Price Owen F, Penman Trent, Bradstock Ross, Borah Rittick
Centre for Environmental Risk Management of Bushfires, Institute for Conservation Biology and Management, University of Wollongong, NSW 2522, Australia.
Centre for Environmental Risk Management of Bushfires, Institute for Conservation Biology and Management, University of Wollongong, NSW 2522, Australia; Department of Forest and Ecosystem Sciences, University of Melbourne, Water Street, Creswick, VIC 3363, Australia.
J Environ Manage. 2016 Oct 1;181:208-217. doi: 10.1016/j.jenvman.2016.06.033. Epub 2016 Jun 27.
Wildfires are complex adaptive systems, and have been hypothesized to exhibit scale-dependent transitions in the drivers of fire spread. Among other things, this makes the prediction of final fire size from conditions at the ignition difficult. We test this hypothesis by conducting a multi-scale statistical modelling of the factors determining whether fires reached 10 ha, then 100 ha then 1000 ha and the final size of fires >1000 ha. At each stage, the predictors were measures of weather, fuels, topography and fire suppression. The objectives were to identify differences among the models indicative of scale transitions, assess the accuracy of the multi-step method for predicting fire size (compared to predicting final size from initial conditions) and to quantify the importance of the predictors. The data were 1116 fires that occurred in the eucalypt forests of New South Wales between 1985 and 2010. The models were similar at the different scales, though there were subtle differences. For example, the presence of roads affected whether fires reached 10 ha but not larger scales. Weather was the most important predictor overall, though fuel load, topography and ease of suppression all showed effects. Overall, there was no evidence that fires have scale-dependent transitions in behaviour. The models had a predictive accuracy of 73%, 66%, 72% and 53% accuracy at 10 ha, 100 ha, 1000 ha and final size scales. When these steps were combined, the overall accuracy for predicting the size of fires was 62%, while the accuracy of the one step model was only 20%. Thus, the multi-scale approach was an improvement on the single scale approach, even though the predictive accuracy was probably insufficient for use as an operational tool. The analysis has also provided further evidence of the important role of weather, compared to fuel, suppression and topography in driving fire behaviour.
野火是复杂适应系统,据推测其在火灾蔓延驱动因素方面呈现出尺度依赖的转变。除此之外,这使得从点火时的条件预测最终火灾规模变得困难。我们通过对决定火灾是否达到10公顷、100公顷、1000公顷以及超过1000公顷的最终规模的因素进行多尺度统计建模来检验这一假设。在每个阶段,预测变量包括天气、燃料、地形和灭火措施。目标是识别模型之间表明尺度转变的差异,评估预测火灾规模的多步方法的准确性(与从初始条件预测最终规模相比),并量化预测变量的重要性。数据来自1985年至2010年在新南威尔士州桉树林发生的1116起火灾。不同尺度下的模型相似,尽管存在细微差异。例如,道路的存在影响火灾是否达到10公顷,但对更大尺度没有影响。总体而言,天气是最重要的预测变量,尽管燃料负荷、地形和灭火难易程度都有影响。总体而言,没有证据表明火灾在行为上有尺度依赖的转变。这些模型在10公顷、100公顷、1000公顷和最终规模尺度下的预测准确率分别为73%、66%、72%和53%。当这些步骤结合起来时,预测火灾规模的总体准确率为62%,而单步模型的准确率仅为20%。因此,多尺度方法比单尺度方法有所改进,尽管预测准确率可能不足以用作操作工具。该分析还进一步证明了与燃料、灭火和地形相比,天气在驱动火灾行为方面的重要作用。