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Projections of climate change impacts on river flood conditions in Germany by combining three different RCMs with a regional eco-hydrological model

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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.

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Acknowledgement

The authors would like to thank the German Federal Ministry of Education and Research (BMBF) and the Berlin-based German Insurance Association (GDV), who supported this work as one part of the GDV research project (Climate impact on the damage situation in the German insurance system). Many thanks go also to the colleagues at PIK who supported the work and especially the set-up of the data bases, namely Hermann Österle and Tobias Vetter.

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Authors and Affiliations

  1. Potsdam Institute for Climate Impact Research, P.O. Box 601203, Telegrafenberg, 14412, Potsdam, Germany

    Shaochun Huang, Fred F. Hattermann, Valentina Krysanova & Axel Bronstert

  2. Chair for Hydrology and Climatology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476, Potsdam-Golm, Germany

    Axel Bronstert

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  1. Shaochun Huang
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  2. Fred F. Hattermann
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Correspondence to Shaochun Huang.

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Huang, S., Hattermann, F.F., Krysanova, V. et al. Projections of climate change impacts on river flood conditions in Germany by combining three different RCMs with a regional eco-hydrological model. Climatic Change 116, 631–663 (2013). https://doi.org/10.1007/s10584-012-0586-2

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