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High Nitrate Content in the Surface Water of Balipara, North Brahmaputra River Basin, Sonitpur District, Assam, India:A Multivariate Approach


Affiliations
1 Department of Chemistry, Assam University, Silchar 788 001, India
2 Department of Pharmaceutical Technology, Defence Research Laboratory, Tezpur 784 001, India
 

The present study is an evaluation of ground and surface water quality at Balipara, North Brahmaputra river basin, Sonitpur district, Assam, India using multivariate statistical methods. The results show high concentration of Fe, Mn, Pb and Cr in groundwater. Arsenic was observed in both ground and surface water. In the surface water, nitrate content was also found to be high. Ward's method was used for hierarchical agglomerative cluster analysis. A close relationship between electrical conductivity (EC) and total dissolved solids (TDS) was established by the smallest proximity distance between these parameters. Group 1 comprised of TDS, EC, total alkalinity (TA), F, Ca, Pb, Cr and Cl based on proximity distances. Group 2 consisted of Fe, Mn, As and Group 3 of TH, Mg, pH, Zn, SO4 and NO3 in groundwater. In surface water, Group 1 comprised of TDS, EC, SO4, NO3, Cl, Zn, pH and Ca. Group 2 accounted for Mg and F and Group 3 for Fe, Mn, TA, Pb, As and Cr. The interrelationships between the contaminants depicted by cluster analysis, categorize the contamination levels. Factor analyses were applied for understanding the interrelationships between the variables and for identifying probable source components. Six factors justifying 83.64% of the total variance in groundwater and five factors describing 81.92% of the total variance in surface water were found responsible for variation in the data structure. The relative contribution of all the water- quality parameters was best explained by discriminant analysis.

Keywords

Contaminants, Groundwater and Surface Water, Multivariate Statistical Techniques, Water Quality Parameters.
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  • High Nitrate Content in the Surface Water of Balipara, North Brahmaputra River Basin, Sonitpur District, Assam, India:A Multivariate Approach

Abstract Views: 230  |  PDF Views: 77

Authors

Richa Chaturvedi
Department of Chemistry, Assam University, Silchar 788 001, India
Saumen Banerjee
Department of Chemistry, Assam University, Silchar 788 001, India
Bodhaditya Das
Department of Chemistry, Assam University, Silchar 788 001, India
Pronobesh Chattopadhyay
Department of Pharmaceutical Technology, Defence Research Laboratory, Tezpur 784 001, India
Chira R. Bhattacharjee
Department of Chemistry, Assam University, Silchar 788 001, India
Vijay Veer
Department of Chemistry, Assam University, Silchar 788 001, India

Abstract


The present study is an evaluation of ground and surface water quality at Balipara, North Brahmaputra river basin, Sonitpur district, Assam, India using multivariate statistical methods. The results show high concentration of Fe, Mn, Pb and Cr in groundwater. Arsenic was observed in both ground and surface water. In the surface water, nitrate content was also found to be high. Ward's method was used for hierarchical agglomerative cluster analysis. A close relationship between electrical conductivity (EC) and total dissolved solids (TDS) was established by the smallest proximity distance between these parameters. Group 1 comprised of TDS, EC, total alkalinity (TA), F, Ca, Pb, Cr and Cl based on proximity distances. Group 2 consisted of Fe, Mn, As and Group 3 of TH, Mg, pH, Zn, SO4 and NO3 in groundwater. In surface water, Group 1 comprised of TDS, EC, SO4, NO3, Cl, Zn, pH and Ca. Group 2 accounted for Mg and F and Group 3 for Fe, Mn, TA, Pb, As and Cr. The interrelationships between the contaminants depicted by cluster analysis, categorize the contamination levels. Factor analyses were applied for understanding the interrelationships between the variables and for identifying probable source components. Six factors justifying 83.64% of the total variance in groundwater and five factors describing 81.92% of the total variance in surface water were found responsible for variation in the data structure. The relative contribution of all the water- quality parameters was best explained by discriminant analysis.

Keywords


Contaminants, Groundwater and Surface Water, Multivariate Statistical Techniques, Water Quality Parameters.



DOI: https://doi.org/10.18520/cs%2Fv110%2Fi7%2F1350-1360