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Treesearch

A wildfire risk modeling system for evaluating landscape fuel treatment strategies

Informally Refereed
Download (PDF 586 KB): https://research.fs.usda.gov/download/treesearch/25942.pdf

Abstract

Despite a wealth of literature and models concerning wildfire risk, field units in Federal land management agencies lack a clear framework and operational tools to measure how risk might change from proposed fuel treatments. In an actuarial context, risk is defined as the expected value change from a fire, calculated as the product of (1) probability of a fire at a specific intensity and location, and (2) the resulting change financial or ecological value. The expected value definition accounts for landscape scale wildfire spread, intensity, and damage in a single measure, providing a relatively robust metric for comparing the effects of fuel treatment scenarios. New advances in calculating burn probabilities and recent work on resource valuation has set the stage for actuarial risk analysis in fuels treatment planning. To demonstrate this approach, we estimated expected net value change on 16,000 ha wildland-urban interface using 12 fuel treatment scenarios and four hypothetical value schemes. Burn probabilities were estimated by simulating 200 randomly-ignited wildfires. The results showed a nonlinear response in expected value with increasing treatment area. Fuels treatments on a relatively minor percentage of the landscape (20%) resulted in 20% to 50% increases in expected net value for most scenarios. The modeling advances the application of actuarial science to wildfire risk management and fuels treatment planning.

Parent Publication

Citation

Ager, Alan; Finney, Mark; McMahan, Andrew. 2006. A wildfire risk modeling system for evaluating landscape fuel treatment strategies. In: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 149-162