Overcoming Social and Technical Barriers for the Broad Adoption of Smart Stormwater Systems
Lead PI:
Branko Kerkez
Co-Pi:
Abstract

In the age of the self-driving car, what role can autonomous technologies play in improving water systems? Floods are the leading cause of severe weather fatalities across the United States. Furthermore, large quantities of metals, nutrients, and other pollutants are washed off during storm events, making their way via streams and rivers to lakes and costal zones. To contend with these concerns, most communities across the United States maintain dedicated infrastructure (pipes, ponds, basins, wetlands, etc.) to convey and treat water during storm events. Much of this stormwater infrastructure is approaching the end of its design life, which results in more flooding and degraded water quality. Instead of building new and bigger stormwater infrastructure, which is cost prohibitive for many communities, it is possible to use existing infrastructure more effectively. The goal of this proposal is to enable the next generation of smart and connected stormwater systems, which use sensors to anticipate changes in weather and the urban landscape, and adapt their operation using active flow controls (e.g., gates, valves, pumps). This will drastically improve community resilience to floods and water quality. Equipping stormwater systems with low-cost sensors and controllers will provide a cost-effective solution to transform infrastructure from static to adaptive, permitting it to be automated and instantly reconfigured to respond to changing community needs and preferences. This research will address a truly national-scale infrastructure challenge and will lay the foundation upon which to empower and educate communities to adopt smart and autonomous stormwater solutions.

The research to enable "smart" stormwater systems will be conducted by a team of engineers, social scientists, computer scientist and environmental experts in tight collaboration with decision makers and citizens across four communities in the United States. The team will close fundamental knowledge gaps to explain (1) to what extent real-time control can improve the hydraulic and water quality performance of individual stormwater sites, (2) how to identify and overcome the barriers that public perception poses to the adoption of smart stormwater systems, and (3) how system-level interoperability can be achieved to guarantee safe and effective performance at the scale of entire communities (100s to 1000s of controlled sites). This will be achieved through three closely coupled scientific objectives, which will include testing of laboratory models of control sites, field-scale water quality studies, the formation of community advisory groups, the analysis of residential surveys in each community, and the stability analysis of system-level control algorithms under various sources of uncertainty. The approach is thus fundamentally motivated around the goal of scalability, as the results will be relevant to many communities across the United States, regardless of their size. By open-sourcing the efforts on Open-Storm.org and other public forums, the project will also support research capacity-building by reducing the overhead required by others to deploy smart and connected stormwater systems.

Branko Kerkez
Branko Kerkez is the Arthur F. Thurnau Associate Professor of Civil and Environmental Engineering at the University of Michigan. His research interests include water, data, and sensors. His group is working to enable smart water systems, which autonomously adapt themselves to changing conditions using real-time data and controls. His research projects have spanned wireless sensing of large mountain basins, real-time flood forecasting, robotics, and real-time control algorithms for water systems. He is the founder of Open-Storm.org, an open-source consortium dedicated to freely sharing hardware, software, and case studies on smart water systems. He received his M.S. and Ph.D. in Civil and Environmental Engineering, and an M.S. in Electrical Engineering and Computer Science, all from UC Berkeley. He is a recipient of the National Science Foundation’s CAREER award and was recognized by National Academy of Engineering as a Gilbreth Lecturer.
Performance Period: 09/01/2017 - 08/31/2022
Institution: Regents of the University of Michigan - Ann Arbor
Sponsor: National Science Foundation
Award Number: 1737432