Background Model simulations of wildfire spread are critically needed for the management and study of shifting fire regimes in semiarid regions, especially for the expanding cheatgrass-fire cycle in the vast sagebrush steppe of North America. By comparing simulated fire-spread to actual wildfire patterns, managers and researchers can gauge the reliability and accuracy of fire-spread models and their fuel inputs, but this requires pre-fire vegetation and information that are typically only available from modeled data, especially for megafires. We assessed the fire-spread model accuracy of Fire-Area Simulator (FARSITE) using alternative fuel-input options for the 2015 Soda Fire (110,000 ha of sagebrush steppe burned in 6 days in Oregon and Idaho, USA) and then assessed model transferability to another fire. Results Parameterizing FARSITE with the fuel inputs from LANDFIRE resulted in low levels of agreement between simulated and observed area burned, with maximum Sorensen’s coefficient (SC) and Cohen’s Kappa (K) values of only 0.38 and 0.36, respectively. To improve burned-area agreement, we tested alternative, customized fuels-input using unsupervised classification of satellite-derived vegetation maps from the Rangeland Analysis Platform (RAP) and determined how different options for aligning the resulting land-cover classifications to standard fire behavior fuel models (FBFMs) affected FARSITE accuracy. Using RAP to inform FBFM selection led to much greater agreement between FARSITE simulations and the observed burn perimeter (SC=0.70, K=0.68). The RAP-based land cover parameterization of FBFMs developed for the Soda wildfire was used for FARSITE simulations of another wildfire within the region (Cherry Road, burned 2016) and led to high accuracy (SC=0.80, K=0.79) Conclusions Using RAP to inform FBFM selection increases the accuracy of FARSITE simulations of burn perimeters compared to the current standard of pre-mapped FBFMs from LANDFIRE, in sagebrush steppe. The method appears to have regional generalizability, meaning that the full FBFM-selection process performed here may not be necessary for each individual fire. Flanking and backfires were the primary source of disagreements between simulated and observed fire spread in FARSITE, which are sources of error that may require modeling of lateral heterogeneity in fuels and fire processes at relatively finer scales than used here.

Background Model simulations of wildfire spread and assessments of their accuracy are needed for understanding and managing altered fire regimes in semiarid regions. The accuracy of wildfire spread simulations can be evaluated from post hoc comparisons of simulated and actual wildfire perimeters, but this requires information on pre-fire vegetation fuels that is typically not available. We assessed the accuracy of the Fire-Area Simulator (FARSITE) model parameterized with maps of fire behavior fuel models (FBFMs) obtained from the widely used LANDFIRE, as well as alternative means which utilized the classification of Rangeland Analysis Platform (RAP) satellite-derived vegetation cover maps to create FBFM maps. We focused on the 2015 Soda wildfire, which burned 113,000 ha of sagebrush steppe in the western USA, and then assessed the transferability of our RAP-to-FBFM selection process, which produced the most accurate reconstruction of the Soda wildfire, on the nearby 2016 Cherry Road wildfire. Results Parameterizing FARSITE with maps of FBFMs from LANDFIRE resulted in low levels of agreement between simulated and observed area burned, with maximum Sorensen’s coefficient (SC) and Cohen’s kappa (K) values of 0.38 and 0.36, respectively. In contrast, maps of FBFMs derived from unsupervised classification of RAP vegetation cover maps led to much greater simulated-to-observed burned area agreement (SC = 0.70, K = 0.68). The FBFM map that generated the greatest simulated-to-observed burned area agreement for the Soda wildfire was then used to crosswalk FBFMs to another nearby wildfire (2016 Cherry Road), and this FBFM selection led to high FARSITE simulated-to-observed burned area agreement (SC = 0.80, K = 0.79). Conclusions Using RAP to inform pre-fire FBFM selection increased the accuracy of FARSITE simulations compared to parameterization with the standard LANDFIRE FBFM maps, in sagebrush steppe. Additionally, the crosswalk method appeared to have regional generalizability. Flanking and backfires were the primary source of disagreements between simulated and observed fire spread in FARSITE, which are sources of error that may require modeling of lateral heterogeneity in fuels and fire processes at finer scales than used here.