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Heliyon ; 7(7): e07606, 2021 Jul.
Article in English | MEDLINE | ID: mdl-34381889

ABSTRACT

This work reports control strategies of the water quality in the city of Souk-Ahras (east Algeria). With the recent development, rapid population growth, and the consequences of climate change, the capacity of water supply reserves becomes more unpredictable in the long term. This has drastically affected the distributed water quantity. A correlation between bacteriological water analysis and the analysis of pollution indicative physicochemical parameters is developed to replace the slow bacteriological analysis, which takes more than two days, by directly accessible physicochemical analysis to anticipate the case-onset of waterborne diseases. A good correlation is found between different combinations of physicochemical pollution parameters: (Turbidity, Nitrates); (Turbidity, Active chlorine) (nitrates, active chlorine); (Ammonium, Chlorine) and (Turbidity, Ammonium) with Spearman rank coefficients of 0.8657, -0.8602 and -0.8531 -0.8227 et 0.7957 respectively. Besides, long term analysis (over several years) revealed a high correlation of more than 0.92 between the analysis of pollution indicative physicochemical parameters and bacteriological analysis. The EPANET software is used to simulate the hydraulic behaviour of the network system over an extended period within pressurized and pressure-deficient conditions. The simulation results of several supply scenarios of daily drinking water pressure in the city center area show that 62% of drinking water distribution system is supplied with a steep slope (80 m), 10% with unsatisfactory pressure and only 23% with acceptable pressure (1-80 m). Therefore, the high working pressure at the mesh, and the interruptions of the water supply are factors that can lead to the occurrence of cross-connection cases. This diagnosis of the defects in the water supply system is combined with a statistical data analysis of physicochemical parameters to set up an effective sampling strategy that takes into account the frequency of analysis and the areas at risk to prevent the risk of waterborne diseases.

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