Journal of Probability and Statistics
Volume 2010 (2010), Article ID 823018, 26 pages
doi:10.1155/2010/823018
Research Article

Forest Fire Risk Assessment: An Illustrative Example from Ontario, Canada

W. John Braun,1 Bruce L. Jones,1 Jonathan S. W. Lee,1 Douglas G. Woolford,2 and B. Mike Wotton3

1Department of Statistical and Actuarial Sciences, The University of Western Ontario, London, Ontario, ON, N6A 5B7, Canada
2Department of Mathematics, Wilfrid Laurier University, Waterloo, ON, N2L 3C5, Canada
3Faculty of Forestry, The University of Toronto, Toronto, ON, M5S 3B3, Canada

Received 2 October 2009; Revised 6 March 2010; Accepted 27 April 2010

Academic Editor: Ricardas Zitikis

Copyright © 2010 W. John Braun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents an analysis of ignition and burn risk due to wildfire in a region of Ontario, Canada using a methodology which is applicable to the entire boreal forest region. A generalized additive model was employed to obtain ignition risk probabilities and a burn probability map using only historic ignition and fire area data. Constructing fire shapes according to an accurate physical model for fire spread, using a fuel map and realistic weather scenarios is possible with the Prometheus fire growth simulation model. Thus, we applied the Burn-P3 implementation of Prometheus to construct a more accurate burn probability map. The fuel map for the study region was verified and corrected. Burn-P3 simulations were run under the settings (related to weather) recommended in the software documentation and were found to be fairly robust to errors in the fuel map, but simulated fire sizes were substantially larger than those observed in the historic record. By adjusting the input parameters to reflect suppression effects, we obtained a model which gives more appropriate fire sizes. The resulting burn probability map suggests that risk of fire in the study area is much lower than what is predicted by Burn-P3 under its recommended settings.