Introduction

An oasis is a distinctive geographical entity that arises from the combination of uneven distribution of the water system and unbalanced spatial precipitation in arid regions, presenting itself as 'islands' within pre-mountain alluvial plains or basin deserts (Zhang et al. 2012a, b; Chen et al. 2002). Within arid zones, the oasis has evolved into a pivotal hub for human production and sustenance, demonstrating a remarkable carrying capacity for life systems. It serves as the central locus for human survival and development within this challenging environment and represents the most ecologically sensitive region (Liu et al. 2022; Yao et al. 2022; Wang and Gao 2002). The scarcity of water resources poses a key constraint to the sustainable development of oases (Afshar et al. 2021; An et al. 2021; Mirdashtvan et al. 2021; Zhang et al. 2020), with a focus on assessing the potential of surface water to sustain favorable growth in arid regions in the future. However, water resource assessments should include both water quality and quantity (Scanlon et al. 2007; Yu et al. 2020), and water quality problems can also cause water shortages (Jia et al. 2020; Ma et al. 2020; Zeng et al. 2013). Therefore, when promoting agricultural development in arid areas of Central Asia, it is imperative to adequately assess water scarcity from a hydrochemical perspective.

The Tarim Basin in arid Central Asia is the largest inland basin in China (Maimaiti et al. 2021), and the oases of the Tarim Basin are important sites of human production and life in the arid zones of Central Asia (Hong et al. 2003; Wang et al. 2021). The scarcity of water resources in arid zones undoubtedly constitutes a significant constraint to sustainable development in the Tarim Basin region (Chen et al. 2020; Li et al. 2021). Research on water quantity and its influencing factors has been very systematic and comprehensive in the Tarim River Basin, for example, the influence of climatic and anthropogenic factors on water resources (Li et al. 2021a, b, c; Li et al. 2021; Xu et al. 2004), sustainable use of water resources in the basin (Liu et al. 2022; Wang et al. 2022; Yang et al. 2019), the water balance in the Tarim River Basin(Xu et al. 2019), and spatial differences in hydrological processes (Fang et al. 2018). Owing to water scarcity in arid regions, any degradation in water quality would significantly decrease the efficiency of water use. On the one hand, the quality of irrigation water directly affects crop yield; on the other hand, the composition of irrigation water is closely linked to soil salinization. Whether water quality in this area can sustain future agricultural development in arid regions poses an urgent scientific challenge. A great deal of research has been carried out on the chemical composition of surface water and its influencing factors, and the water quality for irrigation in the main basins of the arid zone of Central Asia, such as the Issyk-Kul basin (Liu et al. 2020; Ma et al. 2018), the Tianshan region, the Altay mountain region (Liu et al. 2021), the Syr Darya river basin (Li et al. 2022a, 2022b; Liu et al. 2020; Ma et al. 2019), and the Chu-Talas River Basin in Central Asia (Ma et al. 2020), etc. The receptor soil in the irrigation system of arid zone oases, which plays a crucial role, has been overlooked in previous studies that have focused on surface water. Additionally, there is a lack of comprehensive investigation into both soil and irrigation water bodies as an integrated system, and the influence of the chemical composition of irrigation water on altering soil salinity composition remains to be elucidated. Additionally, owing to severe water scarcity in arid regions, the oasis has built a substantial number of reservoirs. These reservoir bodies are extensively utilized for farmland irrigation, resulting in the transformation of fluid bodies into quasi-stationary water bodies. What changes occur in the chemical characteristics of water? What implications does this transformation have for the utilization of water resources? The dearth of relevant research has also limited the sustainable development of oasis agriculture in arid regions. This study will exert a positive influence on the planning and utilization of regional water resources.

In arid regions, surface rivers serve as the main source of irrigation, and limited research on the hydrochemical composition and irrigation applicability of these rivers poses a significant constraint to the sustainable development of agriculture in the basin. In view of this, the present study considers soil and water (rivers, lakes, and reservoirs) as an integrated system, along with soil and water samples collected from various locations in the region. The application of classical hydrogeochemical methods and the models of ordinary least squares (OLS) and geographically weighted regression modeling (GWR) were used to analyze these samples in order to obtain results that address the following research questions: (1) Is the concentration of the main ions significantly different in the tributaries of the Tarim River basin, and what factors influence the chemical composition of river water? (2) Is water quality suitable for irrigation, and how does it affect agricultural sustainability? (3) What is the change in water chemistry from a fluid body to a quasi-stationary body and what is the important impact of this change on the sustainable development of agriculture in arid areas? 4) What is the relationship between the irrigation water quality and soil salinity? These findings provide valuable references for managing and utilizing water resources in the arid regions of Central Asia.

Materials and methods

Study area

Tarim Basin is located in Central Asia (Fig. 1), with a latitude of 35°–43° N and a longitude of 74°–90° E, with a total area of 1.19 × 106 km2 (Wang et al. 2016). The study area is primarily encompassed by the Tianshan, Pamirs, Karakoram, West Kunlun, and Altun Mountains. Situated in the heart of the Tarim Basin, the Taklimakan Desert represents China's largest desert, ranks tenth largest globally, and is the world's second largest active sand sea. Given its arid nature, agricultural development in this region is primarily based on irrigation systems that draw water from the rivers within the Tarim Basin.

Fig. 1
figure 1

a Geographical location of the Tarim Basin; b sampling sites for rivers, lakes, reservoirs, and soils from oasis agricultural fields with a topographic background map. The global map was obtained from the Natural Earth (https://www.naturalearthdata.com/). Topographic data b were extracted from FABDEM (Hawker et al. 2022)

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Sampling

Systematic collection of river water samples was conducted from June 6 to June 27, 2021, encompassing the main river and tributaries of the Tarim River. Water samples were collected from 35 sites, including rivers (27 sites) and lakes/reservoirs (8 sites). Soil samples were obtained from the upper layer (0–20 cm) at 78 locations to investigate the relationship between irrigation water quality and soil salinity. Garmin GPSmap 621sc device was used to determine the latitude and longitude coordinates at the site for each sampling point. The geographical distribution of these points is shown in Fig. 1b. Soil sampling was conducted in strict accordance with the technical specifications for field investigation and sampling of China's third national soil survey (Office of the Leading Group 2023). The surface water body sample collection process strictly adhered to the national standard of China (Ministry of Ecology and Environment 2022). A 500 ml polyethylene sampling bottle was used as the test sample for conventional water chemical components. During sampling, each bottle was rinsed thrice with river water before being poured downstream of the sampling point. Owing to the wide sampling range, all samples were placed in a vehicle refrigerator and kept at 4 °C to ensure sampling quality.

Laboratory analysis

For waters, detailed methods were described in the standard book of the China's state environmental protection administration (SEPA China 2002). Temperature (T), oxidation reduction potential (ORP), pH, and conductivity (EC) were measured in situ using a HI 9828 multiparameter water quality meter (Hanna Instruments, Italy). A Thermo ICS-2100 ion chromatography system was used to determine the concentrations of major ions (Ca, Na, K, Mg, Cl, and SO4). The mass concentrations of HCO3 and CO3 were determined via potentiometric titration using a compact G20 titrator (Mettler Toledo AG, Switzerland). Unfortunately, the CO3 levels were below the detection limit of 0.03 mg/L and could not be detected. Different forms of nitrogen, including ammonia nitrogen (N–NH3), nitrate nitrogen (N–NO3), and nitrite nitrogen (N–NO2), were analyzed using a flow autoanalyzer (AA3 HR) provided by Seal Analytical.

The soil samples collected were air-dried in the laboratory and, subsequently, any remaining membranes, gravel, roots, and other residues were manually removed before being sieved through a 1 mm mesh sieve into labeled envelopes. The air-dried ground soil was sieved through a 1 mm sieve, and 10 g of soil samples was mixed with 25 g of distilled water (water–soil ratio of 2.5:1), shaken, and centrifuged, and the supernatant was collected to determine the pH, EC, soil salts, and their components. Detailed methods for the analysis of the supernatant solution were provided by China's State Environmental Protection Administration (SEPA China 2002). The soil conductivity was determined using a LeiCi DDSJ-308A conductivity meter. pH was determined using a METTLER-TOLEDO SevenEasy pH meter. The major ion compositions of the soils were analyzed in the laboratory using the aforementioned instruments for the water samples. The mass content of the soil salt was calculated by conversion based on the volume concentration obtained from the soil leaching solution. The determination of water chemistry involved in this study was completed at the Analytical and Testing Center of the **njiang Institute of Ecology and Geography, Chinese Academy of Sciences.

Hydrochemical research methods

In this study, classical hydrochemical methods for water quality assessment, such as Piper (Zhou et al. 2023) and Gibbs diagrams (Gao et al. 2020) for hydrochemical characteristics, as well as Wilcox diagrams (Zhang et al. 2012a, b), USSL (Islam et al. 2017), and permeability index diagrams (Bouaroudj et al. 2019) to evaluate the suitability of surface water for irrigation purposes. The Piper diagram is widely used for cationic-anionic facies identification and is expressed as milliequivalent percentages of total major ions. The Gibbs diagram can directly reflect the mechanisms contributing to the hydrochemical components of water, based on the relationship between the cation ratio Na/(Na + Ca), anion ratio Cl/(Cl + HCO3), and TDS (mg/L). The USSL diagram is mainly used to characterize the sodium damage caused by water to the soil, that is, by decreasing the permeability of the soil, which in turn inhibits water uptake by crops. The Wilcox diagram divides irrigation water quality into five categories based on the magnitude of Na% and EC, and the structure of the diagram is divided into zones of very good (1), good (2), suitable (3), retained (4), and unsuitable (5) water quality. The permeability index (PI) serves as a reliable indicator for evaluating water suitability in irrigation because of its correlation with sodium, calcium, magnesium, and bicarbonate ion concentrations and their impact on soil permeability. According to the magnitude of SAR and EC values, the USSL diagram was divided into 16 zones, in which C1–C4 represents the salinity level, and a higher EC value indicates that the quality concentration of soluble salts is too high, which makes the soil salinized when used for irrigation; S1–S4 represents the alkalinity level, the higher the SAR value, the more the soil tends to be alkalized. Increase the map of the areas of sample sites that are not suitable for irrigation. The diagrams were created using hydrogeochemical diagrams (HGCD) (He and Li 2020). The ion concentration used in the calculation and drawing of the diagrams mentioned above is expressed as milligram equivalent concentrations.

The reverse ion exchange process is reflected in the chloro-alkaline indices (CAI1 and CAI2): CAI1 = [Cl–(Na + K)]/Cl; CAI2 = [Cl–(Na + K)]/(Cl + HCO3 + SO4 + NO3). Positive values indicate direct ion exchange processes between ions, while negative values suggest reverse ion exchange processes occurring within the aquifer water (Ayyandurai et al. 2022; Zaidi et al. 2015). The relationship between ions and samples was elucidated using a cluster heat map, which was generated using Number Cruncher Statistical System software (NCSS, 2023). Proportion scaling methods were applied for variables, while the group average clustering method and Euclidean distance method were utilized for the variable dendrogram and row dendrogram.

The methods of ordinary least squares (OLS) (Zhang et al. 2022) and geographically weighted regression (GWR) (Tian et al. 2023) were used to simulate the nitrate nitrogen content in this study to study the factors that influence nitrate nitrogen. The OLS model is a global regression model that assumes that the relationship between variables is fixed (Zhang et al. 2023), and the OLS model was constructed using ArcGIS software. However, ordinary least squares (OLS) regression can obscure potentially significant local spatial variations in the relationships between variables. The geographically weighted regression (GWR) model, on the other hand, accounts for the spatial non-stationarity of variable relationships. The GWR model can be expressed as yi = β0(μi, vi) + ∑k βk(μi, vi)xik + εi, where yi is the dependent variable, xik is the explanatory variable, (μi, vi) is the spatial information, β0(μi, vi) is the intercept term, βk(μi, vi) is the regression coefficient, and εi is a random error term. A Gaussian model type with a fixed Gaussian kernel was used in the GWR4.09 software (Nakaya 2016).

Results

Variability in the major ionic compositions of surface waters

In the dataset comprising 27 sampling locations distributed across the Tarim Basin river networks (Fig. 2a), the pH exhibited a mean value of 8.05 ± 0.15, ranging from a minimum of 7.75 to a maximum of 8.32. The oxidation–reduction potential (ORP) displayed an average value of 197.6 ± 68.28 mV, with a minimum measurement of 32.6 mV and a maximum reading of 323.40 mV. Furthermore, the electrical conductivity (EC) demonstrated an average magnitude of 653.67 ± 336.40 μS/cm, varying between a minimum level of 256 μS/cm and reaching its highest point at 1473 μS/cm. The mean concentration of total dissolved solids (TDS) was 553.72 ± 363.54 mg/L, exhibiting significant variability ranging from 159.63 mg/L to 1570.04 mg/L, with the maximum value approximately ten times higher than the minimum value. Among all the cations analyzed, calcium (Ca) and sodium (Na) were found to be the most abundant in the water samples. The average Na concentration was determined at 82.04 ± 88.35 mg/L, with a minimum recorded value of 6.03 mg/L and a maximum observed value of 329.34 mg/L; additionally, the median concentration was calculated at 44.53 mg/L. The mean concentration of K was 5.24 ± 3.66 mg/L, ranging from a minimum of 1.33 mg/L to a maximum of 15.09 mg/L, with a median value of 4.22 mg/L. The mean Ca concentration was 98.44 ± 43.51 mg/L, varying between a minimum value of 48.45 mg/L and a maximum value of 225.76 mg/L, and the median concentration was found to be 85.74 mg/L. For Mg, the mean concentration was determined as 30.32 ± 19.51 mg/L, with values ranging from a minimum of 7.80 mg/L to a maximum of 76.05 mg /L; the median recorded concentration was approximately 22.03 mg /L. Among all the anions, SO4 was the most abundant with a mean value of 168.58 ± 127.36 mg/L, ranging from 31.92 to 507.85 mg/L and a median value of 129.37 mg/L. The mean value of Cl was 97.60 ± 111.71 mg/L, ranging from 4.87 to 440.43 mg/L and a median value of 51.71 mg/L while the mean value of HCO3 was found to be at 137.18 ± 32.86 mg/L with minimum and maximum values recorded as 94.26 and 208.25 mg/L, respectively.

Fig. 2
figure 2

Differences in the major ion composition, various nitrogen forms, and total nitrogen content were observed between the Tarim Basin river water (a and c) and lake/reservoir water (b and d)

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In the dataset comprising eight sampling points that included lakes and reservoirs in the Tarim Basin (Fig. 2b), the average pH value was determined to be 7.99 ± 0.29, with a minimum of 7.96 and a maximum of 8.58. The mean oxidation–reduction potential (ORP) was calculated as 180.51 ± 55.81 mV, ranging from a minimum of 118.20 mV to a maximum of 247.80 mV. Electrical conductivity (EC) exhibited a mean value of 3631.88 ± 4375.24 μS/cm, ranging from a minimum of 310 μS/cm to a maximum of 12,350 μS/cm. Meanwhile, total dissolved solids (TDS) showed an average value of 2367.27 ± 2518.55 mg/L, fluctuating between the range of 205.43–7275.49 mg/L. Among all cations, sodium (Na) exhibited the highest abundance with a mean value of 543.81 ± 655.69 mg/L, ranging from a minimum of 14.73 mg/L to a maximum of 1838.98 mg/L; the median value was 263.34 mg/L. Potassium (K) had an average concentration of 20.82 ± 23.34 mg/L, varying between 3.72 and 71.33 mg/L; the median value of K was determined as 10.59 mg/L. Calcium (Ca), on the other hand, showed an average level of 226.97 ± 206.37 mg/L, with a minimum recorded at 55.43 mg/L and a maximum of 654.45 mg/L; its median concentration was calculated as equal to 138.17 mg/L. The average concentration of Mg was 113.76 ± 102.92 mg/L, ranging from a minimum of 9.80 mg/L to a maximum of 318.48 mg/L, with a median value of 80.63 mg/L. Among all anions, Cl and SO4 were found to be the most abundant in the samples analyzed. The mean concentration of Cl was 696.61 ± 835.28 mg/L, varying from a minimum of 18.87 mg/L to a maximum of 2268.08 mg/L, with a median value of 351.46 mg/L. The average concentration of SO4 was 699.12 ± 718.20 mg/L, ranging from a minimum of 43.58 mg/L to a maximum of 2058.97 mg/L, with a median value of 405.49 mg/L. The mean concentration of HCO3 was 128.50 ± 45.21 mg/L, varying between a minimum value of 58.05 mg/L and a maximum value of 213.03 mg/L, while the median concentration was found to be 129.46 mg/L.

To investigate the composition of individual ions and the interrelationships among samples, a heatmap was used to provide a more visually representative depiction of the response (Fig. 3). The heatmap displaying the absolute values of the matrix indicated similarities in the major ionic compositions. However, strong correlations were observed between the two groups: one consisting of Na, Cl, and K, and the other consisting of SO4, Mg, and Ca. In contrast, HCO3 exhibited a weak correlation with the aforementioned ions. The heatmap effectively illustrates the Euclidean distances between individual sample points. In particular, lake samples L01, L02, and L03 exhibited different characteristics compared with all other surface water samples.

Fig. 3
figure 3

Clustered heat map of similarities among the major ions and sampling sites

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Nitrogen content and its difference in surface water of Tarim Basin

The total nitrogen content (ToN) of river water bodies is predominantly influenced by nitrate nitrogen (N–NO3), with relatively low levels of ammonia (N–NH3) and nitrite nitrogen (N-NO2). The mean ToN value was 0.69 ± 0.37 mg/L, ranging from a minimum of 0.09 mg/L to a maximum of 1.42 mg/L, with a median value of 0.69 mg/L (Fig. 2c). The total nitrogen content in lakes and reservoirs is mainly influenced by nitrate nitrogen (N–NO3), whereas the levels of ammonia (N-NH3) and nitrite nitrogen (N–NO2) are relatively low. The mean total nitrogen concentration was 0.49 ± 0.59 mg/L, ranging from a minimum of 0.01 mg/L to a maximum of 1.66 mg/L, with a median value of 0.19 mg/L (Fig. 2d).

Although the nitrogen content in the Tarim Basin is relatively low, particularly with regard to ammonia nitrogen and nitrite nitrogen, the detection of these compounds implies that human activities directly or indirectly influence the river's water chemistry through the discharge of substances during their daily lives and production. Nitrate levels in the water body are affected by various sources of human activity, including manure and domestic sewage, soil nitrogen, precipitation, fertilizer nitrogen, and other forms of pollution. Ammonia nitrogen in water is mainly derived from nitrogenous organic matter present in domestic sewage, which is decomposed by ammonia-producing bacteria to generate ammonia. In addition, industrial wastewater and chemical fertilizers contribute to the presence of ammonia. Surface water exhibits varying levels of both ammonia and nitrogen because of different degrees of pollution. Based on the ORP analysis, the water environment within the Tarim Basin demonstrates an oxidative state, with different states of nitrogen detection that have different environmental chemical significance. Nitrogen was detected at varying levels at all sampling sites. The three forms of nitrogen were identified at six specific locations (L01, L02, L07, T06, T24, and T27), which had previously experienced nitrogen contamination and underwent self-cleaning processes, while also being newly contaminated. Only ammonia nitrogen was detected at three sampling points (L04, T01, and T15), indicating recent nitrogen pollution of the water body. Nitrate nitrogen and nitrite nitrogen were not detected at five other sampling points (L06, T04, T10, T20, and T26), suggesting that these pollutants have undergone significant decomposition but lack complete self-purification. The absence of nitrite nitrogen in the analysis of ammonia nitrogen and nitrate nitrogen at ten sample collection sites (L03, L05, L08, T02, T07, T12, T18, T19, T21, and T22) indicates a new form of pollution that has undergone significant self-cleaning compared to previous instances. Only nitrate nitrogen was detected at 11 sample points (T03, T5, T08, T09, T11, T13, T14, T16, T17, T23, and T25), indicating the predominance of inorganic pollutants and a significant self-purification capacity within the water body. To effectively safeguard the invaluable water resources in this arid zone, future efforts should focus on strengthening control measures for nitrogen-containing pollutant discharge.

Similarity in the ionic assemblies between surface waters and soils

All lake and river/reservoir water samples belonged to three water types: SO4 Cl–Ca Mg, SO4 Cl–Na, and HCO3–Ca Mg (Fig. 4a). However, the three water samples exhibited an uneven distribution. Most of the river samples were SO4 Cl-Ca Mg. Seven samples were of type HCO3–Ca Mg, including samples T07, T12, T13, T15, T08, and T09, and lake sample L08 (Karakul Lake, located on the Pamirs Plateau). The sample located downstream of T26 is similar to some river/reservoir water types (L01, L06, and L02), which belong to the SO4 Cl–Na type. The concentrations of SO4, Cl, and Na in the lake water samples increased significantly relative to the river, and there was a tendency to change from SO4 Cl–Ca Mg to SO4 Cl–Na.

Fig. 4
figure 4

Piper diagram of hydrochemical types and soil salinity. a Left Piper diagram for river water (square) and lake/reservoir samples (round). b Right Piper diagram for soil salinity types

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The chemical properties of the soil in the Tarim Basin oasis are shown in Fig. 5. The pH ranged from 7.66 to 8.97, whereas the conductivity exhibited a maximum value of 1270 μS/cm and a minimum value of 108.9 μS/cm. Furthermore, the total soluble salt content was measured at 15.16 mg/g, with the lowest recorded value being only 0.45 mg/g. The mean concentration of water-soluble chloride (Cl) in the soil was determined to be 0.25 mg/g, the sulfate content (SO4) at 1.09 mg/g, and the bicarbonate content (HCO3) at 0.166 mg/g. Calcium (Ca) showed an average content of 0.46 mg/g, potassium (K) had an average concentration of 0.06 mg/g, and magnesium (Mg) showed an average level of 0.105 mg/g in soil samples analyzed for this study. Sodium (Na), on the other hand, showed an average content of 0.24 mg/g. To investigate the correlation between the chemical composition of the surface water and its ionic composition, we employed a Piper diagram to depict the relative percentages of ions in the three-component system. As depicted in Fig. 4b, there was a significant similarity between the composition of water-soluble salts in soil and that in surface irrigation water. It is widely recognized that under arid climate conditions, with mineralized irrigated water, there is a convergence effect on salt types between oasis farmland soil and irrigation water.

Fig. 5
figure 5

Variation range of pH value, conductivity (EC), total salt, and soluble salt in the soils of the Tarim Basin

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Irrigation suitability for surface water in the Tarim Basin

Lake Taitama (L01 and L02) is located at the lowest point of the Tarim Basin and serves as a tailrace lake for the main stroma of the river. Owing to its location, it exhibits exceptionally high salinity levels and lacks ecological significance for irrigation purposes. Consequently, this section did not include an evaluation of its suitability for irrigation. The sodium adsorption ratio (SAR) in the USSL diagram (Fig. 6a) suggests that the waters in the Tarim Basin belong to area C2–S1, C3–S1, C3–S2, and C4–S2. From the Wilcox diagram (Fig. 6b), most surface waters can be classified as exhibiting excellent (1) or good (2) water quality. In the study area, the PI classified the collected water samples into two classes: Class 1 (maximum permeability greater than 75%, suitable for irrigation) and Class 2 (maximum permeability 25–75%, suitable for irrigation) (Fig. 6c), which are generally suitable for irrigation. In general, the Tarim Basin has a relatively low alkali hazard level. Irrigation with surface water is mainly at the risk of salinization of the soil. In terms of distribution, the risk to the west is significantly higher than that to the east, and the risk to the main stream is significantly higher than that to the tributaries.

Fig. 6
figure 6

Evaluation of surface water suitability for irrigation in the Tarim Basin (blue color for river sampling sites and orange color for lake sampling sites), including the USSL diagram a, Wilcox diagram b, permeability index (PI) c, and reverse ion exchange process for surface water (all sampling sites)

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The chloro-alkaline indices (CAI1 and CAI2) offer valuable insights into the ion exchange reactions that occur between water and aquifer materials (Ayyandurai et al. 2022; Zaidi et al. 2015). The CAI1 index ranged from − 3.25 to − 0.06, while the CAI2 index ranged from − 0.2 to − 0.03 (Fig. 6d). Additionally, a reverse ion exchange phenomenon was observed between the water and the substrate. Although the risk of soil alkalization caused by irrigation water quality in the study area was considered low based on hydrochemical evaluation, the water flow process induced reverse ion exchange between calcium and magnesium with sodium in the soil, leading to an influx of sodium ions into the soil environment through irrigation. Consequently, this results in an increase in soluble Na content within the soil, causing alkaline damage.

Discussions

The main hydrochemical processes affecting the chemical composition of waters

The hydrochemical characteristics of natural waters are influenced by a combination of inherent factors including rock properties, precipitation patterns, vegetation cover, and anthropogenic activities. These characteristics provide valuable insights into the geographical attributes, petrochemical weathering processes, and human-induced impacts of the basin. The hydrochemistry of the surface waters in the Tarim Basin exhibited a notable concentration, which is indicative of the homogeneous geochemical background and climatic conditions prevailing in the study area. Gibbs diagrams are commonly employed to investigate hydrogeochemical processes in surface waters. Most of the water sampling sites in the study area were predominantly located within the middle and upper regions of the Gibbs diagrams, specifically within the weathering zone of rocks, while being significantly distant from the atmospheric precipitation zone (Fig. 7). The force of evaporation also plays a large role in the process along the runoff course, and a considerable part of the water samples are located in the transition zone of the rock dominance and evaporation dominance zones (Fig. 6). In general, the factors that affect water quality in arid zones are mainly influenced by water–rock interactions, which is similar to the results of the study of the Aral Sea Basin (Ma et al. 2019). This finding indicates that surface runoff in arid regions is significantly influenced by evapotranspiration, whereas the tributaries or upstream river sampling sites are primarily impacted by weathering processes occurring on the Earth's surface.

Fig. 7
figure 7

Gibbs plots for surface waters in the Tarim Basin (blue color for river sampling sites and orange for lake sampling sites)

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The dissolution of carbonate rocks and evaporated salts (gypsum) in the water column can be characterized by the ratios of (Ca + Mg)/HCO3 and (Ca + Mg)/(HCO3 + SO4) (Capaccioni et al. 2001; Yechieli et al. 1992). If the ratio of (Ca + Mg)/HCO3 is 1, this indicates that Ca and Mg in the water body originate primarily from the dissolution of carbonate rocks. In our study area, all samples showed significantly higher values of (Ca + Mg)/HCO3, ranging from 1.7 to 28.8. A ratio of (Ca + Mg)/(HCO3 + SO4) of 1 indicates that the presence of Ca and Mg in the water body can also be attributed to the dissolution of evaporite minerals such as gypsum. Furthermore, most of the surface water samples in our study area aligned closely with the 1:1 ratio line. The calculated values for (Ca + Mg) / (HCO3 + SO4) range from a minimum of 1.03 to a maximum of 1.54 across all samples, suggesting that Ca, Mg, and SO4 originate primarily from dissolution processes involving gypsum and carbonate rocks. The presence of Na and K in natural water bodies originates primarily from the dissolution of evaporite and silicate minerals, resulting in a (Na + K)/Cl ratio of 1. This indicates that the dominant source of Na and K in water bodies is the dissolution of salt rocks from the evaporites. However, the analysis revealed that surface water samples within the basin exhibited a (Na + K)/Cl ratio ranging from 1.07 to 4.31, suggesting an additional influence from the dissolution of silicate minerals. The occurrence of reverse ion exchange between water and the substrate can also result in an increase in the sodium ion content in the water (Mahmoudi et al. 2017). In general, evaporation and reverse ion exchange are crucial hydrological processes that cannot be ignored when controlling the water chemistry within the study area; thus, they require significant attention.

Significant influence of human activities on the chemical composition of water

Despite the relatively low nitrogen content observed in the surface waters of the Tarim Basin within the study area, investigating nitrogen levels and their sources remains a major concern in current research because of their inherent polluting characteristics (Basu et al. 2022; Hu et al. 2019). The prevailing belief is that a portion of nitrate found in water bodies originates from natural weathering processes. Furthermore, rivers with higher pollution levels have been observed to exhibit elevated NO3/Na and Cl/Na values (Nisi et al. 2013). In particular, the surface water within the Tarim Basin shows a lower NO3/Na ratio, which implies minimal influence from human activities.

With the results of the OLS model, the projected value of N-NO3 was correlated with the observed value of N-NO3 with a coefficient of determination R2 = 0.404 (p < 0.0001) (Fig. 8a); however, OLS hides potentially important local spatial variations in the relationships between variables. Based on the GWR model, the effect of natural weathering on nitrate was investigated, and the distribution of nitrate content was also simulated using Na, K, Ca, Mg, Cl, SO4, and HCO3 as variables representing natural weathering. The local correlation R2 ranged from 0.87 to 1.0. By establishing a correlation analysis of the simulated and measured values (Fig. 8b), the simulation results showed that the correlation R2 reached 0.986, which was significantly correlated at the level of 0.0001, reflecting that natural weathering has a dominant influence on the nitrate or nitrate nitrogen content of environmental factors. However, there are spatial differences in the type of rock weathering that dominates the change in nitrate nitrogen content at a particular site.

Fig. 8
figure 8

Linear correlation between the measured value of nitrate nitrogen and the predicted values based on the ordinary least squares (OLS) model a and geographically weighted regression model (GWR) b

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Implications of water quality differences between quasi-stationary water bodies

Rapid population growth in the Tarim Basin has resulted in a significant surge in water consumption over the past three decades driven by the development of both water and land resources (Zhang et al. 2015). The degradation of surface water quality in arid zones results in the inaccessibility of a portion of the limited surface water resources for irrigated agriculture, thus exacerbating the problem of water scarcity. According to this study, while surface water is generally suitable for irrigation, some water bodies are unsuitable for irrigation, particularly those close to the main streams, which are no longer suitable for irrigation.

In contrast, to effectively address the scarcity of water resources, a multitude of reservoirs has been constructed within the oasis for irrigation purposes. It has been observed that quasi-static water bodies, such as lakes and reservoirs, exhibit significantly different hydrochemical characteristics compared to mobile water bodies, with an especially pronounced elevation in salinity levels. For example, the salinity of the **aoxihaizi Reservoir (L03, sampling site in Fig. 1) reaches 3003 mg/L, which represents approximately 50% of the salinity level observed in Lake Daitama (L01, sampling site in Fig. 1), with a concentration of 7275 mg/L. In contrast to the Chala Reservoir (L04, sampling site in Fig. 1), located within the same geographical area, the salinity of the water body is only at a level of 552 mg/L because of significant variations in water exchange cycles. Therefore, it is recommended to implement more scientific water management for reservoirs located within oases in arid regions.

Shortcomings and prospects

This study explored and investigated the impact of water quality on the suitability of irrigation water for the sustainable development of oasis agriculture in the Tarim Basin through an in-depth analysis of samples collected from rivers, reservoirs, and lakes during the irrigation period. However, there are still some limitations to our research process, and more research should be conducted to address the following aspects in future studies.

  1. (1)

    Strengthening continuous monitoring and comprehensive assessment: Due to the vast expanse of the Tarim Basin, the limited accessibility to certain river sampling sites, and the impact of the Covid-19 pandemic, this study focused solely on monitoring changes in hydrochemical components during the summer irrigation period in rivers within the Tarim Basin. Consequently, the data obtained were relatively scarce and restricted, leading to an increased uncertainty in the results. Analysis of samples from different seasons should also be strengthened to elucidate differences in water chemistry characteristics as well as differences in drivers between different periods. Furthermore, considering the intricate interaction between surface water and soil, future research should prioritize improving the environmental monitoring of surface water bodies and soil in the Tarim Basin to acquire more comprehensive data for systematic evaluation of soil and water environmental safety.

  2. (2)

    Expanding the scope and objective: Our research focused on investigating the sustainability of water resources for the agricultural development of oases in the Tarim Basin. Future studies should examine the changes in heavy metals and persistent organic pollutants through combined model simulations and isotope measurements to quantitatively identify pollution sources that pose significant risks to human health.

  3. (3)

    Strengthening research in the field of water resource allocation: Construction of irrigation reservoirs in arid zones to effectively address agricultural water shortages can lead to deterioration of irrigation water quality, which requires further comprehensive investigations to achieve a harmonious balance between water conservation and water quality preservation. Furthermore, it is imperative to continuously monitor pollution in the future to ensure the cleanliness and safety of the invaluable water resources in arid areas.

Conclusions

The applicability of surface water irrigation was evaluated by collecting samples from surface water bodies such as rivers, lakes, and reservoirs, and the following conclusions were drawn.

  1. (1)

    A convergence phenomenon occurred under long-term irrigation conditions, showing a similarity between the salt composition of soils and surface irrigation waters.

  2. (2)

    The current surface water quality is generally suitable for irrigation, indicating its potential to sustain future agricultural needs in terms of water quality.

  3. (3)

    In addition to evapotranspiration, the reverse ion exchange process has a more important effect on surface water bodies and soil salinity, resulting in an increase in soil Na-ion content and, subsequently, enhanced alkaline hazards.

  4. (4)

    Nitrogen nitrate is mainly affected by natural weathering; however, the factors that influence it have spatial differences. For ensuring the sustainable use of water resources in arid regions, the increasing nitrogen concentration caused by human activities needs to be addressed in future irrigation management.

  5. (5)

    Quasi-static water bodies, such as lakes and reservoirs, exhibit significantly increased salt content. It is recommended that more scientific water management be implemented for reservoirs located within oases located in arid regions.