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

Abstract

The objective of stormwater detention basins is to capture stormwater runoff to reduce and delay peak flow and to improve the water quality. These objectives can be improved upon by actively controlling the outflow of the basins rather than traditional passive outflow structures. There are studies demonstrating the performance of the active controls that respond in real-time to basin hydraulics, detention time, and rainfall forecasts. We hypothesize that the performance of these active controls can be improved upon by incorporating real-time water quality data streams into the control algorithm. Furthermore, we hypothesize that performance of these active controls also depends on hydrologic variability, perturbing the highly dynamic rainfall-runoff process. Here, these hypotheses are tested using a numerical modeling framework evaluating the systemslevel reliability of passive and active control of stormwater basin outflow using a Monte Carlo method. The numerical modeling is performed in EPA-SWMM urban hydrologic model driven by stochastic rainfall time-series generated from the Modified Bartlett-Lewis Rectangular Pulses Model. Water quality-informed real-time active control algorithms are developed, tested, and demonstrated to result in a clear improvement over the traditional passive (no control) systems and other storage-based active controls for water and suspended sediment capture. Duration curve analysis showed that both water level-and water quality-informed control performance varied for different storm return periods and this variability could partly be attributed to the fraction of time the valve is closed. In addition, control performance was sensitive to rainfall variability, generally decreasing as storms become less frequent and more intense. Therefore, control system performance may depend on seasonal and longer timescale variability in climate and rainfall-runoff processes. We anticipate this study to be a starting point to incorporate theories of reliability to assess detention basin and conveyance network performance under more complex real-time control algorithms and failure modes.

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

“…Regarding future work, rather than using historical records, considering forecasting information like rainfall forecasts as the FIS optimization inputs to tune CMFPs is valuable for control operation decsision-making (Shishegar et al, 2019). This could facilitate the performance of SWMM_FLC by making the fuzzy control strategy more adaptive to the coming storm events and more resilient to the potential failures (Parolari et al, 2018;Sharior et al, 2019). Although this study has address the downstream flooding problem, future work can switch to water quantity improvement by reducing the pollutant concentration and sedimentation issues in UDSs, especially in some cases with frequent combined sewer overflow and severe illicit intrusions.…”

Urban stormwater characterization, control, and treatment

“…The potential benefits of real‐time control of CSP outlets were demonstrated using a conceptualized CSP modeled in SWMM with a four‐dimensional dynamic system of passive, detention, on/off, and TSS control schemes followed by the use of the Monte Carlo method for failure analysis. The case study, situated in Milwaukee, Wisconsin, USA, showed that TSS control reduced system failure probability compared to on/off and detention control options and that TSS and detention controls settled greater amounts of solids relative to on/off control (Sharior, Mcdonald, & Parolari, 2019). Shishegar, Duchesne, and Pelletier (2019) also explored the use of real‐time control of a CSP outlet via modeling with PCSWMM 7.0.…”

Nature-based solutions and Real-time control: Challenges and opportunities

“…Detention basins are large-scale devices and are directly connected to urban drainage system. Several results shows that detention basins have good performance avoiding flood downstream, however water quality can be an issue [57]. The detention basin cycle over rainy and dry seasons can accumulate sediments.…”

“…In order to improve quality performance at detention basins, [57] used RTC algorithms to control a simulated detetion basin. While passive device have shown 64% of TSS removal efficiency, the performance of detention basin with RTC were 95%.…”