Abstract

Understanding flood driver interactions is essential for assessing compound floods, as their nonlinear contributions largely determine flood severity. This requires quantifying the spatiotemporal contributions of each driver to the compound water level across all combinations. Although several mathematical approaches have been developed, none fully account for all possible driver combinations or accurately represent the proportional contribution of each driver to the compound water level. To address these limitations, we introduce a Shapley value-based approach to compute the relative contributions of four flood drivers: tide, storm surge, river discharge, and precipitation, simulating Hurricane Beryl (2024) in the Houston–Galveston region, Texas. The spatiotemporal analysis revealed how compound flooding changes across space and time, including instances where certain drivers contributed negatively (reduced the compound water level when considered nonlinearly along with other flood drivers) to the overall water level. The comparison with Hurricane Harvey confirmed the method’s ability to capture variations in flood driver contributions across different hurricanes. By incorporating all driver combinations with non-uniform weights, our method accurately reproduced the compound water levels, including all four flood drivers. Overall, this Shapley value-based approach provides new insights into the spatiotemporal dynamics of each flood driver’s contributions and has the potential to inform flood driver-specific, targeted mitigation and risk management strategies.