CONTROLS ON POST-WILDFIRE DRY RAVEL LOADING IN CHANNELS USING REPEAT AIRBORNE LIDAR

Wildfires are disturbances in mountainous terrain that increase the potential for the generation of debris flow hazards that threaten human lives and infrastructure along the wildlife urban interface. Dry ravel transport is a well-documented process characteristic of the steep mountains of Southern California that conveys post-wildfire sediment from hillslopes to channels in the absence of rainfall. However, the signature of dry ravel loading in channels has been difficult to quantify an there is a need to understand the topographic and lithological controls on dry ravel and its relation to debris flow generation. In this study, we use a combination of multitemporal, high resolution imagery and airborne lidar data from 230 km² of the burned landscapes from the 2020 Apple, El Dorado, and Bobcat fires in the San Gabriel and San Bernadino Mountains, California. We used the M3C2 change detection algorithm between the pre-fire and immediate post-fire lidar datasets to determine patterns in dry ravel loading across different topographic and lithological factors, burn severities, fire histories, and background erosion rates. Manual mapping using post-fire lidar and 4-10 cm commercial aerial imagery was performed to characterize dry ravel deposits below the lower limit of detection (~ 50 cm) from automated approaches. Preliminary results suggest slope is the primary control on dry ravel volume in channels, but that systematic regional variations exist that likely depend on lithologic controls such as bedrock fracture density. This study highlights the potential of using multitemporal lidar to understand large scale sediment transport and storage following fires and the implications for debris flow generation and hazard assessment.