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    Importance of catchment hydrological processes and calibration of hydrological‐hydrodynamic rainfall‐runoff models in small rural catchments (2023)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2024-01-19
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉In recent years, many two‐dimensional (2D) hydrodynamic models have been extended to include the direct rainfall method (DRM). This allows their application as a hydrological‐hydrodynamic model for the determination of floodplains in one model system. In previous studies on DRM, the role of catchment hydrological processes (CaHyPro) and its interaction with the calibration process was not investigated in detail. In the present, case‐oriented study, the influence of the spatiotemporal distribution of the processes precipitation and runoff formation in combination with the 2D model HEC‐RAS is investigated. In a further step, a conceptual approach for event‐based interflow is integrated. The study is performed on the basis of a single storm event in a small rural catchment (low mountain range, 38 km〈sup〉2〈/sup〉) in Hesse (Germany). The model results are evaluated against six quality criteria and compared to a simplified baseline model. Finally, the calibrated improved model is contrasted with a calibrated baseline model. The results show the enhancement of the model results due to the integration of the CaHyPro and highlight its interplay with the calibrated model parameters.〈/p〉
    Keywords: ddc:551.48 ; 2D hydrodynamic modeling ; calibration ; direct rainfall modeling ; hydrological processes ; radar data ; runoff formation
    Language: English
    Type: doc-type:article
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  • 2
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    Toward an adequate level of detail in flood risk assessments (2023)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2024-01-24
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Flood risk assessments require different disciplines to understand and model the underlying components hazard, exposure, and vulnerability. Many methods and data sets have been refined considerably to cover more details of spatial, temporal, or process information. We compile case studies indicating that refined methods and data have a considerable effect on the overall assessment of flood risk. But are these improvements worth the effort? The adequate level of detail is typically unknown and prioritization of improvements in a specific component is hampered by the lack of an overarching view on flood risk. Consequently, creating the dilemma of potentially being too greedy or too wasteful with the resources available for a risk assessment. A “sweet spot” between those two would use methods and data sets that cover all relevant known processes without using resources inefficiently. We provide three key questions as a qualitative guidance toward this “sweet spot.” For quantitative decision support, more overarching case studies in various contexts are needed to reveal the sensitivity of the overall flood risk to individual components. This could also support the anticipation of unforeseen events like the flood event in Germany and Belgium in 2021 and increase the reliability of flood risk assessments.〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: BMBF http://dx.doi.org/10.13039/501100002347
    Description: Federal Environment Agency http://dx.doi.org/10.13039/501100010809
    Description: http://howas21.gfz-potsdam.de/howas21/
    Description: https://www.umwelt.niedersachsen.de/startseite/themen/wasser/hochwasser_amp_kustenschutz/hochwasserrisikomanagement_richtlinie/hochwassergefahren_und_hochwasserrisikokarten/hochwasserkarten-121920.html
    Description: https://download.geofabrik.de/europe/germany.html
    Description: https://emergency.copernicus.eu/mapping/list-of-components/EMSN024
    Description: https://data.jrc.ec.europa.eu/collection/id-0054
    Description: https://oasishub.co/dataset/surface-water-flooding-footprinthurricane-harvey-august-2017-jba
    Description: https://www.wasser.sachsen.de/hochwassergefahrenkarte-11915.html
    Keywords: ddc:551.48 ; decision support ; extreme events ; integrated flood risk management ; risk assessment
    Language: English
    Type: doc-type:article
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