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Modelling suppression difficulty: current and future applications

Rodríguez y Silva, Francisco, O’Connor, Christopher D., Thompson, Matthew P., Molina Martínez, Juan Ramón, Calkin, David E.·2020·International Journal of Wildland Fire
DOI 10.1071/wf19042
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Abstract

Improving decision processes and the informational basis upon which decisions are made in pursuit of safer and more effective fire response have become key priorities of the fire research community. One area of emphasis is bridging the gap between fire researchers and managers through development of application-focused, operationally relevant decision support tools. In this paper we focus on a family of such tools designed to characterise the difficulty of suppression operations by weighing suppression challenges against suppression opportunities. These tools integrate potential fire behaviour, vegetation cover types, topography, road and trail networks, existing fuel breaks and fireline production potential to map the operational effort necessary for fire suppression. We include case studies from two large fires in the USA and Spain to demonstrate model updates and improvements intended to better capture extreme fire behaviour and present results demonstrating successful fire containment where suppression difficulty index (SDI) values were low and containment only after a moderation of fire weather where SDI values were high. A basic aim of this work is reducing the uncertainty and increasing the efficiency of suppression operations through assessment of landscape conditions and incorporation of expert knowledge into planning.

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Crossref · 10.1071/wf19042

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  • Expert opinion is widely used in the development of comparable wildland fire spatial decision support datasets, such as GET v1 and the Suppression Difficulty Index.

    “It is widely used in the development of comparable wildland fire spatial decision support datasets, such as GET v1 and the Suppression Difficulty Index [22,23].”

    From Wildland firefighter estimated ground evacuation time modeling to support risk-informed decision-making (2024) · cites this paper as [22]

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Metadata

Authors
Rodríguez y Silva, F., O’Connor, C. D., Thompson, M. P., Molina Martínez, J. R., & Calkin, D. E.
Affiliations
  • ADepartment of Forest Engineering, Forest Fire Laboratory, University of Córdoba, Edificio Leonardo da Vinci, Campus de Rabanales, E-14071 Córdoba, Spain.
  • BUS Department of Agriculture Forest Service, Rocky Mountain Research Station, 800 East Beckwith Avenue, Missoula, MT 59801, USA.
  • CUS Department of Agriculture Forest Service, Rocky Mountain Research Station, 240 West Prospect Road, Fort Collins, CO 80526, USA.
Venue
International Journal of Wildland Fire
Publisher
CSIRO Publishing
Published
2020-05-05
Volume
29
Issue
8
Pages
739-751
ISSN
  • 1049-8001
  • 1448-5516
DOI
10.1071/wf19042
Cited by
39
References
6
Language
en
Licence
doi.org/10.1071/journalslicense (vor, 1826 d)

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