To increase the resilience of water supplies, this project is developing a smart water system that integrates smart and connected (S&C) technology and adaptive management to ensure safe drinking water for communities. The smart water system will consist of sensor networks embedded in a drinking water reservoir to reduce delays and enhance feedbacks between the detection of water quality degradation and decisive management action to mitigate such threats.
Major Research Innovations
Objective 1: We will create an embedded network of high-frequency water quality sensors in a drinking water reservoir in Roanoke, Virginia that will become a prototype for hundreds of other water supply reservoirs. Our team will be deploying novel sensor technology that has the potential to transform both water quality monitoring and our understanding of freshwater biogeochemical cycling.
Objective 2: We will develop and evaluate a new model-data fusion approach that will advance the field of environmental forecasting. At the core of our forecasting system is a novel predictive modeling framework that integrates data from distributed sensors at the reservoir with a simulation model to support human-in-the-loop decisions. We will also develop new cyberinfrastructure techniques using virtual private network overlays to ensure secure data transfer and simulation modeling. Our networking methods will be scalable to many other applications for improving sensor access, data transfer, and scheduling and execution of model simulations.
Objective 3: We will use human-centered design (HCD) to translate complex high-frequency data and simulation model output into useful decision support tools for managers. This HCD application fundamentally contributes to the resilience of the drinking water social-ecological system by increasing the adaptive capacity of the water utility by enabling iterative decision-making and rapid management interventions. Moreover, by determining the most effective way to communicate data and model output to managers, we will advance our understanding of how S&C technologies affect decision-making.
Objective 4: We will evaluate the factors driving social trust and acceptance of S&C technology in the community. This project is one of the first studies that quantifies how the public perceives the adoption and use of S&C technologies to improve drinking water quality by their utilities, and the relationship between public perception, trust in the utility, and acceptance of the S&C technology. Our results will serve as a guide to other communities to better evaluate how institutional decisions made in the interest of the public are understood by the public.
Objective 5: Finally, by developing teaching materials that expose students to data emerging from S&C technology, we will improve students’ interest in and preparedness for STEM degrees. Engaging students in hands-on data analysis activities translates into a workforce with increased data science, systems thinking, and quantitative skills.
Community Engagement: Our project examines how different stakeholders in the community perceive the adoption and use of S&C technology by institutions. The foundation of this project is our 20-year collaboration with the Western Virginia Water Authority (WVWA), a drinking water utility in Roanoke, Virginia that provides water for >300,000 people. WVWA managers will participate in the co-design and application of decision support tools from the smart water system in their day-to-day management activities (Obj. 3). In addition, we will assess the Roanoke public’s understanding of the risks and benefits of S&C technology, and their general acceptance of the smart water system by embedding information on S&C technology in their yearly water quality reports and assessing their perceptions with survey research (Obj. 4). To enhance resilience of drinking water systems, we must understand how managers adopt and adapt to this S&C technology over time, as well as how the public perceives the operation and use of S&C technology within their water system.