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

洪水是美国自然灾害造成人员伤亡和财产损失的主要原因。与此同时，河流沿岸的社区正面临前所未有的生态挑战，如有害的藻类大量繁殖、受污染的水域和退化的鱼类栖息地。这一公民创新挑战(Civic)项目将实现智能分水岭-一种由连接的传感器覆盖的景观，其数据被分析以协调社区之间的水流。智能分水岭将有助于应对水污染、洪水和极端天气的挑战。这个由社区主导的项目将密歇根州休伦河沿岸的分水岭规划者、政策规划者、生态学家、人种学家、工程师和大坝操作员聚集在一起。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。一旦在这种规模上得到验证，智能分水岭将成为美国各地社区解决洪水、生态保护和气候适应能力的可行蓝图。该项目的指导假设是，智能分水岭将通过帮助大坝运营者协调社区之间的水资源释放，减少洪水泛滥，恢复河流的自然流量。这一假设将通过回答以下研究问题来检验：(1)哪些社会机制支撑了流域中分布式大坝运营商之间采用实时协调的主要障碍，(2)实时数据应该如何传播，以最大限度地提高决策支持系统的可用性，以及(3)动态控制算法应该如何构建、参数化和约束，以支持最大限度地激励一组运营商参与的正反馈循环？这项研究将导致基础知识的进步，跨越生态学、水科学、社会科学、数据科学和控制。该项目将产生基于网络的决策支持系统，该系统将摄取传感器数据，以帮助操作员实时协调水流。从长远来看，该项目将以生态指标、洪水的减少和运营商的信任为衡量标准，成功地展示实时协调。生态指标将通过传感器和实验室样本直接测量，而操作员的感知、信任和更广泛的结果将通过民族志方法、访谈和调查来测量。最后，集体团队将与地方政府联盟的政策规划者合作，将该项目的发现作为最佳实践的一部分，供全国各地的其他人效仿。该项目是对公民创新挑战计划的回应-轨道A。生活在不断变化的气候：围绕适应、恢复和缓解的灾难前行动-是NSF、国土安全部和能源部的合作。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.