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.

海岸地区对沿海洪水的脆弱性正在增加。沿海社区需要弹性和可持续的适应替代品，以减轻危害事件中的损害并保护生命。已经实施了常规的结构（灰色）方法（即舱壁，调查）来稳定和保护海岸线。天然（绿色）和杂化绿色灰色溶液已成为有效替代方案。绿色方法除了保护新的发展或扩大发达的海岸线附近的传统基础设施的使用寿命外，还可以提供生态，经济和文化共同利益。但是，根本缺乏对绿色和混合基础设施的性能和相关不确定性的理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，以量化混合自然结构系统对水危害的响应。有针对性的大规模物理模型投资和数值模型活动将重点关注佛罗里达州南部共有的两种系统类型：红树林 +舱壁和红树林 + REDETMENT。该项目将利用政府，行业和研究机构的基于自然的工程，生态学以及生物学专家以及利益相关者的专业知识。将创建一个研究协调和咨询网络（RCAN），以告知实验设计并传播项目成果。研究人员将利用先前表征红树林几何和机械性能的现场调查的数据，并继承可变性，以告知大规模物理模型和目标数值模型模拟的构建。这些数据将使研究人员能够分解系统组件对氢化响应的影响，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，蔬菜构型和结构几何形状上的预期性能。这项工作将通过对混合植被结构系统的波反应进行定量，并具有传播的不确定性，包括临时变化，例如系统成熟时间和预期的未来条件（例如，相对海平面上升）。将确定并合成影响通过这些系统的波动转化的基本过程，以告知这些系统的设计，以增强沿海弹性。该项目将通过两种方法扩展对与自然和混合系统的波浪相互作用的基本理解：（1）识别和参数化事件波和涌动条件之间的基本相互作用，测深，新兴的植被以及随后的沿海舱壁和岸上的超越； （2）量化相互作用的不确定性，以实现随机方法来评估混合沿海系统中预期性能的范围。通过确定事件波动条件，浪涌水平，植被和结构细节之间的基本关系，研究人员将确定降低危险的性能指标（波动量减少，波力减少），这是结构性几何形状（CREST高度，坡度，渗透性，渗透性），植被特征（植被特征）（wave，密度，生成）（浪潮）（浪潮），浪潮，浪潮，浪潮，通过有针对性的物理模型测试验证的数值模型将被外推到其他流体动力条件和植被/结构构型，以确定性能度量阈值的超出可能性以及对系统几何以及认知和分析不确定性的敏感性。 RCAN将汇集工程，生态和政策领域的专家，以告知该项目并广泛传播项目成果，以促进成功实施研究结果的成功实践。学生培训将通过与RCAN互动并为物理和数值建模工作做出贡献的机会整合到整个项目中。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，被认为是珍贵的支持。