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

堤防是防洪的关键基础设施，是用土料建造的。它们与河流和海岸线平行，旨在将水挡在堤坝后面的低洼社区和农田之外。美国超过10万英里长的堤坝是使用各种材料建造的，质量水平各不相同，这些材料往往由可用性而不是工程规格决定，这些老化的堤坝正因气候变化而面临越来越大的压力。此外，堤防的建设出现了所谓的堤防悖论，即堤防系统的存在降低了公众对保护区风险的认识，从而减少了采取辅助预防措施的动机，并导致防备工作减少。这项领先的美国繁荣、健康和基础设施工程(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，并为预计极端天气事件频率的增加做好计划。该项目将扩大我们对基础设施在自然灾害期间的反应和故障的理解。它将包括大学(包括一所历史悠久的黑人大学)、政府机构和社会之间的合作。最后，该项目将通过培训不同的学生群体，开发和部署用于评估洪水和环境危险的尖端技术，从而促进美国劳动力的发展。该项目将通过一种融合的方法来解决堤防性能和堤防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防破坏和堤防保护泛滥平原的洪水的概率和确定性建模相结合。该项目将研究一个集成的堤防监测和洪水风险评估系统，该系统由无人机辅助部署新型传感器、自动数据收集以及耦合的数据驱动、概率和基于物理的模型组成。这些高保真的空间和时间测量和建模能力将被水文和水力学、结构可靠性和岩土工程领域的专业知识所利用，以创建堤防可靠性的脆弱性度量，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攸关方能够监测和修复脆弱的堤坝，制定对策，并支持旨在制定有效的风险沟通和洪水管理政策的基于风险的决策过程。该项目将扩大对滩地水文学以及土壤参数和水力荷载的动态相互作用的了解。考虑到该项目的数据、传感器设计和建模工具有可能造福于公共利益，该项目的人工制品将是开源的并免费提供，以使其他研究人员和从业者能够利用该项目的进步。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.