Simple Spread Models for Understory Surface Fires

Surface fire frequently occurs beneath the canopy of North American forests under moderate wind speed and moisture-deficit conditions. Surface rate of spread (sROS) models can provide guidance for suppression operations and can be incorporated into fire growth modelling systems and other tools. We used a database of primarily Canadian experimental surface fires in conifer and deciduous stands from multiple sites to fit empirical sROS models for operational use and compare with pre-existing models. Various predictor combinations represented fires in boreal conifer (BOCON), deciduous, and Ponderosa pine-dominated stands, the latter analyzed to estimate grass-curing influence. The main predictors were wind speed (WS₁₀), estimated fuel moisture, and Canadian Fire Weather Index (FWI) System components (original and stand-adjusted). The ensuing fitted models (N = 51–93) were evaluated using standard metrics and tested using an independent conifer dataset (N = 26). The simplest model finds BOCON sROS to be equal to 1.2% of the WS₁₀, 1/7th the speed of crown fire spread under similar conditions; it is easily calculated as 20% of WS₁₀ using a common unit conversion (WS₁₀ in km h⁻¹, sROS in m min⁻¹). The best-performing sROS models displayed nonlinear-sigmoidal responses to wind and litter moisture variables, including the Initial Spread Index (ISI), and improved upon pre-existing models. Estimated accuracy was mostly +/− 2–4 m min⁻¹ within the range of the data in both training and validation datasets. These models reflect a dataset gathered from multiple sites using varying experimental methods. While imprecise, they are suitable for many applications, including operational forecasting and designing hazard reduction treatments.