CAREER: Towards Watersheds as Water Treatment Plants through Advances in Distributed Sensing and Control

这一学院早期职业发展(CALEAR)奖支持的研究将探索实时控制水力基础设施的潜力，以减少河网中的营养物质污染。营养物污染是全世界地表水系统面临的最昂贵和最普遍的环境问题之一。农业和城市径流中的氮和磷助长了河流、湖泊和沿海水域藻类的生长。这些藻类繁殖会耗尽氧气水平，并释放出对人类健康有害的毒素。该项目将研究水坝等水利基础设施的实时控制如何通过模拟分水岭规模的废水处理厂的过程来处理营养污染。这一新方法有可能大大减少营养物质污染的影响，同时消除了对昂贵的基础设施扩建项目的需要。这些研究工作将得到一项教育计划的补充，该计划旨在通过开发一种新的以各级学生为对象的计算机模拟游戏，促进主动学习地表水水质概念。研究活动将很好地纳入教学和推广计划，通过积极和互动的学习机会进一步传播影响，以扩大对科学、技术、工程和数学(STEM)的参与。该项目将结合计算模型和真实世界实验评估，揭示水力控制对养分动态的影响的新的基础知识。首先，将开发一个新的计算水质模型来模拟营养盐在河网中的去向和迁移，该模型考虑了非恒定水力、多组分反应动力学和地下水交换。下一步，将研究水质数据同化的新方法，以提供有效控制所需的水质实时估计。第三，将使用稳健的模型预测控制方法来探索去除营养物质和藻类的最优水库调度策略，并在河网尺度上进行评估。营养动态的建模、估计和控制将根据测量数据进行验证，使用实验室规模的试验台和系统规模的案例研究，重点是不同大小的真实世界流域。这项研究将描述和量化积极控制水库的潜力，以减轻流域范围内的营养物质污染和藻类水华。为了促进广泛的教育推广，这项研究的结果将被整合到一个新的“沙盒”电脑游戏中，该游戏将模拟河流网络中营养物质与生态系统的相互作用。通过鼓励学生在他们自己的虚拟生态系统中管理水生生物，这个模拟游戏将有机地教授富营养化的机制和防止它所需的干预措施。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。

This Faculty Early Career Development (CAREER) award supports research that will explore the potential for real-time control of hydraulic infrastructure to reduce nutrient pollution in river networks. Nutrient pollution is one of the most costly and widespread environmental problems facing surface water systems worldwide. Nitrogen and phosphorus from agricultural and urban runoff fuel the growth of algae in rivers, lakes, and coastal waters. These algal blooms deplete oxygen levels and release toxins that are hazardous to human health. This project will investigate how real-time control of hydraulic infrastructure like dams can treat nutrient pollution by emulating processes from wastewater treatment plants at the watershed scale. This new approach has the potential to substantially reduce nutrient pollution impacts while obviating the need for expensive infrastructure expansion projects. These research efforts will be complemented with an educational plan designed to promote active learning of surface water quality concepts through the development of a new computer simulation game targeted at students of all levels. The research activities will be well integrated into teaching and outreach plans, to further disseminate the impacts through active and interactive learning opportunities to broaden participation in science, technology, engineering, and mathematics (STEM). This project will reveal new fundamental knowledge about the effects of hydraulic controls on nutrient dynamics using a combination of computational modeling and real-world experimental assessments. First, a new computational water quality model will be developed to simulate nutrient fate and transport in river networks accounting for unsteady hydraulics, multispecies reaction kinetics, and hyporheic exchange. Next, new methods for water quality data assimilation will be investigated to provide real-time estimates of water quality required for effective control. Third, optimal reservoir operation strategies for nutrient and algae removal will be explored using a robust model-predictive control approach and evaluated at the river network scale. Modeling, estimation, and control of nutrient dynamics will be validated against measured data using both a laboratory-scale testbed and system-scale case studies focused on real-world watersheds of different sizes. This research will characterize and quantify the potential for active control of reservoirs to mitigate nutrient pollution and algal blooms at the watershed scale. To facilitate broad educational outreach, the results of this research will be integrated into a new ‘sandbox’ computer game that will simulate nutrient-ecosystem interactions in river networks. By encouraging students to steward aquatic life in their own virtual ecosystems, this simulation game will organically teach the mechanics of eutrophication and the interventions needed to prevent it.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.