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Shredding post-fire debris flow likelihood: A field-constrained catchment-scale model of wood-shred surface treatment effectiveness
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DOI：10.1016/j.geomorph.2026.110343.png)
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Abstract
En 中文
Post-fire debris flows threaten life, property, infrastructure, and the water supplies of many major cities. One mitigation strategy is the broadscale application of surface mulches to burned hillslopes to reduce surface runoff; however, few studies have evaluated the effectiveness of mulching treatments specifically for debris flow mitigation. Uncertainty around treatment effectiveness has prevented quantitative assessments of cost-effectiveness. This research addresses this gap by integrating plot-scale field hydrologic measurements with catchment-scale post-fire debris flow modelling to quantify treatment effectiveness for reducing debris flow likelihood. Twelve runoff plots were installed with four treatments (unburned, control burned, low wood-shred cover [54%], and high wood-shred cover [72%]) and monitored continuously for 12 months under natural and simulated rainfall. These data were combined with existing observations to estimate infiltration parameters as a function of treatment application rate, time since fire, and site productivity. These infiltration parameters were then used in a post-fire debris flow model to evaluate changes in debris flow initiation likelihood, represented by the Annual Exceedance Probability (AEP, %) of the initiating rainfall event, for a similar to 32,000-ha case-study catchment exhibiting high spatial variability in post-fire hydrogeomorphic susceptibility. The results suggest that wood-shred treatment would be highly effective in reducing debris flow likelihood, with the maximum AEP decreasing from 72% with no surface treatment to 32% (2.25-fold reduction) and 4% (18-fold reduction), under the low and high cover treatments, respectively. This study fills a critical gap in quantifying the effectiveness post-fire surface treatments by integrating empirical field data with a process-based debris-flow model.
Keywords:
Peak runoff
Geomorphic hazard
Post-fire
Mitigation
Surface mulch
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