PREEVENTS Track 2: Fire Spread at the Wildland-Urban Interface (WUI) Modeling and Data Assimilation for Prediction and Risk assessment (WUI MAPR)

大火威胁着荒地边缘的社区和城市环境。例如，2017年10月加州北部野地大火摧毁了8900多座建筑，造成44名平民死亡，预计损失超过94亿美元。在过去的十年里，这类火灾造成的破坏速度有所增加。调查人员将使用数值模型来模拟野火蔓延到社区的过程。他们将使用美国国家标准与技术研究所(NIST)和加州森林与消防局(CalFire)的数据来测试这些模型。研究结果将与研究社区、联邦事件管理人员、当地社区规划者和公众分享。该项目将通过外展活动和本科生研究机会鼓励人们从事野火研究。研究人员将通过在欧洲地球物理联盟(EGU)、国际燃烧研讨会(澳大利亚阿德莱德，2020)和国际火灾安全科学研讨会(加拿大滑铁卢，2020)等国际会议上展示他们的成果来促进国际合作。这个项目将建立品牌或余烬的模型，以及它们如何促进荒地-城市交界处的火灾传播。这是一个具有挑战性的研究问题，因为在特定的地点有不同的燃料、不同类型的品牌、风和堆积的品牌。研究计划是利用从最新文献中综合的信息来修改现有的随机荒地火灾模型(Firefly)。调查人员将检查火灾周长和观察到的火灾蔓延的观测数据，并利用这些观测数据来验证模型的改进。萤火虫模型改进的预测能力可以在社会上用于实际火灾事件的规划和应急响应。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Large wildland fires threaten communities at the margins of wildlands and the urban environment. For example, the Northern California wildland fires in October 2017 destroyed over 8900 structures and killed 44 civilians with projected losses exceeding $9.4 billion. The rate of destruction from these types of fires has increased over the last decade. The investigators will use numerical models to simulate the spread of wildland fires into communities. They will test these models using data from the National Institute for Standards and Technology (NIST) and the California Department of Forest and Fire Protection (CalFIRE). The findings will be shared with the research community, federal incident managers, local community planners, and the public. The project will encourage people to engage in wildland fire research through outreach events and undergraduate research opportunities. The investigators will promote international collaboration by presenting their results at international meetings, such as the European Geophysical Union (EGU), the International Symposium on Combustion (Adelaide, Australia, 2020) and International Symposium on Fire Safety Science (Waterloo, Canada, 2020).This project will model brands or embers and how they contribute to the spread of fires at the Wildland-Urban Interface. This is a challenging research problem because there are different fuels, different types of brands, winds, and the pile up of brands in specific locations. The research plan is to modify an existing stochastic wildland fire model (FIREFLY) using information synthesized from the recent literature. The investigators will examine observational data of fire perimeters and observed fire spread, and use these observations to validate model improvements. The improved predictive capability of the FIREFLY model could be useful in society for planning and emergency response during real fire events.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.