Feature importance measures for flood forecasting system design

Effective proxy selection in hydrological processes is crucial in several applications. This study investigates the role of sub-basins in hydrological response, which remains unclear. Our focus is on exploring feature importance measures to identify influential sub-basins in a flood forecasting system. We use the Tiber River basin as a case study and employ a synthetic flood hydrograph dataset, consisting in approximately 20 000 simulated annual maximum hydrographs across 39 sub-basins and the basin outlet. Through this study, we present a proof of concept for ranking sub-basins based on their contribution to basin response using six feature importance measures. The results reveal eight influential sub-basins and provide guidance for strategically installing measurement instrumentation for an efficient and cost-effective flood early warning system.