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New conceptual framework for flood risk assessment in Sheffield, UK

机译:洪水风险评估的新的概念框架在谢菲尔德,英国

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摘要

This study explores a new framework of flood risk assessment that considers four components, namely hazard, exposure, vulnerability, and community resilience. The key variables and coefficients were selected using principal component analysis and geographically weighted regression (GWR) in a geographic information system (GIS). GWR was applied to present a spatial relation between flood risks and regeneration areas for dependent and independent variables in the four components. Then the new conceptual framework was overlaid as a flood risk map using risk indicators of the four components. The first three components were included in the GIS framework to map flood risk indices, whereas the community resilience component was subtracted from the total indices. Finally, the total number of indices of the flood risk map were divided into nine levels, from 0 to 8. Overall, the study shows the utility of the flood risk map, which is based on the spatial coincidence of mapping of the four components in a case study of Sheffield in the United Kingdom. Areas with an index value of 8 on the flood risk map had the highest flood risks, which points to where there is a need for regeneration to improve flood defences and resilience.
机译:本研究探讨了一项新的洪水风险评估框架,即考虑四个组成部分,即危险,曝光,脆弱性和社区恢复力。在地理信息系统(GIS)中使用主成分分析和地理加权回归(GWR)来选择关键变量和系数。 GWR被应用于在四个组件中呈现洪水风险和再生区域之间的空间关系和再生区域。然后,使用四个组件的风险指标,新概念框架被重叠为洪水风险地图。前三个组成部分包括在GIS框架中,以映射洪水风险指标,而社区恢复力分量从总索引中减去。最后,洪水风险地图的指数总数分为九个层次,从0到8。总体而言,该研究显示了洪水风险地图的效用,这是基于四个组件映射的空间巧合谢菲尔德在英国的案例研究。洪水风险地图上有8个指标值的地区具有最高的洪水风险,这指出了需要再生以改善洪水防御和抵御能力的地方。

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