DRY RAVEL LOADING OF STEEP HEADWATER VALLEY NETWORKS FUELS POST-WILDFIRE SEDIMENTATION HAZARDS IN SOUTHERN CALIFORNIA

Landscapes undergo dramatic shifts in dominant hydrologic and sediment transport processes following wildfire due to vegetation loss and changes in soil properties relative to unburned conditions. The associated sharp increases in sediment yield characteristic of burned watersheds can pose a hazard to life and property, and the prediction of destructive post-wildfire debris flows remains a significant challenge. Ultimately, sediment yields are governed by processes that deliver sediment from hillslopes to channels, but it is often unclear the degree to which hillslope sediment delivery is driven by dry versus wet transport processes.

Here we address this knowledge gap using repeat airborne lidar topography of the 2009 Station Fire in San Gabriel Mountains, California. Topographic change detection using pre-fire lidar and lidar collected immediately following the fire shows the pattern of headwater valley aggradation by dry ravel processes, and matches predictions based on a model of dry ravel sediment transport. Analysis of lidar flown 6 years following the fire reveals storm-driven erosion of accumulated dry ravel deposits and underlying channel fill. Lidar-derived erosion correlates with independent estimates of sediment yield from debris basins, and in general is highest for steep (>33°) burned catchments. We find no correlation of erosion with slope or dNBR, a metric of burn severity. Instead, geologic setting strongly controls patterns of post-wildfire erosion, with highly fractured and more mafic crystalline rocks in the southern range front facilitating post-wildfire debris flows fueled by dry ravel loading of headwater valleys. Overall, our data highlight the importance of hillslope sediment supply in determining post-wildfire channel erosion. Notably, the initial loading of headwater valleys with dry ravel is resolvable through repeat airborne lidar surveys and has the potential to assist in rapid-response hazard analysis for future wildfires.