Determining the factors controlling the chemical composition of groundwater using geochemical methods and groundwater health assessment in Qixing Town, southwest China

Water is essential for sustaining human life and development, and groundwater forms an important component of water resources, with around 30% of the global human population dependent on groundwater for drinking water (Yang et al. 2016). However, increased socioeconomic development and growth of the human population has contributed to the increasing production of domestic solid waste (Yang et al. 2014). Most developing countries currently continue to dispose of this waste in landfills, and leachate from these landfills often infiltrates the groundwater, resulting in groundwater pollution and threatening the sustainability of groundwater development (Eslami et al. 2019; Liu et al. 2019a, 2019b; Gao et al. 2020; Qian et al. 2020).

Groundwater constitutes an important drinking water source in rural China, and human health shows a strong relationship to drinking water quality (Li et al. 2014). Groundwater and the aquifer media undergo a range of hydrogeochemical reactions during the runoff process, which contribute to the variability in groundwater chemical compositions and evolutionary patterns (Liu et al. 2019a, 2019b, 2021). Also, anthropogenic activities significantly affect groundwater chemistry, thereby influencing groundwater quality (Qasemi et al. 2022). The security of a region's water supply is highly dependent on groundwater quality. Therefore, assessment of the quality of groundwater and hazard posed to the health of local residents is extremely important.

Statistical analysis (Gan et al. 2018) and ion ratio (Peng et al. 2021) have been commonly applied for the characterization of the chemistry of groundwater and evalution of water quality. The Water Quality Index (WQI) provides a detailed quantitative characterization of the overall quality of the water environment and is commonly applied in surface or groundwater quality evaluation, both in China and internationally. The WQI is simple, easy to apply, and suitable for evaluation of water quality monitoring data against standard limits (Xiao et al. 2019; Nong et al. 2020). However, the WQI does not take into account the weight of each indicator, with only the objective weight method applied (Islam et al. 2020; Zhang et al. 2020). The Entropy-Weighted Water Quality Index (EWQI) is derived from the WQI and represents a currently available water quality evaluation model with the most unbiased water quality evaluation model reflecting the true weight of each parameter (Ukah et al. 2020). The EWQI has seen common use in assessing groundwater quality (Nguyen et al. 2021; Kumar & Augustine 2022). However, the EWQI ignores the limit standards for some factors, whereas the Hazard Index (HI) does reflect the hazard posed by trace elements to human health (Chen et al. 2020). The integration of the EWQI and HI can comprehensively indicate the acceptability of groundwater as drinking water.

Landfill remains a common method of disposing of solid domestic waste in China. However, infiltration of leachate from landfill into the groundwater system can lead to groundwater pollution. There is a long history of groundwater use for drinking water among residents of Qixing Town, Langzhong City. The study area is the red-bed areas consisting of sandstone and mudstone, and its groundwater quantity is limited by the low permeability of the shallow weathered fracture zone, and the total pumping capacity of a single well cannot meet the basic needs of a large population. In the meantime, most of the landfills in the red-bed areas are located in suburban and rural areas, while the people living around the landfills often have no other choice but to draw water from wells for drinking. For this reason, it is urgent to conduct relevant research on the identification and risk assessment of groundwater pollution around the landfill in red-bed areas. Although the groundwater in Qixing Town, Langzhong City, may exhibit varying degrees of contamination due to the presence of the landfill, there are still no studies on the hydrogeochemical characteristics of groundwater and the risks of heavy metals to human health. Zhang et al. (2021) studied the hydrogeochemical characteristics and non-carcinogenic hazard due to nitrate posed by groundwater to the health of residents in Nanchong City; Zhang et al. (2015) analyzed groundwater chemistry of Siyi Town, Langzhong, utilizing using Piper trilinear, Durov, and Scholler diagrams along with other graphical methods, factor analysis, and cluster analysis. So, the objectives of the current study were to (1) characterize groundwater chemistry; (2) identify the major sources of groundwater ions; (3) characterize the quality of groundwater; and (4) evaluate the non-carcinogenic and carcinogenic hazards posed by groundwater to the health of children and adults by applying the USEPA guidelines. This study not only can help further characterize groundwater chemistry in the region and the risks posed by groundwater heavy metal pollution to human health, but also can provide the necessary technical support and targeted suggestions for the later management and treatment of groundwater in the area, and provide an important basis for the prevention of groundwater pollution and the protection of water resources. In addition, it can also provide a reference for similar landfill groundwater pollution management in other places.

The study area is in northeastern Sichuan Province, southwest China (Figure 1(a)). The region is affected by a subtropical humid monsoon climate with four different seasons and a lot of rainfall. The region experiences average annual, minimum, and maximum temperatures of 17.8, 36.4, and 6.6 °C, respectively. The annual average precipitation is 1,006.7 mm, with 40%–50% falling in June to August, and that in December to February constituting less than 5% of the annual total. The topology of the study area is low hills, with hill slopes becoming gentler from west to east and north to south. The region has an altitude of 300–450 m, with the maximum and minimum of 410 and 330 m in the southwest and south, respectively. The overall terrain of the study area slopes toward a stream gully in the northwest, which is a seasonal flow gully, with farmland on both sides of the gully falling in a floodplain.

Twenty-five groundwater samples were collected from May to October of 2021 (Figure 1(a)). A geographic positioning system (GPS) was utilized to geo-locate sampling points. A portable analyzer (PHS-3C) was used to measure the pH of groundwater samples on site. The electrodes of the pH meter were calibrated prior to measurements. Samples of groundwater were stored using 0.5 L polyethylene bottles which had been sterilized beforehand by rinsing one to two times using pure water. Before taking each groundwater sample, the sample bottle was washed two to three times with the source water. The heavy metals in each sample were stabilized by the addition of 2 mL 1% HNO₃. Samples were transported to the laboratory at 4 °C for further analysis.

Water samples were filtered through 0.45 μm microporous membranes. Total dissolved solids (TDS) were measured by oven drying; measurement of major anions (SO₄²⁻, NO₃⁻, Cl⁻, and F⁻) was through an ion chromatograph; HCO₃⁻ and CO₃²⁻ were measured using the titrimetric method; a flame atomic absorption spectro-photometer was used to measure major cations (K⁺, Na⁺, Ca²⁺, and Mg²⁺); ICP-MS (inductively coupled plasma-mass spectrometry; IRIS Intrepid II XSP, China) was used to measure eight toxic metals (Cd, As, Cr, Fe, Mn, Zn, Cu, and Pb). Measures to assure quality and control (QA/QC) were implemented to ensure accurate experimental results using a two-step process: (1) random selection of 20% of samples for parallel control experiments to ensure an allowable range of the relative deviation of 5% and (2) the comparison of each sample with a standard reference solution and a blank sample. Analytical grade chemical reagents were used.

The EWQI represents a method of evaluation of water quality that is less biased than the traditional water quality index (Adimalla 2019; Hasan & Rai 2020). The index includes information entropy within the quantitative evaluation of water quality to eliminate human bias. The EWQI is calculated over four steps:

• ① The X eigenvalue matrix is calculated using Equation (1); n and m are the indices and sample number, respectively:

  

  (1)
• ② Equations (2) and (3) are used to derive the standard matrix Y. Significant dimensional differences exist in the assessment of water chemistry indices. The effects of these differences need to be removed by pre-processing and standardization of data (Amiri et al. 2014). In the equations, (x_ij)_max and (x_ij)_min represent the maximum and minimum values, respectively, and x_ij denotes the i-th row and the j-th column of the matrix X:

  

  (2)

  

  (3)
• ③ Equations (4) to (6) are used to calculate the entropy weight w_j and information entropy e_j, and P_ij represents the index j for sample i:

  

  (4)

  

  (5)

  

  (6)
• ④ Equations (7) and (8) are used to calculate the EWQI; q_j represents the quantitative grading scale for hydrochemical indices and is calculated using each water quality variable's concentration in each water sample (C_j) and the World Health Organisation (WHO) drinking standards (S_j). Under this formula, the complete absence of variable j in the water sample leads to q_j = 0, whereas q_j = 100 when its concentration is equal to the permissible limit. The EWQI was calculated by combining the entropy weight w_j and quantitative grading scale q_j. Table 1 further describes the ranking system used within the EWQI rank. Groundwater with an EWQI rank of 1 or 2 is suitable for drinking (Zhang et al. 2015).

  

  (7)
  

  (8)

Table 4 provides the mean, maximum, minimum, coefficient of variation (CV), and standard deviation of the main groundwater sample physicochemical parameters. Water pH reflects its acid–base characteristics and is a basic index of water suitability for different applications (Şener et al. 2017). The pH of water samples extended from 6.46 to 7.6, suggesting the neutral status of groundwater. The rank of groundwater cations based on average content was Na⁺ > Ca²⁺ > K⁺ > Mg²⁺, and for anions it was HCO₃⁻ > Cl⁻ > SO₄²⁻ > CO₃²⁻ > NO₃⁻ > F⁻. Besides pH, the CV of all indicators ranged from 34 to 158, indicating moderate or high spatial variability. The indicators showing strong spatial variability (CV > 100) included K⁺, NH₄⁺, NO₂⁻, and NO₃⁻, the remainder showed moderate variability (30 < CV < 100). These results indicated high spatial variability in groundwater chemistry and the strong influence of anthropogenic and natural activities.

The Gibbs diagram indicated that weathering of rocks and water–rock interactions are the main factors influencing the chemistry of groundwater in the study area, with a delayed alternating effect of groundwater flow. Isolated water–rock interactions included dissolution/sedimentation, cation adsorption and exchange, and evaporation and concentration. The Gibbs plot indicated no obvious effect of evaporative concentration in the study area. Hence, the current study further investigated dissolution/sedimentation and cation adsorption and exchange. There can be significant differences in the contents and ratios of water chemistry indicators among different aquifers. Therefore, the ion area ratio diagram can be applied to identify the main hydrogeochemical processes influencing groundwater (Yang et al. 2016; Liu et al. 2018).

The current study also investigated the correlation between groundwater HCO₃⁻ and Ca²⁺ concentrations. The HCO₃⁻:Ca²⁺ ratio approximating 1 indicated calcite dissolution, whereas 2 indicated dissolution of dolomite (Li et al. 2016). As demonstrated in Figure 5(c), 40% of the water sample points plotted above y = 2x, suggesting the presence of dolomite dissolution, whereas 20% fell between y = x and y = 2x, implying the contribution of carbonate to groundwater hydrochemistry evolution. Water sample points plotting below the y = x line (40%) exhibited high Ca²⁺ concentrations, implying that the weathering of dolomite and calcite were not dominant processes and the presence of other sources of Ca²⁺ or cation exchange.

(HCO₃⁻ + SO₄²⁻) and (Ca²⁺ + Mg²⁺) bivariate plots can be applied to identify the dominant Ca²⁺ and Mg²⁺ sources (Marghade et al. 2015). Most groundwater sample points plotted above the y = x line and had a ratio exceeding 1, indicating reduced contents of Ca²⁺ and Mg²⁺. Therefore, Ca²⁺ and Mg²⁺ predominantly originated from the dissolution of silicate and sulfate or the presence of cation exchange (Figure 5(e)).

Plotting (Na⁺ + K⁺ − Cl⁻) against (Ca²⁺ + Mg²⁺ − SO₄²⁻ − HCO₃⁻) can be utilized to isolate the dominant cation exchange process. Variations in these two indices indicate the acquisition or migration of Ca²⁺, Na⁺, and Mg²⁺ from sources other than salt rock, hydrochloride rock, and gypsum dissolution. The two indices will show a linear relationship if cation exchange dominates, with a slope of −1 (Wu & Qian 2017). Groundwater points mainly plotted near the y = −x line, suggesting that cation exchange is an important process influencing groundwater chemistry (Figure 5(f)).

In addition, the study of the relationship between HCO₃⁻/Na⁺ and Mg²⁺/Na⁺, Ca²⁺/Na⁺ can qualitatively reflect the influence of the dissolution of different rock types on groundwater chemistry (Gaillardet et al. 1999). As shown in Figure 5(g) and 5(h), there were high contents of silicate in groundwater samples, indicating silicate weathering to be an important hydrochemical process regulating groundwater chemistry, whereas evaporite dissolution is responsible for a certain proportion of groundwater chemistry. This result is consistent with that shown in Figure 5(d). Around 76% of water sample points plotted below the y = 0.5x line, indicating the dominant role of silicate dissolution.

Anthropogenic activities represent the main factor affecting groundwater chemistry in many places. The study area is not industrially developed, with agricultural and domestic wastewater acting as the main contributors to groundwater pollution. NO₃⁻ is a special pollutant in groundwater in agricultural areas. Given the conservative nature of Cl⁻, the relationships among Na⁺, Cl⁻, and NO₃⁻ can be utilized to isolate the influences of anthropogenic activities on groundwater chemistry. Most groundwater samples plotted within the triangular area, indicating the dominant source of groundwater NO₃⁻ to be urban sewage (Figure 5(i)).

As shown in Figure 5(j), most samples provided CAI-I and CAI-II values < 0. Therefore, reverse cation exchange was identified as the process that resulted in decreases in Ca²⁺ and Mg²⁺, consistent with the results in Figure 5(e).

The current study assessed the risk of groundwater to the wellbeing of children and adults through skin contact and drinking water. Table 5 summarizes the results of the evaluation. The rank of the eight different groundwater toxic metals according to their risk to human health was As > Cr > Cd > Cu > Pb > Zn > Mn > Fe. The groundwater concentrations of As, Cd, and Cr were higher than the maximum permissible risk value (1 × 10⁻⁴) suggested by USEPA (2011). These metals are the main contributors to the carcinogenic hazard of groundwater to human health through ingestion and dermal contact. The results indicated that Cr and As in the groundwater can greatly affect human health through drinking water and skin contact, similar to the conclusions of previous studies (Qiu et al. 2018; Podgorski & Berg 2020). Even though the levels of Fe and Mn were higher than the national standards, their HI values were low at 0.03. Despite their low non-carcinogenic risks, the small upper thresholds of Fe and Mn were established in the standards due to their effects on drinking water taste at higher concentrations (Munger et al. 2016).

The present study used various computational techniques, including the EWQI and USEPA mathematical models, to investigate and analyze groundwater chemical characteristics and their drivers in Qixing Town, Langzhong City, and to assess the associated risks to human health. The main groundwater chemistry types were HCO₃–Na and HCO₃–Ca. The order of groundwater cations according to concentration was Na⁺ > Ca²⁺ > K⁺ > Mg²⁺, whereas that of anions was HCO₃⁻ > Cl⁻ > SO₄²⁻ > CO₃²⁻ > NO₃⁻ > F⁻. The main processes affecting groundwater chemistry were determined to be ion exchange and dissolution of calcite and dolomite. The result of the analysis of the vertical distribution characteristics of heavy metals in groundwater shows that the depth of local residential wells is more appropriate at 5–25 m. The results of the EWQI showed that most groundwater samples fell within the WHO drinking water standards and were suitable for drinking. The human health risk evaluation showed that As, Cd, and Cr presented carcinogenic risks to human health as high intake of these toxic metals can result in many diseases including cancer. Therefore, there should be an increased focus on managing the presence of these elements in the groundwater environment through appropriate contaminant control measures. The results of this study can improve comprehension of landfill contamination of groundwater in the study area and the associated risks to the health of locals. This study can guide future management of groundwater pollution in the study area.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.