Study Findings on Environmental Research Are Outlined in Reports from University of California San Diego (Stochastic Decision Trigger Modelling To Assess the Probability of Wildland Fire Impact)

2020 MAY 05 (NewsRx) -- By a News Reporter-Staff News Editor at Ecology Daily News -- Investigators discuss new findings in Environmental Research. According to news reporting out of La Jolla, California, by NewsRx editors, research stated, “The ability to estimate both the time and probability of a wildfire reaching an area to be protected is critically important to preventing loss of human life and property, and damage to ecological and economic assets. Wildfire decision trigger modelling has been used to assess fire exposure and create evacuation trigger buffers around the communities providing a specific amount of warning time.”

Financial supporters for this research include Ministerio de Economia y Competitividad, Technosylva USA, Research Executive Agency (European Commission), INSURANCE: OASIS INNOVATION HUB FOR CATASTROPHE AND CLIMATE EXTREMES RISK ASSESSMENT, Research Executive Agency (European Commission), HEIMDALL: MULTI-HAZARD COOPERATIVE MANAGEMENT TOOL FOR DATA EXCHANGE; RESPONSE PLANNING AND SCENARIO BUILDING.

Our news journalists obtained a quote from the research from the University of California San Diego, “This approach has been applied in multiple scenarios including household-level and community-level evacuation planning and during suppression operations. However, little attention has been paid to input data uncertainty using this modelling approach. This study presents an innovative stochastic fire simulation decision trigger modelling method that produces a probability map of the fire arrival to areas to be protected by simulating (n) wildfire decision trigger buffers with varied input data according to a potential range of deviations. The Tubbs fire (USA) was used as case study to show the applicability of this approach to estimate the probability of wildland fire impact. Our results highlighted the importance of considering input data uncertainty in operational environments to estimate fire progression and decision trigger buffers to better develop suppression tactic and strategy. The method presented may be solved in real-time and used with any empirical fire propagation model as a core engine.”

According to the news editors, the research concluded: “Practical real-time implications of this fire simulation mode are discussed.”

For more information on this research see: Stochastic Decision Trigger Modelling To Assess the Probability of Wildland Fire Impact. The Science of The Total Environment, 2019;694():. The Science of The Total Environment can be contacted at: Elsevier, Radarweg 29, 1043 Nx Amsterdam, Netherlands.

Our news journalists report that additional information may be obtained by contacting A. Cardil, University of California San Diego CALIT2 Qualcomm Inst, Technosylva, La Jolla, CA 92037, United States. Additional authors for this research include J. Ramirez, S. Monedero and C.A. Silva.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.scitotenv.2019.07.311. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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