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Article

Geochemical Characterization of the River Waters in the Pumqu Catchments, Central Himalayas

by 1,†, 1,†, 2 and 1,*
1
Laboratory of Environmental Chemistry on the Tibet Plateau River Basins, School of Sciences, Tibet University, Lhasa 850000, China
2
Tibet Huatailong Mining Development Co., Ltd., Lhasa 850000, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Water 2022, 14(22), 3652; https://doi.org/10.3390/w14223652
Received: 18 September 2022 / Revised: 9 November 2022 / Accepted: 11 November 2022 / Published: 13 November 2022
(This article belongs to the Special Issue Basin Water Quality Changes)

Abstract

:
Pumqu is the biggest river in the Qomolangma National Natural Reserve in China. It is one of the headwaters of the river Ganges and is an important international river in southern Tibet Autonomous Region (T.A.R). However, there are a lack of systematic studies on Pumqu’s geochemical properties. In this study, water samples were collected systematically from all the river catchments in different seasons in 2021, the spatiotemporal variations of the geochemical characteristics of the catchments and their controlling factors were studied, and the overall water quality of the river was also evaluated. Overall, the results showed that the water from the Pumqu catchments was slightly alkaline, with an average pH of 8.22. The number of total dissolved solids was comparable to the other rivers on the Tibetan Plateau and showed a similar variation over the year. Affected by the natural geothermal spring water discharge, the values of oxidation reduction potential at some sampling sites were negative in the wet season. Generally, Ca2+ and HCO3 were the dominant ions. Carbonate weathering was the main factor affecting the geochemical features of the studied catchments. The results of correlation analysis showed the influence of rock weathering, glacial meltwater, geothermal water discharge and riverine physicochemical processes on the trace elements. The natural geothermal water discharge was particularly responsible for the elevated Li, which appeared in some of the sampling sites and resulted in relatively high WQI values in the sites. The overall water quality of the Pumqu catchments was excellent. This study provides first-hand information on the overall spatial and temporal span of the physicochemical characteristics and water quality of all the catchments of the river Pumqu, one of the major water systems in the central Himalayas.

Graphical Abstract

1. Introduction

As an important component of the water cycle, the chemical composition of a river is generally influenced by climate conditions (e.g., atmospheric precipitation and evaporative crystallization), geological features (e.g., rock weathering and soil erosion) and the human activities occurring in the river’s catchments [1,2]. The understanding of the chemical composition of the river water and its evolutionary patterns, therefore, can improve our knowledge of the possible controlling factors present in the catchments [3]. In addition, the riverine chemical composition is also an indicator of water quality evaluation [4,5,6,7]. Researchers worldwide have conducted large numbers of systematic studies on geochemical characteristics and their ionic sources in major rivers in the world [8,9] to provide a basis for water quality assessment. Moreover, the distribution characteristics of trace elements in the river course have also been studied extensively and used for comprehensive water quality evaluation [10,11,12], which has provided further practical information for the sustainable use of these river resources.
The Tibet Autonomous Region is rich in water resources and is one of the regions with the most rivers in the world [13]. However, due to its unique geological structure and ecological fragility and, driven by the combination of global warming and rapid development of regional economy and urban–rural integration processes, changes in water quantity and quality in the region are obvious. The performance of relevant studies is therefore a major priority [14]. In the region, as a result of global warming, the amount of glacial meltwater is increasing, which has led to an increased degree of weathering and erosion of rocks [15]. Furthermore, the region’s rivers, which are mainly recharged by glacial meltwater, exhibit increased runoff and probably overall reduced ionic concentrations [16]. However, the discharge of widely distributed thermal springs might also increase the riverine ionic contents under some circumstances [17]. Therefore, it is urgently required to conduct relevant studies to better understand the current status of the river geochemical features within the region, where some of the largest Asian rivers originate.
Pumqu, a major river system located in the Qomolangma National Natural Reserve (QNNR) in T.A.R in the central Himalayas, is the biggest river in the southern Plateau and is the one of the headwaters of the river Ganges. A comparison of satellite images from 1970 to 2013 revealed that the glacier coverage within the river Pumqu catchments (PC) decreased by 19.05% and, on the other hand, the total area of glacial lakes has increased by 26.76% in recent decades [18]. Meanwhile, in the catchments, the cultivated land area has also increased by 2.28% within the last 10 years (2008–2018) [19]. These changes will undoubtedly have an impact on the geochemical characteristics and trace element contents of the river. Studies showed that, for example, the geochemical properties of its middle reaches tributary, i.e., Yairu Tsangpo and its lower reaches tributary, i.e., Rongbuk River were mainly influenced by natural processes occurring in the catchments and with a minimal anthropogenic impact [20,21]. However, no studies have reported on the overall chemical conditions and features of the catchments. In this paper, the entire PC, including its mainstream and major tributaries (i.e., Luoluo River, Jilong Tsanpo, Yairu Tsanpo and Rongbuk River) was studied. Water samples were collected systematically from the rivers during May (normal season [22]), August (wet season) and November (dry season) in 2021, and in situ measurements of physicochemical parameters were also carried out in the sites. The spatiotemporal variations of the geochemical characteristics of the river catchments and their controlling factors were studied, and the overall water quality of the river was also evaluated. The results not only provide a better understanding of the riverine chemistry, but also offer a basis for the evaluation and protection of the water environment in the QNNR.

2. Materials and Methods

2.1. Study Area

Pumqu is one of the headwaters of the Koshi River in the Ganges system, originating in the end of the Dasuopu Glacier on the northern slope of Mt. Shishapangma. The PC is located in the southwestern T.A.R and drains between 85°38′~88°57′ E and 27°49′~29°05′ N. The main stream is 376 km long, with a drainage area of 25,307 km2 [23]. Its major tributaries, from the upper to the downstream, are Luoluo River, Jilong Tsangpo, Yairu Tsangpo and Rongbuk River (Figure 1). From its source to Gangga township is the upper reaches of the PC. This part of the river is 153 km long and features a drop in altitude of about 1200 m. The river bed is wide and shallow at the end of the middle reaches, with a curved and bifurcated channel and extensive wetlands on both sides of the river. Paleozoic-Cenozoic limestone is widely distributed in the middle and upper reaches of the catchments, and it is mostly interbedded with quartz sandstones and shales [23]. The mainstream in the upper and middle reaches extend stratigraphically in a west–east direction and residual karst features, such as clints and karst ditches, are widely present and become more complex and diverse from the middle to the upper reaches due to strong geological and tectonic movements in the catchments [24]. After the confluence of the Yairu Tsangpo (Figure 1), the river turns southward and cuts through the Himalayan range, forming a north–south trending canyon zone in the lower reaches, with schist, gneiss and quartzite distributed in the valley [25]. The length of this part of the river is 97 km; however, there is a drop in altitude near 2000 m. Geothermal springs are widely distributed in the PC [26,27].
Most of the PC is located on the northern side of the Himalayas and has an elevation above 4000 m, showing a typical continental plateau climate, with an annual precipitation of around 300 mm, more than 90% of which occurs between June and September. By contrast, evaporation in the area is rather strong, with an annual evaporation intensity of about 2500 mm [28]. Only a small part of the catchments is located on the southern side of the Himalayas, with an average altitude of 2400 m. The region is influenced by the wet and warm air currents of the Indian Ocean, showing maritime monsoon climate characteristics. The annual precipitation can reach 1500 mm, and the precipitation from June to September accounts for about half of the annual precipitations. The evaporation and precipitation in this region are generally equal [29,30].

2.2. Sampling and Sample Analyses

Taking into account that the possible effects of rock weathering processes, human activities and runoff dilution on geochemical contents of the river, a total of 26 sampling sites were set up along the river course and water samples were collected during the normal season (May), the wet season (August) and the dry season (November) in 2021. The sampling sites consisted of 11 sites (P1–P11) in the mainstream, 2 (L1–L2) in the upper reaches tributary, Luoluo River, 5 (Y1–Y5) in the middle reaches tributary, Yairu Tsanpo and 3 (J1–J3) in its branch Jilong Tsanpo and, finally, 5 (R1–R5) in the lower reaches of Rongbuk River (Figure 1). Water samples were collected in reverse using 2 L polypropylene (PP) beakers 30 cm under the surface. The collected samples were immediately filtered through disposable filter membranes (0.45 μm, hydrophilic polyethersulfone, Millipore) into a pre-acid-washed (65% HNO3, 10% v/v) and deionized water-washed 125 mL and 250 mL colorless PP bottles and screw capped and stored at 4 °C for trace elements and major ions analyses, respectively. Blank and parallel samples were collected and processed in the same way as the samples.
In situ measurements of some water physicochemical parameters were also conducted using portable instruments, i.e., the pH, total dissolved solids (TDS) and electrical conductivity (EC) were determined by using a multiparameter water quality analyzer (HANNA HI98195) with an accuracy of pH 0.01, TDS 1 mg·L−1 and EC 1 μS·cm−1, respectively. The oxidation reduction potential (ORP) was determined by using a redox potential meter (HACH ECO10), with an accuracy of 0.1 mV. In the laboratory inductively coupled plasma emission spectrometer (ICP-OES, PerkinElmer, Optima 5300 DV) was applied for the determination of major cations (Ca2+, K+, Mg2+, Na+) and SiO2. For that of anions (SO42−, NO3, Cl, CO32−), ion chromatograph (IC, DIONEX, ICS-1000) was applied, and a volumetric method was used for the determination of HCO3 contents. Inductively coupled plasma mass spectrometer (ICP-MS, PerkinElmer, NexION 300X, Massachusetts, USA) and atomic fluorescence spectrometry (AFS, Beijing Jitian, AFS-820, AFS-830, AFS-220a, Beijing, China) were applied for the determination of trace elements, i.e., Ag, Al, Cd, Co, Cr, Cu, Fe, Li, Mo, Mn, Ni, Pb, Zn As, Hg and Se.
Quality control of the data in this study was carried out by checking normalized inorganic charge balance (NICB (%) = (TZ+ − TZ)/TZ). The results showed that the absolute SD value was within 5%, revealing good quality of the analytical data obtained in this study [32].

2.3. Water Quality Index (WQI)

In recent years, WQI has been widely used for evaluating water quality of various types of water body [33,34,35]. A WQI calculation can be divided into three steps. Firstly, the relative weight of each parameter needs to be calculated using formula (1).
W i = w i i = 1 n w i
where Wi is the relative weight of parameter i and wi is the weight of parameter i.
Each different parameter i is given a different wi, which is usually a number between 1 and 5 according to the extent to which the parameter has an influence on water quality, from small to large. The weights of the parameters in this study refer to existing water quality evaluation cases (Table 1) [34]. The pH can intuitively reflect the quality of water, and EC and TDS are mostly used for groundwater quality evaluation; therefore, pH is selected as the evaluation parameter in conventional physicochemical parameter selections. Sulfate can be converted to H2S under reducing conditions, and NO3 is used as an indicator of human influence; therefore, SO42− and NO3 are selected as evaluation parameters in anions. Since major cations have little effect on water quality, they were not used in the evaluation. Combined with the results of the analysis of the cooccurrence network, Mn, Fe, Ni, Cu and As were selected as the evaluation parameters, among which As, Fe and Cu showed seasonal changes and could suggest whether there were seasonal changes in water quality. Ni, as the parameter with the strongest correlation with physicochemical parameters, was selected as the evaluation index and Mn with no correlation with physicochemical parameters was also selected as the evaluation parameter; the results could reflect water quality more comprehensively. Note that there is no calculated Wi for Fe in Table 1; since Fe was not detected in more than 67% of the sampling sites during the dry season, there was no corresponding WQI calculation.
Secondly, a single factor index is calculated for each parameter with formula (2).
q i = C i S i × 100
where qi is the single factor index of parameter i, Ci is the measured concentration of parameter i and Si is the limit value of parameter i. In this study, the limit value of national standards for surface water of Grade I [36] is used for Si.
Finally, the water quality index of each parameter and the comprehensive water quality index are then calculated with the following equations.
S I i = W i × q i
W Q I = i = 1 n S I i
where SIi is the water quality index of parameter i. WQI refers to a different quality level and is generally divided into five categories: <50 excellent; 50–100 good; 100–200 poor; 200–300 very poor; >300 unsuitable for drinking [37].

3. Results and Discussions

3.1. Status of In-Stream Physiochemical Parameters in the PC

The results of the in situ determination of the river waters’ pH, ORP, TDS and EC are shown in Figure 2. It can be seen from the figure that the river water in the PC appeared to be alkaline and had a small variation in pH in the three water periods, ranging from 7.47 to 8.74 (avg. 8.22). This is similar to the other major rivers (e.g., Nujiang River, Lhasa River) on the Tibetan Plateau [38,39].
Affected by seasonal temperatures [40] and changes in water pH [41], the ORP in the studied catchments varied from −78.0 to 149.0 mV (avg., 80.2 mV) during the year, with a tendency towards relatively high values in the dry season, with lower values in the normal season and the lowest values in the wet season. A reductive condition of the water environment with the negative values of ORP was observed, shown in the upper reaches of Yairu Tsangpo (Figure 2) (i.e., sampling sites Y2 and Y3, with ORP values of −70.0 mV and −78.0 mV, respectively) during the wet season. Intensively distributed geothermal springs in this part of the riverbanks were responsible for these values, since some of the springs that can be found during the dry season, with an ORP value somewhat below −146.0 mV (unpublished data), passed through the river in the high flow season. However, the impact only continued for 72 km downstream and the ORP value returned to −1.0 mV (at Y4) and 33 mV a further 75 km down (at Y5).
In the catchments, generally, the TDS (ranging from 26 to 231 mg·L−1) and EC (ranging from 56 to 461 μS·cm−1) showed a similar trend in all the periods (Figure 2), although the mainstream clearly differed from its tributaries. The TDS and EC contents in the mainstream gradually increased from upstream to midstream and then decreased in the downstream; however, the values tended to decrease from the upper to the downstream for all the tributaries. The average TDS content in the PC (138 mg·L−1) was slightly higher than the world average for rivers (120 mg·L−1) [42]; however, it was comparable to those of the other rivers on the plateau [43]. The rivers on the plateau are mainly fed by melting water at the source areas and feature relatively low dissolved contents, while geothermal/groundwater discharge and strong evaporation usually contribute to the elevated TDS contents in rivers in their middle reaches [44,45], ultimately decreasing in the downstream through dilution [46].
Although the water’s physicochemical parameters varied slightly between the different water periods, a statistical analysis found that there were still significant differences between them. Therefore, it is necessary to explore the controlling factors of geochemical in PC by different water periods.

3.2. Hydrochemical Types and Their Controlling Factors in the PC

The average contents of the major anions and cations in the main stream and their tributaries in the PC showed the same distribution pattern as HCO3 > SO42− > Cl > NO3 and Ca2+ > Na+ > Mg2+ > K+, respectively, over the year. Evidently, HCO3 is the dominant anion, accounting for 66.48%, 53.89% and 62.81% of the total anions in the normal, wet and dry season, respectively. The content of NO3 makes up only for 0.70%, 0.79% and 1.24%, respectively, of the total anion content in the different seasons. On the other hand, Ca2+ is the dominant cation, accounting for 66.21%, 76.05% and 70.17% of the total cations in the corresponding periods.
Generally, the characteristics of major ions can reveal the chemical features of a river. In this study, Shukarev hydrochemical classification combined with the Piper trilinear diagram (Figure 3) was applied for the classification of the river’s chemical features. The results (Figure 4) suggested that the HCO3·SO4−Ca type and HCO3−Ca type are the primary river hydrochemical types in the PC. Moreover, a consistent pattern of the hydrochemical type from the middle to the downstream parts of all the catchments appeared in the wet and dry water periods; however, this differs from the normal season. This is consistent with the results of the distribution pattern and the total contents of the major ions mentioned above. For example, in the mainstream, HCO3−Ca type water is mainly found in the upstream area and HCO3·SO4−Ca type represents the rest of the river course in the wet and dry season. In the tributaries, i.e., Jilong Tsangpo, Yairu Tsangpo and Rongbuk River, a HCO3·SO4−Ca type is the hydrochemical type both in wet and dry season. Unlike these tributaries in the middle and lower reaches, the Mg2+ content in Luoluo River showed an increasing trend from the normal season to the wet season and then decreased in the dry season; therefore, the hydrochemical type of this river transitioned from the HCO3·SO4−Ca type to the HCO3·SO4−Ca·Mg type and then to a complex of the HCO3·SO4−Ca type and HCO3·SO4−Ca·Mg type, accordingly.
By contrast, the water chemistry type of the catchments in the normal season is more complex, with 61.54% of the sampling sites having a HCO3·SO4-Ca type and 23.08% of the sampling sites displaying HCO3-Ca type dominance in this season. It can be observed that the water chemical types in this period are correlated with water pH (Figure 4, normal season). Taking the mainstream as an example, from the sampling site P1 to P11, the river chemical type mainly varies from the HCO3-Ca to the HCO3·SO4-Ca type when the water pH increasing, i.e., the water chemical type of HCO3·SO4-Ca is more saline than the chemical type of HCO3-Ca in the river course during the normal season. However, this correlation does not appear in the wet and dry periods.
Similar to the cases of most of the surface waters in the Tibetan Plateau hinterland [47,48], rock weathering processes occurred in the remaining catchments as the major controlling factors for the ionic composition and geochemical characteristics of the studied catchments (Figure 5). Precipitation and evaporative crystallization have a limited effect on the major ionic contents of the rivers in the studied area (Figure 5). It is generally accepted that river waters with relatively high Cl and Na+ contents are mainly influenced by atmospheric precipitation or evaporative crystallization [49]. In the studied catchments, the mean values of Cl/Na+ were 0.23, 0.18 and 0.20 during the normal, wet and dry season, respectively. These are much lower than those of the world average seawater ratio (Cl/Na+ = 1.16) [50]. This further indicates that weathering is the governing process in the water chemistry of the catchments. However, compared to the effect of rock weathering on the ionic concentration, differences in the river flow may also play a significant role in the ionic concentration [46]. The ion contents in the PC were relatively low in the wet season (high flow level) compared to the other water periods.
The weathering of different rocks produces different ions [51]. Geoscientists adopted a lithological end-map (HCO3/Na+~Ca2+/Na+ vs. Mg2+/Na+~Ca2+/Na+ molar concentration graph) to determine the contribution of silicate rocks, carbonate rocks and evaporite rocks weathering to the major ions in river water [50]. In Figure 6, most of the sampling sites in the PC during the normal, wet and dry seasons fall in the middle of the diagram, indicating that the ionic composition of the studied rivers mainly consists of a combination of carbonate weathering and silicate weathering in the catchments. This accords with another river running through the southern plateau, i.e., Nyangchu, which flows northward and joins the Yarlung Tsangpo near Shigatse city [45]; however, it differs from some rivers draining in southern Himalayas, e.g., the Seti River, where carbonate weathering has largely controlled the solute acquisition processes [52].
The ratio of (Ca2+ + Mg2+)/(Na+ + K+) in a river water can be an indicator for the screening of the weathering intensity of evaporite and carbonate rocks [53]. A low ratio of (Ca2+ + Mg2+)/(Na+ + K+) indicates a domain of evaporite weathering and, vice versa. The mean values of the (Ca2+ + Mg2+)/(Na+ + K+) ratio in the PC were 7.22, 5.98 and 8.26 during the normal, wet and dry season, respectively. These are much higher than those of world rivers (2.2) [54] and confirm that the major ions in the studied rivers originate from carbonate weathering. The impact of evaporite dissolution is therefore limited in the studied catchments (Figure 6).
In surface waters, generally, the equivalent ratio of (Ca2+ + Mg2+) to HCO3 should be 1 when carbonate rocks are dissolved without the influence of exogenous acids [55]. The mean values of the equivalent ratios during the normal, wet and dry seasons in the PC were 1.74, 1.98 and 1.53, while the ratios of (Ca2+ + Mg2+) to (HCO3 + SO42−) were 1.02, 1.00 and 0.91, respectively. This indicates the involvement of sulfuric acid in the carbonate weathering or presence of gypsum in the studied area [56]. Furthermore, studies have revealed that when the Ca2+/Mg2+ equivalent ratio is 1, both ions intend to originate from the dissolution of dolomite and, if the ratio is between 1 and 2, there is a greater contribution from calcite dissolution. However, when the ratio is higher than 2, the additional dissolution of silicate rocks or gypsum to provide Ca2+ is suggested [57]. Within the PC, except at the headwater sampling site of Luoluo River (L1), the equivalent ratios of Ca2+/Mg2+ were all greater than 2. These results reveal that, in addition to the carbonate weathering, the sources of Ca2+ and Mg2+ in the river water were also associated with silicate weathering and gypsum dissolution (Figure 6). This is consistent with the fact that there is a wide distribution of carbonate and silicate rocks in the studied areas [28].
The products of silicate weathering are mainly dissolved SiO2 [58]. The contents of SiO2 within the studied catchments ranged from 2.47 to 18.68, 1.73 to 9.16, and 2.58 to 9.16 mg·L−1 in the normal, wet, and dry seasons, with average values of 7.78, 5.96 and 6.99 mg·L−1, respectively. This further indicates that the weathering of silicate rocks has a small effect on the chemical composition of the river flow in the catchments [59]. It can be concluded that, similar to the other rivers on the Tibetan Plateau [45,46], the major ions of the rivers in the Pumqu catchments are mainly controlled by the weathering of the carbonate rocks distributed in the studied area and the impact of human activities is restricted.

3.3. Contents of Trace Elements in the PC

A total of 17 trace elements (including Ag, Al, As, Cd, Co, Cr, Cu, Fe, Hg, Li, Mo, Mn, Ni, Pb, Se, Ti and Zn) were analyzed in this study. Among these, the contents of Ag, Cd, Hg, Pb, Se and Zn were not detected in the sampling seasons; in the dry season, the contents of Fe in 62% of the sampling sites were also below the detection limits (DL). Therefore, these elements are not discussed later in the study. For the rest of the elements (Table 1), the median value from all the sampling sites was eventually used for further calculations [60] due to the fact that a relatively large variation (coefficient of variation ranging from 17.43% to 366.42%) was obtained for those elements.
Nevertheless, except for Cr, the concentrations of these detectable elements were extremely low when compared with those of the environmental quality standards for surface water of Grade I [36] and the standard for the irrigation water quality of dry land crops [61] (Table 1). There seemed to be a source of Cr in the wet season as the concentrations of Cr showed a “∧” shape from the normal to wet and then to the day season for all the rivers. However, the Cr in this study was detected as the total. Further elemental speciation analysis is required for identifying possible contaminations. Unlike that of Cr, variations of As and Li between the three seasons showed a “∨” form as the lowest concentrations occurred in the wet season as a result of dilution in the high flow season. By contrast, the contents of Li in Yairu Tsangpo over the year and As in the river in the normal season exceeded the guideline values of the national standards for drinking water quality [62] (Table 2).
The contents of As, Cu, Mn and Ni in the normal season were greatly affected by the water chemistry type and the maximum values were all of the water chemistry type containing Na. In Yairu Tasngpo, the maximum concentration of Li was as high as 1583 μg·L−1 at the Y2 sampling site during the normal season. Similarly, the As content at Y2 during the normal season reached 355.5 μg·L−1. This high level of As exceeds the limitation for national environmental quality standards for surface water of Grade V (100 μg·L−1) [36]. Geothermal waters (Kongmar hot springs), located 14 km upstream of the Y2 sampling site, caused the high concentrations of Li and As in the river. Geothermal waters, enriched in Li and As, are widely distributed in the PC [26,27] and are often utilized for physical therapy by locals in spring and autumn seasons. The discharge of the geothermal water directly into the river, especially in the normal (spring) and dry (autumn) seasons, is a major reason for the high contents of Li and As found in Tibetan rivers [17,43,63].
Variations in the other physicochemical parameters of a water generally have a major impact on the distribution and transportation of trace elements in water [41,64]. In the present study, a cooccurrence network analysis [65] was adopted for a visual display of the significant correlations (p < 0.05) among the trace elements, major ions and the rest of parameters examined (Figure 7), after a normal distribution examination of the data set by applying Kolmogorov–Smirnov (K-S) test. Subsequently, a Pearson correlation analysis was performed for the normally distributed data, and a Spearman correlation analysis was carried out for the non-normally distributed data prior to the correlation analysis.
The cooccurrence network (Figure 7) shows that among the measured trace elements, Co, Cr, Cu, Li and Ni exhibited a significant positive correlation with the major ionic contents, with a trend showing a decrease in strength from the normal (i.e., lean flow period) to the wet (high flow period) and, finally, the dry (low flow period) season (Figure 5). These results revealed two outcomes: (1) the trace elements measured in PC were closely associated with the major ions and were also mainly derived from the continental crust [50]; and (2) similar to the effects on the ionic concentration (Section 3.2), the river flow rate also played an important role in the variations of those trace elements. By contrast, it can be seen from the network (Figure 7) that Al, Fe and Ti, generally also considered as major components of the Earth, had a negative correlation with the major ions. Recent studies have shown that, on the plateau, high concentrations of Al, Fe and Ti are present in glacial meltwater runoff [48]. This suggests that the major contributor of Al, Fe and Ti in PC could also be glacier meltwater runoff rather than rock weathering. This can be further substantiated by the variations in the correlation strength shown in Figure 7, i.e., an increased in strength from the normal to the wet season as the meltwater runoff usually increased, however, the correlation became insignificant in the dry season as, generally, there was little or no relevant runoff into the rivers during this season.
However, the water recharge type and dilution may not be the only controlling factor, since riverine physiochemical processes and possible anthropogenic inputs also vary the riverine geochemical characteristics [66,67,68]. Affected by the riverine physiochemical properties, generally, Al, Fe and Ti often exist in the form of metal hydroxides and form aqueous complexes [66]. Therefore, it can be seen from the network (Figure 7) that these three elements also have a significant negative correlation with the pH of the water in the normal season, when the river waters have a relatively high pH (avg., 8.29). Although the pH increased to 8.34 in the wet season, with an increase in the river flow rate that reduced the adsorption of trace elements by sediments [69], the correlation disappeared. With the pH decreases in the dry season (avg., 8.03) and the decrease in the river flow, the correlation reappeared. In addition, it is worth noting that during the wet season only, there was a strong negative correlation between As and ORP (Figure 7). This further confirmed the fact that the elevated concentrations of As found in the PC mainly originate from the natural geothermal springs distributed in the catchments (as discussed at the beginning of this section). In the wet season, when a river with a high flow rate drifts over some hot springs with a reductive condition, the ORP of the river becomes more reductive (with a more negative value, as discussed in Section 3.1); however, the content of As in the river is low due to the process of dilution. This correlation was not shown in the normal and dry seasons (Figure 7), although the contents of As discharged from the springs in these seasons already contaminated the river, as discussed early in this section. This is because at these times of the year, hot spring waters are usually saved in a natural or mortified pond for physical therapy for some time and then discharged into the nearby river; hence As are provides to the river, albeit with little impact on the ORP.

3.4. Evaluation of Water Quality of the PC by WQI

The results of the calculated WQI, as displayed in Figure 8, suggest that, except for one sampling site (Y2), all the WQI values were smaller than 50, indicating that the overall water quality of the studied rivers in the PC is excellent, with a relatively stable contribution of pH to the WQI. The average contributions of the pH to the WQI are 14.17%, 14.25% and 15.52% during the normal, wet and dry seasons, respectively. It can be seen from Figure 8 that the river water quality at sampling site Y2 is poor; however, the impact is limited, as the quality returns to excellent in the downstream. Around the site at the headwater area of the tributary, Yairu Tsangpo, as discussed in Section 3.1 and Section 3.3, natural geothermal hot springs are widely distributed. This study showed that discharges from geothermal waters in Tibet could have extremely high arsenic concentrations from over 10 mg·L−1 to up to 126 mg·L−1 [70]. Further detailed environmental studies are needed not only for a better understanding of the widely distributed geothermal springs in the region, but to make sustainable use of these springs. Through the test of the difference in WQI between different water periods, it was found that there was no significant difference in WQI in the three water periods, which was consistent with the better water quality in the three water periods, indicating that WQI can comprehensively reflect the water quality in Pumqu catchments.

4. Conclusions and Prospect

4.1. Conclusions

This study provides first-hand information on the overall spatial and temporal span of the physicochemical characteristics and water quality of the entire PC, the major water system in the QNNR in the central Himalayas. The main purpose was to define the current geochemical status of the river catchments and its major controlling factors.
The results revealed that the studied rivers were all alkaline, with the potential for high buffering capacity. The spatial and temporal variations in the major ionic contents were relatively constant and followed the following trend: HCO3− > SO42− > Cl > NO3− and Ca2+ > Na+ > Mg2+ > K+. Accordingly, HCO3− was the dominant anion and Ca2+ was the dominant cation, accounting for 66.48%, 66.21% and 53.89% and 76.05%, 62.81%and 70.17% of the total anions and cations in the normal, wet and dry seasons, respectively. Rock weathering, especially carbonate rock weathering occurring in the catchments was the major contributor of the water chemistry features, with HCO3·SO4–Ca and HCO3–Ca as the predominant hydrochemical types. Among the 17 measured trace elements, the concentrations of Ag, Cd, Hg, Pb, Se and Zn were negligible and, in general, the levels of Al, As, Co, Cu, Fe, Li, Mo, Mn, Ni and Ti were also low when compared to those of the Chinese national standards for surface water and irrigation water quality. In the wet season only, relatively high concentration of Cr appeared in the catchments; however, Cr was detected as the total in this study. Overall, unlike the major ions, the total contents of the trace elements in the rivers originated from a combination of rock weathering, glacial meltwater, geothermal water discharge and physicochemical processes. Generally, this study showed that the water quality of the rivers in the PC is excellent, although in a few locations, the influence of natural geothermal springs might be significant. Further studies are required to determine the sustainability of the QNNR’ environment.

4.2. Prospects

The evaluation of river water quality can provide a reference for the sustainable use of water resources. Generally, this study showed that the water quality of the rivers in the PC is excellent, although in a few locations, the influence of natural geothermal springs might be significant. Further studies are required to determine the sustainability of the QNNR’ environment. In the selection of indicators for water quality evaluation, there is a lack of organic pollutants and biological indicators, although heavy metal elements are added, but with more relevant data, the screening results will become more reliable. TOC is the most comprehensive indicator of organic matter, and studies related to TOC and pollution effects should be carried out to make the evaluation results more accurate.

Author Contributions

Y.Y.: Conceptualization, methodology, investigation, formal analysis, data curation, and writing—original draft. H.C.: Methodology, validation, investigation, resources, project administration, and writing—original draft. L.R.: Methodology, formal analysis, and investigation. X.H.: Conceptualization, validation, investigation, writing—review and editing, supervision, and funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Nature Science Foundation of China (22066022), Science and Technology Basic Work of Science and Technology(2015FY111000), the “High-level Talents Training Program” for postgraduates of Tibet University (2020-GSP-S057) and Tibet University 2022 Central Financial Support Special Funds for Local Colleges and Universities ([2022] No. 1).

Data Availability Statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

The authors would like to thank for the travel admission supported by Qomolangma National Nature Reserve Administration.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Distribution map of sampling sites in the Pumqu catchments (the distribution of rocks in the catchments is plotted according to the Geological Atlas of China [31]).
Figure 1. Distribution map of sampling sites in the Pumqu catchments (the distribution of rocks in the catchments is plotted according to the Geological Atlas of China [31]).
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Figure 2. Whisker plot analysis of pH, ORP, TDS and EC of the Pumqu catchments in three different water periods (in the plots, N, W and D on x-axes indicate normal season, wet season and dry season, respectively).
Figure 2. Whisker plot analysis of pH, ORP, TDS and EC of the Pumqu catchments in three different water periods (in the plots, N, W and D on x-axes indicate normal season, wet season and dry season, respectively).
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Figure 3. Piper trilinear diagram of the Pumqu catchments in three different water periods.
Figure 3. Piper trilinear diagram of the Pumqu catchments in three different water periods.
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Figure 4. Spatial distribution of hydrochemical types of the Pumqu catchments in three different water periods.
Figure 4. Spatial distribution of hydrochemical types of the Pumqu catchments in three different water periods.
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Figure 5. Gibbs distribution of Pumqu catchments in three different water periods.
Figure 5. Gibbs distribution of Pumqu catchments in three different water periods.
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Figure 6. Lithologic end-map of Pumqu catchments in three different water periods.
Figure 6. Lithologic end-map of Pumqu catchments in three different water periods.
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Figure 7. Cooccurrence network of trace elements with major ions and physicochemical parameters in the Pumqu catchments (the red line represents a positive correlation; the green line represents a negative correlation, and the thickness of the line represents the strength of the correlation).
Figure 7. Cooccurrence network of trace elements with major ions and physicochemical parameters in the Pumqu catchments (the red line represents a positive correlation; the green line represents a negative correlation, and the thickness of the line represents the strength of the correlation).
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Figure 8. WQI values of the Pumqu catchments at the different water periods (for each sampling site, the bar from left to the right represents the normal, wet and dry season).
Figure 8. WQI values of the Pumqu catchments at the different water periods (for each sampling site, the bar from left to the right represents the normal, wet and dry season).
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Table 1. Parameters used and their relative weights for WQI evaluation in the Pumqu catchments.
Table 1. Parameters used and their relative weights for WQI evaluation in the Pumqu catchments.
ParamentspHSO42−NO3MnFeNiCuAs
Unitmg·L−1mg·L−1μg·L−1μg·L−1μg·L−1μg·L−1μg·L−1
Limit value [36]6~925010100300201050
wi43533125
Wi for normal and wet season0.15380.11540.18230.11540.11540.03850.07690.1823
Wi for dry season0.17930.13040.21740.13040.04350.08700.2174
Table 2. Contents of detectable trace elements in the Pumqu catchments (median value, μg·L−1).
Table 2. Contents of detectable trace elements in the Pumqu catchments (median value, μg·L−1).
SeasonAlAsCoCrCuFeLiMnMoNiTi
Main stream
Pumqunormal24.101.000.096.800.5625.0058.203.660.621.151.45
wet37.200.410.1918.300.5836.0023.801.910.732.591.68
dry12.001.230.389.450.68DL79.002.720.772.430.86
Tributary
Luoluo Rivernormal10.352.690.148.000.4615.0063.702.901.311.390.59
wet15.350.420.2518.850.6627.0018.240.511.283.170.75
dry5.452.410.448.590.90DL85.508.471.184.160.20
Jilong Tsangponormal3.680.030.138.500.3321.002.8721.400.531.240.20
wet31.300.560.2311.200.6637.000.623.620.542.331.20
dry13.000.670.359.220.61DL3.1010.000.403.520.20
Yairu Tsangponormal34.1010.370.148.320.8343.00313.001.950.451.391.70
wet30.001.740.2420.700.7936.00250.000.580.453.131.56
dry12.006.450.216.770.63DL350.001.800.322.260.47
Rongbuk Rivernormal83.605.430.155.860.2963.0012.402.820.850.694.83
wet104.000.970.1314.400.2676.0010.502.120.621.697.04
dry14.005.080.377.820.33DL17.001.320.771.430.90
SEPA and AQSIQ [36]-50-10 #10------
MOH and SAC [62]-10-50 #10003002001007020-
SEPA and SAMR [61]-100-100 #1000----200-
Hyphen indicates no information available; DL indicates the value is below the detection limit; # indicates the value is detected as Hexavalent Cr.
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Yang, Y.; Chen, H.; Renzeng, L.; Huang, X. Geochemical Characterization of the River Waters in the Pumqu Catchments, Central Himalayas. Water 2022, 14, 3652. https://doi.org/10.3390/w14223652

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Yang Y, Chen H, Renzeng L, Huang X. Geochemical Characterization of the River Waters in the Pumqu Catchments, Central Himalayas. Water. 2022; 14(22):3652. https://doi.org/10.3390/w14223652

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Yang, Yang, Hulin Chen, Lamu Renzeng, and Xiang Huang. 2022. "Geochemical Characterization of the River Waters in the Pumqu Catchments, Central Himalayas" Water 14, no. 22: 3652. https://doi.org/10.3390/w14223652

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