Assessing fire risk using Monte Carlo simulations of fire spread |
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Authors: | Yohay Carmel Shlomit Paz Faris Jahashan Maxim Shoshany |
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Affiliation: | 1. Faculty of Civil and Environmental Engineering, Technion-Israel Institute of Technology, Haifa, Israel;2. Department of Geography and Environmental Studies, University of Haifa, Haifa, Israel |
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Abstract: | Understanding the spatial pattern of fire is essential for Mediterranean vegetation management. Fire-risk maps are typically constructed at coarse resolutions using vegetation maps with limited capacity for prescribing prevention activities. This paper describes and evaluates a novel approach for fire risk assessment that may produce a decision support system for actual fire management at fine scales. FARSITE, a two-dimensional fire growth and behavior model was activated, using ArcView VBA code, to generate Monte Carlo simulations of fire spread. The study area was 300 km2 of Mt. Carmel, Israel. FARSITE fuel models were adjusted for Mediterranean conditions. The simulation session consisted of 500 runs. For each simulation run, a calendar date, fire length, ignition location, climatic data and other parameters were selected randomly from known distributions of these parameters. Distance from road served as a proxy for the probability of ignition. The resulting 500 maps of fire distribution (the entire area burnt in a specific fire) were overlaid to produce a map of ‘hotspots’ and ‘cold spots’ of fire frequency. The results revealed a clear pattern of fires, with high frequency areas concentrated in the northwestern part. The spatial pattern of the fire frequency map bears partial resemblance to the fuel map, but seems to be affected by several other factors as well, including the location of urban areas, microclimate, topography and the distribution of ignition locations (which is affected by road pattern). These results demonstrate the complexities of fire behavior, showing a very clear pattern of risk level even at fine scales, where neighboring areas have different risk levels due to combinations of vegetation cover, topography, microclimate and other factors. |
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Keywords: | Fire risk Fire behavior Fire spread model Monte Carlo simulation Fire management |
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