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dc.contributor.authorKwio-Tamale, Julius Caesar
dc.date.accessioned2023-02-10T08:23:18Z
dc.date.available2023-02-10T08:23:18Z
dc.date.issued2022-10
dc.identifier.citationKwio-Tamale, Julius Caesar(2022) Comparison of physical and statistical models in predicting space-time decay of residual chlorine in water distribution systemen_US
dc.identifier.urihttps://hdl.handle.net/20.500.12504/1208
dc.descriptionxviii,127p.:ill (some col)en_US
dc.description.abstractChlorine is the most widely used disinfectant in water distribution due to its efficacy, ease of application, low cost and extended disinfection durability. The World Health Organization recommends concentrations of residual chlorine in drinking water to be within 0.2 – 5 mg/l. Concentrations lower than 0.2 mg/l expose water consumers to secondary water-borne diseases. Chlorine concentrations more than 5 mg/l expose consumers to carcinogenic disinfection by-products. Studies on comparative analysis of performance of physical and statistical models in predicting chlorine decay in drinking water distribution system are lacking. The specific objectives of this study were: (1) characterization of residual chlorine decay parameters in water distribution, (2) assessment of space-time decay of chlorine in water distribution, (3) comparison of performance of models in predicting chlorine decay in water distribution and (4) identification of appropriate model(s) for predicting chlorine decay in water distribution system. Performance of EPANET physical model was compared with statistical models of multiple linear regression (MLR), principal component regression (PCR), lasso regression (LR), ridge regression (RR), decision tree (DT), random forest (RF) and artificial neural network (ANN). ANN performed best with R2 of 94% followed by MLR (63%), PCR (61%), RF (55%) and DT (41%). Initial chlorine and electrical conductivity were the two most significant parameters in water distribution that together contributed to about 90% of chlorine decay. Based on generalizability, dimensionality control and interpretability as desired factors for a good model, linear regression with R-squared of 63% and 0.045 mg/l error estimate performed best in predicting residual chlorine. Water zoning is recommended with existing water reservoirs as secondary chlorination points to maintain residual chlorine concentrations within 0.2 – 5 mg/l. In return, high and low dosages that cause carcinogenic disinfection by-products and predispose public health to secondary pathogenic infectious water-borne diseases respectively will both be avoided throughout water distribution networken_US
dc.language.isoenen_US
dc.publisherKyambogo University[unpublished work]en_US
dc.subjectSatistical models.en_US
dc.subjectResidual chlorine.en_US
dc.subjectWater distribution system.en_US
dc.titleComparison of physical and statistical models in predicting space-time decay of residual chlorine in water distribution systemen_US
dc.typeThesisen_US


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