Background Wildfires are increasing in incidence, size, and severity in the USA along with associated firefighting costs. Evaluation of firefighting containment and mop-up activities are crucial to reduce costs and to inform safe and effective wildfire response. As geospatial technologies advance, fireline effectiveness metrics have continued to be updated and improved. However, to develop standard analysis protocols and performance evaluations, there is a need to understand how widely metrics vary within and across fire events and are dependent on the different sources and accuracy of geospatial datasets, including firelines, fire perimeters, and severity layers. To ascertain the usefulness and limitations of four fireline effectiveness metrics, we evaluated several metrics including ratios of fireline engaged, held, and burned over. We performed a sensitivity analysis across 13 recent wildfires in north-central Washington State. Results Our study found that fire perimeter source and fireline buffer width had the largest impact on quantified fireline effectiveness metrics. Misclassification of firelines produced dramatic erroneous results which artificially increased the effectiveness and decreased suppression effort. High-severity fires were shown to be less effective across all fireline types and required higher suppression than most low- and moderate-severity fires. Conclusion Our results suggest that the fireline effectiveness methodology we tested was robust but could benefit from further refinement with the additional step of visual inspection for fireline misclassifications and database errors. Users should also consider evaluating a range of buffer widths prior to calculating fireline metrics to allow for some minor discrepancies between firelines and fire perimeters. Importantly, our results showed that for high-severity burns firelines were less efficient, and the placement of firelines should be carefully considered to more efficiently allocate firefighting resources and new dozer lines within high-severity landscapes, such as dense mixed conifer forests.
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