A method to produce a flexible and customized fuel models dataset

IntroductionIn Portugal, the 2017 fire season was particularly extreme, leading to an unprecedented large number of fatalities, injured people, destruction of houses and infrastructures. These dramatic outcomes have contributed to raise awareness regarding the importance of ensuring the safety of people and assets from high intensity uncontrollable wildfires. It is crucial to identify the settlements at higher risk and the most suitable mitigation actions that can maximize the protection of people and assets.MethodsWe developed a simple methodology that combines exposure and vulnerability to estimate wildfire risk at the local level. Exposure was estimated using a fire spread simulation approach that was used to determine the probability of (i) a wildfire generating firebrands that could affect a settlement and (ii) a high intensity wildfire occurring adjacent to a settlement. Exposure was estimated using two fuel scenarios created to represent the current year of 2023 (short-term scenario) and 2030, assuming that no fuel management nor large fires occur in the meantime (medium-term worst-case scenario). Vulnerability was determined by the (i) Index of Total Dependence (IDT), and (ii) evacuation difficulty. Exposure and vulnerability metrics were normalized in percentiles, distributed into quadrants and combined to provide six levels of wildfire risk. For each vulnerability\exposure combination, we proposed a set of priority mitigation actions. The methodology was applied to three areas in Portugal where the risk estimates were analyzed and compared with the implementation rate of two risk mitigation programs already in place.ResultsResults showed that 8.7% of the settlements had “very high” wildfire risk and about 19.5% had “high” wildfire risk, potentially affecting 8,403 and 34,762 inhabitants, respectively. The spatial distribution of settlements at higher risk was very heterogeneous across the study areas and the total fraction ranged between 14% in Coimbra to 36% in Barlavento Algarvio. The overall implementation of mitigation programs in the study areas is very low, with only around 1% of the settlements in “very high” risk having any of the mitigation programs implemented. Conversely, our results also suggest that the implementation rate in settlements classified in lower risk classes is disproportionately high.DiscussionThe application of this risk analysis methodology can be used to assess the implementation status of mitigation actions, and contribute to tailor the actions that maximize the protection of people and assets according to the specific conditions found in each targeted area.

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The Mathematical Model Based on the Parameters of Simulation Results Predicts the Fire Extinguishing Resource Demand of Naval Fires

Guo,

Zhang,

Zhao

et al. 2024

Applied Sciences

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In recent years, due to the diversity of fire scenes in ports and ships, the problem of fire command is complicated. In the case of power failure, the original command platform and fire extinguishing system will not be able to be used normally, or the fire extinguishing resources carried by the ship when it is on fire cannot be used. In the traditional firefighting ability research, there is no clear measure of firefighting ability, resulting in inaccurate calculation results. By corresponding to the quantity and composition of resources for the study of fire extinguishing capability, the combination of the fire dynamics simulation software PyroSim2020 and a calculation model that converts its resources into the total amount and flow of fire extinguishing agent can be provided. Based on the analytic hierarchy process (AHP), a firefighting demand grade calculation and judgment model was established, which included five factors: fire scale, combustion material characteristics, foam extinguishing agent performance, firefighting object characteristics, and external factors. It concluded that the demand assignment values of each index element were 2, 5, 6, 9, and 10, and further proposed the grade judgment criteria for the calculation results of comprehensive fire demand. Through the quantitative simulation of firefighting demand based on the fire scenario and calculation model test of the consumption prediction of cooperative firefighting equipment, it can also provide a strategic reference for related cooperative fire rescue.

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A method to produce a flexible and customized fuel models dataset

Cited by 3 publications

References 41 publications

Developing customized fuel models for shrub and bracken communities in Galicia (NW Spain)

Developing customized fuel models for shrub and bracken communities in Galicia (NW Spain)

Defining priorities for wildfire mitigation actions at the local scale: insights from a novel risk analysis method applied in Portugal

The Mathematical Model Based on the Parameters of Simulation Results Predicts the Fire Extinguishing Resource Demand of Naval Fires

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