What can we learn from long-term groundwater data to improve climate change impact studies?
- Journal Article
Rechte / LizenzCreative Commons Attribution 3.0 Unported
Future risks for groundwater resources, due to global change are usually analyzed bydriving hydrological models with the outputs of climate models. However, this modelchain is subject to considerable uncertainties. Given the high uncertainties it is es-sential to identify the processes governing the groundwater dynamics, as these processes are likely to affect groundwater resources in the future, too. Information aboutthe dominant mechanisms can be achieved by the analysis of long-term data, whichare assumed to provide insight in the reaction of groundwater resources to changingconditions (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 informationthe analysis of the data is carried out together with hydrological model simulations.High spatio-temporal correlations, even over large distances could be detected andare assumed to be related to large-scale atmospheric circulation patterns. As a resultit is suggested to prefer innovative weather-type-based downscaling methods to other stochastic downscaling approaches. In addition, with the help of a qualitative proce-dure to distinguish between meteorological and anthropogenic causes it was possibleto identify processes which dominated the groundwater dynamics in the past. It couldbe shown that besides the meteorological conditions, land use changes, pumping ac-tivity and feedback mechanisms governed the groundwater dynamics. Based on these findings, recommendations to improve climate change impact studies are suggested. Mehr anzeigen
Zeitschrift / SerieHydrology and Earth System Sciences Discussions
Seiten / Artikelnummer
Organisationseinheit03432 - Kinzelbach, Wolfgang