title: Groundwater quality in Imphal West district, Manipur, India, with multivariate statistical analysis of data.
abstract: The aim of this paper was to analyze the groundwater quality of Imphal West district, Manipur, India, and assess its suitability for drinking, domestic, and agricultural use. Eighteen physico-chemical variables were analyzed in groundwater from 30 different hand-operated tube wells in urban, suburban, and rural areas in two seasons. The data were subjected to uni-, bi-, and multivariate statistical analysis, the latter comprising cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA). Arsenic concentrations exceed the Indian standard in 23.3% and the WHO limit in 73.3% of the groundwater sources with only 26.7% in the acceptable range. Several variables like iron, chloride, sodium, sulfate, total dissolved solids, and turbidity are also beyond their desirable limits for drinking water in a number of sites. Sodium concentrations and sodium absorption ratio (SAR) are both high to render the water from the majority of the sources unsuitable for agricultural use. Multivariate statistical techniques, especially varimax rotation of PCA data helped to bring to focus the hidden yet important variables and understand their roles in influencing groundwater quality. Widespread arsenic contamination and high sodium concentration of groundwater pose formidable constraints towards its exploitation for drinking and other domestic and agricultural use in the study area, although urban anthropogenic impacts are not yet pronounced.
authors.affiliation: Department of Ecology and Environmental Science, Assam University, Silchar 788011, India.
authors.forename: Elangbam J K
authors.initials: EJ
authors.lastname: Singh
authors.forename: Abhik
authors.initials: A
authors.lastname: Gupta
authors.forename: N R
authors.initials: NR
authors.lastname: Singh
mesh_terms: D001151:Arsenic / Q000032:analysis*; D016000:Cluster Analysis; D005163:Factor Analysis, Statistical; D060587:Groundwater / Q000737:chemistry*; D007194:India; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D012621:Seasons; D013057:Spectrum Analysis; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014877:Water Pollution, Chemical / Q000032:analysis / Q000706:statistics & numerical data*; D060753:Water Quality
chemical_list: D014874:Water Pollutants, Chemical; D001151:Arsenic