SCC-IRG track 2: smart watersheds for conservation and resilience

This federal Project Grant award, valued at $755,416.00, was provided by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) to the Regents of the University of Michigan. The objective is to develop and implement a "digital water management system" that enhances coordination among dam operators to optimize water flow and improve ecological outcomes within a watershed.

The key research objectives are: 1) investigating the role of social capital in decision-making among rural and urban dam operators, 2) developing new methodologies to understand the relationship between river flows and fish habitats, and 3) creating novel control algorithms to regulate water flow using model-predictive control theory. The project will deploy a network of sensors and a web-based decision support system to facilitate real-time data sharing and predictive modeling. A sub-award of $21,176 was provided to the Huron River Watershed Council to assist in developing and launching a tool for use by the Council and its stakeholders, with the potential to scale the solution regionally and nationally. The award period runs from September 1, 2024 to August 31, 2027.

Abstract

The objective of this smart and connected communities (SCC) project is to support research on mitigating flooding risk, improving water quality, and restoring ecological habitats through coordinated DAM releases across communities within a watershed. Flooding is the leading natural disaster causing fatalities and property damage in the united states, and the increasing frequency and intensity of storms exacerbate this problem. Additionally, rural and low-income communities are disproportionately affected, as they often reside in low-lying areas prone to flooding. This project addresses these challenges by researching creation and implementation of a digital watershed system ? An interconnected landscape of sensors and data analysis tools to manage water flow effectively. IT provides environmental benefits, reduces flooding risk, and fosters social capital by building trust and collaboration among diverse groups of community members. The broader significance lies in its potential to transform watershed management across the country, offering a scalable, technology-driven solution to pressing water and environmental issues. The primary goal of this research project is to develop and implement a digital water management system that enhances coordination among DAM operators to optimize water flow and improve ecological outcomes. Three integrative research objectives are pursued: (1) investigating the role of social capital in decision-making among rural and urban DAM operators, and translating these insights into digital tools that promote coordination; (2) developing new methodologies to understand the relationship between river flows and fish habitats, and setting flow targets based on real-time sensor data; (3) creating novel control algorithms to regulate water flow using model-predictive control (MPC) theory, ensuring stability and efficiency even under varying levels of human operator participation. The interdisciplinary team, comprising DAM operators, watershed planners, regulators, social scientists, ecohydrologists, and engineers, deploys a network of sensors and a web-based decision support system to facilitate real-time data sharing and predictive modeling. The output includes fundamental scientific insights and practical solutions for watershed management, potentially serving as a model for similar efforts nationwide. 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.- subawards are planned for this award.