Local Scale Fuel Type Mapping and Surface Fire Behavior Prediction Using FARSITE (Case study: Toshi Forest-Siahkal)

Iranian Northern forests have been subject to increased wildfire in recent years. The area and intensity of these fires is strongly dependent upon the type of fuels and its spatial variability across the Landscape. It is very important to develop accurate ways to assess fuel characteristics and predict the probability of fires occurring in heterogeneous landscapes for fire prevention and management. The objectives of this research were to build local scale fuel type map and simulate their fire behavior. The spatial extent of the different fuel types of Toshi forest in Siahkal characterized by heterogeneous vegetation and topography was determined using a field survey. Utilizing the spatial database capabilities of GIS, FARSITE fire area simulator was used to modeling potential wildfire spread and behavior. Four different fuel types (grass, grass-shrub, natural forest and plantation) of the study area were analyzed. The fuel types were developed by field sampling and the collected data was inserted in the FARSITE simulator. The simulation results revealed that the fuel type for the shrublands and natural forests demonstrated the longest flame length, the highest fireline intensity and the greatest heat release per unit area. The fuel type for the grass fields presented the fastest surface rate of spread; and the fuel type for the plantation the lower fire intensity. The fire behavior maps are an end product which can be fully exploited operationally from local fire management authorities without further processing for an effective wildfire management and proactive emergency response.