Modeling Fuel Treatment Leverage: Encounter Rates, Risk Reduction, and Suppression Cost Impacts

Abstract

Abstract:The primary theme of this study is the cost-effectiveness of fuel treatments at multiple scales of investment. We focused on the nexus of fuel management and suppression response planning, designing spatial fuel treatment strategies to incorporate landscape features that provide control opportunities that are relevant to fire operations. Our analysis explored the frequency and magnitude of fire-treatment encounters, which are critical determinants of treatment efficacy. Additionally, we examined avoided area burned, avoided suppression costs, and avoided damages, and combined all three under the umbrella of leverage to explore multiple dimensions with which to characterize return on investment. We chose the Sierra National Forest, California, USA, as our study site, due to previous work providing relevant data and analytical products, and because it has the potential for large, long-duration fires and corresponding potential for high suppression expenditures. Modeling results generally confirmed that fire-treatment encounters are rare, such that median suppression cost savings are zero, but in extreme years, savings can more than offset upfront investments. Further, reductions in risk can expand areas where moderated suppression response would be appropriate, and these areas can be mapped in relation to fire control opportunities.

A Model-Based Framework to Evaluate Alternative Wildfire Suppression Strategies

“…Indeed, moderate rather than low severity fire may be needed to restore stand structure, with patches of high-severity fire needed to restore landscape heterogeneity [94,95]. In addition, strategically-placed fuel treatments have the potential to reduce risk to highly valued resources from future fires and could facilitate the return of fire on this landscape [96]. Whether fire managers are interested in utilizing alternative suppression approaches in pursuit of ecological goals, enhanced fire responder safety, exploring temporal feedbacks, or other concerns, we believe the general approach presented here could have broad global applicability.…”

“…While this work demonstrates the potential to leverage managed lightning fires as a restoration tool, many questions remain about where and when such fires would be likely to meet ecological goals in terms of acreage burned, fire severity and effect on highly valued resources. Because stand structure in the U.S. West has changed as a result of fire suppression and timber harvest, restoration of stands via prescribed burning perhaps accompanied by mechanical fuel treatment where feasible may be warranted [96]; however, recent observations indicate that fire alone may be sufficient to restore stands to a desirable structure over the long term, though this may require more than one fire [91,95,98]. Fire severity in the Sierra Nevada is strongly influenced by relative humidity and time since fire, among other factors, suggesting that choices about when and where to utilize managed lightning fires may depend on both weather and location [99].…”

“…Next steps include integrating fire model outputs with additional data and models to estimate consequences to the wildland-urban interface, forest resources, and suppression budgets. Planned modeling work also includes merging response strategies with landscape fuel treatment strategies [30,96] to explore whether expanding the footprint of fuel treatments expands opportunities for more managed fire.…”

Designing Operationally Relevant Daily Large Fire Containment Strategies Using Risk Assessment Results

“…PODs can be built using a combination of geospatial analysis and local expert knowledge, often with supporting analytical products identifying suppression opportunities and potential control locations (PCLs) [24,25]. PODs have been used to summarize suppression difficulty and protection demand [26], to optimize fuel treatment placement across a landscape [27], and, most relevant for our purposes, to optimize creation of clustered, or aggregated, response PODs (rPODs) for real-time incident support [28]. It is worth emphasizing that PODs are more than an academic concept; locally developed PODs were used for real-time decision support during the 2017 fire season on the Tonto National Forest in Arizona, USA [22,28,29], and analytical products serving as the building blocks of PODs [23,24] were delivered for real-time decision support Forests 2019, 10, 311 3 of 23 for fifteen large fires across the western USA during the 2017 fire season [Risk Management Assistance Teams (RMAT) website, https://wfmrda.nwcg.gov/RMAT.html].…”

“…As a basis we used a landscape-scale risk assessment framework that evaluates both the hazard (fire likelihood and intensity) and vulnerability (exposure and susceptibility) of HVRAs at every location (i.e., each grid cell) across a landscape [33,34]. The framework outlined in [35] is generalizable and scalable, such that risk assessment results can be used for a variety of purposes, including strategic budgeting, fuel treatment prioritization, and incident decision support [27,28,35,36]. In a pre-fire landscape-scale risk assessment, the fire likelihood and intensity estimates used to calculate expected net value change (eNVC) are commonly generated by a stochastic simulator such as FSim [37].…”