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Analysis of Capacity and Funding Provides Insights to Wildfire Protection Planning

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Analysis of Capacity and Funding Provides Insights to Wildfire Protection Planning United States Department of Agriculture D E E P R A U R T LT MENT OF AGRICU Forest Service PNW Pacific Northwest Research Station InsiDE Best of Both Worlds............................................. 2 The Mathematics of Firefighting....................... 3 Doing More with Less....................................... 3 From Computer to Collaborators..................... 5 FINDINGS issue one hundred sixty four / august 2014 “Science affects the way we think together.” Lewis Thomas Efficient Initial Attacks: Analysis of Capacity and Funding Provides Insights to Wildfire Protection Planning IN SUMMARY Kari Greer Large wildfires in the United States pose significant challenges to fire management agencies charged with protecting lives, property, and natural resources. A vigorous initial response to a wildfire, a process referred to as “initial attack,” can greatly reduce the likelihood of the fire becoming larger and causing substantial damage. Successful initial attack depends on deploying the right number and kind of firefighting resources in a timely way. As people build homes where high-intensity wildfire is likely, they place greater strain on finite staffing and budgets. Fire planners have sought analytic guidance in designing an efficient initial attack system that minimizes both escaped fires and money spent on underutilized firefighting resources. Forest Service scientists and colleagues with Oregon State University developed a system that combines historical fire data and fire simulation programming with an optimization protocol to recommend the allocation of equipment and staff that will most effectively support initial attack Severe wildfires pose a greater threat to life and property as more people build homes in relatively and reduce escaped fires. remote locations. In an analysis of three fire units in the “Creativity is the ability be reduced to a mathematical equation. The central Sierra Nevada mountains of California, researchers discovered that to introduce order into the other had unshakeable faith that his field of expertise had something to contribute, and by consolidating equipment and staff randomness of nature.” trusted his friend’s intelligence and creativity into fewer stations strategically selected —Eric Hoffer to make the seemingly impossible happen. based on historical fire patterns, crews could effectively reach as many fires and aybe if the two Forest Service Together, Bob Haight and Jeremy Fried, who stop the occurrence of escaped fires at research foresters weren’t already first met three decades earlier on the the same level as if their initial attack M friends, they wouldn’t have been University of California-Berkeley campus, budgets had been increased by so persistent. created a program that optimizes the distribu- 25 percent. One thought his subject matter too complex, tion and placement of firefighting resources with too many variables and uncertainties, to that could potentially allow firefighters to reach more wildfires sooner with greater con- tainment success. For firefighting agencies KEY FINDINGS facing rapid growth of population, buildings, and infrastructure in places with relatively • A strategic-level model helps in allocating firefighting equipment and staff to effec- high likelihood of high-intensity wildfire, the tively support initial attacks and reduce escaped fires. This is useful for optimizing optimization program couldn’t have come at a response under current conditions or planning ahead for changes in funding or environ- better time. mental conditions. The inspiration to optimize wildland firefight- ing came from the urban environment, where • Consolidating firefighting resources among fewer fire stations reduced about the same many metropolitan fire departments seek to number of escaped fires as would a 25-percent increase in initial attack budgets without strategically place stations so firefighters can consolidation. This was for days on which several fires occurred. arrive on scene within 9 minutes of any call within city limits. • When the model wasn’t allowed to increase the capacities of stations, existing con- figurations of initial attack resources—designed by local and regional fire managers “But it’s not just about getting to more fires without any formal optimization—nearly matched the best solutions provided by the sooner,” says co-investigator Fried, a research optimization model. forester at the Pacific Northwest Research Station in Portland, Ore. “It’s also trying to make sure limited firefighting resources aren’t “Simulation is about trying to represent to improved fire management and because of assigned to locations where they’ll be under- reality,” Fried says. “Optimization tries to his confidence in Fried. utilized.” represent an abstraction of that reality math- “I’ve always had great respect for Jeremy. ematically to come up with the best answer.” To do that, Fried and Haight, a research for- He’s really hard-working and a creative ester at the Northern Research Station in St. The mathematical reduction of the problem problem-solver,” Haight says. “Optimization Paul, Minn., would combine two fields of necessary to make optimization possible is about identifying the key components of a study that at times appeared to be at odds with seemed incompatible with the wildfire sys- system, extracting them, and then building a one another. tem, and Fried had already witnessed multiple simulation around them. I knew Jeremy could unsuccessful attempts by economists and identify those components—or let me know if Haight first approached Fried on the project a operations research scientists to produce con- I was crazy to think it possible.” decade earlier, but it wasn’t an easy sell. Fried structive tools in this realm. spent part of his academic career studying The process wasn’t easy, and it was marked by wildfires and developing simulation models to “It’s such a complex system with a lot of mov- several failed attempts. But eventually Fried accurately predict fire suppression effective- ing parts and uncertainties, plus diverse tac- and Haight settled on the initial attack phase ness and efficiency. Meanwhile, Haight, who tics and objectives,” Fried says. “I just didn’t of wildfire suppression and focused their came from an economics background, special- think it lent itself to optimization.” efforts on the process necessary to minimize ized in optimizing systems or processes. the number of fires not contained by initial But Haight persisted, partly because of his attack (the 2-hour window after a fire report). conviction that optimization could contribute BEST OF BOTH WORLDS Purpose of PNW Science Findings aking the model work would draw Although simulation models are great for To provide scientific information to people who on both researchers’ areas of exploring the impacts of marginal changes make and influence decisions about managing to a system, they’re less ideal for identifying land. M expertise. optimal configurations from scratch. Haight, PNW Science Findings is published monthly by: Fried had already created a simulation pro- however, could use information from the Pacific Northwest Research Station gram that could predict the number of fires simulation model and apply it to a manage- USDA Forest Service not contained by initial attack. His California ment objective that serves as a proxy for P.O. Box 3890 Fire Economics Simulator (CFES2) accounted fires that exceed containment—specifically, Portland, Oregon 97208 for location-specific deployment policies, minimizing the number of fires not receiving Send new subscriptions and change of address firefighting equipment, tactics, fireline pro- a standard response (a situation-appropriate information to: duction rates, fire intensity, and fire velocity dispatch of firefighting resources) when a fire [email protected] using probabilistic parameters and functions. is reported—to guide decisionmaking. Rhonda Mazza, editor; [email protected] “Optimization contributes a lot of potential FIRE Cheryl Jennings, layout; [email protected] solutions to questions like: Where should CAL resources be located? In what allocations or Science Findings is online at: http://www. arrangements?” Fried says. “We take the best fs.fed.us/pnw/publications/scifi.shtml solutions from the optimization model and run To receive this publication electronically, them through the simulation model to see how change your delivery preference here: they would actually play out.” http://www.fs.fed.us/pnw/publications/subscription. The two-step process allowed Fried and shmtl Haight to compare the effectiveness of initial attack for alternative resource deployments, United States Forest Department Service Optimizing the distribution and placement of dispatching rules, and multi-agency collabora- of Agriculture firefighting resources allows firefighters to tion arrangements. reach more wildfires sooner with greater con- tainment success. 2 THE MATHEMATICS OF FIREFIGHTING ne defined objective for Fried and Haight’s model was to get the typi- O cally requested complement of fire- fighting resources, such as helicopters, fire engines, and bulldozers (“standard response”) to any fire within 30 or 60 minutes, depending on the resource type. The standard response varies by unit. For example, a unit with fewer roads might have more helicopters and fewer fire engines than a unit with more roads. The number of homes in need of protection and the terrain are other factors that influence a fire- fighting unit’s standard response to a wildfire.
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