A cellular automata model to link surface fires to firebrand lift-off and dispersal
Holly A. Perryman A E , Christopher J. Dugaw B , J. Morgan Varner C D and Diane L. Johnson B
+ Author Affiliations
- Author Affiliations
A Division of Marine Biology and Fisheries, Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, Miami, FL 33149, USA.
B Department of Mathematics, Humboldt State University, 1 Harpst Street, Arcata, CA 95521, USA.
C Wildland Fire Laboratory, Department of Forestry and Wildland Resources, Humboldt State University, 1 Harpst Street, Arcata, CA 95521, USA.
D Present address: Department of Forestry, Box 9681, Mississippi State, MS 39762, USA.
E Corresponding author. Email: hperryman@rsmas.miami.edu
International Journal of Wildland Fire 22(4) 428-439 https://doi.org/10.1071/WF11045
Submitted: 25 March 2011 Accepted: 10 August 2012 Published: 26 October 2012
Abstract
In spite of considerable effort to predict wildland fire behaviour, the effects of firebrand lift-off, the ignition of resulting spot fires and their effects on fire spread, remain poorly understood. We developed a cellular automata model integrating key mathematical models governing current fire spread models with a recently developed model that estimates firebrand landing patterns. Using our model we simulated a wildfire in an idealised Pinus ponderosa ecosystem. Varying values of wind speed, surface fuel loading, surface fuel moisture content and canopy base height, we investigated two scenarios: (i) the probability of a spot fire igniting beyond fuelbreaks of various widths and (ii) how spot fires directly affect the overall surface fire’s rate of spread. Results were averages across 2500 stochastic simulations. In both scenarios, canopy base height and surface fuel loading had a greater influence than wind speed and surface fuel moisture content. The expected rate of spread with spot fires occurring approached a constant value over time, which ranged between 6 and 931% higher than the predicted surface fire rate of spread. Incorporation of the role of spot fires in wildland fire spread should be an important thrust of future decision-support technologies.
Additional keywords: firebrands, fire-behaviour modelling, fuelbreaks, spot fires.
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