DISES: Decentralized management of integrated water resources: Understanding cross-scale decision feedbacks to support coordinated sustainability

DISES：综合水资源的分散管理：了解跨尺度决策反馈以支持协调的可持续性

• 批准号: 2205239
• 负责人: Jonathan Herman
• 金额: $ 160万
• 依托单位: University of California-Davis
• 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: 2022-10-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2205239&HistoricalAwards=false
• 关键词: DISES; Decentralized; management; integrated; water

In many water-scarce regions of the U.S., surface and groundwater resources are managed by a combination of institutions at the federal, state, and local scale. This decentralized structure allows flexible decisions regarding water storage and allocation, but also creates challenges for long-term coordination. Planners and water users must anticipate the actions of others in the system, which intensifies the challenge of managing for variability in future hydrology. Water availability, infrastructure management, regulation, and patterns of water consumption all depend on each other in complex ways. These cross-scale interactions must be captured in engineering models of water resources planning to better understand the impacts of decentralized management and plan accordingly. This project focuses on California’s Central Valley, where surface and groundwater are managed through an evolving network of infrastructure and regulation to support agriculture, cities, and the environment. The team aims to provide findings to advance the critical challenge of water sustainability, while also training students in interdisciplinary research.This project will advance quantitative understanding of the feedbacks governing decentralized water resources systems, and the system-level dynamics that result. This will be achieved through data-driven approaches to describe interactions among infrastructure operators, regulators, and local/regional water districts, enabling a broad evaluation of emergent behavior and opportunities for coordination. Specifically, this work will make three primary scientific contributions addressing knowledge gaps in socio-environmental systems related to scale, heterogeneity, and uncertainty. First, it will advance data-driven approaches to characterize the structure of decision-making relationships in a multi-scale system of heterogeneous water users and institutions. Second, it will develop a data-driven framework to quantify the drivers and consequences of dynamic water management decisions to support prediction of bi-directional feedbacks. Third, it will quantify and attribute the uncertainty in simulated system-level outcomes to uncertainty in exogenous hydroclimate, social dynamics, and their interactions. This work will culminate in the production of open datasets and models to support transfer to water systems facing similar challenges in prediction and management arising from the decentralized context, in which multi-level institutional decisions regarding water allocation and regulation co-evolve.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.

在美国的许多水域中，这种分散的结构都可以进行储存和分配，但也为长期协调而产生了charlense。计划更好地了解加利福尼亚州中央山谷的水资源模型，并计划通过基础设施和监管来管理地面和地下水。水可持续性的关键挑战还将培训培训将使资源系统以及通过数据驱动的方法来促进资源系统，并通过数据驱动的方法来划分，以进行分解相互作用，基础架构调节器和本地/地区水域，这是对的广泛评估。新兴的行为和机会伪造的工作，他的工作将在与规模相关的社会环境系统中构成三个主要的科学知识差距其次，它将开发一个数据驱动的框架，以量化动态水管理决策的驱动力和后果，以支持双向反馈的预测。外源氢化物质及其相互作用。值得支持使用Fe F Fe f oundation的知识分子和更广泛影响的评论标准的支持。