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

合作研究：了解混合绿灰色沿海基础设施流程和缓解洪水灾害的性能不确定性

• 批准号: 2110439
• 负责人: Daniel Cox
• 金额: $ 23.31万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2110439&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Hybrid; Green

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.

沿海地区对沿海洪水的脆弱性日益增加，沿海社区需要采取弹性和可持续的适应替代方案来减轻灾害事件期间的损害并保护生命，以稳定和保护海岸线。自然（绿色）和混合绿灰色解决方案作为有效的替代方案而受到关注，除了保护新开发或延长发达海岸线附近的遗留基础设施的使用寿命外，绿色方法还可以提供生态、经济和文化的协同效益。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了解限制了这些系统的广泛实施。在该项目中，研究人员将开发一个框架来量化混合自然结构系统对大型水害的响应。规模物理模型调查和数值模型活动将重点关注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政府、行业利益相关者的专业知识。和研究机构。将创建协调和咨询网络（RCAN），为实验设计提供信息并传播项目成果，研究人员将利用先前实地调查的数据来表征红树林的几何和机械特性以及固有的变异性，为大规模物理模型和目标数值的构建提供信息。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事件水动力条件、植被配置下的预期性能。 ，和结构这项工作将能够量化波浪对混合植被结构系统的响应，包括时间变化，例如系统成熟的时间和预期的未来条件（例如，影响波浪转变的相对海平面上升）。这些系统将被识别和综合，为这些系统的设计提供信息，以增强沿海的恢复能力。该项目将通过两种方法扩展对波浪与自然和混合系统相互作用的基本理解：（1）识别并参数化入射波浪和浪涌之间的基本相互作用。状况，测深、新兴植被以及随后的沿海舱壁和护岸的溢出；以及（2）通过确定入射波浪条件、浪涌水平、植被之间的基本关系，量化相互作用的不确定性，以采用随机方法来评估混合沿海系统的预期性能范围。和结构细节，研究人员将根据结构几何形状（波峰高程、坡度、渗透性）、植被特征（宽度、密度、通过目标物理模型测试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超出概率和对系统几何形状的敏感性。 RCAN 将汇集工程、生态学和政策领域的专家，为项目提供信息并广泛传播项目成果，以促进研究的成功实施。学生培训将通过参与 RCAN 的机会融入到整个项目中，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，并通过利用基金会的智力优势和更广泛的评估进行评估，被认为值得支持。影响审查标准。