Using correlation and multivariate statistical analysis to identify hydrogeochemical processes affecting the major ion chemistry of waters: a case study in Laoheba phosphorite mine in Sichuan, China

摘要

Prior to mining, the water in and around the mine is rarely influenced by human activities, and hydrogeochemical processes are the major factors influencing and controlling water chemistry. To identify these natural hydrogeochemical processes in Laoheba phosphorite mine (Sichuan Province, China), correlation and multivariate statistical techniques were used. Results show that water quality in the area is generally good before the Laoheba phosphorite mine goes into construction and production. The cluster analysis classified water samples into 4 clusters (C1-C4). Samples from C1 and C2 are of HCO_3-Ca·Mg and HCO_3-Ca type, while those from C3 and C4 are of HCO_3-Ca·Mg type. Most parameters except Cl- and pH show an increasing trend in the order of C1 to C4. Three principal components were extracted, and PC1 represents the ion exchange and the weathering of calcite, dolomite, and silicate minerals. PC2 and PC3 indicate the process of water recharge from upstream waters and the process of evaporation, respectively. The hydrochemistry of waters in the area is a result of multiple factors, and natural mineral weathering and ion exchange are the most important ones.