Simulation and analysis of the impact of projected climate change on the spatially distributed waterbalance in Thuringia, Germany

摘要

The impact of projected climate change on the long-term hydrological balance andseasonal variability in the federal German state of Thuringia was assessedand analysed. For this study projected climate data for the scenarios A2 andB1 were used in conjunction with a conceptual hydrological model. Thedownscaled climate data are based on outputs of the general circulation modelECHAM5 and provide synthetic climate time series for a large number ofprecipitation and climate stations in Germany for the time period of 1971 to 2100.These data were used to compute the spatially distributed hydrological quantities,i.e. precipitation, actual evapotranspiration and runoff generation with aconceptual hydrological model. This paper discusses briefly the statisticaldownscaling method and its validation in Thuringia and includes an overviewof the hydrological model. The achieved results show that the projectedclimate conditions in Thuringia follow the general European climate trends –increased temperature, wetter winters, drier summers. But, in terms of thespatial distribution and interannual variability regional differences occur.The analysis showed that the general increase of the winter precipitation ismore distinct in the mid-mountain region and less pronounced in the lowlandwhereas the decrease of summer precipitation is higher in the lowland andless distinct in the mid-mountains. The actual evapotranspiration showed astatewide increase due to higher temperatures which is largest in the summerperiod. The resulting runoff generation in winter was found to increase in themid-mountains and to slightly decrease in the lowland region. In summer andfall a decrease in runoff generation was estimated for the entire area due tolower precipitation and higher evapotranspiration rates. These spatiallydifferentiated results emphasize the need of high resolution climate inputdata and distributed modelling for regional impact analyses.