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A geospatial framework to assess fireline effectiveness for large wildfires in the western USAAuthor(s): Benjamin M. Gannon; Matthew P. Thompson; Kira Z. Deming; Jude Bayham; Yu Wei; Christopher D. O’Connor
Source: Fire. 3(3): 43.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
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DescriptionQuantifying fireline effectiveness (FLE) is essential to evaluate the efficiency of large wildfire management strategies to foster institutional learning and improvement in fire management organizations. FLE performance metrics for incident-level evaluation have been developed and applied to a small set of wildfires, but there is a need to understand how widely they vary across incidents to progress towards targets or standards for performance evaluation. Recent efforts to archive spatially explicit fireline records from large wildfires facilitate the application of these metrics to a broad sample of wildfires in different environments. We evaluated fireline outcomes (burned over, held, not engaged) and analyzed incident-scale FLE for 33 large wildfires in the western USA from the 2017 and 2018 fire seasons. FLE performance metrics varied widely across wildfires and often aligned with factors that influence suppression strategy. We propose a performance evaluation framework based on both the held to engaged fireline ratio and the total fireline to perimeter ratio. These two metrics capture whether fireline was placed in locations with high probability of engaging with the wildfire and holding and the relative level of investment in containment compared to wildfire growth. We also identify future research directions to improve understanding of decision quality in a risk-based framework.
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CitationGannon, Benjamin M.; Thompson, Matthew P.; Deming, Kira Z.; Bayham, Jude; Wei, Yu; O’Connor, Christopher D. 2020. A geospatial framework to assess fireline effectiveness for large wildfires in the western USA. Fire. 3(3): 43.
Keywordsperformance evaluation, suppression effectiveness, incident strategy, risk management, decision support
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