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Predicting potential postfire debris-flow hazards across California prior to wildfire

Rebecca Rossi , Paul Richardson, David Cavagnaro, Stefani Lukashov, Mary Ellen Miller, Donald Lindsay

Abstract

Background. Wildfires and consequent postfire hazards, specifically runoff-generated debris flows, are a major threat to California communities. Aim. To help prefire planning efforts across California, we identified areas that are most susceptible to postfire debris flows before fire occurs. Methods. We developed a calibration method for an established model that relates existing vegetation type to fire severity, a critical input to the US Geological Survey’s postfire debris-flow likelihood model. We calibrated the model for eight regions with data from 81 wildfires that occurred in 2020 and 2021 in California. Key results. We predicted debris-flow likelihood, volume, and combined hazard classification, and created statewide maps that use simulated fire frequency and rainfall data to predict the probability that a basin will experience a wildfire and subsequent debris flow. Conclusions. We suggest that the model predictions are useful for identifying areas that pose the greatest risk of postfire debris-flow hazard for a simplified wildfire scenario. Implications. Although actual patterns of wildfire severity may vary from our simulated products, we show that applying a consistent methodology for all of California is useful for identifying areas that are likely to pose the greatest postfire hazards, which should help focus prefire mitigation efforts.

WF24225  Accepted 26 May 2025

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