Tracing Sulfate Sources of Surface Water and Groundwater in Liuyang River Basin Based on Hydrochemistry and Environmental Isotopes

Abstract

Sulfate as a potential pollution source in the water environment of the basin, identifying sulfate sources and migration mechanisms is essential for protecting the water environment and ensuring sustainable water management. Liuyang River is a primary tributary of the Xiangjiang River. It has experienced progressively intensifying anthropogenic influences in recent decades, manifested by sustained sulfate concentration increases. However, the sulfate sources and their contributions were not clear. This study used hydrochemistry and multi-isotopes methods combined with Simmr model to study the hydrochemical characteristics, sulfate sources, and migration–transformation processes of surface water and groundwater. The results showed that the hydrochemical types of surface water were HCO₃-Ca and HCO₃·SO₄-Ca·Mg, and groundwater were HCO₃-Ca, HCO₃-Ca·Mg, and HCO₃·SO₄-Ca. Ions in the water primarily originated from carbonate and silicate rocks dissolution and sulfide oxidation, augmented by mining operations, sewage discharge, and chemical production. The analyses of hydrochemistry, isotopes, and Simmr model revealed that surface water sulfate originated from soil sulfate (35.70%), sulfide oxidation (26.56%), sewage (16.58%), and atmospheric precipitation (12.45%). Groundwater sulfate was derived predominantly from sewage (34.96%), followed by soil sulfate (28.09%), atmospheric precipitation (17.35%), and sulfide oxidation (12.25%). Sulfate migration and transformation were controlled by the natural environment and anthropogenic impacts. When unaffected by human activities, sulfate mainly originated from soil and atmospheric precipitation, relating to topography, geological conditions, agricultural activities, and precipitation intensity. However, in regions with intense human activities, contributions from sewage and sulfide oxidation significantly increased due to the influences of mining and industrial activities.

1. Introduction

Surface water and groundwater in river basins serve as crucial water supply sources for human society and industrial-agricultural development, with their environmental quality being of paramount importance [1,2,3]. In recent decades, China’s rapid economic growth has substantially increased water demands for industrial manufacturing and agricultural production. This has exacerbated irrational exploitation of water resources, resulting in extensive contamination of surface water and groundwater while severely threatening water security and sustainable environmental development [4,5]. Dissolved sulfate (SO₄²⁻) is a key chemical component in water bodies that reflects water quality. Sulfate originates from natural sources (evaporite dissolution, sulfide oxidation, soil, seawater intrusion, and atmospheric precipitation) and anthropogenic pollutants (industrial and domestic sewage, agricultural fertilizers, and mining drainage) [6,7,8]. Variation in sulfate concentrations significantly impacts sulfur biogeochemical cycling, induces water acidification and acid rain formation [9,10,11], and generates toxic compounds (e.g., hydrogen sulfide) that endanger public health and water environment [12,13].

Due to the existence of multiple potential sources of sulfate, it is difficult to accurately distinguish the sources only by using conventional hydrochemical methods. For example, ion ratio relationships (e.g., SO₄²⁻/Cl⁻, SO₄²⁻/Ca²⁺) cannot accurately identify the influences of natural and anthropogenic factors on sulfate concentrations [14]. Sulfur isotope of sulfate (δ³⁴S_SO4) serves as a natural tracer for sulfate source identification, undergoing minimal isotopic fractionation during biogeochemical processes [15,16]. The values of δ³⁴S_SO4 in water preserve the inherent isotopic characteristics of their sources [17]. Therefore, δ³⁴S_SO4 is widely used to identify sulfate sources [18]. For instance, Han et al. applied δ³⁴S_SO4 to identify sulfate sources in the Daweijia area of Dalian, China, indicating fertilizers as primary sources in Quaternary groundwater [19]. However, overlapping δ³⁴S_SO4 ranges among different sources limit the accuracy of sulfate isotope tracing [20]. Zhang et al. utilized δ³⁴S_SO4 to trace sulfate sources in the Yiluo River, revealing overlapping isotopic ranges between gypsum and domestic sewage, which made these sources difficult to distinguish [21]. The value of δ¹⁸O_SO4 is related to the ratio of oxygen derived from water and oxygen [22,23]. Combining δ¹⁸O_SO4 with δ³⁴S_SO4 can resolve these limitations and significantly improves sulfate source identification accuracy [24]. For example, Otero et al. applied δ³⁴S_SO4 and δ¹⁸O_SO4 to groundwater in the Llobregat potash mining basin, identifying potassium fertilizers production and mine tailing drainage as predominant sulfate sources [25]. This dual-isotope approach has been extensively employed to investigate sulfate sources and migration processes in water environment [26,27].

The Liuyang River, a primary tributary of the Xiangjiang River, holds exceptional significance for regional water supply. The basin features fireworks manufacturing, and mining and agricultural activities are also active. Surface water and groundwater receive sulfate inputs from both natural processes and anthropogenic activities, with sulfate concentrations demonstrating significant influence from mining, industrial production, and agricultural activities [28]. However, few studies have addressed sulfate source tracing in the Liuyang River Basin, and pollution sources and contributions of sulfate remain unclear. To address these challenges, surface water and groundwater samples were collected from the Liuyang River Basin. Hydrochemistry combined with multi-isotopes (δ³⁴S_SO4, δ¹⁸O_SO4, δD_H2O, δ¹⁸O_H2O) was employed to identify various sources of sulfate. The Stable Isotope Mixing Models in R (Simmr) was utilized to quantify contributions from different sources of sulfate. Sulfate migration–transformation was elucidated based on topography, land use types, and geological conditions. This study comprehensively revealed the impacts of human activities and natural processes on sulfate in water bodies. It is of great significance for the environmental protection and the sustainable utilization of water resources in the basin. By identifying sulfate sources, contributions and migration-transformation processes via hydrochemical-isotopic approaches, this research provides a scientific basis for water pollution prevention and management in the basin.

2. Materials and Methods

2.1. Study Area

The Liuyang River Basin is situated in eastern Hunan Province, China. Its trunk stream (the Liuyang River) serves as a primary tributary of the Xiangjiang River. Originating from the northern foothills of Dawei Mountain within the Luoxiao Mountain Range, the Liuyang River extends 234.8 km in total length and drains a catchment area of 4665 km². The basin exhibits diverse geomorphological features, characterized by a northeast to southwest topographic gradient. The upstream, spanning from Shuangjiangkou to eastern of Daweishan Town, features mountainous terrain. The midstream, extending from Shuangjiangkou to Zhentou Town, transitions to hilly landscapes, while the downstream (west of Zhentou Town) comprises extensive alluvial plains. There are also larger tributaries, such as Xiaoxi River and Jianjiang River developed within the basin. Climatically classified as a subtropical monsoon zone, the basin receives a multi-year average precipitation of 1345.7 mm, 47.7% of which occurs from May to July.

The Liuyang River Basin exposes relatively complete stratigraphy, spanning from the Pre-Sinian to Quaternary. The oldest units comprise the Pre-Sinian Banxi and Lengjiaxi Groups, consisting of metamorphic rocks that extensively outcrop in the study area. Clastic rocks of Devonian, Cretaceous, and Paleogene are predominantly distributed in the downstream. Carboniferous-Permian carbonate rocks occur along the Xiaoxi River, and Liuyang River upstream and downstream. Quaternary unconsolidated deposits concentrate along the river valley in the upstream and downstream. Limited exposures of Yanshanian magmatic rocks, primarily acidic and intermediate-acidic lithology, are localized in the headwater of Liuyang River and Xiaoxi River.

Within the basin, groundwater is classified into four aquifer types by aquifer media: weathered fissure water in metamorphic rocks, weathered fissure water in clastic rocks, karst water in carbonate rocks, and pore water in Quaternary unconsolidated deposits. weathered fissure water is widely distributed in the study area. Quaternary pore water is distributed along the surface water, while karst water predominantly emerges in the upstream and midstream. Groundwater recharge modes include atmospheric precipitation infiltration, recharge from surface water percolation, and lateral inflow from adjacent aquifers. Regionally, groundwater flows along a NE-SW direction (Figure 1).

2.2. Sample Collection and Analysis

Surface water and groundwater samples were collected in the study area in November 2023 (Figure 1). Surface water sampling adhered to the following principles: sampling points were evenly distributed along the river course with additional sites at tributaries-trunk stream confluences; all surface water samples (n = 28) were collected from mid-channel locations, including 21 from the trunk stream, 3 from Xiaoxi River, 3 from Jianjiang River, and 1 from Unnamed River. Groundwater samples were sourced from wells (n = 17) proximate to surface water sites, extracted from shallow aquifers. During sampling, a multiparameter water quality probe (Eureka Manta+30, Austin, TX, USA) recorded in situ measurements of pH, dissolved oxygen (DO), electrical conductivity (EC), and oxidation-reduction potential (ORP).

Anion, cation, and water stable isotope (δD_H2O, δ¹⁸O_H2O) samples were stored in 50 mL amber high-density polyethylene (HDPE) bottles. Samples for the analysis of δ³⁴S_SO4 and δ¹⁸O_SO4 were collected in 1.5 L amber HDPE bottles. All samples were filtered through 0.45 μm cellulose acetate membranes prior to preservation. Cation samples were acidified with 2–4 mL ultrapure HNO₃ to pH < 2, anion samples were sealed unpreserved and refrigerated at 4 °C. Sulfate isotope samples were acidified with 1 mL ultrapure HCl to pH <2 in the laboratory, followed by supersaturated BaCl₂ addition to convert dissolved SO₄²⁻ to BaSO₄. The precipitate was rinsed with deionized water to remove Cl⁻, filtered through 0.22 μm membranes, and dried at 850 °C for 2 h in a muffle furnace.

Figure 1. Hydrogeological conditions and distribution of sampling sites in the study area.

Figure 1. Hydrogeological conditions and distribution of sampling sites in the study area.

The concentrations of HCO₃⁻ were determined via titration, while other anions were analyzed using ion chromatography (Dionex ICS-3000, Sunnyvale, CA, USA). Cation concentrations were quantified through inductively coupled plasma optical emission spectrometry (Thermo ICAP-6300, Waltham, MA, USA), achieving measurement precision better than 2%. Total dissolved solids (TDS) were measured gravimetrically by drying and weighing. δD_H2O and δ¹⁸O_H2O were analyzed using a laser-based liquid water isotope analyzer (IWA-35EP, LICA United Technology Co. Ltd., Beijing, China), with analytical precisions surpassing 0.1‰ and 0.5‰, respectively. δ³⁴S_SO4 and δ¹⁸O_SO4 were determined via gas-source isotope ratio mass spectrometry (Thermo Delta V Advantage, Waltham, MA, USA and MAT253, Jacksonville, FL, USA), attaining precisions better than 0.2‰ and 0.5‰. All analyses were conducted at the laboratory in Wuhan Center of China Geological Survey.

2.3. The Stable Isotope Mixing Models in R (Simmr)

Simmr, a Bayesian mixing framework based on Dirichlet distributions, employs probabilistic source apportionment through R implementation to quantify proportional contributions of multiple sulfate sources [29]. Unlike conventional linear mixing models requiring fixed end-member mean values, Simmr inputs end-member ranges, thereby enhancing analytical capability for complex source mixtures. The model structure is formally expressed as

$$X_{\mathit{ij}}=\sum _{k=1}^k{P}_k\left(S_{\mathit{jk}}+C_{\mathit{jk}}\right)+{\epsilon }_{\mathit{ij}}$$

(1)

$$S_{\mathit{jk}}~N\left({\mu }_{\mathit{jk}},{\omega }_{\mathit{jk}}^{\mathit{2}}\right)$$

(2)

$$C_{\mathit{jk}}~N\left({\lambda }_{\mathit{jk}},{\tau }_{\mathit{jk}}^{\mathit{2}}\right)$$

(3)

$${\epsilon }_{\mathit{ij}}~N\left(0,{\sigma }_j^{\mathit{2}}\right)$$

(4)

where X_ij is the isotopic value j of sample i (j = δ³⁴S_SO4 and δ¹⁸O_SO4 in this study). S_jk is the isotopic value j of source k, characterized by its mean μ_jk and standard deviation ω²_jk. P_k quantifies the proportional contribution of source k (k is potential source of sulfate). C_jk, the isotopic fractionation factor for the isotope j in source k, is defined by its mean λ_jk and standard deviation τ²_jk, this term may be disregarded when significant isotopic fractionation is absent. The residual error ε_ij, with a mean of 0 and standard deviation of σ²_j, accounts for unquantified variability in sample i.

3. Results and Discussion

3.1. Hydrochemical Characteristics

3.1.1. Hydrochemical Compositions and Types

The TDS values in surface water ranged from 48.70 to 262.00 mg·L⁻¹, with an average of 134.45 mg·L⁻¹. The EC values varied between 75.00 and 518.20 μS·cm⁻¹, averaging 281.47 μS·cm⁻¹. Groundwater exhibited higher TDS (186.07 mg·L⁻¹) and EC (351.79 μS·cm⁻¹) compared to surface water, suggesting more intensive water-rock interactions (

Table 1. Statistics of the main hydrochemistry indexes in water bodies of the study area.

	Statistic	TDS	EC	K+	Na+	Ca2+	Mg2+	HCO3−	SO42−	Cl−	NO3−
		mg·L−1	μS·cm−1	mg·L−1
Surface water	Max	262	518.20	7.01	22.30	55.90	8.83	111	76.70	36	21.80
	Min	48.70	75	1.85	3.01	5.30	1.75	34	4.42	1.87	1.58
	Mean	134.45	281.47	4.34	11.99	22.99	5.13	76.23	19.06	17.15	8.70
Groundwater	Max	413	759.90	7.34	22.60	103	24.80	312	58.50	28.50	89.20
	Min	52.90	86.80	0.74	4.73	2.74	1.90	19.60	0.81	3.92	0.66
	Mean	186.07	351.79	2.40	10.86	34.47	9.79	114.70	18.75	14.07	26.45

). The maximum, minimum, and average concentrations of cations and anions are shown in Table 1. In surface water, average concentrations of cations were manifested as Ca²⁺ > Na⁺ > Mg²⁺ > K⁺, while anions followed the concentration gradient: HCO₃⁻ > SO₄²⁻ > Cl⁻ > NO₃⁻. In groundwater, Ca²⁺ and HCO₃⁻ exhibit the highest average concentrations, followed by Na⁺, Mg²⁺, SO₄²⁻, and NO₃⁻, K⁺, and Cl⁻ having the lowest concentrations. Along the flow path, surface water showed a gradually increase trend in both cation and anion concentrations. In the upstream, Ca²⁺, HCO₃⁻, and SO₄²⁻ of groundwater exhibited higher concentrations than the midstream and downstream. K⁺ concentrations remained relatively stable spatially. Na⁺, Mg²⁺, Cl⁻, and NO₃⁻ concentrations showed an initial increase followed by a gradual decrease.

Ions in the surface water and groundwater were dominated by HCO₃⁻and Ca²⁺. Hydrochemical types of surface water in the upstream were primarily HCO₃-Ca, transitioning to mixed HCO₃·Cl-Ca·Na and HCO₃·SO₄-Ca·Mg in the midstream, and finally to HCO₃·Cl-Ca·Na in the downstream. Hydrochemical types in groundwater were more complex. The upstream included HCO₃-Ca and HCO₃·SO₄-Ca types; the midstream and downstream were dominated by HCO₃-Ca·Mg type with minor HCO₃·SO₄-Ca type, some samples showed elevated Na⁺, SO₄²⁻, and Cl⁻. Specifically, SO₄² was the dominant anion in sample S28. Samples S5, G3 (located downstream of mine) and G5, S12 (near Liuyang city) displayed a HCO₃·SO₄-Ca type, indicating the effluents from mining activities and industrial sewage (Figure 2).

3.1.2. Sulfate Characteristics

The sulfate concentrations in surface water ranged from 4.41 to 76.70 mg·L⁻¹, with an average of 19.06 mg·L⁻¹. Historical data from three key monitoring sections in the Liuyang River Basin (Huanghuadong, Xiaoxi, and Sanshuichang) showed average sulfate concentrations of 5.98 mg·L⁻¹, 7.58 mg·L⁻¹, and 2.50 mg·L⁻¹, respectively [30]. It indicates a rising trend in recent years, likely linked to intensified human activities. Spatially, surface water in the upstream exhibited the widest sulfate variability (4.41–37.20 mg·L⁻¹), followed by midstream (17.20–32.60 mg·L⁻¹) and downstream (17.90–19.30 mg·L⁻¹). Notably, sulfate levels in Xiaoxi River (5.86 mg·L⁻¹) and Jianjiang River (12.93 mg·L⁻¹) were significantly lower than in the trunk stream, while the unnamed river showed an exceptionally high concentration of 76.70 mg·L⁻¹. Pronounced variation in the upstream suggests multiple sulfate sources, whereas the minimal fluctuation of downstream implies dominance by a single source. Groundwater sulfate concentrations (0.81–58.50 mg·L⁻¹) were slightly lower than those in the surface water. In the upstream, groundwater exhibited higher sulfate levels (23.29 mg·L⁻¹) compared to midstream (19.48 mg·L⁻¹) and downstream (14.86 mg·L⁻¹), with a gradual decline along the flow path (Figure 3).

For surface water, the minimum sulfate concentration (4.41 mg·L⁻¹) was recorded at the headwater site (S1), attributable to its location in a granite-dominated area with minimal human activity and limited sulfate inputs. In contrast, the maximum sulfate concentration (76.70 mg·L⁻¹) was found in an unnamed river (S28), likely due to industrial sewage discharge with high sulfate concentrations in the upstream of this river. Along the flow path, sulfate concentrations initially increased, then slightly decreased and stabilized. This pattern is linked to mining drainage in the upstream and sewage discharge in the midstream urban areas [31,32]. In groundwater, the lowest sulfate concentration (0.81 mg·L⁻¹) occurred northwest of Zhentou Town (G12), potentially resulting from dilution or bacterial sulfate reduction (BSR) [33]. The highest concentration (58.50 mg·L⁻¹) was detected in Liuyang city (G5), likely influenced by urban industrial effluents and mining drainage. Compared to surface water, groundwater sulfate concentrations exhibited a broader variation range, reflecting the control of complex lithology and hydrogeological conditions (Figure 4).

3.2. Hydrochemical Analysis of Sulfate Sources

Gibbs diagram is a tool for preliminary analysis of hydrochemical controls by rock weathering, precipitation, and evaporation [34]. All surface water samples in the study area fall within the rock-dominated field, distant from the evaporation and precipitation dominance fields. This indicates that the hydrochemical composition of surface water is primarily governed by rock weathering processes. For groundwater, most samples cluster in the rock-dominated domain, with a few approaching the precipitation dominance field. This distribution suggests that water–rock interactions dominate groundwater chemistry, and some groundwater is affected by atmospheric precipitation (Figure 5).

To further distinguish different types of water–rock interactions, Gaillardet et al. delineated typical HCO₃⁻/Na⁺ and Ca²⁺/Na⁺ ratio ranges for carbonate rocks, silicate rocks, and evaporites [35]. In the study area, surface water samples plot between the silicate and carbonate rocks end members, positioned closer to the silicate domain. Groundwater samples also fall within the silicate–carbonate transition zone but exhibit stronger influence from carbonate dissolution. Evaporite dissolution shows a negligible impact on the hydrochemical characteristics in the study area (Figure 6). Along the flow path, samples S1–S2 and G1–G2 plot near the silicate dissolution end member, while S3–S12 and G3–G6 occupy intermediate positions between silicate and carbonate domains, reflecting increased carbonate dissolution effects. Subsequently, both surface water and groundwater gradually shift back toward silicate-dominated signatures, consistent with the exposed lithology of the basin.

Water–rock interactions serve as a significant source of sulfate in water bodies. Analyzing ionic ratios associated with these processes enables identification of sulfate sources [36]. Water–rock interactions associated with sulfate primarily involve the dissolution of evaporite such as gypsum (CaSO₄·2H₂O) and mirabilite (Na₂SO₄·10H₂O), and the oxidation of sulfide including pyrite (FeS₂) [37]. As observed in Figure 7a, all surface water and groundwater samples plot above the gypsum dissolution line, with groundwater samples positioned farther from this line than surface water. This indicates limited Ca²⁺ and SO₄²⁻ contributions from gypsum dissolution, and there are other Ca²⁺ and SO₄²⁻ sources in the water bodies. Most water samples in the study area plot between the calcite (CaCO₃) and dolomite (CaMg(CO₃)₂) dissolution lines (Figure 7b), implying Ca²⁺ and HCO₃⁻ predominantly originate from the dissolution of calcite and dolomite. Individual samples plotting above the calcite dissolution line may be attributed to gypsum dissolution, sulfuric acid-induced carbonate dissolution, or cation exchange processes. The milligram equivalent ratio of [SO₄²⁻] + [HCO₃⁻] and [Ca²⁺] + [Mg²⁺] provide preliminary evidence for sulfuric acid involvement in rock weathering [38]. A 1:1 ratio indicates the dissolution of carbonate rocks by sulfuric acid. Most surface water and groundwater samples align along the 1:1 line (Figure 7c), suggesting combined weathering effects from both carbonic acid and sulfuric acid. Groundwater samples in the middle and lower reaches plot below this line are due to reverse cation exchange processes or Ca-Mg silicate minerals dissolution. Figure 7d reveals a scattered distribution of samples across the mirabilite dissolution line, with no significant correlation between Na⁺ and SO₄²⁻ concentrations, only individual surface water samples in the tributary plot near the mirabilite dissolution line. These findings suggest negligible contributions from mirabilite dissolution to sulfate in the basin.

The study area’s stratigraphy contains abundant pyrite. Mining activities expose pyrite to the atmosphere, generating sulfate and H⁺ through oxidation processes. Water polluted by pyrite leachate shows elevated SO₄²⁻, TDS, total hardness (TH) and Fe²⁺ coupled with depressed pH [39]. Sulfuric acid derived from sulfide oxidation further accelerates carbonate weathering, establishing correlations between SO₄²⁻ and Mg²⁺/Ca²⁺ ratios. Surface water exhibits strong positive correlations between SO₄²⁻ and both TDS (R² = 0.83) and TH (R² = 0.82) (p < 0.01), while weaker associations are observed in groundwater (Figure 7e,f). Sample S4, affected by mine drainage in Qibaoshan mining area, exhibited abrupt increases in SO₄²⁻, TDS, and TH compared to sample S3 in the upstream. As the Jianjiang River (S19–S21) receives discharge from Guanzhuang mining area, its hydrochemical characteristics showed depressed pH values (mean 6.9) and elevated Fe²⁺ concentrations (0.06 mg·L⁻¹) compared to other samples. Furthermore, surface water samples exhibit strong negative correlations between SO₄²⁻ and Mg²⁺/Ca²⁺ ratios (R² = 0.76), contrasted with moderate correlations in groundwater (R² = 0.41) (Figure 7g). These findings indicate sulfide oxidation as the predominant source of sulfate, exerting more significant impact on surface water than groundwater.

Anthropogenic activities significantly influence sulfate concentrations in both surface water and groundwater. Primary anthropogenic sources include industrial and domestic sewage, agricultural activities, and mining drainage. The SO₄²⁻/Ca²⁺ and NO₃⁻/Ca²⁺ ratios serve as effective tracers for distinguishing impacts from diverse human activities on hydrochemical characteristics [40,41]. As shown in Figure 7h, all surface water samples plot below the 1:1 line, with SO₄²⁻/Ca²⁺ ratios exceeding NO₃⁻/Ca²⁺ ratios, indicating that mining activities have a significant impact on sulfate concentrations in surface water. This effect was particularly pronounced at sites S5–S7 and S19–S21 due to direct drainage inputs from Qibaoshan and Guanzhuang mining areas. Conversely, groundwater in the mid-lower reaches predominantly clusters above the 1:1 line. This indicates the influences of agricultural activities and sewage, related to the dense town and farmland in the mid-lower reaches. Some groundwater samples (G2–G4) are located below the 1:1 line, as is related to their proximity to the mining area.

The analysis of SO₄²⁻/Cl⁻ ratios and Cl⁻ concentrations provides evidence for anthropogenic sulfate source identification. Sulfur fertilizers application elevates SO₄²⁻/Cl⁻ ratios with depressed Cl⁻ levels, whereas mining activities induce high SO₄²⁻/Cl⁻ ratios without significant Cl⁻ variation. Sewage inputs typically manifest as Cl⁻ enrichment with reduced SO₄²⁻/Cl⁻ ratios, while low values in SO₄²⁻/Cl⁻ ratios and Cl⁻ concentrations indicate natural source like soil or precipitation [42]. Figure 7i reveals concurrent influences from soil sulfate, mining activities, and sewage, with sulfur fertilizers demonstrating negligible impact. Surface water in the upper reaches, Xiaoxi River, and Jianjiang River exhibited dual control by soil sulfate and mining-derived inputs. Soil sulfate and sewage influences increased in the middle and lower reaches. Groundwater was predominantly influenced by sewage infiltration and soil, with mining-impacted exceptions at samples G3–G4.

3.3. Isotopic Analysis of Sulfate Sources

3.3.1. Analysis of Hydrogen and Oxygen Isotopes

δD and δ¹⁸O isotopes in water bodies serve as effective tracers for identifying recharge sources and hydraulic connectivity between surface water and groundwater, while also indicating atmospheric precipitation influences on sulfate [43,44]. Surface water in the study area exhibited δD and δ¹⁸O ranges of −47.86‰ to −31.60‰ and −7.44‰ to −5.16‰, averaging −36.25‰ and −5.77‰, respectively. Spatially, upper, middle, and lower reaches along with tributaries demonstrated diverse isotopic compositions, with average δD values of −34.63‰, −34.88‰, −33.59‰, and −41.99‰, and corresponding δ¹⁸O values of −5.74‰, −5.51‰, −5.26‰ and −6.47‰. The δD values of groundwater samples ranged from −47.86‰ to −31.60‰, with an average of −32.03‰, while the δ¹⁸O values ranged from −7.44‰ to −5.16‰, averaging −5.52‰. Spatially, upstream, midstream, and downstream exhibited average δD values of −31.39‰, −32.41‰ and −32.31‰, with corresponding δ¹⁸O average of −5.59‰, −5.49‰ and −5.47‰, respectively (

Table 2. Isotopic compositions of δD and δ¹⁸O in water bodies of the study area.

	Statistic	Surface Water				Groundwater
		Upstream	Midstream	Downstream	Tributaries	Upstream	Midstream	Downstream
δD (%)	Max	−32.05	−31.60	−33.28	−35.85	−29.55	−28.09	−29.39
	Min	−37.02	−38.55	−34.07	−47.86	−33.13	−38.02	−34.52
	Mean	−34.63	−34.88	−33.59	−41.99	−31.39	−32.41	−32.31
δ18O (%)	Max	−5.20	−5.16	−5.19	−5.91	−5.38	−4.67	−4.32
	Min	−6.27	−6.08	−5.35	−7.44	−5.91	−6.57	−6.50
	Mean	−5.74	−5.51	−5.26	−6.47	−5.59	−5.49	−5.47

).

Due to the lack of local precipitation isotope values, Changsha’s meteoric water line (LMWL: δD = 8.44δ¹⁸O + 15.01 [45]) was adopted as the regional reference. The global meteoric water line (GMWL) is defined as δD = 8δ¹⁸O + 10. Surface water and groundwater samples exhibit significant linear correlations between δD and δ¹⁸O. Surface water predominantly plot along the GMWL with minor deviations toward the lower right of the LMWL, implying atmospheric precipitation recharge and limited evaporation. Most groundwater samples were near the LMWL, indicating the recharge from atmospheric precipitation. Samples in the downstream show a deviation relative to the LMWL, and a δ¹⁸O drift phenomenon exists, suggesting the influence of water–rock interactions and evaporation (Figure 8a). The relationship of δ¹⁸O and Cl⁻ can indicate the intensity of evaporation [46]. Figure 8b reveals weak positive correlations between Cl⁻ concentrations and δ¹⁸O values, indicating that evaporation effects were limited.

Hydraulic connectivity exists between surface water and groundwater in the upper, middle, and lower reaches. Groundwater in the downstream exhibited significantly enriched δD and δ¹⁸O values relative to mid-upper reaches, suggesting limited hydraulic connectivity with midstream and upstream. Surface water in the upstream exhibited more depleted isotopic signatures than adjacent groundwater, with progressive enrichment along the runoff path. This indicates that groundwater recharges to surface water in the upstream. Sample G5 in the midstream demonstrated marked isotopic enrichment relative to nearby samples S11–S13, revealing poor hydraulic connection. Conversely, isotopic similarities between samples S14–S18 and G6–G10 expressed active surface water-groundwater exchange. In the downstream, surface water exhibited minimal isotopic variation, while groundwater displayed progressive δD and δ¹⁸O enrichment, reflecting weak hydraulic connectivity (Figure 8a).

3.3.2. Sulfur and Oxygen Isotopic Composition of Sulfate

The δ³⁴S_SO4 and δ¹⁸O_SO4 values of surface water ranged from 1.70‰ to 7.43‰ and 1.89‰ to 7.92‰, with average values of 5.28‰ and 4.12‰, respectively. In the upper reaches, δ³⁴S_SO4 and δ¹⁸O_SO4 values spanned 2.82–7.43‰ and 2.78–6.49‰, averaging 4.84‰ and 4.65‰. Midstream samples exhibited δ³⁴S_SO4 values of 1.70–7.01‰ (mean: 5.14‰) and δ¹⁸O_SO4 values of 1.89–5.66‰ (mean: 3.65‰). Downstream water showed δ³⁴S_SO4 values of 5.57–6.52‰ and δ¹⁸O_SO4 values of 3.27–7.92‰, with averages of 6.32‰ and 4.18‰. Spatially, δ³⁴S_SO4 exhibited an overall increasing trend during the runoff process, contrasting with the decreasing pattern observed for δ¹⁸O_SO4.

Groundwater exhibited higher δ³⁴S_SO4 (2.84–9.01‰) and δ¹⁸O_SO4 (2.30–8.60‰) values compared to surface water. Upstream samples showed δ³⁴S_SO4 values of 6.19–8.38‰ and δ¹⁸O_SO4 values of 2.30–7.86‰, with averages of 6.97‰ and 5.24‰. In the middle reaches, δ³⁴S_SO4 and δ¹⁸O_SO4 values spanned 6.59–8.66‰ and 5.02–8.60‰, averaging 7.27‰ and 6.45‰. The δ³⁴S_SO4 and δ¹⁸O_SO4 values of downstream samples ranged from 2.84‰ to 9.01‰ and 3.62‰ to 8.28‰, with average values of 6.24‰ and 6.79‰, respectively. Spatially, δ³⁴S_SO4 displayed a gradual decrease contrasting with the increasing δ¹⁸O_SO4 trend, demonstrating inverse variation pattern relative to surface water (Figure 9).

3.3.3. Analysis of Sulfur and Oxygen Isotopes

Sulfate undergoes significant isotopic fractionation predominantly during BSR process, which decreases sulfate concentrations while enriching δ³⁴S_SO4 and δ¹⁸O_SO4 values [47]. Other biogeochemical pathways exhibit minimal fractionation effects. Consequently, sulfate from distinct sources demonstrates characteristic δ³⁴S_SO4 and δ¹⁸O_SO4 signature ranges (

Table 3. Characteristics of δ³⁴S_SO4 and δ¹⁸O_SO4 from different potential sources.

Sources	δ34SSO4 (‰)		δ18OSO4 (‰)		Reference
	Average	Standard Deviation	Average	Standard Deviation
Atmospheric precipitation	5.90	1.80	9.40	1.64	[48]
Soil sulfate	5.48	1.99	3.66	2.78	[48]
Sulfide oxidation	−0.10	4.90	−0.50	3.03	[32]
Sewage	8.70	2.40	6.86	1.60	[47]
Evaporite	22.50	7.50	14.00	1.00	[49]
Chemical fertilizers	2.30	7.70	16.10	4.00	[50]

).

Surface water and groundwater in the study area show no significant correlation between δ³⁴S_SO4 and 1/SO₄²⁻, with most samples outside the BSR-dominated field. This indicates minimal influence of BSR process on δ³⁴S_SO4 and δ¹⁸O_SO4 values, and suggests multiple sources contributing to sulfate. Most samples predominantly fall within soil sulfate and sewage end members, with some falling into sulfide oxidation and atmospheric precipitation domains. This reveals soil sulfate and sewage as primary sulfate sources, alongside sulfide oxidation and atmospheric inputs. The absence of samples in the evaporite range shows that few sulfate inputs derive from evaporite dissolution. No water samples fall within the fertilizer end member, as is related to the predominant use of nitrogen fertilizers in the basin (Figure 10a,b).

Sulfate in surface water was primarily derived from multiple sources, including soil, sulfide oxidation, sewage, and atmospheric precipitation (Figure 10b). Upstream samples (S4, S5) and Jianjiang River samples (S19–S21) plot in the upper-right quadrant of the sulfide oxidation end member. This indicates that sulfide oxidation dominates sulfate contributions in these water samples, accompanied by soil sulfate or sewage inputs. Sample S28, located in an unnamed river, exhibited the highest sulfate concentration (76 mg·L⁻¹) and δ¹⁸O_SO4 value (7.92‰) among surface water. This suggests sewage as the primary sulfate source, with additional contributions from precipitation and soil. Samples in the downstream showed minimal variation in δ³⁴S_SO4 and δ¹⁸O_SO4 values, with isotopic compositions closely matching soil sulfate, confirming soil as the predominant sulfate source in these samples.

Groundwater shared similar sulfate sources with surface water. Its higher δ³⁴S_SO4 and δ¹⁸O_SO4 values relative to surface water indicate reduced sulfide oxidation and soil but increased sewage and precipitation inputs on sulfate concentrations (Figure 10b). Specifically, sample G5 exhibited high sulfate concentration, δ³⁴S_SO4 and δ¹⁸O_SO4 values, attributable to municipal sewage inputs within Liuyang city. Samples G10 and G17 from open dug wells showed significantly enriched δ¹⁸O_SO4, indicating inputs from direct atmospheric precipitation. Sample G14 displayed abrupt sulfate concentration increases with depleted δ³⁴S_SO4 and δ¹⁸O_SO4 values relative to adjacent samples, suggesting anthropogenic sulfide inputs like coal combustion.

The relationship between δ¹⁸O_H2O and δ¹⁸O_SO4 provides further validation of sulfide oxidation impacts on sulfate in water bodies [51]. Existing studies demonstrated that >50% of oxygen in sulfate derived from sulfide oxidation originates from water [52,53]. Most surface water samples in the study area plot below the 50%H₂O reference line, indicating >50% oxygen derivation from water and confirming sulfide oxidation as the dominant sulfate source (Figure 10c). Exceptions include samples S1–S3 and tributary sample S28, which plot above the 50%H₂O line, showing limited sulfide oxidation contributions due to absence of a mine drainage recharge. Groundwater samples predominantly plot above the 50%H₂O line, suggesting limited sulfide oxidation influence (Figure 10c). Affected by mine drainage, there were obvious contributions from sulfide oxidation in samples G3 and G4.

Balci et al. obtained the upper (δ¹⁸O_SO4 = 0.62δ¹⁸O_H2O + 9) and lower (δ¹⁸O_SO4 = δ¹⁸O_H2O) limit equations of sulfide oxidation through experiments [54]. Figure 10d shows that most surface water samples fall inside the sulfide oxidation domain, whereas most groundwater resided outside this range. This result is consistent with the analysis of Figure 10c. Furthermore, Δδ¹⁸O (δ¹⁸O_SO4 − δ¹⁸O_H2O) > 8‰ typically indicates active sulfide oxidation [55]. Surface water and groundwater in the study area exhibited average Δδ¹⁸O values of 9.90‰ and 11.62‰, respectively, reaffirming sulfide oxidation as a major sulfate source in water bodies.

3.3.4. Sulfate Contributions from Different Sources

The preceding analysis of sulfate sources and biogeochemical processes showed that sulfate in the study area was derived from multiple sources. Soil sulfate, sewage discharge, sulfide oxidation, and atmospheric precipitation were the main sources, and minimal contributions originated from evaporites and fertilizers. Given the absence of pronounced BSR effects and negligible isotopic fractionation, the Simmr was employed to quantify different source contributions of sulfate in surface water and groundwater [56].

Quantitative analysis revealed marked spatial heterogeneity in sulfate contributions from different sources of surface water and groundwater (Figure 11). In surface water, sulfate was derived primarily from soil sulfate (35.70%), sulfide oxidation (26.56%), sewage (16.58%), and atmospheric precipitation (12.45%), with negligible contributions from evaporite dissolution (4.21%) and chemical fertilizers (4.50%). Groundwater sulfate originated predominantly from sewage (34.96%) and soil sulfate (28.09%), complemented by atmospheric precipitation (17.35%) and sulfide oxidation (12.25%), while evaporite (4.29%) and chemical fertilizers (3.06%) remain minor sources. Spatially, contributions from soil sulfate in surface water were manifested as downstream > midstream > upstream > tributaries, while sulfide oxidation showed an opposite law. Contributions from sewage and precipitation showed limited fluctuations, with only individual samples displaying significantly elevated contributions. In groundwater, contributions from sewage intensified in midstream and downstream regions, while contributions from soil sulfate diminished along the flow path. Sulfide oxidation and atmospheric precipitation displayed lower contributions except for individual samples.

3.4. Sulfate Migration and Transformation

The mid-upper reaches of the study area are surrounded by mountains on three sides with steep slopes. This topography facilitates soil sulfate transport to river through surface runoff (Figure 12a). Upstream areas expose extensive carbonate rocks, characterized by well-developed karst fissures and thin soil cover (Figure 1). These conditions enhance soil sulfate infiltration into groundwater. Downstream regions contain extensive farmland (Figure 12b). Intensive agricultural activities and high precipitation accelerate soil erosion [48]. However, the flat terrain and extensive impermeable surfaces restrict soil sulfate leaching into groundwater [57]. Thus, soil sulfate critically influences sulfate migration in both surface water and groundwater. The contribution of soil sulfate was significantly higher in surface water (35.70%) than groundwater (28.09%), and it was close to 60% when surface water flows to the downstream.

The study area possesses abundant mineral resources. Sulfide oxidation during mining operations constitutes a critical biogeochemical process governing sulfate migration in surface water. Its contribution (26.52%) significantly exceeded that in groundwater (12.25%). This disparity arises because surface water directly receives mining drainage inputs, whereas transport of groundwater sulfate is constrained by limited flow systems and restricted runoff range. Specifically, after flowing through S4 and G3, sulfide-derived contributions increased significantly under the influence of the Qibaoshan mining area, while along the flow path, contributions from sulfide oxidation progressively decreased. Sulfate in Jianjiang River also primarily originated from sulfide oxidation influenced by Guanzhuang mining area. Additionally, sample G14 exhibited anomalously elevated sulfate concentrations and sulfide oxidation contribution. However, no sulfide deposits occur nearby, the contribution from sulfide oxidation may be linked to rural sulfur-rich coal combustion.

Sewage in the study area primarily comprises industrial discharges from chemical industry, paper plants and domestic sewage from rural settlements. It significantly influences sulfate in both surface water and groundwater. Surface water exhibited relatively low contributions from sewage (16.58%), attributable to dominant sulfate inputs from soil and sulfide oxidation. In contrast, sulfate in groundwater was significantly contributed by sewage (34.96%). This correlates with widespread rural wells featuring low water tables that enable sewage infiltration into aquifers via fractures [58]. For example, samples S22, G2 and G5–G7 were collected from the vicinity of towns and urban areas with a large number of industrial sewage discharge sources (

Table 4. The quantity of industrial sewage discharge sources in the towns of the study area [59].

Towns	Quantity	Towns	Quantity	Towns	Quantity
Daweishan	17	Gaoping	28	Zhentou	35
Dahu	23	Gugang	33	Puji	18
Yonghe	20	Liuyang	199	Guanqiao	13
Guandu	14	Chengchong	44	Baijia	7

). Sample S28 was collected from the vicinity of a factory. They received substantial industrial and domestic sewage, resulting in higher contributions from sewage (>40%).

The study area receives abundant atmospheric precipitation, serving as the primary recharge source for different water bodies. Precipitation exhibited low and stable sulfate concentrations, contributing moderately to surface water (12.45%) and groundwater (17.26%). Precipitation contributions showed limited spatial variability, primarily controlled by recharge conditions and hydrogeological conditions [26]. For example, aquifer media in G1–G4 and G9–G17 predominantly consist of carbonate and clastic rocks with high permeability coefficient, and part of the wells were exposed to the air during sampling. They can receive more atmospheric precipitation recharge. Conversely, samples G5 and G8 (weathered fissure water in metamorphic rocks) exhibit limited precipitation recharge, resulting in comparatively minor atmospheric contributions to sulfate.

Evaporite and chemical fertilizers showed negligible contributions to sulfate without notable variation in the water bodies of the study area.

In summary, the migration and transformation of sulfate in surface water and groundwater within the study area results from the dual control of natural processes and anthropogenic activities. Soil, sulfide oxidation, sewage, atmospheric precipitation, evaporite, and chemical fertilizers govern sulfate migration and transformation through distinct geochemical processes and physical mixing processes (Figure 13).

4. Conclusions

Surface water and groundwater in the Liuyang River Basin exhibited hydrochemical types dominated by the HCO₃-Ca type. Anthropogenic impacts had significantly elevated SO₄²⁻ proportions in some samples, resulting in the emergence of HCO₃·SO₄-Ca·Mg and HCO₃·SO₄-Ca types of water. Sulfate in the water bodies was unevenly distributed in space, and the high value areas were distributed in areas with strong human activities such as mining areas and towns.

The analyses of hydrochemistry and isotopes showed that surface water and groundwater primarily underwent carbonate and silicate rock dissolution, with concurrent sulfide oxidation process. Evaporite dissolution (like gypsum) contributed minimally to sulfate. Both water bodies received atmospheric precipitation recharge and existed hydraulic connectivity, indicating precipitation as a major sulfate source. Mining and agricultural activities significantly influenced sulfate concentrations, where sulfide oxidation, soil sulfate and sewage constituted dominant contributors, while fertilizers inputs showed negligible impacts.

There were distinct variations in the contributions of different sulfate sources. Soil sulfate dominated sulfate inputs in surface water, while sewage constituted the primary contributor in groundwater. The calculation results of the Simmr model revealed that surface water sulfate was derived from soil sulfate (35.70%), sewage (16.58%), sulfide oxidation (26.56%), and atmospheric precipitation (12.45%), whereas groundwater sulfate originated from sewage (34.96%), soil sulfate (28.09%), atmospheric precipitation (17.35%), and sulfide oxidation (12.25%).

The migration and transformation of sulfate in surface water and groundwater were jointly influenced by natural processes and anthropogenic activities. Key controlling factors included geochemical processes (sulfide oxidation and evaporite dissolution) and physical mixing (soil, sewage, atmospheric precipitation, and fertilizers). In the absence of human influence, sulfate primarily originated from soil leaching and precipitation inputs. However, when water flowed through anthropogenically impacted zones like mining areas and towns, sulfide oxidation and sewage emerged as dominant factors for the sulfate migration and transformation.

However, this study only conducted sampling and analysis of surface water and groundwater in the Liuyang River Basin during the dry season, and it lacked comparative analysis between wet and dry seasons. Future research should strengthen investigations in the wet season to reveal temporal variations in sulfate distribution and sources in the basin. Additionally, future studies should perform direct measurements of isotope signatures from potential sulfate sources in the study area to enhance source identification accuracy.