Model Performance Indicator of Aging Pipes in a Domestic Water Supply Distribution Network

Abstract

Aging pipes in the domestic water distribution network have the potential to decrease the quality and quantity of the treated water supplied to the consumers. Therefore, a calibrated water distribution model is helpful to monitor and understand the behaviour of a real water distribution network. However, a comprehensive performance indicator and an integrated method to assess the efficiency of model performance have not been well established in the literature. This study developed a methodology for a model calibration exercise, with consideration of two uncertainty parameters, i.e., Hazen–Williams roughness coefficient of the pipes and Non-Revenue Water (NRW) in each nodal demand. Following this, a statistical color-coded performance indicator was established, based on the Nash–Sutcliffe Efficiency Coefficient (NSEC), the coefficient of determination (R2), the correlation coefficient (r), and the Mean Absolute Error (MAE). The accuracy of the calibrated model was measured by Discrepancy Ratio (DR) analysis. This study concluded that the model performed well when NRW was added to the nodal demand in zone(s) with suspected water loss activities. The suggested Hazen–Williams roughness coefficient for PVC pipes was between 130 and 140 for pipes aged more than 20 years. The threshold error value to determine the accuracy of the simulated model was proposed to be between –0.05 and 0.05.

Chlorine Decay Simulation in Water Distribution System Using EPANET

“…Other than graphical approach (as illustrated in Fig. 2), four statistical analyses were also used to evaluate the model performance, namely, the Nash-Sutcliffe Efficiency Coefficient (NSEC), Mean Absolute Error (MAE), Determination Coefficient (R2) and Discrepancies Ratio (DR) [10]. NSEC value of 1 indicates that the model is able to estimate the flow as good as the observed data, while the efficiency value of less than zero shows that the simulated result is less than the actual mean [12][13].…”

“…For the purpose of model calibration, the simulated flow estimated by EPANET is compared with observed (measured) flow. A comprehensive colour-coded indicator developed by Abd Rahman et al [10] was used to determine the model performance in replicating the real hydraulic characteristics and residual chlorine concentrations in the water distribution system.…”

“…Following this, the first order chlorine decay model was selected in terms of the reaction of chlorine with natural organic matter, represented by bulk decay (kb) and the inner surface of the pipe, also known as wall decay (kw). The wall decay coefficient (kw) is determined by trial and error method during the model calibration process [10]. The calibration file was created based on the measurement of chlorine concentration at three points in the water distribution system.…”

Development of a Fuzzy-Function-Based Performance Indicator for Water Distribution System’s Emergency Condition

“…This clearly demonstrates that reservoirs at higher elevations are more responsible for WDS EIO. Therefore, to improve the satisfaction with the water supply (i.e., increase FMPM) under emergency water supply conditions, an energy head can be added to the reservoir (e.g., install operating pumps) to increase the available supply Equation (1). Figure 7 shows the changes in FMPME for each block in all scenarios.…”

“…In addition, the results of a performance assessment under various abnormal conditions can contribute to the decision-making process of policymakers by establishing measures to reduce damage and quantifying the damage reduction effect. A number of studies have been conducted on performance assessment, and performance indicators (PIs) have been developed for WDS O&M in some countries [1][2][3][4]. PIs play a key role in the setting of objectives and development of effective countermeasures by providing an objective and reliable standard for assessment [5].…”