APPLICATION OF MULTIPLE LINEAR REGRESSION MODELS TO DETERMINE MICROBIAL WATER QUALITY CHANGES ACROSS HIGHLY DISTURBED LOWER HIMALAYAN STREAM AND THE GROUNDWATER SOURCES IN THE PROXIMITY, JAMMU (INDIA)

Abstract

The study investigated the microbial quality of Behlol stream- a Lower Himalayan stream and groundwater sources in its proximity areas in terms of MPN index/100 ml for total and faecal coliforms and application of statistical tools like correlation and linear regression to deduce beneficial parametric associations for easy interpretation of the data. MPN/100 ml index analysis revealed severe microbial contamination at the surface water sampling site S2 and the nearby groundwater sites G2 and G3 indicating the impact of surface water pollution on the groundwater sources. The authors observed that the rate of groundwater contamination decreased with the increase in distance from the surface water sites suggesting that the groundwater pollution is mainly contributed by the release of combined industrial and sewage wastes into the Behlol stream. The study also identified bacterial genera like Escherichia, Enterobacter, Klebsiella, Citrobacter, Proteus, Salmonella, and Shigella, belonging to the family Enterobacteriaceae via colony cultural characteristics and biochemical tests. A significant relationship obtained from an orderly linear correlation and regression in this study provides a better alternative for a systematic study over the conventional techniques; reducing the quantum of analysis and can therefore be treated as a rapid method for water quality monitoring