Studying wildfire fronts using advection-diffusion-reaction models
Koondanibha Mitra, Qiyao Peng, Cordula Reisch
TL;DR
The paper addresses wildfire front propagation using advection--diffusion--reaction models that couple temperature $T$ and biomass $Y$, and introduces a persistent-fire variant to capture on/off combustion behavior. By non-dimensionalizing and applying a traveling-wave ansatz in one dimension, the authors reduce the problem to a semi-autonomous ODE system in $(u,v,z)$ with an unknown wave speed $c$ and develop a shooting method to locate traveling waves. Numerical experiments compare the full EF and PF PDEs with a linearized approximation, showing two TWs in the no-wind or mild-wind regime (one in each direction) and a single forward TW under strong wind, with solver agreement at the few-percent level. The work yields a practical framework for rapid prediction of wildfire front speeds under varying wind and parameter conditions and sets the stage for rigorous mathematical proofs and extensions to more complex geometries.
Abstract
In this work, we study the propagation of wildfires using an advection--diffusion--reaction model which also includes convective and radiative heat loss. An existing model is discussed \cite{asensio_2002} and a physically consistent modification of the model is proposed. Using this, the existence of travelling waves (TWs) in the one-dimensional case is investigated. Prior numerical studies reveal the existence of TWs \cite{reisch_2023}. Under the travelling wave ansatz and certain approximation, the model is reduced to a semi-autonomous dynamical system with three unknowns which can be analyzed by a shooting algorithm. It is hypothesized that under mild wind speeds, TWs in both directions exist, and under strong tailwinds only TWs in the direction of wind are possible. The theoretical implications are investigated using both solvers for the PDE models and the shooting algorithm. The results match, and unveil the dependence of the fronts on the parameters consistent with the predictions.
