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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},
}