CIVIC-PG Track A: Smart Watersheds for Conservation and Resilience

CIVIC-PG 轨道 A：保护和恢复力的智能流域

• 批准号: 2228343
• 负责人: Branko Kerkez
• 金额: $ 5万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2228343&HistoricalAwards=false
• 关键词: CIVIC; PG; Track; Smart; Watersheds

Flooding is the leading cause of natural disaster fatalities and property damage in the US. Simultaneously, communities along rivers are facing unprecedented ecological challenges, such as harmful algal blooms, polluted waters, and degraded fish habitats. This Civic Innovation Challenge (CIVIC) project will enable the smart watershed – a landscape covered by connected sensors, whose data are analyzed to coordinate the flow of water between communities. The smart watershed will help address challenges of water pollution, flooding, and extreme weather. This community-led project brings together watershed planners, policy planners, ecologists, ethnographers, engineers, and dam operators along the Huron River in Michigan. The research will span multiple disciplines, ecosystems, communities, and residents across 800 square miles. Once validated at this scale, the smart watershed will become a viable blueprint to address flooding, ecological conservation, and climate resilience for communities across the US.The guiding hypothesis of this project is that smart watersheds will reduce flooding and restore the natural flows of rivers by helping dam operators coordinate water releases between communities. The hypothesis will be tested by answering the following research questions: (1) which social mechanisms underpin the major barriers to the adoption of real-time coordination between distributed dam operators in a watershed, (2) how should real-time data be disseminated to maximize the usability of decision- support systems, and (3) how should dynamical control algorithms be structured, parametrized, and constrained to support a positive feedback loop that maximally incentivizes participation by a group of operators? This research will lead to advances in fundamental knowledge, spanning ecology, water science, social science, data science, and controls. The project will result web-based decision support systems, which will ingest sensor data to help operators coordinate the flow of water in real-time. In the long term, the project will culminate in a successful demonstration of real-time coordination, as measured by ecologic indicators, reduction in flooding and operator trust. Ecological indicators will be measured directly via sensors and laboratory samples, while operator perceptions, trust, and broader outcomes will be measured through ethnographic methods, interviews, and surveys. Finally, the collective team, in partnership with policy planners from the coalition of local governments, will promote the findings of the project as part of best practices that can be followed by others across country.This project is in response to the Civic Innovation Challenge program—Track A. Living in a changing climate: pre-disaster action around adaptation, resilience, and mitigation—and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.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.

洪水是美国自然灾害死亡和财产损失的主要原因。同时，河流沿岸的社区面临着前所未有的生态挑战，例如有害的藻类血液，受污染的水和鱼类栖息地。这项公民创新挑战（CIVIC）项目将使智能分水岭（CIVECIC） - 一个由连接的传感器覆盖的景观，其数据进行了分析以协调社区之间的水流。智能流域将有助于应对水污染，洪水和极端天气的挑战。这个社区主导的项目将分水岭的计划者，政策计划者，生态学家，民族志学家，工程师和大坝经营者汇集在一起​​，沿着密歇根州的休伦河沿线。这项研究将跨越800平方英里的多个学科，生态系统，社区和居民。一旦在这个规模上进行了验证，智能流域将成为一个可行的蓝图，以解决美国各地社区的洪水，生态保护和气候韧性。该项目的指导假设是，智能水域将减少洪水泛滥并恢复河流的自然流量，通过帮助河流的自然流动，通过帮助大坝在社区之间进行水上的水平，以帮助水流。 The hypothesis will be tested by answering the following research questions: (1) which social mechanisms underpin the major barriers to the adoption of real-time coordination between distributed dam operators in a watershed, (2) How should real-time data be disseminated to maximize the usability of decision- support systems, and (3) how should dynamic control algorithms be structured, parametrized, and constrained to support a positive feedback loop that maximum incentivizes一组运营商的参与？这项研究将导致基本知识的进步，涵盖生态学，水科学，社会科学，数据科学和控制。该项目将导致基于Web的决策支持系统，该系统将获取传感器数据以帮助操作员实时协调水流。从长远来看，通过生态指标，减少洪水和运营商的信任，该项目将在成功展示实时协调方面达到顶峰。生态指标将通过传感器和实验室样本直接测量，而操作员的看法，信任和更广泛的结果将通过人种学方法，访谈和调查来衡量。 Finally, the collective team, in partnership with policy planners from the coalition of local governments, will promote the findings of the project as part of best practices that can be followed by others across country.This project is in response to the Civic Innovation Challenge program—Track A. Living in a changing climate: pre-disaster action around adaptation, resilience, and mitigation—and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.This award反映了NSF的法定任务，并通过使用基金会的知识分子和更广泛的影响审查标准评估来诚实地表示支持。