Evaluation of hydrochemical data using multivariate statistical methods to elucidate heavy metal contamination in shallow aquifers of the Manipur valley in Indo-Myanmar Range

摘要

Descriptive statistics, factor analysis, correlation matrices, and cluster analysis are used to gain insights on hydrochemical processes and contamination in the shallow aquifers of Manipur valley. Groundwater has remained as a prime source of water supply for a population of nearly 3 million people living in this valley. Sixteen variables (pH, ORP, TDS, Ti, V, Cr, Cu, Ge, As, Rb, Sr, Nb, Mo, Hf, Ta, and W) are monitored from 28 shallow wells. Mean pH and TDS values (6.8 and 800 mg/l, respectively) suggest fresh quality water in terms of its acidity, alkalinity, or salinity. Oxidation reduction potential values (mean -6.75 mV) indicate dissolution of metals in anoxic condition. The order of abundance of metals is Sr > As > Rb > Ti > Cu > V > Cr > Mo > Ge > W > Hf > Ta > Nb. Sr, As, Cr, Cu, and Mo are elevated than the WHO limit. Elevation of Sr is attributed to weathering of gypsum, evaporite, and rock salt which reflects in factor 5 of the factor analysis. Factors 2 represents Cr, As, and Mo elevations and signifies geogenic weathering from ultramafic rocks of Manipur Ophiolite Melange Zone. Factor 3 represents Rb, V, and Cu elevations owing to natural weathering of clay and Fe-oxyhydroxides along with dissociation of solid organic carbons. Factor 4 is related to a reduced environment under low pH condition. Factor 1 reflects dissolution of Nb, Hf, Ta, and Ti under anoxic environment as insoluble oxides. Analysis on Pearson correlation and hierarchical clustering strongly support observation made by factor analysis. Thus, the present study shows the accountability of multivariate statistical techniques in interpreting and delineating the sources of contaminations in shallow groundwater.