Canadian Forest Service Publications
Predicting the number of daily human-caused bushfires to assist suppression planning in south-west Western Australia. 2014. Plucinski, M.P.; McCaw, W.L.; Gould, J.S.; Wotton, B.M. International Journal of Wildland Fire 23: 520-531.
Year: 2014
Issued by: Great Lakes Forestry Centre
Catalog ID: 36579
Language: English
Availability: PDF (request by e-mail)
Available from the Journal's Web site. †
DOI: 10.1071/WFI3090
† This site may require a fee
Abstract
Data from bushfire incidents in south-west Western Australia from the Departments of Parks and Wildlife and Fire and Emergency Services were used to develop models that predict the number of human-caused bushfires within 10 management areas. Fire incident data were compiled with weather variables, binary classifications of day types (e.g. school days) and counts of the number of fires that occurred over recent days. Models were developed using negative binomial regression with a dataset covering 3 years and evaluated using data from an independent year. A common model form that included variables relating to fuel moisture content, the number of recent human-caused bushfires, work day (binary classification separating weekends and public holidays from other days) and rainfall was applied to all areas. The model had reasonable fit statistics across all management areas, but showed enough day-to-day prediction variability to be of practical use only in the more densely populated management areas, which were dominated by deliberate ignitions. The findings of this study should be of interest to fire managers in Mediterranean climatic regions where a variety of practices are used to manage wildfires.
Plain Language Summary
We used data from bushfire incidents in south-west Western Australia to develop models to predict the number of human-caused bushfires occurring daily. We used weather-based fuel moisture content estimates, day types (e.g. school days, holidays) and data about recent fires to create the model. We found that the model worked reasonably well to predict the incidence of fires, but showed enough day-to-day variability to be of practical use only in the more densely populated management areas, where deliberate ignitions occur. We expect the findings of this study to be of interest to fire managers in regions with Mediterranean-like climates, where fuels can be quite volatile and a variety of practices are used to manage wildfires.
