TY  - JOUR
PY  - 2023//
TI  - Predicting burn severity for integration with post-fire debris-flow hazard assessment: a case study from the Upper Colorado River Basin, USA
JO  - International journal of wildland fire
A1  - Wells, Adam G.
A1  - Hawbaker, Todd J.
A1  - Hiers, J. Kevin
A1  - Kean, Jason
A1  - Loehman, Rachel A.
A1  - Steblein, Paul F.
SP  - 1315
EP  - 1331
VL  - 32
IS  - 9
N2  - 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>
LA  - en
SN  - 1049-8001
UR  - http://dx.doi.org/10.1071/WF22200
ID  - ref1
ER  -