Groundwater is an important source of drinking water, particularly in arid regions. In this study, a total of 66 groundwater samples were collected from the phreatic aquifer in the Shizuishan area, a traditional irrigation region of Ningxia. The results showed that the TDS values were above the drinking water standards for nearly 50% of the groundwater samples. The ions followed the order of Na⁺ > Ca²⁺ > Mg²⁺ > K⁺ and SO₄²⁻ > Cl⁻ > HCO₃⁻ in the groundwater. There were four dominant factors in controlling groundwater chemistry based on principal component analysis: the salinity factor, alkalinity factor, carbonate factor, and pollution factor. The high concentration of NH₄-N in groundwater was attributed to agricultural activities, but the high NO₃-N levels were mainly due to sewage or wastewater. F and As were derived from geogenic sources. Based on the result of the WQI assessment, about 40% of the samples in the central part of the study region showed unacceptable water quality for drinking, which was mainly associated with high NH₄-N, TDS, and As concentrations. The total non-carcinogenic risks of drinking the groundwater were 0.05–10.62 for adults and 0.09–20.65 for children, respectively. The order of pollutants in the groundwater in terms of their hazard to residents was: As > F⁻ > NO₃-N > NH₄-N. The carcinogenic risk values of As through oral ingestion for children and adults were 0–7.37 × 10⁻⁴ and 0–1.89 × 10⁻⁴, respectively. Chronic exposure by oral ingestion presented as the main source of susceptibility to exposure to groundwater contaminants for children.

Fluoride and nitrogen contamination is a global concern and has been a serious problem in agricultural areas. This study aims to identify the source of fluoride and nitrogen in the groundwater and assess groundwater quality and human health risks in the Guanzhong Plain, northwest China. The results showed that the concentrations were 0.15–4.74 mg/L for F−, 0.02–89.89 mg/L for NO3−-N, and BDL-2.40 mg/L for NH4+-N in groundwater. Distinct area-dependent distributions of fluoride and nitrogen were observed in the study region. Higher F− and NO3−-N concentrations in groundwater were detected in the northern part, and higher NH4+-N levels were observed in the southern part. Water–rock interaction and agricultural activities were the controlling factors for fluoride and nitrogen distribution in groundwater. About 80% of samples are considered to have good water quality with WQI < 100. Exposure to fluoride and nitrogen through drinking should require more attention. The total non-carcinogenic risks through oral ingestion of groundwater were 0.22–3.19 for adults and 0.51–7.44 for children, respectively. The order of pollutants in the groundwater in terms of their hazard to residents was F− > NH4+-N > NO3−-N > NO2−-N. The findings of this study could provide more insights into groundwater management.

Accurately identifying the impact of different factors on water conservation is influenced by the spatial grid scale. However, existing studies on water conservation often overlook the Modifiable Areal Unit Problem (MAUP). MAUP is one of the key factors contributing to the uncertainty in spatial analysis results. The Qinling Mountains are a critical water conservation area, with the Yiluo River Basin (YLRB) as a key sub-basin. This study uses the Optimized Parameter GeoDetector (OPGD) model to analyze water conservation changes and influencing factors in the YLRB from 1990 to 2020. By optimizing spatial scale (2 km grid) and driving factor discretization, the OPGD model addresses spatial heterogeneity and the MAUP, enhancing analysis accuracy. Results show a fluctuating upward trend in water conservation depth, averaging 0.94 mm yearly, with a spatial decline from southwest to northeast. High–high and low–low clusters dominate the region, with some areas consistently showing high or low values. Key conservation zones expanded by 2748 km², reflecting significant enhancement. Natural factors, particularly precipitation, predominantly influence water conservation, outweighing human activities. The interaction between precipitation and temperature notably affects dynamic changes, while human impacts, such as land use, play a secondary role. The findings suggest water management should prioritize climatic factors and integrate land-use policies to enhance conservation. The OPGD model’s application improves factor identification and supports targeted ecological and water management strategies.