This study examines spatial disparities in flood risk and social vulnerability across the CONUS, emphasizing urban-rural differences and environmental justice implications. It analyzes social factors using ACS 2016-2020 data and PCA, focusing on their spatial distribution.
Using the MGWR package in Python, we conducted separate GWR models for "Urban" and "Rural" areas and created an overall model to capture the localized impacts of environmental factors. QGIS was used to map and visualize the data. Statistical tests reveal significant differences in flood risk and vulnerability between urban and rural areas. Cluster analysis identifies high-risk clusters in urban zones like the Gulf Coast and Mississippi River. Regression models highlight spatial variability in social vulnerability and its local impacts on flood risk, emphasizing regional disparities with higher risks in urban areas. Even low-risk rural areas exhibit significant vulnerability, urging targeted flood mitigation and resilience strategies. These findings inform policymakers on environmental justice and equitable flood risk management.
