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Evaluating a simulation-based wildfire burn probability map for the conterminous U.S.

Amanda Carlson , Todd Hawbaker, Lucas Bair, Chad Hoffman, James Meldrum , L. Scott Baggett, Paul Steblein

Abstract

Background Wildfire simulation models are used to derive maps of burn probability (BP) based on fuels, weather, topography, and ignition locations, and BP maps are key components of wildfire risk assessments. Aims Few studies have compared BP maps to real-world fires to evaluate their suitability for near-future risk assessment. Here, we evaluated a BP map for the conterminous U.S. based on the large fire simulation model (FSim). Methods We compared BP to observed wildfires from 2016-2022 across 128 regions representing similar fire regimes (‘pyromes’). We evaluated the distribution of burned areas across BP values, and additionally compared burned area distributions among fire size classes. Key results Across all pyromes, mean BP was moderately correlated with observed burned area. An average of 71% of burned area occurred in higher-BP classes, vs. 79% expected. BP under-predicted burned area in the Mountain West, especially for extremely large fires. Conclusions The FSim BP map was useful for estimating subsequent wildfire hazard, but may have underestimated burned areas where input data did not reflect recent climate change, vegetation change, or human ignition patterns. Implications Our evaluations indicate that caution is needed when relying on simulation-based BP maps to inform management decisions. Our results also highlight potential opportunities to improve model estimates.

WF23196  Accepted 03 September 2024

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