Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE (Open Access)

Factors influencing travel time and getaway time of helitack crews on wildfires in the province of Quebec

Frédéric Brunet A * , Jonathan Boucher B and Mathieu Bouchard A
+ Author Affiliations
- Author Affiliations

A Département des sciences du bois et de la forêt, Université Laval, 2405 rue de la Terrasse, Québec, QC, G1V 0A6, Canada.

B Laurentian Forestry Centre, Canadian Forest Service, Natural Resources Canada, 1055 rue du PEPS, Québec, QC, G1V 4C7, Canada.

* Correspondence to: frederic.brunet.3@ulaval.ca

International Journal of Wildland Fire 33, WF24012 https://doi.org/10.1071/WF24012
Submitted: 23 January 2024  Accepted: 28 September 2024  Published: 29 October 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Background

Reducing the delay between the detection of a fire and the arrival of the initial attack (IA) crew can have a significant impact on the likelihood of the IA’s success.

Aims

The objective of this study was to identify factors influencing same-day getaway time, next-day getaway time and travel time of helitack IA crews in the province of Quebec, Canada.

Methods

Using generalised linear modelling and model selection, we analysed the impact of multiple factors on these three distinct times.

Key results

Our results show that factors such as the distance between the departure base and the fire, the number of flight legs to reach a fire, dispatch hour, departure base location, the fire’s rate of spread, Julian date, the number of active fires, fuel type and the fire’s size at detection all influenced getaway time and travel time with varying degrees of influence.

Conclusions

The factors with the highest influence were distance for travel time and dispatch hour for both same-day and next-day getaway times.

Implications

Addressing these high-impact factors through the modification of deployment policies and the positioning of helitack crews could help reduce response times.

Keywords: Deployment policies, fire management, fire suppression, helitack, initial attack, presuppression, resource deployment, response time, travel time, wildfire.

References

Arienti MC, Cumming S, Boutin S (2006) Empirical models of forest fire initial attack success probabilities: the effects of fuels, anthropogenic linear features, fire weather, and management. Canadian Journal of Forest Research 36, 3155-3166.
| Crossref | Google Scholar |

Arrubla JAG, Ntaimo L, Stripling C (2014) Wildfire initial response planning using probabilistically constrained stochastic integer programming. International Journal of Wildland Fire 23, 825-838.
| Crossref | Google Scholar |

Beverly JL (2017) Time since prior wildfire affects subsequent fire containment in black spruce. International Journal of Wildland Fire 26, 919.
| Crossref | Google Scholar |

Brooks M, Kristensen K, van , Benthem K, Magnusson A, Berg CW, Nielsen A, Skaug H, Mächler M, Bolker B (2017) glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R Journal 9, 378-400.
| Crossref | Google Scholar |

Burnham KP, Anderson DR (Eds) (2004) ‘Model selection and multimodel inference.’ (Springer New York: New York, NY, USA) 10.1007/b97636.

Cardil A, Lorente M, Boucher D, Boucher J, Gauthier S (2019) Factors influencing fire suppression success in the province of Quebec (Canada). Canadian Journal of Forest Research 49, 531-542.
| Crossref | Google Scholar |

Chabot M, Blanchet P, Drapeau P, Fortin J, Gauthier S, Imbeau L, Lacasse G, Lemaire G, Nappi A, Quenneville R, Thiffault E (2009) ‘Manuel de foresterie.’ (Editions MultiMondes: Québec City, CANADA) Available at http://ebookcentral.proquest.com/lib/ulaval/detail.action?docID=3374931

Canadian Interagency Forest Fire Centre (CIFFC) (2021) Glossaire Canadien des termes employés en gestion des incendies forestiers. (CIFFC). Available at https://ciffc.ca/sites/default/files/2020-12/Glossaire%20Canadien%20des%20termes%20employ%C3%A9s%20en%20gestion%20des%20incendies%20forestiers%202021.pdf.

CIFFC Training Working Group (2023) Canadian wildland fire glossary. Available at https://ciffc.ca/sites/default/files/2023-05/CWFM_glossary_v2023-04-24-EN.pdf.

Cumming SG (2005) Effective fire suppression in boreal forests. Canadian Journal of Forest Research 35, 772-786.
| Crossref | Google Scholar |

Dauni P, Firdaus MD, Asfariani R, Saputra MIN, Hidayat AA, Zulfikar WB (2019) Implementation of Haversine formula for school location tracking. Journal of Physics: Conference Series 1402, 077028.
| Crossref | Google Scholar |

Forestry Canada Fire Danger Group (1992) Development and Structure of the Canadian Forest Fire Behavior Prediction System. ST-X-3. (Hull). (Minister of Supply and Services Canada). Available at https://cfs.nrcan.gc.ca/publications?id=10068

Fortin J (1989) ‘Daily deployment of air tankers for initial attack on forest fires in the Province of Quebec.’ (University of Toronto: Ontario, Canada)

Hartig F (2022) DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. Available at https://CRAN.R-project.org/package=DHARMa

Hirsch K, Podur J, Janser R, McAlpine R, Martell D (2004) Productivity of Ontario initial-attack fire crews: results of an expert-judgement elicitation study. Canadian Journal of Forest Research 34, 705-715.
| Crossref | Google Scholar |

Hope ES, McKenney DW, Pedlar JH, Stocks BJ, Gauthier S (2016) Wildfire suppression costs for Canada under a changing climate. PLoS One 11, e0157425.
| Crossref | Google Scholar | PubMed |

Hothorn T, Bretz F, Westfall P (2008) Simultaneous inference in general parametric models. Biometrical Journal 50, 346-363.
| Crossref | Google Scholar | PubMed |

Lee Y, Fried JS, Albers HJ, Haight RG (2013) Deploying initial attack resources for wildfire suppression: spatial coordination, budget constraints, and capacity constraints. Canadian Journal of Forest Research 43, 56-65.
| Crossref | Google Scholar |

Lee Y, Lee B, Kim KH (2014) Optimal spatial allocation of initial attack resources for firefighting in the republic of Korea using a scenario optimization model. Journal of Mountain Science 11, 323-335.
| Crossref | Google Scholar |

Lüdecke D, Ben-Shachar M, Patil I, Waggoner P, Makowski D (2021) performance: An R Package for assessment, comparison and testing of statistical models. Journal of Open Source Software 6, 3139.
| Crossref | Google Scholar |

Ntaimo L, Gallego-Arrubla JA, Gan J, Stripling C, Young J, Spencer T (2013) A simulation and stochastic integer programming approach to wildfire initial attack planning. Forest Science 59, 105-117.
| Crossref | Google Scholar |

National Wildfire Coordinating Group (NWCG) (2024) NWCG glossary of wildland fire. Available at https://www.nwcg.gov/publications/pms205/nwcg-glossary-of-wildland-fire-pms-205

Parks GM (1964) Development and application of a model for suppression of forest fires. Management Science 10, 760.
| Crossref | Google Scholar |

Paudel A (2014) Characterizing the forest fire initial attack system in northeastern Ontario, Canada. (University of Toronto). Available at https://central.bac-lac.gc.ca/.item?id=TC-OTU-68051&op=pdf&app=Library&oclc_number=1033009755

Paudel A, Martell DL, Woolford DG (2019) Factors that affect the timing of the dispatch of initial attack resources to forest fires in northeastern Ontario, Canada. International Journal of Wildland Fire 28, 15-24.
| Crossref | Google Scholar |

Payette S (1992) Fire as a controlling process in the North American boreal forest. In ‘A systems analysis of the global boreal forest’. (Eds GB Bonan, HH Shugart, R Leemans) pp. 144–169. (Cambridge University Press: Cambridge) 10.1017/CBO9780511565489.006.

Plucinski MP (2012) Factors affecting containment area and time of Australian forest fires featuring aerial suppression. Forest Science 58, 390-398.
| Crossref | Google Scholar |

Plucinski MP, Dunstall S, McCarthy NF, Deutsch S, Tartaglia E, Huston C, Stephenson AG (2023) Fighting wildfires: predicting initial attack success across Victoria, Australia. International Journal of Wildland Fire 32, 1689-1703.
| Crossref | Google Scholar |

Rapp CE, Wilson RS, Toman EL, Jolly WM (2021) Assessing the role of short-term weather forecasts in fire manager tactical decision-making: a choice experiment. Fire Ecology 17, 35.
| Crossref | Google Scholar |

R Core Team (2022) R: A Language and Environment for Statistical Computing. Available at https://www.R-project.org/

Reimer J, Thompson DK, Povak N (2019) Measuring initial attack suppression effectiveness through burn probability. Fire 2, 60.
| Crossref | Google Scholar |

Rodrigues M, Alcasena F, Vega-García C (2019) Modeling initial attack success of wildfire suppression in Catalonia, Spain. Science of the Total Environment 666, 915-927.
| Crossref | Google Scholar | PubMed |

Symonds MRE, Moussalli A (2011) A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion. Behavioral Ecology and Sociobiology 65, 13-21.
| Crossref | Google Scholar |

Taylor SW, Woolford DG, Dean CB, Martell DL (2013) Wildfire prediction to inform fire management: statistical science challenges. Statistical Science 28, 586-615.
| Crossref | Google Scholar |

Transport Canada (1996) Canadian Aviation Regulations. Available at https://laws-lois.justice.gc.ca/PDF/SOR-96-433.pdf

Tymstra C, Stocks B, Cai X, Flannigan M (2019) Wildfire management in Canada: review, challenges and opportunities. Progress in Disaster Science 5, 100045.
| Crossref | Google Scholar |

Van Wagner CE (1987) Development and structure of the Canadian Forest Fire Weather Index System. (Canadian Foresty Service: Ottawa). Available at https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/19927.pdf

Wotton M, Nock C, Flannigan M (2010) Forest fire occurrence and climate change in Canada. International Journal of Wildland Fire 19, 253-271.
| Crossref | Google Scholar |

Wotton BM, Flannigan MD, Marshall GA (2017) Potential climate change impacts on fire intensity and key wildfire suppression thresholds in Canada. Environmental Research Letters 12, 095003.
| Crossref | Google Scholar |

Zuur AF, Ieno EN, Elphick CS (2010) A protocol for data exploration to avoid common statistical problems. Methods in Ecology and Evolution 1, 3-14.
| Crossref | Google Scholar |