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Assessment of Physico-Chemical Quality of Groundwater by Multivariate Analysis in some Populated Villages nearby Sagar City, MP, India | OMICS International | Abstract
ISSN: 2161-0525

Journal of Environmental & Analytical Toxicology
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Research Article

Assessment of Physico-Chemical Quality of Groundwater by Multivariate Analysis in some Populated Villages nearby Sagar City, MP, India

Hemant Pathak*
Department of Chemistry, Indra Gandhi Govt. Engineering College, Sagar, Madhya Pradesh, India
Corresponding Author : Hemant Pathak
Department of Chemistry
Indra Gandhi Govt. Engineering College, Sagar
Madhya Pradesh, India
E-mail: [email protected]
Received November 22, 2011; Accepted May 28, 2012; Published May 30, 2012
Citation: Pathak H (2012) Assessment of Physico-Chemical Quality of Groundwater by Multivariate Analysis in some Populated Villages nearby Sagar City, MP, India. J Environ Anal Toxicol 2:144. doi: 10.4172/2161-0525.1000144
Copyright: © 2012 Pathak H. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Ground water is one of the major resources of the drinking water in rural area nearby Sagar city, Madhya Pradesh. In the present study groundwater quality of the selected 02 villages near by Sagar city were taken for under investigations, by collecting 75 groundwater samples from entire villages and assessed for their suitability for human consumption. Physico-chemical parameters were carried out during different months of the pre monsoon, monsoon and post monsoon seasons in Oct. 2007– July 2011. WHO water directive value is 44 mg/l for nitrate and11 mg/l nitrate in drinking water. pH values of all samples were between 5.5-8.5 limits. Conductivity of all samples was below WHO water standards. The statistical analysis of the experimentally estimated water quality parameters on water samples yielded the range of the variation, mean, standard deviation, co-efficient of variation, correlation analysis and principal component analysis.

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