Section: New Results
Model evaluation for fire propagation
Participants : Vivien Mallet, Jean-Baptiste Fillipi [CNRS] , Bahaa Nader [University of Corsica] .
In the field of forest fires risk management, important challenges exist in terms of people and goods preservation. Answering to strong needs from different actors (firefighters, foresters), researchers focus their efforts to develop operational decision support system tools that may forecast wildfire behavior. This requires the evaluation of model performance, but currently, simulation errors are not sufficiently qualified and quantified.
We consider that the proper evaluation of a model requires to apply it to a large number of fires – instead of carrying out a fine tuning on just one fire. We implemented a software to simulate a large number of fires (from the Prométhée database, http://www.promethee.com/ ) with the simulation model ForeFire (CNRS/University of Corsica) and evaluate the results with error measures  . One simulation requires mainly the following data: the ignition point, the ground elevation, the vegetation cover and the wind field. See illustration in Fig. 6 . We simulated 80 fires with four physical models, which proved that the most advanced models performed better overall, even though the input data is often inaccurate. We also carried out Monte Carlo simulations to evaluate the impact of the uncertainty in input data. We showed that the Monte Carlo approach led to a reliable forecasting system, which suggests that the probability densities derived from the simulations (see Fig. 6 ) may be useful information for preventive actions in an operational context.