CLIMA: Climate-Resilient Infrastructure Adaptations for Maladaptive Levee Networks
CLIMA: Climate-Resilient Infrastructure Adaptations for Maladaptive Levee Networks
批准号:
2332169
负责人:
Alfonso Mejia
金额:
$75.8万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2026-08-31
中文摘要
在美国,数百万人和数万亿美元的财产受到堤坝系统的保护,免受洪水的侵袭。然而,大多数联邦政府监控的堤坝都达不到最低认证标准。此外,气候变化加剧了洪水,可能会使目前的堤坝保护在未来变得不足。升级和扩建现有堤坝需要大量投资,而且可能不会对特定河网上的所有社区产生净积极影响。这个土木基础设施研究气候变化减缓和适应(CLIMA)项目旨在通过探索一个理论指导的系统建模框架来设计气候适应性堤防基础设施,以公平的方式支持洪泛区社区,从而解决这一问题。该项目侧重于两个相互关联的问题:(1)堤防网络的性能、未来气候、自然基础设施和行为反馈之间的相互作用如何驱动社区洪水风险的变化;(2)设计适应性如何重新构想堤坝网络,以支持公平、有弹性和可持续的社区。为了解决这些问题,该项目创建了一个新的系统建模框架来评估堤防适应策略,考虑了在堤防决策中经常被忽视的因素,如自然洪水基础设施、堤防性能的可变性、气候变化、堤防建设的意外后果以及社会公平。这个框架将堤坝视为一个更大的适应性网络的一部分,在这个网络中,一个社区的堤坝决定会影响同一流域的其他社区。通过适应的视角,该项目推进了对自然防洪基础设施的潜力的认识,以减少对堤坝的需求并实现协同效益(如减少淡水污染),在流域水平上驱动堤坝性能的岩土因素,以及使堤坝适应不断变化的洪水条件的干预措施和政策选择。这些进展有可能通过促进确定恢复力建设战略,使全国洪泛区社区受益。通过利用广泛的生物物理和社会数据集,包括岩土工程现场和社区调查等新来源,该项目创造性地将自然基础设施、堤防基础设施、洪水淹没风险和堤防决策的计算模型结合起来。这种综合方法产生了堤防调整和堤防分析的详细路线图,允许更明智的决策,优先考虑公平性、弹性和成本效益。该项目由工程局(ENG)土木、机械和制造创新司(CMMI)的人类、灾害和建筑环境(HDBE)计划和土木基础设施系统(CIS)计划提供支持。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。
英文摘要
Millions of people and trillion dollars of property in the US are protected from flooding by levee systems. However, most federally monitored levees fall short of minimum accreditation standards. Further, climate change exacerbates flooding, likely making current levee protection inadequate in the future. Upgrading and extending existing levees require substantial investments and may not lead to net positive effects for all communities across a given river network. This CiviL Infrastructure research for climate change Mitigation and Adaptation (CLIMA) project aims to address this problem by exploring a theory-guided systems modeling framework for designing climate-resilient levee infrastructure that supports floodplain communities in an equitable way. The project focuses on two interrelated questions: (1) How interactions between a levee network’s performance, future climates, natural infrastructure, and behavioral feedback drive changes in flood risk across communities; and (2) How design adaptations reimagine a levee network that supports equitable, resilient, and sustainable communities. To address them, the project creates a novel systems modeling framework to evaluate levee adaptation strategies, considering factors often overlooked in levee decision-making, such as natural flood infrastructure, variability in levee performance, climate change, unintended consequences of levee construction, and social equity. This framework sees levees as part of a larger adaptive network, where levee decisions made in one community affect others in the same watershed. Through the adaptation lens, the project advances knowledge of the potential of natural flood infrastructure to reduce the need for levees and achieve co-benefits (such as reducing freshwater pollution), the geotechnical factors that drive levee performance at the watershed level, and the interventions and policy options for adapting levees to changing flood conditions. These advancements have the potential to benefit floodplain communities nationwide by facilitating the identification of resilience-building strategies. By utilizing extensive biophysical and social datasets, including new sources like geotechnical field and community surveys, the project creatively couples computational models of natural infrastructure, levee infrastructure, flood inundation risk, and levee decision-making. This integrated approach yields detailed roadmaps of levee adaptations and levee analytics, allowing for better-informed decisions that prioritize equity, resilience, and cost-effectiveness.This project is supported by the Humans, Disasters, and the Built Environment (HDBE) Program and the Civil Infrastructure Systems (CIS) Program of the Division of Civil, Mechanical and Manufacturing Innovation (CMMI) of the Directorate for Engineering (ENG).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.
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