Adaptive Management of Water Supply Infrastructure for Persistent Anomalies versus Climate Trends

针对持续异常与气候趋势的供水基础设施的适应性管理

• 批准号: 2207036
• 负责人: Sarah Fletcher
• 金额: $ 49.8万
• 依托单位: Stanford University
• 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
• 起止时间: 2023-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2207036&HistoricalAwards=false
• 关键词: Adaptive; Management; Water; Supply; Infrastructure

This project addresses climate challenges faced by critical infrastructure sectors by establishing a new adaptive management approach to water supply infrastructure planning that incorporate the impacts of multi-year climate oscillations on water availability. Large scale infrastructure investments in the water sector will be needed to maintain reliable water supply globally in a changing climate. To enable resilience at lower cost, adaptive management approaches have been developed to monitor gradual changes in precipitation patterns to guide adaptations. However, existing adaptive management approaches are confounded by the presence of multi-year climate oscillations, which make it difficult to infer long-term trends from near-term observations. This grant supports research that seeks to address this gap by integrating climate science on multi-year oscillations with decision-support modeling for water resources management. The outcome of this research is expected to help water planners identify low-cost, adaptive approaches to maintain water supply reliability. The research team will partner with water planners to make sure the research is useful for decision-making. Additionally, the grant will support new interactive educational materials in water resources management.This project designs new adaptive management strategies for water supply planning that can address uncertainty in climate trends, multi-year large-scale climate oscillations, and annual variability. It will develop an approach for decomposing precipitation uncertainty into these three timescales and quantifying future opportunities to reduce uncertainty in each timescale. This uncertainty characterization will be integrated into stochastic dynamic optimization models of water resource systems. This approach will be used to assess the potential for different combinations of adaptive strategies including flexibility in the timing, sizing, modularity, and operations of water supply infrastructure to address the different timescales of uncertainty in future precipitation. By applying this approach to river basins in sub-Saharan Africa with contrasting patterns of precipitation variability, the project will build theory on how different temporal patterns of precipitation variability affect adaptive approaches to water infrastructure planning, design, and operations. This new knowledge can help water planners target water supply infrastructure investment to support low-cost water supply reliability.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.

该项目旨在应对关键基础设施部门面临的气候挑战，为供水基础设施规划建立一种新的适应性管理方法，其中纳入多年气候波动对水供应的影响。需要在水部门进行大规模基础设施投资，以在不断变化的气候中保持全球可靠的供水。为了以较低的成本实现抗灾能力，制定了适应性管理办法，以监测降水模式的逐步变化，指导适应工作。然而，现有的适应性管理方法因存在多年气候振荡而受到干扰，这使得难以从近期观测中推断出长期趋势。该补助金支持旨在通过将多年振荡的气候科学与水资源管理的决策支持模型相结合来解决这一差距的研究。这项研究的结果有望帮助水资源规划者确定低成本的适应性方法，以保持供水的可靠性。研究团队将与水资源规划者合作，确保研究对决策有用。此外，赠款将支持新的水资源管理互动教材，该项目为供水规划设计新的适应性管理策略，以解决气候趋势的不确定性，多年大规模气候振荡和年度变化。它将制定一种方法，将降水不确定性分解为这三个时间尺度，并量化未来的机会，以减少每个时间尺度的不确定性。这种不确定性特征将被集成到水资源系统的随机动态优化模型。这种方法将被用来评估适应战略的不同组合的潜力，包括供水基础设施的时间，规模，模块化和业务的灵活性，以解决未来降水的不确定性的不同时间尺度。通过将这种方法应用于撒哈拉以南非洲地区具有对比降水变化模式的河流流域，该项目将建立关于降水变化的不同时间模式如何影响水基础设施规划，设计和运营的适应性方法的理论。这一新的知识可以帮助水规划者确定供水基础设施投资的目标，以支持低成本的供水可靠性。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。

项目成果

Valuing Combinations of Flexible Planning, Design, and Operations in Water Supply Infrastructure

重视供水基础设施灵活规划、设计和运营的组合

• DOI: 10.1029/2023wr036048
• 发表时间: 2024
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Willebrand, Keani;Zaniolo, Marta;Skerker, Jennifer;Fletcher, Sarah
• 通讯作者: Fletcher, Sarah

Bayesian Estimation of Advanced Warning Time of Precipitation Emergence

降水出现提前预警时间的贝叶斯估计

• DOI: 10.1029/2023ef004079
• 发表时间: 2024
• 期刊: Earth's Future
• 作者: Lickley, Megan;Fletcher, Sarah
• 通讯作者: Fletcher, Sarah

Quantifying the Value of Learning for Flexible Water Infrastructure Planning

量化灵活水利基础设施规划学习的价值

• DOI: 10.1029/2022wr034412
• 发表时间: 2023
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Skerker, J. B.;Zaniolo, M.;Willebrand, K.;Lickley, M.;Fletcher, S. M.
• 通讯作者: Fletcher, S. M.