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Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Two methods for calculating wildland fire rate of forward spread

Jim S. Gould A and Andrew L. Sullivan https://orcid.org/0000-0002-8038-8724 A B
+ Author Affiliations
- Author Affiliations

A CSIRO, GPO Box 1700, Canberra, ACT, 2601, Australia.

B Corresponding author. Email: andrew.sullivan@csiro.au

International Journal of Wildland Fire 29(3) 272-281 https://doi.org/10.1071/WF19120
Submitted: 1 August 2019  Accepted: 11 December 2019   Published: 6 February 2020

Abstract

Accurate estimation of a wildland fire’s progression is critical for the development of robust fire spread prediction models and their validation. Two methods commonly used to determine spread rate are the cumulative spread rate, calculated as the total distance travelled by a fire divided by the total time of travel, and the interval spread rate, calculated using the minimum time and maximum distance between observations. This paper analyses the differences between these two methods using experimental fires conducted in dry eucalypt forest leaf litter in either a combustion wind tunnel or large (4 ha) field sites. Fires were ignited from a point, 400-mm and 800-mm line ignitions in the wind tunnel, and point and 120-m line ignitions in the field experiments. A total of 312 and 397 observations of distance travelled and time taken were made during the laboratory and field experiments respectively, along with associated environmental variables. Mean spread rates and standard deviations were significantly greater for the interval method than those of the cumulative method for all the laboratory data and the field point ignition fires, and the difference between them varied with distance and time since ignition. These findings have important implications for fire spread and acceleration model development.

Additional keywords: behaviour, bushfire, cumulative, eucalypt fuel, field experiments, interval, laboratory, Pyrotron, rate of spread, wildland fire.


References

Anderson WR, Catchpole EA, Butler BW (2010) Convective heat transfer in fire spread through fine fuel beds. International Journal of Wildland Fire 19, 284–298.
Convective heat transfer in fire spread through fine fuel beds.Crossref | GoogleScholarGoogle Scholar |

Burrows ND (1999) Fire behaviour in jarrah forest fuels: 2. Field experiments. CALMScience 3, 57–84.

Byram GM (1959) Combustion of forest fuels. In ‘Forest fire: control and use’. (Ed. K P Davis) pp. 61–89 (McGraw Hill: New York, NY, USA).

Catchpole EA, Catchpole WR, Rothermel RC (1993) Fire behaviour experiments in mixed fuel complexes. International Journal of Wildland Fire 3, 45–57.
Fire behaviour experiments in mixed fuel complexes.Crossref | GoogleScholarGoogle Scholar |

Catchpole WR, Catchpole EA, Butler BW, Rothermel RC, Morris GA, Latham DJ (1998) Rate of spread of fire – burning fires in woody fuels in a wind tunnel. Combustion Science and Technology 131, 1–37.
Rate of spread of fire – burning fires in woody fuels in a wind tunnel.Crossref | GoogleScholarGoogle Scholar |

Cheney NP, Gould JS (1995) Fire growth in grassland fuels. International Journal of Wildland Fire 5, 237–247.
Fire growth in grassland fuels.Crossref | GoogleScholarGoogle Scholar |

Cheney NP, Gould JS, Catchpole WR (1998a) Prediction of fire spread in grasslands. International Journal of Wildland Fire 8, 1–13.
Prediction of fire spread in grasslands.Crossref | GoogleScholarGoogle Scholar |

Cheney NP, Gould JS, McCaw L (1998b) Project Vesta: research initiative into the effects of fuel structure and fuel load on behaviour of wildfires in dry eucalypt forest. In ‘Proceedings 13th Conference of Fire and Forest Meteorology’, October 27–31, 1996, Lorne, Australia. pp. 375–378 (International Association of Wildland Fire: Moran, WY, USA).

Cheney NP, Gould JS, McCaw WL, Anderson WR (2012) Predicting fire behaviour in dry eucalypt forest in southern Australia. Forest Ecology and Management 280, 120–131.
Predicting fire behaviour in dry eucalypt forest in southern Australia.Crossref | GoogleScholarGoogle Scholar |

Cruz MG, McCaw WL, Anderson WR, Gould JS (2013) Fire behaviour modelling in mallee-heath shrublands of southern Australia. Environmental Modelling & Software 40, 21–34.
Fire behaviour modelling in mallee-heath shrublands of southern Australia.Crossref | GoogleScholarGoogle Scholar |

Curry JR, Fons WL (1938) Rate of spread of surface fires in ponderosa pine type of California. Journal of Agricultural Research 57, 239–267.

Fernandes PAM (2001) Fire spread prediction in shrub fuel in Portugal. Forest Ecology and Management 144, 67–74.
Fire spread prediction in shrub fuel in Portugal.Crossref | GoogleScholarGoogle Scholar |

Finney MA, Cohen JD, Forthofer JM, McAllister SS, Gollner MJ, Gorhan DJ, Saito K, Akafuah NK, Adam BA, English JD (2015) Role of buoyant flame dynamics in wildfire spread. Proceedings of the National Academy of Sciences 112, 9833–9838.
Role of buoyant flame dynamics in wildfire spread.Crossref | GoogleScholarGoogle Scholar |

Forestry Canada Fire Danger Group (1992) Development and structure of the Canadian Forest Fire Behaviour Prediction System. Forestry Canada Science and Sustainable Development Directorate, Information Report ST-X-3. (Ottawa, ON, Canada)

Fujioka FM (1985) Estimating wildland fire rate of spread in spatially non-uniform environment. Forest Science 31, 21–29.

Gould JS, McCaw WL, Cheney NP, Ellis PE, Knight IK, Sullivan AL (2007) ‘Project Vesta--Fire in Dry Eucalypt Forest: fuel structure, fuel dynamics and fire behaviour.’ (Ensis–CSIRO, Canberra, ACT and Department of Environment and Conservation, Perth, WA, Australia)

Gould JS, McCaw LW, Cheney NP (2011) Quantifying fine fuel dynamics and structure in dry eucalypt forest (Eucalyptus marginata) in Western Australia for fire management. Forest Ecology and Management 262, 531–546.
Quantifying fine fuel dynamics and structure in dry eucalypt forest (Eucalyptus marginata) in Western Australia for fire management.Crossref | GoogleScholarGoogle Scholar |

Gould JS, Sullivan AL, Hurley R, Koul V (2017) Comparison of three methods to quantify the fire spread rate in laboratory experiments. International Journal of Wildland Fire 26, 877–883.
Comparison of three methods to quantify the fire spread rate in laboratory experiments.Crossref | GoogleScholarGoogle Scholar |

Marcelli T, Santoni PA, Simeoni A, Leoni E, Porterie B (2004) Fire spread across pine needle fuel beds: characterization of temperature and velocity distribution within the fire plume. International Journal of Wildland Fire 13, 37–48.
Fire spread across pine needle fuel beds: characterization of temperature and velocity distribution within the fire plume.Crossref | GoogleScholarGoogle Scholar |

Marsden-Smedley JB, Catchpole WR (1995) Fire behaviour modelling in Tasmanian buttongrass moorlands II. Fire behaviour. International Journal of Wildland Fire 5, 215–228.
Fire behaviour modelling in Tasmanian buttongrass moorlands II. Fire behaviour.Crossref | GoogleScholarGoogle Scholar |

Martinez MN, Bartholomew MJ (2017) What does it ‘mean’? A review of interpreting and calculating different types of means and standard deviations. Pharmaceutics 9, 14
What does it ‘mean’? A review of interpreting and calculating different types of means and standard deviations.Crossref | GoogleScholarGoogle Scholar |

Matthews S (2010) Effects of drying temperature on fuel moisture content measurements. International Journal of Wildland Fire 19, 800–802.
Effects of drying temperature on fuel moisture content measurements.Crossref | GoogleScholarGoogle Scholar |

McAlpine RS, Wakimoto RH (1991) The acceleration of fire from point source to equilibrium spread. Forest Science 37, 1314–1337.

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

McArthur AG (1967) Fire behaviour in eucalypt forest. Commonwealth Department of National Development, Forestry and Timber Bureau Leaflet 107. (Canberra, ACT, Australia)

McCaw LW, Gould JS, Cheney NP, Ellis PE, Anderson WR (2012) Changes in fire behaviour in dry eucalypt forest as fuel increases with age. Forest Ecology and Management 271, 170–181.
Changes in fire behaviour in dry eucalypt forest as fuel increases with age.Crossref | GoogleScholarGoogle Scholar |

Morandini F, Silvani X, Rossi L, Santoni PA, Simeoni A, Balbi JH, Rossi JL, Marcelli T (2006) Fire spread experiment across Mediterranean shrub: influence of wind on flame front properties. Fire Safety Journal 41, 229–235.
Fire spread experiment across Mediterranean shrub: influence of wind on flame front properties.Crossref | GoogleScholarGoogle Scholar |

Mulvaney JJ, Sullivan AL, Cary GJ, Bishop GR (2016) Repeatability of free-burning fire experiments using heterogeneous forest fuel beds in a combustion wind tunnel. International Journal of Wildland Fire 25, 445–455.
Repeatability of free-burning fire experiments using heterogeneous forest fuel beds in a combustion wind tunnel.Crossref | GoogleScholarGoogle Scholar |

Peet GB (1965) A fire danger rating and controlled burning guide for the northern jarrah (Eucalyptus marginata Sm.) forest of Western Australia. Forests Department Bulletin No. 74. (Perth, WA, Australia)

R Core Team (2017) R: A language and environment for statistical computing. R Foundation for Statistical Computing. (Vienna, Austria) Available at https://www.r-project.org/. [Verified 20 December 2019]

Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. US Forest Service Research Paper INT-115. (Odgen UT, USA)

Rothermel RC, Anderson HE (1966) Fire spread characteristics determined in the laboratory. US Forest Service Research Paper INT-30. (Ogden, UT, USA).

Show SB (1919) Clime and forest fires in northern California. Journal of Forestry 17, 965–979.

Simard AJ, Deacon AG, Adams KB (1982) Non-directional sampling of wildland fire spread. Fire Technology 18, 221–228.
Non-directional sampling of wildland fire spread.Crossref | GoogleScholarGoogle Scholar |

Simard AJ, Eenigenburg KB, Nissen RL, Deacon AG (1984) General procedure for sampling and analysing wildland fire spread. Forest Science 30, 51–64.

Stocks BJ, Lawson BD, Alexander ME, Van Wagner CE, McAlpine RS, Lyham TJ, Dube DE (1989) Canadian Forest Fire Danger Rating System – an overview. Forestry Chronicle 65, 258–265.
Canadian Forest Fire Danger Rating System – an overview.Crossref | GoogleScholarGoogle Scholar |

Sullivan AL (2009a) Wildland fire spread modelling, 1990–2007. 1: Physical and quasi-physical models. International Journal of Wildland Fire 18, 349–368.
Wildland fire spread modelling, 1990–2007. 1: Physical and quasi-physical models.Crossref | GoogleScholarGoogle Scholar |

Sullivan AL (2009b) Wildland fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models. International Journal of Wildland Fire 18, 369–386.
Wildland fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models.Crossref | GoogleScholarGoogle Scholar |

Sullivan AL, Gould JS (2019) Wildland fire rate of spread. In ‘Encyclopedia of wildfires and wildland–urban interface (WUI) fires’. (Ed. S Manzello) (Springer: Cham, Switzerland)10.1007/978-3-319-51727-8.

Sullivan AL, Knight IK (2001) Estimating error in wind speed measurements for experimental fires. Canadian Journal of Forest Research 31, 401–409.
Estimating error in wind speed measurements for experimental fires.Crossref | GoogleScholarGoogle Scholar |

Sullivan AL, Matthews S (2013) Determining landscape fine fuel moisture content of the Kilmore East ‘Black Saturday’ wildfire using spatially extended point-based models. Environmental Modelling & Software 40, 98–108.
Determining landscape fine fuel moisture content of the Kilmore East ‘Black Saturday’ wildfire using spatially extended point-based models.Crossref | GoogleScholarGoogle Scholar |

Sullivan AL, Knight IK, Hurley RJ, Webber C (2013) A contractionless, low-turbulence wind tunnel for the study of free-burning fires. Experimental Thermal and Fluid Science 44, 264–274.
A contractionless, low-turbulence wind tunnel for the study of free-burning fires.Crossref | GoogleScholarGoogle Scholar |

Wolff MF, Carrier GF, Fendell FB (1991) Wind-aided fire spread across arrays of discrete fuel elements. II Experiment. Combustion Science and Technology 77, 261–289.
Wind-aided fire spread across arrays of discrete fuel elements. II Experiment.Crossref | GoogleScholarGoogle Scholar |