Estimating the effects of meteorology and land cover on fire growth in Peru using a novel difference equation model

Abstract

Statistical analyses of wildfire growth are rarely undertaken, particularly in South America. In this study, we describe a simple and intuitive difference equation model of wildfire growth that uses a spread parameter to control the radial speed of the modeled fire and an extinguish parameter to control the rate at which the burning perimeter becomes inactive. Using data from the GlobFire project, we estimate these two parameters for 1003 large, multi-day fires in Peru between 2001 and 2020. For four fire-prone ecoregions within Peru, a set of 24 generalized linear models are fit for each parameter that use fire danger indexes and land cover covariates. Akaike weights are used to identify the best-approximating model and quantify model uncertainty. We find that, in most cases, increased spread rates and extinguish rates are positively associated with fire danger indexes. When fire danger indexes are included in the models, the spread component is usually the best choice, but we also find instances when the fire weather index and burning index are selected. We also find that grassland cover is positively associated with spread rates and extinguish rates in tropical forests, and that anthropogenic cover is negatively associated with spread rates in xeric ecoregions. We explore potential applications of this model to wildfire risk assessment and burned area forecasting.