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Forestry Sciences Lab
800 E. Beckwith Ave
Missoula, Montana 59801

(406) 542-4150

Stratified Cost Index (SCI)

Due to growing fire suppression costs and the lack of a quantifiable performance measure for suppression expenditures, Congress directed the Forest Service to develop, in collaboration with the Department of Interior, such a measure and began reporting in FY 2006.

The Stratified Cost Index (SCI) was developed by economists at the U.S Forest Service’s Rocky Mountain Research Station and subsequently adopted as a performance measure in FY 2006; the DOI has adopted SCI, but due to data gaps were not able to report in FY 2006. Using historical data, SCI calculated estimated suppression costs of large fires (>= 300 acres) with similar fire characteristics such as fuel types, fire intensity, topography, region, and values at risk. Actual expenditures on current and future large fires will be compared to their “projected” cost as calculated by the SCI.

SCI was modified for the WFDSS system and it's use is described below in the following briefing paper.  

U.S. Forest Service
Rocky Mountain Research Station RMRS-4853
Briefing Paper

Topic: Use of the Stratified Cost Index in WFDSS

Background: In FY 2006, the FS adopted a performance measure designated the “Stratified Cost Index” (SCI). In FY 2007, the SCI was also incorporated into the new wildland fire decision support system (WFDSS). The SCI is simply a set of regression equations developed to estimate suppression expenditures on individual large wildland fires (fires greater than 300 acres). That is, characteristics of the fire, such as fire size, the fire environment (slope, aspect, energy release component, fuel model, etc), housing values within proximity to the fire, and geographic area are used in a statistical model to come up with an estimate of the cost of the fire. Currently, there are three regression equations incorporated into WFDSS -- two Forest Service models (one for the western U.S. and one for the eastern U.S.) and one DOI model. These cost models are built using historic information on suppression expenditures and fire characteristics, using data for fires occurring in FYs 2004-2007 from all geographic areas. The independent variables (the fire characteristics used to predict cost) vary somewhat by model (FS west, FS east, DOI). The models also include a regional variable that accounts for differing costs across geographic areas (defined as either FS regions or Geographic Area Coordination Centers). The dependent variable (what we are trying to predict) in each of the models is suppression expenditures per acre, which includes expenditures by all federal agencies (FS and DOI) on the fire in question. It does not include state expenditures unless those expenditures are already captured in the federal accounting system. The FS regression models were developed using data on fires where the FS was the protection agency of record. Similarly, the DOI model was built using data on fires where one of the DOI agencies was the protection agency of record.

Use of SCI in WFDSS:
The SCI for a particular fire is calculated in the new WFDSS simply by entering the latitude and longitude of the fire start and estimated acreage burned for the alternative fire scenarios from the WFSA. From this, all of the independent variables (fire characteristics) in the model are calculated and entered into one of the three regression equations, depending upon which agency is the designated protection agency. The WFDSS system then calculates the SCI and provides a range of values with which to compare actual suppression expenditures (see example below).

The goal of the fire manager should be to keep costs at or below the 50 percent level in order to cut agency suppression expenditures. In this case, fires with similar characteristics, in terms of size, fuel models, housing values, etc., on average cost about $1,591 per acre. Keeping the actual fire costs at or below this level will contribute towards cost containment goals. If actual costs reach the yellow and red levels, this does not imply that the fire is being poorly managed. However, the probability that the fire will be reviewed after the fire season increases. In these instances, the use of FSPro and RAVAR may be helpful in determining if the fire poses higher risk than fires typical to these conditions, or if strategies should be revised to address identified cost concerns.

 

Contact: Krista Gebert, RMRS

 

Estimating Suppression Expenditures for Individual
Large Wildland Fires (WJAF, 2007)

 

Modeling Fuel Treatment Costs on Forest
Service Lands in the Western United States (WJAF, 2006)

 

 

Briefing Papers

Use of SCI in WFDSS

Calculating SCI for Fire Complexes within the WFDSS System

Use of SCI in WFDSS for Multi-Agency Incidents

 

 

 

USDA Forest Service - Rocky Mountain Research Station
Last Modified: Monday, 16 December 2013 at 14:18:31 CST


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