NH001-0008
Rainfall-intensity thresholds for post-wildfire debris-flow initiation vary with climatology of extreme rainfall
Rainfall-intensity thresholds for post-wildfire debris-flow initiation vary with climatology of extreme rainfall
Monday, 7 December 2020
Poster
Abstract:
With an ever-larger population at risk of post-wildfire debris-flow hazards, there is a growing need to accurately predict the rainfall intensities required for debris-flow initiation. As wildfires can occur in steeplands across a wide range of hydroclimates, a reliable prediction strategy must prove accurate across this full range. There is a growing body of observational evidence suggesting that post-wildfire debris-flow initiation thresholds can vary widely across the diverse climatic and geologic settings found in the western U.S. Through analyzing basin-scale observations of the rainfall intensities associated with post-wildfire debris-flow initiation, we find that rainfall-intensity thresholds for debris-flow initiation are systematically higher at sites that frequently experience higher maximum rainfall intensities. In particular, there is a strong correlation between a site’s observed 15-minute rainfall intensity threshold for debris-flow initiation and the site’s maximum 15-minute rainfall intensity associated with a one-year return interval. Since prior work has found that the physics of debris-flow initiation by rainfall-runoff processes are most sensitive to the 15-minute rainfall intensity, this correlation suggests that runoff generation and sediment transport processes in steep landscapes may be tuned to the local climatology of intense rainfall. We propose possible physical mechanisms by which landscapes frequently subjected to intense rainfall would have higher initiation thresholds. Results suggest that incorporation of the spatially variable maximum 15-minute rainfall intensity at a one year recurrence interval into empirical models used to predict probability of occurrence of post-wildfire debris flows will likely increase accuracy when making predictions across diverse hydroclimates.