Spatial Wildfire Risk Assessment

How is fire likely to affect the most important human assets and natural resources on a landscape?  

The spatial wildfire risk assessment uses four key components: probability, intensity, susceptibility, and relative importance to determine the risk of wildfire to important values. Wildfire ignition, spread, and intensity are simulated using the advanced FSIM modeling platform that runs thousands of iterations of a fire season using a distribution of local weather and fuel conditions. Once we have an understanding of fire likelihood and relative intensity, we turn to local experts and scientific literature to determine how each of the highly valued resources and assets (HVRAs) on a forest are likely to respond to the range of possible fire intensities. This effects-analysis allows the forest to incorporate both the positive and negative outcomes from fire exposure given the most likely fire intensity conditions. Finally, we work with agency line officers and our partners to prioritize the relative importance of HVRAs relative to each other.

By combining all four components we can begin to prioritize fuel treatments and other mitigation actions depending on the relative likelihood of fire exposure. For example, on a fire-adapted ponderosa pine forest with high fire probability and low fire intensity, fires tend to be a net benefit to ecosystems, wildlife, and watersheds. If these are the primary HVRAs in this area, then the net outcome from fire exposure would most likely be positive. Conversely, in areas with sensitive infrastructure such as the wildland-urban interface of southern California, where chaparral ecosystems have high burn probabilities and high fire intensities, fires tend to have very negative outcomes on HVRAs. The potential hazards and benefits of fire are weighted based on landscape management priorities to produce a map of wildfire risk that accounts for both human and natural resource values. The map of wildfire risk can be used to prioritize hazardous fuel treatments, determine candidate landscapes for fire restoration, and to engage landscape partners to help plan for fires.

Suppression Difficulty Index

Firefighting is an inherently hazardous occupation and responder safety is the primary concern on all incidents. Researchers from the Wildfire Risk Management Science Team are collaborating with fire scientists in Spain and Oregon State University as well as wildfire operations specialists to develop and apply spatial tools that weigh the potential hazards of fire against our ability to position people and resources where they are likely to be effective.   

This Suppression Difficulty Index (SDI) provides a spatial summary of “watch out” situations as well as areas with reduced risk to fire responders that can be used to facilitate strategic and tactical fire management decisions. While much of this information is intuitive to firefighters on the ground, the spatial overlay can also be used to help with strategic decision making.

Suppression Difficulty Index is part of the potential control locations model but can also be used as a stand-alone product. During incident support, Suppression Difficulty Index can be produced in real-time using spot weather forecasts to identify dynamic changes to fire responder exposure.

The current generation of Suppression Difficulty Index does not directly address snag hazards or smoke and heat exposure, however, researchers are currently working on ways to integrate these additional hazards into the index.

Wildfire Suppression Difficulty Index (terrestrial) (SDIt) is a quantitative rating of relative difficulty in performing fire control work. In its original formulation for use in Spain, Suppression Difficulty Index included aerial resource use, however for development and application in the United States we removed the aerial resource component due to a lack of consistent data. We note this distinction of “terrestrial only” calculations with the inclusion of “t” in the acronym. SDIt factors in topography, fuels, expected fire behavior under severe fire weather conditions, firefighter line production rates in various fuel types, and accessibility (distance from roads/trails) to assess relative suppression effort. For this dataset severe fire behavior is modeled with 15 mph up-slope winds and fully cured fuels. Suppression Difficulty Index has a continuous value distribution from 1-10. Here it is binned to six classes from lowest to highest difficulty.

The Risk Management Assessment (RMA) dashboard map viewer displays the most recent Suppression Difficulty Index version in use. Earlier versions of tSDI are available from the RMA team upon request.

Atlas of Potential Control Locations

Two big questions drive the operational decisions of fire management teams. 

1. Where are the best available opportunities to engage a fire when containment is the strategy?
2. Where are the places where fire is likely to continue burning regardless of what management actions are taken? 

Researchers with the Wildfire Risk Management Science Team are helping both incident response teams and fire planners answer these questions by turning to analytics to understand where and under what conditions fires have been successfully contained in the past, and conversely where containment efforts have failed.

Building models from these data allows researchers to produce near real-time predictions of the best and worst locations for engaging fire during active fire management operations, and to develop spatial planning tools that integrate fire into land and resource management.

By building the model off of historical fires that burned under similar conditions on the same landscape, researchers produce a customized product that identifies conditions where fires tend to spread or slow, and which factors are most important for successful containment.

Bringing It All Together in PODs: Risk, Opportunities, and Strategic Response

Working with local fire managers, the atlas of potential control locations can be further refined to a network of best available control features known as Potential Operational Delineations (PODs). PODs are spatial units or containers defined by potential control features, such as roads and ridge tops, within which relevant information on forest conditions, ecology, and fire potential can be summarized. The Wildfire Risk Management Science Team co-developed PODs to pre-plan for fire using a risk management approach, and to give land managers a formal process for developing landscape-scale wildfire response options before fires start. In areas where negative fire outcomes are likely, PODs should be as small as possible and may include control features that will need to be fortified prior to or during a fire. 

Overlaying the network of PODs onto the wildfire risk assessment results allows forest managers to summarize wildfire risk in a way that is operationally relevant. PODs can then be classified into strategic response zones based on the projected outcomes of exposure of prioritized forest resources and assets to fire. PODs with majority positive outcomes are classified as fire maintenance zones. PODs with majority negative outcomes are classified as fire protection zones. PODs with positive fire outcomes under moderate conditions and negative fire outcomes under more severe conditions are classified as fire restoration zones where the right kind of fire can help mitigate future hazards.

On the Tonto National Forest Strategic Response Zone map presented above, two additional zones were introduced to represent 1) vegetation types that burn only when invasive grass species are present; these are classified as excluding zones, and 2) zones of high complexity where control opportunities do not exist to separate parts of the POD with projected positive and negative outcomes from fire. In these PODs, hazardous fuel mitigation treatments could be combined with actions by private lands owners to mitigate negative fire outcomes and move toward more fire adapted communities and ecosystems.

This map serves as a means of tracking progress toward more fire adapted landscapes and as a tool for communicating the realities of fire management among forest staff and resource specialists, out-of-area fire teams, and with landscape partners.