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Conceptualizing a probabilistic risk and loss assessment framework for wildfires

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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.

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Funding

This work was supported through the National Science Foundation's Leading Engineering for America's Prosperity, Health, and Infrastructure (LEAP HI) program by grant number CMMI-1953333 and the division of Engineering Education and Centers (EEC) program by planning grant number 2124455. Opinions and perspectives expressed in this study are those of the authors and do not necessarily reflect the sponsor's views. Also, this research was supported by the US Department of Agriculture, Forest Service. The findings and conclusions in this report are those of the author(s) and should not be construed to represent any official USDA or US Government determination or policy. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US government.

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Authors and Affiliations

  1. University at Buffalo, Buffalo, USA

    Negar Elhami-Khorasani

  2. University of Nevada, Reno, USA

    Hamed Ebrahimian & Neil Lareau

  3. University of Nevada, Reno, USA

    Lawrence Buja

  4. University of South Carolina, Columbia, USA

    Susan L. Cutter

  5. Weather Systems and Assessment Program, National Center for Atmospheric Research, Boulder, USA

    Branko Kosovic

  6. Meacham Associates, Shrewsbury, USA

    Brian J. Meacham

  7. Desert Research Institute, Reno, USA

    Eric Rowell

  8. University of California, Los Angeles, USA

    Ertugrul Taciroglu

  9. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, USA

    Matthew P. Thompson

  10. USDA Forest Service, Pacific Wildland Fire Sciences Laboratory, Seattle, WA, USA

    Adam C. Watts

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  1. Negar Elhami-Khorasani
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Elhami-Khorasani, N., Ebrahimian, H., Buja, L. et al. Conceptualizing a probabilistic risk and loss assessment framework for wildfires. Nat Hazards 114, 1153–1169 (2022). https://doi.org/10.1007/s11069-022-05472-y

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