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

GSTDTAP

项目编号	1854952
	PREEVENTS Track 2: Fire Spread at the Wildland-Urban Interface (WUI) Modeling and Data Assimilation for Prediction and Risk assessment (WUI MAPR)
	Michael Gollner (Principal Investigator)
主持机构	University of Maryland College Park
项目开始年	2019
	2019-07-01
项目结束日期	2022-06-30
资助机构	US-NSF
项目类别	Continuing grant
项目经费	380710(USD)
国家	美国
语种	英语
英文摘要	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.
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/213393
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Michael Gollner .PREEVENTS Track 2: Fire Spread at the Wildland-Urban Interface (WUI) Modeling and Data Assimilation for Prediction and Risk assessment (WUI MAPR).2019.