RAPID: Quantifying the fluvial response to cascading dam failures at Edenville and Sanford, Michigan

RAPID：量化密歇根州伊登维尔和桑福德的河流对梯级大坝溃坝的反应

• 批准号: 2038072
• 负责人: Brian Yanites
• 金额: $ 2.24万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2038072&HistoricalAwards=false
• 关键词: RAPID; Quantifying; fluvial; response; cascading

Our understanding of how floodplains and river channels respond to dam removal mostly comes from coordinated removal where the process is slow and predictable rather than from catastrophic dam breaks. Studies of coordinated removal are limited, and virtually no data exist on river response to dam failure. These are knowledge gaps are of practical significance because many dams in the United States are aging and at risk of failure. The work will advance understanding of the impacts of large floods and an aging infrastructure in the United States, which presents an increasing hazard to communities built downstream of dams. Such understanding is necessary for quantifying risk to best inform stakeholders. The work will also provide valuable research experience for two graduate students, one from an underrepresented group in geosciences. Finally, the team will disseminate the results of the work at conferences, in manuscripts, and openly host the data on Open Topography.The intellectual merit of this project is the ability to gather high resolution topographic data using an UAV lidar to characterize the aftermath of dam failure on the river and floodplain and how the river responds in the next year. The lidar data generated by this project will provide an important baseline dataset for models aimed at predicting river response to dam failure. The work will advance understanding of the impacts of large floods and an aging infrastructure in the United States, which presents an increasing hazard to communities built downstream of dams. The results will be presented at the annual meeting of the Society for Advancement of Chicanos/Hispanics and Native Americans in Science.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.

我们对洪水平原和河道如何应对大坝拆除的理解，主要来自于协调的拆除，即过程缓慢和可预测的，而不是来自灾难性的溃坝。协调清除的研究有限，而且几乎没有关于河流对大坝坍塌的反应的数据。这些是具有实际意义的知识差距，因为美国的许多大坝都在老化，面临着崩溃的风险。这项工作将促进人们对美国大洪水和老化基础设施的影响的了解，这对大坝下游的社区构成了越来越大的危险。这样的理解对于量化风险以最好地向利益相关者提供信息是必要的。这项工作还将为两名研究生提供宝贵的研究经验，其中一名来自地球科学中代表性不足的群体。最后，该团队将在会议上以手稿的形式传播工作成果，并公开托管开放地形数据。该项目的智力优势是能够使用无人机激光雷达收集高分辨率地形数据，以表征河流和滩涂大坝坍塌的后果以及河流在明年的反应。该项目产生的激光雷达数据将为旨在预测河流对大坝溃决反应的模型提供重要的基线数据集。这项工作将促进人们对美国大洪水和老化基础设施的影响的了解，这对大坝下游的社区构成了越来越大的危险。结果将在美国奇卡诺人/拉美裔和美国原住民科学促进会的年会上公布。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。