Enhancing resilience: Integrating future flood modeling and socio-economic analysis in the face of climate change impacts.

As climate change intensifies, future floods will become more severe in some areas with geographic variation, necessitating that local and regional governments implement systems to provide information for climate adaptation, particularly for vulnerable populations. Therefore, we aimed to develop a methodology to identify areas that are at an increased risk from future floods and independently socially vulnerable. In this study, 100-year recurrence interval flood extents and depths were estimated using an ensemble of six independent Coupled Model Intercomparison Project Phase 6 climate models for a past and future period under the highest-emissions climate scenario. The flood inundation results were related to social vulnerability for two selected study areas in the Mississippi River Basin. The range of flood extents and depths for both time periods were estimated, and differences were evaluated to determine the effects from climate change. To identify at-risk areas, the relationship between the spatial distribution of flood depths and vulnerability was then assessed. Finally, an analysis of the current and future damages on infrastructure from flooding on residential housing was performed to determine whether damages are correlated with higher vulnerability areas. Results show in every flooding scenario, flood extents and depths are increasing in the future compared with the past, ranging from an increase of 6 to 76 km in extent across both locations. A statistically significant relationship between spatial clusters of flooding and of vulnerability was found. The infrastructure analysis found that residential structures in the most vulnerable census tracts are 6 to 59 times more likely to experience moderate damage compared with the least vulnerable tracts depending on scenario. Overall, a framework was established to holistically understand the hydrologic and socioeconomic impacts of climate change, and a methodology was developed to use for allocating resources at the local scale.