Hydrochemistry and environmental implications in the western alpine region of China

ZHAO Yue; LI Zongxing; LI Zhongping; AOBULI Gulihumaer; NIMA Zhaxi; WANG Dong

doi:10.1007/s40333-025-0072-0

Journal of Arid Land >

2025 , Vol. 17 >Issue 4: 411 - 439

DOI: https://doi.org/10.1007/s40333-025-0072-0

Research article

Hydrochemistry and environmental implications in the western alpine region of China

ZHAO Yue ¹^,²^,³ ,
LI Zongxing ^,¹^,⁴^,^* ,
LI Zhongping ² ,
AOBULI Gulihumaer ⁵ ,
NIMA Zhaxi ⁶ ,
WANG Dong ⁶

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¹Observation and Research Station of Eco-Hydrology and National Park by Stable Isotope Tracing in Qilian Mountains/Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
²Oil and Gas Research Center, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
³University of Chinese Academy of Sciences, Beijing 100049, China
⁴College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
⁵Pishan Meteorological Bureau of Xinjiang Uygur Autonomous Region, Hetian 848000, China
⁶Ali Branch of the Xizang Autonmous Region Hydrology Bureau, Ali 895000, China

^*LI Zongxing (E-mail: lizxhhs@163.com)

Received date: 2024-08-11

Revised date: 2024-11-20

Accepted date: 2024-11-25

Online published: 2025-08-13

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Abstract

The western alpine region is an important freshwater supply and water conservation area for China and its surrounding areas. As ecological civilization construction progresses, the ecohydrology of the western alpine region in China, which is a crucial ecological barrier, has undergone significant changes. In this study, we collected 1077 sampling points and presented a comprehensive overview of research results pertaining to the hydrochemistry of river water, meltwater, groundwater, and precipitation in the western alpine region of China using piper diagram, end-member diagram, and hydrological process indication. Water resources in the western alpine region of China were found to be weakly alkaline and have low total dissolved solids (TDS). The mean pH values for river water, meltwater, groundwater, and precipitation are 7.92, 7.58, 7.72, and 7.32, respectively. The mean TDS values for river water, meltwater, groundwater, and precipitation are 280.99, 72.48, 544.41, and 67.68 mg/L. The hydrochemical characteristics of the water resources in this region exhibit significant spatial and temporal variability. These characteristics include higher ion concentrations during the freezing period and higher ion concentrations in inland river basins, such as the Shule River Basin and Tarim River Basin. The principal hydrochemical type of river water and meltwater is HCO₃^-•SO₄^2--Ca²⁺, whereas the principal cations in groundwater are Mg²⁺ and Ca²⁺, and the principal anions are HCO₃^- and SO₄^2-. In terms of precipitation, the principal hydrochemical type is SO₄^2--Ca²⁺. The chemical ions in river water and groundwater are primarily influenced by rock weathering and evaporation-crystallization, whereas the chemical ions in meltwater are mainly affected by rock weathering and atmospheric precipitation, and the chemical ions in precipitation are derived primarily from terrestrial sources. The main forms of water input in the western alpine region of China are precipitation and meltwater, and mutual recharge occurs between river water and groundwater. Hydrochemical characteristics can reflect the impact of human activities on water resources. By synthesizing the regional hydrochemical studies, our findings provide insights for water resources management and ecological security construction in the western alpine region in China.

Key words： hydrochemical type; ion source; piper diagram; end-member diagram; hydrological process; western alpine region of China

Cite this article

ZHAO Yue , LI Zongxing , LI Zhongping , AOBULI Gulihumaer , NIMA Zhaxi , WANG Dong . Hydrochemistry and environmental implications in the western alpine region of China[J]. Journal of Arid Land, 2025 , 17(4) : 411 -439 . DOI: 10.1007/s40333-025-0072-0

1 Introduction

Water is a vital natural resource and its storage, use, and quality are inextricably linked to human survival and social development. Typically, water resources exist in a variety of forms, including solids (glacier ice, ice sheet, sea ice, snow, hail, frozen soil, etc.), liquids (ocean, river, lake, groundwater, snow meltwater, etc.), and gases (water vapor, clouds, fog, etc.). The chemical composition of natural water bodies is influenced by several factors, including rock lithology, climate, runoff, dry and wet atmospheric deposition, vegetation, and human activities (Li et al., 2017a; Shen et al., 2021; Vorobyev et al., 2021). The factors influencing hydrological processes in the alpine region are complex and diverse (Dong et al., 2007; Tian et al., 2021; Liang et al., 2022; Zhang et al., 2022).

Hydrochemistry is the study of the chemical composition of natural water bodies, as well as their spatial and temporal distribution and evolution. It combines hydrology with chemical methods and is a fundamental process for understanding, identifying, and controlling the chemical characteristics of water bodies (Wang, 2010). Hydrochemistry can provide insights into the evolution of water bodies, chemical weathering, ion sources, and other relevant information (Hindshaw et al., 2011; Zhou et al., 2014; Han et al., 2021). Research on the chemical composition of natural water bodies can be used to scientifically analyze the transformational relationship of water resources, trace the source, and objectively evaluate the quality of water resources; this provides a theoretical basis for the rational development, utilization, and management of water resources (Liu et al., 2020c).

The western alpine region of China, a vital source of water resources in the arid and semi-arid areas, serves as a crucial ecological shield and plays an irreplaceable role in preserving regional and national ecological balance. However, this region is sensitive to climate change, which can significantly impact the water resources supply and accelerate the water transformation (Chen et al., 2021; Zhang et al., 2023). The change of water resources in the western alpine region of China directly affects the river runoff and water conservation function of the "Asian water tower", thereby affecting the water cycle and water balance in China and on a global scale (Shang et al., 2021; Wang et al., 2021d). To understand the stability of water resources and water ecological security in the western alpine region of China amidst the backdrop of intensifying warming and humidification, this study extended previous research by expanding the focus from a single cold region to the entire western alpine region. This expansion addressed the data scarcity stemming from the challenges of sampling in individual regional studies mainly related to geographical and climatic constraints (Bai and Yang, 2007; Fan et al., 2014; Gao et al., 2019). By reviewing the current situation of regional hydrochemistry in the western alpine region of China, this study endeavored to uncover the hydrochemical characteristics of river water, meltwater, groundwater, and precipitation in the region. The specific objectives of this study were: (1) to elucidate the patterns of hydrochemical change influenced by environmental factors; (2) to discern the variations in hydrochemical influencing factors in different river basins; (3) to analyze the hydrochemical processes indicated by hydrochemistry; and (4) to determine the impact of human activities on water resources in ecologically sensitive areas. The findings of this research will provide reference for future studies on hydrochemical processes in the western alpine regions of China. They will also provide a practical basis for the realization of long-term environmental change research and the establishment of comprehensive monitoring networks, as well as informing the development of environmental protection and water resources management policies.

2 Materials and methods

2.1 Study area

The western alpine region of China (73°40′12′′-107°38′24′′E, 21°00′36′′-49°00′36′′N; Fig. 1) encompasses Gansu Province, Qinghai Province, Xinjiang Uygur Autonomous Region, Xizang Autonomous Region, Aba Tibetan and Qiang Autonomous Prefecture and Ganze Tibetan Autonomous Prefecture in western Sichuan Province, northern Yunnan Province, Yulong Snow Mountains, and northern Gaoligong Mountains in China (Ding et al., 2017). The western boundary is the Pamir Plateau, the eastern boundary is the Hengduan Mountains, the northern boundary is the Altay Mountains, and the southern boundary is the Himalayas Mountains. The region is characterized by high altitude and extensive snow and glaciers, with the majority of the glaciers distributed in the Kunlun, Tianshan, and Nyainqêntanglha mountain systems. The total number of glaciers in the region is 48,571 and the total area reaches 51,766.08 km² (Liu et al., 2015a). The western alpine region of China not only serves as the source of numerous large rivers but also provides valuable water resources for arid areas through the meltwater runoff from the glaciers and snow (Feng et al., 2011). It has a low average temperature, with a large diurnal temperature range, a short frost-free period, and intense ultraviolet radiation. The average annual temperature is approximately 3°C and the average annual precipitation is about 306 mm (Zhang et al., 2023). This region is highly sensitive to climate change and the warming trend has intensified in recent years. Sedimentary rocks, magmatic rocks, and metamorphic rocks are widely distributed in the region. Sedimentary rocks primarily consist of sandstone, shale, and limestone. Magmatic rocks mainly include granite, pyrodiorite, gabbro, basalt, etc. Metamorphic rocks comprise gneiss, schist, and marble (Zhang, 1990; Qian et al., 2012; Ma et al., 2024). These rock types reflect a complex geological history and provide an important geological record for the hydrochemistry of alpine regions.

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Fig. 1 Overview of the study area and distribution of sampling points of different water bodies. Note that the figure is based on the standard map (GS(2020)4619) of the Map Service System (https://bzdt.ch.mnr.gov.cn/), and the standard map has not been modified.

2.2 Data sources

To gain insight into the hydrochemical characteristics of the western alpine region of China, we searched for research papers related to the keywords "precipitation hydrochemistry", "groundwater hydrochemistry", "river hydrochemistry", "meltwater hydrochemistry", and "hydrological processes" before January 2024. At the same time, these papers had the distribution of sampling points in the western alpine region of China, and recorded the pH, total dissolved solids (TDS), electrical conductivity (EC), and concentrations of chemical ions (Na⁺, Ca²⁺, Mg²⁺, K⁺, Cl^-, HCO₃^-, SO₄^2-, and NO₃^-) of hydrochemistry. For these reasons, a total of 198 relevant papers were collected from Web of Science and China National Knowledge Network. The research data were primarily selected from 89 articles published before January 2022 by determining whether there are distribution of glaciers and frozen soil around the sampling points, whether the sampling points are located in mountain runoff, and whether the sampling points are in the upper reaches of river basin. The articles collected included a total of 579 river sampling points, 142 glacial and snow meltwater sampling points, 139 groundwater sampling points, and 217 precipitation sampling points, some of which did not have precise coordinates. The sampling data included river basins of Ertix River, Urumqi River, Tarim River, Heihe River, Shiyang River, Shule River, Yarlung Zangbo River, Yangtze River, Nujiang River, Jinsha River, Minjiang River, Yalong River, Yellow River, Lancang River, Rongbuk River, Kuytun River, Ili River, Baishui River, and Nagqu River in the western alpine region of China. The distribution of the sampling points is shown in Figure 1 and the data sources are shown in Table 1.

Table 1 Date sources for different types of sampling points

Sampling point type	Reference
River water	Liu (1986); Guo (1987); Su and Tang (1987); Pu et al. (1988); Qin et al. (1999); Liu et al. (2000); Sun et al. (2002); Zhou et al. (2004); Nie et al. (2005); Wu et al. (2008); Huang et al. (2009); Noh et al. (2009); Wei et al. (2010a); Feng et al. (2011); Huang et al. (2011); Pu et al. (2011); Zhang et al. (2012a); Fan et al. (2014); Li et al. (2014b); Zhou et al. (2014); Guo et al. (2015); Jiang et al. (2015); Qu et al. (2015); Wang et al. (2015); Wang (2016); Wei et al. (2016); Xu (2016); Bu (2017); He et al. (2017); Li et al. (2017a); Yang (2017); Li (2018); Li et al. (2018b); Liu et al. (2018); Bao (2019); He et al. (2019); Hu (2019); Li et al. (2019b); Liu et al. (2019, 2020c); Li et al. (2020b); Liu et al. (2020b); Zhao (2020); Zhao et al. (2020); Han et al. (2021); Ma et al. (2021); Renzeng et al. (2021); Wang et al. (2021a); Wang et al. (2021b); Wang et al. (2021c)
Meltwater	Pu et al. (1988); Qin et al. (1999); Kang et al. (2002); Sun et al. (2002); Nie et al. (2005); Li et al. (2007b); Li et al. (2008, 2016a, 2019a); Wu et al. (2008); Zheng et al. (2008); Wu et al. (2009); Dong et al. (2010); Wei et al. (2010a); Li et al. (2011a); Li et al. (2011b); Pu et al. (2011); Feng et al. (2012); Zhang et al. (2012b); Zhao et al. (2012); Dong et al. (2013); Guo et al. (2015); Li et al. (2015b); Wang (2016); Wang et al. (2016); Wei et al. (2016); Bu (2017); Feng et al. (2017); Hu (2019); Song et al. (2019); Zhou et al. (2019); Li et al. (2020a)
Groundwater	Nie et al. (2005); Zhu et al. (2008); Zhu et al. (2010); Zhang et al. (2012a); Li et al. (2013); Li et al. (2014b); Wang et al. (2015); Wang (2016); Luo et al. (2017); Yang (2017); Li et al. (2018a); Li et al. (2018c); Zhang et al. (2018a); Hu (2019); Li et al. (2019a, 2020b); Ma (2019); Liu et al. (2020c); Ma et al. (2021)
Precipitation	Pu et al. (1988); Williams et al. (1992); Tang et al. (2000); Sun et al. (2002); Zhang et al. (2004); Li et al. (2007a); Li et al. (2009, 2014b); Feng et al. (2011); Ma et al. (2012); Wang (2012); Zhou et al. (2014); Guo et al. (2015); Li et al. (2015a, 2017b, 2020c); Wang et al. (2015); Wang et al. (2016); Yang (2017); Yu and Zhao (2017); Li (2018); Wang et al. (2019b); Li et al. (2020b); Zhang et al. (2020); Wang et al. (2022)

Data quality was determined using Pearson correlation coefficient and the ratio of anion to cation concentrations (Liu et al., 2015b). In this study, the Pearson correlation coefficient between anion concentration and cation concentration is 0.67 (P=0.000), and the ratio of anion to cation concentrations is 0.96, which is close to 1.00. These results indicated that there is a good anion-cation charge balance, and the data are considered reliable.

2.3 Methods

2.3.1 Piper diagram

The Piper diagram is an effective graphical method for classifying and analyzing the chemical types of water samples and examining water-rock interaction around sampling points (Piper, 1944; Wang, 1983). This diagram consists of cation triangles (Ca²⁺, Mg²⁺, and Na⁺+K⁺), anion triangles (Cl^-, SO₄^2-, and HCO₃^-+CO₃^2-), and a rhombus area.

2.3.2 Gibbs diagram

Gibbs diagram can intuitively reflect the hydrochemistry of different water bodies. Based on the relationship between TDS and molar concentration ratio of cations (Na⁺/(Na⁺+Ca²⁺)) or anions (Cl^-/(Cl^-+HCO₃^-)), factors affecting the water samples can be roughly divided into atmospheric precipitation, rock weathering, and evaporative crystallization (Gibbs, 1970). When the TDS is moderate (about 70.00-300.00 mg/L) and the Na⁺/(Na⁺+Ca²⁺) or Cl⁻/(Cl⁻+HCO₃⁻) ratio is less than 0.50, that is, when the sample data points are distributed in the middle or left side of the Gibbs diagram, it usually reflects the obvious influence of rock weathering on hydrochemistry. When the TDS is small (less than 70.00 mg/L) and the ratio of Na⁺/(Na⁺+Ca²⁺) or Cl⁻/(Cl⁻+HCO₃⁻) is close to 1.00, the sample data point is located at the lower right corner of Gibbs diagram, which usually reflects the influence of atmospheric precipitation on hydrochemistry. When the TDS is high (more than 300.00 mg/L) and the ratio of Na⁺/(Na⁺+Ca²⁺) or Cl⁻/(Cl⁻+HCO₃⁻) is close to 1.00, the sample data point is located in the upper right corner of Gibbs diagram, which usually reflects the influence of evaporative crystallization on hydrochemistry (Yang, 2017).

2.3.3 End-member model

Gaillardet et al. (1999) analyzed 60 rivers worldwide and proposed end-member diagrams to determine the weathering products affecting surface and groundwater chemistry. They categorized weathering products into carbonate, silicate, and evaporite rocks and determined the types of rock weathering by calculating the ionic molar concentration ratios of Ca²⁺/Na⁺, Mg²⁺/Ca²⁺, and HCO₃^-/Na⁺. In general, when Ca²⁺/Na⁺ is close to 50.00, Mg²⁺/Ca²⁺ is close to 10.00, and HCO₃⁻/Na⁺ is close to 120.00, it indicates that surface water (or groundwater) is subject to weathering control of carbonate rocks. When Ca²⁺/Na⁺ is close to 0.35 (±0.15), Mg²⁺/Ca²⁺ is close to 0.24 (±0.12), and HCO₃⁻/Na⁺ is close to 2.00 (±1.00), it indicates that the surface water (or groundwater) is controlled by the weathering of silicate rock. When Ca²⁺/Na⁺<0.20, Mg²⁺/Ca²⁺<0.12, and HCO₃⁻/Na⁺<1.00, it indicates that the surface water (or groundwater) is subject to weathering control of evaporative salt rocks (Anatolaki and Roxani, 2009).

2.3.4 Enrichment factor and end-member contribution method

The enrichment factor can be used to study the relative enrichment degree of chemical ion concentration in water bodies relative to the ocean (EF_sea) and soil (EF_soil) to determine the element source and contribution degree of each source. This study referred to the research results of Xiao et al. (1993). Cl^- and Ca²⁺ were selected as reference elements in the ocean and soil, respectively (Wang et al., 2015; Lu et al., 2017). The formulas are as follows:

(1)$\text{E}{{\text{F}}_{\text{sea}}}\text{=}\frac{{{\left[ X\text{/C}{{\text{l}}^{\text{--}}} \right]}_{\text{sample}}}}{{{\left[ X\text{/C}{{\text{l}}^{\text{--}}} \right]}_{\text{sea}}}}$,

(2)$\text{E}{{\text{F}}_{\text{soil}}}\text{=}\frac{{{\left[ X\text{/C}{{\text{a}}^{\text{2+}}} \right]}_{\text{sample}}}}{{{\left[ X\text{/C}{{\text{a}}^{\text{2+}}} \right]}_{\text{soil}}}}$,

where X is chemical ion concentration (μeq/L) in water samples; [X/Cl^-]_sample is the equivalent ratio of ion concentration to Cl^- concentration in water samples; [X/Ca²⁺]_sample is the equivalent ratio of ion concentration to Ca²⁺ concentration in water samples; and [X/Cl^-]_sea and [X/Ca²⁺]_soilare the background values of sea and soil, respectively.

The end-member contribution method can identify and quantify potential ion sources in water bodies (Lu et al., 2017), and the three fractions can be calculated: sea salt fraction (SSF; %), soil/rock weathering fraction (CF; %), and anthropogenic fraction (AF; %). Taking precipitation as an example, the formulas are as follows:

(3)$\text{SSF=}\frac{{{\left[ X\text{/C}{{\text{l}}^{\text{--}}} \right]}_{\text{sea}}}}{{{\left[ X\text{/C}{{\text{l}}^{\text{--}}} \right]}_{\text{sample}}}}\times \text{100 }\!\!%\!\!\text{ }$,

(4)$\text{CF=}\frac{{{\left[ X\text{/C}{{\text{a}}^{\text{2+}}} \right]}_{\text{soil}}}}{{{\left[ X\text{/C}{{\text{a}}^{\text{2+}}} \right]}_{\text{sample}}}}\times \text{100 }\!\!%\!\!\text{ }$,

(5)$\text{AF}=100%-\text{SSF}-\text{CF}$.

3 Results and discussion

3.1 Spatial variations in pH, TDS, and EC of different water bodies

The water resources in the western alpine region of China are generally weakly alkaline, with pH ranging from 5.50 to 9.87 (Fig. 2a). The pH ranges of river water, meltwater, groundwater, and precipitation are 6.50-9.87, 5.50-8.94, 6.31-9.32, and 5.90-8.20, respectively. The mean pH values of river water, meltwater, groundwater, and precipitation are 7.92, 7.58, 7.72, and 7.32, respectively. The only weakly acidic samples are those from the meltwater in the source area of the Ertix River Basin (Wei et al., 2016), precipitation in the source area of the Yangtze River Basin (Li et al., 2020c), and river water in the Lancang River Basin (Zhou et al., 1996). Previous studies have shown that the average pH is approximately 6.60 in the source area of the Yangtze River Basin (Pu et al., 1988; Wang et al., 2019b). The range of TDS in water resources is 2.10-2996.34 mg/L (Fig. 2b), showing considerable fluctuations in the range. Generally speaking, salinity is relatively low when the TDS is less than 1000.00 mg/L. The TDS contents of river water, meltwater, precipitation and groundtwater are less than 100.00 mg/L in most basins of the study area, and the water samples are classified as low-salinity waters (Zhu et al., 2010; Feng et al., 2011; Pu et al., 2011; Li et al., 2018c; Bao, 2019; Liu et al., 2020c). In the study area, groundwater has the highest average TDS (544.41 mg/L), followed by river water (280.99 mg/L), meltwater (72.48 mg/L) and precipitation (67.68 mg/L) show the lowest average TDS. The TDS of groundwater and river water in the Ertix, Heihe, Shiyang, and Shule river basins and the source area of the Yellow River Basin has been observed to increase with an increase in runoff (Zhu et al., 2010; Wang et al., 2014; LYU, 2017; Li et al., 2018b; Gao et al., 2019; Zhang and Song, 2020; Meng, 2021), whereas the TDS of river water in main streams of the Yalong River Basin and Nagqu River Basin shows a decreasing trend with an increase in runoff (Li et al., 2014a; Wang et al., 2019a). The EC of water can be used to determine the amount of TDS in a water source. As the concentration of dissolved solids increases, TDS increases accordingly, resulting in a higher conductivity in water (Wei et al., 2010b; Gu et al., 2017). As shown in Figure 2d, a significant positive correlation between EC and TDS of water resources in the study area can be observed, with coefficient of determination (R²) of 0.83 and slope of 1.53.

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Fig. 2 Spatial distributions of pH (a), TDS (b), and EC (c), as well as fitting relationship between TDS and EC (d) of different water bodies. TDS, total dissolved solids; EC, electrical conductivity.

3.2 Spatial and temporal variations in hydrochemistry of different water bodies

The hydrochemical characteristics of water resources in the study area show seasonal fluctuations (Wu et al., 2008). Typically, the concentrations of chemical ions are lower during the ablation period for river water, meltwater, groundwater, and precipitation (Xu, 2016; Labaciren, 2017; Li et al., 2018c; Yang et al., 2018; Zhu et al., 2018; Shi et al., 2021). This is mainly attributed to the rise in temperature and increase in precipitation during the ablation period, which initially lead to a decrease in the ion concentrations of precipitation. Subsequently, the increase in glacial and snow meltwater contributes to a reduction in the ion concentrations of meltwater. With the combined increase in precipitation and meltwater, the concentrations of chemical ions in river water are diluted, and the interconversion between surface water and groundwater further diminishes the ion concentrations of groundwater (Li et al., 2016b; Webb et al., 2018). However, in the early stage of melting, when glaciers and snow begin to melt, large amounts of dust and chemical substances are released into runoff, which can also lead to an increase in the ion concentrations of river water. At this time, the temporal variation in the chemical ion concentrations of river water depends on the dilution intensity of precipitation and meltwater, as well as the intensity of chemical ion released by meltwater (Yang et al., 2021). The reduction in ablation leads to a significant decrease in runoff and a decrease in volume and frequency of precipitation that is laden with a large amount of suspended particles, thereby increasing the ion concentrations of precipitation (Li et al., 2016b, 2017a). During the freezing period, the gradual decrease in temperature, the reduction in ablation, and the effects of evapotranspiration lead to an increase in the concentrations of ions in glacial and snow meltwater (Chang, 2019). In spring and winter, the increasing trend in the ion concentrations of precipitation is influenced by meteorological events such as sand and dust storms (Dong et al., 2014; Li et al., 2016a). Different recharge modes of hydrological processes during various periods also result in spatial differences in chemical ion concentrations of different water bodies. For instance, the hydrochemistry of the Binggou River in the Shiyang River Basin is primarily affected by meltwater and groundwater before and after the rainy season, while precipitation has a greater impact during the rainy season (Xiang, 2020).

Ion concentrations of different water bodies vary considerably, along with significant spatial differences (Meybeck, 2003). Figure 3 shows the variations in the concentrations of different ions in precipitation in different river basins. The average total ion concentrations of precipitation are lower than 20.00 mg/L in the source area of the Heihe River Basin (9.21 mg/L), source area of the Shiyang River Basin (15.24 mg/L), source area of the Yarlung Zangbo River Basin (9.14 mg/L), source area of the Yangtze River Basin (18.66 mg/L), Baishui River Basin (2.96 mg/L), and source area of the Urumqi River Basin (13.68 mg/L). The total ion concentration in precipitation is the highest in the source area of the Shule River Basin, primarily due to the frequent occurrence of dust weather in the basin, which significantly increases the total ion concentration of precipitation (Yu and Zhao, 2017). Ca²⁺ concentration accounts for the highest proportion of the total cation concentration of precipitation in the study area, ranging between 47.41% (source area of the Shiyang River Basin) and 79.49% (source area of the Tarim River Basin). HCO₃^- concentration accounts for the highest proportion of the total anion concentration in the source area of the Urumqi River Basin, source area of the Tarim River Basin, source area of the Shiyang River Basin, source area of the Shule River Basin, source area of the Yarlung Zangbo River Basin, source area of the Yangtze River Basin, source area of the Yellow River Basin, and Baishui River Basin, accounting for 71.64%, 76.69%, 82.01%, 66.20%, 80.68%, 70.68%, 84.90%, and 45.97%, respectively. The higher concentrations of HCO₃^-and Ca²⁺ in precipitation indicate the greater influence of crustal dust on the concentrations of chemical ions in precipitation in the river basins. The main anions in the Heihe River Basin are NO₃^- (ion concentration of 2.93 mg/L), Cl^- (2.43 mg/L), and SO₄^2- (1.42 mg/L). The reason for the higher NO₃^- concentration may be attributed to the influence of human activities and the unestimated HCO₃^- concentration (Li et al., 2015a).

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Fig. 3 Variations in the concentrations of Ca²⁺ (a), Na⁺ (b), Mg²⁺ (c), K⁺ (d), HCO₃^- (e), SO₄^2- (f), Cl^- (g), and NO₃^- (h) in precipitation in different river basins. URB, Urumqi River Basin; HRB, Heihe River Basin; SYRB, Shiyang River Basin; SLRB, Shule River Basin; YZRB, Yarlung Zangbo River Basin; YARB, Yangtze River Basin; YERB, Yellow River Basin; TRB, Tarim River Basin; BSRB, Baishui River Basin. Box boundaries indicate the 25^th and 75^th percentiles, and whiskers below and above the box indicate the minimum and maximum, respectively. The black horizontal line within each box indicates the median. The solid red dot indicates the mean.

The variations in the concentrations of different ions in meltwater in different river basins are shown in Figure 4, indicating that different ion sources and dissolution processes of glaciers and snow in different regions cause differences in the ion concentrations of meltwater (Li et al., 2015b). Meltwater is another form of precipitation recharge. Similar to precipitation, the ion concentrations of meltwater were generally low. The ion concentrations of meltwater range from 0.86 to 434.42 mg/L in the study area. The average cation and anion concentrations of meltwater in the Shule River Basin are the highest at 110.41 and 324.01 mg/L, respectively. This is primarily due to the significant influence of terrestrial minerals in the dust source region of Asia on the glacial and snow meltwater in this region (Dong et al., 2013). The average cation and anion concentrations of meltwater in the Kuytun River Basin are the lowest at 0.25 and 0.26 mg/L, respectively. This is attributed to the relatively high altitude of the sampling points in this region, where marine water vapor brought by the westerlies is the main source of meltwater, resulting in a lower concentration of chemical ions (Dong et al., 2010). Ca²⁺ is the major cation in meltwater in the study area, ranging between 42.84% (Shiyang River Basin) and 89.79% (source area of the Yangtze River Basin), which indicates that the dissolution of calcite, dolomite, and other carbonate rocks will release more Ca²⁺ in the study area (Ma et al., 2023). HCO₃^- is the major anion in meltwater in the source areas of the Tarim River Basin, Heihe River Basin, Shule River Basin, and Urumqi River Basin, whereas SO₄^2- is the major anion in meltwater in the Shiyang River Basin, Rongbuk River Basin, and Kuytun River Basin, and SO₄^2- is mainly from soil/dust sources, such as sulphate rock (Wang et al., 2016). In general, the concentrations of NH₄⁺ and NO₃^- in meltwater samples can reflect the impact of human activities on hydrochemistry (Wang et al., 2016; Wei et al., 2016). The average NO₃^- concentration of meltwater is the highest in the Ertix River Basin, the source area of the Yarlung Zangbo River Basin, source area of the Yangtze River Basin, source area of the Yellow River Basin, and Ili River Basin, indicating anthropogenic interference. In addition, the anion concentrations of meltwater in source area of Urumqi River Basin, the Tarim River Basin, Heihe River Basin, and Shule River Basin show the same characteristics, that is, HCO₃^->SO₄^2->Cl^->NO₃^-, which indicates similarities in the hydrochemistry of the inland river basins.

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Fig. 4 Variations in the concentrations of Ca²⁺ (a), Na⁺ (b), Mg²⁺ (c), K⁺ (d), HCO₃^- (e), SO₄^2- (f), Cl^- (g), and NO₃^- (h) in meltwater in different river basins. ERB, Ertix River Basin; IRB, Ili River Basin; KRB, Kuytun River Basin. Box boundaries indicate the 25^th and 75^th percentiles, and whiskers below and above the box indicate the minimum and maximum, respectively. The black horizontal line within each box indicates the median. The solid red dot indicates the mean.

The variations in the concentration of different ions in river water in different river basins are shown in Figure 5. The average concentrations of Ca²⁺, Na⁺, Mg²⁺, K⁺, HCO₃^-, Cl^-, SO₄^2-, and NO₃^- range from 8.01 to 76.63 mg/L, 1.01 to 132.39 mg/L, 0.90 to 36.27 mg/L, 0.72 to 4.83 mg/L, 13.18 to 177.51 mg/L, 0.28 to 176.40 mg/L, 6.08 to 240.10 mg/L, and 0.03 to 7.15 mg/L, respectively. The total concentrations of cations and anions are highest in river water of the Shule River Basin (241.64 and 584.01 mg/L, respectively). The total concentrations of cations and anions of river water in the source area of the Yangtze River Basin (173.85 and 367.65 mg/L, respectively) are lower than those in the Shule River Basin. The total concentrations of cations and anions are the lowest in river water of the source area of Urumqi River Basin (16.85 and 49.43 mg/L, respectively). Ca²⁺ is the major cation in in river water in the study area (Hu, 2019; Liu et al., 2020a; Wang et al., 2021a; Zhang et al., 2021b; Xie et al., 2024), while Na⁺ dominates the cations in river water in the Shule River Basin (54.79%), source area of the Yangtze River Basin (58.73%), and Jinsha River Basin (55.17%) (Yang et al., 2021; Yuan et al., 2021; Li et al., 2023). Na⁺ is mainly derived from rock salt or groundwater mineral recharge (Qu et al., 2015). However, the characteristics of dominant ions may also change with time. For example, the dominant cation in river water samples collected in 2020 is Ca²⁺ in the source area of the Jinsha River Basin, which is mainly derived from weathering of carbonate rocks (Kang and Li, 2023).

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Fig. 5 Variations in the concentrations of Ca²⁺ (a), Na⁺ (b), Mg²⁺ (c), K⁺ (d), HCO₃^- (e), SO₄^2- (f), Cl^- (g), and NO₃^- (h) in river water in different river basins. NRB, Nujiang River Basin; JRB, Jinsha River Basin; MRB, Minjiang River Basin; YLRB, Yalong River Basin; LCRB, Lancang River Basin; RBRB, Rongbuk River Basin. Box boundaries indicate the 25^th and 75^th percentiles, and whiskers below and above the box indicate the minimum and maximum, respectively. The black horizontal line within each box indicates the median. The solid red dot indicates the mean.

The variation characteristics of the chemical ion concentrations of groundwater are primarily influenced by the geological type of the flow-through area and groundwater depth with horizontal zonation, and the concentrations gradually decrease with increasing groundwater depth (Ma et al., 2005; Bai and Yang, 2007; LYU, 2017; Miao et al., 2020). The chemical ion concentrations of groundwater are generally higher than those of other water bodies. Figure 6 shows the variation in the concentrations of different ions in groundwater in different river basins. The highest total ion concentration of groundwater is observed in the Tarim River Basin (1095.80 mg/L), mainly because runoff and groundwater of the Tarim River Basin are replenished by numerous rivers (Wang et al., 2021e). In addition, the vegetation in the Tarim River Basin is sparse, and the overall purification and adsorption effect on groundwater is low (Ma et al., 2021). In contrast, the groundwater in the the Yarlung Zangbo River Basin has the lowest observed total ion concentration (262.68 mg/L). The Yarlung Zangbo River Basin mainly has plateau climate, with runoff predominantly sourced from alpine meltwater and precipitation. Moreover, there are abundant vegetation types in the basin. The order of cation concentrations in the Heihe River Basin and Shiyang River Basin is Ca²⁺>Na⁺>Mg²⁺>K⁺ (Yang, 2017; Xie et al., 2024). The order of cation concentrations of groundwater in the Tarim River Basin, source area of the Yangtze River Basin, and source area of the Yellow River Basin is Na⁺>Ca²⁺>Mg²⁺>K⁺ (Li et al., 2018c; Li et al., 2020b; Wang et al., 2021e). The average concentrations of Na⁺, Mg²⁺, and Ca²⁺ in groundwater of the Shule River Basin are close and account for 32.96%, 32.52%, and 32.22%, respectively (Wang et al., 2015). The average anion concentrations of groundwater in the Heihe River Basin, Shule River Basin, Yarlung Zangbo River Basin, and source area of the Yellow River Basin are in the order of HCO₃^->SO₄^2->Cl^->NO₃^- (Wang et al., 2015; Zhang et al., 2018a; Ma, 2019; Li et al., 2020b; Xie et al., 2024). The anion concentration order of groundwater in the Shiyang River Basin is SO₄^2->Cl^->HCO₃^->NO₃^- (Ma et al., 2021). The anion concentration order of groundwater in the source area of the Yangtze River Basin is Cl^->SO₄^2->HCO₃^->NO₃^- (Li et al., 2018c). The NO₃^-concentration of groundwater in the study area is low with proportion of less than 7.00%, indicating the groundwater has less human influence (Deng et al., 2007).

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Fig. 6 Variations in the concentrations of Ca²⁺ (a), Na⁺ (b), Mg²⁺ (c), K⁺ (d), HCO₃^- (e), SO₄^2- (f), Cl^- (g), and NO₃^- (h) in groundwater in different river basins. Box boundaries indicate the 25^th and 75^th percentiles, and whiskers below and above the box indicate the minimum and maximum, respectively. The black horizontal line within each box indicates the median. The solid red dot indicates the mean.

3.3 Hydrochemical type of different water bodies

The hydrochemical types of different water bodies in the study area are shown in Figure 7. Precipitation is an important water source in the study area. Precipitation not only maintains seasonal runoff (Lan et al., 2010), but also has a significant impact on the variations in the ion concentrations of various water bodies. The pH and concentrations of K⁺, Cl^-, Na⁺, SO₄^2-, and NO₃^- exhibit complex fluctuations with changes in precipitation (Shi et al., 2015). Figure 7a shows that Ca²⁺ is the dominant cation in precipitation, and the dominant anion is SO₄^2-, followed by HCO₃^-. The hydrochemical type of precipitation is HCO₃^--Ca²⁺ in the Tarim River Basin and the permafrost area of the Qinghai-Xizang Plateau of China (Sun et al., 2002; Liu et al., 2004; Ma et al., 2012; Li et al., 2020c; Yu and Zhao, 2017).

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Fig. 7 Piper diagram showing hydrochemical types of precipitation (a), meltwater (b), river water (c), and groundwater (d) in different river basins

Glacial and snow meltwater is the second-most important water source in the study area. In the context of global warming, glaciers are melting at an accelerated rate and are in a negative equilibrium state, and glacial meltwater runoff becomes the main source of supply for several major rivers (Pu, 2015; Li et al., 2020a). The retreat of glaciers has intensified the water cycle in the study area (Wang et al., 2011). The hydrochemical type of meltwater in the study area is dominated by HCO₃^-•SO₄^2--Ca²⁺ (Fig. 7b), and the main hydrochemical type of meltwater is SO₄^2--Ca²⁺ in the source area of the Urumqi River Basin and Ili River Basin (Li et al., 2011b; Zhao, 2012; Wei et al., 2016; Li, 2018; Ma et al., 2021). The hydrochemical types of meltwater in the study area are basically the same as those in the Qinghai-Xizang Plateau and surrounding areas during 2008-2010 (Zhang et al., 2016).

Rivers are the primary components of the water cycle and are important surface water resources. The river environment is an important part of the ecological environment (Birol et al., 2008), and river hydrochemistry can reflect local water quality (Li et al., 2022). Figure 7c shows that the river water in the study area is characterized by alkaline earth metals and weak acidity. The dominant cation is Ca²⁺, the dominant anion is HCO₃^-, and the dominant anion is SO₄^2- in some river basins. HCO₃^--Ca²⁺ is the dominant hydrochemical type of river water in the source area of the Ertix River Basin, Tarim River Basin, Yarlung Zangbo River Basin, source area of the Yangtze River Basin, source area of the Yellow River Basin, Nujiang River Basin, Lancang River Basin, Yalong River Basin, and Minjiang River Basin (Huang et al., 2011; Li et al., 2014a; Tao et al., 2015; Wei et al., 2016; Li, 2018; Liu et al., 2019; Liu et al., 2020a; Wang et al., 2021a). Besides, HCO₃^--Ca²⁺ is also the dominant hydrochemical type in the alpine regions of the world, such as the upper Indus River Basin in China, and Koshi River Basin in China and Nepal (Bhat et al., 2023; Bishwakarma et al., 2024). The main hydrochemical type of river water is HCO₃^-•SO₄^2--Ca²⁺ in the source area of the Urumqi River Basin and Rongbuk River Basin (Liu et al., 2000; Feng et al., 2011). The main hydrochemical type of river water in the Jinsha River Basin is Cl^--Na⁺ (Yuan et al., 2021). HCO₃^-•SO₄^2--Ca²⁺•Mg²⁺ is the main hydrochemical type of river water in the Heihe River Basin (Zhu et al., 2008; Yang et al., 2011; Feng et al., 2017; Li et al., 2017a). The hydrochemical type of river water in the Shiyang River Basin is dominated by strong acid, whereas the upstream hydrochemical type is HCO₃^-•SO₄^2--Ca²⁺, and the hydrochemical type changed with the increase of runoff (Yang, 2017). The hydrochemical types of river water are mainly HCO₃^-•Cl^--Ca²⁺•Mg²⁺and HCO₃^-•Cl^--Ca²⁺•Mg²⁺•Na⁺ in the Shule River Basin (Zhou et al., 2004).

Groundwater has emerged as a significant source of potable water owing to its widespread distribution and high resistance to contamination (Zhang et al., 2021a). Groundwater security affects the health and stable development of human society (Li, 2021; Li et al., 2021). In the study area, the cations in groundwater are mainly composed of Mg²⁺ and Ca²⁺, whereas the anions are mainly composed of HCO₃^- and SO₄^2- (Fig. 7d), which are consistent with the findings in the high altitude and high mountain areas of Austria (Strauhal et al., 2016). HCO₃^--Ca²⁺•Mg²⁺ and SO₄^2-•Cl^--Na⁺ dominate in the hydrochemical type of groundwater in the upper reaches of the Heihe River Basin (Ma, 2019). HCO₃^-•SO₄^2--Ca²⁺•Mg²⁺ is the main hydrochemical type of groundwater in the recharge area of the Shiyang River Basin, Shule River Basin, and Yarlung Zangbo River Basin (Wang et al., 2014; Liu et al., 2020c; Zhang and Song, 2020). The main hydrochemical type of groundwater is Cl^-•SO₄^2--Ca²⁺•Na⁺ in the frozen soil layer of the source area of the Yangtze River Basin, and it is affected by altitude (Li et al., 2018c). HCO₃^--Ca²⁺ dominates in the hydrochemical type of groundwater in the source area of the Yellow River Basin (Wang et al., 2021f). HCO₃^--Ca²⁺•Mg²⁺ is the main hydrochemical type of groundwater in the northern Nagqu River in the source area of the Nujiang River Basin (Zhao, 2020).

3.4 Ion source analysis of different water bodies

3.4.1 Factors controlling the hydrochemical characteristics of different water bodies

The sources of chemical ions in precipitation typically include terrigenous material supply, sea salt aerosol transfer, anthropogenic influences, and climate change (Sun et al., 2002; Liu et al., 2004; Ma et al., 2012; Li et al., 2017a, 2020c; Yu and Zhao, 2017). Most existing studies have used the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model to determine the sources of water vapor and chemical ions in precipitation (Li et al., 2015a; He et al., 2019). For example, the majority of air masses reaching the Qilian Mountains in China originate from the west and traverse desert areas, whereas some monsoon air masses originate from the Indian Ocean and other sea areas (Wang et al., 2016). Water vapor in the Shiyang River Basin is influenced by monsoon precipitation, westerly precipitation, and local water vapor cycle (He et al., 2019; Zhang et al., 2020). Seasonal variations exist in the sources of ions in the Shule River Basin, with Na⁺ typically dominated by inputs from marine sources, but originating from land in winter (Zhao, 2017). A study of the source area of the Yangtze River Basin reveals that the water vapor sources exhibit seasonal variations and altitude effects (Li et al., 2020c). In the source area of the Urumqi River Basin, local climatic factors and human activities have a significant influence on the ion concentration of precipitation, followed by the influence of the ocean or surrounding salt lakes (Hou, 2001). In the Tarim River Basin, 85.54% of the precipitation ions are recharged by crustal sources, with only 4.87% being recharged by marine sources, and the chemical composition is significantly influenced by the westerly circulation (Wang et al., 2021a). Consequently, the chemical composition of precipitation is influenced by different atmospheric circulation backgrounds and air mass sources (Wang et al., 2019b).

The ions in river water in the study area are primarily derived from the combined effects of rock weathering and evaporative crystallization (Fig. 8a). Additionally, in the source area of the Ertix River Basin and Shule River Basin, the ions in river water are more susceptible to the combined effects of rock weathering and atmospheric precipitation (Su and Tang, 1987; Deng, 1988; Wang et al., 2010; Li et al., 2014b; Wei et al., 2016; Wang et al., 2019a; Zhao et al., 2020; Wang et al., 2021f). The ion composition and concentration of meltwater in the study area are mainly affected by rock weathering and atmospheric precipitation (Fig. 8b), and the chemical formation process of meltwater has undergone adsorption, dissolution, and precipitation (Li et al., 2015b). Besides, the ion composition and concentration of meltwater are also influenced by evaporative crystallization in some regions, such as the Shule River Basin and the Yuzhu Peak Glacier in Kunlun Mountains (Song et al., 2019; Yang et al., 2021). In addition, the melting speed of glaciers and snow can also influence the ion concentration of meltwater (Li et al., 2019b). In the circulating flow process, groundwater has undergone a series of chemical reactions with chemical substances and mineral components in the aquifer medium that determine the formation and evolution of its chemical components (Yu et al., 2021). The hydrochemical type of groundwater in the study area is mainly affected by the dissolution of salt, weathering, and evaporation (Fig. 8c), and it is affected by the weathering of rock salt in the Yarlung Zangbo River Basin. The determination of groundwater hydrochemistry is complicated under the influence of natural factors such as aquifer lithology, geological formations, and human activities (Liu et al., 2020b). Therefore, chemical weathering of rock salts is an important source of chemical ions in water and is a key link between the lithosphere, hydrosphere, and atmosphere, and between terrestrial and oceanic cycles (Balagizi et al., 2015). This characteristic effect of rock weathering on hydrochemistry could be seen in the Chena River in the United States and the Gangotri Glacier in India (Douglas et al., 2013; Ahmad and Ansari, 2020).

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Fig. 8 Gibbs diagrams showing the hydrochemical formation process of river water (a), meltwater (b), and groundwater (c) in different river basins

3.4.2 Influence of rock types on hydrochemistry of different water bodies

The principal rock types of meltwater in the study area are carbonate rock and silicate rock, and evaporite rock (sulfuric acid rock) is present at some sampling sites (Fig. 9a) (He et al., 2019; Song et al., 2019). The principal rock types of river water are mainly carbonate rock and evaporite rock (Fig. 9b), which are mainly composed of chlorinated sedimentary rocks and sulfate minerals. The chemical ion sources in the source area of the Yellow River is also affected by silicate rock, and the contribution of rock weathering to chemical ions is more evident during the wet season (Xia et al., 2000; Zhou et al., 2004; Yang et al., 2011; Zhang et al., 2017; Bao, 2019; Liu et al., 2019; Li et al., 2020b; Ma et al., 2021; Renzeng et al., 2021; Wang et al., 2021c; Wang et al., 2021f). The hydrochemical type of groundwater is affected by the weathering and dissolution of the surrounding salt rocks (dominated by carbonate rocks) (Fig. 9c), such as the dissolution of calcite and dolomite. In the middle and lower reaches of the river basins in the study area, human activities are more intensive under the influence of industry and agriculture (Shi et al., 2001; Zhu et al., 2010; Guo et al., 2015; Liu et al., 2020c; Meng, 2021; Wang et al., 2021f).

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Fig. 9 End-member diagrams determining the rock types of river water (a), meltwater (b), and groundwater (c) in different river basins

3.4.3 Correlations between chemical ions in different water bodies

The Pearson correlation coefficient between ions reflects the material origin of the ions and the characteristics of their chemical reaction (Başak and Alagha, 2004). As shown in Figure 10, the TDS and EC of precipitation, meltwater, river water, and groundwater exhibit significant positive correlations with ion concentrations (P<0.01) (Zhang et al., 2018b). The high positive correlation between ions indicates that the sources and forms of ions are consistent (Wang et al., 2019b). For precipitation ions, the correlation coefficients between Cl^- and Na⁺, Cl^- and Ca²⁺, and Cl^- and SO₄^2- are all above 0.80 (Fig. 10a), which is consistent with the enrichment factor analysis. This correlation analysis between ions in precipitation broadly encapsulates the ion correlation conclusions across various basins in the study area. For example, the correlations of Ca²⁺ with Na⁺ and K⁺ with Mg²⁺ in precipitation in the Shiyang River Basin are significant, which are mainly attributed to the contribution of crustal sources; meanwhile, Cl^- and Na⁺ might be derived from marine sources, soil dust aerosols, and human activities (Ma et al., 2012). In the source area of the Yangtze River Basin, there is a significant positive correlation among Na⁺, Ca²⁺, and Mg²⁺ in precipitation, and Cl^- is significantly positively correlated with Ca²⁺, Mg²⁺, and K⁺, while SO₄^2- is significantly positively correlated with other ions, indicating that Na⁺, Cl^-, and SO₄^2- in precipitation in this region are controlled by multiple sources (Li et al., 2020c).

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Fig. 10 Correlation coefficients between ions in precipitation (a), meltwater (b), river water (c), and groundwater (d). ^* indicates that the correlation is significant at P<0.001 level; ^ indicates that the correlation is significant at P<0.01 level; ^* indicates that the correlation is significant at P<0.05 level.

The ion correlation of meltwater is shown in Figure 10b. The correlation coefficient between Cl^- and Na⁺ is the highest (0.75); the correlation coefficients of SO₄^2- with Mg²⁺, K⁺, and HCO₃^- are above 0.70; and the correlation coefficients of K⁺ with Ca²⁺, HCO₃^-, and SO₄^2- are 0.74, 0.78, and 0.72, respectively. The sources of these chemical ions include dolomite, silicates, carbonates, and evaporites. Furthermore, Na⁺ is significantly correlated with HCO₃^-, with a correlation coefficient of 0.74. This correlation analysis between ions in meltwater can basically reflect the regional characteristics, demonstrating the universal applicability of the research findings. There is a significant correlation between cations in meltwater of Huohugou No.12 Glacier in the Qilian Mountains and Hasilegen No.51 Glacier in the Kuytun River Basin in the Tianshan Mountains of China (Dong et al., 2010, 2013). Additionally, a significant correlation is observed between EC (or TDS) and other ions (Song et al., 2019). In the source area of the Urumqi River Basin, a significant correlation between Ca²⁺ and SO₄^2- in meltwater is likely influenced by the crustal dust minerals in the dust source area of Central Asia, and there is also a good correlation between EC and pH (Li et al., 2011b). Furthermore, a significant correlation between SO₄^2- and Mg²⁺ is found in meltwater of the Glacier No.72 of Qingbingtan, Tomur Peak, Tianshan Mountains (Zhao et al., 2012). In the Qilian Mountains, Cl^- is mainly derived from sea salt, soil dust, and saline lake materials, while Na⁺ is mostly from marine sources (Dong et al., 2013; Wang et al., 2016).

The ion correlation of river water is shown in Figure 10c. Cl^- is significantly positively correlated with Na⁺ and K⁺, with correlation coefficients of 0.83 and 0.77, respectively. A significant positive correlation is observed between SO₄^2- and Ca²⁺, with a correlation coefficient of 0.86. HCO₃^- is positively correlated with Ca²⁺, Na⁺, and K⁺ (P<0.001), indicating the weathering of carbonate rocks. The correlation coefficient between K⁺ and Na⁺ is 0.67. Mg²⁺ is positively correlated with K⁺, SO₄^2-, Cl^-, Na⁺, and Ca²⁺ (P<0.001). This correlation analysis between ions in river water of the study area is consistent with the research conclusion for each river basin. In the Yarlung Zangbo River, TDS is positively correlated with Ca²⁺, Mg²⁺, K⁺, Na⁺, HCO₃^-, Cl^-, and SO₄^2-, indicating that these constituents are the sources of TDS. Due to the weathering dissolution of carbonates and sulfate minerals, SO₄^2- is also significantly correlated with Ca²⁺ and Mg²⁺, while Na⁺, K⁺, and Cl^- might be derived from the dissolution of evaporite rocks (Liu et al., 2018). Na⁺, K⁺, and Cl^- in river water of the Ertix River Basin are generally derived from atmospheric precipitation, weathering dissolution of evaporite, and anthropogenic input (Liu et al., 2020a). There is a significant correlation between Ca²⁺ and HCO₃^-, and a significant correlation among Mg²⁺, Na⁺, and K⁺ in river water of the source area of the Nujiang River Basin (Zhao et al., 2020). Furthermore, a significant positive correlation exists between ions in river water of the Yellow River Basin (He et al., 2017).

There is a significant positive correlation between ions in groundwater (P<0.001), and the correlation coefficients between Cl^- and Na⁺, Ca²⁺ and SO₄^2-, and Mg²⁺ and HCO₃^- are all above 0.80 (Fig. 10d). The changes of TDS in groundwater in the Shule River Basin are mainly related to Na⁺ and SO₄^2-, reflecting a correlation between ions (Guo et al., 2015). HCO₃^-, Ca²⁺, SO₄^2-, and Mg²⁺ contribute significantly to the TDS in groundwater in the Lhasa River Basin of the Yarlung Zangbo River Basin, indicating that rock weathering plays a dominant role in hydrochemical evolution (Zhang et al., 2018a). Ca²⁺ in the suprapermafrost water of the source area of the Yangtze River Basin is significantly positively correlated with Mg²⁺, K⁺, Na⁺, SO₄^2-, Cl^-, and F^-, indicating that they may have a common source, and SO₄^2- and Cl^- are mainly derived from evaporite dissolution (Li et al., 2018c). The TDS in groundwater of the source area of the Yellow River Basin is positively correlated with HCO₃^-, Ca²⁺, and Mg²⁺, indicating that carbonate karst hydrolysis is the main source of the chemical components of groundwater (Wang et al., 2021f). In the Heihe River Basin, HCO₃^- and Mg²⁺ in groundwater might be derived from dolomite weathering, while Ca²⁺ and SO₄^2- are derived from gypsum, dolomite, and surface water leaching (Zhu et al., 2010).

3.4.4 Quantification of hydrochemical ion sources

As shown in Table 2, Ca²⁺, Mg²⁺, K⁺, and HCO₃^- in precipitation, meltwater, river water, and groundwater are typical crustal source ions, respectively. Notably, for Ca²⁺ and HCO₃^-, the contributions of non-marine sources exceed 99.00%, while the contribution rates of non-marine sources are 96.75%-98.65% for K⁺. For Mg²⁺ in meltwater, river water, and groundwater, the anthropogenic contribution could be clearly quantified, but crustal sources are still the main sources. The contribution of crustal sources for Mg²⁺ in meltwater is 78.98% and the anthropogenic contribution is 17.96%. The crustal contribution for Mg²⁺ in river water is 76.31% and the anthropogenic contribution is 23.14%. In groundwater, the crustal and anthropogenic contributions for Mg²⁺ are 48.56% and 50.15%, respectively. The sources and their contributions for Ca²⁺, Mg²⁺, K⁺, and HCO₃^- are basically consistent with the conclusions in terrestrial ecosystem areas and typical karst valley areas in China (Huang et al., 2019). As an ocean indicator, the sources of Cl^- is mainly sea salt and water vapor under the action of atmospheric circulation, and the contribution of crustal sources is less. There is a significant correlation between Na⁺ and Cl^- (Fig. 10), but the ratio of Na⁺ to Cl^- is high, and the ratios for precipitation, meltwater, river water, and groundwater are 1.97, 2.12, 12.48, and 4.45, respectively, indicating that there are other sources of Na⁺ besides marine sources, such as rock weathering and other crustal sources (Li et al., 2024). The EF_sea and EF_soil of SO₄^2- and NO₃^- are greater than 1.00, indicating that SO₄^2- and NO₃^- are enriched compared to the ocean and soil. The anthropogenic contributions for SO₄^2- and NO₃^- can reach more than 88.05%, but the remote and local contributions to SO₄^2- and NO₃^- through atmospheric circulation trapping and crustal dust cannot be ignored. For example, increased NO₃^- concentration in the Chena River in the United States is also associated with precipitation events (Douglas et al., 2013).

Table 2 Analysis of enrichment factors and contribution rate of ion sources

Precipitation	EF_sea	EF_soil	SSF (%)	NSSF (%)
Precipitation	EF_sea	EF_soil	SSF (%)	CF (%)	AF (%)
Ca²⁺	167.26	-	0.60	99.40
Na⁺	2.29	0.75	43.73	56.27
Mg²⁺	6.33	0.57	15.79	84.21
K⁺	74.19	0.46	1.35	98.65
Cl^-	-	176.56	-	0.57	-
SO₄^2-	44.88	100.49	2.23	1.00	96.77
HCO₃^-	471.60	-	0.21	99.79
NO₃^-	126,773.29	533.15	0.00	0.19	99.81
Meltwater	EF_sea	EF_soil	SSF (%)	NSSF (%)
Meltwater	EF_sea	EF_soil	SSF (%)	CF (%)	AF (%)
Ca²⁺	855.90	-	0.12	99.88
Na⁺	2.46	0.44	40.57	59.43
Mg²⁺	32.68	1.27	3.06	78.98	17.96
K⁺	30.75	0.22	3.25	96.75
Cl^-	-	132.13	-	0.76	-
SO₄^2-	68.59	85.12	1.46	1.17	97.37
HCO₃^-	6966.36	-	0.01	99.99
NO₃^-	41,611.80	44.27	0.00	2.26	97.74
River water	EF_sea	EF_soil	SSF (%)	NSSF (%)
River water	EF_sea	EF_soil	SSF (%)	CF (%)	AF (%)
Ca²⁺	942.58	-	0.11	99.89
Na⁺	14.51	1.37	6.89	73.22	19.89
Mg²⁺	180.67	1.31	0.55	76.31	23.14
K⁺	52.28	0.08	1.91	98.09
Cl^-	-	246.26	-	0.41	-
SO₄^2-	546.29	47.18	0.18	2.12	97.70
HCO₃^-	4779.42	-	0.02	99.98
NO₃^-	18,533.28	8.38	0.01	11.94	88.05
Groundwater	EF_sea	EF_soil	SSF (%)	NSSF (%)
Groundwater	EF_sea	EF_soil	SSF (%)	CF (%)		AF (%)
Ca²⁺	694.87	-	0.14	99.86
Na⁺	4.45	0.97	22.45	77.55
Mg²⁺	77.32	2.06	1.29	48.56	50.15
K⁺	31.58	0.04	3.17	96.83
Cl^-	-	193.86	-	0.52	-
SO₄^2-	179.43	50.60	0.56	1.98	97.46
HCO₃^-	5760.10	-	0.02	99.98
NO₃^-	23,998.65	13.28	0.00	7.53	92.47

Note: "-" indicates that the corresponding contribution of ion sources cannot be determined by the formulas of enrichment factor (EF). EF_sea and EF_soil are relative enrichment degree of an element in each kind of water body relative to the ocean and soil, respectively; SSF is the sea salt fraction; NSSF is the non-sea salt fraction, when the source of chemical ions is more complex, it is impossible to better distinguish the crustal and anthropogenic contributions; CF is the soil/rock weathering fraction; AF is the anthropogenic fraction.

3.5 Hydrological processes indicated by hydrochemistry

The study area is dominated by the Qinghai-Xizang Plateau, where frequent precipitation events occur and glaciers and frozen soils are widely distributed, forming a diversified form of runoff recharge in this region (Yao and Yao, 2010). Consequently, the ion concentrations in river runoff are subject to changes. Precipitation in the glacier area plays a role in recharging the glacial and snow meltwater (Wu et al., 2008), which is consistent with the results indicated by the source of Cl^- in precipitation (Table 2) (Dong et al., 2013). Isotope analysis is typically used to demonstrate the hydrological transformation process (Liu et al., 2019; Shi et al., 2021). The mutual recharge between surface water and groundwater can also be observed through ion concentration changes and TDS differences (Wu et al., 2008; Ma, 2019; Yang et al., 2021). Furthermore, the acid ion concentration can indicate the recharge effect of precipitation and meltwater on groundwater (Zhu et al., 2018). Li et al. (2022) also confirms the hydrological recharge process by combining the hydrochemical evolution and the characteristics of the hydrochemical types. The hydrological recharge processes in the study area are shown in Figure 11. Precipitation hydrochemistry is typically affected by meteorological factors, atmospheric circulation, human influences, and aerosols. However, the formation and occurrence of precipitation hydrochemistry involve only scouring and wrapping of aerosolic, rather than direct interactions with the surface. Therefore, the ion concentration of precipitation is the lowest in the study area, followed by that of meltwater. Meltwater comes from the melting of glaciers and snow in the alpine region, and the environment is pure during its formation. Moreover, the weathering of rocks around the alpine region is weak and the ambient low temperature would also weaken the weathering intensity, leading to relatively low chemical ion concentrations of meltwater (Li et al., 2020a). The water-rock interaction of groundwater and river water is the most intense, with significant weathering of silicates and carbonates, infiltration of groundwater by surface water, and mutual conversion between surface water and groundwater, resulting in the highest chemical ion concentrations in river water and groundwater. The difference in the mean ion concentrations between groundwater and river water in the study area is relatively small, and the proportions of ion concentration are similar (Fig. 11a and b). However, owing to bias in the data collection process, an ionization imbalance between anions and cations in each water bodies can be observed. In summary, hydrological processes in the western alpine region of China are influenced by several factors, including temperature, precipitation, water-rock interactions, rock weathering (mainly silicates and carbonates), atmospheric circulation, and human activities. The main forms of water input in the western alpine region of China are precipitation and meltwater, and groundwater and river water recharge each other.

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Fig. 11 Hydrological processes indicated by hydrochemistry in the western alpine region. (a), variations in ion concentrations of different water bodies; (b), hydrological processes and ionic composition of cations and anions in different water bodies. Arrows in Figure 11b represent the direction of hydrological recharge.

4 Conclusions

This study summarized the findings of hydrochemical research in the western alpine region of China at the regional and basin scales. Water resources in this region are generally weakly alkaline, and the TDS of different water bodies is low. The hydrochemical characteristics of water resources in the region exhibit significant seasonal fluctuations, and the ion concentrations in the inland river basins (e.g., Shule River Basin and Tarim River Basin) are relatively high. In the western alpine region of China, the hydrochemistry type of river water and meltwater is dominated by HCO₃^-•SO₄^2--Ca²⁺. The cations in groundwater are dominated by Mg²⁺ and Ca²⁺, and the anions are dominated by HCO₃^- and SO₄^2-. The dominant cation in precipitation is Ca²⁺, followed by Mg²⁺. The dominant anion in precipitation is SO₄^2-, followed by HCO₃^-. The chemical ion concentration of river water in the western alpine region of China is primarily influenced by the combined effects of rock weathering and evaporation crystallization. The ion composition and concentration of meltwater are mainly affected by rock weathering and atmospheric precipitation. The hydrochemical type of groundwater is affected by the weathering, dissolution of the surrounding salt rock, and evaporation crystallization. The precipitation ion input is mainly from sea salt sources, crustal sources, and anthropogenic sources. The contribution of non-marine sources exceeds 96.00% for Ca²⁺, K⁺, and HCO₃^-, and the anthropogenic contribution exceeds 88.00% for SO₄^2- and NO₃^-. In addition, the contributions of marine sources for Na⁺ in precipitation and meltwater are higher, accounting for 43.73% and 40.57%, respectively. The main forms of water input in the region are precipitation and meltwater, and mutual recharge between river water and groundwater is present. Building upon previous research findings, this study systematically reviewed and analyzed the hydrochemical characteristics of the western alpine regions of China, resulting in a thorough understanding of the spatiotemporal patterns and influencing factors of hydrochemistry in this region. The findings will lay a strong foundation for setting up long-term monitoring networks and enhance our understanding of hydrochemical changes in cold regions. In future, we plan to integrate remote sensing technology for a more comprehensive analysis of hydrochemical dynamics and combine this with meteorological data to delve into the underlying mechanisms of hydrochemical changes.

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study was supported by the National Science Foundation for Distinguished Young Scholars (42425107), the Top Talent Project of Gansu province, Chinese Academy of Sciences Young Crossover Team Project (JCTD-2022-18), the "Western Light"-Key Laboratory Cooperative Research Cross-Team Project of Chinese Academy of Sciences, the Ecological Civilization Special Project of Key Research and Development Program in Gansu Province (24YFFA009), the Gansu Science and Technology Program (25RCKA026), the Science and Technology Project of Lanzhou (2022-2-43), the Excellent Doctoral Program in Gansu Province (23JRRA573), and the Lanzhou Talent-Driven City Development Initiative. We greatly appreciate suggestions from anonymous reviewers for the improvement of our paper. Thanks also to the editorial staff.

Author contributions

Conceptualization: LI Zongxing, ZHAO Yue; Formal analysis: ZHAO Yue; Writing - original draft preparation: ZHAO Yue; Writing - review and editing: LI Zongxing, LI Zhongping; Funding acquisition: LI Zongxing; Supervision: LI Zongxing, LI Zhongping; Investigation: AOBULI Gulihumaer, NIMA Zhaxi, WANG Dong. All authors approved the manuscript.

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模态框（Modal）标题

Abstract

Cite this article

1 Introduction

2 Materials and methods

2.1 Study area

Fig. 1 Overview of the study area and distribution of sampling points of different water bodies. Note that the figure is based on the standard map (GS(2020)4619) of the Map Service System (https://bzdt.ch.mnr.gov.cn/), and the standard map has not been modified.

2.2 Data sources

Table 1 Date sources for different types of sampling points

2.3 Methods

2.3.1 Piper diagram

2.3.2 Gibbs diagram

2.3.3 End-member model

2.3.4 Enrichment factor and end-member contribution method

3 Results and discussion

3.1 Spatial variations in pH, TDS, and EC of different water bodies

Fig. 2 Spatial distributions of pH (a), TDS (b), and EC (c), as well as fitting relationship between TDS and EC (d) of different water bodies. TDS, total dissolved solids; EC, electrical conductivity.

3.2 Spatial and temporal variations in hydrochemistry of different water bodies

3.3 Hydrochemical type of different water bodies

Fig. 7 Piper diagram showing hydrochemical types of precipitation (a), meltwater (b), river water (c), and groundwater (d) in different river basins

3.4 Ion source analysis of different water bodies

3.4.1 Factors controlling the hydrochemical characteristics of different water bodies

Fig. 8 Gibbs diagrams showing the hydrochemical formation process of river water (a), meltwater (b), and groundwater (c) in different river basins

3.4.2 Influence of rock types on hydrochemistry of different water bodies

Fig. 9 End-member diagrams determining the rock types of river water (a), meltwater (b), and groundwater (c) in different river basins

3.4.3 Correlations between chemical ions in different water bodies

3.4.4 Quantification of hydrochemical ion sources

Table 2 Analysis of enrichment factors and contribution rate of ion sources

3.5 Hydrological processes indicated by hydrochemistry

4 Conclusions

Conflict of interest

Acknowledgements

Author contributions

References