Real-time foul sewer hydraulic modelling driven by water consumption data from water distribution systems
•Water consumption data is used to drive real-time FSS modelling.•WDS and FSS models are integrated to simulate sewer hydraulics in real-time.•The equifinality issue within the FSS modelling is solved.•The utility of the proposed method is demonstrated using two real FSSs.•The proposed method is a n...
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Veröffentlicht in: | Water research (Oxford) 2021-01, Vol.188, p.116544-116544, Article 116544 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Water consumption data is used to drive real-time FSS modelling.•WDS and FSS models are integrated to simulate sewer hydraulics in real-time.•The equifinality issue within the FSS modelling is solved.•The utility of the proposed method is demonstrated using two real FSSs.•The proposed method is a novel manner for real-time FSS modelling.
Real-time hydraulic modelling can be used to address a wide range of issues in a foul sewer system and hence can help improve its daily operation and maintenance. However, the current bottleneck within real-time FSS modelling is the lack of spatio-temporal inflow data. To address the problem, this paper proposes a new method to develop real-time FSS models driven by water consumption data from associated water distribution systems (WDSs) as they often have a proportionally larger number of sensors. Within the proposed method, the relationship between FSS manholes and WDS water consumption nodes are determined based on their underlying physical connections. An optimization approach is subsequently proposed to identify the transfer factor k between nodal water consumption and FSS manhole inflows based on historical observations. These identified k values combined with the acquired real-time nodal water consumption data drive the FSS real-time modelling. The proposed method is applied to two real FSSs. The results obtained show that it can produce simulated sewer flows and manhole water depths matching well with observations at the monitoring locations. The proposed method achieved high R2, NSE and KGE (Kling-Gupta efficiency) values of 0.99, 0.88 and 0.92 respectively. It is anticipated that real-time models developed by the proposed method can be used for improved FSS management and operation.
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ISSN: | 0043-1354 1879-2448 |
DOI: | 10.1016/j.watres.2020.116544 |