A simulation model of the growth and suppression of large forest fires in Ontario

Abstract

Most of the area burned by forest fires in Canada is due to the few fires that escape initial attack and become large. We developed a discrete event simulation model of the growth and suppression of large fires in the province of Ontario. Based on fire, weather and suppression data from the Ontario Ministry of Natural Resources, our model includes a logistic regression component to predict the probability that a fire will escape initial attack and burn more than 100 ha, a component that simulates the growth of large fires based on weather and forest vegetation, and a component that simulates fire suppression by firefighters and aircraft. We used our model to predict area burned under mild and severe weather with varying levels of fire suppression resources. We found that, although severe weather limits fire suppression effectiveness, suppression has a significant effect on area burned even during severe fire seasons.