Fuel treatment effectiveness in the context of landform, vegetation, and large, wind-driven wildfires.
Fuel treatment effectiveness in the context of landform, vegetation, and large, wind-driven wildfires.
复制标题
地形、植被和大型风驱动野火背景下的燃料处理效果。
DOI：
10.2737/rds-2020-0003
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
D. Peterson
中科院分区：
文献类型：
--
作者：
S. Prichard;N. Povak;M. Kennedy;D. Peterson
在美国西部的半干旱地区，大型野火（> 50，000公顷）越来越常见。虽然燃料减少处理用于减轻潜在的野火影响，但它们在具有极端火灾行为的风力驱动野火事件中可能会被淹没。我们评估了2014年卡尔顿综合体火灾严重程度和燃料处理有效性的驱动因素，这是华盛顿州中北部创纪录的野火综合体。在不同的地形，植被和不同的火灾进展，我们使用了同步自回归（SAR）和随机森林（RF）的方法相结合的模型火灾严重程度的驱动程序，并评估如何燃料处理减轻火灾的严重程度。预测变量包括燃料处理类型，治疗后的时间，地形指数，植被和燃料，以及按进展间隔总结的天气。我们发现，这两种空间回归方法一般是互补的，并作为一种组合的方法火灾的严重性景观分析是有益的。SAR改进了传统的线性模型，通过纳入有关相邻像素烧伤严重程度的信息，避免了系数估计和不正确的推断中的I型错误。RF建模提供了一个灵活的建模环境，能够捕捉复杂的相互作用和非线性，同时仍然占空间自相关通过使用空间显式预测变量。所有治疗领域燃烧的比例较高的中度和高度严重的火灾在早期火灾进展，但薄和欠烧，欠烧，过去的野火比薄，薄和堆烧伤治疗更有效。治疗单位有更大的百分比未燃烧和低严重程度的地区在后来的进展，燃烧在温和的火灾天气条件下，治疗之间的差异不太明显。我们的研究结果提供的证据表明，战略布局的燃料减少处理可以有效地减少局部火灾蔓延和严重程度，即使在恶劣的火灾天气。在风力驱动的火灾蔓延进展，燃料处理，位于背风坡往往有较低的火灾严重性比处理位于迎风坡。当火灾和燃料管理人员评估提高景观对未来气候变化和野火的适应能力的选择时，燃料处理的战略布局可能会受到对过去大型野火事件的回顾性研究的指导。
Large wildfires (>50,000 ha) are becoming increasingly common in semi-arid landscapes of the western United States. Although fuel reduction treatments are used to mitigate potential wildfire effects, they can be overwhelmed in wind-driven wildfire events with extreme fire behavior. We evaluated drivers of fire severity and fuel treatment effectiveness in the 2014 Carlton Complex, a record-setting complex of wildfires in north-central Washington State. Across varied topography, vegetation and distinct fire progressions, we used a combination of simultaneous autoregression (SAR) and random forest (RF) approaches to model drivers of fire severity and evaluated how fuel treatments mitigated fire severity. Predictor variables included fuel treatment type, time since treatment, topographic indices, vegetation and fuels, and weather summarized by progression interval. We found that the two spatial regression methods are generally complementary and are instructive as a combined approach for landscape analyses of fire severity. SAR improves upon traditional linear models by incorporating information about neighboring pixel burn severity, which avoids type I errors in coefficient estimates and incorrect inferences. RF modeling provides a flexible modeling environment capable of capturing complex interactions and non-linearities while still accounting for spatial autocorrelation through the use of spatially explicit predictor variables. All treatment areas burned with higher proportions of moderate and high severity fire during early fire progressions, but thin and underburn, underburn only, and past wildfires were more effective than thin-only and thin and pile burn treatments. Treatment units had much greater percentages of unburned and low severity area in later progressions that burned under milder fire weather conditions, and differences between treatments were less pronounced. Our results provide evidence that strategic placement of fuels reduction treatments can effectively reduce localized fire spread and severity even under severe fire weather. During wind-driven fire spread progressions, fuel treatments that were located on leeward slopes tended to have lower fire severity than treatments located on windward slopes. As fire and fuels managers evaluate options for increasing landscape resilience to future climate change and wildfires, strategic placement of fuel treatments may be guided by retrospective studies of past large wildfire events.