Conceptualizing a probabilistic risk and loss assessment framework for wildfires

Negar Elhami-Khorasani (), Hamed Ebrahimian, Lawrence Buja, Susan L. Cutter, Branko Kosovic, Neil Lareau, Brian J. Meacham, Eric Rowell, Ertugrul Taciroglu, Matthew P. Thompson and Adam C. Watts
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Negar Elhami-Khorasani: University at Buffalo
Hamed Ebrahimian: University of Nevada
Lawrence Buja: University of Nevada
Susan L. Cutter: University of South Carolina
Branko Kosovic: National Center for Atmospheric Research
Neil Lareau: University of Nevada
Brian J. Meacham: Meacham Associates
Eric Rowell: Desert Research Institute
Ertugrul Taciroglu: University of California
Matthew P. Thompson: USDA Forest Service, Rocky Mountain Research Station
Adam C. Watts: USDA Forest Service, Pacific Wildland Fire Sciences Laboratory

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 114, issue 2, No 4, 1153-1169

Abstract: Abstract Wildfires are an essential part of a healthy ecosystem, yet the expansion of the wildland-urban interface, combined with climatic changes and other anthropogenic activities, have led to the rise of wildfire hazards in the past few decades. Managing future wildfires and their multi-dimensional impacts requires moving from traditional reactive response to deploying proactive policies, strategies, and interventional programs to reduce wildfire risk to wildland-urban interface communities. Existing risk assessment frameworks lack a unified analytical method that properly captures uncertainties and the impact of decisions across social, ecological, and technical systems, hindering effective decision-making related to risk reduction investments. In this paper, a conceptual probabilistic wildfire risk assessment framework that propagates modeling uncertainties is presented. The framework characterizes the dynamic risk through spatial probability density functions of loss, where loss can include different decision variables, such as physical, social, economic, environmental, and health impacts, depending on the stakeholder needs and jurisdiction. The proposed approach consists of a computational framework to propagate and integrate uncertainties in the fire scenarios, propagation of fire in the wildland and urban areas, damage, and loss analyses. Elements of this framework that require further research are identified, and the complexity in characterizing wildfire losses and the need for an analytical-deliberative process to include the perspectives of the spectrum of stakeholders are discussed.

Keywords: Wildfire; Damage; Loss; Spatial probability density function; Performance-based approach (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-022-05472-y

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