Abstract Accurately assessing tropical cyclone (TC) flood risk requires capturing the dynamic interactions between rainfall‐driven and coastal flood processes. We simulate flooding from over 2,800 synthetic TCs impacting five HUC6 watersheds in eastern North and South Carolina under historical and future (SSP5‐8.5) conditions using climatologically consistent data derived from physics‐based numerical models. Projected future TCs in our data set exhibit slower translation speeds and produce higher rainfall rates, driving substantial increases in flood extent and depth despite a slight decrease in average wind speeds and storm surge. The 1% annual flood hazard grows by 36%, with the contribution of compound flooding nearly doubling from 12% to 25%. When sea level rise is included, coastal and compound flooding expand further inland and upriver. Importantly, we show that inundation is underestimated when runoff and coastal flood hazards are modeled in isolation. Additionally, we find that the joint‐probability of the peak or average boundary conditions for a storm does not equal the probability of the overland flood extent at the HUC6 scale. By leveraging a probabilistic framework, our results highlight that using process‐based models to capture the spatiotemporal dynamics of flooding is essential for accurate watershed‐scale TC flood hazard assessment. These findings underscore the growing importance of compound flooding under climate change and sea level rise and provide a foundation for improved risk‐informed planning, infrastructure design, and adaptation to future hazards in coastal areas.
Grimley et al. (Sun,) studied this question.