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Assessment of seasonal and polluting effects on the quality of river indus water by using multiple linear regression analysis

Author: 
Aziz-ur-Rahman, Pervez Akhter and Muhammad Mansha
Subject Area: 
Physical Sciences and Engineering
Abstract: 

In this study, statistical techniques such as Multiple linear regression analysis is applied to water quality data set monitored during Pre and Post monsoon 1982 -2012 to investigate in the extent of pollution and seasonal variation in river Indus waters. The variables were pH, BOD (Biochemical Oxygen Demand), COD (Chemical Oxygen Demand, TSS (Total Suspended Solid), TDS (Total Dissolve Solid), alkalinity, Cl-, HCO3-, SO4-2, Ca+2, Mg+2, Na+ and K+. Multiple linear regression equations established between above parameters and dependent variable such as electrical conductivity, which caused to predict the value of one parameter, if value of other is known. The above study provides us a tool to find the value of physico-chemical parameters and extent of pollution theoretically and seasonal variation, which is time saving as well as cost effective. The result obtained provides a method to characterize river water quality using statistical multiple linear regression analysis.

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