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

The effect of fuel bed height in grass fire spread: addressing the findings and recommendations of Moinuddin et al. (2018)

Miguel G. Cruz A B , Andrew L. Sullivan https://orcid.org/0000-0002-8038-8724 A and James S. Gould A
+ Author Affiliations
- Author Affiliations

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

B Corresponding author. Email: miguel.cruz@csiro.au

International Journal of Wildland Fire 30(3) 215-220 https://doi.org/10.1071/WF19186
Submitted: 8 November 2019  Accepted: 10 January 2020   Published: 7 February 2020

Abstract

A recent numerical simulation study by Moinuddin et al. (2018) determined that over a specific range of Froude numbers defined by them as ‘plume mode’, grass fuel height has a strong inverse effect on the rate of fire spread in grasslands. They then suggested that a relationship for effect of fuel height derived from their simulation results could be used to support fire management decision-making. The present analysis used fire spread measurement data from two outdoor experimental burning studies in grass fuels where an explicit control of fuel height was imposed to verify the realism of their results. It was found that a reduction in grass height, with or without removal of the cut fuel and regardless of the Froude number, led to a significant reduction in rate of fire spread, a result opposite to the simulations obtained by Moinuddin et al. (2018).

Additional keywords: crop fuels, fire behaviour experiments, fire mitigation, grass fuels, headfire.


References

Alexander ME, Quintilio D (1990) Perspectives on experimental fires in Canadian forestry research. Mathematical and Computer Modelling 13, 17–26.
Perspectives on experimental fires in Canadian forestry research.Crossref | GoogleScholarGoogle Scholar |

Anderson HE (1982) Aids to determining fuel models for estimating fire behavior. USDA Forest Service, Intermountain Forest and Range Experimental Station, General Technical Report No. INT-122. (Odgen, UT, USA)

Anderson WR, Cruz MG, Fernandes PM, McCaw L, Vega JA, Bradstock RA, Fogarty L, Gould JS, McCarthy G, Marsden-Smedley JB, Matthews S, Mattingley G, Pearce HG, van Wilgen BW (2015) A generic, empirical-based model for predicting rate of fire spread in shrublands. International Journal of Wildland Fire 24, 443–460.
A generic, empirical-based model for predicting rate of fire spread in shrublands.Crossref | GoogleScholarGoogle Scholar |

Andrews PL, Anderson SAJ, Anderson WR (2006) Evaluation of a dynamic load transfer function using grassland curing data. In ‘Fuels management: how to measure success conference proceedings,’ 28–30 March 2006, Portland, OR, USA. (Eds PL Andrews, BW Butler) pp. 381–395. USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-41. (Fort Collins, CO, USA)

Apte V, Bilger R, Green A, Quintiere J (1991) Wind-aided turbulent flame spread and burning over large-scale horizontal PMMA surfaces. Combustion and Flame 85, 169–184.
Wind-aided turbulent flame spread and burning over large-scale horizontal PMMA surfaces.Crossref | GoogleScholarGoogle Scholar |

Cheney NP, Gould JS, Catchpole WR (1993) The influence of fuel, weather and fire shape variables on fire-spread in grasslands. International Journal of Wildland Fire 3, 31–44.
The influence of fuel, weather and fire shape variables on fire-spread in grasslands.Crossref | GoogleScholarGoogle Scholar |

Clark RG (1983) Threshold requirements for fire spread in grassland fuels. PhD Thesis, Texas Tech University. (Lubbock, TX, USA)

Clements CB, Kochanski AK, Seto D, Davis B, Camacho C, Lareau NP, Contezac J, Restaino J, Heilman WE, Krueger SK, Butler B, Ottmar RD, Vihnanek R, Flynn J, Filippi J-B, Barboni T, Hall DE, Mandel J, Jenkins MA, O’Brien J, Hornsby B, Teske C (2019) The FireFlux II experiment: a model-guided field experiment to improve understanding of fire–atmosphere interactions and fire spread. International Journal of Wildland Fire 28, 308–326.

Cohen JD, Finney MA, Yedinak KM (2006) Active spreading crown fire characteristics: implications for modelling. In ‘Proceedings of the V International Conference on Forest Fire Research,’ 16–20 November 2006, Figueira da Foz, Coimbra, Portugal. (Ed. DX Viegas) pp. 1–12. (ADAI Press: Coimbra, Portugal)

Country Fire Authority (CFA) (2019) Grassfires – rural. (Country Fire Authority of Victoria) Available at https://www.cfa.vic.gov.au/plan-prepare/grassfires-rural [Verified 14 August 2019]

Cruz MG, Hurley R, Bessell R, Sullivan AL (2020) Fire behaviour in wheat crops – effect of fuel structure on rate of fire spread. International Journal of Wildland Fire

Cruz MG, Sullivan AS, Kidnie S, Hurley R, Nichols S (2016) The effect of grass curing and fuel structure on fire behaviour – final report. CSIRO Client Report No. EP 166414. (Canberra, ACT, Australia)

Cruz MG, Sullivan AL, Gould JS, Hurley RJ, Plucinski MP (2018) Got to burn to learn: the effect of fuel load on grassland fire behaviour and its management implications. International Journal of Wildland Fire 27, 727–741.
Got to burn to learn: the effect of fuel load on grassland fire behaviour and its management implications.Crossref | GoogleScholarGoogle Scholar |

Cruz MG, Hurley R, Bessell R, Sullivan AL (2019) Fire behaviour in wheat crops. Final report. CSIRO Client Report No. EP 195825. (Canberra, ACT, Australia)

Hoffman C, Sieg C, Linn R, Mell W, Parsons R, Ziegler J, Hiers J (2018) Advancing the science of wildland fire dynamics using process-based models. Fire 1, 32
Advancing the science of wildland fire dynamics using process-based models.Crossref | GoogleScholarGoogle Scholar |

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

Mell W, Jenkins MA, Gould JS, Cheney NP (2007) A physics-based approach to modelling grassland fires. International Journal of Wildland Fire 16, 1–22.
A physics-based approach to modelling grassland fires.Crossref | GoogleScholarGoogle Scholar |

Moinuddin KAM, Sutherland D, Mell W (2018) Simulation study of grass fire using a physics-based model: striving towards numerical rigour and the effect of grass height on the rate of spread. International Journal of Wildland Fire 27, 800–814.
Simulation study of grass fire using a physics-based model: striving towards numerical rigour and the effect of grass height on the rate of spread.Crossref | GoogleScholarGoogle Scholar |

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

NSW Rural Fire Service (RFS) (2010) Grass fires. (State of New South Wales) Available at https://www.rfs.nsw.gov.au/__data/assets/pdf_file/0017/9431/Grass-Fires-Factsheet.pdf [Verified 14 August 2019]

Penman HL, Long IF (1960) Weather in wheat: an essay in micro‐meteorology. Quarterly Journal of the Royal Meteorological Society 86, 16–50.
Weather in wheat: an essay in micro‐meteorology.Crossref | GoogleScholarGoogle Scholar |

R Core Team (2018) R: A language and environment for statistical computing. (R Foundation for Statistical Computing: Vienna, Austria) Available at https://www.R-project.org/ [Verified 13 January 2020]

Sneeuwjagt RJ, Frandsen WH (1977) Behavior of experimental grass fires vs. predictions based on Rothermel’s fire model. Canadian Journal of Forest Research 7, 357–367.
Behavior of experimental grass fires vs. predictions based on Rothermel’s fire model.Crossref | GoogleScholarGoogle Scholar |

Thomas PH, Simms DL, Wraight HG (1964) Fire spread in wooden cribs. Joint Fire Research Organization, Fire Research Note 537. (Boreham Wood, UK)

Watts JM (1987) Editorial: validating fire models. Fire Technology 23, 93–94.
Editorial: validating fire models.Crossref | GoogleScholarGoogle Scholar |