*3.1. Sample Collection and Analysis*

In this study, a total of 14 groundwater samples were collected from shallow aquifer I+II during the monsoon period (June–August, 2011), with sampling buried depths of groundwater levels ranging from 50 to 150 m. The groundwater samples were collected appropriately according to the Code of Practice for Groundwater Environmental Monitoring (HJ 164-2020). The collected samples were first stored in a refrigerated box and then sent to the laboratory for chemical analysis. Samples requiring additives, added before sampling is completed. Finally, the status of the samples is checked regularly. The spatial distribution map of groundwater sampling points area was generated using the MAPGIS 6.7 software (Figure 2). It can be seen from Figure 2 that the sampling points were evenly distributed, covering the aquifer area in the study area.

The analytical data include the results of analyses of more than 20 parameters, in which the groundwater depth, longitude, latitude, smell and taste, turbidity, and naked-eye visible matter were measured and recorded in-situ. Other hydrochemical parameters, namely pH, hardness, total dissolved solids (TDS), mineralization, silicon dioxide (SiO2), potassium (K<sup>+</sup> ), sodium (Na<sup>+</sup> ), calcium (Ca2+), magnesium (Mg2+), sulfate (SO<sup>4</sup> <sup>2</sup>−), chloride (Cl−), bicarbonate (HCO<sup>3</sup> <sup>−</sup>), iron (Fe2+/Fe3+), fluorine (F−), nitrite (NO<sup>2</sup> −), nitrate (NO<sup>3</sup> −), arsenic (As), and manganese (Mn). However, Fe3+ was not considered in this study due to its low concentration in groundwater, which was below the detection limit.

All the analytical methods used in the analyses were carried out according to the standard methods reported by Nsabimana et al. [13]. On the other hand, in order to check the reliability of the water quality analysis results, the ionic balance was used calculated according to the following formula:

$$\mathrm{E}(\%) = \frac{\sum \mathrm{N\_c} - \sum \mathrm{N\_a}}{\sum \mathrm{N\_c} + \sum \mathrm{N\_a}} \times 100 \tag{1}$$

where E is the relative error; N<sup>c</sup> is the concentration of the cation in the groundwater sample (meq/L); N<sup>a</sup> is the concentration of the anion (meq/L).

**Figure 2.** Spatial distribution of sampling points in the study area. **Figure 2.** Spatial distribution of sampling points in the study area.

All the analytical methods used in the analyses were carried out according to the standard methods reported by Nsabimana et al. [13]. On the other hand, in order to check According to the results obtained, all the analytical data of groundwater samples showed E values less than ±5%, which suggests appropriate analytical methods.

### the reliability of the water quality analysis results, the ionic balance was used calculated *3.2. Data Analysis Methods*

according to the following formula: E(%) = ∑ N<sup>c</sup> − ∑ N<sup>a</sup> ∑ N<sup>c</sup> + ∑ N<sup>a</sup> × 100 (1) where E is the relative error; N<sup>c</sup> is the concentration of the cation in the groundwater sample(meq/L); N<sup>a</sup> is the concentration of the anion (meq/L). According to the results obtained, all the analytical data of groundwater samples In addition to, descriptive statistics, the principal component analysis test was performed in this study using the SPSS software to determine the main influencing factors affecting the hydrochemical characteristics of groundwater in Yongqing County [14,15]. In addition, ionic ratios were used to analyze the alternate adsorption of cations and investigate the main sources of hydrochemical elements in groundwater. On the other hand, the PHREEQC software was used for hydrogeochemical inversion simulations.

### showed E values less than ±5%, which suggests appropriate analytical methods. **4. Results and Discussion**
