TY  - JOUR
A1  - Sairam, Nivedita
A1  - Brill, Fabio Alexander
A1  - Sieg, Tobias
A1  - Farrag, Mostafa
A1  - Kellermann, Patric
A1  - Viet Dung Nguyen, 
A1  - Lüdtke, Stefan
A1  - Merz, Bruno
A1  - Schröter, Kai
A1  - Vorogushyn, Sergiy
A1  - Kreibich, Heidi
T1  - Process-based flood risk assessment for Germany
T2  - Earth's future / American Geophysical Union
N2  - Large-scale flood risk assessments are crucial for decision making, especially with respect to new flood defense schemes, adaptation planning and estimating insurance premiums. We apply the process-based Regional Flood Model (RFM) to simulate a 5000-year flood event catalog for all major catchments in Germany and derive risk curves based on the losses per economic sector. The RFM uses a continuous process simulation including a multisite, multivariate weather generator, a hydrological model considering heterogeneous catchment processes, a coupled 1D-2D hydrodynamic model considering dike overtopping and hinterland storage, spatially explicit sector-wise exposure data and empirical multi-variable loss models calibrated for Germany. For all components, uncertainties in the data and models are estimated. We estimate the median Expected Annual Damage (EAD) and Value at Risk at 99.5% confidence for Germany to be euro0.529 bn and euro8.865 bn, respectively. The commercial sector dominates by making about 60% of the total risk, followed by the residential sector. The agriculture sector gets affected by small return period floods and only contributes to less than 3% to the total risk. The overall EAD is comparable to other large-scale estimates. However, the estimation of losses for specific return periods is substantially improved. The spatial consistency of the risk estimates avoids the large overestimation of losses for rare events that is common in other large-scale assessments with homogeneous return periods. Thus, the process-based, spatially consistent flood risk assessment by RFM is an important step forward and will serve as a benchmark for future German-wide flood risk assessments.
KW  - risk model chain
KW  - continuous simulation
KW  - expected annual damage
KW  - risk
KW  - curves
KW  - multi-sector risk
Y1  - 2021
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/61288
SN  - 2328-4277
VL  - 9
IS  - 10
PB  - Wiley-Blackwell
CY  - Hoboken, NJ
ER  -