We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981-2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981-2010, 2011-2040, and 2041-2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041-2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities.
Abstract. Wildfire simulators based on empirical or physical models need to be locally calibrated and validated when used under conditions that differ from those where the simulators were originally developed. This study aims to calibrate the FARSITE fire spread model considering a set of recent wildfires that occurred in northern Iranian forests. Sitespecific fuel models in the study areas were selected by sampling the main natural vegetation type complexes and assigning standard fuel models. Overall, simulated fires presented reliable outputs that accurately replicated the observed fire perimeters and behavior. Standard fuel models of Scott and Burgan (2005) afforded better accuracy in the simulated fire perimeters than the standard fuel models of Anderson (1982). The best match between observed and modeled burned areas was observed on herbaceous fuel models. Fire modeling showed a high potential for estimating spatial variability in fire spread and behavior in the study areas. This work represents a first step in the application of fire spread modeling in northern Iran for wildfire risk monitoring and management.
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