Collaborative Research: Understanding Hybrid Green-Gray Coastal Infrastructure Processes and Performance Uncertainties for Flood Hazard Mitigation

沿海地区对沿海洪水的脆弱性正在增加。沿海社区需要有弹性和可持续的适应办法，以减轻灾害事件期间的损害和保护生命。采用了传统的结构(灰色)方法(即舱壁、护岸)来稳定和保护海岸线。天然(绿色)和绿色-灰色混合解决方案作为有效的替代方案受到了关注。除了保护新的开发或延长发达海岸线附近遗留基础设施的使用寿命外，绿色方法还可以提供生态、经济和文化方面的共同效益。然而，对绿色和混合基础设施的性能和相关不确定性的根本缺乏理解限制了这些系统的广泛实施。在这个项目中，研究人员将开发一个框架，以量化混合自然-结构系统对水灾害的反应。有针对性的大规模物理模型调查和数值模型活动将集中在佛罗里达州南部常见的两种系统类型：红树林+舱壁和红树林+护岸。该项目将利用基于自然的工程、生态和生物学专家以及来自政府、行业和研究机构的利益相关者的专业知识。将建立一个研究协调和咨询网络(RCAN)，为实验设计提供信息并传播项目成果。研究人员将利用以前现场调查的数据来表征红树林的几何和机械特性以及固有的可变性，以便为建立大规模物理模型和有针对性的数值模型模拟提供信息。这些数据将使研究人员能够分解系统组件对水力响应的影响，并验证和比较模型限制。经过验证的数值模型将用于研究混合系统在一系列入射水动力条件、植被配置和结构几何形状下的预期性能。这项工作将能够在传播不确定性的情况下量化波浪对混合植被-结构系统的响应，包括系统成熟时间和预期未来条件(例如相对海平面上升)等时间变化。将确定和综合影响通过这些系统的波浪变换的基本过程，以便为这些系统的设计提供信息，以增强海岸的复原力。该项目将通过两种方法扩大对波浪与自然系统和混合系统相互作用的基本理解：(1)确定入射波浪和涌浪条件、水深测量、新兴植被以及随后的海岸舱壁和护岸溢流之间的基本相互作用；(2)量化相互作用的不确定性，以便能够采用随机方法评估混合海岸系统的预期性能范围。通过确定入射波浪条件、涌浪水平、植被和结构细节之间的基本关系，调查人员将确定作为结构几何形状(波峰高程、坡度、渗透率)、植被特征(宽度、密度、出现率)和环境参数(涌浪水平、波高、波浪周期)的函数的减灾性能指标(波浪越顶减小、波浪力减小)。通过有针对性的物理模型试验验证的数值模型将被外推到其他水动力条件和植被/结构构型，以确定性能指标阈值的超越概率和对系统几何以及认知和高空不确定性的敏感性。RCAN将汇集工程、生态和政策领域的专家，为项目提供信息并广泛传播项目成果，目的是促进研究成果的成功实施。学生培训将通过参与RCAN的机会整合到整个项目中，并为物理和数值模拟工作做出贡献。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。

The vulnerability of shore regions to coastal flooding is increasing. Coastal communities need resilient and sustainable adaptation alternatives to mitigate damage and protect lives during hazard events. Conventional structural (gray) methods (i.e., bulkheads, revetments) have been implemented to stabilize and protect coastlines. Natural (green) and hybrid green-gray solutions have gained attention as effective alternatives. Green methods may provide ecological, economic, and cultural co-benefits in addition to protecting new development or expanding the service life of legacy infrastructure near developed coastlines. However, a fundamental lack of understanding of the performance and associated uncertainty of green and hybrid infrastructure limits these systems’ broad implementation. In this project, the investigators will develop a framework to quantify the response of hybrid natural-structural systems to water hazards. A targeted large scale physical model investigation and numerical model campaign will focus on two system types common to southern Florida: mangrove + bulkhead and mangrove + revetment. The project will leverage the expertise of nature-based engineering, ecology, and biology experts and stakeholders from government, industry, and research institutions. A Research Coordination and Advisory Network (RCAN) will be created to inform experimental design and disseminate project outcomes. The investigators will leverage data from previous field investigations characterizing mangrove geometric and mechanical properties and inherent variability to inform the construction of a large scale physical model and targeted numerical model simulations. These data will allow the investigators to disaggregate system component effects on hydraulic response and to validate and compare model limits. The validated numerical models will be used to investigate the expected performance of hybrid systems over a range of incident hydrodynamic conditions, vegetation configurations, and structural geometries. This work will enable quantification, with propagated uncertainties, of wave response to hybrid vegetation-structural systems, including temporal variations such as time to system maturity and expected future conditions (e.g., relative sea level rise). Fundamental processes affecting wave transformation through these systems will be identified and synthesized to inform the design of these systems for enhanced coastal resilience. The project will expand fundamental understanding of wave interaction with natural and hybrid systems through two approaches: (1) Identify and parameterize fundamental interactions among incident wave and surge conditions, bathymetry, emergent vegetation, and subsequent overtopping of coastal bulkheads and revetments; and (2) Quantify interaction uncertainties to enable stochastic approaches for assessing the range of expected performance in hybrid coastal systems. By identifying fundamental relationships between incident wave conditions, surge level, vegetation, and structural details, the investigators will determine performance metrics for hazard reduction (wave overtopping reduction, wave force reduction) as a function of structural geometry (crest elevation, slope, permeability), vegetation characteristics (width, density, emergence), and environmental parameters (surge level, wave height, wave period). Numerical models validated by targeted physical model tests will be extrapolated to other hydrodynamic conditions and vegetation/structural configurations to determine exceedance probabilities of performance metric thresholds and sensitivity to system geometry and epistemic and aleatory uncertainties. The RCAN will bring together domain experts in engineering, ecology, and policy to inform the project and broadly disseminate project outcomes, with the goal of catalyzing the successful implementation of research findings into practice. Student training will be integrated throughout the project through opportunities to engage with the RCAN and contribute to physical and numerical modeling efforts.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.