Description: Future changes in regional climate due to global warming can result in changes of extreme floods. While change assessments of climatic variables, such as temperature and precipitation abound, regional estimations of projected flood impact variables, such as river discharges, inundation extent and depths and flood losses, are rare. We apply the Regional Flood Model (RFM) to assess the projected changes of flood risk for Germany. RFM consists of a model chain covering all major flood impact processes – from a triggering meteorological event to inundation and damage. To this end, a multi-variate stochastic weather generator conditioned on circulation patterns and regional temperature deduced from global climate models is developed to generate long spatially consistent synthetic series of precipitation. The non-stationary weather generator thus considers dynamic and thermo-dynamic change signals simulated by the global climate models. Projected future changes in flood impact variables are estimated for an ensemble of the climate models, two shared socioeconomic pathways and two future periods up to 2100. Changes in climate are then propagated through a process-based hydrological, a coupled 1D-2D hydrodynamic and flood damage model of RFM to estimate flood impact and risk shifts. The analysis reveals specific circulation patterns responsible for flood changes in winter and summer seasons.

Description: The influence of meteorological (pre-) condition on landslide and rockfall probability in the German low mountain regions is assessed. The landslide events analysed for this study are taken from the landslide database for Germany (Damm and Klose, 2015) and from an event inventory from the German railway company (Deutsche Bahn). For each of the hazards a logistic regression model was developed which considers the combined (compound) effect of the most important meteorological triggers. The most relevant variables identified and included in the model for landslides are daily precipitation, frost, snowmelt and a soil moisture proxy determined from accumulated precipitation and potential evapotranspiration. The model for rockfall takes daily precipitation, freeze-thaw cycles and a cleft water proxy into account. The climate change signal is determined by applying the statistical models to the output of a multi-model ensemble of 23 EURO-CORDEX regional climate scenario simulations. When comparing the periods 1971-2000 and 2071-2100, it is found that the probability for rockfall would decrease under RCP8.5 scenario conditions by up to 10% while the probability for landslides would increase by up to 30%. Although the probability for both hazards peaks in summer, the projected changes are strongest in winter and related to a decrease in the number of freeze-thaw cycles and days with frost. The study demonstrates that for this type of application, it is essential to consider all climatic factors that promote or suppress hillslope failure together, as they can reinforce or cancel each other.

Description: A multisite method of fragments-based rainfall temporal (daily to hourly) disaggregation procedure conditioned on circulation pattern (CP) classification is developed and applied to the German part of the Rhine river basin. The performance of the CP-based disaggregation in representing key rainfall characteristics is evaluated and the influence of different number of CP classes is investigated. Compared with the standard (monthly-based) method of fragments disaggregation, the CP-based procedure including a seasonal stratification improves the disaggregation quality in hourly rainfall extremes, although it shows no improvement in reproducing standard rainfall statistics, such as mean and standard deviation. CP classifications with more classes tend to perform better in representing hourly rainfall statistics in the Rhine basin. The developed procedure opens up the possibility to consider dynamic changes in the atmosphere, such as changes in the frequency, persistence and seasonality of circulation patterns, that may be associated with climate change.