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Open AccessArticle

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

1
Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, CO 80523, USA
2
Rocky Mountain Research Station, USDA Forest Service, Fort Collins, CO 80526, USA
3
Pyrologix, LLC, Missoula, MT 59801, USA
4
Rocky Mountain Research Station, USDA Forest Service, Missoula, MT 59801, USA
5
Department of Forest Engineering, Resources & Management, Oregon State University, Corvallis, OR 97331, USA
*
Author to whom correspondence should be addressed.
Forests 2019, 10(4), 311; https://doi.org/10.3390/f10040311
Received: 21 March 2019 / Revised: 29 March 2019 / Accepted: 3 April 2019 / Published: 5 April 2019
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. View Full-Text
Keywords: wildland fire management; probability; arrival time; mixed integer program; GIS; decision support; operations research wildland fire management; probability; arrival time; mixed integer program; GIS; decision support; operations research
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Wei, Y.; Thompson, M.P.; Scott, J.H.; O’Connor, C.D.; Dunn, C.J. Designing Operationally Relevant Daily Large Fire Containment Strategies Using Risk Assessment Results. Forests 2019, 10, 311.

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