APPLICATION OF MULTIPLE LINEAR REGRESSION MODELS TODETERMINE MICROBIAL WATER QUALITY CHANGES ACROSSHIGHLY DISTURBED LOWER HIMALAYAN STREAM AND THEGROUNDWATER SOURCES IN THE PROXIMITY, JAMMU (INDIA)RENU SHARMA AND DEEPIKA SLATHIAAbstract The study investigated the microbial quality of Behlol stream- a Lower Himalayan stream andgroundwater sources in its proximity areas in terms of MPN index/100 ml for total and faecalcoliforms and application of statistical tools like correlation and linear regression to deducebeneficial parametric associations for easy interpretation of the data. MPN/100 ml index analysisrevealed severe microbial contamination at the surface water sampling site S2 and the nearbygroundwater sites G2 and G3 indicating the impact of surface water pollution on the groundwatersources. The authors observed that the rate of groundwater contamination decreased with theincrease in distance from the surface water sites suggesting that the groundwater pollution ismainly contributed by the release of combined industrial and sewage wastes into the Behlolstream. The study also identified bacterial genera like Escherichia, Enterobacter, Klebsiella,Citrobacter, Proteus, Salmonella, and Shigella, belonging to the family Enterobacteriaceae viacolony cultural characteristics and biochemical tests. A significant relationship obtained from anorderly linear correlation and regression in this study provides a better alternative for a systematicstudy over the conventional techniques; reducing the quantum of analysis and can therefore betreated as a rapid method for water quality monitoring. |