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• W3110073964 abstract "In the last two decades, probabilistic approaches to flood risk modeling have emerged, often as an extension of more consolidated methods used in probabilistic seismic risk assessment. Nonetheless, only a few studies deal with best-practice methodologies for flood physical vulnerability assessment, and existing approaches/models often lack appropriate guidance for their selection/rating and use. These concerns underline the need for a rational, integrated and comprehensive compendium of existing flood-related fragility (i.e., the likelihood of various damage states as a function of hazard intensity measure(s)) and vulnerability (i.e., the likelihood of loss levels as a function of hazard intensity measure(s)) models to be used in probabilistic flood risk assessment. To this aim, and following the approach used in the guidelines recently developed by the Global Earthquake Model (GEM) project, this paper proposes a model taxonomy for flood fragility and vulnerability assessment of buildings. A review of state-of-the-art large-scale models for flood vulnerability assessment is first carried out. A discussion on the main factors affecting the reliability of empirical fragility and vulnerability relationships is presented, focusing on data sources, building classification, statistical techniques for data collection/fitting, and damage scales/loss metrics. As a proof of concept, a compendium of existing studies dealing with empirical fragility and vulnerability models for buildings is finally developed and discussed based on the proposed model taxonomy. This type of database can benefit (re)insurance companies interested in flood loss assessment and various decision-makers (e.g., governmental agencies) committed to mitigate flood risk and communicate its level to different stakeholders." @default.
• W3110073964 created "2020-12-07" @default.
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• W3110073964 date "2021-02-01" @default.
• W3110073964 modified "2023-10-15" @default.
• W3110073964 title "A model taxonomy for flood fragility and vulnerability assessment of buildings" @default.
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• W3110073964 doi "https://doi.org/10.1016/j.ijdrr.2020.101985" @default.
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