% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Groh:878466,
author = {Groh, Jannis and Diamantopoulos, Efstathios and Duan,
Xiaohong and Ewert, Frank and Herbst, Michael and Holbak,
Maja and Kamali, Bahareh and Kersebaum, Kurt‐Christian and
Kuhnert, Matthias and Lischeid, Gunnar and Nendel, Claas and
Priesack, Eckart and Steidl, Jörg and Sommer, Michael and
Pütz, Thomas and Vereecken, Harry and Wallor, Evelyn and
Weber, Tobias K. D. and Wegehenkel, Martin and
Weihermüller, Lutz and Gerke, Horst H.},
title = {{C}rop growth and soil water fluxes at erosion‐affected
arable sites: {U}sing weighing lysimeter data for model
intercomparison},
journal = {Vadose zone journal},
volume = {19},
number = {1},
issn = {1539-1663},
address = {Alexandria, Va.},
publisher = {GeoScienceWorld},
reportid = {FZJ-2020-02871},
pages = {e20058},
year = {2020},
abstract = {Agroecosystem models need to reliably simulate all
biophysical processes that control crop growth, particularly
the soil water fluxes and nutrient dynamics. As a result of
the erosion history, truncated and colluvial soil profiles
coexist in arable fields. The erosion‐affected
field‐scale soil spatial heterogeneity may limit
agroecosystem model predictions. The objective was to
identify the variation in the importance of soil properties
and soil profile modifications in agroecosystem models for
both agronomic and environmental performance. Four
lysimeters with different soil types were used that cover
the range of soil variability in an erosion‐affected
hummocky agricultural landscape. Twelve models were
calibrated on crop phenological stages, and model
performance was tested against observed grain yield,
aboveground biomass, leaf area index, actual
evapotranspiration, drainage, and soil water content.
Despite considering identical input data, the predictive
capability among models was highly diverse. Neither a single
crop model nor the multi‐model mean was able to capture
the observed differences between the four soil profiles in
agronomic and environmental variables. The model's
sensitivity to soil‐related parameters was apparently
limited and dependent on model structure and
parameterization. Information on phenology alone seemed
insufficient to calibrate crop models. The results
demonstrated model‐specific differences in the impact of
soil variability and suggested that soil matters in
predictive agroecosystem models. Soil processes need to
receive greater attention in field‐scale agroecosystem
modeling; high‐precision weighable lysimeters can provide
valuable data for improving the description of
soil–vegetation–atmosphere process in the tested
models.},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {255 - Terrestrial Systems: From Observation to Prediction
(POF3-255)},
pid = {G:(DE-HGF)POF3-255},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000618773300053},
doi = {10.1002/vzj2.20058},
url = {https://juser.fz-juelich.de/record/878466},
}