Thompson Matthew P, Carriger John F
Human Dimensions Program, USDA Forest Service, Fort Collins, CO, United States.
Office of Research and Development, US Environmental Protection Agency, Cincinnati, OH, United States.
Front For Glob Change. 2023 Nov 8;6:1-9. doi: 10.3389/ffgc.2023.1266413.
Assessing the effectiveness and measuring the performance of fuel treatments and other wildfire risk mitigation efforts are challenging endeavors. Perhaps the most complicated is quantifying avoided impacts. In this study, we show how probabilistic counterfactual analysis can help with performance evaluation. We borrow insights from the disaster risk mitigation and climate event attribution literature to illustrate a counterfactual framework and provide examples using ensemble wildfire simulations. Specifically, we reanalyze previously published fire simulation data from fire-prone landscapes in New Mexico, USA, and show applications for post-event analysis as well as pre-event evaluation of fuel treatment scenarios. This approach found that treated landscapes likely would have reduced fire risk compared to the untreated scenarios. To conclude, we offer ideas for future expansions in theory and methods.
评估燃料处理及其他野火风险缓解措施的有效性并衡量其绩效是具有挑战性的工作。或许最复杂的是量化避免的影响。在本研究中，我们展示了概率性反事实分析如何有助于绩效评估。我们借鉴灾害风险缓解和气候事件归因文献中的见解来说明一个反事实框架，并提供使用集合野火模拟的示例。具体而言，我们重新分析了美国新墨西哥州火灾频发地区先前发表的火灾模拟数据，并展示了其在事件后分析以及燃料处理情景的事前评估中的应用。该方法发现，与未处理的情景相比，经过处理的地区可能降低了火灾风险。最后，我们提出了未来理论和方法扩展的思路。
