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Estimating the Cost of Predictive Services in Wildfire Equipment Allocation

 

Issue (Who cares and why?)
Predictive Services has evolved into a respected and widely-used resource for land management agencies, however, the program has never been able to associate an economic value on the products and services provided. This project will look at a single process where Predictive Services is thought to have an economic impact; providing decision support tools to aid in the pre-positioning of Initial Attack assets (e.g. Single Engine Airtankers (SEATs), heavy tankers, engines, smokejumpers, etc.). By focusing on this narrowly defined aspect, we hope to be able to place a value on decision support products of the Predictive Service program.

What has been done?
The University of Nevada, Reno investigation team selected the Western Great Basin as a case study. Members of the team input relevant data from historical records (weather, terrain, etc.) to a fire spread model that takes into account the effect of Initial Attack. A decision problem was developed to determine if a particular allocation of fire suppression resources is an efficient arrangement given a set of fire potential probabilities.

Impact
Given current budget restraints, it seems prudent to plan for a scarcity of suppression resources over many geographic areas. Given scarcity, it then becomes important to understand not only how fire managers decide to deploy Initial Attack resources but the value of the information upon which those decisions are made. Fire suppression models have long confirmed the notion that Initial Attack response times affect a wildfire's final size and overall suppression costs, but more importantly, the investigation team determined that knowledge of future fire conditions and acting on this knowledge significantly affects total dollars spent on fire suppression.

This study shows that optimal positioning is not just about being closer to areas of greater risk, but also about minimizing distances to all protection areas. Most importantly, within the context of the stylized landscape it was found that using Predictive Services’ 7 Day Outlook can reduce fire agency suppression costs by up to 35% if optimal positioning is implemented.

The information provided by this investigation are currently being used by US Forest Service and BLM land managers and Nevada Division of Forestry to preposition firefighting equipment and resources to reduce the time it takes to arrive at a fire.

CONTACT INFORMATION

Kimberly Rollins

Department of Center for Resource Economics

1664 North Virginia Street

Reno, Nevada   89557

 

Phone: (775) 784-1677

Email: krollins@unr.edu

Personal Web Site: http://www.unr.edu/business/research-and-outreach/core/esnr

 

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