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

洪水是美国自然灾害死亡和财产损失的主要原因。与此同时，河流沿着社区正面临前所未有的生态挑战，例如有害藻华、沃茨水污染和鱼类栖息地退化。这个公民创新挑战（CIVIC）项目将实现智能流域-连接传感器覆盖的景观，其数据经过分析以协调社区之间的水流。智能流域将有助于解决水污染，洪水和极端天气的挑战。这个社区主导的项目汇集了流域规划者，政策规划者，生态学家，人种学家，工程师和沿着密歇根州休伦河的大坝运营商。该研究将跨越800平方英里的多个学科、生态系统、社区和居民。一旦在这个规模上得到验证，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，生态保护和气候适应能力。该项目的指导假设是，智能流域将减少洪水，并通过帮助水坝运营商协调社区之间的水释放来恢复河流的自然流量。将通过回答以下研究问题来检验假设：（1）哪些社会机制是流域中分布式大坝运营商之间采用实时协调的主要障碍的基础，（2）如何传播实时数据以最大化决策支持系统的可用性，以及（3）如何构造动态控制算法，参数化，并限制支持一个积极的反馈循环，最大限度地激励一组运营商的参与？这项研究将导致基础知识的进步，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，以帮助运营商实时协调水流。从长远来看，该项目将最终成功展示实时协调，如生态指标，减少洪水和运营商的信任。生态指标将通过传感器和实验室样本直接测量，而运营商的看法，信任和更广泛的成果将通过人种学方法，访谈和调查来衡量。最后，集体团队将与地方政府联盟的政策规划者合作，推广该项目的成果，将其作为最佳实践的一部分，供全国各地的其他人效仿。生活在不断变化的气候中：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。

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.