Water distribution networks (WDNs) could present problems of pathogen intrusion that affect the health of consumers. One solution to diminish this risk is to add more disinfectant to the water at the drinking water treatment plant (DWTP). However, this increases the cost of water treatment and may also cause the formation of trihalomethanes. Mexico has the largest bottled water market in the world. Also, most houses are built with individual storage containers due to intermittent service, which generates a greater residence time of the water before use. This paper shows an alternative to guarantee minimum disinfection along WDNs and diminish the use of disinfectant at the DWTP considering the conditions of water consumption and use in Mexico. We propose a model based on Genetic Algorithms to obtain scenarios where free chlorine is maintained at the minimum permissible concentration throughout the day. In addition, Water Managers could optimize the use of disinfectant by implementing booster chlorination stations (BCSs). The results show that chlorine use could be reduced by 38%, therefore guaranteeing the chlorine concentration limits along the WDN.

Chlorine demand as a disinfectant for water utility impacts on unintended energy consumption from electrolysis manufacture; thus, diminishing the chlorine consumption also reduces the environmental impact and energy consumption. Problems of disinfectant distribution and uniformity in Water Distribution Networks (WDN) are associated with the exponential urban growth and the physical and biochemical difficulties within the network. This study optimizes Chlorine Booster Stations (CBS) location on a network with two main objectives; (1) to deliver minimal Free Residual Chlorine (FRC) throughout all demand nodes according to country regulations, and (2) to reduce day chlorine mass concentration supplied in the system by applying an hour time pattern in CBS, consequently associated economic, energy and environmental impacts complying with regulatory standards. The application is demonstrated on a real-world WDN modeled from Guanajuato, Mexico. The resulting optimal location and disinfectant dosage schedule in CBS provided insights on maintaining disinfectant residuals throughout all the WDN to prevent health issues and diminishing chlorine consumption.

Abstract:In Water Distribution Networks, the chlorine control is feasible with the use of water quality simulation codes. EPANET is a broad domain software and several commercial computer software packages base their models on its methodology. However, EPANET assumes that the solute mixing at cross-junctions is "complete and instantaneous". Several authors have questioned this model. In this paper, experimental tests are developed while using Copper Sulphate as tracer at different operating conditions, like those of real water distribution networks, in order to obtain the Residence Time Distribution and its behavior in the mixing as a novel analysis for the cross-junctions. Validation tests are developed in Computational Fluid Dynamics, following the k-ε turbulence model. It is verified that the mixing phenomenon is dominated by convection, analyzing variation of Turbulent Schmidt Number vs. experimental tests. Having more accurate mixing models will improve the water quality simulations to have an appropriate control for chlorine and possible contaminants in water distribution networks.

In Water Distribution Networks (WDN), the water quality could become vulnerable due to several operational and temporal factors. Epanet is a hydraulic and water quality simulation software, widely used, to preserve the control of chemical disinfectants in WDN among other capabilities. Several researchers have shown that the flow mixing at Cross-Junctions (CJs) is not complete as Epanet assumes for the cases of two contiguous inlets and outlets. This paper presents a methodology to obtain the outlet concentrations in CJs based on experimental scenarios and a validated Computational Fluid Dynamics (CFD) model. In this work, the results show that the Incomplete Mixing Model (IMM) based on polynomial equations, represents in a better way the experimental scenarios. Therefore, the distribution of the concentration could be in different proportions in some sectors of the network. Some comparisons were made with the complete mixing model and the Epanet-Bulk Advective Mixing (BAM), obtaining relative errors of 90% in some CJs.

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