Open AccessArticle

Hydrochemical Evolution Process and Mechanism of Groundwater in the Hutuo River Alluvial Fan, North China

Junbai Gai

^1,2,3

Baizhong Yan

^2,3

Chengbo Fan

^1,*

Yapeng Tuo

^2,3 and

Miaomiao Ma

^2,3

Hebei Key Laboratory of Geological Resources and Environment Monitoring and Protection, Hebei Geological and Environmental Monitoring Institute, Shijiazhuang 050031, China

Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang 050031, China

Hebei Center for Ecological and Environmental Geology Research, Shijiazhuang 050031, China

Author to whom correspondence should be addressed.

Water 2024, 16(16), 2229; https://doi.org/10.3390/w16162229

Submission received: 2 July 2024 / Revised: 29 July 2024 / Accepted: 5 August 2024 / Published: 7 August 2024

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Figure 1
(a) Distribution of the groundwater and precipitation monitoring points in the study area; (b) hydrogeologic profile along the I–I’ line. "> Figure 2
Groundwater flow fields in 1980, 2015, and 2021. "> Figure 3
(a) Duration curve of groundwater hydrochemical composition; (b) hydrochemical Piper plots of groundwater from 1980 to 2021. "> Figure 4
Spatial distributions of major ions. "> Figure 5
(a,b) Gibbs diagram of groundwater; (c,d) Diagram of relative contribution rate of rock weathering and dissolution. "> Figure 6
Relationship between chloro–alkali index and TDSs. "> Figure 7
(a) Ratio of Na+ to Cl− in groundwater; (b) Ratio of Ca2+ to HCO3− in groundwater; (c) Ratio of Ca2+ + Mg2+ to HCO3− in groundwater; (d) Ratio of Ca2+ + Mg2+ to HCO3− + SO42− in groundwater. "> Figure 8
Comparison between the variation of groundwater level and ion concentration. ">

Versions Notes

Abstract

Due to extensive groundwater exploitation, a groundwater funnel has persisted in the Hutuo River alluvial fan in Shijiazhuang since the 1980s, lasting nearly 40 years and significantly impacting the groundwater chemical characteristics. In this study, based on the groundwater level and chemistry data, the hydrochemical evolution processes and mechanisms of the groundwater during the 1980 groundwater funnel period and the post-2015 artificial governance period were investigated using traditional hydrogeochemical methods and inverse hydrogeochemical simulations. The results show the following: (1) The ion concentrations gradually increased along the groundwater flow path, where they displayed a pattern of lower levels in the northwest and higher levels in the southeast. From 1980 to 2021, the concentrations of major ions were increased. (2) In 1980s, the groundwater hydrochemical type predominantly exhibited HCO₃—Ca. From 1980 to 2015, the hydrochemical types diversified into HCO₃·Cl—Ca, HCO₃—Ca·Mg, and HCO₃·SO₄—Ca types. Following the artificial governance, the groundwater level rise led to an increase in the concentrations of SO₄²⁻ and Mg²⁺. Post-2015, the prevailing hydrochemical type changed to HCO₃·SO₄—Ca·Mg. (3) The changes in the groundwater level and ion concentrations were quantitatively strongly correlated and exhibited spatial similarity. (4) In the 1980s, the groundwater hydrochemical composition was primarily controlled by the dissolution of albite, dolomite, halite, and quartz; reverse cation exchange; and groundwater exploitation. Since 2015, the hydrochemical composition has mainly been influenced by the dissolution of albite, calcite, and quartz; positive cation exchange; river–groundwater mixing; and industrial activities, with increasing intensities of both water–rock interactions and human activities.

Keywords:

Hutuo river alluvial fan; groundwater funnel areas; artificial governance; hydrochemistry; formation mechanism

1. Introduction

Groundwater is essential for the sustainability of Earth’s ecosystems and the development of human societies. The over-extraction of groundwater results in the formation of groundwater funnels, which subsequently lead to a decline in groundwater levels, seawater intrusion, and land subsidence. In response, policies have been formulated by various nations to address these challenges. Policies have been enacted by Saudi Arabia to reduce the demand for agricultural water, yielding significant outcomes [1]. Furthermore, aquifer mapping and management initiatives have been undertaken by the Indian government to mitigate the over-extraction of groundwater [2]. With the implementation of effective measures, the phenomena of groundwater funnels were diminished, leading to a rise in water levels and a reversal of the depletion trend [3]. Researchers worldwide have also studied this issue. Nazanin (2024) [4] investigated the mechanisms by which groundwater over-extraction causes subsidence using the differential interferometric synthetic aperture radar (DInSAR) technique. Lu et al. (2024) [5] developed an intelligent simulation model for groundwater over-extraction in Lake Ayding using a reverse calculation method. In recent years, the issue of changes in groundwater chemistry resulting from the artificial management of groundwater levels has attracted increasing attention. However, the mechanisms of changes in groundwater chemistry due to changes in groundwater dynamics under different time periods remain unclear, especially after artificial governance. Scholars have also discussed this problem. Maghrebi et al. (2021) [6] evaluated the groundwater hydrochemistry in Iran and discovered a significant correlation between the geological and geomorphological features and the hydrochemical facies/groundwater quality in the region. However, the connection between groundwater levels and groundwater quality was not examined. Wang et al. (2024) [7] analyzed the impact of river water replenishment on the groundwater chemical field, revealing that using reclaimed water for groundwater replenishment can have adverse effects on the groundwater quality. However, it was not discussed whether changes in groundwater quality were related to fluctuations in the groundwater levels under recharge conditions. Chen et al. (2023) [8] analyzed the characteristics and formation mechanisms of the groundwater chemical field in Hengshui City after artificial remediation. The findings revealed an increase in the concentration of SO₄²⁻ in groundwater after artificial governance. During artificial governance, water–rock interactions, changes in the redox environment, and the influence of external waters can significantly alter the chemical characteristics of groundwater [9]. The issue of changes in the groundwater chemistry field that occur during the process of artificial management of groundwater levels needs further investigation.

At present, limiting groundwater exploitation and the artificial recharge of groundwater are the main control measures for groundwater overexploitation around the world [10]. To restrict groundwater extraction, groundwater overexploitation areas were first designated as groundwater prohibition zones. Subsequently, all extraction wells within these zones were closed to reduce groundwater withdrawal in the area [11]. This was often the initial step in managing groundwater over-extraction. In some highly urbanized areas, it is often very difficult for precipitation to infiltrate and recharge groundwater. Simply restricting groundwater extraction is not effective for the recovery of groundwater levels [12]. The artificial recharge of groundwater was especially important at this time. It is used to inject surface water or other water sources into groundwater through artificial water injection wells or river channels to recharge them [5]. The artificial recharge of groundwater is an important measure in the treatment of groundwater overexploitation.

Groundwater, as one of the primary water sources for the North China Plain, plays a crucial role in urban development and the lives of people [13]. The Shijiazhuang Hutuo River alluvial fan is one of the fastest developing regions in the North China Plain. Years of overexploitation of groundwater have altered the local aquifer system, creating the largest groundwater funnel area in the region [14]. Following interventions in 2015, the groundwater funnel gradually diminished. The groundwater chemical field changed dramatically from 1980 to 2021. Most of the groundwater chemistries were HCO₃-Ca before 1980. After the emergence of groundwater funnels, the groundwater types became complex. The groundwater quality deteriorated and the HCO₃·Cl—Ca and HCO₃·SO₄—Ca types appeared locally. The groundwater funnel disappeared after artificial governance in 2015. The groundwater types became simple but mostly HCO₃·SO₄—Ca·Mg. While artificial governance often primarily focuses on changes in groundwater levels, the characteristics of groundwater geochemical under artificial governance also determine the effectiveness of these interventions and the future development of the city. The hydrochemical evolution processes and mechanisms of groundwater are crucial in shaping future groundwater management strategies [15]. Thus, elucidating these connections is vital for groundwater management and sustainable exploitation.

In this study, the Hutuo River alluvial fan was chosen as the research area. Since the 1980s, a groundwater funnel has formed in the Hutuo River alluvial fan due to excessive groundwater extraction. As this extraction increased, the depth of the funnel’s center deepened, and its affected area expanded. In 2015, local government measures, including restricting groundwater extraction and artificial recharge, curbed the development of the funnel area. By 2021, the groundwater funnel in the study area had disappeared, causing significant changes in the groundwater dynamic field. However, the impact of its evolution on hydrochemical changes remains unclear. Therefore, based on the analysis of regional geological and hydrogeological conditions, the dynamic monitoring data of the groundwater chemical composition from 1980 to 2021 were obtained from 64 groundwater-monitoring wells. Hydrochemical diagram methods, ion ratio relationship analysis, Spearman correlation analysis, and inverse hydrogeochemical modeling were employed to investigate the chemical evolution and formation mechanisms of the groundwater during the transition from extensive to restricted extraction. The chemical evolution of the groundwater was revealed during artificial governance measures, including restricted extraction and surface water recharge. Scientific evidence is provided for comprehensive and efficient groundwater management.

2. Materials and Methods

2.1. Study Area

Located in the Hutuo River alluvial fan of Shijiazhuang city (Figure 1a), the study area was the largest groundwater funnel area. The groundwater funnel, which had been present since 1980, gradually diminished following artificial governance in 2015. This groundwater funnel had a long duration and affected a wide area. Long-term observational data from 1980 to 2015 indicate an average groundwater level decline of 30.59 m.

Covering an area of 648.33 km², the study region experiences a temperate continental monsoon climate, maintaining an average temperature of 13 °C annually. Most of its precipitation falls between July and August, totaling an average of 514.9 mm per year. There is one river in the northern part of the study area: the Hutuo River. The groundwater here is Quaternary loose rock pore water. Through analysis of the hydrogeological traits and Quaternary sedimentation trends, the groundwater consisted of shallow pore water. The aquifer’s lithology primarily consisted of medium-to-coarse sand and gravelly sand (Figure 1b). The predominant minerals were calcite, dolomite, gypsum, and halite. Spanning northwest to southeast, the study area’s terrain demonstrates a gradual descent, which is paralleled by the flow of the groundwater. Since 1980, extensive extraction of groundwater and inadequate management policies have led to continuous declines in the groundwater levels and a subsequent deterioration in the groundwater quality. Post-2015, artificial governance has been implemented to rectify groundwater over-extraction and funnel issues. These measures facilitated an annual restoration of groundwater levels and a progressive amelioration in groundwater quality.

2.2. Data Source

Precipitation data, groundwater quality, and groundwater level monitoring data were collected for three distinct periods in this study: the period of excessive groundwater extraction in 1980, the initial phase of artificial groundwater governance in 2015, and the period following the commencement of artificial governance in 2021. A total of 64 groups of groundwater-monitoring wells and one precipitation monitoring station were used. Data were sourced from the National Geological Data Museum (China), which were measured and compiled by the Hebei Geological Environmental Monitoring Institute. The locations of groundwater-monitoring points were evenly distributed (Figure 1a). The components tested for groundwater quality include K⁺, Na⁺, Ca²⁺, Mg²⁺, SO₄²⁻, Cl⁻, HCO₃⁻, NO₃⁻, and TDSs. The groundwater level data were sampled annually in December.

2.3. Research Method

The groundwater flow field was analyzed using the ordinary Kriging method in ArcGIS 10.8.1 to study the groundwater level evolution in the area. Ordinary Kriging, which is a statistical technique prevalent in the earth sciences, minimizes prediction errors by estimating unknown data points through the weighted averages of known values [16]. Piper diagrams, box plots of groundwater ion concentrations, spatial distribution maps of major ion concentrations, and spatial distribution maps illustrating changes in major ion concentrations from 1980 to 2021 were utilized to analyze the hydrochemical types and major ion concentrations. Correlation analyses between groundwater levels and ion concentrations were performed to assess the effects of groundwater level fluctuations on hydrochemistry and major ion concentrations. Gibbs diagrams and rock-weathering diagrams were constructed to qualitatively investigate the origins of groundwater hydrochemistry. Subsequently, correlation heat maps, ion ratio analyses, chloride alkalinity indices, and the hydrogeochemical software Phreeqc (3.6.2) were employed to quantitatively assess the mechanisms influencing the groundwater hydrochemistry [17].

The spatial distribution and temporal variability of ion concentrations in the study area were analyzed using the ordinary Kriging method within the geographic information system software ArcGIS 10.8.1. The correlation coefficient quantifies the association level between two random variables. A coefficient greater than 0 indicates a positive correlation, which strengthens as the value approaches 1; conversely, a value less than 0 indicates a negative correlation, intensifying as it nears −1. A coefficient close to 0 suggests a weak correlation. The Pearson correlation coefficient is used for variables describable by linear relationships, while the Spearman correlation coefficient is preferable for non-linear relationships [18].

In the Gibbs diagram, the primary origins of chemical components in groundwater are classified into three distinct categories: evaporation, rock, and precipitation. The diagram’s vertical axis quantifies the TDS values of groundwater samples, whereas the horizontal axis delineates the ratios of either the Na⁺/(Na⁺ + Ca²⁺) or Cl⁻/(Cl⁻+ HCO₃⁻) present in these samples [19].

The chloro–alkali index was employed to evaluate the intensity of ion exchange adsorption during the formation of chemical constituents in groundwater and to ascertain the direction of the cation exchange processes. An increase in the absolute value of this index signifies an intensification of ion exchange adsorption. A negative chloro–alkali index indicates an exchange of Ca²⁺ or Mg²⁺ in the groundwater with Na⁺ or K⁺ from the aquifer medium, whereas a positive index reflects the reverse scenario. Equations (1) and (2) provide the calculation methodology [20].

C A I - 1 = \frac{{m e q}_{{C l}^{-}} - ({m e q}_{{N a}^{+}} + {m e q}_{K^{+}})}{{m e q}_{{C l}^{-}}}

(1)

C A I - 2 = \frac{{m e q}_{{C l}^{-}} - ({m e q}_{{N a}^{+}} + {m e q}_{K^{+}})}{{m e q}_{{S O}_{4}^{2 -}} + {m e q}_{{H C O}_{3}^{-}} + {m e q}_{{C O}_{3}^{2 -}} + {m e q}_{{N O}_{3}^{-}}}

(2)

Inverse hydrogeochemical simulation was employed to elucidate the disparities in chemical constituents between two groundwater samples along identical flow paths and to identify the geochemical reactions that engender these differences. The present study examined two simulation trajectories, which were designated S84→S63 from 1980 and S85→S96 from 2021 (Figure 2a,b).

In order to avoid the limitations and errors brought by the research methods, this study used traditional hydrogeochemical methods and reverse hydrogeochemical simulation. First, the traditional hydrogeochemical method was used for the qualitative analysis. On the basis of the qualitative analysis, the reverse hydrogeochemical simulation was used for the quantitative research. The two methods supported each other to reduce the potential error sources.

3. Results

3.1. Characteristics of Groundwater Level Evolution

By 1980, a groundwater funnel had established in the Qiaoxi District, where the core zone’s groundwater level fell below 50 m. The groundwater flow was directed from northwest to southeast, culminating in a convergence at the funnel in Qiaoxi District. During this period, the groundwater levels were between 50 and 95 m (Figure 2a).

Artificial groundwater management started from the year 2015. The groundwater funnel only remained along the western boundary, and thus, there was no significant groundwater convergence phenomenon within the study area. Compared with 1980, the overall groundwater level had decreased, where the reductions ranged from 5 to 30 m and the groundwater levels varied between 20 and 90 m (Figure 2b). By 2021, the groundwater levels in the Yuhua District and Loudi Town had significantly recovered. The lowest groundwater level had risen from 20 m to 22 m. Concurrently, the groundwater funnels within the area were eliminated. However, a decrease in the groundwater levels was recorded near Huangbizhuang Town in the northwest sector (Figure 2c). During the period from 1980 to 2021, there was a progressive increase in the hydraulic gradient.

From 1980 to 2021, the groundwater level ranged from −27.92 to 8.79 m. The areas where the groundwater level rose were Xinhua District and Qiaoxi District in 1980, where the groundwater levels rose from 1.49 to 8.79 m. The locations of the groundwater level decline were concentrated in the eastern part, which included the eastern part of Zhengding County, Chang’an District, Yuhua District, and most areas of Loudi Town, where the groundwater levels decreased from 2.55 to 27.92 m (Figure S1). Overall, the study area exhibited regional disparities in the groundwater dynamics, with increases primarily in the western sectors and decreases in the eastern sectors. The extent of areas whose groundwater levels rose surpassed those with declined levels. Artificial governance positively influenced the groundwater levels throughout the study region.

3.2. Distribution of Hydrochemical Characteristics

3.2.1. Temporal Distribution

There were increases in the concentrations of Ca²⁺, Mg²⁺, Na⁺, SO₄²⁻, Cl⁻, HCO₃⁻, and the TDSs, whereas the concentration of NO₃⁻ decreased (Figure 3a). Compared with 1980, the average concentrations of SO₄²⁻, Ca²⁺, and TDSs significantly increased to 111.84 mg/L, 48.61 mg/L, and 332.99 mg/L, respectively. Relative to 2015, the average concentrations of SO₄²⁻ and HCO₃⁻ exhibited significant rises to 86.26 mg/L and 43.98 mg/L, whereas those of NO₃⁻ and Cl⁻ declined to 25.03 mg/L and 19.56 mg/L. Between 1980 and 2021, the concentrations of Na⁺, Cl⁻, and HCO₃⁻ fluctuated. Specifically, the concentrations of Na⁺ and Cl⁻ initially rose and subsequently declined, whereas those of HCO₃⁻ decreased initially before they increased.

Between 1980 and 2021, a diverse spatial distribution of major ion concentrations was documented within the study area (Table 1). Na⁺, Cl⁻, SO₄²⁻, and NO₃⁻ demonstrated significant variability, where NO₃⁻ exhibited exceptionally high variability; its coefficient of variation reached 1.05 in 2018. After 2015, the coefficient of variations for these four ions decreased. The spatial distribution of the ion concentrations gradually stabilized. This variability during the early period (1980–2015) was largely attributed to human influences, such as excessive groundwater exploitation and agricultural and industrial activities. Conversely, the decrease in variability from 2015 to 2021 was primarily due to effective artificial governance. The variabilities of Ca²⁺, Mg²⁺, HCO₃⁻, and TDSs were relatively low and did not significantly change.

The groundwater chemical types in the study area showed strong variability at different times (Figure 3b). In the 1980s, the groundwater chemical types were complex and primarily included HCO₃—Ca, HCO₃·Cl—Ca, and HCO₃·SO₄—Ca. By 2015, the groundwater chemical typology had simplified, where the concentrations of SO₄²⁻, Cl⁻, Ca²⁺, and Mg²⁺ rose, which culminated in predominately HCO₃·SO₄—Ca·Mg and HCO₃·Cl—Ca·Mg types. In 2018, the number of hydrochemical types was more singular than in 2015. The concentration of SO₄^2- in the groundwater increased, while the concentration of Cl⁻ decreased. The dominant hydrochemical type was HCO₃·SO₄—Ca·Mg, where some points showed HCO₃·SO₄—Ca·Na- and HCO₃—Ca·Na-type groundwaters. In 2021, as the concentrations of Mg²⁺ and SO₄²⁻ were consistently elevated, 97% of the monitoring sites were categorized as HCO₃·SO₄—Ca·Mg types.

3.2.2. Correlation Analysis between Groundwater Level and Hydrochemistry

The impact of groundwater level changes on the ion concentration variations from 1980 to 2021 was analyzed using the Spearman correlation coefficient method (Figure S2). A robust positive correlation was found between the groundwater level changes and the variations in concentrations of Ca²⁺, Mg²⁺, Na⁺, and HCO₃⁻. Mg²⁺ exhibited the highest correlation coefficient at 0.72, which signified a substantial influence from the changes in the groundwater levels.

Variations in the HCO₃⁻ concentrations were strongly correlated with changes in the concentrations of Na⁺, Ca²⁺, and Mg²⁺, where Mg²⁺ displayed the highest correlation coefficient of 0.84. Cl⁻ also showed a strong positive correlation with these ions. In contrast, SO₄²⁻ exhibited only a weak correlation with Ca²⁺ and no significant correlation with either Na⁺ or Mg²⁺. The correlations between the ion concentration variations suggested that the groundwater chemical components likely stemmed from water–rock interactions that involved carbonate, silicate, and gypsum, as well as from human activities [21].

3.2.3. Spatial Distribution

The spatial distribution of the principal groundwater ions was characterized by lower concentrations in the north and higher concentrations in the south, where the concentrations progressively increased along the groundwater flow path (Figure 4). An inverse correlation existed between the ion concentrations and the groundwater levels. Between 1980 and 2021, notable fluctuations occurred in the concentration ranges of the cations Ca²⁺ and Mg²⁺. The spatial distribution of Mg²⁺ remained relatively constant, with lower concentrations in Huangbizhuang Town and the northern part of Zhengding County, and higher concentrations in Qiaoxi District, Yuhua District, and Loudi Town. In 1980, the spatial distribution of Ca²⁺ was like that of Mg²⁺. In 2021, the regions with low Ca²⁺ concentrations shifted to the western parts of Huangbizhuang Town and eastern Zhengding County, while high concentrations were prevalent in central Zhengding County and the study area’s southern regions. Between 1980 and 2021, the numerical range of Na⁺ concentrations remained relatively stable, although there were significant changes in the spatial distribution. In 1980, lower Na⁺ concentrations were identified in Huangbizhuang Town, Zhengding County, Luquan District, and Xinhua District, with higher concentrations observed in Qiaoxi District, Chang’an District, and Yuhua District. There was an absence of a transitional zone between the areas of high and low concentrations, which reflected the strong variability in Na⁺ concentrations documented during that period. In 2021, the Na⁺ concentrations across the study area tended toward uniformity, with a diminished area of low concentrations in western Zhengding County. The areas of high concentration remained largely unchanged, where the remaining regions exhibited medium concentrations, which confirmed the reduction in Na⁺ concentration variability, as indicated in Table 1.

From 1980 to 2021, the concentration range of the anion SO₄²⁻ varied significantly. There was no evident correlation between the spatial distribution of the SO₄²⁻ concentration in the groundwater and the direction of the groundwater flow. In 1980, the low concentration areas were in the northern part of the study area and the northwest of Qiaoxi District, while the high concentration areas were in the central and eastern parts of the study area. By 2021, lower concentrations were identified in Huangbizhuang Town, Yuhua District, and Loudi Town, whereas higher concentrations were noted in the western regions, which encompassed Luquan District, Xinhua District, and Qiaoxi District. Between 1980 and 2021, the range and spatial distribution of the HCO₃⁻ concentrations exhibited minimal variability, as characterized by lower concentrations in the north and higher concentrations in the south. In 2021, an expansion in the area of high HCO₃⁻ concentrations was recorded compared with 1980. The changes in the Cl⁻ concentrations were similar to those of Na⁺. In 2021, the maximum concentration of Cl⁻ increased compared with 1980. However, the extent of high-Cl⁻-concentration areas diminished, while areas with lower concentrations expanded. The distribution of the TDS concentration showed lower levels in the north and higher levels in the south. The TDS concentration gradually increased along the direction of the groundwater flow. The peak concentration in 2021 increased from 632.00 mg/L in 1980 to 1121.00 mg/L. The lowest concentration in 2021 decreased from 338 mg/L in 1980 to 161.00 mg/L. This change was related to the artificial governance. In the northern part of the study area, the Hutuo River groundwater recharge project introduced low-concentration surface water into the groundwater, which caused a dilution effect and resulted in a decrease in the lowest concentration. The southern part of the study area was a restricted groundwater extraction area, where the groundwater level rose significantly. The ions were mostly enriched in this area, and thus, the concentration of TDSs in this area increased.

3.3. Sources of Hydrochemical Components

3.3.1. Dissolution

To elucidate the origins of the chemical components in the groundwater, the principal factors that influenced the groundwater chemistry within the study area were initially differentiated by employing a Gibbs diagram. Between 1980 and 2021, the groundwater-monitoring points were within the rock dominance areas (Figure 5a,b). Exceptionally, a single station in 2015 was positioned in the evaporation crystallization dominance areas. This distribution suggested that the chemical composition of the groundwater was primarily influenced by rock weathering.

Upon establishing rock-weathering dissolution as the principal controlling factor, the influence of various rocks’ dissolution processes on the groundwater’s chemical composition was evaluated through a rock-weathering end-member diagram. Between 1980 and 2021, groundwater samples predominantly aligned between the silicate and carbonate rock end members (Figure 5c,d). The groundwater’s chemical composition in the study area was influenced by both rock types, which corroborated the hypothesis stated in Section 3.2.3. From 1980 to 2021, the groundwater-monitoring sites transitioned from dispersed to concentrated and progressively clustered around the silicate rock end member. During the artificial governance process, the weathering and dissolution of silicate rocks in the groundwater were enhanced [22].

3.3.2. Ion Exchange

From 1980 to 2021, the groundwater-monitoring sites were predominantly located near a slope of −1 (Figure S3), indicating the presence of cation exchange adsorption in the area’s groundwater [8]. The direction and intensity of the cation exchange adsorption within the groundwater were analyzed by the chloro–alkali index (CAI) [23]. In 1980, 73.33% of the monitoring sites reported positive CAI values compared with 26.67% with negative values. By 2021, the proportion of sites with positive CAI values decreased to 67.74%, while those with negative values increased to 32.26% (Figure 6). Reverse cation exchange adsorption was the dominant process in the groundwater, which is characterized by the exchange of Na⁺ and K⁺ in the groundwater with Ca²⁺ and Mg²⁺ in the aquifer medium. Conversely, a minority of sites demonstrated direct cation exchange adsorption, which involves the exchange of Ca²⁺ and Mg²⁺ in the groundwater with Na⁺ and K⁺ in the aquifer medium. In 2021, the smallest absolute value of the chloro–alkali index indicates that following the implementation of the artificial management, the strength of the cation exchange adsorption in the groundwater of the study area declined. And the correlation coefficients between the TDSs and the chloro–alkali index in the groundwater were relatively high, where both exceeded 0.6, indicating a strong positive correlation. The TDSs were strongly influenced by cation exchange adsorption.

3.3.3. Ion Proportion Relation

From 1980 to 2021, differences existed in the correlation coefficients between the major ions in the groundwater of the study area (Figure S4). In 1980, a robust correlation existed between Na⁺ and HCO₃⁻, as well as Cl⁻, and Ca²⁺ showed strong correlations with HCO₃⁻ and SO₄²⁻. By 2015, the correlation between Ca²⁺ and SO₄²⁻ had diminished to a coefficient of 0.36, whereas the correlations of Mg²⁺ with HCO₃⁻ and Cl⁻ had strengthened, with coefficients of 0.80 and 0.88, respectively. Post-2021, there was a bolstered correlation between Na⁺ and SO₄²⁻ (coefficient: 0.81). Na⁺ and Ca²⁺ maintained their strong correlation with HCO₃⁻ and Cl⁻. Moreover, Mg²⁺ demonstrated strong correlations with HCO₃⁻, Cl⁻, and SO₄²⁻.

The majority of data points clustered around slope 1, suggesting a strong correlation between Na⁺ and Cl⁺ (Figure 7a). This correlation implies the dissolution of halite during the groundwater’s chemical composition formation (Equation (3)). However, some monitoring points deviated from slope 1, indicating that Na⁺ in the groundwater was not solely derived from halite [24]. Furthermore, since Na⁺ also exhibited a strong correlation with HCO₃⁻, the points positioned to the left of the 1:1 line might have been influenced by albite (Equation (4)). Conversely, the points located to the right of the 1:1 line might have been impacted by reverse cation exchange adsorption, which led to lower Na⁺ concentrations.

N a C l \to {N a}^{+} + {C l}^{-}

(3)

4 N a A l {S i}_{3} O_{8} + 4 {C O}_{2} + 22 H_{2} O = {A l}_{4} ({S i}_{4} O_{10}) + 8 H_{4} {S i O}_{4} + 4 {N a}^{+} + 4 {H C O}_{3}^{-}

(4)

Strong reverse cation exchange adsorption occurred in the groundwater, which resulted in an elevated concentration of Ca²⁺. The ratio of Ca²⁺ to HCO₃⁻ predominantly ranged between 2:1 and 1:1, and a minority fell between 1:1 and 1:2 (Figure 7b). Considering the prior analysis of the correlations between Ca²⁺, HCO₃⁻, Mg²⁺, and SO₄²⁻, this suggests a broad source for Ca²⁺. The Ca²⁺ concentration at monitoring points proximal to the 1:1 line might have been influenced by the dissolution of anorthite (Equation (5)) and minor amounts of gypsum (Equation (6)), while those between 1:1 and 1:2 might have been impacted by the dissolution of calcite (Equation (7)) and minor quantities of dolomite (Equation (8)) [20,25]. In 1980, the majority of Ca²⁺ + Mg²⁺-to-HCO₃⁻ ratios fell between 2:1 and 1:1 (Figure 7c), suggesting elevated Mg²⁺ concentrations, which were potentially influenced by human activities, such as agricultural activity. After 2015, most ratios shifted to or above the 2:1 line, which was possibly due to the rise in groundwater levels caused by the artificial governance. This rise led to the dissolution of magnesium fertilizers that accumulated in the strata over many years, which resulted in a sustained increase in Mg²⁺ concentrations. The ratio of Ca²⁺ + Mg²⁺-to-HCO₃⁻ + SO₄²⁻ predominantly exceeded 1:1 (Figure 7d). This ratio supported the hypothesis of magnesium fertilizer dissolution in the groundwater.

C a {A l}_{2} {S i}_{2} O_{8} + 2 {C O}_{2} + 8 H_{2} O \to {A l}_{2} O_{3} \cdot 3 H_{2} O + {C a}^{2 +} + 2 {H C O}_{3}^{-} + 4 H_{2} S i O_{4}^{2 -}

(5)

C a {S O}_{4} \cdot 2 H_{2} O \to {C a}^{2 +} + {S O}_{4}^{2 -} + 2 H_{2} O

(6)

C a {C O}_{3} + {C O}_{2} + H_{2} O \to {C a}^{2 +} + 2 {H C O}_{3}^{-}

(7)

C a M g {({C O}_{3})}_{2} + 2 {C O}_{2} + 2 H_{2} O \to {M g}^{2 +} + {C a}^{2 +} + 4 {H C O}_{3}^{-}

(8)

3.4. Inverse Hydrogeochemical Simulation

Drawing on the analysis of groundwater chemical component sources presented earlier, ten mineral phases that potentially contributed to the formation of these components were identified. The established reaction pathways (S84→S63, S85→S96) were subjected to hydrogeochemical modeling using the Phreeqc software (Figure 2), which facilitated a quantitative investigation into the mechanisms that drove the groundwater chemistry formation. In 1980, the mineral phases dissolved in the groundwater included albite, dolomite, halite, and quartz, while the mineral phases precipitated were calcite and gypsum (Table 2). Of these ten mineral phases, anorthite did not participate in the reaction. Groundwater exhibited reverse cation exchange, where 6.152 × 10⁻⁴ mmol/L of Ca²⁺ was dissolved from the aquifer medium into the groundwater, while 1.230 × 10⁻³ mmol/L of Na⁺ from the groundwater was adsorbed onto the aquifer medium. In 1980, halite exhibited the highest dissolution rate at 2.225 × 10⁻³ mmol/L, whereas albite showed the lowest at 7.420 × 10⁻⁷ mmol/L. The deposition rates of calcite and gypsum were comparable and measured at 2.318 × 10⁻⁴ mmol/L and 2.640 × 10⁻⁴ mmol/L, respectively.

In 2021, significant alterations occurred in the forms and extents of reactions that involved mineral phases in the groundwater. The minerals that dissolved included albite, calcite, and quartz, whereas those that precipitated were dolomite, gypsum, and halite. Among these mineral phases, anorthite remained unreactive. In 2021, groundwater exhibited positive cation exchange, where Na⁺ from the aquifer media dissolved at a rate of 1.456 × 10⁻³ mmol/L, and Ca²⁺ was adsorbed onto the aquifer media at 7.278 × 10⁻⁴ mmol/L. Calcite experienced the highest rate of dissolution at 1.105 × 10⁻³ mmol/L, whereas albite, although the least dissolved, showed an increase from its 1980 levels to 1.706 × 10⁻⁶ mmol/L. Gypsum recorded the highest precipitation rate in 2021, which increased to 7.201 × 10⁻⁴ mmol/L from 1980, while dolomite showed the lowest at 1.372 × 10⁻⁴ mmol/L. Between 1980 and 2021, the groundwater experienced substantial shifts in the mineral phases that reacted within it. Dolomite and halite transitioned from dissolution to precipitation, while calcite moved from precipitation to dissolution. Over this period, the groundwater chemical field underwent profound transformations.

4. Discussion

4.1. Influence of Groundwater Dynamic Field

In the study area, the terrain rose toward the northwest and declined toward the southeast. Correspondingly, the groundwater flow predominantly followed this topographical gradient (Figure 4). In 1980, excessive groundwater extraction led to the formation of a groundwater funnel in the southern part of the study area, where the groundwater converged. The artificial governance began in 2015. By 2021, the groundwater funnel had completely disappeared. However, due to the large amount of water consumption caused by urban expansion, and the upper reaches of the Hutuo River having been subjected to river regulation based on anti-seepage in recent years, this resulted in a smaller amount of river water infiltration recharge, and thus, the groundwater level near Huangbizhuang in the northwest declined (Figure 2c). From 1980 to 2015, the main area of groundwater exploitation was located in the middle of the study area. This kind of irregular mining made the groundwater level in the middle of the study area drop sharply, which led to the increase in the water head difference and the increase in the hydraulic gradient. After 2015, the artificial groundwater governance with the main measures of limiting the exploitation and artificial recharge of groundwater began to be implemented. The northern parts of the study area were the primary artificial recharge zones, which led to significant groundwater level increases in these regions. Conversely, the southern and eastern parts of the study area, which were characterized by high water consumption and challenges in artificial recharge, saw less significant groundwater level rises, where some areas experienced continued declines. Consequently, the hydraulic gradient continued to increase.

The main characteristic of the ion concentration in the groundwater was that it was low in the northwest and high in the southeast, which was similar to the characteristic of the groundwater flow direction. The underlying cause was that the northwest region was a groundwater recharge area. The groundwater flow rate was fast and the groundwater residence time was short. Therefore, the hydrochemical process was weak, which resulted in a low ion concentration. In contrast, the southeastern region was a groundwater discharge area, where the groundwater retention time was longer and the hydrochemical processes were more intense, which resulted in higher ion concentrations. By 1980, the southeastern region had become a groundwater funnel area, where the groundwater convergence led to ion accumulation and increased ion concentrations (Figure 4). Consequently, it was widely believed that ion concentrations were low in recharge areas and high in discharge areas [26]. The influence of the groundwater flow field on the groundwater chemical field was evident not only in the direction of the groundwater flow and the distribution of concentrations but also in the spatial distribution of changes in the groundwater levels and concentrations (Figure 8) [27]. In general, the western portion of the study area (including Qiaoxi District, Xinhua District, and Luquan District) was identified as an area that experienced rising groundwater levels and a primary locus of increasing ion concentrations. Conversely, the eastern sector (including Loudi Town, Yuhua District, Chang’an District, and Zhengding County) was classified as a region with declining groundwater levels and a primary locus of decreasing ion concentrations (Figure 4). When the groundwater level dropped, the contact area between the groundwater and the surrounding rock decreased, which weakened the water–rock interaction. This led to a decrease in the ion concentration of the main source of the water–rock interaction in the groundwater. The decrease in the groundwater level exposed the surrounding rock that was originally in contact with the groundwater. In 1980, the surrounding rock contacted by groundwater was mainly composed of mild clay and sandy silt. By 2021, it was fine sand and coarse sand with gravel (Figure 1b). The change in the surrounding rock affected the flow rate of the groundwater, and the existence of the groundwater funnel changed the flow direction of the groundwater. Thus, the order of reaction and contact time between the groundwater and surrounding rock changed, which resulted in the change in the chemical composition of the groundwater. When the groundwater table rose, so did the quantity of the groundwater. This increase enhanced the water–rock interactions due to a greater contact area of groundwater with the surrounding rock, and also influenced the flow velocity and residence time of the groundwater [28]. Furthermore, the augmented groundwater quantity promoted ion enrichment, which elevated the ion concentrations. Simultaneously, the groundwater levels were strongly positively correlated with the primary ions in the water (excluding SO₄²⁻ and Cl⁻). This correlation indicates that changes in the groundwater levels affected the concentrations of these main ions.

In summary, the direction of the groundwater flow was correlated with the spatial distribution of the major ion concentrations. This exhibited lower concentrations in the recharge zones and higher concentrations in the discharge zones. Changes in the groundwater levels and ion concentrations exhibited similarities, both quantitatively and spatially. An increase in the groundwater levels led to an increase in the ion concentrations.

4.2. Ion Sources and Hydrochemical Evolution

The Gibbs diagram delineates three distinct regions, with each representing a different controlling process in the origins of ions in groundwater: evaporation, water–rock interaction, and precipitation [29]. Water–rock interaction predominantly governed the origin of the major ions in the groundwater (Figure 5). Between 1980 and 2015, the groundwater depth increased to 40.65 m. Following the artificial governance in 2015, the groundwater depth experienced a partial recovery; however, the groundwater depth still exceeded 35 m by 2021 (Figure S5). An increased groundwater depth extended the precipitation’s infiltration path and diminished the influence of the evaporation and precipitation. As indicated by the rock-weathering end-member diagram, the primary sources of the ions were the dissolution and precipitation processes that involved silicate and carbonate rocks (Figure 5). The groundwater was subject to cation exchange, which decreased in intensity. This trend was likely associated with increases in the hydraulic gradient and the acceleration of the groundwater flow within the groundwater system. The Mg²⁺ concentrations were notably elevated, and a strong correlation existed between the Mg²⁺ and SO₄²⁻ concentrations, suggesting that the groundwater was influenced by the application of magnesium fertilizer. Since most of the land in the study area was agricultural land in the 1980s, a large amount of magnesium fertilizer was used in agricultural production. These magnesium fertilizers remained in the shallow layers. When the groundwater level rose, these residues were dissolved into the groundwater, and thus, showed a high correlation between Mg²⁺ and SO₄²⁻.

Following the artificial governance, the northern part of the study area initiated a pilot project to recharge groundwater via river water from the Hutuo River (Figure S6a). The surface water and reclaimed water brought by the South-to-North Water Diversion Project in China were injected into the Hutuo River channel to recharge the groundwater through the river channel. The ion contents in the South-to-North Water Diversion Project were generally lower than those of the groundwater in the study area (Table S1) [7]. This led to substantial quantities of river water entering and integrating with the aquifer. It was estimated that the infiltration of river water into groundwater in this segment of the river accounted for approximately 70–90% of the flow (Figure S6b) [7]. River water, which is characterized by its rapid flow, undergoes comparatively weak water–rock interactions, and is significantly affected by precipitation-induced dilution. As a result, the concentrations of key ions in river water are generally lower than those in groundwater. This mixing effect serves to decrease the concentration of certain ions within the groundwater, for instance, Na⁺ and Cl⁻.

The Phreeqc analysis revealed distinct differences in the hydrochemical evolution processes between 1980 and 2021, indicating a shift in the dominant factors over time (Table 2). The pronounced dissolution of halite primarily drove the increased concentrations of Na⁺ and Cl⁻ from 1980 to 2015. Concurrently, the dissolution of dolomite and reverse cation exchange predominantly contributed to the elevated levels of Ca²⁺ and Mg²⁺ during this period. Between 1980 and 2021, gypsum was consistently precipitated. However, the SO₄²⁻ concentrations persistently increased, which was likely due to human activities [30]. Despite the transition of dolomite from dissolution to precipitation, the Mg²⁺ levels continued to rise. The behaviors of Mg²⁺ and SO₄²⁻ could be attributed to increased groundwater levels and riverine recharge, which enhanced the dissolution and facilitated the dissolution of residual magnesium fertilizers into the groundwater. The dissolution of calcite was the primary controlling factor for the increase in the Ca²⁺ concentration in 2021, while halite precipitation was the primary reason for the decrease in the Na⁺ and Cl⁻ concentrations in the later period (after 2015).

In 1980, the chemical evolution of groundwater was predominantly influenced by water–rock interactions and human activities. Following artificial governance in 2015, the influence of mixing (dilution) increasingly became apparent. By 2021, the chemical evolution of the groundwater was influenced by several factors, including the water–rock interactions, mixing (dilution) effects, and human activities. In the water–rock interactions, the primary processes were the dissolution of silicates and carbonates and the alternating adsorption of cations. For the silicates, the dissolution of albite was dominant. In the carbonates, the dissolution of dolomite was prevalent in 1980, while by 2021, calcite dissolution had become the main process, which was coupled with the dominant reverse cation exchange.

4.3. Human Activities

After 2015, the artificial recharge of groundwater in the northern part of the study area increased the groundwater recharge. A large amount of surface water with low ion concentration infiltrated into the groundwater through the Hutuo River channel. This enhanced the leaching effect and increased the ion concentration. At the same time, the study area limited the exploitation of groundwater. This made the groundwater discharge conditions change, and the artificial discharge decreased significantly. The artificial governance increased the groundwater quantity and extended the retention time in the aquifer. This enhanced the water–rock reactions, which led to an expansion of the area with high ion concentration after the artificial treatment. This caused the area of high ion concentration to expand after the artificial governance. After the artificial recharge, the groundwater level was shallow, which made it more likely for major ions to penetrate the unconfined aquifer through the unsaturated zone, which also increased the ion concentrations. Therefore, after 2015, the concentrations of TDSs, HCO₃⁻, SO₄²⁻, Mg²⁺, Ca²⁺, and Na⁺ increased. And there were high correlations between Na⁺ and SO₄²⁻, Mg²⁺ and HCO₃⁻, Mg²⁺ and Cl⁻, and Mg²⁺ and SO₄²⁻ after the artificial treatment. This increase in ion concentrations that followed the artificial governance was also observed in the surrounding areas of the study region. In Hengshui City, Hebei Province, China, the ion concentrations also increased after the artificial management in 2014.

The intensity of human activities and water–rock interactions that affect the groundwater chemistry can be inferred from the relationship between the total dissolved solids (TDSs) and the ratio of (SO₄²⁻ + NO₃⁻ + Cl⁻) to (SO₄²⁻ + NO₃⁻ + Cl⁻ + HCO₃⁻). NO₃⁻ is employed as an indicator to assess the presence and magnitude of human activities that influence water quality [31]. The distribution of monitoring points in the direction of “Human activities” indicates the presence of human activities within the study area. Conversely, the alignment of monitoring points in the direction of “Water-rock interactions” suggests the occurrence of water–rock interactions within the study area (Figure S7). Groundwater-monitoring points were primarily distributed along the direction of “Human activities”. There was a significant influence of human activities on groundwater, with the impact of water–rock interactions being secondary. In 2015, while the monitoring points remained primarily distributed along the “Human activities” direction, the points distributed along the “Water-rock interactions” direction increased, suggesting a gradual rise in the influence of water–rock interactions. By 2021, the number of groundwater-monitoring points along the “Water-rock interactions” direction exceeded those in 2015, and most were also aligned with the “Human activities” direction. The distribution points were higher than those points in 1980 and 2015, indicating that in 2021, the combined impact of human activities and water–rock interactions on the groundwater chemistry was more pronounced than in previous years.

Human activities are categorized as industrial or agricultural based on the resultant ions (Figure S7). The period from 2015 to 2021 saw the predominance of industrial activity impacts, with a trend of continuous intensification. The study area’s land-use types also exhibited corresponding characteristics, with a continuous decline in arable land from 461.67 km² in 1985 to 265.85 km² in 2021. The extent of artificial surfaces expanded from 177.07 km² in 1985 to 376.97 km² in 2021 (Figure S8). The intensification of industrial activities and the difficulties in precipitation infiltration due to ground hardening influenced the evolution of the groundwater chemistry. Groundwater exploitation had a decreasing trend from 1980 to 2021 (Figure S9). Groundwater exploitation in 1980 was 39,741 × 10⁴ m³, and in 2021, it was 3935 × 10⁴ m³. Groundwater exploitation in 1980 was a major factor in the decline of groundwater levels and indirectly influenced the formation of the groundwater chemistry.

5. Conclusions

Over the 41-year period from 1980 to 2021, there were significant changes in human attitudes toward groundwater. These changes inevitably led to alterations in the hydrochemical field and the factors that controlled the evolution of the water chemistry. Qualitative and quantitative research was conducted on the hydrochemical characteristics and influencing factors of the groundwater funnel area of the Hutuo River alluvial fan in Shijiazhuang, North China. The following results were obtained:

(1): The ion concentrations gradually increased along the groundwater flow path and displayed a pattern of lower levels in the northwest and higher levels in the southeast. The spatial distribution of major ion concentrations in 1980 indicated a diverse spread. In 2021, the spatial distribution of major ion concentrations indicated a more uniform distribution. From 1980 to 2021, the concentrations of major ions increased.
(2): In 1980, the dominant cation in the groundwater was Ca²⁺, and the dominant anion was HCO₃⁻, where the hydrochemical type was primarily the HCO₃—Ca type. From 1980 to 2015, the concentrations of Cl⁻ and SO₄²⁻ increased, which rendered the hydrochemical type more complex and resulted in the formation of HCO₃·Cl—Ca, HCO₃—Ca·Mg, and HCO₃·SO₄—Ca types. Following artificial management, the groundwater level rose, which led to an increase in the concentrations of SO₄²⁻ and Mg²⁺. The implementation of artificial governance in 2015 resulted in the emergence of HCO₃·SO₄—Ca·Mg-type water. By 2021, this type of groundwater had become the predominant hydrochemical type.
(3): The groundwater flowed from northwest to southeast. The western region was an area of rising groundwater levels, while the eastern region experienced declining groundwater levels. Changes in the groundwater level and ion concentrations were strongly quantitatively correlated and exhibited spatial similarity. The evolution of the groundwater chemical components was predominantly influenced by fluctuations in the groundwater levels.
(4): In 1980s, the groundwater hydrochemical composition was primarily controlled by the dissolution of albite, dolomite, halite, and quartz; reverse cation exchange; and groundwater exploitation. Since 2015, the hydrochemical composition has been mainly influenced by the dissolution of albite, calcite, and quartz; positive cation exchange; river–groundwater mixing; and industrial activities, with an increasing intensity of both water–rock interactions and human activities.
(5): The water–rock interactions predominantly involved cation exchange and the dissolution of silicate and carbonate rocks, while human activities were mainly influenced by industrial activities.
(6): The hydrochemical evolution and formation mechanisms of the Hutuo River alluvial fan in 1980 and post-2015 were analyzed in this study. However, the hydrochemical evolution of groundwater between 1980 and 2015 was not analyzed. Future research could address this gap and extend the findings of this study to explore further aspects, such as the response mechanisms of groundwater chemical evolution. This study found that the concentrations of SO4^2- and Mg²⁺ in the groundwater increased following the artificial groundwater governance. This phenomenon was also observed in Hengshui City, Hebei Province, China, where similar governance practices were implemented [8]. Investigating the reasons for this occurrence will be a direction for future research.

Supplementary Materials

The following supporting information can be downloaded from https://www.mdpi.com/article/10.3390/w16162229/s1.

Author Contributions

Conceptualization, writing—original draft preparation, and formal analysis, J.G.; conceptualization and writing—review and editing, B.Y.; conceptualization and investigation, C.F.; data curation and investigation, Y.T.; data curation and investigation, M.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Youth Fund Project (42002251); Scientific Research Projects of the Higher University in Hebei (BJK2022007); Natural Science Foundation of Hebei Province (D2024403005); Hebei Key Laboratory of Geological Resources and Environmental Monitoring and Protection Fund (JCYKT202001); and Natural Science Funds Project in Hebei Province (D2020403022).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. (a) Distribution of the groundwater and precipitation monitoring points in the study area; (b) hydrogeologic profile along the I–I’ line.

Figure 2. Groundwater flow fields in 1980, 2015, and 2021.

Figure 3. (a) Duration curve of groundwater hydrochemical composition; (b) hydrochemical Piper plots of groundwater from 1980 to 2021.

Figure 4. Spatial distributions of major ions.

Figure 5. (a,b) Gibbs diagram of groundwater; (c,d) Diagram of relative contribution rate of rock weathering and dissolution.

Figure 6. Relationship between chloro–alkali index and TDSs.

Figure 7. (a) Ratio of Na⁺ to Cl⁻ in groundwater; (b) Ratio of Ca²⁺ to HCO₃⁻ in groundwater; (c) Ratio of Ca²⁺ + Mg²⁺ to HCO₃⁻ in groundwater; (d) Ratio of Ca²⁺ + Mg²⁺ to HCO₃⁻ + SO₄²⁻ in groundwater.

Figure 8. Comparison between the variation of groundwater level and ion concentration.

Table 1. Statistics of the groundwater hydrochemical components in the study area (1980–2021).

Item	Date	Minimum	Maximum	Mean	Median	Coefficient of Variation
Ca²⁺	1980	77.00	176.00	110.36	107.00	0.23
	2015	52.36	398.79	132.77	118.20	0.55
	2018	51.30	248.50	144.20	149.15	0.31
	2021	36.16	584.00	152.82	151.10	0.51
Mg²⁺	1980	14.00	46.00	26.39	25.00	0.28
	2015	7.33	102.22	35.70	33.30	0.57
	2018	8.75	59.30	36.29	35.61	0.35
	2021	10.01	192.00	41.13	40.02	0.27
Na⁺	1980	9.00	67.00	26.15	25.00	0.50
	2015	4.40	63.80	30.56	26.20	0.60
	2018	6.24	92.94	43.92	43.21	0.46
	2021	9.11	68.50	39.71	39.68	0.35
Cl⁻	1980	24.00	227.00	73.79	62.00	0.71
	2015	8.44	212.53	94.84	80.23	0.65
	2018	7.09	292.13	91.03	89.15	0.59
	2021	11.20	246.00	86.84	80.94	0.67
SO₄²⁻	1980	42.00	156.00	85.33	83.00	0.33
	2015	15.40	200.70	101.03	98.55	0.45
	2018	17.00	261.60	154.65	158.25	0.44
	2021	9.18	318.50	164.29	162.10	0.44
HCO₃⁻	1980	198.00	471.00	293.94	300.00	0.18
	2015	127.02	425.63	269.29	247.68	0.27
	2018	132.84	540.63	316.08	331.93	0.26
	2021	102.70	640.00	313.99	417.00	0.25
NO₃⁻	1980	\	\	\	\	\
	2015	1.56	103.63	41.68	33.57	0.65
	2018	0.68	148.81	37.36	20.65	1.05
	2021	0.81	44.47	16.65	16.33	0.61
TDSs	1980	186.00	632.00	428.27	408.00	0.25
	2015	233.38	1629.07	628.73	536.53	0.48
	2018	245.54	1255.12	718.75	727.23	0.31
	2021	161.00	1121.00	761.26	797.00	0.29

Note: “\” indicates no reaction.

Table 2. The result of inverse hydrogeochemical models (10⁻³ mmol/L).

Mineral Phase	1980	2021
Simulation path	S84→S63	S85→S96
Albite	+0.0007420	+0.001706
Anorthite	\	\
Calcite	−0.2318	+1.105
Dolomite	+0.4754	−0.1372
Gypsum	−0.2640	−0.7201
Halite	+2.225	−0.4434
Quartz	+0.07118	+0.04011
CaX2	+0.6152	−0.7278
NaX	−1.230	+1.456
CO₂ (g)	+1.464	+1.140

Note: “+” represents dissolution; “−“ represents precipitation; “\” indicates no reaction.

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Gai, J.; Yan, B.; Fan, C.; Tuo, Y.; Ma, M. Hydrochemical Evolution Process and Mechanism of Groundwater in the Hutuo River Alluvial Fan, North China. Water 2024, 16, 2229. https://doi.org/10.3390/w16162229

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Gai J, Yan B, Fan C, Tuo Y, Ma M. Hydrochemical Evolution Process and Mechanism of Groundwater in the Hutuo River Alluvial Fan, North China. Water. 2024; 16(16):2229. https://doi.org/10.3390/w16162229

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Gai, Junbai, Baizhong Yan, Chengbo Fan, Yapeng Tuo, and Miaomiao Ma. 2024. "Hydrochemical Evolution Process and Mechanism of Groundwater in the Hutuo River Alluvial Fan, North China" Water 16, no. 16: 2229. https://doi.org/10.3390/w16162229

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