The Analysis of Ground Water Quality Status using Linear Regression Method

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2016 by IJETT Journal
Volume-38 Number-4
Year of Publication : 2016
Authors : Rahane Prashant Bhausaheb, Dr. M. V. Jadhav
DOI :  10.14445/22315381/IJETT-V38P240


Rahane Prashant Bhausaheb, Dr. M. V. Jadhav"The Analysis of Ground Water Quality Status using Linear Regression Method", International Journal of Engineering Trends and Technology (IJETT), V38(4),223-228 August 2016. ISSN:2231-5381. published by seventh sense research group

Availability of ground water in Sangamner Taluka is ranging in between 5.5 and 10.25 m below ground level, out of the available ground water sources about 75 % is unfit for drinking purpose. Scenario becomes worse during the summer. Most of the groundwater sources are contaminated due to intensive irrigation and effluent discharge by Sugar Factories in the Pravara river basin. Ground water is depleting day by day leading to increased concentration of contaminant such as TDS, Alkalinity , Hardness , Ca, Mg ,Cl. Rural areas are facing drinking water scarcity due to increased use of available ground water sources for irrigation use and deteriorating water quality due to intensive irrigation, excessive use of fertilizer and other anthropogenic sources. Overall ground water quality scenario is not bright. Looking to situation the samples were collected for the study area from dug well, bore well, hand pump and percolation well during Pre monsoon and Post monsoon period. Collected samples were analyzed by physicchemical method recommended by NEERI. Obtained results were further used for assessing the ground water quality status by using NSFWQI method. Normal statistic of the parameters is computed and tabulated. Moreover, Correlation Coefficient is calculated amongst the all water quality parameters obtained during the analysis. These results are further used for regression analysis. The parameters which are strongly correlated with each other are selected for developing the Regression Equation. The equation thus formed provides the mathematical tool for assessing the Water Quality and to frame the Management Plan accordingly.


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The equation thus formed provides the mathematical tool for assessing the Water Quality and to frame the Management Plan accordingly.