Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, India
Groundwater samples from Moradabad city were analyzed for chemical parameters. For present study 58 water samples were collected from different localities on the basis of various land use patterns. The higher values of most of the parameters were found in the area of old settlement, while lower valu...
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doaj-e9086f66ba2d47d891b7518a9334f3252020-11-24T23:50:20ZengHindawi LimitedE-Journal of Chemistry0973-49452090-98102008-01-015360761910.1155/2008/359182Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, IndiaJ. K. Pathak0Mohd Alam1Shikha Sharma2Hydrobiology Lab, P.G. Department of Zoology, University of Rohilkhand, Hindu College, Moradabad, 244001, IndiaHydrobiology Lab, P.G. Department of Zoology, University of Rohilkhand, Hindu College, Moradabad, 244001, IndiaHydrobiology Lab, P.G. Department of Zoology, University of Rohilkhand, Hindu College, Moradabad, 244001, IndiaGroundwater samples from Moradabad city were analyzed for chemical parameters. For present study 58 water samples were collected from different localities on the basis of various land use patterns. The higher values of most of the parameters were found in the area of old settlement, while lower values observed in new settlements. This shows clear impact of land use on groundwater. Water quality data collected from different localities are used in conjunction with multivariate statistical technique to identify key variables. The first four components were chosen for interpretation of the data, which accounts for 77.38% of the total variance in the data set. The maximum number of variables, i.e. Cl, Na, TH, TDS, EC and salinity were characterized by first component, while second component is characterized by DO and Mg. The third and fourth components were characterized by Ca, SiO2 HCO3 and K respectively. This shows that hydrochemical constituents of the groundwater are mainly controlled by TDS and EC. For cluster analysis single linkage method was used. The findings of the cluster analysis are presented in the form of dendrogram of the sampling stations (cases) as well as hydrochemical variables, which produced four major groupings, suggests that groundwater monitoring can be consolidated.http://dx.doi.org/10.1155/2008/359182 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
J. K. Pathak Mohd Alam Shikha Sharma |
spellingShingle |
J. K. Pathak Mohd Alam Shikha Sharma Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, India E-Journal of Chemistry |
author_facet |
J. K. Pathak Mohd Alam Shikha Sharma |
author_sort |
J. K. Pathak |
title |
Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, India |
title_short |
Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, India |
title_full |
Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, India |
title_fullStr |
Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, India |
title_full_unstemmed |
Interpretation of Groundwater Quality Using Multivariate Statistical Technique in Moradabad City, Western Uttar Pradesh State, India |
title_sort |
interpretation of groundwater quality using multivariate statistical technique in moradabad city, western uttar pradesh state, india |
publisher |
Hindawi Limited |
series |
E-Journal of Chemistry |
issn |
0973-4945 2090-9810 |
publishDate |
2008-01-01 |
description |
Groundwater samples from Moradabad city were analyzed for chemical parameters. For present study 58 water samples were collected from different localities on the basis of various land use patterns. The higher values of most of the parameters were found in the area of old settlement, while lower values observed in new settlements. This shows clear impact of land use on groundwater. Water quality data collected from different localities are used in conjunction with multivariate statistical technique to identify key variables. The first four components were chosen for interpretation of the data, which accounts for 77.38% of the total variance in the data set. The maximum number of variables, i.e. Cl, Na, TH, TDS, EC and salinity were characterized by first component, while second component is characterized by DO and Mg. The third and fourth components were characterized by Ca, SiO2 HCO3 and K respectively. This shows that hydrochemical constituents of the groundwater are mainly controlled by TDS and EC. For cluster analysis single linkage method was used. The findings of the cluster analysis are presented in the form of dendrogram of the sampling stations (cases) as well as hydrochemical variables, which produced four major groupings, suggests that groundwater monitoring can be consolidated. |
url |
http://dx.doi.org/10.1155/2008/359182 |
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