@article{HuangHattermannKrysanovaetal.2013, author = {Huang, Shaochun and Hattermann, Fred Fokko and Krysanova, Valentina and Bronstert, Axel}, title = {Projections of climate change impacts on river flood conditions in Germany by combining three different RCMs with a regional eco-hydrological model}, series = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change}, volume = {116}, journal = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change}, number = {3-4}, publisher = {Springer}, address = {Dordrecht}, issn = {0165-0009}, doi = {10.1007/s10584-012-0586-2}, pages = {631 -- 663}, year = {2013}, abstract = {A general increase in precipitation has been observed in Germany in the last century, and potential changes in flood generation and intensity are now at the focus of interest. The aim of the paper is twofold: a) to project the future flood conditions in Germany accounting for various river regimes (from pluvial to nival-pluvial regimes) and under different climate scenarios (the high, A2, low, B1, and medium, A1B, emission scenarios) and b) to investigate sources of uncertainty generated by climate input data and regional climate models. Data of two dynamical Regional Climate Models (RCMs), REMO (REgional Model) and CCLM (Cosmo-Climate Local Model), and one statistical-empirical RCM, Wettreg (Wetterlagenbasierte Regionalisierungsmethode: weather-type based regionalization method), were applied to drive the eco-hydrological model SWIM (Soil and Water Integrated Model), which was previously validated for 15 gauges in Germany. At most of the gauges, the 95 and 99 percentiles of the simulated discharge using SWIM with observed climate data had a good agreement with the observed discharge for 1961-2000 (deviation within +/- 10 \%). However, the simulated discharge had a bias when using RCM climate as input for the same period. Generalized Extreme Value (GEV) distributions were fitted to the annual maximum series of river runoff for each realization for the control and scenario periods, and the changes in flood generation over the whole simulation time were analyzed. The 50-year flood values estimated for two scenario periods (2021-2060, 2061-2100) were compared to the ones derived from the control period using the same climate models. The results driven by the statistical-empirical model show a declining trend in the flood level for most rivers, and under all climate scenarios. The simulations driven by dynamical models give various change directions depending on region, scenario and time period. The uncertainty in estimating high flows and, in particular, extreme floods remains high, due to differences in regional climate models, emission scenarios and multi-realizations generated by RCMs.}, language = {en} } @phdthesis{Huang2012, author = {Huang, Shaochun}, title = {Modelling of environmental change impacts on water resources and hydrological extremes in Germany}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-59748}, school = {Universit{\"a}t Potsdam}, year = {2012}, abstract = {Water resources, in terms of quantity and quality, are significantly influenced by environmental changes, especially by climate and land use changes. The main objective of the present study is to project climate change impacts on the seasonal dynamics of water fluxes, spatial changes in water balance components as well as the future flood and low flow conditions in Germany. This study is based on the modeling results of the process-based eco-hydrological model SWIM (Soil and Water Integrated Model) driven by various regional climate scenarios on one hand. On the other hand, it is supported by statistical analysis on long-term trends of observed and simulated time series. In addition, this study evaluates the impacts of potential land use changes on water quality in terms of NO3-N load in selected sub-regions of the Elbe basin. In the context of climate change, the actual evapotransipration is likely to increase in most parts of Germany, while total runoff generation may decrease in south and east regions in the scenario period 2051-2060. Water discharge in all six studied large rivers (Ems, Weser, Saale, Danube, Main and Neckar) would be 8 - 30\% lower in summer and autumn compared to the reference period (1961 - 1990), and the strongest decline is expected for the Saale, Danube and Neckar. The 50-year low flow is likely to occur more frequently in western, southern and central Germany after 2061 as suggested by more than 80\% of the model runs. The current low flow period (from August to September) may be extended until the late autumn at the end of this century. Higher winter flow is expected in all of these rivers, and the increase is most significant for the Ems (about 18\%). No general pattern of changes in flood directions can be concluded according to the results driven by different RCMs, emission scenarios and multi-realizations. An optimal agricultural land use and management are essential for the reduction in nutrient loads and improvement of water quality. In the Weiße Elster and Unstrut sub-basins (Elbe), an increase of 10\% in the winter rape area can result in 12-19\% more NO3-N load in rivers. In contrast, another energy plant, maize, has a moderate effect on the water environment. Mineral fertilizers have a much stronger effect on the NO3-N load than organic fertilizers. Cover crops, which play an important role in the reduction of nitrate losses from fields, should be maintained on cropland. The uncertainty in estimating future high flows and, in particular, extreme floods remain high due to different RCM structures, emission scenarios and multi-realizations. In contrast, the projection of low flows under warmer climate conditions appears to be more pronounced and consistent. The largest source of uncertainty related to NO3-N modelling originates from the input data on the agricultural management.}, language = {en} }