Nivedita Sairam, Fabio Alexander Brill, Tobias Sieg, Mostafa Farrag, Patric Kellermann, Viet Dung Nguyen, Stefan Lüdtke, Bruno Merz, Kai Schröter, Sergiy Vorogushyn, Heidi Kreibich
- 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 byLarge-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.…
MetadatenAuthor details: | Nivedita SairamORCiDGND, Fabio Alexander BrillORCiDGND, Tobias SiegORCiDGND, Mostafa FarragORCiDGND, Patric KellermannORCiD, Viet Dung Nguyen, Stefan LüdtkeORCiD, Bruno MerzORCiDGND, Kai SchröterORCiD, Sergiy VorogushynORCiDGND, Heidi KreibichORCiD |
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DOI: | https://doi.org/10.1029/2021EF002259 |
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ISSN: | 2328-4277 |
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Title of parent work (English): | Earth's future / American Geophysical Union |
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Publisher: | Wiley-Blackwell |
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Place of publishing: | Hoboken, NJ |
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Publication type: | Article |
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Language: | English |
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Date of first publication: | 2021/10/09 |
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Publication year: | 2021 |
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Release date: | 2023/11/10 |
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Tag: | continuous simulation; curves; expected annual damage; multi-sector risk; risk; risk model chain |
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Volume: | 9 |
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Issue: | 10 |
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Article number: | e2021EF002259 |
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Number of pages: | 12 |
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Funding institution: | German Federal Ministry of Education and Research (BMBF) project DECIDERFederal Ministry of Education & Research (BMBF) [01LZ1703A-H]; BMBFFederal Ministry of Education & Research (BMBF) [01LP1903E]; DFGGerman Research Foundation (DFG)European Commission [FOR 2416, 278017089]; Projekt DEAL |
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Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie |
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DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
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Peer review: | Referiert |
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Publishing method: | Open Access / Hybrid Open-Access |
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| DOAJ gelistet |
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License (German): | CC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International |
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