The Hydrogeochemical Processes of Groundwater in the Bieletan Area, the Western Potash Production Region in China

Abstract

The hydrogeochemical research of groundwater in the Bieletan area, China’s largest potash producing zone, used a variety of methods, including multivariate analysis, saturation index, and hydrogeochemical modeling. Water samples were collected and analyzed for physicochemical parameters, along with soluble ions from soil cores. The results showed that total dissolved solids (TDS) of groundwater exceeded 300 g/L, with the main hydrochemical characteristics being Cl-Mg type and Cl-Na type. Groundwater is recharged by lake water and canal water, with evaporation being the main factor affecting water chemistry. Hydrogeochemical modeling analyzed the processes occurring from these two different recharge sources: mineral precipitation mainly occurred with lake water recharge, while mineral dissolution mainly occurred with canal water recharge. Regarding potash dissolution, canal water and lake water recharge resulted in 8.860 mmol/L of polyhalite dissolution and 0.278 mmol/L of carnallite dissolution, respectively. This study highlights the complex hydrogeochemical processes controlling groundwater in the potash-rich Bieletan area, providing insights for water resource management and potash mining.

1. Introduction

Potash is considered a strategic resource because potassium is an essential nutrient for plants, as well as for animals and humans [1,2,3]. Potash resources are abundant worldwide, but both resources and production are primarily concentrated in a few countries such as Canada [4], Russia [5], and Belarus [6]. Due to limited land availability, China’s agricultural production heavily relies on fertilizers, especially potash, to increase crop yields [7,8]. Most potash mines around the world use traditional underground mining methods to extract solid potash [9,10]. Solution mining is another method that involves extracting potash-bearing solutions from groundwater. The extracted saturated potash solution is then transferred to evaporation ponds, where the salt and potash are concentrated through evaporation. This method of potash extraction is used in countries such as Chile [11,12], the United States [13], and China [14].

Qarhan Salt Lake is the largest salt lake in China. The Bieletan area, situated in the western part of Qarhan Salt Lake, is the largest potash production region in Qarhan Salt Lake and China. The potash-bearing layers in the Bieletan area are thin and lenticular, with multiple sedimentary strata that are generally thin and discontinuous. Therefore, solution mining is used to extract potash from these layers. Understanding the hydrogeochemical processes occurring during groundwater flow is crucial for the development and utilization of potash [15]. Xiao et al. used isotopic and numerical simulation methods to study the origin of groundwater in the Qarhan Salt Lake area, finding that the contribution of modern groundwater to the salt lake area is minimal [16]. Li et al. used PHREEQC to study the factors affecting the dissolution of solid potash minerals in the Qarhan Salt Lake area [17]. However, previous studies have primarily concentrated on the groundwater origin and potash development in the study area, paying less attention to the hydrogeochemical processes of groundwater during potash extraction. Understanding these processes is crucial for comprehending the hydrogeochemical mechanisms of groundwater.

A suite of hydrogeochemical techniques, including multivariate statistics, saturation indices, and hydrogeochemical modeling, is extensively employed to investigate groundwater sources, influencing factors, and hydrogeochemical processes [18,19,20,21,22]. De Caritat et al. used multivariate statistical analysis and saturation indices to study the factors influencing groundwater chemistry in the arid regions of Saudi Arabia [23]. El Alfy et al. investigated the groundwater sources in the Lake Woods region of Australia using saturation indices and hydrogeochemical modeling, concluding that the weathering of potassium silicates in the main aquifer is the source of potassium enrichment [24]. Parisi et al. investigated the spatiotemporal distribution of groundwater chemistry in the arid and semi-arid regions of southern Italy using multivariate statistical analysis and hydrogeochemical methods [25]. These studies demonstrate that the combination of these methods can effectively analyze hydrogeochemical processes in groundwater.

This study combines multivariate statistics, saturation indices, and hydrogeochemical modeling methods to analyze the hydrogeochemical processes of groundwater in the Bieletan area by examining soluble salts in soil and groundwater chemical indicators. The objectives of this study are to (1) examine the hydrogeochemical characteristics of groundwater in the Bieletan area; (2) analyze the key influencing factors of groundwater; and (3) investigate the primary hydrogeochemical processes occurring during groundwater recharge.

2. Study Area

2.1. Location and Climate

The Qaidam Basin is a large, closed basin located in the northwest of China. Surrounded by mountains exceeding 4000 m in height, the basin’s core plain has an average elevation of around 2800 m. This central plain is covered by dry salt flats and numerous shallow saline lakes (Figure 1). It contains roughly 27 salt lakes [26]. Eight rivers converge in the Qarhan Salt Lake area, which includes four major lakes from west to east: Senie Lake, Dabuxun Lake, South Huobuxun Lake, and North Huobuxun Lake [27]. These lakes are all terminal lakes. The Bieletan area, where Senie Lake is located, serves as the primary production area for potassium and lithium salts in the Qarhan Salt Lake area. The Bieletan area, covering approximately 950 km², extends between east longitudes 94°00′00″–94°55′00″ and north latitudes 36°45′00″–37°18′00″. Situated at elevations ranging from 2678 to 2681 m, it features relatively flat terrain.

The mountain ranges in the southwest of the Qaidam Basin block warm and wet air currents from the Indian Ocean, creating a climate dominated by cold air masses from Siberia, characterized as a dry continental climate. The Bieletan area has a dry environment with low relative humidity, low moisture content, strong atmospheric transparency, long daylight hours, intense solar radiation, relatively high temperatures, and a short frost-free season. The Bieletan area has an average annual temperature of 5.3 °C, with 24.1 mm of precipitation and 3500 mm of evaporation. The average relative humidity is 26%, and the average wind speed is 4.3 m/s, primarily from the northwest and southwest directions.

2.2. Geological and Hydrogeological Settings

The Qaidam Basin, situated within a complex network of compressive structures in the northeastern Qinghai-Tibet Plateau, represents the largest topographic depression on the plateau [28]. This geological environment has fostered the formation of extensive halite deposits intertwined with clastic sediment [29]. The Bieletan region, entirely covered in quaternary sediments, has sediment thicknesses of up to 2700 m. The upper portion has salt-bearing strata up to 70 m thick, mostly formed of clastic, halite, and potash layers (Figure 2). The postal layer is predominantly located in the uppermost layers. Shallow groundwater is primarily found in the upper quaternary porous sediments, which are also the focus of this study. Senie Lake and artificial water replenishment canals are the main sources of groundwater recharge. Groundwater primarily flows from the surrounding areas toward the central area, with evaporation and human extraction serving as the main discharge processes. Extracted groundwater is transported through brine transportation canals to salt farms beyond the study area. It is evident that there are two groundwater depression funnels in the research region, associated with groundwater extraction.

3. Material and Methods

3.1. Sampling Collection

This study collected 26 groundwater samples in September 2023. Additionally, 2 replenishment canal samples and 1 Senie Lake water sample were collected to investigate their impact on groundwater recharge. The water quality data included measurements of pH, concentrations of specific cations (K⁺, Na⁺, Ca²⁺, Mg²⁺), anions (SO₄²⁻, Cl⁻, CO₃²⁻, HCO₃⁻), TDS, Li⁺, and water density. In October 2023, a total of 21 soluble salt samples were collected from three boreholes (GW6, GW16, GW19). Each borehole yielded 7 soluble salt samples from depths of 0.5 m, 1 m, 2 m, 3 m, 5 m, 7 m, and 10 m below the surface, respectively. Dissolved ions in these samples were detected by analyzing the filtrate, which was filtered after the soil sample was mixed with no-CO₂ water by a ratio of 1 (soil) to 5 (water) and vibrated for 3 min. The detection of all samples included measurements of pH, concentrations of specific cations (K⁺, Na⁺, Ca²⁺, Mg²⁺), anions (SO₄²⁻, Cl⁻, CO₃²⁻, HCO₃⁻), and Li⁺. All samples were analyzed by the Xi’an Center of the China Geological Survey. The concentrations of K⁺, Na⁺, Ca²⁺, Mg²⁺, and Li⁺ were analyzed using an Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES) (PerkinElmer Inc., Shelton, WA, USA). SO₄²⁻ was also measured using ICP-OES. Cl⁻ was determined by silver nitrate titration, while CO₃²⁻ and HCO₃⁻ were analyzed using titration methods. TDS were measured by drying and weighing. To ensure the validity and accuracy of the data, duplicate analyses were performed for each sample, with the replicates showing an error within ±5%. The accuracy and precision of the analyses were verified by analyzing certified reference materials (CRMs) under the same conditions, thereby guaranteeing the reliability of the data. Additionally, blank samples were included in the analysis to monitor and control potential contamination during sample handling and processing. The ion charge balance error percentage (%CBE) is used to calculate the ion balance error of water samples. The ion charge balance error percentage is calculated according to Formula (1):

$$\%\mathrm{CEB}=\frac{(|\mathrm{TC}-\mathrm{TA}|)}{(\mathrm{TC}-\mathrm{TA})}\times 100\%$$

(1)

where TC and TA represent the total concentrations of cations and anions, respectively. The units for both cations and anions are milliequivalents per liter (meq/L). The ion balance error for all water samples was less than 1.69%, and the ion balance error for soluble salts was less than 9.65%. An ion balance error of less than 10% is considered to provide reliable chemical analysis results for hydrogeochemical investigations [30].

3.2. Saturation Index

The Saturation Index (SI) is crucial for evaluating the equilibrium and reactivity between minerals and groundwater [31]. The SI of minerals in water was calculated according to the following Formula (2):

$$\mathrm{SI}=\log (\frac{\mathrm{IAP}}{{\mathrm{K}}_{\mathrm{sp}}})$$

(2)

where, IAP is the ion activity product of the dissolving mineral, and K_sp is the solubility product constant of the mineral. PHREEQC 3.7.3 was used to calculate the SI of possible mineral phases [32]. A positive SI indicates supersaturation (precipitation potential), a negative SI indicates undersaturation (dissolution potential), and an SI of zero indicates equilibrium.

3.3. Hydrogeochemical Modeling

Geochemical simulation is an essential tool for studying the evolution of water chemistry, and inverse modeling is one of the key modeling methods for hydrogeochemical research [33,34]. In this study, PHREEQC is employed for geochemical simulation. Determining the initial and final solutions along the groundwater flow path is a necessary step in modeling. Inverse modeling calculates the moles of minerals dissolved in or precipitated from the solution based on mass balance rules to explain the compositional differences between the initial and final endpoint solutions [35]. The mass balance of the conceptual models can be expressed as the following Formula (3):

$${\displaystyle \sum }_{j=1}^n{a}_{ij}{x}_j=b_i$$

(3)

where a_ij represents the stoichiometric coefficient of element i in mineral j, x_j denotes the molar quantity of minerals or gases that have either dissolved, precipitated, or degassed, and b_i signifies the change in concentration of element i in the final water solution relative to the initial water solution.

4. Results

4.1. Characteristics of Major Indices

The statistical summary of chemical analysis results for groundwater (GW), replenishment canal water samples (SW), and lake water (LW) is presented in

Table 1. Statistical analysis of hydrogeochemical parameters of water samples (in g/L except pH and density in g/cm³).

Type	ID	pH	K+	Na+	Ca2+	Mg2+	SO42−	Cl−	TDS	CO32−	HCO3−	Li+	Density
GW	GW1	8.49	4.05	60.02	0	37.81	6.24	200.54	309.96	0.15	0.18	0.09	1.21
	GW2	8.23	32.81	66.24	1.87	28.39	3.13	214.80	347.67	0	0.32	0.11	1.23
	GW3	6.76	1.85	106.12	1.62	8.32	3.43	190.74	312.23	0	0.48	0.02	1.20
	GW4	8.56	20.97	31.23	0.44	58.08	6.74	229.06	347.22	0.09	0.70	0.17	1.24
	GW5	8.61	6.79	62.04	0.66	37.12	6.84	203.21	317.09	0.04	0.54	0.09	1.22
	GW6	8.65	5.61	56.52	0.54	39.42	8.28	202.32	313.16	0.05	0.52	0.10	1.22
	GW7	8.49	15.30	20.50	0.31	69.06	7.06	237.97	350.73	0.05	0.52	0.11	1.24
	GW8	8.57	6.70	40.53	0.34	53.01	10.65	213.02	324.77	0.04	0.77	0.09	1.23
	GW9	8.67	1.27	26.38	0.29	66.03	9.47	224.60	328.76	0.13	0.82	0.12	1.23
	GW10	8.52	15.80	19.78	0.40	68.82	5.94	238.87	350.54	0.05	0.78	0.27	1.25
	GW11	8.55	12.01	25.62	0.28	64.00	10.33	228.17	341.97	0	1.63	0.51	1.24
	GW12	8.63	8.39	42.20	0.16	51.48	19.85	206.78	329.87	0.08	0.90	0.22	1.23
	GW13	8.61	9.78	20.78	0.18	67.81	12.04	229.06	341.37	0.06	1.31	0.48	1.24
	GW14	8.30	9.47	64.11	0.17	37.09	33.19	191.05	335.32	0	0.10	0.25	1.23
	GW15	8.42	9.62	60.86	0.19	39.81	33.05	194.64	338.44	0.08	0.02	0.26	1.23
	GW16	8.44	7.78	52.24	0.59	39.50	10.48	195.09	305.91	0	0	0.21	1.21
	GW17	8.40	6.77	64.82	0.39	34.48	16.61	195.54	318.83	0.07	0	0.21	1.22
	GW18	8.47	11.48	34.67	0.37	57.01	10.77	218.86	333.31	0.19	0	0.14	1.23
	GW19	8.52	6.69	21.71	0.35	70.09	9.43	234.11	342.53	0.21	0.06	0.14	1.24
	GW20	8.61	6.62	10.82	0.13	84.04	12.27	254.74	368.80	0.32	0.09	0.18	1.26
	GW21	8.42	2.40	101.94	0.83	12.86	5.95	193.30	317.32	0.01	0	0.02	1.21
	GW22	7.85	4.55	78.08	1.31	25.79	5.04	197.78	312.65	0	0.06	0.07	1.21
	GW23	8.54	12.02	74.89	0.17	33.69	41.30	188.36	350.75	0.16	0	0.32	1.24
	GW24	8.56	11.59	40.64	0.28	51.59	14.04	209.89	328.22	0.21	0	0.18	1.23
	GW25	8.71	12.34	36.60	0.63	52.47	6.69	216.64	325.96	0.11	0.18	0.05	1.23
	GW26	8.17	14.01	27.29	5.58	58.56	0.47	232.63	339.45	0	0.52	0.31	1.23
	Min	6.76	1.27	10.82	0	8.32	0.47	188.36	305.91	0	0	0.02	1.20
	Max	8.71	32.81	106.12	5.58	84.04	41.30	254.74	368.80	0.32	1.63	0.51	1.26
	Mean	8.41	9.87	47.95	0.70	47.94	11.89	213.14	332.03	0.08	0.40	0.18	1.23
	SD	0.38	6.58	25.21	1.09	18.58	9.84	18.31	15.88	0.08	0.44	0.12	0.01
	CV(%)	5	67	53	149	39	83	9	5	97	109	68	1
SW	SW1	8.88	0.54	3.63	0.06	47.25	7.55	137.26	196.89	0.28	0.01	0.11	1.15
	SW2	8.81	0.90	7.62	0.17	56.78	9.70	167.28	242.58	0.47	0.09	0.12	1.18
	mean	8.85	0.72	5.62	0.11	52.02	8.62	152.27	219.73	0.37	0.05	0.11	1.16
LW	LW	8.75	2.52	4.70	0.05	106.5	16.61	297.79	428.46	0.78	0.11	0.22	1.31

. The pH values of GW range from 7.76 to 8.71, with an average of 8.41. The average pH for SW is 8.85, and for LW it is 8.75. Therefore, all water bodies in the study area exhibit weak alkalinity. The average concentrations of K⁺, Na⁺, and Ga²⁺ in GW are 9.98 g/L, 47.95 g/L, and 0.73 g/L, respectively, whereas in SW they are 0.72 g/L, 5.62 g/L, and 0.11 g/L, respectively. For LW, the concentrations of K⁺, Na⁺, and Ga²⁺ are 2.52 g/L, 4.70 g/L, and 0.05 g/L, respectively. This suggests that the average concentrations of K⁺, Na⁺, and Ga²⁺ are higher in GW compared to SW and LW. The average concentrations of Mg²⁺ and CO₃²⁻ in GW are 47.94 g/L and 0.08 g/L, respectively, while in SW they are 52.02 g/L and 0.37 g/L, and in LW they are 106.56 g/L and 0.78 g/L, respectively. This indicates that the average concentrations of Mg²⁺ and CO₃²⁻ in GW are lower compared to SW and LW. The average concentrations of SO₄²⁻, Cl⁻, and total dissolved solids (TDS) in GW are 11.89 g/L, 213.24 g/L, and 332.03 g/L, respectively, while in SW they are 8.62 g/L, 152.27 g/L, and 219.73 g/L, and in LW they are 16.61 g/L, 297.79 g/L, and 428.46 g/L, respectively. The average concentrations of SO₄²⁻, Cl⁻, and TDS are higher in GW compared to SW but lower compared to LW. The coefficient of variability (CV) represents the ratio of the standard deviation (SD) to the mean, with a higher CV indicating greater variability. The CV values for the chemical components of GW range from 1% to 149%, with Ca²⁺ and HCO₃⁻ having CV values greater than 100% and Cl⁻, pH, TDS, and density having CV values less than 10%.

The statistical results of core soluble salts are presented in

Table 2. Statistical analysis of physiochemical parameters of soluble ions (in g/kg except pH).

Indices	Soluble Ions
	Min	Max	Mean	SD	CV (%)
pH	8.03	8.53	8.28	0.16	1.93
K+	0.36	16.62	3.31	3.72	112.19
Na+	2.53	313.40	150.01	117.47	78.31
Ca2+	0.37	11.81	5.40	3.20	59.25
Mg2+	0.40	20.59	8.10	6.27	77.46
SO42−	1.96	26.80	10.32	5.74	55.57
Cl−	31.40	570.00	302.70	198.48	65.57
CO32−	0.00	0.28	0.08	0.06	77.95
HCO3−	0.05	0.32	0.15	0.09	59.78
Li+	0.00	0.42	0.13	0.14	110.67

, showing the average contents of K⁺, Na⁺, Ca²⁺, and Mg²⁺ in borehole cores to be 3.31, 150.01, 5.40, and 8.10 g/kg, respectively. The average contents of SO₄²⁻, Cl⁻, CO₃²⁻, and HCO₃⁻ are 10.32, 302.70, 0.08, and 0.15 g/kg, respectively. The average content of Li⁺ is 0.13 g/kg. The pH average of core leachates is 8.28, ranging from 8.03 to 8.53, indicating alkaline properties across the cores, which is one of the reasons for the alkalinity of groundwater in the study area. Na⁺ and Cl⁻ have the largest amounts in soluble salts. K⁺ and Li⁺ have the largest coefficients of variation, indicating an unequal distribution throughout the strata.

4.2. Correlation Analysis

Correlation analysis is a valuable tool in groundwater chemistry studies for identifying relationships between different chemical parameters, understanding the underlying geochemical processes [36]. The findings of a Spearman correlation study performed to evaluate the possible link between various ions of the soluble salts are shown in

Table 3. Correlation matrix of the main ions in soluble salt.

	K+	Na+	Ca2+	Mg2+	Cl−	SO42−	CO32−	HCO3−	Li+	pH
K+	1	−0.42	0.04	0.82 **	−0.4	0.45 *	0.4	0.62 **	0.59 **	0.12
Na+		1	0.58 **	−0.76 **	0.99 **	0.19	−0.82 **	−0.87 **	−0.89 **	−0.71 **
Ca2+			1	−0.22	0.61 **	0.78 **	−0.47 *	−0.35	−0.57 **	−0.47 *
Mg2+				1	−0.73 **	0.19	0.79 **	0.86 **	0.87 **	0.57 **
Cl−					1	0.21	−0.79 **	−0.85 **	−0.88 **	−0.71 **
SO42−						1	−0.15	0.01	−0.11	−0.2
CO32−							1	0.80 **	0.85 **	0.73 **
HCO3−								1	0.81 **	0.63 **
Li+									1	0.71 **
pH										1

Note: ** indicates a significant correlation at the 0.01 level; * indicates a significant correlation at the 0.05.

. The analysis examined the correlation coefficients among 21 sets of 10 ions. The substantial correlation coefficients between Na⁺ and Cl⁻, Ca²⁺ and SO₄²⁻, Mg²⁺ and CO₃²⁻, Mg²⁺ and HCO₃⁻, with values of 0.99, 0.78, 0.79, and 0.86, respectively, indicate widespread distribution of rock salt minerals, gypsum, and dolomite in the region. Negative correlation coefficients between K⁺, Mg²⁺, CO₃²⁻, HCO₃⁻, and Na⁺, Cl⁻ suggest that the formation of rock salt in the area inhibits the formation of other minerals.

Table 4. Correlation matrix of GW.

	K+	Na+	Ca2+	Mg2+	Cl−	SO42−	CO32−	HCO3−	Li+	TDS	pH
K+	1	−0.32	−0.07	0.28	0.38	−0.01	0.01	0.16	0.48 *	0.63 **	−0.01
Na+		1	0.38	−0.98 **	−0.91 **	−0.06	−0.44 *	−0.47 *	−0.37	−0.55 **	−0.49 *
Ca2+			1	−0.42 *	−0.12	−0.87 **	−0.52 **	−0.08	−0.55 **	−0.48 *	−0.44 *
Mg2+				1	0.89 **	0.11	0.48 *	0.43 *	0.37	0.57 **	0.48 *
Cl−					1	−0.21	0.33	0.49 **	0.19	0.59 **	0.37
SO42−						1	0.44 *	−0.22	0.51 **	0.19	0.28
CO32−							1	−0.13	0.18	0.35	0.53 **
HCO3−								1	0.13	0.21	0.44 *
Li+									1	0.54 **	0.02
TDS										1	0.11
pH											1

Note: ** indicates a significant correlation at the 0.01 level; * indicates a significant correlation at the 0.05.

analyzes the correlation coefficients of major ions in groundwater. TDS show a positive correlation with most indicators, notably significant positive correlations with K⁺, Mg²⁺, Cl⁻, and Li⁺. Conversely, TDS exhibit a significant negative correlation with Na⁺ and Ca²⁺. The negative correlations of Na⁺ and Ca²⁺ with other indicators suggest that they are subjected to inhibition by other ions. Specifically, the correlation coefficients between Na⁺ and Mg²⁺, and between Na⁺ and Cl⁻, are highest at −0.98 and −0.91, respectively. This indicates that the dissolution of Na⁺ is most strongly inhibited by Mg²⁺ and Cl⁻. The highest correlation coefficient between Ca²⁺ and SO₄²⁻ is −0.87, suggesting that Ca²⁺ is most strongly inhibited by SO₄²⁻. Additionally, Mg²⁺ and Cl⁻ demonstrate a high degree of correlation, suggesting they share a common source, likely due to the dissolution of halite and magnesium chloride. The correlation coefficients of Mg²⁺, CO₃⁻ and HCO₃⁻ with pH are 0.48, 0.53 and 0.44, respectively, indicating a positive correlation, whereas those of Na⁺ and Ca²⁺ with pH are −0.49 and −0.44, indicating a negative correlation.

4.3. Saturation Index (SI)

The SI is crucial for studying groundwater chemistry processes, serving as a key parameter used to assess the equilibrium state between groundwater and minerals [37,38]. As illustrated in Figure 3, the distribution of saturation indices in the water samples from the survey area reveals that all minerals in the LW and SW water samples have SI values less than 0, indicating undersaturation. In most water samples from the GW body, the saturation indices of dolomite minerals are greater than 0, indicating saturation, while calcite and halite in the GW body are distributed near the SI = 0 line, indicating equilibrium. The saturation indices of the remaining minerals, polyhalite, bischofite, carnallite, and sylvite, are less than 0, indicating an undersaturated state. During the replenishment of GW by SW water, the saturation indices of most minerals increase, suggesting mineral dissolution in the aquifer. Similarly, during the replenishment of GW by LW water, the saturation indices of polyhalite, calcite, and dolomite significantly increase, indicating mineral dissolution during water transport. Conversely, the saturation indices of bischofite and carnallite minerals decrease, suggesting mineral precipitation during water transport.

4.4. Hydrochemical Processes: Inverse Modeling

Reverse hydrogeochemical modeling employs mass balance models to determine the amount of mineral dissolution or precipitation occurring between two different points in groundwater flow processes [39]. In this study, PHREEQC is utilized for reverse water-rock interaction modeling, quantitatively representing water–rock interactions and validating hydrogeochemical processes occurring during groundwater recharge based on the groundwater flow field, in order to study the hydrogeochemical processes occurring along the groundwater recharge routes from lake water and canal water. The reaction simulation paths selected were LW to GW24 and SW1 to GW13, as illustrated in Figure 4. Figure 4a,b show schematic diagrams of groundwater flow patterns between points LW and GW24, and points SW1 and GW13, respectively. Figure 4c,d compare the hydrochemical characteristics between points LW and GW24, and points SW1 and GW13, displaying variations in major indices. From LW to GW24, it can be observed that the concentrations of Na⁺, K⁺, and Ca²⁺ increase, while the values of the other indices decrease. From SW1 to GW13, the concentration of CO₃²⁻ decreases, while the other indices increase. This indicates significant differences in the hydrochemical processes occurring along the paths from LW to GW24 and from SW1 to GW13.

The transfer of mineral components in groundwater along the flow paths is reported in

Table 5. Mineral phase transfer for different pathways calculated by PHREEQC.

Phase	ρ/(mmol/L)
	Chemical Formula	LW-GW	SW-GW
CaX2	CaX2	18.720	2.671
NaX	NaX	−37.450	−5.342
Bischofite	MgCl2·6H2O	−15.980	/
Calcite	CaCO3	/	−5.626
Carnallite	KMgCl3·6H2O	−17.860	0.278
Dolomite	CaMg(CO3)2	/	2.820
Polyhalite	K2MgCa2(SO4)4·2H2O	8.860	/
Gypsum	CaSO4·2H2O	−36.490	−0.017
Halite	NaCl	38.100	6.346

Note: positive value indicates that the mineral phase has dissolved into groundwater, whereas negative values indicate that mineral phases may precipitate out of groundwater.

. For LW to GW24, along the flow path, cation exchange leads to the entry of 18.72 mmol/L of Ca²⁺ into groundwater and 37.45 mmol/L of Na⁺ out of groundwater. The primary water–rock interactions causing changes in groundwater chemistry include the precipitation of bischofite, carnallite, and gypsum, with precipitation rates of 15.980 mmol/L, 17.860 mmol/L, and 36.490 mmol/L, respectively. Additionally, polyhalite and halite dissolve, with dissolution rates of 8.860 mmol/L and 38.100 mmol/L, respectively.

For SW1 to GW13, along the flow path, cation exchange results in 2.671 mmol/L of Ca²⁺ entering groundwater and 5.342 mmol/L of Na⁺ leaving groundwater. The main water–rock interactions causing changes in groundwater chemistry are the precipitation of calcite and gypsum, with precipitation rates of 5.626 mmol/L and 0.017 mmol/L, respectively. Additionally, carnallite, dolomite, and halite dissolve, with dissolution rates of 0.278 mmol/L, 2.820 mmol/L, and 6.346 mmol/L, respectively.

5. Discussion

5.1. Hydrogeochemistry

The Piper diagram is frequently utilized for analyzing the hydrochemical types of groundwater. As shown in Figure 5, the anions of GW water are primarily distributed in Zones C (Magnesium type) and D (Sodium type), while cations are mainly distributed in Zone G (Chloride type). Therefore, the hydrochemical types of GW are identified as Cl-Mg type and Cl-Na type. SW and LW exhibit anion distributions in Zone C (Magnesium type) and cation distributions in Zone G (Chloride type), indicating that the hydrochemical types of SW and LW are Cl-Mg type. All water bodies belong to the low-Ca high-Cl type, with the lowest Na⁺ + K⁺ content and the highest Mg²⁺ content in SW and LW waters, suggesting that during the migration process from SW and LW to GW, the concentration of Na⁺ + K⁺ gradually increases while the concentration of Mg²⁺ decreases. The concentration of Cl⁻ is highest in all water bodies, indicating that Cl⁻ is the dominant anion during water migration, and its variation is relatively small.

5.2. Water–Rock Interaction

The Gibbs diagram is a widely used tool for understanding the natural formation mechanisms of water bodies [40,41]. According to the Gibbs diagram, there are three primary mechanisms: Evaporation Dominance, Rock Dominance, and Precipitation Dominance. As shown in Figure 6, all the water sample points are clustered in the upper right corner, indicating that the formation mechanism of all the water samples is predominantly influenced by evaporation.

To further analyze the factors influencing the formation of water chemistry, scatter plots depicting the relationships between various components were created as shown in Figure 7. Figure 7a,b illustrate the relationships between Cl⁻ vs. Na⁺ and Cl⁻ vs. Mg²⁺, respectively. It can be observed that Na⁺ is negatively correlated with Cl⁻. As the Cl⁻ concentration increases in the GW water bodies, the Na⁺ concentration decreases exponentially, with all water samples falling below the 1:1 line. This indicates that the excess Cl⁻ may originate from the dissolution of minerals such as carnallite and bischofite. The Na⁺ concentrations in LW and SW are lower compared to those in GW, suggesting that as LW and SW recharge the groundwater, the Na⁺ concentration rises, indicating the dissolution of halite. Mg²⁺ shows a positive correlation with Cl⁻, with its concentration increasing as Cl⁻ concentration rises. This is attributed to the dissolution of carnallite and bischofite. Figure 7c shows the relationship between Ca²⁺ and SO₄²⁻. In GW, Ca²⁺ is negatively correlated with SO₄²⁻, with most water samples lying below the 1:1 line. This suggests that the dissolution of gypsum is not the source of Ca²⁺ and SO₄²⁻ in the study area. Additionally, there is evidence of Ca²⁺ depletion and SO₄²⁻ enrichment, indicating that the dissolution of polyhalite affects the sources of Ca²⁺ and SO₄²⁻.

Figure 7d displays the relationship between (Ca²⁺ + Mg²⁺) and (HCO₃⁻ + SO₄²⁻). All water samples are located above the 1:1 line, indicating that the contributions of calcite, dolomite, and gypsum dissolution to the concentrations of (Ca²⁺ + Mg²⁺) in groundwater are minimal. Instead, the dissolution of other minerals, such as polyhalite, increases the concentrations of Ca²⁺ and Mg²⁺.

5.3. Cation Exchange Interaction

Cation exchange is another crucial mechanism that governs water chemistry [42]. Chloro-alkaline indices (CAI-I and CAI-II) serve as valuable tools for evaluating the direction of alternating cation adsorption processes. These indices are calculated as follows:

$$\mathrm{CAI}-\mathrm{I}=\frac{{\mathrm{Cl}}^{-}-\left({\mathrm{Na}}^{+}+{\mathrm{K}}^{+}\right)}{{\mathrm{Cl}}^{-}}$$

(4)

$$\mathrm{CAI}-\mathrm{II}=\frac{{\mathrm{Cl}}^{-}-\left({\mathrm{Na}}^{+}+{\mathrm{K}}^{+}\right)}{{{\mathrm{HCO}}_3}^{-}+{{\mathrm{SO}}_4}^{2-}+{{\mathrm{CO}}_3}^{2-}+{{\mathrm{NO}}_3}^{-}}$$

(5)

If both are negative values, it indicates cation exchange as shown in Equation (6) occurring in the groundwater system. Conversely, if both are positive values, it indicates reverse cation exchange as shown in Equation (7).

$${\mathrm{Na}}_2{\mathrm{X}+\mathrm{Ca}}^{2+}\to { 2\mathrm{Na}}^{+}{+\mathrm{CaX}}_2$$

(6)

$$2{\mathrm{Na}}^{+}{+\mathrm{CaX}}_2\to { \mathrm{Ca}}^{2+}{+\mathrm{Na}}_2\mathrm{X}$$

(7)

As shown in Figure 8a, all sampling points in the study area lie in the first quadrant, indicating cation exchange as described in Equation (7), where adsorbed Ca²⁺ is replaced by Na⁺. This process leads to an increase in Ca²⁺ concentration and a decrease in Na⁺ concentration in groundwater. There is an outlier in the Figure 8a with a very high CAI-II value, indicating strong cation exchange at this point, which has led to a significant decrease in Na⁺. It is hypothesized that this point may have been more strongly influenced by confined groundwater recharge. Additionally, the relationship between [(Ca²⁺ + Mg²⁺) − (HCO₃⁻ + SO₄²⁻)] vs. [Na⁺ + K⁺ − Cl⁻] and is commonly used to study cation exchange. [(Ca²⁺ + Mg²⁺) − (HCO₃⁻ + SO₄²⁻)] represents the increase or decrease in Ca²⁺ and Mg²⁺ in the water body, excluding dissolution of gypsum, calcite, and dolomite. [Na⁺ + K⁺ − Cl⁻] represents the increase or decrease in Na⁺, excluding the dissolution of halite. If cation exchange is the primary process controlling groundwater mineralization, their relationship should be linear, and the slope should be close to −1. As shown in Figure 8b, there is a good linear relationship between [(Ca²⁺ + Mg²⁺) − (HCO₃⁻ + SO₄²⁻)] vs. [Na⁺ + K⁺ − Cl⁻] in the study area, with a linear regression slope of −1.019, which is very close to the theoretical value of −1.0. This indicates the involvement of Na⁺, Ca²⁺, and Mg²⁺ in cation exchange in groundwater.

5.4. Hydrogeochemical Processes

Chloro-alkaline indices and reverse hydrogeochemical modeling show that cation exchange has a greater impact on groundwater chemistry during groundwater recharge from lake water than from canal water, with the cation exchange process being stronger in the former. Carnallite precipitates along the flow path of groundwater recharge from lake water, whereas it dissolves along the flow path of groundwater recharge from canal water. Gypsum precipitates along both lake water and canal water flow paths for groundwater recharge, but the precipitation rate is faster in lake water recharge. During the processes of groundwater recharge from both lake water and canal water, halite experiences varying degrees of dissolution, with a faster dissolution rate in lake water, possibly due to the cation exchange processes occurring along the flow paths.

6. Conclusions

This paper investigates groundwater, surface water, and soluble salts in the Bieletan region. Utilizing multivariate techniques, saturation indices, and hydrogeochemical modeling, the study identifies the hydrochemical characteristics of groundwater, the main influencing factors on groundwater, and the hydrogeochemical processes occurring during different recharge processes in the Bieletan area. The following key conclusions are summarized:

• Groundwater (GW) cation concentrations are ranked as Na⁺ > Mg²⁺ > K⁺ > Ga²⁺, while in the case of lake water (LW) and stream water (SW), cation concentrations are Mg²⁺ > Na⁺ > K⁺ > Ga²⁺. The anion concentrations in GW are ranked as Cl⁻ > SO₄²⁻ > HCO₃⁻ > CO₃²⁻, whereas in LW and SW, the order is Cl⁻ > SO₄²⁻ > CO₃²⁻ > HCO₃⁻. The mean total dissolved solids (TDS) values for GW and SW are 332.03 g/L and 219.73 g/L, respectively, while for LW, it is 428.46 g/L. The hydrochemical types of GW are classified as Cl-Mg type and Cl-Na type, whereas LW and SW are categorized as Cl-Mg type.
• Evaporation is the primary mechanism governing the formation of GW, LW, and SW. Cation exchange and mineral precipitation/dissolution are identified as the primary factors influencing water chemistry. Minerals in LW and SW are generally undersaturated, while in GW, apart from dolomite, calcite, and halite, which are saturated or near-saturated, other minerals remain undersaturated.
• GW receives recharge from two distinct sources, LW and SW. These two different water bodies undergo distinct hydrogeochemical processes during groundwater recharge. The rates of cation exchange and mineral dissolution are faster in LW, where mineral precipitation predominantly occurs, whereas mineral dissolution is more prevalent in SW.