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Water SA

versión On-line ISSN 1816-7950
versión impresa ISSN 0378-4738

Resumen

HAIDER, Husnain et al. Framework for optimizing chlorine dose in small - to medium-sized water distribution systems: A case of a residential neighbourhood in Lahore, Pakistan. Water SA [online]. 2015, vol.41, n.5, pp.614-623. ISSN 1816-7950.  http://dx.doi.org/10.4314/WSA.V41I5.04.

To maintain desirable residual chlorine for a groundwater source, optimizing the chlorine dose in small- to medium-sized water distribution systems (SM-WDS) is a daunting task in developing countries. Mostly, operators add a random chlorine dose without recognizing the smaller size of their distribution network. In this research, a modelling framework for optimizing chlorine dose in SM-WDS is developed. In order to evaluate its practicality, the proposed framework has been applied in a case study of a residential neighbourhood in Lahore (Pakistan) with a small network spanning over 0.35 km2. Three datasets for residual chlorine were monitored at 6 locations spread over the study area. EPANET 2.0 software was used for hydraulic and residual chorine modelling. The bulk decay coefficient (Kb) was determined in the laboratory, whereas the wall decay coefficient (K ) was estimated by calibrating the simulation results with the residual chlorine determined in the field. Based on the calibrated EPANET simulations, a fuzzy rule-based model was developed for pragmatic application of the proposed framework. Scenario analyses for different situations have also been carried out for achieving residual chlorine required at the consumer end. This exercise revealed that much lower chlorine doses than the existing practice can generate detectable chlorine residuals. Moreover, the model can be used to deal with emergency situations, which may arise in developing countries due to viral outbreaks and cross-contamination events in SM-WDS.

Palabras clave : small-to-medium-sized water distribution systems; residual chlorine modelling; water quality; chlorine decay coefficients; fuzzy rule-based modelling; EPANET.

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