Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2333-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-2333-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A comprehensive dataset of vegetation states, fluxes of matter and energy, weather, agricultural management, and soil properties from intensively monitored crop sites in western Germany
Tim G. Reichenau
CORRESPONDING AUTHOR
Institute of Geography, University of Cologne, Cologne, Germany
Wolfgang Korres
Institute of Geography, University of Cologne, Cologne, Germany
Marius Schmidt
Institute of Bio- and Geosciences 3: Agrosphere (IBG-3),
Jülich Research Centre, Jülich, Germany
Alexander Graf
Institute of Bio- and Geosciences 3: Agrosphere (IBG-3),
Jülich Research Centre, Jülich, Germany
Gerhard Welp
Institute of Crop Science and Resource Conservation
(INRES), Soil Science and Soil Ecology, University of Bonn, Bonn, Germany
Nele Meyer
Institute of Crop Science and Resource Conservation
(INRES), Soil Science and Soil Ecology, University of Bonn, Bonn, Germany
Department of Forest Sciences, University of Helsinki, Helsinki,
Finland
Anja Stadler
Institute of Crop Science and Resource Conservation (INRES), Crop
Science, University of Bonn, Bonn, Germany
Cosimo Brogi
Institute of Bio- and Geosciences 3: Agrosphere (IBG-3),
Jülich Research Centre, Jülich, Germany
Karl Schneider
Institute of Geography, University of Cologne, Cologne, Germany
Related authors
Christian Willmes, Lorenzo Canals, Christopher Ganser, Dirk Mennecke, Finn Luis Phillipps, Anne-Kathrin Pietsch, Tim Reichenau, Elisabeth Reuhl, Philip Schildkamp, Maximilian Stempel, Daniel Wickeroth, Jan Wieners, and Øyvind Eide
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W11-2024, 153–160, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-153-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-153-2024, 2024
Tobias K. D. Weber, Joachim Ingwersen, Petra Högy, Arne Poyda, Hans-Dieter Wizemann, Michael Scott Demyan, Kristina Bohm, Ravshan Eshonkulov, Sebastian Gayler, Pascal Kremer, Moritz Laub, Yvonne Funkiun Nkwain, Christian Troost, Irene Witte, Tim Reichenau, Thomas Berger, Georg Cadisch, Torsten Müller, Andreas Fangmeier, Volker Wulfmeyer, and Thilo Streck
Earth Syst. Sci. Data, 14, 1153–1181, https://doi.org/10.5194/essd-14-1153-2022, https://doi.org/10.5194/essd-14-1153-2022, 2022
Short summary
Short summary
Presented are measurement results from six agricultural fields operated by local farmers in southwestern Germany over 9 years. Six eddy-covariance stations measuring water, energy, and carbon fluxes between the vegetated soil surface and the atmosphere provided the backbone of the measurement sites and were supplemented by extensive soil and vegetation state monitoring. The dataset is ideal for testing process models characterizing fluxes at the vegetated soil surface and in the atmosphere.
Salar Saeed Dogar, Cosimo Brogi, Dave O'Leary, Ixchel M. Hernández-Ochoa, Marco Donat, Harry Vereecken, and Johan Alexander Huisman
SOIL, 11, 655–679, https://doi.org/10.5194/soil-11-655-2025, https://doi.org/10.5194/soil-11-655-2025, 2025
Short summary
Short summary
Farmers need precise information about their fields to use water, fertilizers, and other resources efficiently. This study combines underground soil data and satellite images to create detailed field maps using advanced machine learning. By testing different ways of processing data, we ensured a balanced and accurate approach. The results help farmers manage their land more effectively, leading to better harvests and more sustainable farming practices.
Mana Gharun, Ankit Shekhar, Lukas Hörtnagl, Luana Krebs, Nicola Arriga, Mirco Migliavacca, Marilyn Roland, Bert Gielen, Leonardo Montagnani, Enrico Tomelleri, Ladislav Šigut, Matthias Peichl, Peng Zhao, Marius Schmidt, Thomas Grünwald, Mika Korkiakoski, Annalea Lohila, and Nina Buchmann
Biogeosciences, 22, 1393–1411, https://doi.org/10.5194/bg-22-1393-2025, https://doi.org/10.5194/bg-22-1393-2025, 2025
Short summary
Short summary
The effect of winter warming on forest CO2 fluxes has rarely been investigated. We tested the effect of the warm winter of 2020 on the forest CO2 fluxes across 14 sites in Europe and found that the net ecosystem productivity (NEP) across most sites declined during the warm winter due to increased respiration fluxes.
Till Francke, Cosimo Brogi, Alby Duarte Rocha, Michael Förster, Maik Heistermann, Markus Köhli, Daniel Rasche, Marvin Reich, Paul Schattan, Lena Scheiffele, and Martin Schrön
Geosci. Model Dev., 18, 819–842, https://doi.org/10.5194/gmd-18-819-2025, https://doi.org/10.5194/gmd-18-819-2025, 2025
Short summary
Short summary
Multiple methods for measuring soil moisture beyond the point scale exist. Their validation is generally hindered by not knowing the truth. We propose a virtual framework in which this truth is fully known and the sensor observations for cosmic ray neutron sensing, remote sensing, and hydrogravimetry are simulated. This allows for the rigorous testing of these virtual sensors to understand their effectiveness and limitations.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Christian Willmes, Lorenzo Canals, Christopher Ganser, Dirk Mennecke, Finn Luis Phillipps, Anne-Kathrin Pietsch, Tim Reichenau, Elisabeth Reuhl, Philip Schildkamp, Maximilian Stempel, Daniel Wickeroth, Jan Wieners, and Øyvind Eide
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W11-2024, 153–160, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-153-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-153-2024, 2024
Sinikka J. Paulus, Rene Orth, Sung-Ching Lee, Anke Hildebrandt, Martin Jung, Jacob A. Nelson, Tarek Sebastian El-Madany, Arnaud Carrara, Gerardo Moreno, Matthias Mauder, Jannis Groh, Alexander Graf, Markus Reichstein, and Mirco Migliavacca
Biogeosciences, 21, 2051–2085, https://doi.org/10.5194/bg-21-2051-2024, https://doi.org/10.5194/bg-21-2051-2024, 2024
Short summary
Short summary
Porous materials are known to reversibly trap water from the air, even at low humidity. However, this behavior is poorly understood for soils. In this analysis, we test whether eddy covariance is able to measure the so-called adsorption of atmospheric water vapor by soils. We find that this flux occurs frequently during dry nights in a Mediterranean ecosystem, while EC detects downwardly directed vapor fluxes. These results can help to map moisture uptake globally.
Nils Eingrüber, Wolfgang Korres, Ulrich Löhnert, and Karl Schneider
Adv. Sci. Res., 20, 65–71, https://doi.org/10.5194/asr-20-65-2023, https://doi.org/10.5194/asr-20-65-2023, 2023
Short summary
Short summary
Sensitivity analyses for wind direction effects upon an ENVI-met microclimate model were performed for a heterogeneous urban study area. Significant temperature differences were found when forcing the model with constant N/E/S/W wind direction data. Best model performance was observed using measured wind direction forcing data. The results demonstrate that cooling effects of park areas are largely directional which is important for urban planning and design of climate change adaptation measures.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
Short summary
Short summary
Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Nils Eingrüber, Wolfgang Korres, and Karl Schneider
Adv. Sci. Res., 19, 81–90, https://doi.org/10.5194/asr-19-81-2022, https://doi.org/10.5194/asr-19-81-2022, 2022
Short summary
Short summary
Cities are particularly affected by climate change. Adaptation strategies require data, models and scenario analyses. This paper characterizes the urban microclimate of a 16 ha study area in Cologne based on a network of 33 calibrated and validated sensors. Using statistical analyses, tests and pairwise comparisons, significant microclimatic differences were identified between a park, courtyard, avenue and narrow street. The data will be used in future to validate an ENVI-met microclimate model.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
Short summary
Short summary
Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Tobias K. D. Weber, Joachim Ingwersen, Petra Högy, Arne Poyda, Hans-Dieter Wizemann, Michael Scott Demyan, Kristina Bohm, Ravshan Eshonkulov, Sebastian Gayler, Pascal Kremer, Moritz Laub, Yvonne Funkiun Nkwain, Christian Troost, Irene Witte, Tim Reichenau, Thomas Berger, Georg Cadisch, Torsten Müller, Andreas Fangmeier, Volker Wulfmeyer, and Thilo Streck
Earth Syst. Sci. Data, 14, 1153–1181, https://doi.org/10.5194/essd-14-1153-2022, https://doi.org/10.5194/essd-14-1153-2022, 2022
Short summary
Short summary
Presented are measurement results from six agricultural fields operated by local farmers in southwestern Germany over 9 years. Six eddy-covariance stations measuring water, energy, and carbon fluxes between the vegetated soil surface and the atmosphere provided the backbone of the measurement sites and were supplemented by extensive soil and vegetation state monitoring. The dataset is ideal for testing process models characterizing fluxes at the vegetated soil surface and in the atmosphere.
Youri Rothfuss, Maria Quade, Nicolas Brüggemann, Alexander Graf, Harry Vereecken, and Maren Dubbert
Biogeosciences, 18, 3701–3732, https://doi.org/10.5194/bg-18-3701-2021, https://doi.org/10.5194/bg-18-3701-2021, 2021
Short summary
Short summary
The partitioning of evapotranspiration into evaporation from soil and transpiration from plants is crucial for a wide range of parties, from farmers to policymakers. In this work, we focus on a particular partitioning method, based on the stable isotopic analysis of water. In particular, we aim at highlighting the challenges that this method is currently facing and, in light of recent methodological developments, propose ways forward for the isotopic-partitioning community.
Cosimo Brogi, Johan A. Huisman, Lutz Weihermüller, Michael Herbst, and Harry Vereecken
SOIL, 7, 125–143, https://doi.org/10.5194/soil-7-125-2021, https://doi.org/10.5194/soil-7-125-2021, 2021
Short summary
Short summary
There is a need in agriculture for detailed soil maps that carry quantitative information. Geophysics-based soil maps have the potential to deliver such products, but their added value has not been fully investigated yet. In this study, we compare the use of a geophysics-based soil map with the use of two commonly available maps as input for crop growth simulations. The geophysics-based product results in better simulations, with improvements that depend on precipitation, soil, and crop type.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
Short summary
Short summary
In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
Short summary
Short summary
Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
Cited articles
Aguilar, E., Auer, I., Brunet, M., Peterson, T. C., and Wieringa, J.:
Guidelines on climate metadata and homogenization, WMO/TD No. 1186, Geneva,
Switzerland, 2003.
Ahrends, H., Haseneder-Lind, R., Schween, J., Crewell, S., Stadler, A., and
Rascher, U.: Diurnal Dynamics of Wheat Evapotranspiration Derived from
Ground-Based Thermal Imagery, Remote Sens., 6, 9775–9801,
https://doi.org/10.3390/rs6109775, 2014.
Ali, M., Montzka, C., Stadler, A., Menz, G., Thonfeld, F., and Vereecken, H.:
Estimation and Validation of RapidEye-Based Time-Series of Leaf Area Index
for Winter Wheat in the Rur Catchment (Germany), Remote Sens., 7,
2808–2831, https://doi.org/10.3390/rs70302808, 2015.
Auer, I., Böhm, R., Jurković, A., Orlik, A., Potzmann, R.,
Schöner, W., Ungersböck, M., Brunetti, M., Nanni, T., Maugeri, M.,
Briffa, K., Jones, P., Efthymiadis, D., Mestre, O., Moisselin, J.-M.,
Begert, M., Brazdil, R., Bochnicek, O., Cegnar, T., Gajić-Čapka, M.,
Zaninović, K., Majstorović, Ž., Szalai, S., Szentimrey, T., and
Mercalli, L.: A new instrumental precipitation dataset for the greater
alpine region for the period 1800–2002: Precipitation Dataset: European
Greater Alpine Region, Int. J. Climatol., 25, 139–166,
https://doi.org/10.1002/joc.1135, 2005.
Beaulieu, C., Seidou, O., Ouarda, T. B. M. J., Zhang, X., Boulet, G., and
Yagouti, A.: Intercomparison of homogenization techniques for precipitation
data: Homogenization of Precipitation, Water Resour. Res., 44, W02425,
https://doi.org/10.1029/2006WR005615, 2008.
Beaulieu, C., Seidou, O., Ouarda, T. B. M. J., and Zhang, X.: Intercomparison
of homogenization techniques for precipitation data continued: Comparison of
two recent Bayesian change point models: Homogenization with Bayesian Change
Point, Water Resour. Res., 45, W08410, https://doi.org/10.1029/2008WR007501, 2009.
Beckers, J. M. and Rixen, M.: EOF Calculations and Data Filling from
Incomplete Oceanographic Datasets, J. Atmos. Ocean. Tech., 20,
1839–1856, https://doi.org/10.1175/1520-0426(2003)020<1839:ECADFF>
2.0.CO;2, 2003.
Bogena, H. R.: TERENO: German network of terrestrial environmental
observatories, J. Large-Scale Res. Facil. JLSRF, 2, A52, https://doi.org/10.17815/jlsrf-2-98,
2016.
Bornemann, L., Herbst, M., Welp, G., Vereecken, H., and Amelung, W.: Rock
Fragments Control Size and Saturation of Organic Carbon Pools in
Agricultural Topsoil, Soil Sci. Soc. Am. J., 75, 1898,
https://doi.org/10.2136/sssaj2010.0454, 2011.
Brandsma, T. and Können, G. P.: Application of nearest-neighbor
resampling for homogenizing temperature records on a daily to sub-daily
level, Int. J. Climatol., 26, 75–89, https://doi.org/10.1002/joc.1236, 2006.
Brogi, C., Huisman, J. A., Pätzold, S., von Hebel, C., Weihermüller,
L., Kaufmann, M. S., van der Kruk, J., and Vereecken, H.: Large-scale soil
mapping using multi-configuration EMI and supervised image classification,
Geoderma, 335, 133–148, https://doi.org/10.1016/j.geoderma.2018.08.001, 2019.
Brogi, C., Huisman, J. A., Herbst, M., Weihermüller, L., Klosterhalfen,
A., Montzka, C., Reichenau, T. G., and Vereecken, H.: Simulation of spatial
variability in crop leaf area index and yield using agroecosystem modeling
and geophysics-based quantitative soil information, Vadose Zone J., 19, e20009,
https://doi.org/10.1002/vzj2.20009, 2020.
Busch, S., van der Kruk, J., and Vereecken, H.: Improved Characterization of
Fine-Texture Soils Using On-Ground GPR Full-Waveform Inversion, IEEE T.
Geosci. Remote, 52, 3947–3958, https://doi.org/10.1109/TGRS.2013.2278297,
2014.
Della-Marta, P. M. and Wanner, H.: A Method of Homogenizing the Extremes and
Mean of Daily Temperature Measurements, J. Clim., 19, 4179–4197,
https://doi.org/10.1175/JCLI3855.1, 2006.
Dengel, S., Graf, A., Grünwald, T., Hehn, M., Kolari, P., Löfvenius,
M. O., Merbold, L., Nicolini, G., and Pavelka, M.: Standardized precipitation
measurements within ICOS: rain, snowfall and snow depth: a review, Int.
Agrophys., 32, 607–617, https://doi.org/10.1515/intag-2017-0046, 2018.
Domonkos, P. and Coll, J.: Homogenisation of temperature and precipitation
time series with ACMANT3: method description and efficiency tests:
Homogenisation of time series with ACMANT3, Int. J. Climatol., 37,
1910–1921, https://doi.org/10.1002/joc.4822, 2017.
Eder, F., Schmidt, M., Damian, T., Träumner, K., and Mauder, M.:
Mesoscale Eddies Affect Near-Surface Turbulent Exchange: Evidence from Lidar
and Tower Measurements, J. Appl. Meteorol. Climatol., 54, 189–206,
https://doi.org/10.1175/JAMC-D-14-0140.1, 2015.
Graf, A.: Gap-filling meteorological variables with Empirical Orthogonal
Functions, Geophys. Res. Abstr.,no. 19, 2017.
Graf, A., Prolingheuer, N., Schickling, A., Schmidt, M., Schneider, K.,
Schüttemeyer, D., Herbst, M., Huisman, J. A., Weihermüller, L.,
Scharnagl, B., Steenpass, C., Harms, R., and Vereecken, H.: Temporal
Downscaling of Soil Carbon Dioxide Efflux Measurements Based on Time-Stable
Spatial Patterns, Vadose Zone J., 10, 239–251, https://doi.org/10.2136/vzj2009.0152,
2011.
Graf, A., Herbst, M., Weihermüller, L., Huisman, J. A., Prolingheuer,
N., Bornemann, L., and Vereecken, H.: Analyzing spatiotemporal variability of
heterotrophic soil respiration at the field scale using orthogonal
functions, Geoderma, 181–182, 91–101, https://doi.org/10.1016/j.geoderma.2012.02.016,
2012.
Heitmann-Weber, B., Mittelstaedt, W., and Fuhr, F.: The degradation of
anilazine and dihydroxy-anilazine at various soil depths of an orthic
luvisol, J. Environ. Sci. Health Pt. B, 29, 247–264,
https://doi.org/10.1080/03601239409372878, 1994.
Hoffmeister, D., Waldhoff, G., Korres, W., Curdt, C., and Bareth, G.: Crop
height variability detection in a single field by multi-temporal terrestrial
laser scanning, Precis. Agric., 17, 296–312,
https://doi.org/10.1007/s11119-015-9420-y, 2016.
IUSS Working Group WRB: World Reference Base for Soil Resources 2014, FAO, Rome, Italy, 2015.
Jakobi, J., Huisman, J. A., Schrön, M., Fiedler, J., Brogi, C.,
Vereecken, H., and Bogena, H. R.: Error Estimation for Soil Moisture
Measurements With Cosmic Ray Neutron Sensing and Implications for Rover
Surveys, Front. Water, 2, 10, https://doi.org/10.3389/frwa.2020.00010, 2020.
Jones, J. W., Antle, J. M., Basso, B., Boote, K. J., Conant, R. T., Foster, I., Godfray,
H. C. J., Herrero, M., Howitt, R. E., Janssen, S., Keating, B. A.,
Munoz-Carpena, R., Porter, C. H., Rosenzweig, C., and Wheeler, T. R.: Toward
a new generation of agricultural system data, models, and knowledge
products: State of agricultural systems science, Agric. Syst., 155,
269–288, https://doi.org/10.1016/j.agsy.2016.09.021, 2017.
Kalis, A. J.: Die menschliche Beeinflussung der Vegetationsverhältnisse
auf der Aldenhovener Platte (Rheinland) während der vergangenen 2000
Jahre, in Archäologie in den rheinischen Lößbörden:
Beiträge zur Siedlungsgeschichte im Rheinland, vol. 24,
Rheinland-Verlag, Köln, 1983.
Kersebaum, K. C., Boote, K. J., Jorgenson, J. S., Nendel, C., Bindi, M.,
Frühauf, C., Gaiser, T., Hoogenboom, G., Kollas, C., Olesen, J. E.,
Rötter, R. P., Ruget, F., Thorburn, P. J., Trnka, M., and Wegehenkel, M.:
Analysis and classification of data sets for calibration and validation of
agro-ecosystem models, Environ. Model. Softw., 72, 402–417,
https://doi.org/10.1016/j.envsoft.2015.05.009, 2015.
Klosterhalfen, A., Herbst, M., Weihermüller, L., Graf, A., Schmidt, M.,
Stadler, A., Schneider, K., Subke, J.-A., Huisman, J. A., and Vereecken, H.:
Multi-site calibration and validation of a net ecosystem carbon exchange
model for croplands, Ecol. Model., 363, 137–156,
https://doi.org/10.1016/j.ecolmodel.2017.07.028, 2017.
Korres, W., Koyama, C. N., Fiener, P., and Schneider, K.: Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions, Hydrol. Earth Syst. Sci., 14, 751–764, https://doi.org/10.5194/hess-14-751-2010, 2010.
Korres, W., Reichenau, T. G., and Schneider, K.: Patterns and scaling
properties of surface soil moisture in an agricultural landscape: An
ecohydrological modeling study, J. Hydrol., 498, 89–102, 2013.
Kuglitsch, F. G., Toreti, A., Xoplaki, E., Della-Marta, P. M., Luterbacher,
J., and Wanner, H.: Homogenization of daily maximum temperature series in the
Mediterranean, J. Geophys. Res., 114, D15108, https://doi.org/10.1029/2008JD011606, 2009.
Mauder, M. and Foken, T.: Documentation and Instruction Manual of the
Eddy-Covariance Software Package TK3, Universität Bayreuth, Abt.
Mikrometeorologie, Bayreuth, 2011.
Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H. P.,
Schmidt, M., and Steinbrecher, R.: A strategy for quality and uncertainty
assessment of long-term eddy-covariance measurements, Agr. Forest Meteorol.,
169, 122–135, https://doi.org/10.1016/j.agrformet.2012.09.006, 2013.
Meier, U., Bleiholder, H., Buhr, L., Feller, C., Hack, H., Heß, M.,
Lancashire, P. D., Schnock, U., Stauß, R., van den Boom, T., Weber, E.,
and Zwerger, P.: The BBCH system to coding the phenological growth stages of
plants – history and publications, J. Cultiv. Plants, 61, 41–52,
2009.
Mestre, O., Gruber, C., Prieur, C., Caussinus, H., and Jourdain, S.:
SPLIDHOM: A Method for Homogenization of Daily Temperature Observations, J.
Appl. Meteorol. Climatol., 50, 2343–2358, https://doi.org/10.1175/2011JAMC2641.1,
2011.
Meyer, N., Bornemann, L., Welp, G., Schiedung, H., Herbst, M., and Amelung,
W.: Carbon saturation drives spatial patterns of soil organic matter losses
under long-term bare fallow, Geoderma, 306, 89–98,
https://doi.org/10.1016/j.geoderma.2017.07.004, 2017.
Moore, C. J.: Frequency response corrections for eddy correlation systems, Bound.-Lay. Meteorol., 37, 17–35, https://doi.org/10.1007/BF00122754, 1986.
Nemes, A., Wosten, J. H. M., Lilly, A., and Voshaar, J. H. O.: Evaluation of
different procedures to interpolate particle-size distributions to achieve
compatibility within soil databases, Geoderma, 90, 187–202, 1999.
Ney, P. and Graf, A.: High-Resolution Vertical Profile Measurements for
Carbon Dioxide and Water Vapour Concentrations Within and Above Crop
Canopies, Bound.-Lay. Meteorol., 166, 449–473,
https://doi.org/10.1007/s10546-017-0316-4, 2018.
Prolingheuer, N., Scharnagl, B., Graf, A., Vereecken, H., and Herbst, M.: On
the spatial variation of soil rhizospheric and heterotrophic respiration in
a winter wheat stand, Agr. Forest Meteorol., 195–196, 24–31,
https://doi.org/10.1016/j.agrformet.2014.04.016, 2014.
Pütz, T.: Lysimeterversuche zum Verlagerungsverhalten von
Methabenzthiazuron und gelöstem organischen Kohlenstoff in einer
Parabraunerde, Aufbau von zwei Klimameßstationen und Untersuchungen zur
Validierung des Lysimetersystems, Forschungszentrum Zentralbibliothek,
Jülich, available at:
http://gso.gbv.de/DB=2.1/PPNSET?PPN=152374191 (last access: 7 March 2019), 1993.
R Core Team: R, R Foundation for Statistical Computing, Vienna, Austria,
2017.
Reichenau, T. G., Korres, W., Montzka, C., Fiener, P., Wilken, F., Stadler,
A., Waldhoff, G., and Schneider, K.: 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), PLOS ONE, 11, e0158451,
https://doi.org/10.1371/journal.pone.0158451, 2016.
Reichenau, T. G., Korres, W., Schmidt, M., Graf, A., Welp, G., Meyer, N.,
Stadler, A., Brogi, C. and Schneider, K.: A comprehensive dataset of
vegetation states, fluxes of matter and energy, weather, agricultural
management, and soil properties from intensively monitored crop sites in
Western Germany, https://doi.org/10.5880/TR32DB.39, 2020.
Sakai, T., Iizumi, T., Okada, M., Nishimori, M., Grünwald, T., Prueger,
J., Cescatti, A., Korres, W., Schmidt, M., Carrara, A., Loubet, B., and
Ceschia, E.: Varying applicability of four different satellite-derived soil
moisture products to global gridded crop model evaluation, Int. J. Appl.
Earth Obs. Geoinf., 48, 51–60, https://doi.org/10.1016/j.jag.2015.09.011, 2016.
Schad, P., Krasilnikov, P. V., and Arnold, R.: German Soil Classification, in:
A handbook of soil terminology, correlation and classification, edited by: Krasilnikov, P.
V., Ibáñez Martí, J. J., Arnold, R., and Shoba, S.,
Earthscan, London, Sterling, VA, 122–130, 2009.
Schiedung, H., Bornemann, L., and Welp, G.: Seasonal Variability of Soil
Organic Carbon Fractions Under Arable Land, Pedosphere, 27, 380–386,
https://doi.org/10.1016/S1002-0160(17)60326-6, 2017.
Schmidt, M., Reichenau, T. G., Fiener, P., and Schneider, K.: The carbon
budget of a winter wheat field: An eddy covariance analysis of seasonal and
inter-annual variability, Agr. Forest Meteorol., 165, 114–126,
https://doi.org/10.1016/j.agrformet.2012.05.012, 2012.
Schotanus, P., Nieuwstadt, F. T. M., and De Bruin, H. A. R.: Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes, Bound.-Lay. Meteorol., 26, 81–93, https://doi.org/10.1007/BF00164332, 1983.
Schulz, E.: Influence of site conditions and management on different soil
organic matter (som) pools, Arch. Agron. Soil Sci., 50, 33–47,
https://doi.org/10.1080/03650340310001627577, 2004.
Simmer, C., Thiele-Eich, I., Masbou, M., Amelung, W., Bogena, H., Crewell,
S., Diekkrüger, B., Ewert, F., Hendricks Franssen, H.-J., Huisman, J.
A., Kemna, A., Klitzsch, N., Kollet, S., Langensiepen, M., Löhnert, U.,
Rahman, A. S. M. M., Rascher, U., Schneider, K., Schween, J., Shao, Y.,
Shrestha, P., Stiebler, M., Sulis, M., Vanderborght, J., Vereecken, H., van
der Kruk, J., Waldhoff, G., and Zerenner, T.: Monitoring and Modeling the
Terrestrial System from Pores to Catchments, B. Am. Meteorol. Soc.,
96, 1765–1787, https://doi.org/10.1175/BAMS-D-13-00134.1, 2015.
Trewin, B.: A daily homogenized temperature data set for Australia, Int. J.
Climatol., 33, 1510–1529, https://doi.org/10.1002/joc.3530, 2013.
Van Dijk, A., Moene, A. F., and De Bruin, H. A. R.: The principles of surface
flux physics: theory, practice and description of the ECPACK library,
Meteorology and Air Quality Group, Wageningen University, Wageningen,
the Netherlands, 2004.
Venema, V. K. C., Mestre, O., Aguilar, E., Auer, I., Guijarro, J. A., Domonkos, P., Vertacnik, G., Szentimrey, T., Stepanek, P., Zahradnicek, P., Viarre, J., Müller-Westermeier, G., Lakatos, M., Williams, C. N., Menne, M. J., Lindau, R., Rasol, D., Rustemeier, E., Kolokythas, K., Marinova, T., Andresen, L., Acquaotta, F., Fratianni, S., Cheval, S., Klancar, M., Brunetti, M., Gruber, C., Prohom Duran, M., Likso, T., Esteban, P., and Brandsma, T.: Benchmarking homogenization algorithms for monthly data, Clim. Past, 8, 89–115, https://doi.org/10.5194/cp-8-89-2012, 2012.
Vereecken, H., Kollet, S., and Simmer, C.: Patterns in
Soil–Vegetation–Atmosphere Systems: Monitoring, Modeling, and Data
Assimilation, Vadose Zone J., 9, 821–827, https://doi.org/10.2136/vzj2010.0122, 2010.
Vincent, L. A., Zhang, X., Bonsal, B. R., and Hogg, W. D.: Homogenization of
Daily Temperatures over Canada, J. Clim., 15, 1322–1334,
https://doi.org/10.1175/1520-0442(2002)015<1322:HODTOC>2.0.CO;2,
2002.
von Hebel, C., Matveeva, M., Verweij, E., Rademske, P., Kaufmann, M. S.,
Brogi, C., Vereecken, H., Rascher, U., and van der Kruk, J.: Understanding
Soil and Plant Interaction by Combining Ground-Based Quantitative
Electromagnetic Induction and Airborne Hyperspectral Data, Geophys. Res.
Lett., 45, 7571–7579, https://doi.org/10.1029/2018GL078658, 2018.
Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of flux measurements for density effects due to heat and water vapour transfer, Q. J. Roy. Meteor. Soc., 106, 85–100, https://doi.org/10.1002/qj.49710644707, 1980.
Webster, R.: Regression and functional relations, Eur. J. Soil Sci., 48,
557–566, https://doi.org/10.1111/j.1365-2389.1997.tb00222.x, 1997.
Wieneke, S., Burkart, A., Cendrero-Mateo, M. P., Julitta, T., Rossini, M.,
Schickling, A., Schmidt, M., and Rascher, U.: Linking photosynthesis and
sun-induced fluorescence at sub-daily to seasonal scales, Remote Sens.
Environ., 219, 247–258, https://doi.org/10.1016/j.rse.2018.10.019, 2018.
Wijngaard, J. B., Klein Tank, A. M. G., and Können, G. P.: Homogeneity of
20th century European daily temperature and precipitation series:
Homogeneity of European Climate Series, Int. J. Climatol., 23, 679–692,
https://doi.org/10.1002/joc.906, 2003.
Zeileis, A. and Grothendieck, G.: zoo: S3 Infrastructure for Regular and
Irregular Time Series, J. Stat. Softw., 14, 6, https://doi.org/10.18637/jss.v014.i06,
2005.
Altmetrics
Final-revised paper
Preprint