Continuous, spatially distributed long-term simulation for assessing river flood risk in Germany

Flood risk assessments are an important basis for risk management. For larger regions, these assessments are typically based on smallscale modelling and are subsequently compiled into a large-scale picture. However, this approach neglects space-time interactions and does not provide realistic risk statements for larger regions. This paper presents the "derived flood risk analysis based on long-term simulation" and its implementation for Germany as an alternative approach. A model chain consisting of spatially distributed hydrological, hydraulic, and damage models simulates the occurrence of extreme runoff, inundation, and direct economic damages. This model chain is driven by a weather generator that provides spatially consistent fields of climate variables. The generation of very long time series, spanning several thousand years with daily resolution, allows the estimation of extreme runoff and the corresponding damages. The inclusion of space-time dependencies in all model components, from the weather generator to the damage model, is able to provide consistent large-scale risk statements. For the considered river floodplains, i.e. large rivers and tributaries in Germany, we estimate the Expected Annual Damage to be around <euro> 580 million for the economic sectors private households and commerce. This approach also allows the development of plausible extreme scenarios posing new challenges for flood risk management.