Flood exposure and structure damage under deterministic design-storm and stochastic storm transposition rainfall scenarios: a case study in South Louisiana, USA

Flood hazard maps and damage estimates guide floodplain management, mitigation planning, and engineering design, but they commonly rely on rainfall frequency analysis to define annual exceedance probability (AEP) storms, commonly referred to as design storms. Current engineering practice typically employs spatially uniform design storms derived from point-based gauge statistics; however, this approach suppresses the spatial organization and intensity gradients present in observed storms. Stochastic storm transposition (SST) offers an alternative by preserving the spatial structure of observed rainfall and stochastically repositioning full storm fields across a watershed. This study compares flood exposure and damage produced by Atlas 14 and SST rainfall representations in the Vermilion River Basin, a low-gradient inland–coastal watershed in south-central Louisiana. Although the TP40-adjusted Atlas 14 rainfall depth was larger than the mean basin-average SST accumulation across the 50 realizations (310 mm vs. 238.1 mm), the SST _max composite produced substantially greater total structure damage than the baseline Atlas 14 scenario (USD 0.923 billion vs. USD 0.477 billion). Moreover, the comparison identified 11 518 buildings that were inundated in at least one SST realization but not under Atlas 14, representing more than USD 110 million in cumulative structural damage. The divergence between the two approaches is concentrated in mid-elevation urban neighborhoods, where spatial rainfall variability can cross local inundation thresholds that were not crossed under the spatially uniform storm. These results show that, in the VRB, the spatially uniform Atlas 14 design storm missed localized flood exposure that emerged when storm placement and rainfall spatial variability were represented.