New conceptual framework for flood risk assessment in Sheffield, UK

Abstract

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.

Inequality and heterogeneity of variables influencing parents' perceived worry before and during COVID-19 outbreak: evidence from a cross-sectional survey in Australia

“…The author summarises three main points for consideration: natural hazard, vulnerability, and elements at risk. Later, Chen H. modi ed the concept to examine the spatial associations of the three above points in the analysis but involved factors related to community resilience [33]. This study outlined factors affecting parents' resilience to worry during a health crisis and everyday life that were grouped and placed on each side of the triangle, Fig.…”