Coupling of Multi-Hydrochemical and Statistical Methods for Identifying Apparent Background Levels of Major Components in Shallow Groundwater in Shanghai, China
Year: 2026
Type: article
Abstract: The determination of groundwater background levels is a prerequisite for assessing and analyzing groundwater characteristics. Shanghai is among the most economically developed regions in China and is located in the estuary of the Yangtze River, where frequent hydrogeochemical processes occur. Moreover, the frequency of anthropogenic activities in Shanghai is very high. Consequently, assessing groundwater background levels in Shanghai is inherently limited if only statistical methods are adopted or anthropogenic impacts are ignored. In this study, hydrochemical and statistical methods were coupled to identify groundwater anomalies and background levels. The results revealed distinct differences in hydrochemical characteristics between the two selected independent units (Chongming and Qingpu units), highlighting the necessity of reasonably delineating hydrogeological units for obtaining background values. Furthermore, for these two independent units, different optimal methods for identifying and eliminating anthropogenic groundwater anomalies were determined. The use of coupled methods was demonstrated to be substantially superior to the use of purely statistical approaches. Hydro-HCA was identified as the optimal identification method for the Chongming unit, whereas Hydro-Grubbs was determined as the most suitable method for the Qingpu unit. This could be attributed mainly to the coupled methods accounting for not only the dispersion of the data itself but also the intrinsic relationships and evolutionary processes of hydrochemical components. These findings could provide reliable information for subsequent groundwater background surveys and studies on groundwater pollution characteristics in Shanghai and to guide future endeavors aimed at protecting groundwater resources.
Source: Hydrology
Authors: Qingqing Li, Min Ji, Shiyang Zhang, Jie Yang, Hainan Lu
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,172
Award: G6716780928
OpenAlex ID: W7128673930
