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@ARTICLE{Jarvis:907532,
author = {Jarvis, Nicholas and Groh, Jannis and Lewan, Elisabet and
Meurer, Katharina H. E. and Durka, Walter and Baessler,
Cornelia and Pütz, Thomas and Rufullayev, Elvin and
Vereecken, Harry},
title = {{C}oupled modelling of hydrological processes and grassland
production in two contrasting climates},
journal = {Hydrology and earth system sciences},
volume = {26},
number = {8},
issn = {1027-5606},
address = {Katlenburg-Lindau},
publisher = {EGU},
reportid = {FZJ-2022-02065},
pages = {2277 - 2299},
year = {2022},
abstract = {Projections of global climate models suggest that ongoing
human-induced climate change will lead to an increase in the
frequency of severe droughts in many important agricultural
regions of the world. Eco-hydrological models that integrate
current understanding of the interacting processes governing
soil water balance and plant growth may be useful tools to
predict the impacts of climate change on crop production.
However, the validation status of these models for making
predictions under climate change is still unclear, since few
suitable datasets are available for model testing. One
promising approach is to test models using data obtained in
“space-for-time” substitution experiments, in which
samples are transferred among locations with contrasting
current climates in order to mimic future climatic
conditions. An important advantage of this approach is that
the soil type is the same, so that differences in soil
properties are not confounded with the influence of climate
on water balance and crop growth. In this study, we evaluate
the capability of a relatively simple eco-hydrological model
to reproduce 6 years (2013–2018) of measurements of soil
water contents, water balance components and grass
production made in weighing lysimeters located at two sites
within the TERENO-SoilCan network in Germany. Three
lysimeters are located at an upland site at Rollesbroich
with a cool, wet climate, while three others had been moved
from Rollesbroich to a warmer and drier climate on the lower
Rhine valley floodplain at Selhausen. Four of the most
sensitive parameters in the model were treated as uncertain
within the framework of the GLUE (generalized likelihood
uncertainty estimation) methodology, while the remaining
parameters in the model were set according to site
measurements or data in the literature.},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {2173 - Agro-biogeosystems: controls, feedbacks and impact
(POF4-217)},
pid = {G:(DE-HGF)POF4-2173},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000789402200001},
doi = {10.5194/hess-26-2277-2022},
url = {https://juser.fz-juelich.de/record/907532},
}