Water quality-based real time control of combined sewer systems

Abstract : Real time control (RTC) is considered as a cost-efficient solution for combined sewer overflow (CSO) reduction as it optimises the available capacity of sewer networks. RTC helps to prevent the need for construction of additional retention volumes, increases the network adaptability to changes in water management policies, and above all alleviates the environmental impact of CSOs. Following increasing interest in water quality-based RTC (QBR), this thesis demonstrates a simple and nothing-to-lose QBR strategy to reduce the amount of CSO loads during storm events. The performance of the QBR strategy, based on Mass-Volume (MV) curves prediction, is evaluated by comparison to a typical hydraulics-based RTC (HBR) strategy. A proof-of-concept study is first performed on a small catchment of 205 ha to test the new QBR concept using 31 storm events during a two-year period. Compared to HBR, QBR delivers CSO load reduction for more than one third of the events, with reduction values from 3 to 43 %. The QBR strategy is then implemented on the Louis Fargue catchment (7700 ha) in Bordeaux, France and similarly compared with the HBR strategy. By implementing QBR on 19 storm events over 15 months, its performance is consistent, bringing valuable benefits over HBR, with 17 out of 19 events having load reduction varying between 6 and 28.8 %. The thesis further evaluates the impact of MV curve prediction uncertainty (due to model prediction uncertainty) on the performance of the QBR strategy, using a representative storm event. The resulting range of uncertainty is limited. Besides, results of the sensitivity study show that the choice of the QBR or HBR strategy should take into account the current tank volumes and their locations within the catchment.
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Submitted on : Tuesday, December 10, 2019 - 4:17:46 PM
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  • HAL Id : tel-02166212, version 2


Duy Khiem Ly. Water quality-based real time control of combined sewer systems. Environmental Engineering. Université de Lyon, 2019. English. ⟨NNT : 2019LYSEI032⟩. ⟨tel-02166212v2⟩



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