Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Efficient simulation of wildfire spread on an irregular grid

Paul Johnston A B , Joel Kelso A and George J. Milne A
+ Author Affiliations
- Author Affiliations

A School of Computer Science and Software Engineering, University of Western Australia, M002, 35 Stirling Highway, Crawley, WA 6009, Australia.

B Corresponding author. Email: paulj@csse.uwa.edu.au

International Journal of Wildland Fire 17(5) 614-627 https://doi.org/10.1071/WF06147
Submitted: 1 November 2006  Accepted: 17 March 2008   Published: 3 October 2008

Abstract

A cell-based wildfire simulator that uses an irregular grid is presented. Cell-based methods are simpler to implement than fire front propagation methods but have traditionally been plagued by fire shape distortion caused by the fire only being able to travel in certain directions. Using an irregular grid randomises the error introduced by the grid, so that the shape of simulated fire spread is independent of the direction of the wind with respect to the underlying grid. The cell-based fire spread simulator is implemented using discrete event simulation, which is a much more efficient computational method than conventional wildfire simulation techniques because computing resources are not used in repeatedly computing small updates to parts of the fire whose dynamics change infrequently, namely those areas of a fire that move slowly. The resulting simulator is comparable in accuracy with traditional fire front propagation schemes but is much faster and can therefore be used as an engine for fire simulation applications that require large numbers of simulations, such as in the role of a risk analysis engine.

Additional keyword: discrete event simulation.


Acknowledgements

Li Shu, Lachlan McCaw and Rick Sneeuwjagt of the Department of Environment and Conservation, Western Australia, are thanked for weather, fuel and fire data for the Mt Cooke fire. Thanks to Jim Gould, Neil Burrows and two anonymous reviewers for reviews of an earlier version of the present paper. This research has been funded in part by the Australian Bushfire Cooperative Research Centre. Support from the National Information and Communications Technology Australia (NICTA) Centre of Excellence to G. J. Milne in the form of a NICTA Fellowship is also gratefully acknowledged.


References


Alexander ME (1985) Estimating the length-to-breadth ratio of elliptical forest fire patterns. In ‘Proceedings of the Eighth National Conference on Fire and Forest Meteorology’, 29 April–2 May 1985, Detroit, MI. pp. 287–304. (Society of American Foresters: Bethesda, MD)

Anderson DH, Catchpole EA, De Mestre NJ , Parkes T (1982) Modelling the spread of grass fires. Journal of the Australian Mathematical. Society B  23, 451–466.
CWFGM Project Steering Committee (2004) ‘Prometheus User Manual ver. 3.0.1.’ (Alberta Sustainable Resource Development: Edmonton, AB, Canada)

Dunbar D , Humphreys G (2006) A spatial data structure for fast Poisson-disk sample generation. ACM Transactions on Graphics  25, 503–508.
Crossref | GoogleScholarGoogle Scholar | Finney MA (1998) FARSITE: Fire Area Simulator – model development and evaluation. USDA Forest Service, Rocky Mountain Research Station, Research Paper RMRS-RP-004. (Ogden, UT)

Finney MA (1999) Mechanistic modelling of landscape fire patterns. In ‘Spatial Modelling of Forest Landscape Change: Approaches and Applications’. (Eds DJ Mladenhoff, WL Baker) pp. 186–209. (Cambridge University Press: New York)

Green DG, Gill AM , Noble IR (1983) Fire shapes and the adequacy of fire spread models. Ecological Modelling  20, 33–45.
Crossref | GoogleScholarGoogle Scholar | McArthur AG (1967) Fire Behaviour in Eucalypt Forests. Department of National Development Forestry and Timber Bureau, Leaflet No 107. (Canberra)

McDaniel J (2007) Calculated risk. Wildfire 16(2). Available at http://wildfiremag.com/mag/calculated_risk [Verified 29 July 2008]

Muzy A, Innocenti E, Aiello A, Santucci J-F, Wainer G (2002) Cell-DEVS quantization techniques in a fire spreading application. In ‘Proceedings of the 2002 Winter Simulation Conference’, 8-11 December 2002, San Diego, CA. (Eds E Yücesan, C-H Chen, JL Snowdon, JM Charnes) pp. 542–549. (IEEE Computer Society: Washington, DC)

Pastor E, Zarate L, Planas E , Arnaldos J (2003) Mathematical models and calculation systems for the study of wildland fire behaviour. Progress in Energy and Combustion Science  29, 139–153.
Crossref | GoogleScholarGoogle Scholar | Sneeuwjagt RJ, Peet GB (1985) ‘Forest Fire Behaviour Tables for Western Australia.’ (Department of Conservation and Land Management: Perth)

Sullivan AL (2008) Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue models. International Journal of Wildland Fire, in press. doi:10.1071/WF06144

Sullivan AL , Knight IK (2001) Estimating error in wind speed measurements for experimental fires. Canadian Journal of Forest Research  31, 401–409.
Crossref | GoogleScholarGoogle Scholar | Sullivan AL, Knight IK (2008) A hybrid cellular automata/semi-physical model of fire growth. Complexity International 12, msid09. Available at http://www.complexity.org.au/ci/vol12/msid09/ [Verified 20 August 2008]

Zeigler BP (1984) ‘Multifaceted Modelling and Discrete Event Simulation.’ (Academic Press: London)