Articles | Volume 14, issue 11
Nat. Hazards Earth Syst. Sci., 14, 3077–3091, 2014
https://doi.org/10.5194/nhess-14-3077-2014

Special issue: Numerical wildland combustion, from the flame to the...

Nat. Hazards Earth Syst. Sci., 14, 3077–3091, 2014
https://doi.org/10.5194/nhess-14-3077-2014

Research article 27 Nov 2014

Research article | 27 Nov 2014

Evaluation of forest fire models on a large observation database

J. B. Filippi1, V. Mallet2,3, and B. Nader1 J. B. Filippi et al.
  • 1Centre National de la Recherche Scientifique, Sciences Pour l'Environnement, Université di Corsica, BP 52, 20250 Corte, France
  • 2Institut National de Recherche en Informatique et en Automatique, BP 105, 78 153 Le Chesnay CEDEX, France
  • 3Centre d'Enseignement et de Recherche en Environnement Atmosphérique (joint laboratory \'Ecole des Ponts ParisTech & EDF R & D, Université Paris Est), Marne-la-Vallée, France

Abstract. This paper presents the evaluation of several fire propagation models using a large set of observed fires. The observation base is composed of 80 Mediterranean fire cases of different sizes, which come with the limited information available in an operational context (burned surface and approximative ignition point). Simulations for all cases are carried out with four different front velocity models. The results are compared with several error scoring methods applied to each of the 320 simulations. All tasks are performed in a fully automated manner, with simulations run as first guesses with no tuning for any of the models or cases. This approach leads to a wide range of simulation performance, including some of the bad simulation results to be expected in an operational context. Disregarding the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more empirical ones. Data and source codes used for this paper are freely available to the community.

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Short summary
A set of 80 Mediterranean fire cases is used as an observation database for model evaluation. Simulations are carried out with 4 different front velocity models. The results are compared with several error scoring methods. All simulations are performed as automatic first guesses with no tuning, as an operational use. Regardless of the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more empirical one.
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