Abstract
Calibration of a water distribution system (WDS) hydraulic model requires adjusting several parameters including hourly or sub-hourly demand multipliers, pipe roughness and settings of various hydraulic components. The water usage patterns or demand patterns in a 24-h cycle varies with the customer types and can be related to many factors including spatial and temporal factors. The demand patterns can also vary on a daily basis. For an extended period of hydraulic simulation, the modelling tools allows modelling of the variable demand patterns using daily multiplication factors. In this study, a linear modelling approach was used to handle the variable demand patterns. The parameters of the linear model allow modelling of the variable demand patterns with respect to the baseline values, and they were optimised to maximise the association with the observed data. This procedure was applied to calibrate the hydraulic model developed in EPANET of a large drinking water distribution system in regional South Australia. Local and global optimisation techniques were used to find the optimal values of the linear modelling parameters. The result suggests that the approach has the potential to model the variable demand patterns in a WDS hydraulic model and it improves the objective function of calibration.
Highlights
IntroductionDrinking water utilities are aimed at continuously delivering good quality water with sufficient pressure to its customers at minimal cost [1]
The EPANET hydraulic model for the Tailem Bend–Keith (TBK) water distribution system (WDS) was calibrated for a period of four weeks in early February–March, 2021
A large drinking water distribution system in South Australia was selected as a case study
Summary
Drinking water utilities are aimed at continuously delivering good quality water with sufficient pressure to its customers at minimal cost [1]. Raw water after it has gone through several treatment processes is supplied to consumers via a water distribution system (WDS). Hydraulic models are frequently used to study and analyse the behaviour of a WDS. The applications of these models include, but are not limited to, the investigation of various management scenarios, extension of the WDS, determination of the optimal network settings and identification of the critical areas for rehabilitation [2]. Ormsbee and Lingireddy [3] suggested that a maximum deviation of 10% between the observed and the model-simulated values can be considered as a satisfactory calibration in most planning applications, while a deviation of 5% is highly desirable for system design, operation and the application of water quality modelling
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