Collaborative Research: Predicting post-wildfire sedimentation of reservoirs: probabilistic modeling of debris flow generation and downstream sediment routing

GSTDTAP

项目编号	1848667
	Collaborative Research: Predicting post-wildfire sedimentation of reservoirs: probabilistic modeling of debris flow generation and downstream sediment routing
	Brendan Murphy (Principal Investigator)
主持机构	Utah State University
项目开始年	2019
	2019-03-01
项目结束日期	2022-02-28
资助机构	US-NSF
项目类别	Continuing grant
项目经费	121179(USD)
国家	美国
语种	英语
英文摘要	In the United States, forested lands provide water supply for two-thirds of the population. However, in the decades since most water infrastructure was constructed in the western U.S., the burned area, frequency, and severity of wildfires has increased considerably. While wildfires can have short-term impacts on the quantity and quality of water supply, the erosion that occurs after severe burns can also deliver significant amounts of sediment to rivers and downstream reservoirs, reducing the long-term storage capacity of water supplies. Further, with projected future increases in wildfire, there will be increases in river sediment. Thus, in this project the researchers will develop new computer-based modeling tools capable of identifying and quantifying the risk that post-wildfire erosion poses to downstream water infrastructure. The first application of this modeling framework will be the water supply reservoirs throughout Utah, one of the driest states in the U.S., where the vulnerability of each reservoir will be quantified as to the erosion and sedimentation risk posed by wildfire. Similar to dammed reservoirs across the nation, sedimentation in Utah reservoirs is a growing concern for aging water infrastructure, even before accounting for the projected increases in future wildfire. Finally, the researchers will integrate their model into online, open-source programs, making these resources available to any person or agency interested in applying the model to other states or regions. The deliverables of this project will provide critical information and tools for improved and more targeted forest management, help identify and protect vulnerable water resources, and address crucial knowledge gaps for predicting downstream impacts from post-wildfire erosion. Collaborating across two universities, this project will provide support for one post-doctoral researcher (PI Murphy), two PhD students, and a minimum of six undergraduate students to train and develop their skills in hydrology, geomorphology, data analysis and management, and science communication. This project will advance fundamental knowledge critical for predicting the locations and timing of post-wildfire sediment delivery to downstream water infrastructure. The researchers will link new and existing models that: 1) predict the locations and magnitudes of post-wildfire erosion, 2) route post-wildfire sediment inputs downstream through river networks in a physics-based and hydro-geomorphically sensitive manner, and 3) determine a range of potential volumetric sediment inputs to downstream reservoirs under a range of wildfire conditions. Applying this new modeling framework to the 133 major reservoirs throughout Utah, this project will answer four key research questions: 1) Which water supply reservoirs in Utah are most vulnerable to post-wildfire erosion? 2) What is the time lag between occurrence of a wildfire and loss of reservoir storage downstream? 3) Which landscape, fire, hydrologic, and vegetation characteristics exert the strongest control on the upstream storage vs. delivery of post-fire sediment to reservoirs? 4) What landscape, fire and river network attributes control the relative increase in post-wildfire sediment yields above background yields? Through this analysis, the researchers will specifically assess the influence of sediment connectivity on reservoir vulnerability, as well as the contribution of coarse sediment inputs to the reductions in reservoir storage over longer transport timescales. Given the complex ownership and management of dams, they will engage a stakeholder advisory group that spans the diverse range of ownership and includes public utilities departments, state and federal forest management agencies, and dam operators. Further, they will work with the Community Surface Dynamics Modeling System (CSDMS) to integrate their models into open-source platforms, and create a public platform to host the project datasets, educational materials, technical reports, and publications. This project represents research at the frontier of integrated geosciences, and this new modeling framework fills a critical gap regarding the tools needed to assess urgent societal concerns regarding wildfire and water security. 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/213115
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Brendan Murphy .Collaborative Research: Predicting post-wildfire sedimentation of reservoirs: probabilistic modeling of debris flow generation and downstream sediment routing.2019.