The ‘Balbi model’ is a simplified steady-state physical propagation model for surface fires that considers radiative heat transfer from the surface area of burning fuel particles as well as from the flame body. In this work, a completely new version of this propagation model for wildand fires is proposed. Even if, in the present work, this model is confined to laboratory experiments, its purpose is to be used at a larger scale in the field under operational conditions. This model was constructed from a radiative propagation model with the addition of a convective heat transfer term resulting from the impingement of packets of hot reacting gases on unburnt fuel elements located at the base of the flame. The flame inside the fuel bed is seen as the ‘fingers of fire’ described in the literature. The proposed model is physics-based, faster than real time and fully predictive, which means that model parameters do not change from one experiment to another. The predicted rate of spread is applied to a large set of laboratory experiments (through homogeneous pine needles and excelsior fuel beds) and is compared with the predictions of both a very simple empirical model (Catchpole) and a detailed physical model (FireStar2D).

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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.

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