Modeling Operations in System-Level Real-Time Control for Urban Flooding Reduction and Water Quality Improvement—An Open-Source Benchmarked Case

Advancements in smart sensing and control technologies enable urban drainage engineers to retrofit stormwater storage facilities with real-time control devices for mitigating stormwater in-site overflow, downstream flooding, and overloaded total suspended solids (TSS) in drainage pipes. While the smart technology can improve the performance of the static drainage systems, coordinatively controlling multiple valve and gate operations poses a significant challenge, especially at a large-scale watershed. Using a benchmark stormwater model located at Ann Arbor, Michigan, USA, we assessed the impact of different real-time control strategies (local individual downstream control and system-level multiple control) on balancing flooding mitigation at downstream outlets and TSS reduction at upstream storage units, such as detention ponds. We examined changes in peak water depth, outflow, and TSS as indicators to assess changes in water quantity and quality. The results indicate that system-level control can reduce peak water depth by up to 7.3%, reduce flood duration by up to 34%, and remove up to 67% of total suspended solids compared with a baseline uncontrolled system, with the outflow from upstream detention ponds being the most important hydraulic indicator for control strategy rule set-up. We find that system-level control does not always outperform the individual downstream controls, particularly in alleviating flooding duration at some downstream outlets. With urban growth and a changing climate, this research provides a foundation for quantifying the benefits of real-time control methods as an adaptive stormwater management solution that addresses both water quantity and quality challenges.