Abstract
Abstract. Cellular automata have been successfully applied to simulate the propagation of wildfires with the aim of assisting fire managers in defining fire suppression tactics and in planning fire risk management policies. We present a cellular automaton designed to simulate a severe wildfire episode that took place in Algarve (southern Portugal) in July 2012. During the episode almost 25 000 ha burned and there was an explosive stage between 25 and 33 h after the onset. Results obtained show that the explosive stage is adequately modeled when introducing a wind propagation rule in which fire is allowed to spread to nonadjacent cells depending on wind speed. When this rule is introduced, deviations in modeled time of burning (from estimated time based on hot spots detected from satellite) have a root-mean-square difference of 7.1 for a simulation period of 46 h (i.e., less than 20 %). The simulated pattern of probabilities of burning as estimated from an ensemble of 100 simulations shows a marked decrease out of the limits of the observed scar, indicating that the model represents an added value to help decide locations of where to allocate resources for fire fighting.
Highlights
Wildfires in the Mediterranean region have severe damaging effects that are mainly caused by large fire events (Amraoui et al, 2013, 2015)
There is a fair agreement between the simulated burned area and the front lines of the fire as indicated by the hot spots identified by satellite, the simulated burning is well behind the fire front, an indication that the modeled propagation of the fire is too slow
The exception is the slot at 25 h, where the modeled propagation of fire is faster than the one suggested by the location of the hot spots
Summary
Wildfires in the Mediterranean region have severe damaging effects that are mainly caused by large fire events (Amraoui et al, 2013, 2015). Wildfire propagation is described in a variety of ways, be it the type of modeling (deterministic, stochastic), type of mathematical formulation (continuum, grid based), or type of propagation (nearest neighbor, Huygens wavelets), and often the formulation adopted combines different approaches (Sullivan, 2009; Alexandridis et al, 2011). Cellular automata (CA) are one of the most important stochastic models (Sullivan, 2009); space is discretized into cells, and physical quantities take on a finite set of values at each cell. Cells evolve in discrete time according to a set of transition rules and the states of the neighboring cells
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