Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall
Abstract. Communities downstream from burned steeplands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream from burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24-hour lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. Sensitivity analyses indicate that reducing uncertainty in postfire debris-flow volume prediction will have the largest impact on reducing inundation outcome uncertainty. The study results are an initial step toward an operational hazard assessment product that includes debris-flow inundation.
Status: final response (author comments only)
Model code and software
Online repository for code and data used in: Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall https://doi.org/10.5281/zenodo.7838914
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