Cost-Effective Fuel Treatment Planning

Abstract:

The cost of fighting large wildland fires in the western United States has grown dramatically over the past decade. This trend will likely continue with growth of the WUI into fire prone ecosystems, dangerous fuel conditions from decades of fire suppression, and a potentially increasing effect from prolonged drought and climate change. Fuel treatments are often considered the primary pre-fire mechanism to reduce the exposure of values at risk to wildland fire, and a growing suite of fire models and tools are employed to prioritize where treatments could mitigate wildland fire damages. Assessments using the likelihood and consequence of fire are critical because funds are insufficient to reduce risk on all lands needing treatment, therefore prioritization is required to maximize the effectiveness of fuel treatment budgets. Cost-effectiveness, doing the most good per dollar, would seem to be an important fuel treatment metric, yet studies or plans that prioritize fuel treatments using costs or cost-effectiveness measures are absent from the literature. Therefore, to explore the effect of using costs in fuel treatment planning we test four prioritization algorithms designed to reduce risk in a case study examining fuel treatments on the Sisters Ranger District of central Oregon. For benefits we model sediment retention and standing biomass, and measure the effectiveness of each algorithm by comparing the differences among treatment and no treat alternative scenarios. Our objective is to maximize the averted loss of net benefits subject to a representative fuel treatment budget. We model costs across the study landscape using the My Fuel Treatment Planner software, tree list data, local mill prices, and GIS-measured site characteristics. We use fire simulations to generate burn probabilities, and estimate fire intensity as conditional flame length at each pixel. Two prioritization algorithms target treatments based on cost-effectiveness and show improvements over those that use only benefits. Variations across the heterogeneous surfaces of costs and benefits create opportunities for fuel treatments to maximize the expected averted loss of benefits. By targeting these opportunities we demonstrate how incorporating costs in fuel treatment prioritization can improve the outcome of fuel treatment planning.