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

海岸地区对沿海洪水的脆弱性正在增加。沿海社区需要有复原力和可持续的适应替代办法，以减轻灾害事件期间的损害和保护生命。传统的结构（灰色）方法（即，为了稳定和保护海岸线，已经实施了各种措施（例如，建造舱壁、护岸等）。自然（绿色）和混合绿色-灰色解决方案作为有效的替代方案已受到关注。绿色方法除了保护新开发或延长发达海岸线附近传统基础设施的使用寿命外，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来量化混合自然结构系统对水灾害的反应。针对性的大比例尺物理模型调查和数值模型活动将侧重于佛罗里达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，生态学和生物学专家以及来自政府，工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实地调查的数据，描述红树林的几何和机械特性以及固有的可变性，为构建大规模物理模型和有针对性的数值模型模拟提供信息。这些数据将使调查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。 经验证的数值模型将被用来调查的预期性能的混合动力系统在一系列的事件的水动力条件下，植被配置，和结构的几何形状。 这项工作将能够量化，传播的不确定性，波响应混合植被结构系统，包括时间变化，如时间系统成熟和预期的未来条件（例如，相对海平面上升）。通过这些系统影响波浪转化的基本过程将被确定和综合，以告知这些系统的设计，以增强沿海的复原力。该项目将通过两种方法扩大对波浪与自然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沿海舱壁和护岸漫顶之间的基本相互作用，并将其参数化;（2）量化相互作用的不确定性，以使随机方法能够评估混合沿海系统的预期性能范围。通过确定入射波条件、涌浪水平、植被和结构细节之间的基本关系，研究人员将确定减少灾害（减少越浪量、减少波浪力）的性能指标，作为结构几何形状（波峰高程、坡度、渗透性）、植被特征（宽度、密度、出露）和环境参数（涌浪水平、波高、波浪周期）的函数。通过有针对性的物理模型试验验证的数值模型将外推到其他水动力条件和植被/结构配置，以确定性能指标阈值的不确定性概率和对系统几何形状的敏感性以及认识和偶然的不确定性。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，其目标是促进研究成果的成功实施。学生培训将通过与RCAN接触的机会整合到整个项目中，并为物理和数值建模工作做出贡献。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 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.