Groundwater is important for human survival and development, particularly in arid and semi-arid regions, such as western Jilin Province. This study aimed to evaluate the hydrochemical characteristics and nitrate human health risks of groundwater in the semi-arid plains of western Jilin Province, northwest China. The study collected of 88 and 151 phreatic and confined water samples, respectively, which were analyzed for 13 water quality indicators using statistical and graphical methods. The Combined Weighted Water Quality Index (CWQI) based on the entropy weight, Criteria Importance Though Inter-criteria Correlation (CRITIC), the coefficient of difference method, and the water quality index (WQI) was used to evaluate the water quality of the study area. The human health risk assessment (HHRA) model was used to assess the risks of nitrate to the health of humans among different age groups. The results indicate that: (1) Groundwater in the study area is weakly alkaline and the main hydrochemical types of the phreatic and confined water were HCO3−·Ca-Mg and HCO3−-Na. (2) Rock weathering was the dominant processes responsible for groundwater ions, whereas groundwater hydrochemistry was also affected by silicate weathering and cation exchange. (3) Although the quality of groundwater was generally good, 9.1% of phreatic water samples failed drinking water standards. (4) The areas in which groundwater nitrate posed a higher risk to human health are mainly in the saline-alkali lands of Qian'an, Tongyu, and Zhenlai, with 15.9% of water samples exceeded the nitrate standard for children. This study can improve the understanding of groundwater hydrochemical characteristics and human health risks in the study area and can contribute to the study of groundwater in semi-arid regions.

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Accurate assessment of groundwater vulnerability objectively reflects an area's potential for groundwater pollution and provides a reference basis for pollution control and prevention. The main objective of this study was to modify the original DRASTIC model to improve the consistency of groundwater vulnerability assessment results with regard to the actual conditions of the study area. To optimize the assessment objectivity, two additional factors that are influenced by human activities (land use and degree of groundwater extraction) were added to form the DRASTICLE model. Then, based on the correlation between all factors and measured nitrate concentrations, the improved