CSIRO Publishing blank image blank image blank image blank imageBooksblank image blank image blank image blank imageJournalsblank image blank image blank image blank imageAbout Usblank image blank image blank image blank imageShopping Cartblank image blank image blank image You are here: Journals > International Journal of Wildland Fire   
International Journal of Wildland Fire
  Published on behalf of the International Association of Wildland Fire
blank image Search
blank image blank image
blank image
  Advanced Search

Journal Home
About the Journal
Editorial Structure
Online Early
Current Issue
Just Accepted
All Issues
Special Issues
Research Fronts
Sample Issue
20-Year Author Index
For Authors
General Information
Submit Article
Author Instructions
Open Access
For Referees
Referee Guidelines
Review an Article
For Subscribers
Subscription Prices
Customer Service
Print Publication Dates
Library Recommendation

blue arrow e-Alerts
blank image
Subscribe to our Email Alert or RSS feeds for the latest journal papers.

red arrow Connect with CP
blank image
facebook twitter logo LinkedIn

red arrow Connect with IAWF
blank image
facebook twitter LinkedIn


Article << Previous     |     Next >>   Contents Vol 23(4)

Predicting the number of daily human-caused bushfires to assist suppression planning in south-west Western Australia

M. P. Plucinski A B E, W. L. McCaw C, J. S. Gould A B and B. M. Wotton D

A CSIRO Ecosystem Sciences and CSIRO Climate Adaptation Flagship, GPO Box 1700, Canberra, ACT 2601, Australia.
B Bushfire Cooperative Research Centre, Level 5, 340 Albert Street, East Melbourne, Vic. 3002, Australia.
C Department of Parks and Wildlife, Locked Bag 2, Manjimup, WA 6258, Australia.
D Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste Marie, ON, P6A 2E5, Canada.
E Corresponding author: Email: matt.plucinski@csiro.au

International Journal of Wildland Fire 23(4) 520-531 http://dx.doi.org/10.1071/WF13090
Submitted: 31 May 2013  Accepted: 19 December 2013   Published: 9 April 2014

PDF (661 KB) $25
 Export Citation

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.

Additional keywords: accidental ignitions, deliberate ignitions, fuel moisture, negative binomial regression, wildfire occurrence.


Albertson K, Aylen J, Cavan G, McMorrow J (2009) Forecasting the outbreak of moorland wildfires in the English Peak District. Journal of Environmental Management 90, 2642–2651.
CrossRef | CAS | PubMed |

Anderson HE (1970) Forest fuels ignitability. Fire Technology 6, 312–319.
CrossRef | CAS |

Andrews PL, Loftsgaarden DO, Bradshaw LS (2003) Evaluation of fire danger rating indexes using logistic regression and percentile analysis. International Journal of Wildland Fire 12, 213–226.
CrossRef |

Australian Bureau of Statistics (2014) 3218.0 – Regional population growth, Australia, 2011–12, Australian Bureau of Statistics. Available at http://www.abs.gov.au/ausstats/abs@.nsf/Products/3218.0~2011-12~Main+Features~Western+Australia?OpenDocument [Verified 26 February 2014]

Beck JA (1995) Equations for the forest fire behaviour tables for Western Australia. CALMScience 1, 325–348.

Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MHH, White JSS (2009) Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology & Evolution 24, 127–135.
CrossRef |

Boyle J, Jessup M, Crilly J, Green D, Lind J, Wallis M, Miller P, Fitzgerald G (2012) Predicting emergency department admissions. Emergency Medicine Journal 29, 358–365.
CrossRef | PubMed |

Bryant CJ (2008) Understanding bushfire: trends in deliberate vegetation fires in Australia. Technical Report, No. 350. Australian Institute of Criminology, Canberra.

Burrows ND (1987) The soil dryness index for use in fire control in Western Australia. Technical Report, No. 17. Department of Conservation and Land Management, Western Australia.

Burrows N, McCaw L (2013) Prescribed burning in southwestern Australian forests. Frontiers in Ecology and the Environment 11, e25–e34.
CrossRef |

Cameron AC, Trivedi PK (1998) ‘Regression Analysis of Count Data.’ Econometric Society Monographs 30. (Cambridge University Press: Cambridge, UK)

Catry FX, Rego FC, Bacao F, Moreira F (2009) Modeling and mapping wildfire ignition risk in Portugal. International Journal of Wildland Fire 18, 921–931.
CrossRef |

Chandler C, Cheney P, Thomas P, Trabaud L, Williams D (1983) ‘Fire in Forestry, Volume I: Forest Fire Behaviour and Effects.’ (Wiley: New York)

Cheney NP, Gould JS (1995) Separating fire spread prediction and fire danger rating. CALMScience 4, 3–8.

Cunningham AA, Martell DL (1973) A stochastic model for the occurrence of man-caused forest fires. Canadian Journal of Forest Research 3, 282–287.
CrossRef |

Dowdy AJ, Mills GA (2012) Atmospheric and fuel moisture characteristics associated with lightning-attributed fires. Journal of Applied Meteorology and Climatology 51, 2025–2037.
CrossRef |

Fosberg MA (1978) Weather in wildland fire management: the fire weather index. In ‘Conference on Sierra Nevada Meteorology’, 19–21 June, Lake Tahoe, CA. pp. 1–4. (American Meteorological Society: Boston, MA)

Goodrick SL (2002) Modification of the Fosberg fire weather index to include drought. International Journal of Wildland Fire 11, 205–211.
CrossRef |

Gould JS, McCaw WL, Cheney NP, Ellis PF, Matthews S (2007) Field guide – Fuel assessment and fire behaviour prediction in dry eucalypt forest. (Ensis-CSIRO, Canberra, ACT, and Department of Environment and Conservation: Perth, WA)

Greene W (2008) Functional forms for the negative binomial model for count data. Economics Letters 99, 585–590.
CrossRef |

Haines DA, Main WA, Frost JS, Simard AJ (1983) Fire-danger rating and wildfire occurrence in the northeastern United States. Forest Science 29, 679–696.

Jeffrey SJ, Carter JO, Moodie KB, Beswick AR (2001) Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environmental Modelling & Software 16, 309–330.
CrossRef |

Keetch JJ, Byram GM (1968) A drought index for forest fire control. USDA Forest Service, Southeastern Forest Experiment Station, Research Paper SE-38. (Asheville, NC)

Magnussen S, Taylor SW (2012) Prediction of daily lightning- and human-caused fires in British Columbia. International Journal of Wildland Fire 21, 342–356.
CrossRef |

Martell DL (1982) A review of operational research studies in forest fire management. Canadian Journal of Forest Research 12, 119–140.
CrossRef |

Martell DL, Boychuk D (1997) Levels of fire protection for sustainable forestry in Ontario: a discussion paper. In ‘NODA/NFP Technical Report 43’. Natural Resources Canada, Canadian Forest Service, Ontario Region. (Sault Ste Marie, ON)

Martell DL, Otukol S, Stocks BJ (1987) A logistic model for predicting daily people-caused forest fire occurrence in Ontario. Canadian Journal of Forest Research 17, 394–401.
CrossRef |

Matthews S (2006) A process-based model of fine fuel moisture. International Journal of Wildland Fire 15, 155–168.
CrossRef |

Matthews S, Gould J, McCaw L (2010) Simple models for predicting dead fuel moisture in eucalyptus forests. International Journal of Wildland Fire 19, 459–467.
CrossRef |

McArthur AG (1966) Weather and grassland fire behaviour. Forestry and Timber Bureau, Number 100. (Commonwealth Department of National Development: Canberra, ACT)

McArthur AG (1967) Fire behaviour in eucalypt forests. Forestry and Timber Bureau, Number 107. (Commonwealth Department of National Development: Canberra, ACT)

Mount AB (1972) The derivation and testing of a soil dryness index using run-off data. State Government of Tasmania, Tasmanian Forestry Commission, Bulletin No. 4. (Hobart).

Nelson RM (2001) Water relations of forest fuels. In ‘Forest Fires: Behavior and Ecological Effects’. (Eds EA Johnson, K Miyanishi) pp. 79–150. (Academic Press: San Diego, CA)

Noble IR, Bary GAV, Gill AM (1980) McArthur’s fire danger meters expressed as equations. Australian Journal of Ecology 5, 201–203.
CrossRef |

Padilla M, Vega-García C (2011) On the comparative importance of fire danger rating indices and their integration with spatial and temporal variables for predicting daily human-caused fire occurrences in Spain. International Journal of Wildland Fire 20, 46–58.
CrossRef |

Penman TD, Bradstock RA, Price O (2013) Modelling the determinants of ignition in the Sydney Basin, Australia: implications for future management. International Journal of Wildland Fire 22, 469–478.
CrossRef |

Podur J, Wotton M (2010) Will climate change overwhelm fire management capacity? Ecological Modelling 221, 1301–1309.
CrossRef |

Preisler HK, Brillinger DR, Burgan RE, Benoit JW (2004) Probability based models for estimation of wildfire risk. International Journal of Wildland Fire 13, 133–142.
CrossRef |

Prestemon JP, Butry DT (2005) Time to burn: modeling wildland arson as an autoregressive crime function. American Journal of Agricultural Economics 87, 756–770.
CrossRef |

Prestemon JP, Chas-Amil ML, Touza JM, Goodrick SL (2012) Forecasting intentional wildfires using temporal and spatiotemporal autocorrelations. International Journal of Wildland Fire 21, 743–754.
CrossRef |

R Development Core Team (2012) R: a language and environment for statistical computing. (R Foundation for Statistical Computing: Vienna, Austria)

Reineking B, Weibel P, Conedera M, Bugmann H (2010) Environmental determinants of lightning- v. human-induced forest fire ignitions differ in a temperate mountain region of Switzerland. International Journal of Wildland Fire 19, 541–557.
CrossRef |

Sakamoto Y, Ishiguro M, Kitagawa G (1986) ‘Akaike Information Criterion Statistics.’ (D. Reidel Publishing Company: Boston, MA)

Sharples JJ, McRae RHD, Weber RO, Gill AM (2009a) A simple index for assessing fire danger rating. Environmental Modelling & Software 24, 764–774.
CrossRef |

Sharples JJ, McRae RHD, Weber RO, Gill AM (2009b) A simple index for assessing fuel moisture content. Environmental Modelling & Software 24, 637–646.
CrossRef |

Simard AJ (1968) Moisture content of forest fuels III: Moisture content variations below the fiber saturation point. Department of Forestry and Rural Development, Forest Fire Research Institute, Information Report FF-X-16, (Ottawa, ON)

Sneeuwjagt RJ, Peet GB (1985) ‘Forest Fire Behaviour Tables for Western Australia’, 3rd edn. (Department of Conservation and Land Management: Perth, WA)

Sullivan AL (2010) Grassland fire management in future climate. Advances in Agronomy 106, 173–208.
CrossRef |

Syphard AD, Radeloff VC, Keuler NS, Taylor RS, Hawbaker TJ, Stewart SI, Clayton MK (2008) Predicting spatial patterns of fire on a southern California landscape. International Journal of Wildland Fire 17, 602–613.
CrossRef |

Tithecott AG (1992) Application of fire occurrence prediction models in Ontario’s fire management program. In ‘Proceedings of the Eighth Central Region Fire Weather Committee Scientific and Technical Seminar’, 3 April 1992, Winnipeg, MB. (Ed. KR Anderson) Forestry Canada, Northwest Region, pp. 57–72. (Edmonton, Alberta)

Todd B, Kourtz PH (1991) Predicting the daily occurrence of people-caused forest fires. Forestry Canada, Petawawa Forest Experimental station, PI-X-103. (Chalk River, ON)

Van Wagner CE (1987) Development and structure of the Canadian forest fire weather index system. Canadian Forestry Service, Forestry Technical Report 35, (Ottawa, ON)

Vasilakos C, Kalabokidis K, Hatzopoulos J, Matsinos I (2009) Identifying wildland fire ignition factors through sensitivity analysis of a neural network. Natural Hazards 50, 125–143.
CrossRef |

Vega-García C, Woodard PM, Titus SJ, Adamowic V, Lee BS (1995) A logit model for predicting the daily occurrence of human caused forest fires. International Journal of Wildland Fire 5, 101–111.
CrossRef |

Venables WN, Ripley BD (2002) ‘Modern Applied Statistics with S.’ (Springer: New York)

Viegas DX, Bovio G, Ferreira A, Nosenzo A, Sol B (1999) Comparative study of various methods of fire danger evaluation in Southern Europe. International Journal of Wildland Fire 9, 235–246.
CrossRef |

Vilar L, Woolford DG, Martell DL, Martin MP (2010a) A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain. International Journal of Wildland Fire 19, 325–337.
CrossRef |

Vilar L, Nieto H, Martin MP (2010b) Integration of lightning- and human-caused wildfire occurrence models. Human and Ecological Risk Assessment 16, 340–364.
CrossRef | CAS |

Viney NR (1991) A review of fine fuel moisture modelling. International Journal of Wildland Fire 1, 215–234.
CrossRef |

Willmott CJ (1982) Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society 63, 1309–1313.
CrossRef |

Wotton BM, Beverly JL (2007) Stand-specific litter moisture content calibrations for the Canadian Fine Fuel Moisture Code. International Journal of Wildland Fire 16, 463–472.
CrossRef |

Wotton BM, Martell DL (2005) A lightning fire occurrence model for Ontario. Canadian Journal of Forest Research 35, 1389–1401.
CrossRef |

Wotton BM, Martell DL, Logan KA (2003) Climate change and people-caused forest fire occurrence in Ontario. Climatic Change 60, 275–295.
CrossRef | CAS |

Wotton BM, Nock CA, Flannigan MD (2010) Forest fire occurrence and climate change in Canada. International Journal of Wildland Fire 19, 253–271.
CrossRef |

Subscriber Login

Legal & Privacy | Contact Us | Help


© CSIRO 1996-2016