A Temporal Framework of Large Wildfire Suppression in Practice, a Qualitative Descriptive Study

Thompson

et al. 2020

Forests

Research Highlights: Our results suggest that weather is a primary driver of resource orders over the course of extended attack efforts on large fires. Incident Management Teams (IMTs) synthesize information about weather, fuels, and order resources based on expected fire growth rather than simply reacting to observed fire growth. Background and Objectives: Weather conditions are a well-known determinant of fire behavior and are likely to become more erratic under climate change. Yet, there is little empirical evidence demonstrating how IMTs respond to observed or expected weather conditions. An understanding of weather-driven resource ordering patterns may aid in resource prepositioning as well as forecasting suppression costs. Our primary objective is to understand how changing weather conditions influence resource ordering patterns. Our secondary objective is to test how an additional risk factor, evacuation, as well as a constructed risk metric combining fire growth and evacuation, influences resource ordering. Materials and Methods: We compile a novel dataset on over 1100 wildfires in the western US from 2007–2013, integrating data on resource requests, detailed weather conditions, fuel and landscape characteristics, values at risk, fire behavior, and IMT expectations about future fire behavior and values at risk. We develop a two-step regression framework to investigate the extent to which IMTs respond to realized or expected weather-driven fire behavior and risks. Results: We find that IMTs’ expectations about future fire growth are influenced by observed weather and that these expectations influence resource ordering patterns. IMTs order nearly twice as many resources when weather conditions are expected to drive growth events in the near future. However, we find little evidence that our other risk metrics influence resource ordering behavior (all else being equal). Conclusion: Our analysis shows that incident management teams are generally forward-looking and respond to expected rather than recently observed weather-driven fire behavior. These results may have important implications for forecasting resource needs and costs in a changing climate.

Section: Discussionsupporting

confidence: 92%

Weather, Risk, and Resource Orders on Large Wildland Fires in the Western US

Bayham

Thompson

et al. 2020

Forests

“…Second, in order to improve efficiency of resource use, we must first be able to describe our response. Yet our currently limited understanding of both resource use and suppression effectiveness [48,49] challenges the utility of this management action. Further, resource movement and prepositioning is an important consideration for efficiency questions.…”

Section: Resultsmentioning

confidence: 99%

Fire Suppression Resource Scarcity: Current Metrics and Future Performance Indicators

Stonesifer

Calkin

2020

Forests

Wildland fire occurrence is highly variable in time and space, and in the United States where total area burned can vary substantially, acquiring resources (firefighters, engines, aircraft, etc.) to respond to fire demand is an important consideration. To determine the composition and scale of this set of suppression resources managers may utilize data produced by past supply and demand information. The key challenge with this approach is that there is currently no clear system of record to track suppression resource supply and demand, and there are potential pitfalls within existing systems that may provide misleading information regarding the true levels of resource scarcity. In this manuscript, we investigate the issue of resource scarcity by examining two key resources that operations personnel have identified as both high value and scarce: type 1 firefighting crews and large airtankers. We examine data from the Resource Ordering and Status System and analyze the level of resource scarcity indicated by these data over the 2014-2018 fire seasons. We focus on data metrics with potential utility for managers responsible for annual national-level decisions regarding crew and airtanker acquisition; some of these metrics are already used to inform such decisions. We examine the limitations of each metric and suggest new metrics that could more accurately reflect true resource use and scarcity. Such metrics could lead to a substantially improved decision-making process.Forests 2020, 11, 217 2 of 20 experiences at least one period of severe fire activity during which fire suppression resources are scarce, resulting in some unfilled requests for fire suppression support, e.g., [2].Balancing the demand for fire suppression resources with budgetary constraints is an ongoing Agency priority for the USFS [3,4]. Fire suppression resource use comprises a large portion of USFS fire suppression expenses, and rising fire expenditures associated with changes in wildfire occurrence and management issues continue to challenge the Agency [5]. Currently, USFS fire suppression expenditures (2.6 billion US Dollars in Fiscal Year 2018; see [6]) represent nearly two-thirds of the total Agency budget, up from 16% in 1995 [5]; this increase in fire expenditures has hindered other Agency priorities such as protection of watersheds and cultural resources, maintenance of current programs and infrastructure for a range of multiple uses, benefits, and ecosystem services provided by the National Forests, and other forestry research and technical assistance. A long-sought "fire funding fix" was approved by the US Congress in 2018 to address the negative effects of increasing wildland fire suppression expenditures on the Agency's non-fire programs. The Wildfire Suppression Funding and Forest Management Activities Act of the 2018 Omnibus Spending Bill stabilizes Agency spending across all programs, but it requires additional accountability and related efficiency metrics reporting on fire system performance in order to maintain lawmaker support ...

“…Engines and dozers may also be suitable for different road conditions and raise different environmental concerns. Another future research direction could include extending the ARA analyses to study resource ordering and assignment patterns under different fire situations, i.e., for different fire size classes, durations, incident management team types, fire suppression stages (as suggested by [23]), etc.…”

Section: Resultsmentioning

confidence: 99%

“…Figures A1 and A2 in Appendix A also show very different daily resource ordering and assignment patterns between RMC and SWC. Different resources may play different roles at different stages of fire suppression [23]. For example, crews are often assigned to build firelines, conduct mop up, develop contingency lines, and prepare for burnout and point protection [8].…”

Section: Suppression Resource Categories and Collaborationsmentioning

confidence: 99%

Understand Daily Fire Suppression Resource Ordering and Assignment Patterns by Unsupervised Learning

Wei

Thompson

et al. 2020

MAKE

Wildland fire management agencies are responsible for assigning suppression resources to control fire spread and mitigate fire risks. This study implements a principle component analysis and an association rule analysis to study wildland fire response resource requests from 2016 to 2018 in the western US to identify daily resource ordering and assignment patterns for large fire incidents. Unsupervised learning can identify patterns in the assignment of individual resources or pairs of resources. Three national Geographic Area Coordination Centers (GACCs) are studied, including California (CA), Rocky Mountain (RMC), and Southwest (SWC) at both high and low suppression preparedness levels (PLs). Substantial differences are found in resource ordering and assignment between GACCs. For example, in comparison with RMC and SWC, CA generally orders and dispatches more resources to a fire per day; CA also likely orders and assigns multiple resource types in combination. Resources are more likely assigned to a fire at higher PLs in all GACCs. This study also suggests several future research directions including studying the causal relations behind different resource ordering and assignment patterns in different regions.