Hydro-geochemical investigations of arsenic rich groundwater using multivariate statistical analysis
Keywords:
Correlation, weathering, dissolution, principal component analysis (PCA), hierarchical cluster analysis (HCA)Abstract
Multivariate statistical analysis has been applied to assess the chemical characteristics of high
arsenic groundwater from the central-southern part of Bangladesh. A total of 43 shallow groundwater samples were collected and analyzed. The groundwater is almost neutral. The results of
cations and anions trends are Na>Ca>Mg>K and HCO3>Cl>SO4>NO3
, respectively. Alkalinity
has a significant positive correlation with Mg, Ca and K suggesting silicate weathering as the
major process of controlling groundwater geochemistry. The significant positive correlation
between Na and Cl indicates the seawater intrusion into groundwater. The R-mode cluster allows variables into four groups. Alkalinity, Mg, K in the first and Ca in the second, Na and Cl in
the third cluster indicate silicate weathering and carbonate dissolution and seawater intrusion,
respectively. R-mode factor analysis allows variables into four components having eigen values
more than 1 which represent 72.5% of total variances. Component 1 positively loaded with K,
Mg, P, and alkalinity suggest silicate weathering. Component 2 positively loaded with Na and Cl
suggests seawater influences groundwater. Component 3 positively loaded with Ca suggest the
carbonate dissolution. The Q-mode cluster analysis represents the highest Fe concentrations
