We present in this study a firebrand model developed for landscape-scale fire spread simulators. The firebrand model features three components used to describe generation, transport and spot ignition. The firebrand generation model uses an empirical relationship based on the heat release rate of the fire. The firebrand transport model uses a prescribed statistical distribution for downwind ember flight distance combined with a model for flight time. The firebrand ignition model considers two scenarios: in wildland fires, the model assumes that spot ignition results from the landing of a single firebrand in flaming state and features a single time delay associated with the growth from a small flame to a large spreading flame; in contrast, in wildland-urban-interface fires, the model assumes that structure ignition results from the ground accumulation of firebrands in smoldering state and features two consecutive time delays, a first delay associated with the occurrence of a small flame due to smoldering-to-flaming transition and based on an empirically-derived probability of ignition, and a second delay similar to that considered in the wildland fire scenario. The modeling capability is coded in MATLAB for ease of analysis and is tested in a series of one-dimensional verification tests. The results of the verification tests show that the firebrand models are “converged”, i.e., are insensitive to changes in numerical resolution provided that the value of the wind-based Courant-Friedrichs-Lewy number is sufficiently low. These results provide a solid mathematical foundation for simulations of firebrand effects in landscape-scale fire spread simulators. • A framework to model firebrand generation, transport and ignition is presented. • The firebrand model is integrated into a landscape-scale fire spread simulator. • The firebrand ignition model describes the growth from a small to a large flame. • The WUI firebrand ignition model describes smoldering-to-flaming transition (SFT). • The description of SFT uses a semi-empirical probability of ignition model. • The model sensitivity to changes in spatial and temporal resolution is evaluated.
Qin et al. (Sun,) studied this question.