindroth, A.; Loustau, D.; Mammarella, I.; Mauder, M.; Merbold, L.; Metzger, S.; Mölder, M.; Montagnani, L.; Papale, D.; Pavelka, M.; Peichl, M.; Roland, M.; Serrano-Ortiz, P.; Siebicke, L.; Steinbrecher, R.; Tuovinen, J.; Vesala, T.; Wohlfahrt, G.; and Franz, D.\n\n\n \n \n \n \n \n ICOS eddy covariance flux-station site setup: a review.\n \n \n \n \n\n\n \n\n\n\n International Agrophysics, 32(4): 471–494. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"ICOS$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{rebmann_icos_2018,\n\ttitle = {{ICOS} eddy covariance flux-station site setup: a review},\n\tvolume = {32},\n\tissn = {2300-8725},\n\tshorttitle = {{ICOS} eddy covariance flux-station site setup},\n\turl = {http://archive.sciendo.com/INTAG/intag.2017.32.issue-4/intag-2017-0044/intag-2017-0044.pdf},\n\tdoi = {10.1515/intag-2017-0044},\n\tabstract = {Abstract \n            The Integrated Carbon Observation System Research Infrastructure aims to provide long-term, continuous observations of sources and sinks of greenhouse gases such as carbon dioxide, methane, nitrous oxide, and water vapour. At ICOS ecosystem stations, the principal technique for measurements of ecosystem-atmosphere exchange of GHGs is the eddy-covariance technique. The establishment and setup of an eddy-covariance tower have to be carefully reasoned to ensure high quality flux measurements being representative of the investigated ecosystem and comparable to measurements at other stations. To fulfill the requirements needed for flux determination with the eddy-covariance technique, variations in GHG concentrations have to be measured at high frequency, simultaneously with the wind velocity, in order to fully capture turbulent fluctuations. This requires the use of high-frequency gas analysers and ultrasonic anemometers. In addition, to analyse flux data with respect to environmental conditions but also to enable corrections in the post-processing procedures, it is necessary to measure additional abiotic variables in close vicinity to the flux measurements. Here we describe the standards the ICOS ecosystem station network has adopted for GHG flux measurements with respect to the setup of instrumentation on towers to maximize measurement precision and accuracy while allowing for flexibility in order to observe specific ecosystem features.},\n\tnumber = {4},\n\turldate = {2022-11-16},\n\tjournal = {International Agrophysics},\n\tauthor = {Rebmann, Corinna and Aubinet, Marc and Schmid, HaPe and Arriga, Nicola and Aurela, Mika and Burba, George and Clement, Robert and De Ligne, Anne and Fratini, Gerardo and Gielen, Bert and Grace, John and Graf, Alexander and Gross, Patrick and Haapanala, Sami and Herbst, Mathias and Hörtnagl, Lukas and Ibrom, Andreas and Joly, Lilian and Kljun, Natascha and Kolle, Olaf and Kowalski, Andrew and Lindroth, Anders and Loustau, Denis and Mammarella, Ivan and Mauder, Matthias and Merbold, Lutz and Metzger, Stefan and Mölder, Meelis and Montagnani, Leonardo and Papale, Dario and Pavelka, Marian and Peichl, Matthias and Roland, Marilyn and Serrano-Ortiz, Penélope and Siebicke, Lukas and Steinbrecher, Rainer and Tuovinen, Juha-Pekka and Vesala, Timo and Wohlfahrt, Georg and Franz, Daniela},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {471--494},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Rink, K.; Chen, C.; Bilke, L.; Liao, Z.; Rinke, K.; Frassl, M.; Yue, T.; and Kolditz, O.\n\n\n \n \n \n \n \n Virtual geographic environments for water pollution control.\n \n \n \n \n\n\n \n\n\n\n International Journal of Digital Earth, 11(4): 397–407. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Virtual$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{rink_virtual_2018,\n\ttitle = {Virtual geographic environments for water pollution control},\n\tvolume = {11},\n\tissn = {1753-8947, 1753-8955},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/17538947.2016.1265016},\n\tdoi = {10.1080/17538947.2016.1265016},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2023-01-23},\n\tjournal = {International Journal of Digital Earth},\n\tauthor = {Rink, Karsten and Chen, Cui and Bilke, Lars and Liao, Zhenliang and Rinke, Karsten and Frassl, Marieke and Yue, Tianxiang and Kolditz, Olaf},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {397--407},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Robinet, J.; von Hebel, C.; Govers, G.; van der Kruk, J.; Minella, J. P.; Schlesner, A.; Ameijeiras-Mariño, Y.; and Vanderborght, J.\n\n\n \n \n \n \n \n Spatial variability of soil water content and soil electrical conductivity across scales derived from Electromagnetic Induction and Time Domain Reflectometry.\n \n \n \n \n\n\n \n\n\n\n Geoderma, 314: 160–174. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{robinet_spatial_2018,\n\ttitle = {Spatial variability of soil water content and soil electrical conductivity across scales derived from {Electromagnetic} {Induction} and {Time} {Domain} {Reflectometry}},\n\tvolume = {314},\n\tissn = {00167061},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0016706117307875},\n\tdoi = {10.1016/j.geoderma.2017.10.045},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Geoderma},\n\tauthor = {Robinet, Jérémy and von Hebel, Christian and Govers, Gerard and van der Kruk, Jan and Minella, Jean P.G. and Schlesner, Alexandre and Ameijeiras-Mariño, Yolanda and Vanderborght, Jan},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {160--174},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Romero-Ruiz, A.; Linde, N.; Keller, T.; and Or, D.\n\n\n \n \n \n \n \n A Review of Geophysical Methods for Soil Structure Characterization: GEOPHYSICS AND SOIL STRUCTURE.\n \n \n \n \n\n\n \n\n\n\n Reviews of Geophysics, 56(4): 672–697. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{romero-ruiz_review_2018,\n\ttitle = {A {Review} of {Geophysical} {Methods} for {Soil} {Structure} {Characterization}: {GEOPHYSICS} {AND} {SOIL} {STRUCTURE}},\n\tvolume = {56},\n\tissn = {87551209},\n\tshorttitle = {A {Review} of {Geophysical} {Methods} for {Soil} {Structure} {Characterization}},\n\turl = {http://doi.wiley.com/10.1029/2018RG000611},\n\tdoi = {10.1029/2018RG000611},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2022-11-16},\n\tjournal = {Reviews of Geophysics},\n\tauthor = {Romero-Ruiz, Alejandro and Linde, Niklas and Keller, Thomas and Or, Dani},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {672--697},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Russo, R.; Becker, J. M.; and Liess, M.\n\n\n \n \n \n \n \n Sequential exposure to low levels of pesticides and temperature stress increase toxicological sensitivity of crustaceans.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 610-611: 563–569. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Sequential$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{russo_sequential_2018,\n\ttitle = {Sequential exposure to low levels of pesticides and temperature stress increase toxicological sensitivity of crustaceans},\n\tvolume = {610-611},\n\tissn = {00489697},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969717320715},\n\tdoi = {10.1016/j.scitotenv.2017.08.073},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Russo, Renato and Becker, Jeremias Martin and Liess, Matthias},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {563--569},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Sabbatini, S.; Mammarella, I.; Arriga, N.; Fratini, G.; Graf, A.; Hörtnagl, L.; Ibrom, A.; Longdoz, B.; Mauder, M.; Merbold, L.; Metzger, S.; Montagnani, L.; Pitacco, A.; Rebmann, C.; Sedlák, P.; Šigut, L.; Vitale, D.; and Papale, D.\n\n\n \n \n \n \n \n Eddy covariance raw data processing for CO$_{\\textrm{2}}$ and energy fluxes calculation at ICOS ecosystem stations.\n \n \n \n \n\n\n \n\n\n\n International Agrophysics, 32(4): 495–515. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Eddy$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{sabbatini_eddy_2018,\n\ttitle = {Eddy covariance raw data processing for {CO}$_{\\textrm{2}}$ and energy fluxes calculation at {ICOS} ecosystem stations},\n\tvolume = {32},\n\tissn = {2300-8725},\n\turl = {http://archive.sciendo.com/INTAG/intag.2017.32.issue-4/intag-2017-0043/intag-2017-0043.pdf},\n\tdoi = {10.1515/intag-2017-0043},\n\tabstract = {Abstract \n             \n              The eddy covariance is a powerful technique to estimate the surface-atmosphere exchange of different scalars at the ecosystem scale. The EC method is central to the ecosystem component of the Integrated Carbon Observation System, a monitoring network for greenhouse gases across the European Continent. The data processing sequence applied to the collected raw data is complex, and multiple robust options for the different steps are often available. For Integrated Carbon Observation System and similar networks, the standardisation of methods is essential to avoid methodological biases and improve comparability of the results. We introduce here the steps of the processing chain applied to the eddy covariance data of Integrated Carbon Observation System stations for the estimation of final CO \n              2 \n              , water and energy fluxes, including the calculation of their uncertainties. The selected methods are discussed against valid alternative options in terms of suitability and respective drawbacks and advantages. The main challenge is to warrant standardised processing for all stations in spite of the large differences in \n              e.g \n              . ecosystem traits and site conditions. The main achievement of the Integrated Carbon Observation System eddy covariance data processing is making CO \n              2 \n              and energy flux results as comparable and reliable as possible, given the current micrometeorological understanding and the generally accepted state-of-the-art processing methods.},\n\tnumber = {4},\n\turldate = {2022-11-16},\n\tjournal = {International Agrophysics},\n\tauthor = {Sabbatini, Simone and Mammarella, Ivan and Arriga, Nicola and Fratini, Gerardo and Graf, Alexander and Hörtnagl, Lukas and Ibrom, Andreas and Longdoz, Bernard and Mauder, Matthias and Merbold, Lutz and Metzger, Stefan and Montagnani, Leonardo and Pitacco, Andrea and Rebmann, Corinna and Sedlák, Pavel and Šigut, Ladislav and Vitale, Domenico and Papale, Dario},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {495--515},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Schmidt, J.; and Hauck, J.\n\n\n \n \n \n \n \n Implementing green infrastructure policy in agricultural landscapes—scenarios for Saxony-Anhalt, Germany.\n \n \n \n \n\n\n \n\n\n\n Regional Environmental Change, 18(3): 899–911. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Implementing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{schmidt_implementing_2018,\n\ttitle = {Implementing green infrastructure policy in agricultural landscapes—scenarios for {Saxony}-{Anhalt}, {Germany}},\n\tvolume = {18},\n\tissn = {1436-3798, 1436-378X},\n\turl = {http://link.springer.com/10.1007/s10113-017-1241-2},\n\tdoi = {10.1007/s10113-017-1241-2},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Regional Environmental Change},\n\tauthor = {Schmidt, Jenny and Hauck, Jennifer},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {899--911},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Schrön, M.; Rosolem, R.; Köhli, M.; Piussi, L.; Schröter, I.; Iwema, J.; Kögler, S.; Oswald, S. E.; Wollschläger, U.; Samaniego, L.; Dietrich, P.; and Zacharias, S.\n\n\n \n \n \n \n \n Cosmic-ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 54(9): 6441–6459. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Cosmic-ray$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{schron_cosmic-ray_2018,\n\ttitle = {Cosmic-ray {Neutron} {Rover} {Surveys} of {Field} {Soil} {Moisture} and the {Influence} of {Roads}},\n\tvolume = {54},\n\tissn = {00431397},\n\turl = {http://doi.wiley.com/10.1029/2017WR021719},\n\tdoi = {10.1029/2017WR021719},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2022-11-16},\n\tjournal = {Water Resources Research},\n\tauthor = {Schrön, M. and Rosolem, R. and Köhli, M. and Piussi, L. and Schröter, I. and Iwema, J. and Kögler, S. and Oswald, S. E. and Wollschläger, U. and Samaniego, L. and Dietrich, P. and Zacharias, S.},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {6441--6459},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Schrön, M.; Zacharias, S.; Womack, G.; Köhli, M.; Desilets, D.; Oswald, S. E.; Bumberger, J.; Mollenhauer, H.; Kögler, S.; Remmler, P.; Kasner, M.; Denk, A.; and Dietrich, P.\n\n\n \n \n \n \n \n Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment.\n \n \n \n \n\n\n \n\n\n\n Geoscientific Instrumentation, Methods and Data Systems, 7(1): 83–99. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Intercomparison$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{schron_intercomparison_2018,\n\ttitle = {Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment},\n\tvolume = {7},\n\tissn = {2193-0864},\n\turl = {https://gi.copernicus.org/articles/7/83/2018/},\n\tdoi = {10.5194/gi-7-83-2018},\n\tabstract = {Abstract. Sensor-to-sensor variability is a source of error common to all\ngeoscientific instruments that needs to be assessed before comparative and\napplied research can be performed with multiple sensors. Consistency among\nsensor systems is especially critical when subtle features of the surrounding\nterrain are to be identified. Cosmic-ray neutron sensors (CRNSs) are a recent\ntechnology used to monitor hectometre-scale environmental water\nstorages, for which a rigorous comparison study of numerous co-located\nsensors has not yet been performed. In this work, nine stationary CRNS probes\nof type “CRS1000” were installed in relative proximity on a grass patch\nsurrounded by trees, buildings, and sealed areas. While the dynamics of the\nneutron count rates were found to be similar, offsets of a few percent from\nthe absolute average neutron count rates were found. Technical adjustments of\nthe individual detection parameters brought all instruments into good\nagreement. Furthermore, we found a critical integration time of 6 h above\nwhich all sensors showed consistent dynamics in the data and their RMSE fell\nbelow 1 \\% of gravimetric water content. The residual differences between\nthe nine signals indicated local effects of the complex urban terrain on the\nscale of several metres. Mobile CRNS measurements and spatial simulations\nwith the URANOS neutron transport code in the surrounding area (25 ha)\nhave revealed substantial sub-footprint heterogeneity to which CRNS detectors\nare sensitive despite their large averaging volume. The sealed and constantly\ndry structures in the footprint furthermore damped the dynamics of the CRNS-derived soil moisture. We developed strategies to correct for the sealed-area\neffect based on theoretical insights about the spatial sensitivity of the\nsensor. This procedure not only led to reliable soil moisture estimation\nduring dry-out periods, it further revealed a strong signal of intercepted\nwater that emerged over the sealed surfaces during rain events. The presented\narrangement offered a unique opportunity to demonstrate the CRNS performance\nin complex terrain, and the results indicated great potential for further\napplications in urban climate research.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Geoscientific Instrumentation, Methods and Data Systems},\n\tauthor = {Schrön, Martin and Zacharias, Steffen and Womack, Gary and Köhli, Markus and Desilets, Darin and Oswald, Sascha E. and Bumberger, Jan and Mollenhauer, Hannes and Kögler, Simon and Remmler, Paul and Kasner, Mandy and Denk, Astrid and Dietrich, Peter},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {83--99},\n}\n\n

\n

\n\n\n

\n Abstract. Sensor-to-sensor variability is a source of error common to all geoscientific instruments that needs to be assessed before comparative and applied research can be performed with multiple sensors. Consistency among sensor systems is especially critical when subtle features of the surrounding terrain are to be identified. Cosmic-ray neutron sensors (CRNSs) are a recent technology used to monitor hectometre-scale environmental water storages, for which a rigorous comparison study of numerous co-located sensors has not yet been performed. In this work, nine stationary CRNS probes of type “CRS1000” were installed in relative proximity on a grass patch surrounded by trees, buildings, and sealed areas. While the dynamics of the neutron count rates were found to be similar, offsets of a few percent from the absolute average neutron count rates were found. Technical adjustments of the individual detection parameters brought all instruments into good agreement. Furthermore, we found a critical integration time of 6 h above which all sensors showed consistent dynamics in the data and their RMSE fell below 1 % of gravimetric water content. The residual differences between the nine signals indicated local effects of the complex urban terrain on the scale of several metres. Mobile CRNS measurements and spatial simulations with the URANOS neutron transport code in the surrounding area (25 ha) have revealed substantial sub-footprint heterogeneity to which CRNS detectors are sensitive despite their large averaging volume. The sealed and constantly dry structures in the footprint furthermore damped the dynamics of the CRNS-derived soil moisture. We developed strategies to correct for the sealed-area effect based on theoretical insights about the spatial sensitivity of the sensor. This procedure not only led to reliable soil moisture estimation during dry-out periods, it further revealed a strong signal of intercepted water that emerged over the sealed surfaces during rain events. The presented arrangement offered a unique opportunity to demonstrate the CRNS performance in complex terrain, and the results indicated great potential for further applications in urban climate research.\n

\n\n\n

\n \n\n \n \n Schwank, M.; and Naderpour, R.\n\n\n \n \n \n \n \n Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: Melting Effects.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 10(3): 354. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Snow$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{schwank_snow_2018,\n\ttitle = {Snow {Density} and {Ground} {Permittivity} {Retrieved} from {L}-{Band} {Radiometry}: {Melting} {Effects}},\n\tvolume = {10},\n\tissn = {2072-4292},\n\tshorttitle = {Snow {Density} and {Ground} {Permittivity} {Retrieved} from {L}-{Band} {Radiometry}},\n\turl = {http://www.mdpi.com/2072-4292/10/2/354},\n\tdoi = {10.3390/rs10020354},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing},\n\tauthor = {Schwank, Mike and Naderpour, Reza},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {354},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Shahid, N.; Becker, J. M.; Krauss, M.; Brack, W.; and Liess, M.\n\n\n \n \n \n \n \n Pesticide Body Burden of the Crustacean Gammarus pulex as a Measure of Toxic Pressure in Agricultural Streams.\n \n \n \n \n\n\n \n\n\n\n Environmental Science & Technology, 52(14): 7823–7832. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Pesticide$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{shahid_pesticide_2018,\n\ttitle = {Pesticide {Body} {Burden} of the {Crustacean} {Gammarus} pulex as a {Measure} of {Toxic} {Pressure} in {Agricultural} {Streams}},\n\tvolume = {52},\n\tissn = {0013-936X, 1520-5851},\n\turl = {https://pubs.acs.org/doi/10.1021/acs.est.8b01751},\n\tdoi = {10.1021/acs.est.8b01751},\n\tlanguage = {en},\n\tnumber = {14},\n\turldate = {2022-11-16},\n\tjournal = {Environmental Science \\& Technology},\n\tauthor = {Shahid, Naeem and Becker, Jeremias Martin and Krauss, Martin and Brack, Werner and Liess, Matthias},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {7823--7832},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Shahid, N.; Becker, J. M.; Krauss, M.; Brack, W.; and Liess, M.\n\n\n \n \n \n \n \n Adaptation of Gammarus pulex to agricultural insecticide contamination in streams.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 621: 479–485. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Adaptation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{shahid_adaptation_2018,\n\ttitle = {Adaptation of {Gammarus} pulex to agricultural insecticide contamination in streams},\n\tvolume = {621},\n\tissn = {00489697},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969717332783},\n\tdoi = {10.1016/j.scitotenv.2017.11.220},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Shahid, Naeem and Becker, Jeremias Martin and Krauss, Martin and Brack, Werner and Liess, Matthias},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {479--485},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Shrestha, P.; Sulis, M.; Simmer, C.; and Kollet, S.\n\n\n \n \n \n \n \n Effects of horizontal grid resolution on evapotranspiration partitioning using TerrSysMP.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 557: 910–915. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Effects$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{shrestha_effects_2018,\n\ttitle = {Effects of horizontal grid resolution on evapotranspiration partitioning using {TerrSysMP}},\n\tvolume = {557},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169418300246},\n\tdoi = {10.1016/j.jhydrol.2018.01.024},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Shrestha, P. and Sulis, M. and Simmer, C. and Kollet, S.},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {910--915},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Siebers, N.; Abdelrahman, H.; Krause, L.; and Amelung, W.\n\n\n \n \n \n \n \n Bias in aggregate geometry and properties after disintegration and drying procedures.\n \n \n \n \n\n\n \n\n\n\n Geoderma, 313: 163–171. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Bias$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{siebers_bias_2018,\n\ttitle = {Bias in aggregate geometry and properties after disintegration and drying procedures},\n\tvolume = {313},\n\tissn = {00167061},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0016706117308455},\n\tdoi = {10.1016/j.geoderma.2017.10.028},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Geoderma},\n\tauthor = {Siebers, Nina and Abdelrahman, Hamada and Krause, Lars and Amelung, Wulf},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {163--171},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Siebers, N.; Bauke, S. L.; Tamburini, F.; and Amelung, W.\n\n\n \n \n \n \n \n Short-term impacts of forest clear-cut on P accessibility in soil microaggregates: An oxygen isotope study.\n \n \n \n \n\n\n \n\n\n\n Geoderma, 315: 59–64. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Short-term$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{siebers_short-term_2018,\n\ttitle = {Short-term impacts of forest clear-cut on {P} accessibility in soil microaggregates: {An} oxygen isotope study},\n\tvolume = {315},\n\tissn = {00167061},\n\tshorttitle = {Short-term impacts of forest clear-cut on {P} accessibility in soil microaggregates},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0016706117312879},\n\tdoi = {10.1016/j.geoderma.2017.11.024},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Geoderma},\n\tauthor = {Siebers, Nina and Bauke, Sara L. and Tamburini, Federica and Amelung, Wulf},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {59--64},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Soltani, M.; Laux, P.; Mauder, M.; and Kunstmann, H.\n\n\n \n \n \n \n \n Spatiotemporal variability and empirical Copula-based dependence structure of modeled and observed coupled water and energy fluxes.\n \n \n \n \n\n\n \n\n\n\n Hydrology Research, 49(5): 1396–1416. October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatiotemporal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{soltani_spatiotemporal_2018,\n\ttitle = {Spatiotemporal variability and empirical {Copula}-based dependence structure of modeled and observed coupled water and energy fluxes},\n\tvolume = {49},\n\tissn = {0029-1277, 2224-7955},\n\turl = {https://iwaponline.com/hr/article/49/5/1396/38883/Spatiotemporal-variability-and-empirical},\n\tdoi = {10.2166/nh.2018.163},\n\tabstract = {Abstract \n            The spatial variations of water and energy budgets are highly influenced by the heterogeneity of land-surface characteristics. We investigate the spatiotemporal variability and dependence structure patterns of water and energy fluxes along an elevation gradient. Our analysis is based on the application of the GEOtop model and empirical Copulas. It is performed for the Rott (∼55 km2) and Upper-Ammer (∼300 km2) catchments in the TERrestrial ENvironmental Observatories prealpine region over two recent summer episodes, as a test case. We found that GEOtop is capable of quantifying the spatiotemporal variability of the water and energy budgets with consideration for the elevation-gradient effect of this heterogeneous landscape, which is confirmed by the linear statistical metrics. Furthermore, the empirical Copula-based function reveals that the dependence structures between the measured and simulated hydrometeorological variables are similar either at upper or lower density maxima. This suggests a reasonable performance of the model, as the interaction of variables is described properly; however, the model shows poorer performance in the middle ranks of the data. It is concluded that the presented Copula-based model performance analysis is a valuable complement to traditional global performance model analyses.},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2022-11-16},\n\tjournal = {Hydrology Research},\n\tauthor = {Soltani, Mohsen and Laux, Patrick and Mauder, Matthias and Kunstmann, Harald},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {1396--1416},\n}\n\n

\n

\n\n\n\n\n\n

\n \n\n \n \n Soltani, M.; Mauder, M.; Laux, P.; and Kunstmann, H.\n\n\n \n \n \n \n \n Turbulent flux variability and energy balance closure in the TERENO prealpine observatory: a hydrometeorological data analysis.\n \n \n \n \n\n\n \n\n\n\n Theoretical and Applied Climatology, 133(3-4): 937–956. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Turbulent$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{soltani_turbulent_2018,\n\ttitle = {Turbulent flux variability and energy balance closure in the {TERENO} prealpine observatory: a hydrometeorological data analysis},\n\tvolume = {133},\n\tissn = {0177-798X, 1434-4483},\n\tshorttitle = {Turbulent flux variability and energy balance closure in the {TERENO} prealpine observatory},\n\turl = {http://link.springer.com/10.1007/s00704-017-2235-1},\n\tdoi = {10.1007/s00704-017-2235-1},\n\tlanguage = {en},\n\tnumber = {3-4},\n\turldate = {2022-11-16},\n\tjournal = {Theoretical and Applied Climatology},\n\tauthor = {Soltani, Mohsen and Mauder, Matthias and Laux, Patrick and Kunstmann, Harald},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {937--956},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Spengler, D.; Förster, M.; and Borg, E.\n\n\n \n \n \n \n \n Editorial.\n \n \n \n \n\n\n \n\n\n\n PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 86(2): 49–51. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Editorial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{spengler_editorial_2018,\n\ttitle = {Editorial},\n\tvolume = {86},\n\tissn = {2512-2789, 2512-2819},\n\turl = {http://link.springer.com/10.1007/s41064-018-0052-5},\n\tdoi = {10.1007/s41064-018-0052-5},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-16},\n\tjournal = {PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science},\n\tauthor = {Spengler, Daniel and Förster, Michael and Borg, Erik},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {49--51},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Sulis, M.; Keune, J.; Shrestha, P.; Simmer, C.; and Kollet, S. J.\n\n\n \n \n \n \n \n Quantifying the Impact of Subsurface-Land Surface Physical Processes on the Predictive Skill of Subseasonal Mesoscale Atmospheric Simulations.\n \n \n \n \n\n\n \n\n\n\n Journal of Geophysical Research: Atmospheres, 123(17): 9131–9151. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Quantifying$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{sulis_quantifying_2018,\n\ttitle = {Quantifying the {Impact} of {Subsurface}-{Land} {Surface} {Physical} {Processes} on the {Predictive} {Skill} of {Subseasonal} {Mesoscale} {Atmospheric} {Simulations}},\n\tvolume = {123},\n\tissn = {2169897X},\n\turl = {http://doi.wiley.com/10.1029/2017JD028187},\n\tdoi = {10.1029/2017JD028187},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2022-11-16},\n\tjournal = {Journal of Geophysical Research: Atmospheres},\n\tauthor = {Sulis, M. and Keune, J. and Shrestha, P. and Simmer, C. and Kollet, S. J.},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {9131--9151},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Sun, H.; Koal, P.; Gerl, G.; Schroll, R.; Gattinger, A.; Joergensen, R. G.; and Munch, J. C.\n\n\n \n \n \n \n \n Microbial communities and residues in robinia- and poplar-based alley-cropping systems under organic and integrated management.\n \n \n \n \n\n\n \n\n\n\n Agroforestry Systems, 92(1): 35–46. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Microbial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{sun_microbial_2018,\n\ttitle = {Microbial communities and residues in robinia- and poplar-based alley-cropping systems under organic and integrated management},\n\tvolume = {92},\n\tissn = {0167-4366, 1572-9680},\n\turl = {http://link.springer.com/10.1007/s10457-016-0009-x},\n\tdoi = {10.1007/s10457-016-0009-x},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Agroforestry Systems},\n\tauthor = {Sun, Hanyin and Koal, Philipp and Gerl, Georg and Schroll, Reiner and Gattinger, Andreas and Joergensen, Rainer Georg and Munch, Jean Charles},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {35--46},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Tauro, F.; Selker, J.; van de Giesen, N.; Abrate, T.; Uijlenhoet, R.; Porfiri, M.; Manfreda, S.; Caylor, K.; Moramarco, T.; Benveniste, J.; Ciraolo, G.; Estes, L.; Domeneghetti, A.; Perks, M. T.; Corbari, C.; Rabiei, E.; Ravazzani, G.; Bogena, H.; Harfouche, A.; Brocca, L.; Maltese, A.; Wickert, A.; Tarpanelli, A.; Good, S.; Lopez Alcala, J. M.; Petroselli, A.; Cudennec, C.; Blume, T.; Hut, R.; and Grimaldi, S.\n\n\n \n \n \n \n \n Measurements and Observations in the XXI century (MOXXI): innovation and multi-disciplinarity to sense the hydrological cycle.\n \n \n \n \n\n\n \n\n\n\n Hydrological Sciences Journal, 63(2): 169–196. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Measurements$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{tauro_measurements_2018,\n\ttitle = {Measurements and {Observations} in the {XXI} century ({MOXXI}): innovation and multi-disciplinarity to sense the hydrological cycle},\n\tvolume = {63},\n\tissn = {0262-6667, 2150-3435},\n\tshorttitle = {Measurements and {Observations} in the {XXI} century ({MOXXI})},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/02626667.2017.1420191},\n\tdoi = {10.1080/02626667.2017.1420191},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2022-11-16},\n\tjournal = {Hydrological Sciences Journal},\n\tauthor = {Tauro, Flavia and Selker, John and van de Giesen, Nick and Abrate, Tommaso and Uijlenhoet, Remko and Porfiri, Maurizio and Manfreda, Salvatore and Caylor, Kelly and Moramarco, Tommaso and Benveniste, Jerome and Ciraolo, Giuseppe and Estes, Lyndon and Domeneghetti, Alessio and Perks, Matthew T. and Corbari, Chiara and Rabiei, Ehsan and Ravazzani, Giovanni and Bogena, Heye and Harfouche, Antoine and Brocca, Luca and Maltese, Antonino and Wickert, Andy and Tarpanelli, Angelica and Good, Stephen and Lopez Alcala, Jose Manuel and Petroselli, Andrea and Cudennec, Christophe and Blume, Theresa and Hut, Rolf and Grimaldi, Salvatore},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {169--196},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Thomas, F. M; Rzepecki, A.; Lücke, A.; Wiekenkamp, I.; Rabbel, I.; Pütz, T.; and Neuwirth, B.\n\n\n \n \n \n \n \n Growth and wood isotopic signature of Norway spruce ( Picea abies ) along a small-scale gradient of soil moisture.\n \n \n \n \n\n\n \n\n\n\n Tree Physiology, 38(12): 1855–1870. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Growth$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{thomas_growth_2018,\n\ttitle = {Growth and wood isotopic signature of {Norway} spruce ( \\textit{{Picea} abies} ) along a small-scale gradient of soil moisture},\n\tvolume = {38},\n\tissn = {1758-4469},\n\turl = {https://academic.oup.com/treephys/article/38/12/1855/5108531},\n\tdoi = {10.1093/treephys/tpy100},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2022-11-16},\n\tjournal = {Tree Physiology},\n\tauthor = {Thomas, Frank M and Rzepecki, Andreas and Lücke, Andreas and Wiekenkamp, Inge and Rabbel, Inken and Pütz, Thomas and Neuwirth, Burkhard},\n\teditor = {Cernusak, Lucas},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {1855--1870},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Trauth, N.; Musolff, A.; Knöller, K.; Kaden, U. S.; Keller, T.; Werban, U.; and Fleckenstein, J. H.\n\n\n \n \n \n \n \n River water infiltration enhances denitrification efficiency in riparian groundwater.\n \n \n \n \n\n\n \n\n\n\n Water Research, 130: 185–199. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"River$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{trauth_river_2018,\n\ttitle = {River water infiltration enhances denitrification efficiency in riparian groundwater},\n\tvolume = {130},\n\tissn = {00431354},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0043135417309867},\n\tdoi = {10.1016/j.watres.2017.11.058},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Water Research},\n\tauthor = {Trauth, Nico and Musolff, Andreas and Knöller, Kay and Kaden, Ute S. and Keller, Toralf and Werban, Ulrike and Fleckenstein, Jan H.},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {185--199},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Trigo, I. F.; de Bruin, H.; Beyrich, F.; Bosveld, F. C.; Gavilán, P.; Groh, J.; and López-Urrea, R.\n\n\n \n \n \n \n \n Validation of reference evapotranspiration from Meteosat Second Generation (MSG) observations.\n \n \n \n \n\n\n \n\n\n\n Agricultural and Forest Meteorology, 259: 271–285. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Validation$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{trigo_validation_2018,\n\ttitle = {Validation of reference evapotranspiration from {Meteosat} {Second} {Generation} ({MSG}) observations},\n\tvolume = {259},\n\tissn = {01681923},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0168192318301606},\n\tdoi = {10.1016/j.agrformet.2018.05.008},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Agricultural and Forest Meteorology},\n\tauthor = {Trigo, Isabel F. and de Bruin, Henk and Beyrich, Frank and Bosveld, Fred C. and Gavilán, Pedro and Groh, Jannis and López-Urrea, Ramón},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {271--285},\n}\n\n

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\n \n\n \n \n Unger, A.; Drager, N.; Sips, M.; and Lehmann, D. J.\n\n\n \n \n \n \n \n Understanding a Sequence of Sequences: Visual Exploration of Categorical States in Lake Sediment Cores.\n \n \n \n \n\n\n \n\n\n\n IEEE Transactions on Visualization and Computer Graphics, 24(1): 66–76. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Understanding$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{unger_understanding_2018,\n\ttitle = {Understanding a {Sequence} of {Sequences}: {Visual} {Exploration} of {Categorical} {States} in {Lake} {Sediment} {Cores}},\n\tvolume = {24},\n\tissn = {1077-2626},\n\tshorttitle = {Understanding a {Sequence} of {Sequences}},\n\turl = {http://ieeexplore.ieee.org/document/8022969/},\n\tdoi = {10.1109/TVCG.2017.2744686},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {IEEE Transactions on Visualization and Computer Graphics},\n\tauthor = {Unger, Andrea and Drager, Nadine and Sips, Mike and Lehmann, Dirk J.},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {66--76},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Wagner, K.; Oswald, S. E.; and Frick, A.\n\n\n \n \n \n \n \n Multitemporal soil moisture monitoring by use of optical remote sensing data in a dike relocation area.\n \n \n \n \n\n\n \n\n\n\n In Neale, C. M.; and Maltese, A., editor(s), Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, pages 71, Berlin, Germany, October 2018. SPIE\n \n\n\n\n
\n\n\n\n \n \n $\"Multitemporal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@inproceedings{wagner_multitemporal_2018,\n\taddress = {Berlin, Germany},\n\ttitle = {Multitemporal soil moisture monitoring by use of optical remote sensing data in a dike relocation area},\n\tisbn = {9781510621497 9781510621503},\n\turl = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10783/2325319/Multitemporal-soil-moisture-monitoring-by-use-of-optical-remote-sensing/10.1117/12.2325319.full},\n\tdoi = {10.1117/12.2325319},\n\turldate = {2022-11-16},\n\tbooktitle = {Remote {Sensing} for {Agriculture}, {Ecosystems}, and {Hydrology} {XX}},\n\tpublisher = {SPIE},\n\tauthor = {Wagner, Kathrin and Oswald, Sascha E. and Frick, Annett},\n\teditor = {Neale, Christopher M. and Maltese, Antonino},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {71},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Wang, J.; Bogena, H. R.; Vereecken, H.; and Brüggemann, N.\n\n\n \n \n \n \n \n Characterizing Redox Potential Effects on Greenhouse Gas Emissions Induced by Water‐Level Changes.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 17(1): 1–13. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Characterizing$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{wang_characterizing_2018,\n\ttitle = {Characterizing {Redox} {Potential} {Effects} on {Greenhouse} {Gas} {Emissions} {Induced} by {Water}‐{Level} {Changes}},\n\tvolume = {17},\n\tissn = {1539-1663, 1539-1663},\n\turl = {https://onlinelibrary.wiley.com/doi/10.2136/vzj2017.08.0152},\n\tdoi = {10.2136/vzj2017.08.0152},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2022-11-16},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Wang, Jihuan and Bogena, Heye R. and Vereecken, Harry and Brüggemann, Nicolas},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {1--13},\n}\n\n

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\n \n\n \n \n Wen, X.; Unger, V.; Jurasinski, G.; Koebsch, F.; Horn, F.; Rehder, G.; Sachs, T.; Zak, D.; Lischeid, G.; Knorr, K.; Böttcher, M.; Winkel, M.; and Liebner, S.\n\n\n \n \n \n \n \n Predominance of methanogens over methanotrophs contributes to high methane emissions in rewetted fens.\n \n \n \n \n\n\n \n\n\n\n Technical Report Biogeochemistry: Environmental Microbiology, April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Predominance$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@techreport{wen_predominance_2018,\n\ttype = {preprint},\n\ttitle = {Predominance of methanogens over methanotrophs contributes to high methane emissions in rewetted fens},\n\turl = {https://bg.copernicus.org/preprints/bg-2018-184/bg-2018-184.pdf},\n\tabstract = {Abstract. The rewetting of drained peatlands alters peat geochemistry and often leads to sustained elevated methane emission. Although this methane is produced entirely by microbial activity, the distribution and abundance of methane-cycling microbes in rewetted peatlands, especially in fens, is rarely described. In this study, we compare the community composition and abundance of methane-cycling microbes in relation to peat porewater geochemistry in two rewetted fens in northeastern Germany, a coastal brackish fen and a freshwater riparian fen, with known high methane fluxes. We utilized 16S rDNA high-throughput sequencing and quantitative polymerase chain reaction on 16S rDNA, mcrA, and pmoA genes to determine microbial community composition and the abundance of total bacteria, methanogens, and methanotrophs. Electrical conductivity was more than three times higher in the coastal fen than in the riparian fen, averaging 5.3 and 1.5 mS cm−1, respectively. Porewater concentrations of terminal electron acceptors varied within and among the fens. This was also reflected in similarly high intra- and inter-site variations of microbial community composition. Despite these differences in environmental conditions and electron acceptor availability, we found a low abundance of methanotrophs and a high abundance of methanogens, represented in particular by Methanosaetaceae, in both fens. This suggests that rapid re/establishment of methanogens and slow re/establishment of methanotrophs contributes to prolonged increased methane emissions following rewetting.},\n\turldate = {2022-11-16},\n\tinstitution = {Biogeochemistry: Environmental Microbiology},\n\tauthor = {Wen, Xi and Unger, Viktoria and Jurasinski, Gerald and Koebsch, Franziska and Horn, Fabian and Rehder, Gregor and Sachs, Torsten and Zak, Dominik and Lischeid, Gunnar and Knorr, Klaus-Holger and Böttcher, Michael and Winkel, Matthias and Liebner, Susanne},\n\tmonth = apr,\n\tyear = {2018},\n\tdoi = {10.5194/bg-2018-184},\n}\n\n

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\n\n\n\n\n\n

\n \n\n \n \n Wentzky, V. C.; Tittel, J.; Jäger, C. G.; and Rinke, K.\n\n\n \n \n \n \n \n Mechanisms preventing a decrease in phytoplankton biomass after phosphorus reductions in a German drinking water reservoir-results from more than 50 years of observation.\n \n \n \n \n\n\n \n\n\n\n Freshwater Biology, 63(9): 1063–1076. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Mechanisms$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{wentzky_mechanisms_2018,\n\ttitle = {Mechanisms preventing a decrease in phytoplankton biomass after phosphorus reductions in a {German} drinking water reservoir-results from more than 50 years of observation},\n\tvolume = {63},\n\tissn = {00465070},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/fwb.13116},\n\tdoi = {10.1111/fwb.13116},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2022-11-16},\n\tjournal = {Freshwater Biology},\n\tauthor = {Wentzky, Valerie Carolin and Tittel, Jörg and Jäger, Christoph Gerald and Rinke, Karsten},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {1063--1076},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Wieneke, S.; Burkart, A.; Cendrero-Mateo, M.; Julitta, T.; Rossini, M.; Schickling, A.; Schmidt, M.; and Rascher, U.\n\n\n \n \n \n \n \n Linking photosynthesis and sun-induced fluorescence at sub-daily to seasonal scales.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing of Environment, 219: 247–258. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Linking$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{wieneke_linking_2018,\n\ttitle = {Linking photosynthesis and sun-induced fluorescence at sub-daily to seasonal scales},\n\tvolume = {219},\n\tissn = {00344257},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0034425718304759},\n\tdoi = {10.1016/j.rse.2018.10.019},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing of Environment},\n\tauthor = {Wieneke, S. and Burkart, A. and Cendrero-Mateo, M.P. and Julitta, T. and Rossini, M. and Schickling, A. and Schmidt, M. and Rascher, U.},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {247--258},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Wilken, F.; Baur, M.; Sommer, M.; Deumlich, D.; Bens, O.; and Fiener, P.\n\n\n \n \n \n \n \n Uncertainties in rainfall kinetic energy-intensity relations for soil erosion modelling.\n \n \n \n \n\n\n \n\n\n\n CATENA, 171: 234–244. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Uncertainties$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{wilken_uncertainties_2018,\n\ttitle = {Uncertainties in rainfall kinetic energy-intensity relations for soil erosion modelling},\n\tvolume = {171},\n\tissn = {03418162},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S034181621830273X},\n\tdoi = {10.1016/j.catena.2018.07.002},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {CATENA},\n\tauthor = {Wilken, Florian and Baur, Martin and Sommer, Michael and Deumlich, Detlef and Bens, Oliver and Fiener, Peter},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {234--244},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Wu, X.; Xiao, X.; Zhang, Y.; He, W.; Wolf, S.; Chen, J.; He, M.; Gough, C. M.; Qin, Y.; Zhou, Y.; Doughty, R.; and Blanken, P. D.\n\n\n \n \n \n \n \n Spatiotemporal Consistency of Four Gross Primary Production Products and Solar‐Induced Chlorophyll Fluorescence in Response to Climate Extremes Across CONUS in 2012.\n \n \n \n \n\n\n \n\n\n\n Journal of Geophysical Research: Biogeosciences, 123(10): 3140–3161. October 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatiotemporal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{wu_spatiotemporal_2018,\n\ttitle = {Spatiotemporal {Consistency} of {Four} {Gross} {Primary} {Production} {Products} and {Solar}‐{Induced} {Chlorophyll} {Fluorescence} in {Response} to {Climate} {Extremes} {Across} {CONUS} in 2012},\n\tvolume = {123},\n\tissn = {2169-8953, 2169-8961},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1029/2018JG004484},\n\tdoi = {10.1029/2018JG004484},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2022-11-16},\n\tjournal = {Journal of Geophysical Research: Biogeosciences},\n\tauthor = {Wu, Xiaocui and Xiao, Xiangming and Zhang, Yao and He, Wei and Wolf, Sebastian and Chen, Jiquan and He, Mingzhu and Gough, Christopher M. and Qin, Yuanwei and Zhou, Yanlian and Doughty, Russell and Blanken, Peter D.},\n\tmonth = oct,\n\tyear = {2018},\n\tpages = {3140--3161},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Yang, J.; Heidbüchel, I.; Musolff, A.; Reinstorf, F.; and Fleckenstein, J. H.\n\n\n \n \n \n \n \n Exploring the Dynamics of Transit Times and Subsurface Mixing in a Small Agricultural Catchment.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 54(3): 2317–2335. March 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{yang_exploring_2018,\n\ttitle = {Exploring the {Dynamics} of {Transit} {Times} and {Subsurface} {Mixing} in a {Small} {Agricultural} {Catchment}},\n\tvolume = {54},\n\tissn = {0043-1397, 1944-7973},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/2017WR021896},\n\tdoi = {10.1002/2017WR021896},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2022-11-16},\n\tjournal = {Water Resources Research},\n\tauthor = {Yang, Jie and Heidbüchel, Ingo and Musolff, Andreas and Reinstorf, Frido and Fleckenstein, Jan H.},\n\tmonth = mar,\n\tyear = {2018},\n\tpages = {2317--2335},\n}\n\n

\n

\n\n\n\n

\n \n\n \n \n Yang, X.; Jomaa, S.; Zink, M.; Fleckenstein, J. H.; Borchardt, D.; and Rode, M.\n\n\n \n \n \n \n \n A New Fully Distributed Model of Nitrate Transport and Removal at Catchment Scale.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 54(8): 5856–5877. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{yang_new_2018,\n\ttitle = {A {New} {Fully} {Distributed} {Model} of {Nitrate} {Transport} and {Removal} at {Catchment} {Scale}},\n\tvolume = {54},\n\tissn = {0043-1397, 1944-7973},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2017WR022380},\n\tdoi = {10.1029/2017WR022380},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2022-11-16},\n\tjournal = {Water Resources Research},\n\tauthor = {Yang, Xiaoqiang and Jomaa, Seifeddine and Zink, Matthias and Fleckenstein, Jan H. and Borchardt, Dietrich and Rode, Michael},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {5856--5877},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Zhang, H.; Kurtz, W.; Kollet, S.; Vereecken, H.; and Franssen, H. H.\n\n\n \n \n \n \n \n Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model.\n \n \n \n \n\n\n \n\n\n\n Advances in Water Resources, 111: 224–238. January 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Comparison$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{zhang_comparison_2018,\n\ttitle = {Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model},\n\tvolume = {111},\n\tissn = {03091708},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0309170817304888},\n\tdoi = {10.1016/j.advwatres.2017.11.003},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Advances in Water Resources},\n\tauthor = {Zhang, Hongjuan and Kurtz, Wolfgang and Kollet, Stefan and Vereecken, Harry and Franssen, Harrie-Jan Hendricks},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {224--238},\n}\n\n

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\n\n\n\n

\n \n\n \n \n Zhang, Y.; Xiao, X.; Wolf, S.; Wu, J.; Wu, X.; Gioli, B.; Wohlfahrt, G.; Cescatti, A.; van der Tol, C.; Zhou, S.; Gough, C. M.; Gentine, P.; Zhang, Y.; Steinbrecher, R.; and Ardö, J.\n\n\n \n \n \n \n \n Spatio‐Temporal Convergence of Maximum Daily Light‐Use Efficiency Based on Radiation Absorption by Canopy Chlorophyll.\n \n \n \n \n\n\n \n\n\n\n Geophysical Research Letters, 45(8): 3508–3519. April 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatio‐Temporal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{zhang_spatiotemporal_2018,\n\ttitle = {Spatio‐{Temporal} {Convergence} of {Maximum} {Daily} {Light}‐{Use} {Efficiency} {Based} on {Radiation} {Absorption} by {Canopy} {Chlorophyll}},\n\tvolume = {45},\n\tissn = {0094-8276, 1944-8007},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1029/2017GL076354},\n\tdoi = {10.1029/2017GL076354},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2022-11-16},\n\tjournal = {Geophysical Research Letters},\n\tauthor = {Zhang, Yao and Xiao, Xiangming and Wolf, Sebastian and Wu, Jin and Wu, Xiaocui and Gioli, Beniamino and Wohlfahrt, Georg and Cescatti, Alessandro and van der Tol, Christiaan and Zhou, Sha and Gough, Christopher M. and Gentine, Pierre and Zhang, Yongguang and Steinbrecher, Rainer and Ardö, Jonas},\n\tmonth = apr,\n\tyear = {2018},\n\tpages = {3508--3519},\n}\n\n

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\n \n\n \n \n Zhang, Y.; Xiao, X.; Zhang, Y.; Wolf, S.; Zhou, S.; Joiner, J.; Guanter, L.; Verma, M.; Sun, Y.; Yang, X.; Paul-Limoges, E.; Gough, C. M.; Wohlfahrt, G.; Gioli, B.; van der Tol, C.; Yann, N.; Lund, M.; and de Grandcourt, A.\n\n\n \n \n \n \n \n On the relationship between sub-daily instantaneous and daily total gross primary production: Implications for interpreting satellite-based SIF retrievals.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing of Environment, 205: 276–289. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{zhang_relationship_2018,\n\ttitle = {On the relationship between sub-daily instantaneous and daily total gross primary production: {Implications} for interpreting satellite-based {SIF} retrievals},\n\tvolume = {205},\n\tissn = {00344257},\n\tshorttitle = {On the relationship between sub-daily instantaneous and daily total gross primary production},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0034425717305801},\n\tdoi = {10.1016/j.rse.2017.12.009},\n\tlanguage = {en},\n\turldate = {2022-11-16},\n\tjournal = {Remote Sensing of Environment},\n\tauthor = {Zhang, Yao and Xiao, Xiangming and Zhang, Yongguang and Wolf, Sebastian and Zhou, Sha and Joiner, Joanna and Guanter, Luis and Verma, Manish and Sun, Ying and Yang, Xi and Paul-Limoges, Eugénie and Gough, Christopher M. and Wohlfahrt, Georg and Gioli, Beniamino and van der Tol, Christiaan and Yann, Nouvellon and Lund, Magnus and de Grandcourt, Agnès},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {276--289},\n}\n\n

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\n \n\n \n \n van der Kruk, J.; Liu, T.; Mozaffari, A.; Gueting, N.; Klotzsche, A.; Vereecken, H.; Warren, C.; and Giannopoulos, A.\n\n\n \n \n \n \n \n GPR full-waveform inversion, recent developments, and future opportunities.\n \n \n \n \n\n\n \n\n\n\n In 2018 17th International Conference on Ground Penetrating Radar (GPR), pages 1–6, Rapperswil, Switzerland, June 2018. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"GPR$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{van_der_kruk_gpr_2018,\n\taddress = {Rapperswil, Switzerland},\n\ttitle = {{GPR} full-waveform inversion, recent developments, and future opportunities},\n\tisbn = {9781538657775},\n\turl = {https://ieeexplore.ieee.org/document/8441667/},\n\tdoi = {10.1109/ICGPR.2018.8441667},\n\turldate = {2022-11-16},\n\tbooktitle = {2018 17th {International} {Conference} on {Ground} {Penetrating} {Radar} ({GPR})},\n\tpublisher = {IEEE},\n\tauthor = {van der Kruk, J. and Liu, T. and Mozaffari, A. and Gueting, N. and Klotzsche, A. and Vereecken, H. and Warren, C. and Giannopoulos, A.},\n\tmonth = jun,\n\tyear = {2018},\n\tpages = {1--6},\n}\n\n

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\n \n\n \n \n van der Maaten, E.; Pape, J.; van der Maaten-Theunissen, M.; Scharnweber, T.; Smiljanić, M.; Cruz-García, R.; and Wilmking, M.\n\n\n \n \n \n \n \n Distinct growth phenology but similar daily stem dynamics in three co-occurring broadleaved tree species.\n \n \n \n \n\n\n \n\n\n\n Tree Physiology, 38(12): 1820–1828. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Distinct$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{van_der_maaten_distinct_2018,\n\ttitle = {Distinct growth phenology but similar daily stem dynamics in three co-occurring broadleaved tree species},\n\tvolume = {38},\n\tissn = {1758-4469},\n\turl = {https://academic.oup.com/treephys/article/38/12/1820/4987942},\n\tdoi = {10.1093/treephys/tpy042},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2022-11-16},\n\tjournal = {Tree Physiology},\n\tauthor = {van der Maaten, Ernst and Pape, Jonas and van der Maaten-Theunissen, Marieke and Scharnweber, Tobias and Smiljanić, Marko and Cruz-García, Roberto and Wilmking, Martin},\n\teditor = {Mäkelä, Annikki},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {1820--1828},\n}\n\n

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\n \n\n \n \n von Hebel, C.; Matveeva, M.; Verweij, E.; Rademske, P.; Kaufmann, M. S.; Brogi, C.; Vereecken, H.; Rascher, U.; and van der Kruk, J.\n\n\n \n \n \n \n \n Understanding Soil and Plant Interaction by Combining Ground-Based Quantitative Electromagnetic Induction and Airborne Hyperspectral Data.\n \n \n \n \n\n\n \n\n\n\n Geophysical Research Letters, 45(15): 7571–7579. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Understanding$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{von_hebel_understanding_2018,\n\ttitle = {Understanding {Soil} and {Plant} {Interaction} by {Combining} {Ground}-{Based} {Quantitative} {Electromagnetic} {Induction} and {Airborne} {Hyperspectral} {Data}},\n\tvolume = {45},\n\tissn = {00948276},\n\turl = {http://doi.wiley.com/10.1029/2018GL078658},\n\tdoi = {10.1029/2018GL078658},\n\tlanguage = {en},\n\tnumber = {15},\n\turldate = {2022-11-16},\n\tjournal = {Geophysical Research Letters},\n\tauthor = {von Hebel, Christian and Matveeva, Maria and Verweij, Elizabeth and Rademske, Patrick and Kaufmann, Manuela Sarah and Brogi, Cosimo and Vereecken, Harry and Rascher, Uwe and van der Kruk, Jan},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {7571--7579},\n}\n\n

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