Predicting Postfire Sediment Yields of Small Steep Catchments Using Airborne Lidar Differencing

Abstract

Predicting sediment yield from recently burned areas remains a challenge but is important for hazard and resource management as wildfire impacts increase. Here we use lidar-based monitoring of two fires in southern California, USA to study the movement of sediment during pre-rainfall periods and postfire periods of flooding and debris flows over multiple storm events. Using a data-driven approach, we examine the relative importance of terrain, vegetation, burn severity, and rainfall amounts through time on sediment yield. We show that incipient fire-activated dry sediment loading and pre-fire colluvium were rapidly flushed out by debris flows and floods but continued erosion occurred later in the season from soil erosion and, in ∼9% of catchments, from shallow landslides. Based on these observations, we develop random forest regression models to predict dry ravel and incipient runoff-driven sediment yield applicable to small steep headwater catchments in southern California.