RAPID: Quantifying the fluvial response to cascading dam failures at Edenville and Sanford, Michigan
RAPID: Quantifying the fluvial response to cascading dam failures at Edenville and Sanford, Michigan
批准号:
2038072
负责人:
Brian Yanites
金额:
$2.24万
依托单位:
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
项目状态:
已结题
起止时间:
2020-07-15 至 2021-06-30
中文摘要
我们对洪泛区和河道对大坝拆除的反应的理解主要来自协调拆除,这一过程是缓慢和可预测的,而不是灾难性的大坝破裂。协调清除的研究是有限的,几乎没有数据存在河流对溃坝的反应。这些知识差距具有实际意义,因为美国的许多水坝正在老化,并面临失败的风险。这项工作将促进对美国大洪水和老化基础设施影响的理解,这对大坝下游的社区造成了越来越大的危害。这种理解对于量化风险以最好地告知利益攸关方是必要的。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领域代表性不足的群体。最后,该团队将在会议上以手稿形式传播工作成果,并在Open Topography上公开托管数据。该项目的智力价值在于能够使用无人机激光雷达收集高分辨率地形数据,以描述河流和洪泛区溃坝的后果以及河流在未来一年的反应。该项目产生的激光雷达数据将为预测河流对溃坝响应的模型提供重要的基线数据集。这项工作将促进对美国大洪水和老化基础设施影响的理解,这对大坝下游的社区造成了越来越大的危害。结果将在科学促进奇卡诺人/西班牙裔和美洲土著人协会的年度会议上公布。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。
英文摘要
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.
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会议论文
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批准号:2041738
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项目类别:Standard Grant
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资助金额:$29.85万
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财政年份:2021
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负责人:Brian Yanites
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依托单位:
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依托单位:
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依托单位:
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依托单位:
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依托单位:
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