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Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Extension of the Balbi fire spread model to include the field scale conditions of shrubland fires

François Joseph Chatelon A , Jacques Henri Balbi A , Miguel G. Cruz https://orcid.org/0000-0003-3311-7582 B , Dominique Morvan C , Jean Louis Rossi A , Carmen Awad A , Nicolas Frangieh A , Jacky Fayad A and Thierry Marcelli A D
+ Author Affiliations
- Author Affiliations

A Systèmes Physiques pour l’Environnement UMR-CNRS 6134, Université de Corse, Campus Grossetti, BP 52 20250 Corte, France.

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

C Centre national de la Recherche Scientifique (CNRS), Aix-Marseille Université, Centrale Marseille, M2P2, Marseille, France.

D Corresponding author. Email: marcelli_t@univ-corse.fr

International Journal of Wildland Fire 31(2) 176-192 https://doi.org/10.1071/WF21082
Submitted: 10 June 2021  Accepted: 24 November 2021   Published: 25 January 2022

Abstract

The ‘Balbi model’ is a simplified rate of fire spread model aimed at providing computationally fast and accurate simulations of fire propagation that can be used by fire managers under operational conditions. This model describes the steady-state spread rate of surface fires by accounting for both radiation and convection heat transfer processes. In the present work the original Balbi model developed for laboratory conditions is improved by addressing specificities of outdoor fires, such as fuel complexes with a mix of live and dead materials, a larger scale and an open environment. The model is calibrated against a small training dataset (n = 25) of shrubland fires conducted in Turkey. A sensitivity analysis of model output is presented and its predictive capacity against a larger independent dataset of experimental fires in shrubland fuels from different regions of the world (Europe, Australia, New Zealand and South Africa) is tested. A comparison with older versions of the model and a generic empirical model is also conducted with encouraging results. The improved model remains physics-based, faster than real time and fully predictive.

Keywords: Balbi model, fire spread, shrubs, live fuel, radiation, convection, fire dynamics, model performance, physical model, steady-state model.


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