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@ARTICLE{Stoll:19801,
author = {Stoll, S. and Hendricks-Franssen, H.J. and Barthel, R. and
Kinzelbach, W.},
title = {{W}hat can we learn from long-term groundwater data to
improve climate change impact studies?},
journal = {Hydrology and earth system sciences},
volume = {15},
issn = {1027-5606},
address = {Katlenburg-Lindau},
publisher = {EGU},
reportid = {PreJuSER-19801},
pages = {3861 - 3875},
year = {2011},
note = {This study was performed in the context of the working
group "Climate and Groundwater" of the Swiss Hydrogeological
Society. We thank David Bendel for his support and we are
indebted to the working group "Climate and Groundwater" of
the Swiss Hydrogeological Society, the Baden-Wurttemberg
State Environmental Agency, the Bavaria State Environmental
Agency and Wolfram Mauser (LMU Munich) for providing the
data used in this study. The study was supported by SNF
Project No. $200021_121862.$},
abstract = {Future risks for groundwater resources, due to global
change are usually analyzed by driving hydrological models
with the outputs of climate models. However, this model
chain is subject to considerable uncertainties. Given the
high uncertainties it is essential to identify the processes
governing the groundwater dynamics, as these processes are
likely to affect groundwater resources in the future, too.
Information about the dominant mechanisms can be achieved by
the analysis of long-term data, which are assumed to provide
insight in the reaction of groundwater resources to changing
conditions (weather, land use, water demand). Referring to
this, a dataset of 30 long-term time series of precipitation
dominated groundwater systems in northern Switzerland and
southern Germany is collected. In order to receive
additional information the analysis of the data is carried
out together with hydrological model simulations. High
spatio-temporal correlations, even over large distances
could be detected and are assumed to be related to
large-scale atmospheric circulation patterns. As a result it
is suggested to prefer innovative weather-type-based
downscaling methods to other stochastic downscaling
approaches. In addition, with the help of a qualitative
procedure to distinguish between meteorological and
anthropogenic causes it was possible to identify processes
which dominated the groundwater dynamics in the past. It
could be shown that besides the meteorological conditions,
land use changes, pumping activity and feedback mechanisms
governed the groundwater dynamics. Based on these findings,
recommendations to improve climate change impact studies are
suggested.},
keywords = {J (WoSType)},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {Terrestrische Umwelt},
pid = {G:(DE-Juel1)FUEK407},
shelfmark = {Geosciences, Multidisciplinary / Water Resources},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000298366200017},
doi = {10.5194/hess-15-3861-2011},
url = {https://juser.fz-juelich.de/record/19801},
}