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From precipitation to damage

  • Flood risk assessments for large river basins often involve piecing together smaller-scale assessments leading to erroneous risk statements. We describe a coupled model chain for quantifying flood risk at the scale of 100,000 km(2). It consists of a catchment model, a 1D-2D river network model, and a loss model. We introduce the model chain and present two applications. The first application for the Elbe River basin with an area of 66,000 km(2) demonstrates that it is feasible to simulate the complete risk chain for large river basins in a continuous simulation mode with high temporal and spatial resolution. In the second application, RFM is coupled to a multisite weather generator and applied to the Mulde catchment with an area of 6,000 km(2). This approach is able to provide a very long time series of spatially heterogeneous patterns of precipitation, discharge, inundation, and damage. These patterns respect the spatial correlation of the different processes and are suitable to derive large-scale risk estimates. We discuss how theFlood risk assessments for large river basins often involve piecing together smaller-scale assessments leading to erroneous risk statements. We describe a coupled model chain for quantifying flood risk at the scale of 100,000 km(2). It consists of a catchment model, a 1D-2D river network model, and a loss model. We introduce the model chain and present two applications. The first application for the Elbe River basin with an area of 66,000 km(2) demonstrates that it is feasible to simulate the complete risk chain for large river basins in a continuous simulation mode with high temporal and spatial resolution. In the second application, RFM is coupled to a multisite weather generator and applied to the Mulde catchment with an area of 6,000 km(2). This approach is able to provide a very long time series of spatially heterogeneous patterns of precipitation, discharge, inundation, and damage. These patterns respect the spatial correlation of the different processes and are suitable to derive large-scale risk estimates. We discuss how the RFM approach can be transferred to the continental scale.show moreshow less

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Metadaten
Author details:Bruno MerzORCiDGND, Heiko ApelORCiDGND, Viet-Dung Dung Nguyen, Daniela FalterGND, Björn GuseORCiD, Yeshewatesfa Hundecha, Heidi KreibichORCiDGND, Kai SchröterORCiDGND, Sergiy VorogushynORCiDGND
DOI:https://doi.org/10.1002/9781119217886.ch10
ISBN:978-1-119-21788-6
ISBN:978-1-119-21786-2
ISSN:0065-8448
Title of parent work (English):Global flood hazard : applications in modeling, mapping and forecasting
Subtitle (English):a coupled model chain for spatially coherent, large-scale flood risk assessment
Publisher:American Geophysical Union
Place of publishing:Washington
Publication type:Article
Language:English
Date of first publication:2018/07/03
Publication year:2018
Release date:2022/02/21
Volume:233
Number of pages:15
First page:169
Last Page:183
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
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