Statistical analysis of hydrochemistry and isotopic characterization of groundwater from the parecis basin

Abstract

Knowledge of mechanism controlling the hydrochemistry of groundwater are crucial requirement to understand the hydrochemical evolution and evaluate the water quality of subsurficial water resources. Thus, to understand the process governing the hydrochemistry variability and flow dynamics of the Parecis and Ronuro Aquifers, the use of statistical analysis and isotopic characterization were combined. In the correlation matrix it was found that the highest correlation coefficient was observed for HCO3-, Ca2+, Mg2+, Sr2+, SO4 2-, and F-, which suggested that these parameters are derived from the same source, most likely from rock–water interactions. Additionally, we noticed moderate to high correlation among NO3-, Cl-, Na+, K+, and Ba2+, which collectively are indicative of domestic sewage contamination. Finally, a principal component analysis (PCA) identified that the most variance in hydrochemistry from the evaluated samples was controlled by HCO3-, Ca2+ and Mg2+, which is associated with rock–water interaction. Regarding the18O and 2 H isotope values, it could be observed that the aquifer recharges were of meteoric origin and that the Ronuro Aquifer samples were more enriched than the PAS samples. This work reinforces the capability of multivariate statistics to discern the main process that controls the variability of groundwater hydrochemistry.