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\n  \n 2016\n \n \n (98)\n \n \n
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\n \n\n \n \n Al-Hazaimay, S.; Huisman, J. A.; Zimmermann, E.; and Vereecken, H.\n\n\n \n \n \n \n \n Using electrical anisotropy for structural characterization of sediments: an experimental validation study.\n \n \n \n \n\n\n \n\n\n\n Near Surface Geophysics, 14(4): 357–369. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"UsingPaper\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{al-hazaimay_using_2016,\n\ttitle = {Using electrical anisotropy for structural characterization of sediments: an experimental validation study},\n\tvolume = {14},\n\tissn = {15694445, 18730604},\n\tshorttitle = {Using electrical anisotropy for structural characterization of sediments},\n\turl = {http://doi.wiley.com/10.3997/1873-0604.2016026},\n\tdoi = {10.3997/1873-0604.2016026},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2023-01-23},\n\tjournal = {Near Surface Geophysics},\n\tauthor = {Al-Hazaimay, Sadam and Huisman, Johan A. and Zimmermann, Egon and Vereecken, Harry},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {357--369},\n}\n\n
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\n \n\n \n \n Altenkirch, N.; Zlatanovic, S.; Woodward, K. B.; Trauth, N.; Mutz, M.; and Mokenthin, F.\n\n\n \n \n \n \n \n “Untangling Hyporheic Residence time Distributions and Whole Stream” “Metabolism Using a Hydrological Process Model”.\n \n \n \n \n\n\n \n\n\n\n Procedia Engineering, 154: 1071–1078. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"“UntanglingPaper\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{altenkirch_untangling_2016,\n\ttitle = {“{Untangling} {Hyporheic} {Residence} time {Distributions} and {Whole} {Stream}” “{Metabolism} {Using} a {Hydrological} {Process} {Model}”},\n\tvolume = {154},\n\tissn = {18777058},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1877705816319877},\n\tdoi = {10.1016/j.proeng.2016.07.598},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Procedia Engineering},\n\tauthor = {Altenkirch, Nora and Zlatanovic, Sanja and Woodward, K. Benjamin and Trauth, Nico and Mutz, Michael and Mokenthin, Frank},\n\tyear = {2016},\n\tpages = {1071--1078},\n}\n\n
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\n \n\n \n \n Andreasen, M.; Jensen, K. H.; Zreda, M.; Desilets, D.; Bogena, H.; and Looms, M. C.\n\n\n \n \n \n \n \n Modeling cosmic ray neutron field measurements: MODELING COSMIC RAY NEUTRON FIELD MEASUREMENTS.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 52(8): 6451–6471. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ModelingPaper\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{andreasen_modeling_2016,\n\ttitle = {Modeling cosmic ray neutron field measurements: {MODELING} {COSMIC} {RAY} {NEUTRON} {FIELD} {MEASUREMENTS}},\n\tvolume = {52},\n\tissn = {00431397},\n\tshorttitle = {Modeling cosmic ray neutron field measurements},\n\turl = {http://doi.wiley.com/10.1002/2015WR018236},\n\tdoi = {10.1002/2015WR018236},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2023-01-23},\n\tjournal = {Water Resources Research},\n\tauthor = {Andreasen, Mie and Jensen, Karsten H. and Zreda, Marek and Desilets, Darin and Bogena, Heye and Looms, Majken C.},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {6451--6471},\n}\n\n
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\n \n\n \n \n Bircher, S.; Andreasen, M.; Vuollet, J.; Vehviläinen, J.; Rautiainen, K.; Jonard, F.; Weihermüller, L.; Zakharova, E.; Wigneron, J.; and Kerr, Y. H.\n\n\n \n \n \n \n \n Soil moisture sensor calibration for organic soil surface layers.\n \n \n \n \n\n\n \n\n\n\n Geoscientific Instrumentation, Methods and Data Systems, 5(1): 109–125. April 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SoilPaper\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{bircher_soil_2016,\n\ttitle = {Soil moisture sensor calibration for organic soil surface layers},\n\tvolume = {5},\n\tissn = {2193-0864},\n\turl = {https://gi.copernicus.org/articles/5/109/2016/},\n\tdoi = {10.5194/gi-5-109-2016},\n\tabstract = {Abstract. This paper's objective is to present generic calibration functions for organic surface layers derived for the soil moisture sensors Decagon ECH2O 5TE and Delta-T ThetaProbe ML2x, using material from northern regions, mainly from the Finnish Meteorological Institute's Arctic Research Center in Sodankylä and the study area of the Danish Center for Hydrology (HOBE). For the Decagon 5TE sensor such a function is currently not reported in the literature. Data were compared with measurements from underlying mineral soils including laboratory and field measurements. Shrinkage and charring during drying were considered. For both sensors all field and lab data showed consistent trends. For mineral layers with low soil organic matter (SOM) content the validity of the manufacturer's calibrations was demonstrated. Deviating sensor outputs in organic and mineral horizons were identified. For the Decagon 5TE, apparent relative permittivities at a given moisture content decreased for increased SOM content, which was attributed to an increase of bound water in organic materials with large specific surface areas compared to the studied mineral soils. ThetaProbe measurements from organic horizons showed stronger nonlinearity in the sensor response and signal saturation in the high-level data. The derived calibration fit functions between sensor response and volumetric water content hold for samples spanning a wide range of humus types with differing SOM characteristics. This strengthens confidence in their validity under various conditions, rendering them highly suitable for large-scale applications in remote sensing and land surface modeling studies. Agreement between independent Decagon 5TE and ThetaProbe time series from an organic surface layer at the Sodankylä site was significantly improved when the here-proposed fit functions were used. Decagon 5TE data also well-reflected precipitation events. Thus, Decagon 5TE network data from organic surface layers at the Sodankylä and HOBE sites are based on the here-proposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but prove to be of value for the acquisition of instantaneous large-scale soil moisture estimates.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-23},\n\tjournal = {Geoscientific Instrumentation, Methods and Data Systems},\n\tauthor = {Bircher, Simone and Andreasen, Mie and Vuollet, Johanna and Vehviläinen, Juho and Rautiainen, Kimmo and Jonard, François and Weihermüller, Lutz and Zakharova, Elena and Wigneron, Jean-Pierre and Kerr, Yann H.},\n\tmonth = apr,\n\tyear = {2016},\n\tpages = {109--125},\n}\n\n
\n
\n\n\n
\n Abstract. This paper's objective is to present generic calibration functions for organic surface layers derived for the soil moisture sensors Decagon ECH2O 5TE and Delta-T ThetaProbe ML2x, using material from northern regions, mainly from the Finnish Meteorological Institute's Arctic Research Center in Sodankylä and the study area of the Danish Center for Hydrology (HOBE). For the Decagon 5TE sensor such a function is currently not reported in the literature. Data were compared with measurements from underlying mineral soils including laboratory and field measurements. Shrinkage and charring during drying were considered. For both sensors all field and lab data showed consistent trends. For mineral layers with low soil organic matter (SOM) content the validity of the manufacturer's calibrations was demonstrated. Deviating sensor outputs in organic and mineral horizons were identified. For the Decagon 5TE, apparent relative permittivities at a given moisture content decreased for increased SOM content, which was attributed to an increase of bound water in organic materials with large specific surface areas compared to the studied mineral soils. ThetaProbe measurements from organic horizons showed stronger nonlinearity in the sensor response and signal saturation in the high-level data. The derived calibration fit functions between sensor response and volumetric water content hold for samples spanning a wide range of humus types with differing SOM characteristics. This strengthens confidence in their validity under various conditions, rendering them highly suitable for large-scale applications in remote sensing and land surface modeling studies. Agreement between independent Decagon 5TE and ThetaProbe time series from an organic surface layer at the Sodankylä site was significantly improved when the here-proposed fit functions were used. Decagon 5TE data also well-reflected precipitation events. Thus, Decagon 5TE network data from organic surface layers at the Sodankylä and HOBE sites are based on the here-proposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but prove to be of value for the acquisition of instantaneous large-scale soil moisture estimates.\n
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\n \n\n \n \n Bogena, H. R.\n\n\n \n \n \n \n \n TERENO: German network of terrestrial environmental observatories.\n \n \n \n \n\n\n \n\n\n\n Journal of large-scale research facilities JLSRF, 2: A52. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"TERENO: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 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{bogena_tereno_2016,\n\ttitle = {{TERENO}: {German} network of terrestrial environmental observatories},\n\tvolume = {2},\n\tissn = {2364-091X},\n\tshorttitle = {{TERENO}},\n\turl = {http://jlsrf.org/index.php/lsf/article/view/98},\n\tdoi = {10.17815/jlsrf-2-98},\n\tabstract = {Central elements of the TERENO network are “terrestrial observatories” at the catchment scale which were selected in climate sensitive regions of Germany for the regional analyses of climate change impacts. Within these observatories small scale research facilities and test areas are placed in order to accomplish energy, water, carbon and nutrient process studies across the different compartments of the terrestrial environment. Following a hierarchical scaling approach (point-plot-field) these detailed information and the gained knowledge will be transferred to the regional scale using integrated modelling approaches. Furthermore, existing research stations are enhanced and embedded within the observatories. In addition, mobile measurement platforms enable monitoring of dynamic processes at the local scale up to the determination of spatial pattern at the regional scale are applied within TERENO.},\n\turldate = {2023-01-23},\n\tjournal = {Journal of large-scale research facilities JLSRF},\n\tauthor = {Bogena, Heye Reemt},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {A52},\n}\n\n
\n
\n\n\n
\n Central elements of the TERENO network are “terrestrial observatories” at the catchment scale which were selected in climate sensitive regions of Germany for the regional analyses of climate change impacts. Within these observatories small scale research facilities and test areas are placed in order to accomplish energy, water, carbon and nutrient process studies across the different compartments of the terrestrial environment. Following a hierarchical scaling approach (point-plot-field) these detailed information and the gained knowledge will be transferred to the regional scale using integrated modelling approaches. Furthermore, existing research stations are enhanced and embedded within the observatories. In addition, mobile measurement platforms enable monitoring of dynamic processes at the local scale up to the determination of spatial pattern at the regional scale are applied within TERENO.\n
\n\n\n
\n\n\n
\n \n\n \n \n Buras, A.; van der Maaten-Theunissen, M.; van der Maaten, E.; Ahlgrimm, S.; Hermann, P.; Simard, S.; Heinrich, I.; Helle, G.; Unterseher, M.; Schnittler, M.; Eusemann, P.; and Wilmking, M.\n\n\n \n \n \n \n \n Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations.\n \n \n \n \n\n\n \n\n\n\n PLOS ONE, 11(7): e0158346. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"TuningPaper\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{buras_tuning_2016,\n\ttitle = {Tuning the {Voices} of a {Choir}: {Detecting} {Ecological} {Gradients} in {Time}-{Series} {Populations}},\n\tvolume = {11},\n\tissn = {1932-6203},\n\tshorttitle = {Tuning the {Voices} of a {Choir}},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0158346},\n\tdoi = {10.1371/journal.pone.0158346},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {PLOS ONE},\n\tauthor = {Buras, Allan and van der Maaten-Theunissen, Marieke and van der Maaten, Ernst and Ahlgrimm, Svenja and Hermann, Philipp and Simard, Sonia and Heinrich, Ingo and Helle, Gerd and Unterseher, Martin and Schnittler, Martin and Eusemann, Pascal and Wilmking, Martin},\n\teditor = {Guralnick, Robert},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {e0158346},\n}\n\n
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\n \n\n \n \n Cai, G.; Vanderborght, J.; Klotzsche, A.; van der Kruk, J.; Neumann, J.; Hermes, N.; and Vereecken, H.\n\n\n \n \n \n \n \n Construction of Minirhizotron Facilities for Investigating Root Zone Processes.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 15(9): vzj2016.05.0043. September 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ConstructionPaper\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_construction_2016,\n\ttitle = {Construction of {Minirhizotron} {Facilities} for {Investigating} {Root} {Zone} {Processes}},\n\tvolume = {15},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2016.05.0043},\n\tdoi = {10.2136/vzj2016.05.0043},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2023-01-23},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Cai, Gaochao and Vanderborght, Jan and Klotzsche, Anja and van der Kruk, Jan and Neumann, Joschka and Hermes, Normen and Vereecken, Harry},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {vzj2016.05.0043},\n}\n\n
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\n \n\n \n \n Chwala, C.; Keis, F.; and Kunstmann, H.\n\n\n \n \n \n \n \n Real-time data acquisition of commercial microwave link networks for hydrometeorological applications.\n \n \n \n \n\n\n \n\n\n\n Atmospheric Measurement Techniques, 9(3): 991–999. March 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Real-timePaper\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{chwala_real-time_2016,\n\ttitle = {Real-time data acquisition of commercial microwave link networks for hydrometeorological applications},\n\tvolume = {9},\n\tissn = {1867-8548},\n\turl = {https://amt.copernicus.org/articles/9/991/2016/},\n\tdoi = {10.5194/amt-9-991-2016},\n\tabstract = {Abstract. The usage of data from commercial microwave link (CML) networks for scientific purposes is becoming increasingly popular, in particular for rain rate estimation. However, data acquisition and availability is still a crucial problem and limits research possibilities. To overcome this issue, we have developed an open-source data acquisition system based on the Simple Network Management Protocol (SNMP). It is able to record transmitted and received signal levels of a large number of CMLs simultaneously with a temporal resolution of up to 1 s. We operate this system at Ericsson Germany, acquiring data from 450 CMLs with minutely real-time transfer to our database. Our data acquisition system is not limited to a particular CML hardware model or manufacturer, though. We demonstrate this by running the same system for CMLs of a different manufacturer, operated by an alpine ski resort in Germany. There, the data acquisition is running simultaneously for four CMLs with a temporal resolution of 1 s. We present an overview of our system, describe the details of the necessary SNMP requests and show results from its operational application.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2023-01-23},\n\tjournal = {Atmospheric Measurement Techniques},\n\tauthor = {Chwala, Christian and Keis, Felix and Kunstmann, Harald},\n\tmonth = mar,\n\tyear = {2016},\n\tpages = {991--999},\n}\n\n
\n
\n\n\n
\n Abstract. The usage of data from commercial microwave link (CML) networks for scientific purposes is becoming increasingly popular, in particular for rain rate estimation. However, data acquisition and availability is still a crucial problem and limits research possibilities. To overcome this issue, we have developed an open-source data acquisition system based on the Simple Network Management Protocol (SNMP). It is able to record transmitted and received signal levels of a large number of CMLs simultaneously with a temporal resolution of up to 1 s. We operate this system at Ericsson Germany, acquiring data from 450 CMLs with minutely real-time transfer to our database. Our data acquisition system is not limited to a particular CML hardware model or manufacturer, though. We demonstrate this by running the same system for CMLs of a different manufacturer, operated by an alpine ski resort in Germany. There, the data acquisition is running simultaneously for four CMLs with a temporal resolution of 1 s. We present an overview of our system, describe the details of the necessary SNMP requests and show results from its operational application.\n
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\n \n\n \n \n Cornelissen, T.; Diekkrüger, B.; and Bogena, H.\n\n\n \n \n \n \n \n Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere.\n \n \n \n \n\n\n \n\n\n\n Water, 8(5): 202. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"UsingPaper\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{cornelissen_using_2016,\n\ttitle = {Using {High}-{Resolution} {Data} to {Test} {Parameter} {Sensitivity} of the {Distributed} {Hydrological} {Model} {HydroGeoSphere}},\n\tvolume = {8},\n\tissn = {2073-4441},\n\turl = {http://www.mdpi.com/2073-4441/8/5/202},\n\tdoi = {10.3390/w8050202},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2023-01-23},\n\tjournal = {Water},\n\tauthor = {Cornelissen, Thomas and Diekkrüger, Bernd and Bogena, Heye},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {202},\n}\n\n
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\n \n\n \n \n Creutzburg, F.; and Frenzel, M.\n\n\n \n \n \n \n Langzeit-Untersuchung von Wildbienen in Agrarlandschaften in Sachsen-Anhalt im TERENO-Projekt (Hymenoptera: Apoidea).\n \n \n \n\n\n \n\n\n\n Entomologische Zeitschrift, 126: 225–240. December 2016.\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{creutzburg_langzeit-untersuchung_2016,\n\ttitle = {Langzeit-{Untersuchung} von {Wildbienen} in {Agrarlandschaften} in {Sachsen}-{Anhalt} im {TERENO}-{Projekt} ({Hymenoptera}: {Apoidea})},\n\tvolume = {126},\n\tjournal = {Entomologische Zeitschrift},\n\tauthor = {Creutzburg, Frank and Frenzel, Mark},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {225--240},\n}\n\n
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\n \n\n \n \n Dadi, T.; Friese, K.; Wendt-Potthoff, K.; and Koschorreck, M.\n\n\n \n \n \n \n \n Benthic dissolved organic carbon fluxes in a drinking water reservoir: Benthic DOC flux.\n \n \n \n \n\n\n \n\n\n\n Limnology and Oceanography, 61(2): 445–459. March 2016.\n \n\n\n\n
\n\n\n\n \n \n \"BenthicPaper\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{dadi_benthic_2016,\n\ttitle = {Benthic dissolved organic carbon fluxes in a drinking water reservoir: {Benthic} {DOC} flux},\n\tvolume = {61},\n\tissn = {00243590},\n\tshorttitle = {Benthic dissolved organic carbon fluxes in a drinking water reservoir},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/lno.10224},\n\tdoi = {10.1002/lno.10224},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2023-01-23},\n\tjournal = {Limnology and Oceanography},\n\tauthor = {Dadi, Tallent and Friese, Kurt and Wendt-Potthoff, Katrin and Koschorreck, Matthias},\n\tmonth = mar,\n\tyear = {2016},\n\tpages = {445--459},\n}\n\n
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\n \n\n \n \n Dahms, T.; Seissiger, S.; Conrad, C.; and Borg, E.\n\n\n \n \n \n \n \n MODELLING BIOPHYSICAL PARAMETERS OF MAIZE USING LANDSAT 8 TIME SERIES.\n \n \n \n \n\n\n \n\n\n\n The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B2: 171–175. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MODELLINGPaper\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{dahms_modelling_2016,\n\ttitle = {{MODELLING} {BIOPHYSICAL} {PARAMETERS} {OF} {MAIZE} {USING} {LANDSAT} 8 {TIME} {SERIES}},\n\tvolume = {XLI-B2},\n\tissn = {2194-9034},\n\turl = {https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/171/2016/},\n\tdoi = {10.5194/isprs-archives-XLI-B2-171-2016},\n\tabstract = {Abstract. Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution.  In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015.  The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement.  Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9.  Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model biophysical parameters.},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},\n\tauthor = {Dahms, Thorsten and Seissiger, Sylvia and Conrad, Christopher and Borg, Erik},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {171--175},\n}\n\n
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\n Abstract. Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model biophysical parameters.\n
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\n \n\n \n \n Desai, A R; Wohlfahrt, G; Zeeman, M J; Katata, G; Eugster, W; Montagnani, L; Gianelle, D; Mauder, M; and Schmid, H.\n\n\n \n \n \n \n \n Montane ecosystem productivity responds more to global circulation patterns than climatic trends.\n \n \n \n \n\n\n \n\n\n\n Environmental Research Letters, 11(2): 024013. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MontanePaper\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{desai_montane_2016,\n\ttitle = {Montane ecosystem productivity responds more to global circulation patterns than climatic trends},\n\tvolume = {11},\n\tissn = {1748-9326},\n\turl = {https://iopscience.iop.org/article/10.1088/1748-9326/11/2/024013},\n\tdoi = {10.1088/1748-9326/11/2/024013},\n\tnumber = {2},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Research Letters},\n\tauthor = {Desai, A R and Wohlfahrt, G and Zeeman, M J and Katata, G and Eugster, W and Montagnani, L and Gianelle, D and Mauder, M and Schmid, H-P},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {024013},\n}\n\n
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\n \n\n \n \n Dietze, E.; Słowiński, M.; Zawiska, I.; Veh, G.; and Brauer, A.\n\n\n \n \n \n \n \n Multiple drivers of Holocene lake level changes at a lowland lake in northeastern Germany.\n \n \n \n \n\n\n \n\n\n\n Boreas, 45(4): 828–845. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MultiplePaper\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{dietze_multiple_2016,\n\ttitle = {Multiple drivers of {Holocene} lake level changes at a lowland lake in northeastern {Germany}},\n\tvolume = {45},\n\tissn = {03009483},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/bor.12190},\n\tdoi = {10.1111/bor.12190},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2023-01-23},\n\tjournal = {Boreas},\n\tauthor = {Dietze, Elisabeth and Słowiński, Michał and Zawiska, Izabela and Veh, Georg and Brauer, Achim},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {828--845},\n}\n\n
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\n \n\n \n \n Dressler, G.; Müller, B.; Frank, K.; and Kuhlicke, C.\n\n\n \n \n \n \n \n Towards thresholds of disaster management performance under demographic change: exploring functional relationships using agent-based modeling.\n \n \n \n \n\n\n \n\n\n\n Natural Hazards and Earth System Sciences, 16(10): 2287–2301. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\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{dressler_towards_2016,\n\ttitle = {Towards thresholds of disaster management performance under demographic change: exploring functional relationships using agent-based modeling},\n\tvolume = {16},\n\tissn = {1684-9981},\n\tshorttitle = {Towards thresholds of disaster management performance under demographic change},\n\turl = {https://nhess.copernicus.org/articles/16/2287/2016/},\n\tdoi = {10.5194/nhess-16-2287-2016},\n\tabstract = {Abstract. Effective disaster management is a core feature for the protection of communities against natural disasters such as floods. Disaster management organizations (DMOs) are expected to contribute to ensuring this protection. However, what happens when their resources to cope with a flood are at stake or the intensity and frequency of the event exceeds their capacities? Many cities in the Free State of Saxony, Germany, were strongly hit by several floods in the last years and are additionally challenged by demographic change, with an ageing society and out-migration leading to population shrinkage in many parts of Saxony. Disaster management, which is mostly volunteer-based in Germany, is particularly affected by this change, leading to a loss of members. We propose an agent-based simulation model that acts as a "virtual lab" to explore the impact of various changes on disaster management performance. Using different scenarios we examine the impact of changes in personal resources of DMOs, their access to operation relevant information, flood characteristics as well as differences between geographic regions. A loss of DMOs and associated manpower caused by demographic change has the most profound impact on the performance. Especially in rural, upstream regions population decline in combination with very short lead times can put disaster management performance at risk.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2023-01-23},\n\tjournal = {Natural Hazards and Earth System Sciences},\n\tauthor = {Dressler, Gunnar and Müller, Birgit and Frank, Karin and Kuhlicke, Christian},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {2287--2301},\n}\n\n
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\n Abstract. Effective disaster management is a core feature for the protection of communities against natural disasters such as floods. Disaster management organizations (DMOs) are expected to contribute to ensuring this protection. However, what happens when their resources to cope with a flood are at stake or the intensity and frequency of the event exceeds their capacities? Many cities in the Free State of Saxony, Germany, were strongly hit by several floods in the last years and are additionally challenged by demographic change, with an ageing society and out-migration leading to population shrinkage in many parts of Saxony. Disaster management, which is mostly volunteer-based in Germany, is particularly affected by this change, leading to a loss of members. We propose an agent-based simulation model that acts as a \"virtual lab\" to explore the impact of various changes on disaster management performance. Using different scenarios we examine the impact of changes in personal resources of DMOs, their access to operation relevant information, flood characteristics as well as differences between geographic regions. A loss of DMOs and associated manpower caused by demographic change has the most profound impact on the performance. Especially in rural, upstream regions population decline in combination with very short lead times can put disaster management performance at risk.\n
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\n \n\n \n \n Dräger, N.; Brauer, A.; Brademann, B.; Tjallingii, R.; Słowiński, M.; Błaszkiewicz, M.; and Schlaak, N.\n\n\n \n \n \n \n \n Spontaneous self-combustion of organic-rich lateglacial lake sediments after freeze-drying.\n \n \n \n \n\n\n \n\n\n\n Journal of Paleolimnology, 55(2): 185–194. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SpontaneousPaper\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{drager_spontaneous_2016,\n\ttitle = {Spontaneous self-combustion of organic-rich lateglacial lake sediments after freeze-drying},\n\tvolume = {55},\n\tissn = {0921-2728, 1573-0417},\n\turl = {http://link.springer.com/10.1007/s10933-015-9875-x},\n\tdoi = {10.1007/s10933-015-9875-x},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Paleolimnology},\n\tauthor = {Dräger, Nadine and Brauer, Achim and Brademann, Brian and Tjallingii, Rik and Słowiński, Michał and Błaszkiewicz, Mirosław and Schlaak, Norbert},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {185--194},\n}\n\n
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\n \n\n \n \n Díaz-Pinés, E.; Heras, P.; Gasche, R.; Rubio, A.; Rennenberg, H.; Butterbach-Bahl, K.; and Kiese, R.\n\n\n \n \n \n \n \n Nitrous oxide emissions from stems of ash (Fraxinus angustifolia Vahl) and European beech (Fagus sylvatica L.).\n \n \n \n \n\n\n \n\n\n\n Plant and Soil, 398(1-2): 35–45. January 2016.\n \n\n\n\n
\n\n\n\n \n \n \"NitrousPaper\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{diaz-pines_nitrous_2016,\n\ttitle = {Nitrous oxide emissions from stems of ash ({Fraxinus} angustifolia {Vahl}) and {European} beech ({Fagus} sylvatica {L}.)},\n\tvolume = {398},\n\tissn = {0032-079X, 1573-5036},\n\turl = {http://link.springer.com/10.1007/s11104-015-2629-8},\n\tdoi = {10.1007/s11104-015-2629-8},\n\tlanguage = {en},\n\tnumber = {1-2},\n\turldate = {2023-02-23},\n\tjournal = {Plant and Soil},\n\tauthor = {Díaz-Pinés, Eugenio and Heras, Paloma and Gasche, Rainer and Rubio, Agustín and Rennenberg, Heinz and Butterbach-Bahl, Klaus and Kiese, Ralf},\n\tmonth = jan,\n\tyear = {2016},\n\tpages = {35--45},\n}\n\n
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\n \n\n \n \n Englert, A.; Kemna, A.; Zhu, J.; Vanderborght, J.; Vereecken, H.; and Yeh, T. J.\n\n\n \n \n \n \n \n Comparison of smoothness-constrained and geostatistically based cross-borehole electrical resistivity tomography for characterization of solute tracer plumes.\n \n \n \n \n\n\n \n\n\n\n Water Science and Engineering, 9(4): 274–286. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ComparisonPaper\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{englert_comparison_2016,\n\ttitle = {Comparison of smoothness-constrained and geostatistically based cross-borehole electrical resistivity tomography for characterization of solute tracer plumes},\n\tvolume = {9},\n\tissn = {16742370},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1674237017300029},\n\tdoi = {10.1016/j.wse.2017.01.002},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2023-01-23},\n\tjournal = {Water Science and Engineering},\n\tauthor = {Englert, Andreas and Kemna, Andreas and Zhu, Jun-feng and Vanderborght, Jan and Vereecken, Harry and Yeh, Tian-Chyi J.},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {274--286},\n}\n\n
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\n \n\n \n \n Fang, Z.; Bogena, H.; Kollet, S.; and Vereecken, H.\n\n\n \n \n \n \n \n Scale dependent parameterization of soil hydraulic conductivity in 3D simulation of hydrological processes in a forested headwater catchment.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 536: 365–375. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ScalePaper\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{fang_scale_2016,\n\ttitle = {Scale dependent parameterization of soil hydraulic conductivity in {3D} simulation of hydrological processes in a forested headwater catchment},\n\tvolume = {536},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169416301251},\n\tdoi = {10.1016/j.jhydrol.2016.03.020},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Fang, Zhufeng and Bogena, Heye and Kollet, Stefan and Vereecken, Harry},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {365--375},\n}\n\n
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\n \n\n \n \n Feilhauer, H.; Doktor, D.; Schmidtlein, S.; and Skidmore, A. K.\n\n\n \n \n \n \n \n Mapping pollination types with remote sensing.\n \n \n \n \n\n\n \n\n\n\n Journal of Vegetation Science, 27(5): 999–1011. September 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MappingPaper\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{feilhauer_mapping_2016,\n\ttitle = {Mapping pollination types with remote sensing},\n\tvolume = {27},\n\tissn = {11009233},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/jvs.12421},\n\tdoi = {10.1111/jvs.12421},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Vegetation Science},\n\tauthor = {Feilhauer, Hannes and Doktor, Daniel and Schmidtlein, Sebastian and Skidmore, Andrew K.},\n\teditor = {Prinzing, Andreas},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {999--1011},\n}\n\n
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\n \n\n \n \n Franz, D.; Koebsch, F.; Larmanou, E.; Augustin, J.; and Sachs, T.\n\n\n \n \n \n \n \n High net $_{\\textrm{2}}$ and CH$_{\\textrm{4}}$ release at a eutrophic shallow lake on a formerly drained fen.\n \n \n \n \n\n\n \n\n\n\n Biogeosciences, 13(10): 3051–3070. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"HighPaper\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_high_2016,\n\ttitle = {High net $_{\\textrm{2}}$ and {CH}$_{\\textrm{4}}$ release at a eutrophic shallow lake on a formerly drained fen},\n\tvolume = {13},\n\tissn = {1726-4189},\n\turl = {https://bg.copernicus.org/articles/13/3051/2016/},\n\tdoi = {10.5194/bg-13-3051-2016},\n\tabstract = {Abstract. Drained peatlands often act as carbon dioxide (CO2) hotspots. Raising the groundwater table is expected to reduce their CO2 contribution to the atmosphere and revitalise their function as carbon (C) sink in the long term. Without strict water management rewetting often results in partial flooding and the formation of spatially heterogeneous, nutrient-rich shallow lakes. Uncertainties remain as to when the intended effect of rewetting is achieved, as this specific ecosystem type has hardly been investigated in terms of greenhouse gas (GHG) exchange. In most cases of rewetting, methane (CH4) emissions increase under anoxic conditions due to a higher water table and in terms of global warming potential (GWP) outperform the shift towards CO2 uptake, at least in the short term.Based on eddy covariance measurements we studied the ecosystem–atmosphere exchange of CH4 and CO2 at a shallow lake situated on a former fen grassland in northeastern Germany. The lake evolved shortly after flooding, 9 years previous to our investigation period. The ecosystem consists of two main surface types: open water (inhabited by submerged and floating vegetation) and emergent vegetation (particularly including the eulittoral zone of the lake, dominated by Typha latifolia). To determine the individual contribution of the two main surface types to the net CO2 and CH4 exchange of the whole lake ecosystem, we combined footprint analysis with CH4 modelling and net ecosystem exchange partitioning.The CH4 and CO2 dynamics were strikingly different between open water and emergent vegetation. Net CH4 emissions from the open water area were around 4-fold higher than from emergent vegetation stands, accounting for 53 and 13 g CH4 m−2 a−1 respectively. In addition, both surface types were net CO2 sources with 158 and 750 g CO2 m−2 a−1 respectively. Unusual meteorological conditions in terms of a warm and dry summer and a mild winter might have facilitated high respiration rates. In sum, even after 9 years of rewetting the lake ecosystem exhibited a considerable C loss and global warming impact, the latter mainly driven by high CH4 emissions. We assume the eutrophic conditions in combination with permanent high inundation as major reasons for the unfavourable GHG balance.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2023-01-23},\n\tjournal = {Biogeosciences},\n\tauthor = {Franz, Daniela and Koebsch, Franziska and Larmanou, Eric and Augustin, Jürgen and Sachs, Torsten},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {3051--3070},\n}\n\n
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\n\n\n
\n Abstract. Drained peatlands often act as carbon dioxide (CO2) hotspots. Raising the groundwater table is expected to reduce their CO2 contribution to the atmosphere and revitalise their function as carbon (C) sink in the long term. Without strict water management rewetting often results in partial flooding and the formation of spatially heterogeneous, nutrient-rich shallow lakes. Uncertainties remain as to when the intended effect of rewetting is achieved, as this specific ecosystem type has hardly been investigated in terms of greenhouse gas (GHG) exchange. In most cases of rewetting, methane (CH4) emissions increase under anoxic conditions due to a higher water table and in terms of global warming potential (GWP) outperform the shift towards CO2 uptake, at least in the short term.Based on eddy covariance measurements we studied the ecosystem–atmosphere exchange of CH4 and CO2 at a shallow lake situated on a former fen grassland in northeastern Germany. The lake evolved shortly after flooding, 9 years previous to our investigation period. The ecosystem consists of two main surface types: open water (inhabited by submerged and floating vegetation) and emergent vegetation (particularly including the eulittoral zone of the lake, dominated by Typha latifolia). To determine the individual contribution of the two main surface types to the net CO2 and CH4 exchange of the whole lake ecosystem, we combined footprint analysis with CH4 modelling and net ecosystem exchange partitioning.The CH4 and CO2 dynamics were strikingly different between open water and emergent vegetation. Net CH4 emissions from the open water area were around 4-fold higher than from emergent vegetation stands, accounting for 53 and 13 g CH4 m−2 a−1 respectively. In addition, both surface types were net CO2 sources with 158 and 750 g CO2 m−2 a−1 respectively. Unusual meteorological conditions in terms of a warm and dry summer and a mild winter might have facilitated high respiration rates. In sum, even after 9 years of rewetting the lake ecosystem exhibited a considerable C loss and global warming impact, the latter mainly driven by high CH4 emissions. We assume the eutrophic conditions in combination with permanent high inundation as major reasons for the unfavourable GHG balance.\n
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\n \n\n \n \n Frenzel, M.; Everaars, J.; and Schweiger, O.\n\n\n \n \n \n \n \n Bird communities in agricultural landscapes: What are the current drivers of temporal trends?.\n \n \n \n \n\n\n \n\n\n\n Ecological Indicators, 65: 113–121. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"BirdPaper\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{frenzel_bird_2016,\n\ttitle = {Bird communities in agricultural landscapes: {What} are the current drivers of temporal trends?},\n\tvolume = {65},\n\tissn = {1470160X},\n\tshorttitle = {Bird communities in agricultural landscapes},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X15006524},\n\tdoi = {10.1016/j.ecolind.2015.11.020},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Ecological Indicators},\n\tauthor = {Frenzel, Mark and Everaars, Jeroen and Schweiger, Oliver},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {113--121},\n}\n\n
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\n \n\n \n \n Fóti, S.; Balogh, J.; Herbst, M.; Papp, M.; Koncz, P.; Bartha, S.; Zimmermann, Z.; Komoly, C.; Szabó, G.; Margóczi, K.; Acosta, M.; and Nagy, Z.\n\n\n \n \n \n \n \n Meta-analysis of field scale spatial variability of grassland soil $_{\\textrm{2}}$ efflux: Interaction of biotic and abiotic drivers.\n \n \n \n \n\n\n \n\n\n\n CATENA, 143: 78–89. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Meta-analysisPaper\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{foti_meta-analysis_2016,\n\ttitle = {Meta-analysis of field scale spatial variability of grassland soil $_{\\textrm{2}}$ efflux: {Interaction} of biotic and abiotic drivers},\n\tvolume = {143},\n\tissn = {03418162},\n\tshorttitle = {Meta-analysis of field scale spatial variability of grassland soil {CO2} efflux},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0341816216301205},\n\tdoi = {10.1016/j.catena.2016.03.034},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {CATENA},\n\tauthor = {Fóti, Szilvia and Balogh, János and Herbst, Michael and Papp, Marianna and Koncz, Péter and Bartha, Sándor and Zimmermann, Zita and Komoly, Cecília and Szabó, Gábor and Margóczi, Katalin and Acosta, Manuel and Nagy, Zoltán},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {78--89},\n}\n\n
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\n \n\n \n \n Groh, J.; Vanderborght, J.; Pütz, T.; and Vereecken, H.\n\n\n \n \n \n \n \n How to Control the Lysimeter Bottom Boundary to Investigate the Effect of Climate Change on Soil Processes?.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 15(7): vzj2015.08.0113. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"HowPaper\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_how_2016,\n\ttitle = {How to {Control} the {Lysimeter} {Bottom} {Boundary} to {Investigate} the {Effect} of {Climate} {Change} on {Soil} {Processes}?},\n\tvolume = {15},\n\tissn = {15391663},\n\turl = {http://doi.wiley.com/10.2136/vzj2015.08.0113},\n\tdoi = {10.2136/vzj2015.08.0113},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Groh, Jannis and Vanderborght, Jan and Pütz, Thomas and Vereecken, Harry},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {vzj2015.08.0113},\n}\n\n
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\n \n\n \n \n Haase, P.; Frenzel, M.; Klotz, S.; Musche, M.; and Stoll, S.\n\n\n \n \n \n \n \n The long-term ecological research (LTER) network: Relevance, current status, future perspective and examples from marine, freshwater and terrestrial long-term observation.\n \n \n \n \n\n\n \n\n\n\n Ecological Indicators, 65: 1–3. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\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{haase_long-term_2016,\n\ttitle = {The long-term ecological research ({LTER}) network: {Relevance}, current status, future perspective and examples from marine, freshwater and terrestrial long-term observation},\n\tvolume = {65},\n\tissn = {1470160X},\n\tshorttitle = {The long-term ecological research ({LTER}) network},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X16000546},\n\tdoi = {10.1016/j.ecolind.2016.01.040},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Ecological Indicators},\n\tauthor = {Haase, Peter and Frenzel, Mark and Klotz, Stefan and Musche, Martin and Stoll, Stefan},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {1--3},\n}\n\n
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\n \n\n \n \n Han, X.; Hendricks Franssen, H.; Jiménez Bello, M. Á.; Rosolem, R.; Bogena, H.; Alzamora, F. M.; Chanzy, A.; and Vereecken, H.\n\n\n \n \n \n \n \n Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 539: 611–624. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SimultaneousPaper\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{han_simultaneous_2016,\n\ttitle = {Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity},\n\tvolume = {539},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169416303171},\n\tdoi = {10.1016/j.jhydrol.2016.05.050},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Han, Xujun and Hendricks Franssen, Harrie-Jan and Jiménez Bello, Miguel Ángel and Rosolem, Rafael and Bogena, Heye and Alzamora, Fernando Martínez and Chanzy, André and Vereecken, Harry},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {611--624},\n}\n\n
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\n \n\n \n \n Hannes, M.; Wollschläger, U.; Wöhling, T.; and Vogel, H.\n\n\n \n \n \n \n \n Revisiting hydraulic hysteresis based on long-term monitoring of hydraulic states in lysimeters: REVISITING HYDRAULIC HYSTERESIS.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 52(5): 3847–3865. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"RevisitingPaper\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{hannes_revisiting_2016,\n\ttitle = {Revisiting hydraulic hysteresis based on long-term monitoring of hydraulic states in lysimeters: {REVISITING} {HYDRAULIC} {HYSTERESIS}},\n\tvolume = {52},\n\tissn = {00431397},\n\tshorttitle = {Revisiting hydraulic hysteresis based on long-term monitoring of hydraulic states in lysimeters},\n\turl = {http://doi.wiley.com/10.1002/2015WR018319},\n\tdoi = {10.1002/2015WR018319},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2023-01-23},\n\tjournal = {Water Resources Research},\n\tauthor = {Hannes, M. and Wollschläger, U. and Wöhling, T. and Vogel, H.-J.},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {3847--3865},\n}\n\n
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\n \n\n \n \n Heidbüchel, I.; Güntner, A.; and Blume, T.\n\n\n \n \n \n \n \n Use of cosmic-ray neutron sensors for soil moisture monitoring in forests.\n \n \n \n \n\n\n \n\n\n\n Hydrology and Earth System Sciences, 20(3): 1269–1288. March 2016.\n \n\n\n\n
\n\n\n\n \n \n \"UsePaper\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{heidbuchel_use_2016,\n\ttitle = {Use of cosmic-ray neutron sensors for soil moisture monitoring in forests},\n\tvolume = {20},\n\tissn = {1607-7938},\n\turl = {https://hess.copernicus.org/articles/20/1269/2016/},\n\tdoi = {10.5194/hess-20-1269-2016},\n\tabstract = {Abstract. Measuring soil moisture with cosmic-ray neutrons is a promising technique for intermediate spatial scales. To convert neutron counts to average volumetric soil water content a simple calibration function can be used (the N0-calibration of Desilets et al., 2010). The calibration is based on soil water content derived directly from soil samples taken within the footprint of the sensor. We installed a cosmic-ray neutron sensor (CRS) in a mixed forest in the lowlands of north-eastern Germany and calibrated it 10 times throughout one calendar year. Each calibration with the N0-calibration function resulted in a different CRS soil moisture time series, with deviations of up to 0.1 m3 m−3 (24 \\% of the total range) for individual values of soil water content. Also, many of the calibration efforts resulted in time series that could not be matched with independent in situ measurements of soil water content. We therefore suggest a modified calibration function with a different shape that can vary from one location to another. A two-point calibration was found to effectively define the shape of the modified calibration function if the calibration points were taken during both dry and wet conditions spanning at least half of the total range of soil moisture. The best results were obtained when the soil samples used for calibration were linearly weighted as a function of depth in the soil profile and nonlinearly weighted as a function of distance from the CRS, and when the depth-specific amount of soil organic matter and lattice water content was explicitly considered. The annual cycle of tree foliation was found to be a negligible factor for calibration because the variable hydrogen mass in the leaves was small compared to the hydrogen mass changes by soil moisture variations. As a final point, we provide a calibration guide for a CRS in forested environments.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2023-01-23},\n\tjournal = {Hydrology and Earth System Sciences},\n\tauthor = {Heidbüchel, Ingo and Güntner, Andreas and Blume, Theresa},\n\tmonth = mar,\n\tyear = {2016},\n\tpages = {1269--1288},\n}\n\n
\n
\n\n\n
\n Abstract. Measuring soil moisture with cosmic-ray neutrons is a promising technique for intermediate spatial scales. To convert neutron counts to average volumetric soil water content a simple calibration function can be used (the N0-calibration of Desilets et al., 2010). The calibration is based on soil water content derived directly from soil samples taken within the footprint of the sensor. We installed a cosmic-ray neutron sensor (CRS) in a mixed forest in the lowlands of north-eastern Germany and calibrated it 10 times throughout one calendar year. Each calibration with the N0-calibration function resulted in a different CRS soil moisture time series, with deviations of up to 0.1 m3 m−3 (24 % of the total range) for individual values of soil water content. Also, many of the calibration efforts resulted in time series that could not be matched with independent in situ measurements of soil water content. We therefore suggest a modified calibration function with a different shape that can vary from one location to another. A two-point calibration was found to effectively define the shape of the modified calibration function if the calibration points were taken during both dry and wet conditions spanning at least half of the total range of soil moisture. The best results were obtained when the soil samples used for calibration were linearly weighted as a function of depth in the soil profile and nonlinearly weighted as a function of distance from the CRS, and when the depth-specific amount of soil organic matter and lattice water content was explicitly considered. The annual cycle of tree foliation was found to be a negligible factor for calibration because the variable hydrogen mass in the leaves was small compared to the hydrogen mass changes by soil moisture variations. As a final point, we provide a calibration guide for a CRS in forested environments.\n
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\n \n\n \n \n Heine, I.; Jagdhuber, T.; and Itzerott, S.\n\n\n \n \n \n \n \n Classification and Monitoring of Reed Belts Using Dual-Polarimetric TerraSAR-X Time Series.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 8(7): 552. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ClassificationPaper\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{heine_classification_2016,\n\ttitle = {Classification and {Monitoring} of {Reed} {Belts} {Using} {Dual}-{Polarimetric} {TerraSAR}-{X} {Time} {Series}},\n\tvolume = {8},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/8/7/552},\n\tdoi = {10.3390/rs8070552},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {Remote Sensing},\n\tauthor = {Heine, Iris and Jagdhuber, Thomas and Itzerott, Sibylle},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {552},\n}\n\n
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\n \n\n \n \n Herbrich, M.; and Gerke, H. H.\n\n\n \n \n \n \n \n Autocorrelation analysis of high resolution weighing lysimeter time series as a basis for determination of precipitation.\n \n \n \n \n\n\n \n\n\n\n Journal of Plant Nutrition and Soil Science, 179(6): 784–798. December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AutocorrelationPaper\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_autocorrelation_2016,\n\ttitle = {Autocorrelation analysis of high resolution weighing lysimeter time series as a basis for determination of precipitation},\n\tvolume = {179},\n\tissn = {1436-8730, 1522-2624},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/jpln.201600169},\n\tdoi = {10.1002/jpln.201600169},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Plant Nutrition and Soil Science},\n\tauthor = {Herbrich, Marcus and Gerke, Horst H.},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {784--798},\n}\n\n
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\n \n\n \n \n Herbst, M.; Tappe, W.; Kummer, S.; and Vereecken, H.\n\n\n \n \n \n \n \n The impact of sieving on heterotrophic respiration response to water content in loamy and sandy topsoils.\n \n \n \n \n\n\n \n\n\n\n Geoderma, 272: 73–82. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\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{herbst_impact_2016,\n\ttitle = {The impact of sieving on heterotrophic respiration response to water content in loamy and sandy topsoils},\n\tvolume = {272},\n\tissn = {00167061},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0016706116301008},\n\tdoi = {10.1016/j.geoderma.2016.03.002},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Geoderma},\n\tauthor = {Herbst, M. and Tappe, W. and Kummer, S. and Vereecken, H.},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {73--82},\n}\n\n
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\n \n\n \n \n Hingerl, L.; Kunstmann, H.; Wagner, S.; Mauder, M.; Bliefernicht, J.; and Rigon, R.\n\n\n \n \n \n \n \n Spatio‐temporal variability of water and energy fluxes – a case study for a mesoscale catchment in pre‐alpine environment.\n \n \n \n \n\n\n \n\n\n\n Hydrological Processes, 30(21): 3804–3823. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Spatio‐temporalPaper\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{hingerl_spatiotemporal_2016,\n\ttitle = {Spatio‐temporal variability of water and energy fluxes – a case study for a mesoscale catchment in pre‐alpine environment},\n\tvolume = {30},\n\tissn = {0885-6087, 1099-1085},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/hyp.10893},\n\tdoi = {10.1002/hyp.10893},\n\tlanguage = {en},\n\tnumber = {21},\n\turldate = {2023-01-23},\n\tjournal = {Hydrological Processes},\n\tauthor = {Hingerl, Luitpold and Kunstmann, Harald and Wagner, Sven and Mauder, Matthias and Bliefernicht, Jan and Rigon, Riccardo},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {3804--3823},\n}\n\n
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\n \n\n \n \n Inostroza, P. A.; Vera-Escalona, I.; Wicht, A.; Krauss, M.; Brack, W.; and Norf, H.\n\n\n \n \n \n \n \n Anthropogenic Stressors Shape Genetic Structure: Insights from a Model Freshwater Population along a Land Use Gradient.\n \n \n \n \n\n\n \n\n\n\n Environmental Science & Technology, 50(20): 11346–11356. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnthropogenicPaper\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{inostroza_anthropogenic_2016,\n\ttitle = {Anthropogenic {Stressors} {Shape} {Genetic} {Structure}: {Insights} from a {Model} {Freshwater} {Population} along a {Land} {Use} {Gradient}},\n\tvolume = {50},\n\tissn = {0013-936X, 1520-5851},\n\tshorttitle = {Anthropogenic {Stressors} {Shape} {Genetic} {Structure}},\n\turl = {https://pubs.acs.org/doi/10.1021/acs.est.6b04629},\n\tdoi = {10.1021/acs.est.6b04629},\n\tlanguage = {en},\n\tnumber = {20},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Science \\& Technology},\n\tauthor = {Inostroza, Pedro A. and Vera-Escalona, Iván and Wicht, Anna-Jorina and Krauss, Martin and Brack, Werner and Norf, Helge},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {11346--11356},\n}\n\n
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\n \n\n \n \n Jaganmohan, M.; Knapp, S.; Buchmann, C. M.; and Schwarz, N.\n\n\n \n \n \n \n \n The Bigger, the Better? The Influence of Urban Green Space Design on Cooling Effects for Residential Areas.\n \n \n \n \n\n\n \n\n\n\n Journal of Environmental Quality, 45(1): 134–145. January 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\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{jaganmohan_bigger_2016,\n\ttitle = {The {Bigger}, the {Better}? {The} {Influence} of {Urban} {Green} {Space} {Design} on {Cooling} {Effects} for {Residential} {Areas}},\n\tvolume = {45},\n\tissn = {00472425},\n\tshorttitle = {The {Bigger}, the {Better}?},\n\turl = {http://doi.wiley.com/10.2134/jeq2015.01.0062},\n\tdoi = {10.2134/jeq2015.01.0062},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Environmental Quality},\n\tauthor = {Jaganmohan, Madhumitha and Knapp, Sonja and Buchmann, Carsten M. and Schwarz, Nina},\n\tmonth = jan,\n\tyear = {2016},\n\tpages = {134--145},\n}\n\n
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\n \n\n \n \n Jagdhuber, T.\n\n\n \n \n \n \n \n An Approach to Extended Fresnel Scattering for Modeling of Depolarizing Soil-Trunk Double-Bounce Scattering.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 8(10): 818. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\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{jagdhuber_approach_2016,\n\ttitle = {An {Approach} to {Extended} {Fresnel} {Scattering} for {Modeling} of {Depolarizing} {Soil}-{Trunk} {Double}-{Bounce} {Scattering}},\n\tvolume = {8},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/8/10/818},\n\tdoi = {10.3390/rs8100818},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2023-01-23},\n\tjournal = {Remote Sensing},\n\tauthor = {Jagdhuber, Thomas},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {818},\n}\n\n
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\n \n\n \n \n Kamjunke, N.; Oosterwoud, M. R.; Herzsprung, P.; and Tittel, J.\n\n\n \n \n \n \n \n Bacterial production and their role in the removal of dissolved organic matter from tributaries of drinking water reservoirs.\n \n \n \n \n\n\n \n\n\n\n Science of The Total Environment, 548-549: 51–59. April 2016.\n \n\n\n\n
\n\n\n\n \n \n \"BacterialPaper\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{kamjunke_bacterial_2016,\n\ttitle = {Bacterial production and their role in the removal of dissolved organic matter from tributaries of drinking water reservoirs},\n\tvolume = {548-549},\n\tissn = {00489697},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0048969716300183},\n\tdoi = {10.1016/j.scitotenv.2016.01.017},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Science of The Total Environment},\n\tauthor = {Kamjunke, Norbert and Oosterwoud, Marieke R. and Herzsprung, Peter and Tittel, Jörg},\n\tmonth = apr,\n\tyear = {2016},\n\tpages = {51--59},\n}\n\n
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\n \n\n \n \n Klotzsche, A.; van der Kruk, J.; He, G.; and Vereecken, H.\n\n\n \n \n \n \n \n GPR full-waveform inversion of horizontal ZOP borehole data using GprMax.\n \n \n \n \n\n\n \n\n\n\n In 2016 16th International Conference on Ground Penetrating Radar (GPR), pages 1–5, Hong Kong, Hong Kong, June 2016. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"GPRPaper\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_gpr_2016,\n\taddress = {Hong Kong, Hong Kong},\n\ttitle = {{GPR} full-waveform inversion of horizontal {ZOP} borehole data using {GprMax}},\n\tisbn = {9781509051816},\n\turl = {http://ieeexplore.ieee.org/document/7572695/},\n\tdoi = {10.1109/ICGPR.2016.7572695},\n\turldate = {2023-01-23},\n\tbooktitle = {2016 16th {International} {Conference} on {Ground} {Penetrating} {Radar} ({GPR})},\n\tpublisher = {IEEE},\n\tauthor = {Klotzsche, A. and van der Kruk, J. and He, G. and Vereecken, H.},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {1--5},\n}\n\n
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\n \n\n \n \n Knapp, S.; Stadler, J.; Harpke, A.; and Klotz, S.\n\n\n \n \n \n \n \n Dispersal traits as indicators of vegetation dynamics in long-term old-field succession.\n \n \n \n \n\n\n \n\n\n\n Ecological Indicators, 65: 44–54. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DispersalPaper\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{knapp_dispersal_2016,\n\ttitle = {Dispersal traits as indicators of vegetation dynamics in long-term old-field succession},\n\tvolume = {65},\n\tissn = {1470160X},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X15005385},\n\tdoi = {10.1016/j.ecolind.2015.10.003},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Ecological Indicators},\n\tauthor = {Knapp, Sonja and Stadler, Jutta and Harpke, Alexander and Klotz, Stefan},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {44--54},\n}\n\n
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\n \n\n \n \n Koch, J.; Cornelissen, T.; Fang, Z.; Bogena, H.; Diekkrüger, B.; Kollet, S.; and Stisen, S.\n\n\n \n \n \n \n \n Inter-comparison of three distributed hydrological models with respect to seasonal variability of soil moisture patterns at a small forested catchment.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 533: 234–249. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Inter-comparisonPaper\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{koch_inter-comparison_2016,\n\ttitle = {Inter-comparison of three distributed hydrological models with respect to seasonal variability of soil moisture patterns at a small forested catchment},\n\tvolume = {533},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169415009415},\n\tdoi = {10.1016/j.jhydrol.2015.12.002},\n\tlanguage = {en},\n\turldate = {2023-02-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Koch, Julian and Cornelissen, Thomas and Fang, Zhufeng and Bogena, Heye and Diekkrüger, Bernd and Kollet, Stefan and Stisen, Simon},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {234--249},\n}\n\n
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\n \n\n \n \n Kurtz, W.; He, G.; Kollet, S. J.; Maxwell, R. M.; Vereecken, H.; and Hendricks Franssen, H.\n\n\n \n \n \n \n \n TerrSysMP–PDAF (version 1.0): a modular high-performance data assimilation framework for an integrated land surface–subsurface model.\n \n \n \n \n\n\n \n\n\n\n Geoscientific Model Development, 9(4): 1341–1360. April 2016.\n \n\n\n\n
\n\n\n\n \n \n \"TerrSysMP–PDAFPaper\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{kurtz_terrsysmppdaf_2016,\n\ttitle = {{TerrSysMP}–{PDAF} (version 1.0): a modular high-performance data assimilation framework for an integrated land surface–subsurface model},\n\tvolume = {9},\n\tissn = {1991-9603},\n\tshorttitle = {{TerrSysMP}–{PDAF} (version 1.0)},\n\turl = {https://gmd.copernicus.org/articles/9/1341/2016/},\n\tdoi = {10.5194/gmd-9-1341-2016},\n\tabstract = {Abstract. Modelling of terrestrial systems is continuously moving towards more integrated modelling approaches, where different terrestrial compartment models are combined in order to realise a more sophisticated physical description of water, energy and carbon fluxes across compartment boundaries and to provide a more integrated view on terrestrial processes. While such models can effectively reduce certain parameterisation errors of single compartment models, model predictions are still prone to uncertainties regarding model input variables. The resulting uncertainties of model predictions can be effectively tackled by data assimilation techniques, which allow one to correct model predictions with observations taking into account both the model and measurement uncertainties. The steadily increasing availability of computational resources makes it now increasingly possible to perform data assimilation also for computationally highly demanding integrated terrestrial system models. However, as the computational burden for integrated models as well as data assimilation techniques is quite large, there is an increasing need to provide computationally efficient data assimilation frameworks for integrated models that allow one to run on and to make efficient use of massively parallel computational resources. In this paper we present a data assimilation framework for the land surface–subsurface part of the Terrestrial System Modelling Platform (TerrSysMP). TerrSysMP is connected via a memory-based coupling approach with the pre-existing parallel data assimilation library PDAF (Parallel Data Assimilation Framework). This framework provides a fully parallel modular environment for performing data assimilation for the land surface and the subsurface compartment. A simple synthetic case study for a land surface–subsurface system (0.8 million unknowns) is used to demonstrate the effects of data assimilation in the integrated model TerrSysMP and to assess the scaling behaviour of the data assimilation system. Results show that data assimilation effectively corrects model states and parameters of the integrated model towards the reference values. Scaling tests provide evidence that the data assimilation system for TerrSysMP can make efficient use of parallel computational resources for  {\\textgreater} 30 k processors. Simulations with a large problem size (20 million unknowns) for the forward model were also efficiently handled by the data assimilation system. The proposed data assimilation framework is useful in simulating and estimating uncertainties in predicted states and fluxes of the terrestrial system over large spatial scales at high resolution utilising integrated models.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2023-01-23},\n\tjournal = {Geoscientific Model Development},\n\tauthor = {Kurtz, Wolfgang and He, Guowei and Kollet, Stefan J. and Maxwell, Reed M. and Vereecken, Harry and Hendricks Franssen, Harrie-Jan},\n\tmonth = apr,\n\tyear = {2016},\n\tpages = {1341--1360},\n}\n\n
\n
\n\n\n
\n Abstract. Modelling of terrestrial systems is continuously moving towards more integrated modelling approaches, where different terrestrial compartment models are combined in order to realise a more sophisticated physical description of water, energy and carbon fluxes across compartment boundaries and to provide a more integrated view on terrestrial processes. While such models can effectively reduce certain parameterisation errors of single compartment models, model predictions are still prone to uncertainties regarding model input variables. The resulting uncertainties of model predictions can be effectively tackled by data assimilation techniques, which allow one to correct model predictions with observations taking into account both the model and measurement uncertainties. The steadily increasing availability of computational resources makes it now increasingly possible to perform data assimilation also for computationally highly demanding integrated terrestrial system models. However, as the computational burden for integrated models as well as data assimilation techniques is quite large, there is an increasing need to provide computationally efficient data assimilation frameworks for integrated models that allow one to run on and to make efficient use of massively parallel computational resources. In this paper we present a data assimilation framework for the land surface–subsurface part of the Terrestrial System Modelling Platform (TerrSysMP). TerrSysMP is connected via a memory-based coupling approach with the pre-existing parallel data assimilation library PDAF (Parallel Data Assimilation Framework). This framework provides a fully parallel modular environment for performing data assimilation for the land surface and the subsurface compartment. A simple synthetic case study for a land surface–subsurface system (0.8 million unknowns) is used to demonstrate the effects of data assimilation in the integrated model TerrSysMP and to assess the scaling behaviour of the data assimilation system. Results show that data assimilation effectively corrects model states and parameters of the integrated model towards the reference values. Scaling tests provide evidence that the data assimilation system for TerrSysMP can make efficient use of parallel computational resources for  \\textgreater 30 k processors. Simulations with a large problem size (20 million unknowns) for the forward model were also efficiently handled by the data assimilation system. The proposed data assimilation framework is useful in simulating and estimating uncertainties in predicted states and fluxes of the terrestrial system over large spatial scales at high resolution utilising integrated models.\n
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\n \n\n \n \n Lausch, A.; Bannehr, L.; Beckmann, M.; Boehm, C.; Feilhauer, H.; Hacker, J.; Heurich, M.; Jung, A.; Klenke, R.; Neumann, C.; Pause, M.; Rocchini, D.; Schaepman, M.; Schmidtlein, S.; Schulz, K.; Selsam, P.; Settele, J.; Skidmore, A.; and Cord, A.\n\n\n \n \n \n \n \n Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives.\n \n \n \n \n\n\n \n\n\n\n Ecological Indicators, 70: 317–339. November 2016.\n \n\n\n\n
\n\n\n\n \n \n \"LinkingPaper\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{lausch_linking_2016,\n\ttitle = {Linking {Earth} {Observation} and taxonomic, structural and functional biodiversity: {Local} to ecosystem perspectives},\n\tvolume = {70},\n\tissn = {1470160X},\n\tshorttitle = {Linking {Earth} {Observation} and taxonomic, structural and functional biodiversity},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X16303223},\n\tdoi = {10.1016/j.ecolind.2016.06.022},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Ecological Indicators},\n\tauthor = {Lausch, A. and Bannehr, L. and Beckmann, M. and Boehm, C. and Feilhauer, H. and Hacker, J.M. and Heurich, M. and Jung, A. and Klenke, R. and Neumann, C. and Pause, M. and Rocchini, D. and Schaepman, M.E. and Schmidtlein, S. and Schulz, K. and Selsam, P. and Settele, J. and Skidmore, A.K. and Cord, A.F.},\n\tmonth = nov,\n\tyear = {2016},\n\tpages = {317--339},\n}\n\n
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\n \n\n \n \n Lausch, A.; Erasmi, S.; King, D.; Magdon, P.; and Heurich, M.\n\n\n \n \n \n \n \n Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 8(12): 1029. December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"UnderstandingPaper\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_2016,\n\ttitle = {Understanding {Forest} {Health} with {Remote} {Sensing} -{Part} {I}—{A} {Review} of {Spectral} {Traits}, {Processes} and {Remote}-{Sensing} {Characteristics}},\n\tvolume = {8},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/8/12/1029},\n\tdoi = {10.3390/rs8121029},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2023-01-23},\n\tjournal = {Remote Sensing},\n\tauthor = {Lausch, Angela and Erasmi, Stefan and King, Douglas and Magdon, Paul and Heurich, Marco},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {1029},\n}\n\n
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\n \n\n \n \n Liu, S.; Herbst, M.; Bol, R.; Gottselig, N.; Pütz, T.; Weymann, D.; Wiekenkamp, I.; Vereecken, H.; and Brüggemann, N.\n\n\n \n \n \n \n \n The contribution of hydroxylamine content to spatial variability of N$_{\\textrm{2}}$O formation in soil of a Norway spruce forest.\n \n \n \n \n\n\n \n\n\n\n Geochimica et Cosmochimica Acta, 178: 76–86. April 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\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_contribution_2016,\n\ttitle = {The contribution of hydroxylamine content to spatial variability of {N}$_{\\textrm{2}}${O} formation in soil of a {Norway} spruce forest},\n\tvolume = {178},\n\tissn = {00167037},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0016703716300102},\n\tdoi = {10.1016/j.gca.2016.01.026},\n\tlanguage = {en},\n\turldate = {2022-11-18},\n\tjournal = {Geochimica et Cosmochimica Acta},\n\tauthor = {Liu, Shurong and Herbst, Michael and Bol, Roland and Gottselig, Nina and Pütz, Thomas and Weymann, Daniel and Wiekenkamp, Inge and Vereecken, Harry and Brüggemann, Nicolas},\n\tmonth = apr,\n\tyear = {2016},\n\tpages = {76--86},\n}\n\n
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\n \n\n \n \n Liu, S.; Hintz, M.; and Li, X.\n\n\n \n \n \n \n \n Evaluation of atmosphere–land interactions in an LES from the perspective of heterogeneity propagation.\n \n \n \n \n\n\n \n\n\n\n Advances in Atmospheric Sciences, 33(5): 571–578. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"EvaluationPaper\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_evaluation_2016,\n\ttitle = {Evaluation of atmosphere–land interactions in an {LES} from the perspective of heterogeneity propagation},\n\tvolume = {33},\n\tissn = {0256-1530, 1861-9533},\n\turl = {http://link.springer.com/10.1007/s00376-015-5212-6},\n\tdoi = {10.1007/s00376-015-5212-6},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2023-01-23},\n\tjournal = {Advances in Atmospheric Sciences},\n\tauthor = {Liu, Shaofeng and Hintz, Michael and Li, Xiaolong},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {571--578},\n}\n\n
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\n \n\n \n \n Luft, L.; Neumann, C.; Itzerott, S.; Lausch, A.; Doktor, D.; Freude, M.; Blaum, N.; and Jeltsch, F.\n\n\n \n \n \n \n \n Digital and real-habitat modeling of Hipparchia statilinus based on hyper spectral remote sensing data.\n \n \n \n \n\n\n \n\n\n\n International Journal of Environmental Science and Technology, 13(1): 187–200. January 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DigitalPaper\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{luft_digital_2016,\n\ttitle = {Digital and real-habitat modeling of {Hipparchia} statilinus based on hyper spectral remote sensing data},\n\tvolume = {13},\n\tissn = {1735-1472, 1735-2630},\n\turl = {http://link.springer.com/10.1007/s13762-015-0859-1},\n\tdoi = {10.1007/s13762-015-0859-1},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-23},\n\tjournal = {International Journal of Environmental Science and Technology},\n\tauthor = {Luft, L. and Neumann, C. and Itzerott, S. and Lausch, A. and Doktor, D. and Freude, M. and Blaum, N. and Jeltsch, F.},\n\tmonth = jan,\n\tyear = {2016},\n\tpages = {187--200},\n}\n\n
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\n \n\n \n \n Marcé, R.; George, G.; Buscarinu, P.; Deidda, M.; Dunalska, J.; de Eyto, E.; Flaim, G.; Grossart, H.; Istvanovics, V.; Lenhardt, M.; Moreno-Ostos, E.; Obrador, B.; Ostrovsky, I.; Pierson, D. C.; Potužák, J.; Poikane, S.; Rinke, K.; Rodríguez-Mozaz, S.; Staehr, P. A.; Šumberová, K.; Waajen, G.; Weyhenmeyer, G. A.; Weathers, K. C.; Zion, M.; Ibelings, B. W.; and Jennings, E.\n\n\n \n \n \n \n \n Automatic High Frequency Monitoring for Improved Lake and Reservoir Management.\n \n \n \n \n\n\n \n\n\n\n Environmental Science & Technology, 50(20): 10780–10794. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AutomaticPaper\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{marce_automatic_2016,\n\ttitle = {Automatic {High} {Frequency} {Monitoring} for {Improved} {Lake} and {Reservoir} {Management}},\n\tvolume = {50},\n\tissn = {0013-936X, 1520-5851},\n\turl = {https://pubs.acs.org/doi/10.1021/acs.est.6b01604},\n\tdoi = {10.1021/acs.est.6b01604},\n\tlanguage = {en},\n\tnumber = {20},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Science \\& Technology},\n\tauthor = {Marcé, Rafael and George, Glen and Buscarinu, Paola and Deidda, Melania and Dunalska, Julita and de Eyto, Elvira and Flaim, Giovanna and Grossart, Hans-Peter and Istvanovics, Vera and Lenhardt, Mirjana and Moreno-Ostos, Enrique and Obrador, Biel and Ostrovsky, Ilia and Pierson, Donald C. and Potužák, Jan and Poikane, Sandra and Rinke, Karsten and Rodríguez-Mozaz, Sara and Staehr, Peter A. and Šumberová, Kateřina and Waajen, Guido and Weyhenmeyer, Gesa A. and Weathers, Kathleen C. and Zion, Mark and Ibelings, Bas W. and Jennings, Eleanor},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {10780--10794},\n}\n\n
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\n \n\n \n \n Maurer, V.; Kalthoff, N.; Wieser, A.; Kohler, M.; Mauder, M.; and Gantner, L.\n\n\n \n \n \n \n \n Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain.\n \n \n \n \n\n\n \n\n\n\n Atmospheric Chemistry and Physics, 16(3): 1377–1400. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ObservedPaper\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{maurer_observed_2016,\n\ttitle = {Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain},\n\tvolume = {16},\n\tissn = {1680-7324},\n\turl = {https://acp.copernicus.org/articles/16/1377/2016/},\n\tdoi = {10.5194/acp-16-1377-2016},\n\tabstract = {Abstract. In the spring of 2013, extensive measurements with multiple Doppler lidar systems were performed. The instruments were arranged in a triangle with edge lengths of about 3 km in a moderately flat, agriculturally used terrain in northwestern Germany. For 6 mostly cloud-free convective days, vertical velocity variance profiles were calculated. Weighted-averaged surface fluxes proved to be more appropriate than data from individual sites for scaling the variance profiles; but even then, the scatter of profiles was mostly larger than the statistical error. The scatter could not be explained by mean wind speed or stability, whereas time periods with significantly increased variance contained broader thermals. Periods with an elevated maximum of the variance profiles could also be related to broad thermals. Moreover, statistically significant spatial differences of variance were found. They were not influenced by the existing surface heterogeneity. Instead, thermals were preserved between two sites when the travel time was shorter than the large-eddy turnover time. At the same time, no thermals passed for more than 2 h at a third site that was located perpendicular to the mean wind direction in relation to the first two sites. Organized structures of turbulence with subsidence prevailing in the surroundings of thermals can thus partly explain significant spatial variance differences existing for several hours. Therefore, the representativeness of individual variance profiles derived from measurements at a single site cannot be assumed.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2023-02-23},\n\tjournal = {Atmospheric Chemistry and Physics},\n\tauthor = {Maurer, V. and Kalthoff, N. and Wieser, A. and Kohler, M. and Mauder, M. and Gantner, L.},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {1377--1400},\n}\n\n
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\n Abstract. In the spring of 2013, extensive measurements with multiple Doppler lidar systems were performed. The instruments were arranged in a triangle with edge lengths of about 3 km in a moderately flat, agriculturally used terrain in northwestern Germany. For 6 mostly cloud-free convective days, vertical velocity variance profiles were calculated. Weighted-averaged surface fluxes proved to be more appropriate than data from individual sites for scaling the variance profiles; but even then, the scatter of profiles was mostly larger than the statistical error. The scatter could not be explained by mean wind speed or stability, whereas time periods with significantly increased variance contained broader thermals. Periods with an elevated maximum of the variance profiles could also be related to broad thermals. Moreover, statistically significant spatial differences of variance were found. They were not influenced by the existing surface heterogeneity. Instead, thermals were preserved between two sites when the travel time was shorter than the large-eddy turnover time. At the same time, no thermals passed for more than 2 h at a third site that was located perpendicular to the mean wind direction in relation to the first two sites. Organized structures of turbulence with subsidence prevailing in the surroundings of thermals can thus partly explain significant spatial variance differences existing for several hours. Therefore, the representativeness of individual variance profiles derived from measurements at a single site cannot be assumed.\n
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\n \n\n \n \n Medinets, S; Gasche, R; Skiba, U; Schindlbacher, A; Kiese, R; and Butterbach-Bahl, K\n\n\n \n \n \n \n \n Cold season soil NO fluxes from a temperate forest: drivers and contribution to annual budgets.\n \n \n \n \n\n\n \n\n\n\n Environmental Research Letters, 11(11): 114012. November 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ColdPaper\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{medinets_cold_2016,\n\ttitle = {Cold season soil {NO} fluxes from a temperate forest: drivers and contribution to annual budgets},\n\tvolume = {11},\n\tissn = {1748-9326},\n\tshorttitle = {Cold season soil {NO} fluxes from a temperate forest},\n\turl = {https://iopscience.iop.org/article/10.1088/1748-9326/11/11/114012},\n\tdoi = {10.1088/1748-9326/11/11/114012},\n\tnumber = {11},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Research Letters},\n\tauthor = {Medinets, S and Gasche, R and Skiba, U and Schindlbacher, A and Kiese, R and Butterbach-Bahl, K},\n\tmonth = nov,\n\tyear = {2016},\n\tpages = {114012},\n}\n\n
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\n \n\n \n \n Merz, S.; Pohlmeier, A.; Balcom, B. J.; Enjilela, R.; and Vereecken, H.\n\n\n \n \n \n \n \n Drying of a Natural Soil Under Evaporative Conditions: A Comparison of Different Magnetic Resonance Methods.\n \n \n \n \n\n\n \n\n\n\n Applied Magnetic Resonance, 47(2): 121–138. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DryingPaper\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{merz_drying_2016,\n\ttitle = {Drying of a {Natural} {Soil} {Under} {Evaporative} {Conditions}: {A} {Comparison} of {Different} {Magnetic} {Resonance} {Methods}},\n\tvolume = {47},\n\tissn = {0937-9347, 1613-7507},\n\tshorttitle = {Drying of a {Natural} {Soil} {Under} {Evaporative} {Conditions}},\n\turl = {http://link.springer.com/10.1007/s00723-015-0736-6},\n\tdoi = {10.1007/s00723-015-0736-6},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2023-01-23},\n\tjournal = {Applied Magnetic Resonance},\n\tauthor = {Merz, Steffen and Pohlmeier, Andreas and Balcom, Bruce J. and Enjilela, Razieh and Vereecken, Harry},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {121--138},\n}\n\n
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\n \n\n \n \n Missong, A.; Bol, R.; Willbold, S.; Siemens, J.; and Klumpp, E.\n\n\n \n \n \n \n \n Phosphorus forms in forest soil colloids as revealed by liquid‐state $^{\\textrm{31}}$ P‐NMR.\n \n \n \n \n\n\n \n\n\n\n Journal of Plant Nutrition and Soil Science, 179(2): 159–167. April 2016.\n \n\n\n\n
\n\n\n\n \n \n \"PhosphorusPaper\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_2016,\n\ttitle = {Phosphorus forms in forest soil colloids as revealed by liquid‐state $^{\\textrm{31}}$ {P}‐{NMR}},\n\tvolume = {179},\n\tissn = {1436-8730, 1522-2624},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/jpln.201500119},\n\tdoi = {10.1002/jpln.201500119},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Plant Nutrition and Soil Science},\n\tauthor = {Missong, Anna and Bol, Roland and Willbold, Sabine and Siemens, Jan and Klumpp, Erwin},\n\tmonth = apr,\n\tyear = {2016},\n\tpages = {159--167},\n}\n\n
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\n \n\n \n \n Montzka, C.; Jagdhuber, T.; Horn, R.; Bogena, H. R.; Hajnsek, I.; Reigber, A.; and Vereecken, H.\n\n\n \n \n \n \n \n Investigation of SMAP Fusion Algorithms With Airborne Active and Passive L-Band Microwave Remote Sensing.\n \n \n \n \n\n\n \n\n\n\n IEEE Transactions on Geoscience and Remote Sensing, 54(7): 3878–3889. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"InvestigationPaper\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{montzka_investigation_2016,\n\ttitle = {Investigation of {SMAP} {Fusion} {Algorithms} {With} {Airborne} {Active} and {Passive} {L}-{Band} {Microwave} {Remote} {Sensing}},\n\tvolume = {54},\n\tissn = {0196-2892, 1558-0644},\n\turl = {http://ieeexplore.ieee.org/document/7426813/},\n\tdoi = {10.1109/TGRS.2016.2529659},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {IEEE Transactions on Geoscience and Remote Sensing},\n\tauthor = {Montzka, Carsten and Jagdhuber, Thomas and Horn, Ralf and Bogena, Heye R. and Hajnsek, Irena and Reigber, Andreas and Vereecken, Harry},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {3878--3889},\n}\n\n
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\n \n\n \n \n Moreira, S.; Schultze, M.; Rahn, K.; and Boehrer, B.\n\n\n \n \n \n \n \n A practical approach to lake water density from electrical conductivity and temperature.\n \n \n \n \n\n\n \n\n\n\n Hydrology and Earth System Sciences, 20(7): 2975–2986. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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{moreira_practical_2016,\n\ttitle = {A practical approach to lake water density from electrical conductivity and temperature},\n\tvolume = {20},\n\tissn = {1607-7938},\n\turl = {https://hess.copernicus.org/articles/20/2975/2016/},\n\tdoi = {10.5194/hess-20-2975-2016},\n\tabstract = {Abstract. Density calculations are essential to study stratification, circulation patterns, internal wave formation and other aspects of hydrodynamics in lakes and reservoirs. Currently, the most common procedure is the use of CTD (conductivity, temperature and depth) profilers and the conversion of measurements of temperature and electrical conductivity into density. In limnic waters, such approaches are of limited accuracy if they do not consider lake-specific composition of solutes, as we show. A new approach is presented to correlate density and electrical conductivity, using only two specific coefficients based on the composition of solutes. First, it is necessary to evaluate the lake-specific coefficients connecting electrical conductivity with density. Once these coefficients have been obtained, density can easily be calculated based on CTD data. The new method has been tested against measured values and the most common equations used in the calculation of density in limnic and ocean conditions. The results show that our new approach can reproduce the density contribution of solutes with a relative error of less than 10 \\% in lake waters from very low to very high concentrations as well as in lakes of very particular water chemistry, which is better than all commonly implemented density calculations in lakes. Finally, a web link is provided for downloading the corresponding density calculator.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {Hydrology and Earth System Sciences},\n\tauthor = {Moreira, Santiago and Schultze, Martin and Rahn, Karsten and Boehrer, Bertram},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {2975--2986},\n}\n\n
\n
\n\n\n
\n Abstract. Density calculations are essential to study stratification, circulation patterns, internal wave formation and other aspects of hydrodynamics in lakes and reservoirs. Currently, the most common procedure is the use of CTD (conductivity, temperature and depth) profilers and the conversion of measurements of temperature and electrical conductivity into density. In limnic waters, such approaches are of limited accuracy if they do not consider lake-specific composition of solutes, as we show. A new approach is presented to correlate density and electrical conductivity, using only two specific coefficients based on the composition of solutes. First, it is necessary to evaluate the lake-specific coefficients connecting electrical conductivity with density. Once these coefficients have been obtained, density can easily be calculated based on CTD data. The new method has been tested against measured values and the most common equations used in the calculation of density in limnic and ocean conditions. The results show that our new approach can reproduce the density contribution of solutes with a relative error of less than 10 % in lake waters from very low to very high concentrations as well as in lakes of very particular water chemistry, which is better than all commonly implemented density calculations in lakes. Finally, a web link is provided for downloading the corresponding density calculator.\n
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\n \n\n \n \n Morling, K.; Kamjunke, N.; and Tittel, J.\n\n\n \n \n \n \n \n A simplified method of recovering CO2 from bacterioplankton respiration for isotopic analysis.\n \n \n \n \n\n\n \n\n\n\n Journal of Microbiological Methods, 121: 8–10. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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{morling_simplified_2016,\n\ttitle = {A simplified method of recovering {CO2} from bacterioplankton respiration for isotopic analysis},\n\tvolume = {121},\n\tissn = {01677012},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0167701215301305},\n\tdoi = {10.1016/j.mimet.2015.12.008},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Microbiological Methods},\n\tauthor = {Morling, Karoline and Kamjunke, Norbert and Tittel, Jörg},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {8--10},\n}\n\n
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\n \n\n \n \n Mozaffari, A.; Klotzsche, A.; He, G.; Vereecken, H.; van der Kruk, J.; Warren, C.; and Giannopoulos, A.\n\n\n \n \n \n \n \n Towards 3D full-waveform inversion of crosshole GPR data.\n \n \n \n \n\n\n \n\n\n\n In 2016 16th International Conference on Ground Penetrating Radar (GPR), pages 1–4, Hong Kong, Hong Kong, June 2016. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\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{mozaffari_towards_2016,\n\taddress = {Hong Kong, Hong Kong},\n\ttitle = {Towards {3D} full-waveform inversion of crosshole {GPR} data},\n\tisbn = {9781509051816},\n\turl = {http://ieeexplore.ieee.org/document/7572687/},\n\tdoi = {10.1109/ICGPR.2016.7572687},\n\turldate = {2023-01-23},\n\tbooktitle = {2016 16th {International} {Conference} on {Ground} {Penetrating} {Radar} ({GPR})},\n\tpublisher = {IEEE},\n\tauthor = {Mozaffari, A. and Klotzsche, A. and He, G. and Vereecken, H. and van der Kruk, J. and Warren, C. and Giannopoulos, A.},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {1--4},\n}\n\n
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\n \n\n \n \n Mueller, C.; Krieg, R.; Merz, R.; and Knöller, K.\n\n\n \n \n \n \n \n Regional nitrogen dynamics in the TERENO Bode River catchment, Germany, as constrained by stable isotope patterns.\n \n \n \n \n\n\n \n\n\n\n Isotopes in Environmental and Health Studies, 52(1-2): 61–74. March 2016.\n \n\n\n\n
\n\n\n\n \n \n \"RegionalPaper\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{mueller_regional_2016,\n\ttitle = {Regional nitrogen dynamics in the {TERENO} {Bode} {River} catchment, {Germany}, as constrained by stable isotope patterns},\n\tvolume = {52},\n\tissn = {1025-6016, 1477-2639},\n\turl = {http://www.tandfonline.com/doi/full/10.1080/10256016.2015.1019489},\n\tdoi = {10.1080/10256016.2015.1019489},\n\tlanguage = {en},\n\tnumber = {1-2},\n\turldate = {2023-02-23},\n\tjournal = {Isotopes in Environmental and Health Studies},\n\tauthor = {Mueller, Christin and Krieg, Ronald and Merz, Ralf and Knöller, Kay},\n\tmonth = mar,\n\tyear = {2016},\n\tpages = {61--74},\n}\n\n
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\n \n\n \n \n Mueller, C.; Zink, M.; Samaniego, L.; Krieg, R.; Merz, R.; Rode, M.; and Knöller, K.\n\n\n \n \n \n \n \n Discharge Driven Nitrogen Dynamics in a Mesoscale River Basin As Constrained by Stable Isotope Patterns.\n \n \n \n \n\n\n \n\n\n\n Environmental Science & Technology, 50(17): 9187–9196. September 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DischargePaper\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{mueller_discharge_2016,\n\ttitle = {Discharge {Driven} {Nitrogen} {Dynamics} in a {Mesoscale} {River} {Basin} {As} {Constrained} by {Stable} {Isotope} {Patterns}},\n\tvolume = {50},\n\tissn = {0013-936X, 1520-5851},\n\turl = {https://pubs.acs.org/doi/10.1021/acs.est.6b01057},\n\tdoi = {10.1021/acs.est.6b01057},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Science \\& Technology},\n\tauthor = {Mueller, Christin and Zink, Matthias and Samaniego, Luis and Krieg, Ronald and Merz, Ralf and Rode, Michael and Knöller, Kay},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {9187--9196},\n}\n\n
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\n \n\n \n \n Munz, M.; Oswald, S. E.; and Schmidt, C.\n\n\n \n \n \n \n \n Analysis of riverbed temperatures to determine the geometry of subsurface water flow around in-stream geomorphological structures.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 539: 74–87. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnalysisPaper\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{munz_analysis_2016,\n\ttitle = {Analysis of riverbed temperatures to determine the geometry of subsurface water flow around in-stream geomorphological structures},\n\tvolume = {539},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169416302797},\n\tdoi = {10.1016/j.jhydrol.2016.05.012},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Munz, Matthias and Oswald, Sascha E. and Schmidt, Christian},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {74--87},\n}\n\n
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\n \n\n \n \n Musolff, A.; Schmidt, C.; Rode, M.; Lischeid, G.; Weise, S. M.; and Fleckenstein, J. H.\n\n\n \n \n \n \n \n Groundwater head controls nitrate export from an agricultural lowland catchment.\n \n \n \n \n\n\n \n\n\n\n Advances in Water Resources, 96: 95–107. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"GroundwaterPaper\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{musolff_groundwater_2016,\n\ttitle = {Groundwater head controls nitrate export from an agricultural lowland catchment},\n\tvolume = {96},\n\tissn = {03091708},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0309170816302172},\n\tdoi = {10.1016/j.advwatres.2016.07.003},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Advances in Water Resources},\n\tauthor = {Musolff, Andreas and Schmidt, Christian and Rode, Michael and Lischeid, Gunnar and Weise, Stephan M. and Fleckenstein, Jan H.},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {95--107},\n}\n\n
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\n \n\n \n \n Pause, M.; Schweitzer, C.; Rosenthal, M.; Keuck, V.; Bumberger, J.; Dietrich, P.; Heurich, M.; Jung, A.; and Lausch, A.\n\n\n \n \n \n \n \n In Situ/Remote Sensing Integration to Assess Forest Health—A Review.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 8(6): 471. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"InPaper\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{pause_situremote_2016,\n\ttitle = {In {Situ}/{Remote} {Sensing} {Integration} to {Assess} {Forest} {Health}—{A} {Review}},\n\tvolume = {8},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/8/6/471},\n\tdoi = {10.3390/rs8060471},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2023-01-23},\n\tjournal = {Remote Sensing},\n\tauthor = {Pause, Marion and Schweitzer, Christian and Rosenthal, Michael and Keuck, Vanessa and Bumberger, Jan and Dietrich, Peter and Heurich, Marco and Jung, András and Lausch, Angela},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {471},\n}\n\n
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\n \n\n \n \n Pritzkow, C.; Wazny, T.; Heußner, K.; Słowiński, M.; Bieber, A.; Liñán, I. D.; Helle, G.; and Heinrich, I.\n\n\n \n \n \n \n \n Minimum winter temperature reconstruction from average earlywood vessel area of European oak (Quercus robur) in N-Poland.\n \n \n \n \n\n\n \n\n\n\n Palaeogeography, Palaeoclimatology, Palaeoecology, 449: 520–530. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MinimumPaper\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{pritzkow_minimum_2016,\n\ttitle = {Minimum winter temperature reconstruction from average earlywood vessel area of {European} oak ({Quercus} robur) in {N}-{Poland}},\n\tvolume = {449},\n\tissn = {00310182},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0031018216001486},\n\tdoi = {10.1016/j.palaeo.2016.02.046},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Palaeogeography, Palaeoclimatology, Palaeoecology},\n\tauthor = {Pritzkow, C. and Wazny, T. and Heußner, K.U. and Słowiński, M. and Bieber, A. and Liñán, I. Dorado and Helle, G. and Heinrich, I.},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {520--530},\n}\n\n
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\n \n\n \n \n Pütz, T.; Kiese, R.; Wollschläger, U.; Groh, J.; Rupp, H.; Zacharias, S.; Priesack, E.; Gerke, H. H.; Gasche, R.; Bens, O.; Borg, E.; Baessler, C.; Kaiser, K.; Herbrich, M.; Munch, J.; Sommer, M.; Vogel, H.; Vanderborght, J.; and Vereecken, H.\n\n\n \n \n \n \n \n TERENO-SOILCan: a lysimeter-network in Germany observing soil processes and plant diversity influenced by climate change.\n \n \n \n \n\n\n \n\n\n\n Environmental Earth Sciences, 75(18): 1242. September 2016.\n \n\n\n\n
\n\n\n\n \n \n \"TERENO-SOILCan: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{putz_tereno-soilcan_2016,\n\ttitle = {{TERENO}-{SOILCan}: a lysimeter-network in {Germany} observing soil processes and plant diversity influenced by climate change},\n\tvolume = {75},\n\tissn = {1866-6280, 1866-6299},\n\tshorttitle = {{TERENO}-{SOILCan}},\n\turl = {http://link.springer.com/10.1007/s12665-016-6031-5},\n\tdoi = {10.1007/s12665-016-6031-5},\n\tlanguage = {en},\n\tnumber = {18},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Earth Sciences},\n\tauthor = {Pütz, Th. and Kiese, R. and Wollschläger, U. and Groh, J. and Rupp, H. and Zacharias, S. and Priesack, E. and Gerke, H. H. and Gasche, R. and Bens, O. and Borg, E. and Baessler, C. and Kaiser, K. and Herbrich, M. and Munch, J.-C. and Sommer, M. and Vogel, H.-J. and Vanderborght, J. and Vereecken, H.},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {1242},\n}\n\n
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\n \n\n \n \n Qu, W.; Bogena, H. R.; Huisman, J. A.; Schmidt, M.; Kunkel, R.; Weuthen, A.; Schiedung, H.; Schilling, B.; Sorg, J.; and Vereecken, H.\n\n\n \n \n \n \n \n The integrated water balance and soil data set of the Rollesbroich hydrological observatory.\n \n \n \n \n\n\n \n\n\n\n Earth System Science Data, 8(2): 517–529. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\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{qu_integrated_2016,\n\ttitle = {The integrated water balance and soil data set of the {Rollesbroich} hydrological observatory},\n\tvolume = {8},\n\tissn = {1866-3516},\n\turl = {https://essd.copernicus.org/articles/8/517/2016/},\n\tdoi = {10.5194/essd-8-517-2016},\n\tabstract = {Abstract. The Rollesbroich headwater catchment located in western Germany is a densely instrumented hydrological observatory and part of the TERENO (Terrestrial Environmental Observatories) initiative. The measurements acquired in this observatory present a comprehensive data set that contains key hydrological fluxes in addition to important hydrological states and properties. Meteorological data (i.e., precipitation, air temperature, air humidity, radiation components, and wind speed) are continuously recorded and actual evapotranspiration is measured using the eddy covariance technique. Runoff is measured at the catchment outlet with a gauging station. In addition, spatiotemporal variations in soil water content and temperature are measured at high resolution with a wireless sensor network (SoilNet). Soil physical properties were determined using standard laboratory procedures from samples taken at a large number of locations in the catchment. This comprehensive data set can be used to validate remote sensing retrievals and hydrological models, to improve the understanding of spatial temporal dynamics of soil water content, to optimize data assimilation and inverse techniques for hydrological models, and to develop upscaling and downscaling procedures of soil water content information. The complete data set is freely available online (http://www.tereno.net, doi:10.5880/TERENO.2016.001, doi:10.5880/TERENO.2016.004, doi:10.5880/TERENO.2016.003) and additionally referenced by three persistent identifiers securing the long-term data and metadata availability.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2023-01-23},\n\tjournal = {Earth System Science Data},\n\tauthor = {Qu, Wei and Bogena, Heye R. and Huisman, Johan A. and Schmidt, Marius and Kunkel, Ralf and Weuthen, Ansgar and Schiedung, Henning and Schilling, Bernd and Sorg, Jürgen and Vereecken, Harry},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {517--529},\n}\n\n
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\n\n\n
\n Abstract. The Rollesbroich headwater catchment located in western Germany is a densely instrumented hydrological observatory and part of the TERENO (Terrestrial Environmental Observatories) initiative. The measurements acquired in this observatory present a comprehensive data set that contains key hydrological fluxes in addition to important hydrological states and properties. Meteorological data (i.e., precipitation, air temperature, air humidity, radiation components, and wind speed) are continuously recorded and actual evapotranspiration is measured using the eddy covariance technique. Runoff is measured at the catchment outlet with a gauging station. In addition, spatiotemporal variations in soil water content and temperature are measured at high resolution with a wireless sensor network (SoilNet). Soil physical properties were determined using standard laboratory procedures from samples taken at a large number of locations in the catchment. This comprehensive data set can be used to validate remote sensing retrievals and hydrological models, to improve the understanding of spatial temporal dynamics of soil water content, to optimize data assimilation and inverse techniques for hydrological models, and to develop upscaling and downscaling procedures of soil water content information. The complete data set is freely available online (http://www.tereno.net, doi:10.5880/TERENO.2016.001, doi:10.5880/TERENO.2016.004, doi:10.5880/TERENO.2016.003) and additionally referenced by three persistent identifiers securing the long-term data and metadata availability.\n
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\n \n\n \n \n Rabbel, I.; Diekkrüger, B.; Voigt, H.; and Neuwirth, B.\n\n\n \n \n \n \n \n Comparing ∆Tmax Determination Approaches for Granier-Based Sapflow Estimations.\n \n \n \n \n\n\n \n\n\n\n Sensors, 16(12): 2042. December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ComparingPaper\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{rabbel_comparing_2016,\n\ttitle = {Comparing ∆{Tmax} {Determination} {Approaches} for {Granier}-{Based} {Sapflow} {Estimations}},\n\tvolume = {16},\n\tissn = {1424-8220},\n\turl = {http://www.mdpi.com/1424-8220/16/12/2042},\n\tdoi = {10.3390/s16122042},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2023-01-23},\n\tjournal = {Sensors},\n\tauthor = {Rabbel, Inken and Diekkrüger, Bernd and Voigt, Holm and Neuwirth, Burkhard},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {2042},\n}\n\n
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\n \n\n \n \n Raeke, J.; Lechtenfeld, O. J.; Wagner, M.; Herzsprung, P.; and Reemtsma, T.\n\n\n \n \n \n \n \n Selectivity of solid phase extraction of freshwater dissolved organic matter and its effect on ultrahigh resolution mass spectra.\n \n \n \n \n\n\n \n\n\n\n Environmental Science: Processes & Impacts, 18(7): 918–927. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SelectivityPaper\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{raeke_selectivity_2016,\n\ttitle = {Selectivity of solid phase extraction of freshwater dissolved organic matter and its effect on ultrahigh resolution mass spectra},\n\tvolume = {18},\n\tissn = {2050-7887, 2050-7895},\n\turl = {http://xlink.rsc.org/?DOI=C6EM00200E},\n\tdoi = {10.1039/C6EM00200E},\n\tabstract = {Solid phase extracts of freshwater dissolved organic matter are compared to the original sample with use of complementary techniques. \n          ,  \n            Solid phase extraction (SPE) is often used for enrichment and clean-up prior to analysis of dissolved organic matter (DOM) by electrospray ionization (ESI) coupled to ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). It is generally accepted that extraction by SPE is not quantitative with respect to carbon concentration. However, little information is available on the selectivity of different SPE sorbents and the resulting effect for the acquired DOM mass spectra. Freshwater samples were extracted by the widely used PPL, HLB and C18 sorbents and the molecular composition and size distribution of the DOM in the extracts and in the permeates was compared to the original sample. Dissolved organic carbon (DOC) recoveries ranged between 20\\% and 65\\% for the three tested SPE sorbents. Size-exclusion chromatography coupled to organic carbon detection (SEC-OCD) revealed that limited recovery by PPL and HLB was primarily due to incomplete elution of a fraction of apparent high molecular weight from the solid phase. In contrast, incomplete retention on the solid phase, mainly observed for the C18 cartridge, was attributed to a fraction of low molecular weight. The FT-ICR mass spectra of the original sample and the SPE extracts did not differ significantly in their molecular weight distribution, but they showed sorbent specific differences in the degree of oxygenation and saturation. We concluded that the selective enrichment of freshwater DOM by SPE is less critical for subsequent FT-ICR MS analysis, because those fractions that are not sufficiently recovered have comparatively small effects on the mass spectra. This was confirmed by the extraction of model compounds, showing that very polar and small molecules are poorly extracted, but also have a low response in ESI-MS. Of the three tested SPE cartridges the PPL material offered the best properties for DOM enrichment for subsequent FT-ICR MS analysis as it minimizes too strong and too weak DOM–sorbent interactions.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Science: Processes \\& Impacts},\n\tauthor = {Raeke, Julia and Lechtenfeld, Oliver J. and Wagner, Martin and Herzsprung, Peter and Reemtsma, Thorsten},\n\tyear = {2016},\n\tpages = {918--927},\n}\n\n
\n
\n\n\n
\n Solid phase extracts of freshwater dissolved organic matter are compared to the original sample with use of complementary techniques. , Solid phase extraction (SPE) is often used for enrichment and clean-up prior to analysis of dissolved organic matter (DOM) by electrospray ionization (ESI) coupled to ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). It is generally accepted that extraction by SPE is not quantitative with respect to carbon concentration. However, little information is available on the selectivity of different SPE sorbents and the resulting effect for the acquired DOM mass spectra. Freshwater samples were extracted by the widely used PPL, HLB and C18 sorbents and the molecular composition and size distribution of the DOM in the extracts and in the permeates was compared to the original sample. Dissolved organic carbon (DOC) recoveries ranged between 20% and 65% for the three tested SPE sorbents. Size-exclusion chromatography coupled to organic carbon detection (SEC-OCD) revealed that limited recovery by PPL and HLB was primarily due to incomplete elution of a fraction of apparent high molecular weight from the solid phase. In contrast, incomplete retention on the solid phase, mainly observed for the C18 cartridge, was attributed to a fraction of low molecular weight. The FT-ICR mass spectra of the original sample and the SPE extracts did not differ significantly in their molecular weight distribution, but they showed sorbent specific differences in the degree of oxygenation and saturation. We concluded that the selective enrichment of freshwater DOM by SPE is less critical for subsequent FT-ICR MS analysis, because those fractions that are not sufficiently recovered have comparatively small effects on the mass spectra. This was confirmed by the extraction of model compounds, showing that very polar and small molecules are poorly extracted, but also have a low response in ESI-MS. Of the three tested SPE cartridges the PPL material offered the best properties for DOM enrichment for subsequent FT-ICR MS analysis as it minimizes too strong and too weak DOM–sorbent interactions.\n
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\n \n\n \n \n Rahman, M.; Sulis, M.; and Kollet, S. J.\n\n\n \n \n \n \n \n Evaluating the dual-boundary forcing concept in subsurface-land surface interactions of the hydrological cycle: Evaluating the Dual-Boundary Forcing Concept.\n \n \n \n \n\n\n \n\n\n\n Hydrological Processes, 30(10): 1563–1573. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"EvaluatingPaper\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{rahman_evaluating_2016,\n\ttitle = {Evaluating the dual-boundary forcing concept in subsurface-land surface interactions of the hydrological cycle: {Evaluating} the {Dual}-{Boundary} {Forcing} {Concept}},\n\tvolume = {30},\n\tissn = {08856087},\n\tshorttitle = {Evaluating the dual-boundary forcing concept in subsurface-land surface interactions of the hydrological cycle},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/hyp.10702},\n\tdoi = {10.1002/hyp.10702},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2023-01-23},\n\tjournal = {Hydrological Processes},\n\tauthor = {Rahman, M. and Sulis, M. and Kollet, S. J.},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {1563--1573},\n}\n\n
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\n \n\n \n \n Rakovec, O.; Kumar, R.; Mai, J.; Cuntz, M.; Thober, S.; Zink, M.; Attinger, S.; Schäfer, D.; Schrön, M.; and Samaniego, L.\n\n\n \n \n \n \n \n Multiscale and Multivariate Evaluation of Water Fluxes and States over European River Basins.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrometeorology, 17(1): 287–307. January 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MultiscalePaper\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{rakovec_multiscale_2016,\n\ttitle = {Multiscale and {Multivariate} {Evaluation} of {Water} {Fluxes} and {States} over {European} {River} {Basins}},\n\tvolume = {17},\n\tissn = {1525-755X, 1525-7541},\n\turl = {http://journals.ametsoc.org/doi/10.1175/JHM-D-15-0054.1},\n\tdoi = {10.1175/JHM-D-15-0054.1},\n\tabstract = {Abstract \n            Accurately predicting regional-scale water fluxes and states remains a challenging task in contemporary hydrology. Coping with this grand challenge requires, among other things, a model that makes reliable predictions across scales, locations, and variables other than those used for parameter estimation. In this study, the mesoscale hydrologic model (mHM) parameterized with the multiscale regionalization technique is comprehensively tested across 400 European river basins. The model fluxes and states, constrained using the observed streamflow, are evaluated against gridded evapotranspiration, soil moisture, and total water storage anomalies, as well as local-scale eddy covariance observations. This multiscale verification is carried out in a seamless manner at the native resolutions of available datasets, varying from 0.5 to 100 km. Results of cross-validation tests show that mHM is able to capture the streamflow dynamics adequately well across a wide range of climate and physiographical characteristics. The model yields generally better results (with lower spread of model statistics) in basins with higher rain gauge density. Model performance for other fluxes and states is strongly driven by the degree of seasonality that each variable exhibits, with the best match being observed for evapotranspiration, followed by total water storage anomaly, and the least for soil moisture. Results show that constraining the model against streamflow only may be necessary but not sufficient to warrant the model fidelity for other complementary variables. The study emphasizes the need to account for other complementary datasets besides streamflow during parameter estimation to improve model skill with respect to “hidden” variables.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrometeorology},\n\tauthor = {Rakovec, Oldrich and Kumar, Rohini and Mai, Juliane and Cuntz, Matthias and Thober, Stephan and Zink, Matthias and Attinger, Sabine and Schäfer, David and Schrön, Martin and Samaniego, Luis},\n\tmonth = jan,\n\tyear = {2016},\n\tpages = {287--307},\n}\n\n
\n
\n\n\n
\n Abstract Accurately predicting regional-scale water fluxes and states remains a challenging task in contemporary hydrology. Coping with this grand challenge requires, among other things, a model that makes reliable predictions across scales, locations, and variables other than those used for parameter estimation. In this study, the mesoscale hydrologic model (mHM) parameterized with the multiscale regionalization technique is comprehensively tested across 400 European river basins. The model fluxes and states, constrained using the observed streamflow, are evaluated against gridded evapotranspiration, soil moisture, and total water storage anomalies, as well as local-scale eddy covariance observations. This multiscale verification is carried out in a seamless manner at the native resolutions of available datasets, varying from 0.5 to 100 km. Results of cross-validation tests show that mHM is able to capture the streamflow dynamics adequately well across a wide range of climate and physiographical characteristics. The model yields generally better results (with lower spread of model statistics) in basins with higher rain gauge density. Model performance for other fluxes and states is strongly driven by the degree of seasonality that each variable exhibits, with the best match being observed for evapotranspiration, followed by total water storage anomaly, and the least for soil moisture. Results show that constraining the model against streamflow only may be necessary but not sufficient to warrant the model fidelity for other complementary variables. The study emphasizes the need to account for other complementary datasets besides streamflow during parameter estimation to improve model skill with respect to “hidden” variables.\n
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\n \n\n \n \n Reichenau, T. G.; Korres, W.; Montzka, C.; Fiener, P.; Wilken, F.; Stadler, A.; Waldhoff, G.; and Schneider, K.\n\n\n \n \n \n \n \n Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).\n \n \n \n \n\n\n \n\n\n\n PLOS ONE, 11(7): e0158451. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SpatialPaper\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{reichenau_spatial_2016,\n\ttitle = {Spatial {Heterogeneity} of {Leaf} {Area} {Index} ({LAI}) and {Its} {Temporal} {Course} on {Arable} {Land}: {Combining} {Field} {Measurements}, {Remote} {Sensing} and {Simulation} in a {Comprehensive} {Data} {Analysis} {Approach} ({CDAA})},\n\tvolume = {11},\n\tissn = {1932-6203},\n\tshorttitle = {Spatial {Heterogeneity} of {Leaf} {Area} {Index} ({LAI}) and {Its} {Temporal} {Course} on {Arable} {Land}},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0158451},\n\tdoi = {10.1371/journal.pone.0158451},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {PLOS ONE},\n\tauthor = {Reichenau, Tim G. and Korres, Wolfgang and Montzka, Carsten and Fiener, Peter and Wilken, Florian and Stadler, Anja and Waldhoff, Guido and Schneider, Karl},\n\teditor = {Hui, Dafeng},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {e0158451},\n}\n\n
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\n \n\n \n \n Richter, R.; Reu, B.; Wirth, C.; Doktor, D.; and Vohland, M.\n\n\n \n \n \n \n \n The use of airborne hyperspectral data for tree species classification in a species-rich Central European forest area.\n \n \n \n \n\n\n \n\n\n\n International Journal of Applied Earth Observation and Geoinformation, 52: 464–474. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\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{richter_use_2016,\n\ttitle = {The use of airborne hyperspectral data for tree species classification in a species-rich {Central} {European} forest area},\n\tvolume = {52},\n\tissn = {15698432},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0303243416301258},\n\tdoi = {10.1016/j.jag.2016.07.018},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {International Journal of Applied Earth Observation and Geoinformation},\n\tauthor = {Richter, Ronny and Reu, Björn and Wirth, Christian and Doktor, Daniel and Vohland, Michael},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {464--474},\n}\n\n
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\n \n\n \n \n Rink, D.; and Arndt, T.\n\n\n \n \n \n \n \n Investigating perception of green structure configuration for afforestation in urban brownfield development by visual methods—A case study in Leipzig, Germany.\n \n \n \n \n\n\n \n\n\n\n Urban Forestry & Urban Greening, 15: 65–74. 2016.\n \n\n\n\n
\n\n\n\n \n \n \"InvestigatingPaper\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{rink_investigating_2016,\n\ttitle = {Investigating perception of green structure configuration for afforestation in urban brownfield development by visual methods—{A} case study in {Leipzig}, {Germany}},\n\tvolume = {15},\n\tissn = {16188667},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1618866715001752},\n\tdoi = {10.1016/j.ufug.2015.11.010},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Urban Forestry \\& Urban Greening},\n\tauthor = {Rink, Dieter and Arndt, Thomas},\n\tyear = {2016},\n\tpages = {65--74},\n}\n\n
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\n \n\n \n \n Rode, M.; Halbedel née Angelstein, S.; Anis, M. R.; Borchardt, D.; and Weitere, M.\n\n\n \n \n \n \n \n Continuous In-Stream Assimilatory Nitrate Uptake from High-Frequency Sensor Measurements.\n \n \n \n \n\n\n \n\n\n\n Environmental Science & Technology, 50(11): 5685–5694. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ContinuousPaper\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{rode_continuous_2016,\n\ttitle = {Continuous {In}-{Stream} {Assimilatory} {Nitrate} {Uptake} from {High}-{Frequency} {Sensor} {Measurements}},\n\tvolume = {50},\n\tissn = {0013-936X, 1520-5851},\n\turl = {https://pubs.acs.org/doi/10.1021/acs.est.6b00943},\n\tdoi = {10.1021/acs.est.6b00943},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Science \\& Technology},\n\tauthor = {Rode, Michael and Halbedel née Angelstein, Susanne and Anis, Muhammad Rehan and Borchardt, Dietrich and Weitere, Markus},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {5685--5694},\n}\n\n
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\n \n\n \n \n Rumm, A.; Foeckler, F.; Deichner, O.; Scholz, M.; and Gerisch, M.\n\n\n \n \n \n \n \n Dyke-slotting initiated rapid recovery of habitat specialists in floodplain mollusc assemblages of the Elbe River, Germany.\n \n \n \n \n\n\n \n\n\n\n Hydrobiologia, 771(1): 151–163. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Dyke-slottingPaper\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{rumm_dyke-slotting_2016,\n\ttitle = {Dyke-slotting initiated rapid recovery of habitat specialists in floodplain mollusc assemblages of the {Elbe} {River}, {Germany}},\n\tvolume = {771},\n\tissn = {0018-8158, 1573-5117},\n\turl = {http://link.springer.com/10.1007/s10750-015-2627-0},\n\tdoi = {10.1007/s10750-015-2627-0},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-23},\n\tjournal = {Hydrobiologia},\n\tauthor = {Rumm, Andrea and Foeckler, Francis and Deichner, Oskar and Scholz, Mathias and Gerisch, Michael},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {151--163},\n}\n\n
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\n \n\n \n \n Sanders, T.; Heinrich, I.; Günther, B.; and Beck, W.\n\n\n \n \n \n \n \n Increasing Water Use Efficiency Comes at a Cost for Norway Spruce.\n \n \n \n \n\n\n \n\n\n\n Forests, 7(12): 296. November 2016.\n \n\n\n\n
\n\n\n\n \n \n \"IncreasingPaper\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{sanders_increasing_2016,\n\ttitle = {Increasing {Water} {Use} {Efficiency} {Comes} at a {Cost} for {Norway} {Spruce}},\n\tvolume = {7},\n\tissn = {1999-4907},\n\turl = {http://www.mdpi.com/1999-4907/7/12/296},\n\tdoi = {10.3390/f7120296},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2023-01-23},\n\tjournal = {Forests},\n\tauthor = {Sanders, Tanja and Heinrich, Ingo and Günther, Björn and Beck, Wolfgang},\n\tmonth = nov,\n\tyear = {2016},\n\tpages = {296},\n}\n\n
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\n \n\n \n \n Scheer, C.; Meier, R.; Brüggemann, N.; Grace, P. R.; and Dannenmann, M.\n\n\n \n \n \n \n \n An improved $^{\\textrm{15}}$ N tracer approach to study denitrification and nitrogen turnover in soil incubations: Improved $^{\\textrm{15}}$ N tracer approach to study soil nitrogen turnover.\n \n \n \n \n\n\n \n\n\n\n Rapid Communications in Mass Spectrometry, 30(18): 2017–2026. September 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\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{scheer_improved_2016,\n\ttitle = {An improved $^{\\textrm{15}}$ {N} tracer approach to study denitrification and nitrogen turnover in soil incubations: {Improved} $^{\\textrm{15}}$ {N} tracer approach to study soil nitrogen turnover},\n\tvolume = {30},\n\tissn = {09514198},\n\tshorttitle = {An improved $^{\\textrm{15}}$ {N} tracer approach to study denitrification and nitrogen turnover in soil incubations},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/rcm.7689},\n\tdoi = {10.1002/rcm.7689},\n\tlanguage = {en},\n\tnumber = {18},\n\turldate = {2023-01-23},\n\tjournal = {Rapid Communications in Mass Spectrometry},\n\tauthor = {Scheer, Clemens and Meier, Rudolf and Brüggemann, Nicolas and Grace, Peter R. and Dannenmann, Michael},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {2017--2026},\n}\n\n
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\n \n\n \n \n Schickling, A.; Matveeva, M.; Damm, A.; Schween, J.; Wahner, A.; Graf, A.; Crewell, S.; and Rascher, U.\n\n\n \n \n \n \n \n Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing, 8(7): 574. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"CombiningPaper\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{schickling_combining_2016,\n\ttitle = {Combining {Sun}-{Induced} {Chlorophyll} {Fluorescence} and {Photochemical} {Reflectance} {Index} {Improves} {Diurnal} {Modeling} of {Gross} {Primary} {Productivity}},\n\tvolume = {8},\n\tissn = {2072-4292},\n\turl = {http://www.mdpi.com/2072-4292/8/7/574},\n\tdoi = {10.3390/rs8070574},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2023-01-23},\n\tjournal = {Remote Sensing},\n\tauthor = {Schickling, Anke and Matveeva, Maria and Damm, Alexander and Schween, Jan and Wahner, Andreas and Graf, Alexander and Crewell, Susanne and Rascher, Uwe},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {574},\n}\n\n
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\n \n\n \n \n Schmadel, N. M.; Ward, A. S.; Kurz, M. J.; Fleckenstein, J. H.; Zarnetske, J. P.; Hannah, D. M.; Blume, T.; Vieweg, M.; Blaen, P. J.; Schmidt, C.; Knapp, J. L.; Klaar, M. J.; Romeijn, P.; Datry, T.; Keller, T.; Folegot, S.; Arricibita, A. I. M.; and Krause, S.\n\n\n \n \n \n \n \n Stream solute tracer timescales changing with discharge and reach length confound process interpretation: SOLUTE TRACER TIMESCALES CONFOUND PROCESS INTERPRETATION.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 52(4): 3227–3245. April 2016.\n \n\n\n\n
\n\n\n\n \n \n \"StreamPaper\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{schmadel_stream_2016,\n\ttitle = {Stream solute tracer timescales changing with discharge and reach length confound process interpretation: {SOLUTE} {TRACER} {TIMESCALES} {CONFOUND} {PROCESS} {INTERPRETATION}},\n\tvolume = {52},\n\tissn = {00431397},\n\tshorttitle = {Stream solute tracer timescales changing with discharge and reach length confound process interpretation},\n\turl = {http://doi.wiley.com/10.1002/2015WR018062},\n\tdoi = {10.1002/2015WR018062},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2023-01-23},\n\tjournal = {Water Resources Research},\n\tauthor = {Schmadel, Noah M. and Ward, Adam S. and Kurz, Marie J. and Fleckenstein, Jan H. and Zarnetske, Jay P. and Hannah, David M. and Blume, Theresa and Vieweg, Michael and Blaen, Phillip J. and Schmidt, Christian and Knapp, Julia L.A. and Klaar, Megan J. and Romeijn, Paul and Datry, Thibault and Keller, Toralf and Folegot, Silvia and Arricibita, Amaia I. Marruedo and Krause, Stefan},\n\tmonth = apr,\n\tyear = {2016},\n\tpages = {3227--3245},\n}\n\n
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\n \n\n \n \n Schneidewind, U.; van Berkel, M.; Anibas, C.; Vandersteen, G.; Schmidt, C.; Joris, I.; Seuntjens, P.; Batelaan, O.; and Zwart, H. J.\n\n\n \n \n \n \n \n LPMLE3: A novel 1-D approach to study water flow in streambeds using heat as a tracer: LPMLE3 METHOD.\n \n \n \n \n\n\n \n\n\n\n Water Resources Research, 52(8): 6596–6610. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"LPMLE3: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{schneidewind_lpmle3_2016,\n\ttitle = {{LPMLE3}: {A} novel 1-{D} approach to study water flow in streambeds using heat as a tracer: {LPMLE3} {METHOD}},\n\tvolume = {52},\n\tissn = {00431397},\n\tshorttitle = {{LPMLE3}},\n\turl = {http://doi.wiley.com/10.1002/2015WR017453},\n\tdoi = {10.1002/2015WR017453},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2023-01-23},\n\tjournal = {Water Resources Research},\n\tauthor = {Schneidewind, U. and van Berkel, M. and Anibas, C. and Vandersteen, G. and Schmidt, C. and Joris, I. and Seuntjens, P. and Batelaan, O. and Zwart, H. J.},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {6596--6610},\n}\n\n
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\n \n\n \n \n Siegmund, J. F.; Sanders, T. G. M.; Heinrich, I.; van der Maaten, E.; Simard, S.; Helle, G.; and Donner, R. V.\n\n\n \n \n \n \n \n Meteorological Drivers of Extremes in Daily Stem Radius Variations of Beech, Oak, and Pine in Northeastern Germany: An Event Coincidence Analysis.\n \n \n \n \n\n\n \n\n\n\n Frontiers in Plant Science, 7. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MeteorologicalPaper\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{siegmund_meteorological_2016,\n\ttitle = {Meteorological {Drivers} of {Extremes} in {Daily} {Stem} {Radius} {Variations} of {Beech}, {Oak}, and {Pine} in {Northeastern} {Germany}: {An} {Event} {Coincidence} {Analysis}},\n\tvolume = {7},\n\tissn = {1664-462X},\n\tshorttitle = {Meteorological {Drivers} of {Extremes} in {Daily} {Stem} {Radius} {Variations} of {Beech}, {Oak}, and {Pine} in {Northeastern} {Germany}},\n\turl = {http://journal.frontiersin.org/Article/10.3389/fpls.2016.00733/abstract},\n\tdoi = {10.3389/fpls.2016.00733},\n\turldate = {2023-01-23},\n\tjournal = {Frontiers in Plant Science},\n\tauthor = {Siegmund, Jonatan F. and Sanders, Tanja G. M. and Heinrich, Ingo and van der Maaten, Ernst and Simard, Sonia and Helle, Gerhard and Donner, Reik V.},\n\tmonth = jun,\n\tyear = {2016},\n}\n\n
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\n \n\n \n \n Stockinger, M. P.; Bogena, H. R.; Lücke, A.; Diekkrüger, B.; Cornelissen, T.; and Vereecken, H.\n\n\n \n \n \n \n \n Tracer sampling frequency influences estimates of young water fraction and streamwater transit time distribution.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 541: 952–964. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"TracerPaper\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{stockinger_tracer_2016,\n\ttitle = {Tracer sampling frequency influences estimates of young water fraction and streamwater transit time distribution},\n\tvolume = {541},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169416304863},\n\tdoi = {10.1016/j.jhydrol.2016.08.007},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Stockinger, Michael P. and Bogena, Heye R. and Lücke, Andreas and Diekkrüger, Bernd and Cornelissen, Thomas and Vereecken, Harry},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {952--964},\n}\n\n
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\n \n\n \n \n Ueberham, M.; Kabisch, S.; and Kuhlicke, C.\n\n\n \n \n \n \n Resilience, risk communication and responsibility in the context of flood prevention - the relation between public protection and private mitigation in flood-prone settlements.\n \n \n \n\n\n \n\n\n\n Hydrologie und Wasserbewirtschaftung, 60(2): 135–145. 2016.\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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@article{ueberham_resilience_2016,\n\ttitle = {Resilience, risk communication and responsibility in the context of flood prevention - the relation between public protection and private mitigation in flood-prone settlements},\n\tvolume = {60},\n\tnumber = {2},\n\tjournal = {Hydrologie und Wasserbewirtschaftung},\n\tauthor = {Ueberham, M. and Kabisch, S. and Kuhlicke, C.},\n\tyear = {2016},\n\tpages = {135--145},\n}\n\n
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\n \n\n \n \n Van Stan, J. T.; Lewis, E. S.; Hildebrandt, A.; Rebmann, C.; and Friesen, J.\n\n\n \n \n \n \n \n Impact of interacting bark structure and rainfall conditions on stemflow variability in a temperate beech-oak forest, central Germany.\n \n \n \n \n\n\n \n\n\n\n Hydrological Sciences Journal, 61(11): 2071–2083. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ImpactPaper\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_stan_impact_2016,\n\ttitle = {Impact of interacting bark structure and rainfall conditions on stemflow variability in a temperate beech-oak forest, central {Germany}},\n\tvolume = {61},\n\tissn = {0262-6667, 2150-3435},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/02626667.2015.1083104},\n\tdoi = {10.1080/02626667.2015.1083104},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2023-06-19},\n\tjournal = {Hydrological Sciences Journal},\n\tauthor = {Van Stan, John T. and Lewis, Elliott S. and Hildebrandt, Anke and Rebmann, Corinna and Friesen, Jan},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {2071--2083},\n}\n\n
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\n \n\n \n \n Vereecken, H.; Pachepsky, Y.; Simmer, C.; Rihani, J.; Kunoth, A.; Korres, W.; Graf, A.; Franssen, H.; Thiele-Eich, I.; and Shao, Y.\n\n\n \n \n \n \n \n On the role of patterns in understanding the functioning of soil-vegetation-atmosphere systems.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 542: 63–86. November 2016.\n \n\n\n\n
\n\n\n\n \n \n \"OnPaper\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{vereecken_role_2016,\n\ttitle = {On the role of patterns in understanding the functioning of soil-vegetation-atmosphere systems},\n\tvolume = {542},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169416305431},\n\tdoi = {10.1016/j.jhydrol.2016.08.053},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Vereecken, H. and Pachepsky, Y. and Simmer, C. and Rihani, J. and Kunoth, A. and Korres, W. and Graf, A. and Franssen, H.J.-Hendricks and Thiele-Eich, Insa and Shao, Y.},\n\tmonth = nov,\n\tyear = {2016},\n\tpages = {63--86},\n}\n\n
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\n \n\n \n \n Vereecken, H.; Schnepf, A.; Hopmans, J.; Javaux, M.; Or, D.; Roose, T.; Vanderborght, J.; Young, M.; Amelung, W.; Aitkenhead, M.; Allison, S.; Assouline, S.; Baveye, P.; Berli, M.; Brüggemann, N.; Finke, P.; Flury, M.; Gaiser, T.; Govers, G.; Ghezzehei, T.; Hallett, P.; Hendricks Franssen, H.; Heppell, J.; Horn, R.; Huisman, J.; Jacques, D.; Jonard, F.; Kollet, S.; Lafolie, F.; Lamorski, K.; Leitner, D.; McBratney, A.; Minasny, B.; Montzka, C.; Nowak, W.; Pachepsky, Y.; Padarian, J.; Romano, N.; Roth, K.; Rothfuss, Y.; Rowe, E.; Schwen, A.; Šimůnek, J.; Tiktak, A.; Van Dam, J.; van der Zee, S.; Vogel, H.; Vrugt, J.; Wöhling, T.; and Young, I.\n\n\n \n \n \n \n \n Modeling Soil Processes: Review, Key Challenges, and New Perspectives.\n \n \n \n \n\n\n \n\n\n\n Vadose Zone Journal, 15(5): vzj2015.09.0131. May 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ModelingPaper\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{vereecken_modeling_2016,\n\ttitle = {Modeling {Soil} {Processes}: {Review}, {Key} {Challenges}, and {New} {Perspectives}},\n\tvolume = {15},\n\tissn = {15391663},\n\tshorttitle = {Modeling {Soil} {Processes}},\n\turl = {http://doi.wiley.com/10.2136/vzj2015.09.0131},\n\tdoi = {10.2136/vzj2015.09.0131},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2023-01-23},\n\tjournal = {Vadose Zone Journal},\n\tauthor = {Vereecken, H. and Schnepf, A. and Hopmans, J.W. and Javaux, M. and Or, D. and Roose, T. and Vanderborght, J. and Young, M.H. and Amelung, W. and Aitkenhead, M. and Allison, S.D. and Assouline, S. and Baveye, P. and Berli, M. and Brüggemann, N. and Finke, P. and Flury, M. and Gaiser, T. and Govers, G. and Ghezzehei, T. and Hallett, P. and Hendricks Franssen, H.J. and Heppell, J. and Horn, R. and Huisman, J.A. and Jacques, D. and Jonard, F. and Kollet, S. and Lafolie, F. and Lamorski, K. and Leitner, D. and McBratney, A. and Minasny, B. and Montzka, C. and Nowak, W. and Pachepsky, Y. and Padarian, J. and Romano, N. and Roth, K. and Rothfuss, Y. and Rowe, E.C. and Schwen, A. and Šimůnek, J. and Tiktak, A. and Van Dam, J. and van der Zee, S.E.A.T.M. and Vogel, H.J. and Vrugt, J.A. and Wöhling, T. and Young, I.M.},\n\tmonth = may,\n\tyear = {2016},\n\tpages = {vzj2015.09.0131},\n}\n\n
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\n \n\n \n \n Verheyen, K.; Vanhellemont, M.; Auge, H.; Baeten, L.; Baraloto, C.; Barsoum, N.; Bilodeau-Gauthier, S.; Bruelheide, H.; Castagneyrol, B.; Godbold, D.; Haase, J.; Hector, A.; Jactel, H.; Koricheva, J.; Loreau, M.; Mereu, S.; Messier, C.; Muys, B.; Nolet, P.; Paquette, A.; Parker, J.; Perring, M.; Ponette, Q.; Potvin, C.; Reich, P.; Smith, A.; Weih, M.; and Scherer-Lorenzen, M.\n\n\n \n \n \n \n \n Contributions of a global network of tree diversity experiments to sustainable forest plantations.\n \n \n \n \n\n\n \n\n\n\n Ambio, 45(1): 29–41. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ContributionsPaper\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{verheyen_contributions_2016,\n\ttitle = {Contributions of a global network of tree diversity experiments to sustainable forest plantations},\n\tvolume = {45},\n\tissn = {0044-7447, 1654-7209},\n\turl = {https://link.springer.com/10.1007/s13280-015-0685-1},\n\tdoi = {10.1007/s13280-015-0685-1},\n\tabstract = {Abstract \n            The area of forest plantations is increasing worldwide helping to meet timber demand and protect natural forests. However, with global change, monospecific plantations are increasingly vulnerable to abiotic and biotic disturbances. As an adaption measure we need to move to plantations that are more diverse in genotypes, species, and structure, with a design underpinned by science. TreeDivNet, a global network of tree diversity experiments, responds to this need by assessing the advantages and disadvantages of mixed species plantations. The network currently consists of 18 experiments, distributed over 36 sites and five ecoregions. With plantations 1–15 years old, TreeDivNet can already provide relevant data for forest policy and management. In this paper, we highlight some early results on the carbon sequestration and pest resistance potential of more diverse plantations. Finally, suggestions are made for new, innovative experiments in understudied regions to complement the existing network.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-02-23},\n\tjournal = {Ambio},\n\tauthor = {Verheyen, Kris and Vanhellemont, Margot and Auge, Harald and Baeten, Lander and Baraloto, Christopher and Barsoum, Nadia and Bilodeau-Gauthier, Simon and Bruelheide, Helge and Castagneyrol, Bastien and Godbold, Douglas and Haase, Josephine and Hector, Andy and Jactel, Hervé and Koricheva, Julia and Loreau, Michel and Mereu, Simone and Messier, Christian and Muys, Bart and Nolet, Philippe and Paquette, Alain and Parker, John and Perring, Mike and Ponette, Quentin and Potvin, Catherine and Reich, Peter and Smith, Andy and Weih, Martin and Scherer-Lorenzen, Michael},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {29--41},\n}\n\n
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\n Abstract The area of forest plantations is increasing worldwide helping to meet timber demand and protect natural forests. However, with global change, monospecific plantations are increasingly vulnerable to abiotic and biotic disturbances. As an adaption measure we need to move to plantations that are more diverse in genotypes, species, and structure, with a design underpinned by science. TreeDivNet, a global network of tree diversity experiments, responds to this need by assessing the advantages and disadvantages of mixed species plantations. The network currently consists of 18 experiments, distributed over 36 sites and five ecoregions. With plantations 1–15 years old, TreeDivNet can already provide relevant data for forest policy and management. In this paper, we highlight some early results on the carbon sequestration and pest resistance potential of more diverse plantations. Finally, suggestions are made for new, innovative experiments in understudied regions to complement the existing network.\n
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\n \n\n \n \n Vieweg, M.; Kurz, M. J.; Trauth, N.; Fleckenstein, J. H.; Musolff, A.; and Schmidt, C.\n\n\n \n \n \n \n \n Estimating time-variable aerobic respiration in the streambed by combining electrical conductivity and dissolved oxygen time series: Variable Respiration in the Streambed.\n \n \n \n \n\n\n \n\n\n\n Journal of Geophysical Research: Biogeosciences, 121(8): 2199–2215. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"EstimatingPaper\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{vieweg_estimating_2016,\n\ttitle = {Estimating time-variable aerobic respiration in the streambed by combining electrical conductivity and dissolved oxygen time series: {Variable} {Respiration} in the {Streambed}},\n\tvolume = {121},\n\tissn = {21698953},\n\tshorttitle = {Estimating time-variable aerobic respiration in the streambed by combining electrical conductivity and dissolved oxygen time series},\n\turl = {http://doi.wiley.com/10.1002/2016JG003345},\n\tdoi = {10.1002/2016JG003345},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Geophysical Research: Biogeosciences},\n\tauthor = {Vieweg, Michael and Kurz, Marie J. and Trauth, Nico and Fleckenstein, Jan H. and Musolff, Andreas and Schmidt, Christian},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {2199--2215},\n}\n\n
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\n \n\n \n \n Wang, C.; Chen, Z.; Unteregelsbacher, S.; Lu, H.; Gschwendtner, S.; Gasche, R.; Kolar, A.; Schloter, M.; Kiese, R.; Butterbach-Bahl, K.; and Dannenmann, M.\n\n\n \n \n \n \n \n Climate change amplifies gross nitrogen turnover in montane grasslands of Central Europe in both summer and winter seasons.\n \n \n \n \n\n\n \n\n\n\n Global Change Biology, 22(9): 2963–2978. September 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ClimatePaper\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{wang_climate_2016,\n\ttitle = {Climate change amplifies gross nitrogen turnover in montane grasslands of {Central} {Europe} in both summer and winter seasons},\n\tvolume = {22},\n\tissn = {13541013},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/gcb.13353},\n\tdoi = {10.1111/gcb.13353},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2023-01-23},\n\tjournal = {Global Change Biology},\n\tauthor = {Wang, Changhui and Chen, Zhe and Unteregelsbacher, Sebastian and Lu, Haiyan and Gschwendtner, Silvia and Gasche, Rainer and Kolar, Allison and Schloter, Michael and Kiese, Ralf and Butterbach-Bahl, Klaus and Dannenmann, Michael},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {2963--2978},\n}\n\n
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\n \n\n \n \n Wang, S.; Seiwert, B.; Kästner, M.; Miltner, A.; Schäffer, A.; Reemtsma, T.; Yang, Q.; and Nowak, K. M.\n\n\n \n \n \n \n \n (Bio)degradation of glyphosate in water-sediment microcosms – A stable isotope co-labeling approach.\n \n \n \n \n\n\n \n\n\n\n Water Research, 99: 91–100. August 2016.\n \n\n\n\n
\n\n\n\n \n \n \"(Bio)degradationPaper\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{wang_biodegradation_2016,\n\ttitle = {({Bio})degradation of glyphosate in water-sediment microcosms – {A} stable isotope co-labeling approach},\n\tvolume = {99},\n\tissn = {00431354},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0043135416302391},\n\tdoi = {10.1016/j.watres.2016.04.041},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Water Research},\n\tauthor = {Wang, Shizong and Seiwert, Bettina and Kästner, Matthias and Miltner, Anja and Schäffer, Andreas and Reemtsma, Thorsten and Yang, Qi and Nowak, Karolina M.},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {91--100},\n}\n\n
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\n \n\n \n \n Weidauer, C.; Davis, C.; Raeke, J.; Seiwert, B.; and Reemtsma, T.\n\n\n \n \n \n \n \n Sunlight photolysis of benzotriazoles – Identification of transformation products and pathways.\n \n \n \n \n\n\n \n\n\n\n Chemosphere, 154: 416–424. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SunlightPaper\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{weidauer_sunlight_2016,\n\ttitle = {Sunlight photolysis of benzotriazoles – {Identification} of transformation products and pathways},\n\tvolume = {154},\n\tissn = {00456535},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0045653516304088},\n\tdoi = {10.1016/j.chemosphere.2016.03.090},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Chemosphere},\n\tauthor = {Weidauer, Cindy and Davis, Caroline and Raeke, Julia and Seiwert, Bettina and Reemtsma, Thorsten},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {416--424},\n}\n\n
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\n \n\n \n \n Wen, Y.; Chen, Z.; Dannenmann, M.; Carminati, A.; Willibald, G.; Kiese, R.; Wolf, B.; Veldkamp, E.; Butterbach-Bahl, K.; and Corre, M. D.\n\n\n \n \n \n \n \n Disentangling gross N2O production and consumption in soil.\n \n \n \n \n\n\n \n\n\n\n Scientific Reports, 6(1): 36517. November 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DisentanglingPaper\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{wen_disentangling_2016,\n\ttitle = {Disentangling gross {N2O} production and consumption in soil},\n\tvolume = {6},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/srep36517},\n\tdoi = {10.1038/srep36517},\n\tabstract = {Abstract \n             \n              The difficulty of measuring gross N \n              2 \n              O production and consumption in soil impedes our ability to predict N \n              2 \n              O dynamics across the soil-atmosphere interface. Our study aimed to disentangle these processes by comparing measurements from gas-flow soil core (GFSC) and \n              15 \n              N \n              2 \n              O pool dilution ( \n              15 \n              N \n              2 \n              OPD) methods. GFSC directly measures soil N \n              2 \n              O and N \n              2 \n              fluxes, with their sum as the gross N \n              2 \n              O production, whereas \n              15 \n              N \n              2 \n              OPD involves addition of \n              15 \n              N \n              2 \n              O into a chamber headspace and measuring its isotopic dilution over time. Measurements were conducted on intact soil cores from grassland, cropland, beech and pine forests. Across sites, gross N \n              2 \n              O production and consumption measured by \n              15 \n              N \n              2 \n              OPD were only 10\\% and 6\\%, respectively, of those measured by GFSC. However, \n              15 \n              N \n              2 \n              OPD remains the only method that can be used under field conditions to measure atmospheric N \n              2 \n              O uptake in soil. We propose to use different terminologies for the gross N \n              2 \n              O fluxes that these two methods quantified. For \n              15 \n              N \n              2 \n              OPD, we suggest using ‘gross N \n              2 \n              O emission and uptake’, which encompass gas exchange within the \n              15 \n              N \n              2 \n              O-labelled, soil air-filled pores. For GFSC, ‘gross N \n              2 \n              O production and consumption’ can be used, which includes both N \n              2 \n              O emitted into the soil air-filled pores and N \n              2 \n              O directly consumed, forming N \n              2 \n              , in soil anaerobic microsites.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-23},\n\tjournal = {Scientific Reports},\n\tauthor = {Wen, Yuan and Chen, Zhe and Dannenmann, Michael and Carminati, Andrea and Willibald, Georg and Kiese, Ralf and Wolf, Benjamin and Veldkamp, Edzo and Butterbach-Bahl, Klaus and Corre, Marife D.},\n\tmonth = nov,\n\tyear = {2016},\n\tpages = {36517},\n}\n\n
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\n Abstract The difficulty of measuring gross N 2 O production and consumption in soil impedes our ability to predict N 2 O dynamics across the soil-atmosphere interface. Our study aimed to disentangle these processes by comparing measurements from gas-flow soil core (GFSC) and 15 N 2 O pool dilution ( 15 N 2 OPD) methods. GFSC directly measures soil N 2 O and N 2 fluxes, with their sum as the gross N 2 O production, whereas 15 N 2 OPD involves addition of 15 N 2 O into a chamber headspace and measuring its isotopic dilution over time. Measurements were conducted on intact soil cores from grassland, cropland, beech and pine forests. Across sites, gross N 2 O production and consumption measured by 15 N 2 OPD were only 10% and 6%, respectively, of those measured by GFSC. However, 15 N 2 OPD remains the only method that can be used under field conditions to measure atmospheric N 2 O uptake in soil. We propose to use different terminologies for the gross N 2 O fluxes that these two methods quantified. For 15 N 2 OPD, we suggest using ‘gross N 2 O emission and uptake’, which encompass gas exchange within the 15 N 2 O-labelled, soil air-filled pores. For GFSC, ‘gross N 2 O production and consumption’ can be used, which includes both N 2 O emitted into the soil air-filled pores and N 2 O directly consumed, forming N 2 , in soil anaerobic microsites.\n
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\n \n\n \n \n Wiedemann, A.; Marañón-Jiménez, S.; Rebmann, C.; Herbst, M.; and Cuntz, M.\n\n\n \n \n \n \n \n An empirical study of the wound effect on sap flux density measured with thermal dissipation probes.\n \n \n \n \n\n\n \n\n\n\n Tree Physiology, 36(12): 1471–1484. December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\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{wiedemann_empirical_2016,\n\ttitle = {An empirical study of the wound effect on sap flux density measured with thermal dissipation probes},\n\tvolume = {36},\n\tissn = {0829-318X, 1758-4469},\n\turl = {https://academic.oup.com/treephys/article-lookup/doi/10.1093/treephys/tpw071},\n\tdoi = {10.1093/treephys/tpw071},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2023-01-23},\n\tjournal = {Tree Physiology},\n\tauthor = {Wiedemann, Andreas and Marañón-Jiménez, Sara and Rebmann, Corinna and Herbst, Mathias and Cuntz, Matthias},\n\teditor = {Oren, Ram},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {1471--1484},\n}\n\n
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\n \n\n \n \n Wiekenkamp, I.; Huisman, J.; Bogena, H.; Graf, A.; Lin, H.; Drüe, C.; and Vereecken, H.\n\n\n \n \n \n \n \n Changes in measured spatiotemporal patterns of hydrological response after partial deforestation in a headwater catchment.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 542: 648–661. November 2016.\n \n\n\n\n
\n\n\n\n \n \n \"ChangesPaper\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{wiekenkamp_changes_2016,\n\ttitle = {Changes in measured spatiotemporal patterns of hydrological response after partial deforestation in a headwater catchment},\n\tvolume = {542},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169416305911},\n\tdoi = {10.1016/j.jhydrol.2016.09.037},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Wiekenkamp, I. and Huisman, J.A. and Bogena, H.R. and Graf, A. and Lin, H.S. and Drüe, C. and Vereecken, H.},\n\tmonth = nov,\n\tyear = {2016},\n\tpages = {648--661},\n}\n\n
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\n \n\n \n \n Wiekenkamp, I.; Huisman, J.; Bogena, H.; Lin, H.; and Vereecken, H.\n\n\n \n \n \n \n \n Spatial and temporal occurrence of preferential flow in a forested headwater catchment.\n \n \n \n \n\n\n \n\n\n\n Journal of Hydrology, 534: 139–149. March 2016.\n \n\n\n\n
\n\n\n\n \n \n \"SpatialPaper\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{wiekenkamp_spatial_2016,\n\ttitle = {Spatial and temporal occurrence of preferential flow in a forested headwater catchment},\n\tvolume = {534},\n\tissn = {00221694},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0022169415009981},\n\tdoi = {10.1016/j.jhydrol.2015.12.050},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Journal of Hydrology},\n\tauthor = {Wiekenkamp, I. and Huisman, J.A. and Bogena, H.R. and Lin, H.S. and Vereecken, H.},\n\tmonth = mar,\n\tyear = {2016},\n\tpages = {139--149},\n}\n\n
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\n \n\n \n \n Wieneke, S.; Ahrends, H.; Damm, A.; Pinto, F.; Stadler, A.; Rossini, M.; and Rascher, U.\n\n\n \n \n \n \n \n Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing of Environment, 184: 654–667. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AirbornePaper\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{wieneke_airborne_2016,\n\ttitle = {Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: {Implications} for improved estimates of gross primary productivity},\n\tvolume = {184},\n\tissn = {00344257},\n\tshorttitle = {Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0034425716302826},\n\tdoi = {10.1016/j.rse.2016.07.025},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Remote Sensing of Environment},\n\tauthor = {Wieneke, S. and Ahrends, H. and Damm, A. and Pinto, F. and Stadler, A. and Rossini, M. and Rascher, U.},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {654--667},\n}\n\n
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\n \n\n \n \n Wissenbach, D. K.; Winkler, B.; Otto, W.; Kohajda, T.; Roeder, S.; Müller, A.; Hoeke, H.; Matysik, S.; Schlink, U.; Borte, M.; Herbarth, O.; Lehmann, I.; and von-Bergen , M.\n\n\n \n \n \n \n \n Long-term indoor VOC concentrations assessment a trend analysis of distribution, disposition, and personal exposure in cohort study samples.\n \n \n \n \n\n\n \n\n\n\n Air Quality, Atmosphere & Health, 9(8): 941–950. December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Long-termPaper\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{wissenbach_long-term_2016,\n\ttitle = {Long-term indoor {VOC} concentrations assessment a trend analysis of distribution, disposition, and personal exposure in cohort study samples},\n\tvolume = {9},\n\tissn = {1873-9318, 1873-9326},\n\turl = {http://link.springer.com/10.1007/s11869-016-0396-1},\n\tdoi = {10.1007/s11869-016-0396-1},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2023-01-23},\n\tjournal = {Air Quality, Atmosphere \\& Health},\n\tauthor = {Wissenbach, D. K. and Winkler, B. and Otto, W. and Kohajda, T. and Roeder, S. and Müller, A. and Hoeke, H. and Matysik, S. and Schlink, U. and Borte, M. and Herbarth, O. and Lehmann, I. and von-Bergen, M.},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {941--950},\n}\n\n
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\n \n\n \n \n Wulf, S.; Dräger, N.; Ott, F.; Serb, J.; Appelt, O.; Guðmundsdóttir, E.; van den Bogaard, C.; Słowiński, M.; Błaszkiewicz, M.; and Brauer, A.\n\n\n \n \n \n \n \n Holocene tephrostratigraphy of varved sediment records from Lakes Tiefer See (NE Germany) and Czechowskie (N Poland).\n \n \n \n \n\n\n \n\n\n\n Quaternary Science Reviews, 132: 1–14. January 2016.\n \n\n\n\n
\n\n\n\n \n \n \"HolocenePaper\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{wulf_holocene_2016,\n\ttitle = {Holocene tephrostratigraphy of varved sediment records from {Lakes} {Tiefer} {See} ({NE} {Germany}) and {Czechowskie} ({N} {Poland})},\n\tvolume = {132},\n\tissn = {02773791},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0277379115301736},\n\tdoi = {10.1016/j.quascirev.2015.11.007},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Quaternary Science Reviews},\n\tauthor = {Wulf, Sabine and Dräger, Nadine and Ott, Florian and Serb, Johanna and Appelt, Oona and Guðmundsdóttir, Esther and van den Bogaard, Christel and Słowiński, Michał and Błaszkiewicz, Mirosław and Brauer, Achim},\n\tmonth = jan,\n\tyear = {2016},\n\tpages = {1--14},\n}\n\n
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\n \n\n \n \n Xie, X.; Evaristo, R.; Simmer, C.; Handwerker, J.; and Trömel, S.\n\n\n \n \n \n \n \n Precipitation and microphysical processes observed by three polarimetric X-band radars and ground-based instrumentation during HOPE.\n \n \n \n \n\n\n \n\n\n\n Atmospheric Chemistry and Physics, 16(11): 7105–7116. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"PrecipitationPaper\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{xie_precipitation_2016,\n\ttitle = {Precipitation and microphysical processes observed by three polarimetric {X}-band radars and ground-based instrumentation during {HOPE}},\n\tvolume = {16},\n\tissn = {1680-7324},\n\turl = {https://acp.copernicus.org/articles/16/7105/2016/},\n\tdoi = {10.5194/acp-16-7105-2016},\n\tabstract = {Abstract. This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Jülich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5 km  ×  5 km region, while three other disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2023-01-23},\n\tjournal = {Atmospheric Chemistry and Physics},\n\tauthor = {Xie, Xinxin and Evaristo, Raquel and Simmer, Clemens and Handwerker, Jan and Trömel, Silke},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {7105--7116},\n}\n\n
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\n Abstract. This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Jülich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5 km  ×  5 km region, while three other disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.\n
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\n \n\n \n \n Zerenner, T.; Venema, V.; Friederichs, P.; and Simmer, C.\n\n\n \n \n \n \n \n Downscaling near-surface atmospheric fields with multi-objective Genetic Programming.\n \n \n \n \n\n\n \n\n\n\n Environmental Modelling & Software, 84: 85–98. October 2016.\n \n\n\n\n
\n\n\n\n \n \n \"DownscalingPaper\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{zerenner_downscaling_2016,\n\ttitle = {Downscaling near-surface atmospheric fields with multi-objective {Genetic} {Programming}},\n\tvolume = {84},\n\tissn = {13648152},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1364815216302122},\n\tdoi = {10.1016/j.envsoft.2016.06.009},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Environmental Modelling \\& Software},\n\tauthor = {Zerenner, Tanja and Venema, Victor and Friederichs, Petra and Simmer, Clemens},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {85--98},\n}\n\n
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\n \n\n \n \n Zhang, H.; Hendricks Franssen, H.; Han, X.; Vrugt, J.; and Vereecken, H.\n\n\n \n \n \n \n \n Joint State and Parameter Estimation of Two Land Surface Models Using the Ensemble Kalman Filter and Particle Filter.\n \n \n \n \n\n\n \n\n\n\n Technical Report Vadose Zone Hydrology/Stochastic approaches, February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"JointPaper\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{zhang_joint_2016,\n\ttype = {preprint},\n\ttitle = {Joint {State} and {Parameter} {Estimation} of {Two} {Land} {Surface} {Models} {Using} the {Ensemble} {Kalman} {Filter} and {Particle} {Filter}},\n\turl = {https://hess.copernicus.org/preprints/hess-2016-42/hess-2016-42.pdf},\n\tabstract = {Abstract. Land surface models (LSMs) contain a suite of different parameters and state variables to resolve the water and energy balance at the soil-atmosphere interface. Many of the parameters of these models cannot be measured directly in the field, and require calibration against flux and soil moisture data. In this paper, we use the Variable Infiltration Capacity Hydrologic Model (VIC) and the Community Land Model (CLM) to simulate temporal variations in soil moisture content at 5, 20 and 50 cm depth in the Rollesbroich experimental watershed in Germany. Four different data assimilation (DA) methods are used to jointly estimate the spatially distributed water content values, and hydraulic and/or thermal properties of the resolved soil domain. This includes the Ensemble Kalman Filter (EnKF) using state augmentation or dual estimation, the Residual Resampling Particle Filter (RRPF) and Markov chain Monte Carlo Particle Filter (MCMCPF). These four DA methods are tuned and calibrated for a five month data period, and subsequently evaluated for another five month period. Our results show that all the different DA methods improve the fit of the VIC and CLM model to the observed water content data, particularly if the maximum baseflow velocity (VIC), soil hydraulic (VIC) properties and/or soil texture (CLM) are jointly estimated along with the model states. In the evaluation period, the augmentation and dual estimation method performed slightly better than RRPF and MCMCPF. The differences in simulated soil moisture values between the CLM and VIC model were larger than variations among the data assimilation algorithms. The best performance for the Rollesbroich site was observed for the CLM model. The strong underestimation of the soil moisture values of the third VIC-layer are likely explained by an inadequate parameterization of groundwater drainage.},\n\turldate = {2023-01-23},\n\tinstitution = {Vadose Zone Hydrology/Stochastic approaches},\n\tauthor = {Zhang, Hongjuan and Hendricks Franssen, Harrie-Jan and Han, Xujun and Vrugt, Jasper and Vereecken, Harry},\n\tmonth = feb,\n\tyear = {2016},\n\tdoi = {10.5194/hess-2016-42},\n}\n\n
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\n Abstract. Land surface models (LSMs) contain a suite of different parameters and state variables to resolve the water and energy balance at the soil-atmosphere interface. Many of the parameters of these models cannot be measured directly in the field, and require calibration against flux and soil moisture data. In this paper, we use the Variable Infiltration Capacity Hydrologic Model (VIC) and the Community Land Model (CLM) to simulate temporal variations in soil moisture content at 5, 20 and 50 cm depth in the Rollesbroich experimental watershed in Germany. Four different data assimilation (DA) methods are used to jointly estimate the spatially distributed water content values, and hydraulic and/or thermal properties of the resolved soil domain. This includes the Ensemble Kalman Filter (EnKF) using state augmentation or dual estimation, the Residual Resampling Particle Filter (RRPF) and Markov chain Monte Carlo Particle Filter (MCMCPF). These four DA methods are tuned and calibrated for a five month data period, and subsequently evaluated for another five month period. Our results show that all the different DA methods improve the fit of the VIC and CLM model to the observed water content data, particularly if the maximum baseflow velocity (VIC), soil hydraulic (VIC) properties and/or soil texture (CLM) are jointly estimated along with the model states. In the evaluation period, the augmentation and dual estimation method performed slightly better than RRPF and MCMCPF. The differences in simulated soil moisture values between the CLM and VIC model were larger than variations among the data assimilation algorithms. The best performance for the Rollesbroich site was observed for the CLM model. The strong underestimation of the soil moisture values of the third VIC-layer are likely explained by an inadequate parameterization of groundwater drainage.\n
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\n \n\n \n \n van der Tol, C.; Rossini, M.; Cogliati, S.; Verhoef, W.; Colombo, R.; Rascher, U.; and Mohammed, G.\n\n\n \n \n \n \n \n A model and measurement comparison of diurnal cycles of sun-induced chlorophyll fluorescence of crops.\n \n \n \n \n\n\n \n\n\n\n Remote Sensing of Environment, 186: 663–677. December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\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_tol_model_2016,\n\ttitle = {A model and measurement comparison of diurnal cycles of sun-induced chlorophyll fluorescence of crops},\n\tvolume = {186},\n\tissn = {00344257},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0034425716303649},\n\tdoi = {10.1016/j.rse.2016.09.021},\n\tlanguage = {en},\n\turldate = {2023-01-23},\n\tjournal = {Remote Sensing of Environment},\n\tauthor = {van der Tol, Christiaan and Rossini, Micol and Cogliati, Sergio and Verhoef, Wouter and Colombo, Roberto and Rascher, Uwe and Mohammed, Gina},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {663--677},\n}\n\n
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