Modeling Wildland Fire Propagation with Level Set Methods

TL;DR

This paper demonstrates how level set methods can effectively model wildland fire spread, addressing topological challenges and providing a flexible computational tool for fire prediction and management.

Contribution

It integrates level set techniques with firespread modeling, introduces a new open-source 2D code, and discusses future directions for fire simulation and decision support.

Findings

Successfully modeled firefront evolution in numerical experiments.

Addressed topological challenges like island swallowing and front merging.

Provided a versatile, extensible computational tool for wildland fire prediction.

Abstract

Level set methods are versatile and extensible techniques for general front tracking problems, including the practically important problem of predicting the advance of a firefront across expanses of surface vegetation. Given a rule, empirical or otherwise, to specify the rate of advance of an infinitesimal segment of firefront arc normal to itself (i.e., given the firespread rate as a function of known local parameters relating to topography, vegetation, and meteorology), level set methods harness the well developed mathematical machinery of hyperbolic conservation laws on Eulerian grids to evolve the position of the front in time. Topological challenges associated with the swallowing of islands and the merger of fronts are tractable. The principal goals of this paper are to: collect key results from the two largely distinct scientific literatures of level sets and firespread; demonstrate the practical value of level set methods to wildland fire modeling through numerical experiments; probe and address current limitations; and propose future directions in the simulation of, and the development of decision-aiding tools to assess countermeasure options for, wildland fires. In addition, we introduce a freely available two-dimensional level set code used to produce the numerical results of this paper and designed to be extensible to more complicated configurations.