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Modeling fire susceptibility in west central Alberta, Canada   总被引:1,自引:0,他引:1  
Strategic modification of forest vegetation has become increasingly popular as one of the few preemptive activities that land managers can undertake to reduce the likelihood that an area will be burned by a wildfire. Directed use of prescribed fire or harvest planning can lead to changes in the type and arrangement of forest vegetation across the landscape that, in turn, may reduce fire susceptibility across large areas. While among the few variables that fire managers can influence, fuel conditions are only one of many factors that determine fire susceptibility. Variations in weather and topography, in combination with fuels, determine which areas are more likely to burn under a given fire regime. An understanding of these combined factors is necessary to identify high fire susceptibility areas for prioritizing and evaluating strategic fuel management activities, as well as informing other fire management activities, such as community protection planning and strategic level allocation of fire suppression resources across a management area. We used repeated fire growth simulations, automated in the Burn-P3 landscape-fire simulation model, to assess spatial variations in fire susceptibility across a 2.4 million ha study area in the province of Alberta, Canada. The results were used to develop a Fire Susceptibility Index (FSI). Multivariate statistical analyses were used to identify the key factors that determine variation in FSI across the study area and to describe the spatial scale at which these variables influence fire susceptibility at a given location. A fuel management scenario was used to assess the impact of prescribed fire treatments on FSI. Results indicated that modeled fire susceptibility was strongly influenced by fuel composition, fuel arrangement, and topography. The likelihood of high or extreme FSI values at a given location was strongly associated with the percent of conifer forest within a 2-km radius, and with elevation and ignition patterns within a 5-km radius. Results indicated that prescribed fire treatments can be effective at reducing forest fire susceptibility in community protection zones and that simulation modeling is an effective means of evaluating spatial variation in landscape fire susceptibility.  相似文献   
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Management around wilderness parks ideally requires thorough fire suppression in proximate settled and commercially exploited lands and natural fire within protected areas. To satisfy these requirements, we explored a potential regional firebreak (firewall) based on a series of prescribed burns in Quetico Provincial Park in northwestern Ontario, Canada. Fire managers were recruited each to independently devise a regional firebreak using simulated prescribed burns. The experts’ five designs consisted of between 9 and 25 prescribed burns, set over periods ranging from 3 to 8 years, and covering from 7900 to 26,100 ha. Each wildlife ignition was run after the entire firebreak was created and the vegetation was reclassified to account for post-fire vegetation re-growth. The potential efficacy of each design was tested using worst-case historical weather and 100 random ignitions in the Prometheus fire growth simulation model. Without a firewall, 100 ignitions resulted in 69 fires escaping the park and consuming 483,900 ha of forest beyond the park boundary. The firewall designs were all effective, reducing the area burned outside the park to between 15,400 and 35,400 ha. There was a 77–90% reduction in the number of fires escaping the firewall areas and an average reduction of fire area beyond the park of 92%. Moreover, one can map the geographic weak points in each design, which encourages iterative firebreak design improvements. For instance, firewalls set nearer the park boundary allowed fewer fires to start between the firewall and the boundary, so increasing firebreak effectiveness. The cost of the above systems can be regarded as taking preventative measures against the risk of future economic loss, and the modeling approach reduces the uncertainties in associated decision making.  相似文献   
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