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

防洪堤是防洪的关键基础设施，是用土材料建造的。它们与河流和海岸线平行，旨在防止洪水进入堤坝后面的低洼社区和农田。美国超过10万英里的堤坝建造质量参差不齐，使用了各种各样的材料，这些材料通常是由可用性而不是工程规格决定的，由于气候变化，这些老化的堤坝正面临越来越大的压力。此外，防洪堤的建设出现了所谓的“防洪堤悖论”，即防洪堤系统的存在降低了公众对保护区风险的认知，从而降低了采取辅助预防措施的动机，导致准备工作减少。这项美国繁荣、健康和基础设施领先工程（LEAP-HI）研究将使河边社区能够更好地分析他们的防洪选择和资源，并为预计的极端天气事件频率的增加做出计划。该项目将扩大我们对基础设施在自然灾害中如何应对和失效的理解。它将包括大学（包括一所历史上的黑人大学）、政府机构和社会之间的合作。最后，该项目将通过培训不同类型的学生开发和部署用于评估洪水和环境危害的尖端技术，为美国的劳动力发展做出贡献。该项目将通过一种融合的方法来解决堤坝性能和堤坝决口洪水的不确定性，该方法将岩土和水力参数的智能传感与堤坝破坏和堤坝保护洪泛平原淹没的概率和确定性建模相结合。该项目将研究一个综合堤坝监测和洪水风险评估系统，该系统由无人机辅助部署的新型传感器、自动数据收集和耦合数据驱动、概率和基于物理的模型组成。这些高保真的时空测量和建模能力将被水文学和水力学、结构可靠性和岩土工程领域的专业知识所利用，以创建堤坝可靠性的脆弱性指标，并将其集成到洪水灾害链的模型系统中。该系统将使决策者和利益相关者能够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的理解，以及土壤参数和水力荷载的动态相互作用。考虑到该项目的数据、传感器设计和建模工具对公共利益的潜在好处，该项目的工件将是开源的，并免费提供给其他研究人员和从业者，使他们能够利用该项目的进步。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

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.