Abstract
Abstract The extreme cost of fighting wildland fires has brought fire suppression expenditures to the forefront of budgetary and policy debate in the United States. Inasmuch as large fires are responsible for the bulk of fire suppression expenditures, understanding fire characteristics that influence expenditures is important for both strategic fire planning and onsite fire management decisions. These characteristics then can be used to produce estimates of suppression expenditures for large wildland fires for use in wildland fire decision support or after-fire reviews. The primary objective of this research was to develop regression models that could be used to estimate expenditures on large wildland fires based on area burned, variables representing the fire environment, values at risk, resource availability, detection time, and National Forest System region. Variables having the largest influence on cost included fire intensity level, area burned, and total housing value within 20 mi of ignition. These equations were then used to predict suppression expenditures on a set of fiscal year 2005 Forest Service fires for the purpose of detecting “extreme” cost fires—those fires falling more than 1 or 2 SDs above or below their expected value.
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