Treating Landscapes
Fuel treatments are always complex. Even if you get past the political controversies and litigation they tend to stir up, even larger questions emerge. How do we design fuel treatments to reduce fire risk while not conflicting with the management restrictions that are always layered across a forest? How do we know that the placement and design of a treatment will actually affect a potential fire? Will the treatment alone have any impact on landscape-level fires, which is the main concern of fire managers?
Resources and opportunities for treating fuels are scarce, so land managers always want to find the best bang for the buck when they finally get the chance to put treatments on the ground. Until recently, the tools just didn't exist to answer such questions absolutely. However, new wildfire simulation models are making land managers' jobs much easier. These powerful tools have quickly become integrated into incident management through the Wildland Fire Decision Support System, or WFDSS, and are now changing fuels management planning at the project and forest level.
Researchers have played a key role in the development of these tools. Mark Finney of the Missoula Fire Lab has developed much of the fire behavior models that underlie these systems, but other researchers have added important components to these new risk assessment frameworks. Dave Calkins, an economist with the Rocky Mountain Research Station, developed the Rapid Assessment of Values At Risk (RAVAR) program to integrate with Finney's WFDSS burn probability mapping. RAVAR is an economic model that provides dollar estimates of values — structures, infrastructure and more — threatened by a fire, as well as assessments of non-monetary values such as critical habitat. In addition, Alan Ager, an operations research analyst at the Western Wildland Environmental Threat Assessment Center, has been working on the ArcFuels program for integrating the proliferation of vegetation and fire behavior models into one GIS framework for fuels project planning purposes.
Other researchers are using risk analysis to examine how wildfire might affect forest restoration goals and to create guidelines for fire-resilient forest composition and structure. The new tools also are being used to look at potential negative wildfire effects such as smoke emissions, soil heating, duff consumption and hydrologic effects. Economic impact also is a major component, weighing financial values such as treatment costs, potential timber revenues and projected changes to future wildfire suppression cost from fuels projects.
Today, fuel planners use computer models that can predict post-treatment fire behavior over large landscapes.
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In the past, we might know that a highintensity fire in a ponderosa pine forest would be bad, but we had no idea of the chance that it would occur. Maybe it was so rare that there was no reason to worry.
"We didn't know how much investment was needed to reduce the probability of occurrence or to change the susceptibility part of the equation," Finney says. "If the chances of a fire affecting something are low, why spend millions of dollars in mitigating a level of risk that doesn't justify the investment?"
The real breakthrough in the application of risk analysis to wildfire came with Finney's development of the minimum travel time fire-spread algorithm. The MTT calculation is an important simplification of a fire's complexity that makes it feasible to simulate thousands of fires and generate burn probability maps over large areas (10,000 — 2 million hectares). The new models create robust fire spread probabilities weeks out from a given ignition or fire location using weather data from remote automated weather stations and recent problem fires. Finney had the insight to model fires based on the big blow-up events that account for almost all fire growth.
"It is bloody practical," Finney says. "You can look at a fire as something very complex — winds blow and then stop, weather fronts move in, etc., but we have known for more than 100 years that most of the fire growth occurs on just a few days. So MTT uses data from old fires in the areas to see which conditions really push it."
This is the basis of new, more powerful fire modeling systems such as FSPro, as well as decision support systems such as WFDSS — new tools that allow the user to look at the likelihood that a given piece of land will be affected by a fire and then assess what there is of value and what the likely loss will be.
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