16 Jun 2025

Enhancing Resilience: Integrating Future Flood Modeling and Socio-Economic Analysis in the Face of Climate Change Impacts

Abstract: As climate change intensifies, floods will become more severe in some areas with geographic variation, necessitating governments implementing systems providing information for climate adaptation. We aimed to develop a methodology identifying areas at an increased risk. 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 study areas in the Mississippi River Basin. To identify at-risk areas, the relationship between the spatial distribution of flood depths and vulnerability was assessed. Finally, an analysis of current and future damages on infrastructure from flooding on residential housing to determine whether damages correlated with higher vulnerability areas. Results show flood extents and depths are increasing in the future, ranging from an increase of 6 to 76 km2 in extent. A statistically significant relationship between spatial clusters of flooding and of vulnerability was found. Overall, a framework was established to holistically understand the hydrologic and socioeconomic impacts of climate change, and a methodology was developed for allocating resources at the local scale.

21 Jun 2024

Multiscale Observation Product (MOP) for Temporal Flood Inundation Mapping of the 2015 Dallas Texas Flood

Abstract: This paper presents a new data fusion multiscale observation product (MOP) for flood emergencies. The MOP was created by integrating multiple sources of contributed open-source data with traditional spaceborne remote sensing imagery to provide a sequence of high spatial and temporal resolution flood inundation maps. The study focuses on the 2015 Memorial Day floods that caused up to US$61 million of damage. The Hydraulic Engineering Center River Analysis System (HEC-RAS) model was used to simulate water surfaces for the northern part of the Trinity River in Dallas, using reservoir surcharge releases and topographic data provided by the US Army Corps of Engineers. A measure of fit assessment is performed on the MOP flood maps with the HEC-RAS simulated flood inundation output to quantify spatial differences. Estimating possible flood inundation using individual datasets that vary spatially and temporally allow an understanding of how much each observational dataset contributes to the overall water estimation. Results show that water surfaces estimated by MOP are comparable with the simulated output for the duration of the flood event. Additionally, contributed data, such as Civil Air Patrol, although they may be geographically sparse, become an important data source when fused with other observation data.