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In this paper we present the Regional Flood Model (RFM), a process‐based model cascade developed for large‐scale basins. The objective of this study is to demonstrate that flood risk assessments, based on a continuous simulation approach, including rainfall–runoff, 1D river network, 2D hinterland inundation and damage estimation models, are feasible at the scale of large catchments. RFM is applied to the German part of the Elbe catchment including around 2700 river‐km. For this proof‐of‐concept study, simulations are performed continuously over the period of 1990–2003. Simplification of equations and parallelisation enable the continuous 2D hydrodynamic inundation simulation with reasonable run‐times on a relatively high resolution of 100 m. As uncertainties are introduced with each module along the model chain, results are evaluated, where possible, with observed data. Results indicate that uncertainties are significant, especially for hydrodynamic simulations. This is basically a consequence of low data quality and disregarding dike breach effects in the simulations. Reliable information on overbank cross‐sections and dikes is expected to considerably improve the results. We conclude that the large‐scale simulation of catchment processes, inundation and damage, driven by long‐term climate data, is viable within a continuous simulation framework. It has the potential to provide a spatially consistent, large‐scale picture of flood risk.

17For a nationwide flood risk assessment in Germany, simulations of inundation depth and 18 extent for all major catchments are required. Therefore, a fast two-dimensional hydraulic

Abstract. Large-scale flood risk assessments are needed for a number of purposes, such as national strategic planning or re-insurance purposes. However, large-scale assessments are typically limited to hazard assessment and/or they are pieced together from smaller-scale assessments, leading to spatially inconsistent hazard and risk estimates. We present the coupled model chain RFM (Regional Flood Model) which is able to derive spatially consistent hazard and risk estimates for large scales (several 100,000 km 2 ). It consists of a hydrological model, a coupled 1D±2D hydrodynamic model and a flood loss model. This model chain can be driven by observed meteorology, output from regional climate models or a weather generator. In this application, we demonstrate for river basins in Germany that this approach is able to provide spatially consistent large-scale patterns of hazard and risk. A multi-site, multi-variate weather generator provides 10,000 years of spatially consistent weather at daily resolution which is used as input for the model chain. This approach allows deriving discharge, inundation and damage patterns which respect spatial interactions within and beyond catchment boundaries.

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