Objective definition of discharge thresholds for post-fire debris flows

Runoff-generated debris flows are a common post-fire hazard in the western United States and growing number of regions around world. As wildfire continues to emerge across broader range geographic plant communities, there is an increasing need for generalizable methods predict debris-flow initiation. The prediction flow during intense rainstorms has traditionally relied upon empirical rainfall thresholds. Rainfall intensity-duration thresholds often developed based on data hydrologic response those rainstorms. They most applicable specific where collected. Here, we present new predictive approach that utilises processes-based models with fundamental physics machine learning estimate discharge runoff-generated initiation four recently burned areas States. We assess performance objectively defined threshold-based predictions from our hybrid framework, which timing within rainstorms, physically numerical simulations runoff, support vector machines method. proposed have good balance between true false floods. Importantly, method permits direct estimation observations limited.