Coupling of multi-hydrochemical and statistical methods for identifying apparent background levels of major components and anthropogenic anomalous activities in shallow groundwater of the Liujiang Basin, China.

Natural background levels (NBLs) is a prerequisite for distinguishing anthropogenic groundwater pollution and judging the evolution of groundwater quality. However, due to regional differences of hydrogeochemitry and water-rock interaction, coupled with long-term anthropogenic activities, it is no longer accurate to assess NBLs with only statistical methods or without considering human impact. Herein, multi-hydrochemical and statistical methods were examined to identify apparent background levels and anthropogenic anomalous activities of shallow groundwater by selecting Liujiang Basin as a study area. The results showed that the differences in hydrochemical characteristics among each hydrogeological unit (HU) fully illustrated the necessity of rationally dividing HU for background value identification. The application of the concept of apparent background levels (ABLs), that is, incorporating normal human activities into the background levels, efficiently solved the problem of being unable to obtain pristine NBLs due to long-term human activities. The coupling of Hydrochemistry and Grubbs' test (Hydro-Grubbs) was confirmed as the optimal method in identifying and eliminating anthropogenic groundwater anomalies, performing sufficiently superiority when compared with purely statistical methods. It is mainly because the Hydro-Grubbs method not only considers the discreteness of the data itself, but also considers the internal connection and evolution process of the hydrochemical compositions. For the eliminated abnormal points, 91.0-93.6% of which have been effectively explained by pollution percentage index and the impact of coal mining, industrial activities, residents, agricultural activities, and septic tanks leakage, proving the rationality and reliability of Hydro-Grubbs method and ABLs evaluation result. This finding will assist in accurately identifying anthropogenic pollution on a regional scale and guiding future efforts to protect groundwater resources.