EAGER: Predicting Wind-Aided Spread of Large-Area Fire in Real Time: Toward an Objective Aid for Decision-Making

EAGER：实时预测风助大面积火灾蔓延：为决策提供客观帮助

• 批准号: 1249627
• 负责人: Francis Fendell
• 金额: $ 5.99万
• 依托单位: Northrop Grumman Aerospace Systems
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1249627&HistoricalAwards=false
• 关键词: EAGER; Predicting; Wind; Aided; Spread

#1249627Francis FendellIndiscriminate fighting of wildland fire can be costly, unsafe, ineffective, counterproductive (may result in soil-destruction), and ecologically more harmful in its execution and consequences than the fire itself. At a large-area wildland-fire incident, under the Incident Command System, the highest-priority information sought by the key decision-maker regarding response, the Incident Commander (IC), concerns firespread. Given where the actively flaming firefront is currently located, and given locally pertinent information on topography and vegetation and meteorology, where will the firefront be located six-to-seven hours in the future, both in the absence of intervention with firefighting countermeasures and with such intervention? Better guidance is continually sought from the in-place Wildland Fire Decision Support System, created under the lead of the United States Department of Agriculture Forest Service, with assistance from the United States Department of Interior land-management agencies. Can more adequate objective prognostic aids be generated for real-time support of decision-making by responders to wildland fire? Here, a systematic approach with three fairly autonomous components is outlined: (1) collection of data on topography, vegetation, and meteorology, with emphasis on meteorology, typically the crucial, short-time-scale variable; (2) systematic laboratory-scale testing under well-characterized, well-controlled conditions in a novel facility dedicated to measurement of the quasisteady rate of firespread as a function of the just-discussed data; and (3) utilization of level-set methods to evolve, in real time, the firefront evolution under the just-discussed semi-empirical rate of firespread, so that an ensemble of realizations permits the uncertainty (robustness) of the forecast to be assessed. A treatment with a one-way interaction between the weather and the firefront, idealized as without structure, adequately encompasses the preponderance of wildland fires encountered by wildland-fire responders. The third component, utilizing limited but already-in-hand spread rates, is to be undertaken first. The goal is to generate and validate an openly accessible, fast-running, robust, readily portable, well documented, easily modified, fire-growth-prediction computer code, useful to both a novice and a specialist in wildland-fire behavior.By developing a computer code that applies well-suited level-set methods to firefront evolution, many basic issues impeding a practically important implementation of what remains a mathematical prescription will be addressed. An accurate, efficient quantitative aid for wildland-fire growth has multiple pre-incident applications (e.g., siting of roads, reservoirs, and firebreaks), during-incident applications (e.g., comparison of alternate firefighting strategies and justification of evacuation orders), and post-incident applications (e.g., certification of personnel and assistance with wildfire-related litigation). The project is transformational re: use of laboratory testing in firespread research; adoption of the ?fire-use? (restrained-response) option by decision-makers; and expediting operational firespread forecasts.

#1249627弗朗西斯·芬德尔不分青红皂白地扑灭野火可能代价高昂、不安全、无效、适得其反（可能导致土壤破坏），而且在执行过程和后果方面对生态的危害比火灾本身更大。在大范围野火事件中，在事件指挥系统下，关键决策者在响应方面寻求的最高优先级信息，即事件指挥官（IC），涉及到消防系统。考虑到火场目前所处的位置，并考虑到当地有关地形、植被和气象的信息，在没有灭火对策干预和有这种干预的情况下，未来6至7小时火场将位于何处？在美国农业部林业局的领导下，在美国内政部土地管理机构的协助下，建立了现有的荒地火灾决策支助系统，不断寻求更好的指导。是否可以产生更充分的客观预测辅助工具，以实时支持野火响应者的决策？本文概述了一种包含三个相当独立的组成部分的系统方法：(1)收集地形、植被和气象数据，重点放在气象学上，气象学通常是关键的短时间尺度变量；(2)系统的实验室规模的测试，在良好的表征，良好的控制条件下，在一个新的设施中，专门用于测量火焰蔓延的准稳态速率，作为刚刚讨论的数据的函数；(3)利用水平集方法在刚刚讨论的火蔓延半经验速率下实时演化火线演化，从而使实现的集合允许对预测的不确定性（鲁棒性）进行评估。天气和火场之间的单向相互作用的处理，理想地没有结构，充分包括野火响应者遇到的野火优势。第三部分，利用有限但已经掌握的传播率，将首先进行。目标是生成并验证一个可公开访问、快速运行、健壮、易于移植、文档完备、易于修改的火灾增长预测计算机代码，对新手和研究野火行为的专家都很有用。通过开发一种将非常适合的水平集方法应用于前线进化的计算机代码，将解决许多阻碍实际重要实现仍然是数学处方的基本问题。对野火增长的准确、有效的定量援助有多种事件前应用（例如，道路、水库和防火线的选址），事件期间应用（例如，替代消防策略的比较和疏散命令的理由），以及事件后应用（例如，人员认证和野火相关诉讼的援助）。该项目具有变革性：将实验室测试应用于火蔓延研究；采用？火使用？决策者的（约束反应）选择；加快火速预测。