@article{ref1,
title="Predicting burn severity for integration with post-fire debris-flow hazard assessment: a case study from the Upper Colorado River Basin, USA",
journal="International journal of wildland fire",
year="2023",
author="Wells, Adam G. and Hawbaker, Todd J. and Hiers, J. Kevin and Kean, Jason and Loehman, Rachel A. and Steblein, Paul F.",
volume="32",
number="9",
pages="1315-1331",
abstract="Background Burn severity significantly increases the likelihood and volume of post-wildfire debris flows. Pre-fire severity predictions can expedite mitigation efforts because precipitation contributing to these hazards often occurs shortly after wildfires, leaving little time for post-fire planning and management.Aim The aim of this study was to predict burn severity using pre-fire conditions of individual wildfire events and estimate potential post-fire debris flow to unburned areas.<br><br>METHODS We used random forests to model dNBR from pre-fire weather, fuels, topography, and remotely sensed data. We validated our model predictions against post-fire observations and potential post-fire debris-flow hazard estimates.Key results Fuels, pre-fire weather, and topography were important predictors of burn severity, although predictor importance varied between fires. Post-fire debris-flow hazard rankings from predicted burn severity (pre-fire) were similar to hazard assessments based on observed burn severity (post-fire).<br><br>CONCLUSION Predicted burn severity can serve as an input to post-fire debris-flow models before wildfires occur, antecedent to standard post-fire burn severity products. Assessing a larger set of fires under disparate conditions and landscapes will be needed to refine predictive models.Implications Burn severity models based on pre-fire conditions enable the prediction of fire effects and identification of potential hazards to prioritise response and mitigation.<p /> <p>Language: en</p>",
language="en",
issn="1049-8001",
doi="10.1071/WF22200",
url="http://dx.doi.org/10.1071/WF22200"
}