Hydrochemical variation during groundwater mixing: a case study with multivariate statistical approach

Abstract

Identification of groundwater mixing and calculation of the mixing ratios between aquifers are important work for hydrological studies and safety of coal mining. In this study, multivariate statistical methods including factor and cluster analysis have been presented for identification of groundwater mixing status in the Renlou coal mine, northern Anhui Province, China. The methods include three steps: identification of hydraulic connection between aquifers by using factor score plots in combination with Q-mode cluster analysis, selection of end members and mass balance calculation for revealing mixing ratios. The hydraulic connection between loose layer and limestone aquifers have been identified in the Renlou coal mine, and three representative end member water samples, as well as mixed samples have been identified. Moreover, the mixing ratios for mixed samples are also calculated. The results indicate that the methods can be used for identification of mixing and quantification of mixing ratios in groundwater systems.

Statistical analyses of groundwater chemistry in the Qingdong coalmine, northern Anhui province, China: implications for water–rock interaction and water source identification

“…Therefore, the water in the karst cave is also a threat to the safety of coal mining. In summary, the water from the fourth aquifer, the crack of the sandstone and the karst cave of the limestone threaten the safety of coal mining activities, which is similar to the Renlou coal mine in the similar hydrological unit (Sun 2013).…”