Integrative Multi-Criteria Geospatial Modeling for Assessing Compound Flood-Contamination Risks in Vulnerable Communities

Abstract This study aims to develop an integrative geospatial framework to assess compound flood–contamination risks and their intersection with social vulnerability, using the Coosa River watershed in Alabama and Georgia as a case study. Employing a Multi-Criteria Decision Analysis (MCDA) based on the Analytic Hierarchy Process (AHP) combined with Bivariate Local Moran’s I, the study evaluates flood risks, industrial contamination potential from Toxic Release Inventory (TRI) facilities, and socio-economic conditions for the years 2000, 2010, and 2020. Flood risk parameters, TRI data, and social indicators were standardized and weighted to produce spatially explicit risk maps, while spatial autocorrelation analysis identified statistically significant clusters of compounded vulnerability. The results show a marked decline in high-risk zones, particularly in the upper and lower Coosa regions, indicating progress in industrial regulation and socio-economic resilience, although moderate-risk clusters persist in areas with ongoing industrial activity. The integrated AHP–LISA framework demonstrates how geospatial and socio-economic data can be effectively combined to identify areas where flood-induced contamination and social vulnerability coincide. This novel methodological approach is transferable to other river systems, offering a practical foundation for assessing and mitigating compound environmental risks while promoting flexible, evidence-based watershed management and equitable policy interventions to protect vulnerable communities. Highlights A novel AHP–LISA framework that integrates flooding, pollution, and social vulnerability risks. High-risk flood-contaminated areas have shifted across the Coosa River watershed. Social vulnerability trends show dynamic changes from 2000 to 2020. Analytic Hierarchy Process enhances environmental risk assessment accuracy.