Evaluation of groundwater quality and health risk assessment in Dawen River Basin, North China

Groundwater is the principal water source of drinking and irrigation in the Dawen River Basin of Shandong Province. Thus, its investigations and evaluations are of significant importances. Based on collected groundwater samples, this study employed a combination of the entropy-weighted water quality index(EWQI), Nitrate Pollution Index(NPI) and the human health risk assessment(HHRA) model to evaluate groundwater quality and associated health risks. The combination of EWQI and NPI provides a more refined classification of groundwater quality in the Dawen River Basin. Geostatistical and GIS spatial analysis methods are employed to analyze the spatial characteristics of groundwater quality and its relationship with geomorphology. Results indicate that the region generally enjoys good water quality, with Entropy Water Quality Index (EWQI) values ranging from 20.32 to 302.37, and an average of 70.88. Downstream quality is poorer than upstream, and flat terrains typically exhibit poorer water quality. The major indicators affecting groundwater quality include Na+, Cl-, SO42-, and NO3-. The NPI results show that due to differences in anthropogenic sources, 38.1%, 27.38%, 26.19%, 4.76%, and 3.57% of the groundwater samples are classified into non-polluted, slightly polluted, moderately polluted, significantly polluted, and extremely significantly polluted types, respectively. The HHRA model reveals high potential non-carcinogenic risks for NO3- and low risks for F- in the study area. The health risks associated with high levels of NO3- in the areas surrounding Dongping Lake and Ningyang County are greater than in those other regions and therefore should be a significant concern for public health. Furthermore, this study attempts to combine the EWQI and NPI to categorize groundwater protection and governance statuses into four types: protective, utilizable, preventive, and remedial. This approach addresses the shortcomings in comprehensively identifying water quality types by single evaluation methods and offers valuable insights for distinguishing water quality types under nitrogen pollution conditions.