High urban flood risk and no shelter access disproportionately impacts vulnerable communities in the USA

The frequency and intensity of extreme flood events are drastically increasing in the U.S., causing significant consequences. The year 2022 witnessed historic flooding and extreme weather, stressing unprepared water infrastructure. Multiple 1-in-1000-year rainstorms caused widespread damage and fatalities across the country. This trend, exacerbated by climate change and risky urbanization patterns, disproportionately impacts vulnerable communities. These communities, often located in low-lying, flood-prone areas due to historical redlining and environmental racism, face deficient infrastructure and limited access to resources. Consequently, they experience greater impacts during severe events, highlighting the intersection of environmental and social inequalities. Existing research has examined flood risk for vulnerable populations and assessed health and economic impacts, but a comprehensive understanding requires incorporating access to shelters—a critical obstacle for vulnerable populations during disasters. Lack of shelter access amplifies flood risk vulnerability, especially in urban areas where resource-limited communities rely on public transport. This study aims to integrate shelter access into flood risk measures to prevent natural hazards from becoming human disasters.

Previous research has explored various aspects of urban flooding, including flood risk for vulnerable populations, health impacts, and economic consequences. Studies have examined shelter location suitability and effectiveness, their connection to community resilience, and optimal siting for flood evacuation. The importance of incorporating shelter access into disaster management, resilience, and urban planning has been emphasized, advocating for a community-centric approach to reduce casualties and minimize flood impacts. However, a comprehensive understanding of flood vulnerability has been hampered by the complexity of accounting for cross-sectoral vulnerabilities. This study builds upon previous work by explicitly integrating access to shelters into the flood risk assessment.

This study integrates three datasets: FEMA's National Risk Index (providing flood risk at the census track level), the National Shelter System Facilities (identifying shelter locations), and the 2015-2019 5-year American Community Survey (ACS) (providing demographic and socioeconomic information at the block group level). Auto access to shelters was calculated at the block group level using the Cumulative Opportunities Measure for 30 and 60-minute travel time thresholds. The Bivariate Local Indicator of Spatial Autocorrelation (BiLISA) clustering technique was used to spatially analyze the relationship between flood risk and shelter access. This identified four risk-exposed areas: (i) high flood risk and high shelter access (HH), (ii) high flood risk and low shelter access (HL), (iii) low flood risk and high shelter access (LH), and (iv) low flood risk and low shelter access (LL). The population of each cluster was then analyzed across seven socially vulnerable cohorts: disabled individuals, the elderly, carless, low-income, Hispanics, Asians, and African Americans. Eight high-risk U.S. cities were selected based on First Street Analysis’s flood risk assessment, representing diverse physiographic regions and flooding types.

The BiLISA analysis revealed that shelter allocation is not aligned with flood risk; areas with low shelter access frequently experience disproportionate flood risk. Shelters are more accessible in inner cities than at the edges, implying that edge residents are more vulnerable during floods. A substantial proportion of block groups fell into the 'Not Significant' (NS) cluster category, highlighting the importance of examining the distribution across other categories. Analysis revealed spatial heterogeneity in shelter access and flood risk across cities. For instance, San Antonio had the highest proportion of HL clusters (13%), while Detroit had the lowest (2%). Focusing on population exposed to each cluster, rather than just block group counts, emphasized the human impact. Analyzing socially vulnerable cohorts revealed unequal distribution of populations in flood risk areas across cities. Cities did not discriminate among cohorts; if one cohort had a higher share of at-risk population, others did as well, indicating a clustered pattern of vulnerability. Indianapolis, Nashville, Fresno, and San Antonio exhibited the highest inequality regardless of cohort. Contrary to previous research, Asians and the elderly were identified as the most at-risk groups, highlighting the importance of considering other vulnerable populations besides African Americans. Carless and disabled individuals were also particularly vulnerable. There was a positive correlation between the percentage of the population and the percentage of land areas exposed to flood risk in each city.

The findings highlight the need for a community-centric approach to flood risk management, rather than a land-centric approach that prioritizes areas based solely on land area at risk. This is crucial for equitable budget allocation and enhanced community resilience. Integrating access to shelters into flood risk assessments offers a more holistic perspective, considering socioeconomic vulnerabilities and improving resource allocation. This also helps to identify at-risk communities with limited access to shelters, enabling targeted interventions. This comprehensive approach improves both long-term (e.g., establishing more permanent shelters) and short-term (e.g., establishing temporary shelters during flood seasons) emergency strategies. Enhanced mobility options for vulnerable populations are also crucial. The integrated approach can inform policy-making and urban planning, providing a basis for developing an interactive strategic planning platform to explore different strategies and interventions.

This study demonstrates the value of integrating access to shelters into flood risk assessments to create more equitable and effective disaster preparedness strategies. The findings emphasize the need to prioritize communities at risk, particularly those with limited access to shelters, in resource allocation and policy development. Future research could refine the methodology by using more precise starting locations for travel time calculations and incorporating more detailed data on shelter operational status and accessibility for diverse populations. The framework presented is readily adaptable to other regions experiencing urban flooding.

The study used population-weighted centroids of block groups for travel time calculations, which may not be entirely precise. The analysis considered only the presence of shelters, not their operational status or suitability for specific populations during floods. Future work should address these limitations by employing more accurate data and incorporating factors like shelter capacity and accessibility for diverse needs.