Assessing social vulnerability and identifying spatial hotspots of flood risk to inform socially just flood management policy

Abstract

This study presents the first nationwide spatial assessment of flood risk to identify social vulnerability and flood exposure hotspots that support policies aimed at protecting high-risk populations and geographical regions of Canada. The study used a nationalscale flood hazard dataset (pluvial, fluvial, and coastal) to estimate a 1-in-100-year flood exposure of all residential properties across 5721 census tracts. Residential flood exposure data were spatially integrated with a census-based multidimensional social vulnerability index (SoVI) that included demographic, racial/ethnic, and socioeconomic indicators influencing vulnerability. Using Bivariate Local Indicators of Spatial Association (BiLISA) cluster maps, the study identified geographic concentration of flood risk hotspots where high vulnerability coincided with high flood exposure. The results revealed considerable spatial variations in tract-level social vulnerability and flood exposure. Flood risk hotspots belonged to 410 census tracts, 21 census metropolitan areas, and eight provinces comprising about 1.7 million of the total population and 51% of half-a-million residential properties in Canada. Results identify populations and the geographic regions near the core and dense urban areas predominantly occupying those hotspots. Recognizing priority locations is critically important for government interventions and risk mitigation initiatives considering socio-physical aspects of vulnerability to flooding. Findings reinforce a better understanding of geographic flood-disadvantaged neighborhoods across Canada, where interventions are required to target preparedness, response, and recovery resources that foster socially just flood management strategies. K E Y W O R D S100-year flood hazard, environmental justice, flood risk management, residential flood exposure, social vulnerability

Assessing the social risks of flooding for coastal societies: a case study for Prince Edward Island, Canada

“…Scientific community has widely applied the flood risk assessment by combining flood exposure and social vulnerability together for a more comprehensive result (e.g., Chen et al 2021, Chakraborty et al 2023, Lipatov et al 2023. Following this strategy, we generated a flood risk matrix using bivariate choropleth mapping method (figure 3).…”

Disaster risk analysis of technological failure of industrial estate: a case study

“…Vulnerability assessment aims to identify the reason(s) for people's decreased resilience due to external factors that may threaten their safety, livelihood, natural resources, infrastructures, economic productivity, and welfare [19]. The aspects of vulnerability are (1) physical vulnerability describes the estimated physical (infrastructure) damage should a certain hazard occur; (2) economic vulnerability measures the loss or damage of economic activities following a hazardous event; and (3) social vulnerability is the susceptibility of a given population to being impacted by a hazardous event [20].…”

“…The sex ratio (female) contributes to vulnerability because women in Indonesia generally stay at home; therefore, the chance of exposure is higher if a technological failure occurs. The age factor in this study reflects that the older people and toddler population have less capacity to keep themselves safe from danger, resulting in lower odds of survival than the remaining cohorts when disasters strike [19], [20]. Meanwhile, people living in poverty are considered vulnerable due to requiring more efforts to adapt and a longer time to recover from disasters because of their lack of access to financial aid.…”

“…In this study, even for the areas with low vulnerability, the classification of disaster risk still depends on the hazard level. Areas with low vulnerability may experience low and even high risk, depending on the hazards that may arise [19], i.e., an area with low vulnerability with a high-hazard level will still have a high-risk level. Some of the examples are Ngimboh Village, Banyuurip Village, Sembayat Village, Manyarejo Village, Banyuwangi Village, Sukomulyo Villa-Pongahan Village, and Peganden Village in Manyar District, all of which have a low vulnerability but indicate a moderate-to high-risk level.…”