Mapping wildfire hazard, vulnerability, and risk to Canadian communities

Erni, Sandy; Wang, Xianli; Swystun, Tom; Taylor, Stephen W.; Parisien, Marc-André; Robinne, François-Nicolas; Eddy, Brian; Oliver, Jackie; Armitage, Brad; Flannigan, Mike D.

doi:10.1016/j.ijdrr.2023.104221

Cited by 11 publications

(13 citation statements)

References 92 publications

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“…Parisien et al, 2005Parisien et al, , 2013, we retained days having high or extreme fire weather conditions, as defined by a FWI ≥19 (Podur & Wotton, 2010). A sequential list of fire weather days (FWI ≥19) was used in fire growth simulation for a specific fire, and the duration of fire burning was determined by a random draw from the historical fire burning duration distribution (for more details, please see Erni et al, 2023).…”

Section: National Fire Simulation Outputsmentioning

confidence: 99%

“…Outputs of the Burn P3 simulation model for Canadian forests (Erni et al, 2023) were used in this study. Specifically, we used the 250-m resolution grid-based FBP System variable ROS, the simulated fire perimeters (GIS polygons) and the ignition location of the simulated fire perimeters (coordinates).…”

Section: National Fire Simulation Outputsmentioning

confidence: 99%

“…(a) Median ROS for each 250 m-resolution pixel, with Canadian Ecozones (ESWG, 1996) overlaid. The Southern Arctic and Mixed Wood Plains were excluded from the study as they were not included in the BP3 modelling of forested areas (Erni et al, 2023). (b) Maximum ROS for each 250 m-resolution pixel.…”

Section: Community Boundariesmentioning

confidence: 99%

“…and climate change was not accounted for by the Burn P3 scenarios used in this study. Although suppression efforts are indirectly represented by using the fire size distribution in Burn P3 model calibrations(Erni et al, 2023;Parisien et al, 2013), any change in future fire management capacity or performance will not be accurately reflected in this study. Importantly, TA B L E 4 Mean distance (standard deviation; km) of fire fronts (d) to ecumene at 1-3 days based on the maximum rate of spread (ROS) by Ecozone accompanied by the mean coefficient of variation (CV) (standard deviation) over all communities within the Ecozone.…”

mentioning

confidence: 99%

“…Here, wildland fire risk is defined as the interaction between fire hazard (likelihood and intensity) and vulnerability (e.g. Erni et al, 2023) or between likelihood and impacts (e.g. Johnston et al, 2020;McFayden et al, 2019).…”

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confidence: 99%

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Mapping the distance between fire hazard and disaster for communities in Canadian forests

Wang,

Swystun,

McFayden

et al. 2024

Global Change Biology

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Communities interspersed throughout the Canadian wildland are threatened by fires that have become bigger and more frequent in some parts of the country in recent decades. Identifying the fireshed (source area) and pathways from which wildland fire may ignite and spread from the landscape to a community is crucial for risk‐reduction strategy and planning. We used outputs from a fire simulation model, including fire polygons and rate of spread, to map firesheds, fire pathways and corridors and spread distances for 1980 communities in the forested areas of Canada. We found fireshed sizes are larger in the north, where the mean distances between ecumene and fireshed perimeters were greater than 10 km. The Rayleigh Z test indicated that simulated fires around a large proportion of communities show significant directional trends, and these trends are stronger in the Boreal Plains and Shields than in the Rocky Mountain area. The average distance from which fire, when spreading at the maximum simulated rate, could reach the community perimeter was approximately 5, 12 and 18 km in 1, 2 and 3 days, respectively. The average daily spread distances increased latitudinally, from south to north. Spread distances were the shortest in the Pacific Maritime, Atlantic Maritime and Boreal Plains Ecozones, implying lower rates of spread compared to the rest of the country. The fire corridors generated from random ignitions and from ignitions predicted from local fire history differ, indicating that factors other than fuel (e.g. fire weather, ignition pattern) play a significant role in determining the direction that fires burn into a community.

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Section: National Fire Simulation Outputsmentioning

confidence: 99%

Section: National Fire Simulation Outputsmentioning

confidence: 99%

Section: Community Boundariesmentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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