Real‐Time Control of Urban Headwater Catchments Through Linear Feedback: Performance, Analysis, and Site Selection

Abstract

The real‐time control of urban watersheds is now being enabled by a new generation of “smart” and connected technologies. By retrofitting stormwater systems with sensors and valves, it becomes possible to adapt entire watersheds dynamically to individual storms. A catchment‐scale control algorithm is introduced, which abstracts an urban watershed as a linear integrator delay dynamical system, parameterizes it using physical watershed characteristics, and then controls network flows using a Linear Quadratic Regulator. The approach is simulated on a 4‐km2 urban headwater catchment in Ann Arbor, Michigan, demonstrating the gains of a stormwater system that can adaptively balance between flood mitigation and flow reduction. We introduce an equivalence analysis and illustrate the performance of the controlled watershed across large events (30‐year storms) to show the uncontrolled passive watershed can only match it during smaller events (10‐year storm). For these smaller events, the storage volume of the controlled storage nodes (ponds, basins, and wetlands) could be reduced as much as 50% and still achieve the same performance of the controlled watershed. A controller placement analysis is also carried out, whereby all possible combinations of controlled sites are simulated across a wide spectrum of design storms. We show that the control of every storage node may not be needed in a watershed, but rather that in our case study a small subset (30%) of the overall watershed can be controlled in coordination to achieve outcomes that match a fully controlled system, even when tested across a long‐term rainfall record and under noisy sensor measurements.

Improved reliability of stormwater detention basin performance through water quality data-informed real-time control

“…There are studies that demonstrate the improved hydraulic and hydrological performance of an urban watershed by actively controlling a series of detention ponds. Wong and Kerkez, (2018) reduced the engineered watershed storage volume up to 50% by actively controlling 4 detention ponds depending on their hydraulics. Mullapudi et al, (2017) showed three ponds and a treatment wetland can be controlled simultaneously to reduce downstream flood risk also getting 46.48% nitrate load reduction.…”

A data-driven improved fuzzy logic control optimization-simulation tool for reducing flooding volume at downstream urban drainage systems

“…Prior modeling studies have documented the performance of real-time control strategies in decreasing flooding magnitude and peak water level approximately by 40% to 70% (Sadler et al, 2019;Wong and Kerkez, 2018). However, these studies, on the one hand, ignore the physical dynamics by a linearizing system or manually set-up the control rules based on experts' experience.…”

“…RTC can be considered as a dynamic, heuristic, and low-cost technique for three perspectives: optimizing operation strategy, adapting UDSs to changing conditions, and improving eco-system (García et al, 2015). By retrofitting the existing UDSs with smart device such as digital controllers and sensors, instead of renewing pipelines or re-sizing storage facilities, RTC adaptively allows existing UDSs to make full use of capacity to selectively purge retained water before the next storm comes by operating remote-controlled actuators (weirs, gates, valves, and orifices) (Wong and Kerkez, 2018). Although RTC has been applied to UDSs for over 50 years since the 1960s, there are still some gaps calling for participation and efforts (Schütze et al, 2004).…”

Recent Advances in Information and Communications Technology (ICT) and Sensor Technology for Monitoring Water Quality

“…Thus, it provides more precise information on the pollutant load during flood events [79,80]. This real-time flow-rate-sensing technology enables the proper management of water distribution systems during flood events in urban watersheds [81].…”