Social and Environmental Vulnerability to Flooding: Investigating Cross-Scale Hypotheses

Flooding is a natural hazard that touches nearly all facets of the globe. The exposure of communities to flooding is only projected to become more frequent and intensified due to climate and land-use change; therefore, it is vital to understand how flooding impacts are distributed across populations. An approach to mapping the landscape of geographic flood-disadvantaged communities is using a social vulnerability index (SoVI). SoVI relies on aggregated socioeconomic data that can be curated at several scales and subject to the effects of the Modifiable Areal Unit Problem (MAUP). Understanding how scale influences flood vulnerability results is limited in literature and advantageous as this information could inform future decision-making for allocating resources within communities.

This multi-scale flood risk analysis integrated social vulnerability, land cover, and flood hazard data to investigate the relationship of vulnerable populations to varying levels of flood exposure across the block group, tract, and county scales within coastal Virginia. The deviation and similarities of social correlates of vulnerability to flooding were investigated across scales. Additionally, the geography of local clusters and spatial outliers of social vulnerability to flood exposure, determined through a bivariate Local Indicators of Spatial Association (LISA) analysis, was utilized to identify social inequities within the floodplain and deviations across scales.

I found that the aggregation of geographic units and scale selection considerably impacts social vulnerability and flood risk results. There are instances where increased aggregated scales significantly undercounted highly vulnerable populations. Similar trends occurred for areas of high vulnerability and varying exposure, which are target locations for current and future flood risk reduction. I also found that based on the integrated scale the landscape of vulnerability and flood risk can identify different priority areas, which can be a real-life consequence of the MAUP. These results warrant the discussion of understanding scale selection implications on research methodological approaches and what this means for practitioners and policymakers that utilize vulnerability information to help guide flood mitigation strategies.