Citation:

Thompson, M. AND John F. Carriger. Avoided wildfire impact modeling with counterfactual probabilistic analysis. Luciana Ghermandi (ed.), Frontiers in Forests and Global Change. Frontiers, Lausanne, Switzerland, 6:1266413, (2023). https://doi.org/10.3389/ffgc.2023.1266413

Impact/Purpose:

This article describes research on counterfactual analysis for fuels treatment on wildfire impacts from a collaboration between EPA and Forest Service personnel.  In the Western United States and elsewhere, the growing damages from wildfires lead to calls for increased investment in hazardous fuel reduction to protect the wildland–urban interface (WUI), among other objectives. Limited resources and operational constraints, among other factors, limit the areas where treatments can be implemented. Therefore, there is a clear need for strategic prioritization based on information about what fire and fuel management scenarios are most likely to be effective.

Description:

Assessing the effectiveness and measuring the performance of fuel treatments and other wildfire risk mitigation efforts are challenging endeavors. Perhaps the most complicated is quantifying avoided impacts. In this study, we show how probabilistic counterfactual analysis can help with performance evaluation. We borrow insights from the disaster risk mitigation and climate event attribution literature to illustrate a counterfactual framework and provide examples using ensemble wildfire simulations. Specifically, we reanalyze previously published fire simulation data from fire-prone landscapes in New Mexico, USA, and show applications for post-event analysis as well as pre-event evaluation of fuel treatment scenarios. This approach found that treated landscapes likely would have reduced fire risk compared to the untreated scenarios. To conclude, we offer ideas for future expansions in theory and methods.

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