Improved prediction of postfire debris flows through rainfall anomaly maps

Geophysical Research Letters
By: , and 

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Abstract

Predicting where runoff-generated debris flows might occur during rainfall on steep, recently burned terrain is challenging. Studies of mass-movement processes in unburned areas indicate that event locations are well-predicted by rainfall anomaly, R*, in which peak observed rainfall is normalized by local rainfall climatology. Here, we use remote and field methods to map debris flows triggered within the 2020 Dolan Fire burn area in coastal California, demonstrate that a short-duration R* metric predicts debris-flow occurrence more effectively than absolute peak intensity or longer-duration rainfall metrics, and show that incorporating an R* criterion into an existing debris-flow likelihood model can reduce false positive predictions and improve accuracy. We test R* at three other climatically distinct fires in California, demonstrating its utility for mapping likely debris-flow locations in different climates. We also consider how R* can benefit postfire debris-flow prediction given recent increases in climatological variability within individual burn perimeters.

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Publication type Article
Publication Subtype Journal Article
Title Improved prediction of postfire debris flows through rainfall anomaly maps
Series title Geophysical Research Letters
DOI 10.1029/2025GL114791
Volume 52
Issue 16
Publication Date August 19, 2025
Year Published 2025
Language English
Publisher American Geophysical Union
Contributing office(s) Geologic Hazards Science Center - Landslides / Earthquake Geology
Description e2025GL114791, 12 p.
Country United States
State Callifornia
County Monterey County
Additional publication details