Abstract: Groundwater, an essential component supporting the ecological environment, requires analysis of its hydro-chemical
characteristics, pollution status, and potential human health risks to ensure its effective protection and sustainable utilization. This study integrates hydro-chemical analysis, the absolute principal component score-multiple linear regression (APCS-MLR) model, the entropy weighted water quality index (EWQI), and the human health risk assessment (HHRA) model to conduct source analysis of groundwater chemical components and health risk assessment in the plain area of Baoding City, with an aim to provide a scientific basis for groundwater environmental protection and high-quality ecological development in the study area. The results show that the groundwater in the study area is generally weakly alkaline with coefficients of variation for Mn, NO₃ -, and Se ranging from 1.08 to 1.89, suggesting uneven spatial distribution and high local enrichment. The groundwater is dominated by the HCO₃- Ca·Mg and HCO₃-Na·Ca·Mg types, accounting for 63.33% and 18.89% of the total samples, respectively. The APCS-MLR model identifies the primary sources influencing groundwater hydro-chemical composition, including water-rock interaction and agricultural activities (45.61%), cation exchange (13.77%), reductive dissolution of Mn (9.55%), K+-specific adsorption and fixation (9.40%), and unidentified sources (21.68%). Meanwhile, the EWQI values range from 15.45 to 109.51, with water quality being categorized as excellent, good, and medium in 77.78%, 20.00%, and 2.22% of the samples, respectively. TDS, Se, Mn, and pH are identified as the key parameters controlling the EWQI. According to the HHRA model, the exceedance rate of noncarcinogenic risk in children (26.67%) is significantly higher than that in adults (4.44%). Spatially, high-risk areas for children are mainly distributed in the northern, central, and southwestern parts of the study area, while those for adults are primarily located in the main urban area of Baoding and the southeastern part of Dingxing County. 

Key words: plain area of Baoding City, hydro-chemical characteristics, absolute principal component-multiple linear regression
model, entropy weight water quality index, health risk assessment