Fire-spotting modelling in operational wildfire simulators based on cellular automata: a comparison study.

Abstract

One crucial mechanism in the spread of wildfires is the so-called fire-spotting: a random phenomenon which occurs when embers are transported over large

distances. Fire-spotting speeds up the Rate of Spread and starts new igni- tions which constitute a menace for fire fighting operations. Unfortunately,

operational fire-spread simulators may not account for spotting e↵ects, thus overlooking the harmful consequences associated with this phenomenon. In this work, several fire spotting methods are integrated in the operational

wildfire simulator PROPAGATOR based on Cellular Automata (CA). Ran- domFront, a physics-based parametrization of fire-spotting, is tested for the

first time in the context of CA simulators. RandomFront is compared with other two parametrizations already adopted in CA based simulators, the ones of Alexandridis et al. and Perryman et al. A wildfire occurred in the summer of 2021 in the municipality of Campomarino (Molise, Italy), and where spotting e↵ects were clearly reported, has been used as a study case. RandomFront parametrization produced a more complex burnt probability

pattern than the other models. Moreover, it predicted higher burning proba- bility in the area of the domain a↵ected by spotting e↵ects in the real wildfire

event.