Large Wildfires and Wildfire Costs: How Much and Why? Chairs

A quantitative tool was developed to predict USDA Forest Service fire suppression expenditures by fiscal year on the basis of fire activity data (i.e., number of fires and acres burned) from Incident Management Situation Reports. Regional regression models were developed with adjusted rsquares ranging from 0.696 to 0.969. National predictions result from aggregating regional predictions. Predictions are made monthly during the fire season, starting in June. Subsequent predictions reflect actual, past expenditure information and the level of fire activity likely to occur in the remaining months of the fiscal year. This tool was used by Fire and Aviation Management to predict fire suppression expenditures for fiscal year 1998. Since fiscal year (FY) 1970, fire suppression has accounted for more than half of all USDA Forest Service (FS) fire-related expenditures (Schuster and others 1997). Generally, appropriated and emergency suppression funds are enough to support fire suppression activities; however, when extraordinary fire seasons occur, funds held in reserve for other purposes (such as Knutson-Vandenberg Funds) must be borrowed to pay the extra costs. Concern has been expressed in recent years that fire suppression expenditures have been increasing, making it even more difficult to appropriate an adequate amount of suppression funds. As part of the annual appropriation process, the FS provides Congress with an estimate of the amount of money that will be needed to suppress fires for the current fiscal year. Starting in June each year, Fire and Aviation Management (FAM) must provide the office of the Chief of the Forest Service and the Office of Management and Budget (OMB) with monthly, up-to-date predictions of total FY fire suppression expenditures. Because it is unknown what the upcoming fire season will entail, predicting expenditures is a difficult task, subject to error. Simply averaging the expenditures from previous years may be too general for an acceptable prediction. On the other hand, a detailed, accounting-based prediction may be far too complicated and time consuming. Another approach might be to increase predictions of fire suppression expenditures by some factor, say 20 percent. However, how does one decide upon the appropriate adjustment? Should it be 10 percent, 20 percent, or 30 percent? In a year as extreme as FY 1994, with fire suppression expenditures of $685 million, one would have needed to add a factor of 218 percent to the 1990-94 average of $215 million to arrive at an accurate prediction. In an attempt to improve their predictions, FAM requested the development of a tool for predicting fire suppression expenditures. This study developed a quantitative tool for predicting annual, fire suppression expenditures that can be updated every month, starting in June, making use of available fire information and yearto-date expenditure information.