Collaborative Research: Integrated Numerical Modeling and Field Observations of Hurricane Impacts to Natural and Hybrid Infrastructure

保护沿海社区、经济中心和基础设施网络对我们的国家安全和长期繁荣至关重要。促进了由堰洲岛、沙丘、湿地、红树林和珊瑚礁组成的自然基础设施，以减轻沿海洪水和侵蚀。然而，自然元素的集体有效性以及它们如何与硬基础设施作为一个混合系统一起工作以提供洪水风险降低仍然未知。该项目利用从路易斯安那州切尼尔平原劳拉飓风和德尔塔飓风（2020年）快速现场运动中收集的独特的水动力、生态地貌和岩土技术数据，填补了这一关键的知识空白。该研究将沿海湿地的形态动力学建模与基于现场的水动力学、生态地貌学和岩土工程测量相结合，以评估和预测自然和混合基础设施在飓风影响下的性能。该项目将利用现有的外联计划和区域伙伴关系传播研究成果。研究小组将与海岸和岩土研究团体以及实践工程师和资源管理人员分享建模工具和新认识。该项目为两个机构在海岸和岩土工程领域交叉培训本科生和研究生提供了独特的机会，并发展了现场观测和数值模拟技能。有效减轻沿海灾害需要综合实地观测和数值模拟，以便在适当的空间和时间尺度上描述沿海动态过程。该项目将海岸湿地的陆地流和形态动力学建模与水动力学、地貌学、生态学和岩土工程测量相结合，以改变我们对受飓风影响的自然和混合基础设施的响应和恢复的理解。该项目利用飓风期间收集的独特数据：(i)提高对混合基础设施提供的陆地流、风暴潮和波浪衰减（防洪）的时空变化的理解；（ii）评估数值模式在预测海岸侵蚀和自然景观中沉积物迁移方面的有效性；（iii）探讨岩土力学特性、地层学和植被生物力学特性在控制海岸线退缩和飓风造成的植被连根拔起的程度方面的作用。综合实地、实验室和遥感数据收集，辅以数值模拟，将确定和评价根和土壤特性及其在连根拔起和侵蚀过程中的作用。新的现场测试将能够成功收集以前具有挑战性或无法量化的观察结果。预计综合方法和建模工具将适用于其他海岸线，以评估沿海恢复力的自然和混合基础设施性能。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。

The protection of coastal communities, economic hubs, and infrastructure networks is critical to our national security and long-term prosperity. Natural infrastructure consisting of barrier islands, dunes, wetlands, mangroves, and reefs has been promoted to mitigate coastal flooding and erosion. However, the collective effectiveness of natural elements and how they work together with hard infrastructure as a hybrid system to provide flood risk reduction remain unknown. This project harnesses the unique hydrodynamic, eco-geomorphic, and geotechnical data collected from rapid field campaigns of Hurricanes Laura and Delta (2020) on the Louisiana Chenier Plain to fill this key knowledge gap. The research integrates morphodynamic modeling of coastal wetlands with field-based hydrodynamic, eco-geomorphic, and geotechnical measurements to assess and predict the performance of natural and hybrid infrastructure subject to hurricane impacts. The project will leverage existing outreach programs and regional partnerships to disseminate research results. The research team will share the modeling tools and new understanding developed with the coastal and geotechnical research communities, as well as practicing engineers and resource managers. The project provides unique opportunities to cross-train undergraduate and graduate students in both coastal and geotechnical engineering areas at two institutions and develop both field observation and numerical modeling skills.Effective coastal hazard mitigation requires integrative field observations and numerical modeling to characterize dynamic coastal processes at appropriate space and time scales. This project integrates overland flow and morphodynamic modeling of coastal wetlands with hydrodynamic, geomorphic, ecological, and geotechnical measurements to transform our understanding of the response and recovery of natural and hybrid infrastructure impacted by hurricanes. The project harnesses the unique data collected during hurricanes to (i) advance the understanding of the spatiotemporal variation in overland flow, storm surge, and wave attenuation (flood protection) provided by hybrid infrastructure; (ii) evaluate the efficacy of numerical models to predict coastal erosion and sediment transport across a natural landscape; and (iii) explore the role of geotechnical properties, stratigraphy, and vegetation biomechanical properties in controlling the magnitude of shoreline retreat and vegetation uprooting by hurricanes. The comprehensive field, laboratory, and remote-sensing data collection, complemented by numerical modeling, will identify and evaluate root and soil properties and their roles in uprooting and erosion processes. The novel field testing will enable successful collection of observations that were previously challenging or impossible to quantify. It is anticipated that the integrative approach and modeling tools will be applicable to other coastlines for evaluating natural and hybrid infrastructure performance for coastal resilience.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.