LEAP-HI: A Data-Driven Fragility Framework for Risk Assessment of Levee Breach

LEAP-HI：用于堤坝溃决风险评估的数据驱动的脆弱性框架

• 批准号: 2152896
• 负责人: Jasim Imran
• 金额: $ 200万
• 依托单位: University of South Carolina at Columbia
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2152896&HistoricalAwards=false
• 关键词: LEAP; HI; Data; Driven; Fragility

Levees are critical infrastructural elements for flood protection that are built with earth materials. They run parallel to rivers and coastlines and are designed to keep water out of the low-lying communities and agricultural lands behind the levee. America’s over 100,000 miles of levees were built with varying levels of quality using a wide variety of materials that are often dictated by availability rather than engineering specifications and these aging levees are being exposed to increasing stress due to climate change. Moreover, the construction of levees presents the so-called levee paradox, in which the presence of the levee system lowers public perception of risk in protected areas, thereby reducing incentives to take auxiliary precautions and leading to reduced preparedness. This Leading Engineering for America's Prosperity, Health, and Infrastructure (LEAP-HI) research will enable riverside communities to better analyze their options and resources for flood defense and plan for a projected increase in the frequency of extreme weather events. The project will expand our understanding of how infrastructure responds and fails during natural hazards. It will include collaborations between universities (including a Historically Black University), government agencies, and society. Finally, the project will contribute to U.S. workforce development through training a diverse group of students on the development and deployment of cutting-edge technology for the assessment of flood and environmental hazards.This project will address uncertainties in levee performance and levee breach flooding through a convergent approach that integrates smart sensing of geotechnical and hydraulic parameters with probabilistic and deterministic modeling of levee failure and inundation of levee-protected floodplains. The project will investigate an integrated levee monitoring and flood risk assessment system consisting of unmanned aerial vehicle-assisted deployment of novel sensors, automated data collection, and coupled data-driven, probabilistic, and physics-based models. These high fidelity spatial and temporal measurement and modeling capabilities will be leveraged by domain expertise in the fields of hydrology and hydraulics, structural reliability, and geotechnical engineering to create fragility metrics for levee reliability that will be integrated into a system of models for the flood disaster chain. The system will allow decision-makers and stakeholders to monitor and repair vulnerable levees, develop countermeasures, and support a risk-based decision-making process aimed at developing effective risk communication and flood management policy. This project will expand the understanding of floodplain hydrology as well as the dynamic interactions of soil parameters and hydraulic loading. Given the potential for the project’s data, sensor designs, and modeling tools to benefit the public good, the project’s artifacts will be open-sourced and made freely available to enable other researchers and practitioners to leverage the project’s advancements.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.

堤坝是防洪的重要基础设施，它们与河流和海岸线平行，旨在防止水进入堤坝后面的低洼社区和农田。美国修建了超过 100,000 英里的堤坝。使用各种材料的质量水平各不相同，这些材料通常取决于可用性而不是工程规格，而且这些老化的堤坝由于气候变化而面临着越来越大的压力。堤坝呈现出所谓的堤坝悖论，其中堤坝系统的存在降低了公众对保护区风险的认知，从而减少了采取辅助预防措施的动力，并导致准备工作减少。 (LEAP-HI) 研究将使河滨社区能够更好地分析他们的防洪方案和资源，并针对预计的极端天气事件发生频率的增加制定计划，该项目将扩大我们对基础设施在洪水期间如何响应和失效的了解。最后，该项目将包括大学（包括历史悠久的黑人大学）、政府机构和社会之间的合作，通过培训不同的学生群体开发和部署尖端技术，为美国劳动力发展做出贡献。用于评估洪水和环境危害。该项目将通过一种收敛方法解决堤坝性能和堤坝决口洪水的不确定性问题，该方法是对岩土和水力参数进行智能传感，并对堤坝破坏和破坏进行概率性和确定性建模。该项目将研究综合堤坝监测和洪水风险评估系统，包括无人机辅助部署的新型传感器、自动数据收集以及耦合数据驱动、概率和基于物理的模型。这些高保真度空间和时间测量和建模功能将通过水文和水力学、结构可靠性和岩土工程领域的专业知识来利用，为堤坝可靠性创建脆弱性指标，并将其集成到该系统将允许决策者和利益相关者监测和修复脆弱的堤坝，制定对策，并支持基于风险的决策过程，旨在制定有效的风险沟通和洪水管理政策。该项目将扩大对洪泛区水文学以及土壤参数和水力载荷的动态相互作用的理解，鉴于该项目的数据、传感器设计和建模工具有可能造福公众利益，该项目的工件将是开源的。免费提供给其他人研究人员和从业者利用该项目的进步。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。