Examining dispatching practices for Interagency Hotshot Crews to reduce seasonal travel distance and manage fatigue

Belval, Erin J.; Calkin, David E.; Wei, Yu; Stonesifer, Crystal S.; Thompson, Matthew P.; Masarie, Alex Taylor

doi:10.1071/wf17163

Cited by 11 publications

(9 citation statements)

References 14 publications

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“…Further, resource movement and prepositioning is an important consideration for efficiency questions. A growing body of research has helped build a foundation of knowledge in this area (e.g., [17,18,[50][51][52]); however, there is still much to be learned for the wide variety of resource types and agencies at play in the national response arena. Finally, imposing restrictions on resource use in an interagency realm is fraught with challenges, particularly given different agency priorities with respect to fire management policy, values at risk, and relative appetite for beneficial fire opportunities.…”

Section: Discussionmentioning

confidence: 99%

Fire Suppression Resource Scarcity: Current Metrics and Future Performance Indicators

Belval

Stonesifer

Calkin

2020

Forests

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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 ...

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Section: Discussionmentioning

confidence: 99%

Fire Suppression Resource Scarcity: Current Metrics and Future Performance Indicators

Belval

Stonesifer

Calkin

2020

Forests

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“…The Resource Ordering and Status System (ROSS) is a database used in the US to track suppression resource requests, dispatching, and release for large fire incidents during each fire day [19]. ROSS has been broadly adopted for tracking interregional resource movements for large fire suppression since 2012 [1,20]. ROSS has also been used to study seasonal fire suppression requests [6], suppression resource productivity and effectiveness [8], and resource dispatching and transferring between fire management regions [21].…”

Section: Resource Ordering and Status System (Ross)mentioning

confidence: 99%

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

Wei

Thompson

Belval

et al. 2020

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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.

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“…Equations (15) and (16) simply make sure the rPOD selection and point protection location decisions from the first step model will be carried over to the second step model. The original Equations (12) and (13) from the first step model would still be included in the second step model. Equation (17) tracks the temporal gap for each selected rPOD boundary and sets the temporal gap for the other not selected POD boundaries to zero.…”

Section: Max Wmentioning

confidence: 99%

“…Operations research (OR) models can be used to help integrate fire data, suggest management strategies, and conduct tradeoff analysis to assist fire decision processes [3][4][5][6]. OR models developed for wildfire management can take many forms, ranging from pre-fire applications determining optimal investment portfolios in prevention/suppression activities along with optimal stationing and deployment rules for suppression resources [7][8][9][10][11][12], to post-fire applications determining optimal mitigation strategies for reducing debris flow risk [13].…”

Section: Introductionmentioning

confidence: 99%

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

Wei

Thompson

Scott³

et al. 2019

Forests

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In this study, we aim to advance the optimization of daily large fire containment strategies for ground-based suppression resources by leveraging fire risk assessment results commonly used by fire managers in the western USA. We begin from an existing decision framework that spatially overlays fire risk assessment results with pre-identified potential wildland fire operational delineations (PODs), and then clusters PODs into a response POD (rPOD) using a mixed integer program (MIP) model to minimize expected loss. We improve and expand upon this decision framework through enhanced fire modeling integration and refined analysis of probabilistic and time-sensitive information. Specifically, we expand the set of data inputs to include raster layers of simulated burn probability, flame length probability, fire arrival time, and expected net value change, all calculated using a common set of stochastic weather forecasts and landscape data. Furthermore, we develop a secondary optimization model that, for a given optimal rPOD, dictates the timing of fire line construction activities to ensure completion of containment line prior to fire arrival along specific rPOD edges. The set of management decisions considered includes assignment of PODs to be included in the rPOD, assignment of suppression resources to protect susceptible structures within the rPOD, and assignment of suppression resources to construct fire lines, on specific days, along the perimeter of the rPOD. We explore how fire manager risk preferences regarding firefighter safety affect optimal rPOD characteristics, and use a simple decision tree to display multiple solutions and support rapid assessment of alternatives. We base our test cases on the FSPro simulation of the 2017 Sliderock Fire that burned on the Lolo National Forest in Montana, USA. The overarching goal of this research is to generate operationally relevant decision support that can best balance the benefits and losses from wildfire and the cost from responding to wildfire.

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Examining dispatching practices for Interagency Hotshot Crews to reduce seasonal travel distance and manage fatigue

Cited by 11 publications

References 14 publications

Fire Suppression Resource Scarcity: Current Metrics and Future Performance Indicators

Fire Suppression Resource Scarcity: Current Metrics and Future Performance Indicators

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

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

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