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Article

Major Ion Chemistry of Waters and Possible Controls under Winter Irrigation in the Saline Land of Arid Regions

1
Nanjing Center, China Geological Survey, Nanjing 210016, China
2
School of Hydraulic and Ecological Engineering, Nanchang Institute of Technology, Nanchang 330099, China
*
Authors to whom correspondence should be addressed.
Water 2023, 15(22), 3968; https://doi.org/10.3390/w15223968
Submission received: 9 October 2023 / Revised: 9 November 2023 / Accepted: 10 November 2023 / Published: 15 November 2023
(This article belongs to the Special Issue Improved Irrigation Management Practices in Crop Production)

Abstract

:
To reduce downstream ecological damage, it is crucial to analyze water and salt sources in saline–alkali farmland drainage and optimize soil salt discharge. This study employs statistical, hydrochemical, and isotope methods to identify controlling factors and characteristics in water bodies during winter irrigation. The results show average TDS values of 0.59, 6.40, and 4.14 g/L for irrigation, phreatic, and drainage water. Irrigation and phreatic water mainly belong to the HCO3-Ca·Mg·Na and Cl·SO4-Na·Mg types. Na+/(Na+ + Ca2+) and Cl/(Cl + HCO3) values suggest the rock–water interaction and evaporation influences in irrigation water, while evaporation primarily controls phreatic water. The main salt types include NaCl, MgSO4, Na2CO3, and CaCO3 for irrigation water and NaCl, MgSO4, Na2SO4, and CaCO3 for phreatic water. These findings lay a research basis for analyzing water and salt sources in farmland drainage during winter irrigation in saline–alkali land.

1. Introduction

Farmland drainage in saline–alkali soil is an important strategy to prevent soil salinization and optimize crop yield [1,2]. The study of the characteristics of water and salt discharge is key to judging whether soil is in a state of salt accumulation or desalinization, and it is also an important basis for the analysis of the soil’s water–salt balance in saline–alkali soil [3]. With the deepening of study on leaching and desalination of saline–alkali land, the characteristics of farmland drainage water in saline–alkali land have been paid more and more attention [4,5,6]. Farmland drainage flows and salinity data during a drainage test in the Murrumbidgee Irrigation Area were monitored by Hornbuckle et al. [7], and they found that the drainage flow and salinity of multi-stage drainage systems were higher than those of single-stage drainage systems. Comparing the data of farmland drainage flow and selenium loads forming shallow drains and deep drains, Deverel et al. [8] found that the drainage selenium loads form shallow drains less often than they form deep drains. Feng et al. [9] conducted an experimental study on the effects of different irrigation water salinities and the buried depth of subsurface pipes on soil salinity and summer maize yield in Nanjing, and the results showed that the amount of salt discharge from farmland increased with increases in the buried depth and irrigation water salinity. Bassil et al. [10] analyzed the drainage test data of shaft drainage at different locations, and they found that the lower the terrain, the greater the drainage volume and the higher the drainage salinity. Bahceci et al. [11] used the SaltMod model to simulate the drainage volume and soil salt content in the root zone and groundwater table at different drainage depths. The results showed that when the drainage depth increased from 1.2 m to 1.6 m, there was no significant change in soil salt content in the root zone, but the drainage volume increased significantly. Parsons et al. [12] used the Watrcom model to simulate and analyze the drainage volume, relative yield, and irrigation water requirement of maize under conditions of conventional drainage, controlled drainage, and subirrigation. The results showed that the yield of maize in dry years of subirrigation treatment was higher than that of controlled drainage treatment and higher than that of conventional drainage treatment, and controlled drainage treatment could significantly reduce the drainage volume compared with conventional drainage treatment. The above analysis on the characteristics of farmland drainage in saline–alkali land mainly covers the following aspects: (1) In terms of farmland drainage methods, the influence of different drainage modes or drainage parameters on the drainage characteristics of farmland was studied. (2) In terms of controlled drainage, the influence of different drainage depths on the drainage characteristics of farmland was studied. (3) In terms of research methods, indoor experiments, field experiments, or numerical simulations were carried out to ascertain the characteristics of farmland drainage. (4) In terms of the characteristics of farmland drainage, the changes in farmland drainage flows, drainage volume, drainage salinity, drainage pH, and ions in drainage were studied. Although the research angles were different, there was a common point: previous studies have mainly focused on the monitoring of drainage volumes and drainage quality, and there have been fewer studies related to the traceability of water and salt in winter irrigation and farmland drainage [5]. However, analyzing the source structure of water and salt in farmland drainage is particularly important, and it is the key to optimizing the effects of soil salt discharge from farmland and protecting the downstream ecological environment [13].
Surface water or groundwater has a series of water–rock interactions with its surrounding environment through the process of surface runoff and groundwater seepage, and the hydrochemical characteristics of the water body show a series of changes [14,15]. In addition, the types of hydrochemicals, main ion sources, evolution mechanism, and influencing factors can be analyzed according to the hydrochemical characteristics of various water bodies [16,17,18]. At the same time, the recharge sources and water quality evolution process of various water bodies can also effectively be captured using hydrogen and oxygen stable isotope technology [19,20]. Geochemical modeling can effectively simulate water–rock interactions; for example, Apollaro et al. [21] simulated water–rock interactions in near-surface steam-heated zones by employing reaction path modeling in kinetic mode, focusing on the primary chemical components. Their study successfully reproduced the observed alteration of solid phases in the “Cave di Caolino” area on Lipari Island. Minerals in rocks and soils are one of the main factors determining water chemistry [22]. Apollaro et al. [23] conducted geochemical research on the soils, stream sediments, and rocks in the Fiume Grande watershed, revealing the roles of natural weathering and anthropogenic pollution in determining the distribution of major oxides and various trace elements in the examined geological environmental matrix. Based on the study of the hydrochemical characteristics of fissure or karst water in Yucatan, Mexico, and Florida, United States of America, Hanshaw et al. [24] defined the evolution law of groundwater in a carbonate environment. The discovery of this law has greatly promoted the development of a hydrochemical evolution law for karst in a carbonate zone. Lawrence et al. [25] analyzed the hydrochemical characteristics of groundwater bodies in Suwannee County and established recharge relationships for each water body. Rao et al. [26] analyzed the hydrochemical characteristics and quality of groundwater in the Varaha River Basin and proposed management measures to improve local water quality. Kim et al. [27] and Abou et al. [28] used the hydrochemical method to analyze the chemical characteristics of nitrate-contaminated groundwater in a Hongseong agricultural area and a Damascus oasis area, respectively. In terms of hydrogen and oxygen stable isotopes, Lambs [29] studied the recharge sources of river water and groundwater using hydrogen and oxygen stable isotope technology. Chiogna et al. [30] studied the hydrogen and oxygen stable isotope characteristics of surface water and groundwater within the Vermigliana catchment, clarifying the main recharge sources and the hydrological cycle of the Vermigliana catchment. Mccarthy et al. [31] studied the dynamic relationship between the Columbia River and groundwater using the hydrogen and oxygen stable isotope technique and determined the contribution of river water to groundwater. Qiu et al. [32] conducted research on the hydrogen and oxygen stable isotope characteristics of different water bodies in the Qilian Mountains, in the northwestern Tibetan Plateau. The results showed that the variations in δ18O values in river water and groundwater were similar, and the differences in deuterium excess were small, suggesting obvious hydraulic connections between surface water and groundwater. Taniguchi et al. [33] analyzed groundwater sources in the Heihe region using hydrogen and oxygen stable isotopes. Additionally, they determined the relationship between the electrical conductivity and isotopic components of groundwater. It is found that the above studies on hydrochemistry and hydrogen and oxygen stable isotopes were mostly focused on large-scale surface water and groundwater. Their primary focus was on the recharge relationship of different water bodies and the evolution and transport of their chemical composites. However, there is a gap in research on small-scale farmlands, particularly in winter irrigation and drainage in saline–alkali farmland. Clarifying the hydrochemical characteristics and controlling factors of various water bodies under winter irrigation is an important prerequisite for analyzing the source structure of water and salt in winter irrigation farmland drainage.
Therefore, the primary aim of this study is to characterize hydrochemical features through the analysis of hydrogen and oxygen stable isotopes and major ions in diverse water bodies. It specifically examines hydrochemical types and factors influencing dissolved solutes while delving into the origins of major ions across different water bodies. To achieve these goals and classify water bodies, this study employs classification methods, ion ratios, the Piper trilinear diagram, and the Gibbs diagram.

2. Materials and Methods

2.1. Site Description

The experiment was conducted in the second company (40°53′03″ N, 86°56′58″ E) of No.31 regiment, Yuli County, Korla City, Xinjiang, China (Figure 1). The study area experiences an annual average temperature of 10.5 °C and a mean annual total sunshine duration of 2941.8 h. It features a warm temperate continental desert climate with an annual precipitation of 34.1 mm and a mean annual free surface evaporation of 2417 mm. The groundwater level fluctuates between 1.5 and 3 m below the soil surface, and the shallow aquifer above is saline-water-bearing. The bedrock is sedimentary rock, and the predominant soil types are wind-blown sandy soil and brown desert soil. Additionally, the climate and special geographical conditions of this region make it prone to salt accumulation on the soil surface. The soil salt content in the cultivated layer ranges from 0.2% to 1.45%. The soil texture in the area is mainly composed of silt and fine sand, with sandy silt following closely. There is a small amount of locally present silt. In the 0-50 cm soil layer, the predominant texture is sandy loam, while the 50-100 cm layer consists mainly of sandy soil with strong water permeability.

2.2. Sample Collection

Water samples were collected during the winter irrigation salt leaching experiment conducted from November to December 2019. The samples comprised irrigation water, phreatic water, initial farmland drainage water, medium-term farmland drainage water, and final farmland drainage water. A total of 23 water samples were collected, and the sampling locations are shown in Figure 2, including 5 samples in field 1 (I1, GW1, and D1-D3 in Figure 2), 5 samples in field 2 (I2, GW2, and D4-D6 in Figure 2), and 13 samples in field 3 (I3, GW3, GW4, GW5, and D7-D15 in Figure 2). Field 1 and field 2 were subsurface-pipe drainage fields, and field 3 was a ditch drainage field. In subsurface-pipe drainage fields, the irrigation water sampling points (I1 and I2) were located at the end of the agricultural canal, and the phreatic water sampling points (GW1 and GW2) and farmland drainage water sampling points (D1-D3 and D4-D6) were located in the collecting wells. In the ditch drainage field, the irrigation water sampling point (I3) was located at the end of the agricultural canal. The phreatic water sampling points (GW3-GW5) and farmland drainage water sampling points were located in the upstream (D7, D10, and D13), midstream (D8, D11, and D14), and downstream (D9, D12, and D15) sections of the drainage ditch. In summary, phreatic water samples were taken from collecting wells or ditches before irrigation, while farmland drainage water samples were taken from collecting wells or ditches after drainage. Pre-washed polyethylene bottles were used to collect samples and were subsequently rinsed with the obtained samples. The collection details are shown in Table 1. In situ measurements of water samples included electrical conductivity (EC) and pH, conducted using a DDS-307A conductivity meter and phs-25 pH meter, respectively. Prior to use, the DDS-307A conductivity meter (Changzhou Zhongjie Experimental Instrument Co. Ltd., Changzhou, China) and phs-25 pH meter (Shanghai Yonggui Analytical Instrument Co. Ltd., Shanghai, China) must be calibrated. For the DDS-307A conductivity meter, a 100.0 μS/cm concentration of calibration solution was prepared, and then the DDS-307A conductivity meter was used to measure the solution’s conductivity with the selector switch knob set to “check”, the “constant” compensation adjusting knob aligned with the “1” scale line, and the “temperature” compensation adjusting knob set to the “25” degree line. The “Calibration” knob was adjusted until the conductivity meter displayed 100.0 μS/cm, completing the calibration. The phs-25 pH meter calibration involved preparing a calibration solution with a pH value of 6.86. The pH meter was then used to measure the solution’s pH, with adjustments made to the temperature regulator to match the solution’s temperature. After stabilization of the reading, it represented the pH value of the calibration solution. Any discrepancies were addressed by adjusting the positioning regulator. Hydrogen and oxygen isotopes were tested at the State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences (Wuhan). The samples were filtered with a needle filter (filter membrane: 0.22 microns) and tested using the MAT253 Stable Isotope Mass Spectrometer (Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany) before being placed on the machine. To obtain the final results, each measured sample and standard was subjected to six injection measurements, with one standard sample per three samples. It must be noted that the obtained results indicate that the δD error is ±0.6‰ and the δ18O error is ±0.2‰. All samples used for the determination of hydrogen and oxygen isotopes and water chemical ions were stored in well-sealed plastic bottles of 500 mL in size and refrigerated at 4 °C until analysis.

2.3. Sample Measurements

2.3.1. Hydrogen and Oxygen Isotopes

Hydrogen and oxygen isotopes were measured using the MAT253 Stable Isotope Mass Spectrometer, manufactured by Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany. All isotopic ratio results of samples were reported in δ-notation (‰) relative to the international Vienna Standard Mean Ocean Water (VSMOW) standard, and the isotope compositions (δD or δ18O) were calculated as follows:
  δ = ( R s a m p l e R s t a n d a r d ) R s t a n d a r d × 1000
where δ represents δD or δ18O, and Rsample and Rstandard are the D/H (or 18O/16O) molar ratios of the sample water and standard water (VSMOW), respectively. The analytical precision was ±0.6‰ for δD and ±0.2‰ for δ18O.

2.3.2. Major Ions

The cations (K+, Ca2+, Na+, and Mg2+) of samples were measured using an iCAP-6300 inductively coupled plasma atomic emission spectrometer (Thermo Fisher Scientific, Waltham, MA, USA), anions such as Cl, NO3 and SO42− were measured by an ICS-2100 ion chromatography (Thermo Fisher Scientific, Waltham, USA), and HCO3 was measured by acid–base titration. Chemical analyses were only accepted when the precision was greater than ±5% for major ions.

3. Results and Discussion

3.1. Isotopic Characteristics

According to data from the China Meteorological Data Service Center “https://data.cma.cn/ (accessed on 8 January 2020)”, Korla Meteorological Station recorded a precipitation of 65.6 mm in 2019 with no rainfall in November and December. Therefore, evaporation during the winter irrigation salt leaching experiment can be considered negligible. Farmland drainage water was mainly a mixture of irrigation water and phreatic water. The δD and δ18O in farmland drainage water were mainly affected by δD and δ18O in irrigation water and phreatic water. Consequently, the sample points of irrigation water, phreatic water, and farmland drainage water in the same field should exhibit two properties on the δD-δ18O diagram: (1) the sample points of irrigation water, phreatic water, and farmland drainage water being distributed along a straight line; (2) the sample points of farmland drainage water being located between irrigation water and phreatic water.
The sample data of each field in Table 1 were plotted on the δD-δ18O diagram (Figure 3). It is evident from Figure 3 that irrigation water, phreatic water, and farmland drainage water generally formed a straight line (property (1)). However, some sample points did not meet property (2) (the sample points of farmland drainage water being located between irrigation water and phreatic water). For example, consider the phreatic water sample of field 1, the initial farmland drainage water sample of field 2, and the midstream and downstream phreatic water samples of field 3. According to the field records of the winter irrigation salt leaching experiment, it was discovered that the leaching of field 1 was carried out after the leaching in the second field on the east side. Additionally, a collecting pipe was shared between field 1 and the second field on the east side of field 1. When obtaining phreatic water samples from the collecting well in field 1, a significant amount of farmland drainage water from the second field on the east side of field 1 was inevitably mixed. Therefore, it was reasonable to conclude that the phreatic water sample points in Figure 3a were problematic. In field 2, a portion of irrigation water overflowed into the collecting well during the initial stage of farmland drainage. Furthermore, the δD and δ18O content of irrigation water in field 2 was similar to that in fields 1 and 3. Thus, it was reasonable to conclude that the irrigation water sample points were unproblematic, while the initial farmland drainage water sample points shown in Figure 3b were problematic. Before the phreatic sampling in field 3, external water flowed from the branch ditch into the downstream and midstream of the farm ditch due to backwater. Therefore, it was reasonable to conclude that the midstream and downstream phreatic water sample points in Figure 3d,e were problematic.
After excluding problematic data from Table 1, we obtained the statistical characteristics of δD, δ18O, and deuterium excess (d) of various water samples in the study area (Table 2). The δD values of irrigation water, phreatic water, and farmland drainage water range from −47.10‰ to −45.50‰, from −40.70‰ to −38.80‰, and from −44.80‰ to −40.50‰, respectively, and the mean values are −46.53‰, −39.75‰, and −42.14‰, respectively, with standard deviation ranging from 0.73‰ to 1.33‰. The δ18O values of irrigation water, phreatic water, and farmland drainage water range from −6.50‰ to −6.00‰, −4.90‰ to −4.10‰, and −6.00‰ to −4.70‰, respectively, and the mean values are −6.33‰, −4.50‰, and −5.12‰, respectively, with standard deviation ranging from 0.24‰ to 0.46‰. The d values of irrigation water, phreatic water, and farmland drainage range from 2.50‰ to 5.00‰, −6.00‰ to −1.50‰, and −4.00‰ to −3.20‰, respectively, and the mean values are 4.13‰, −3.75‰, and −1.17‰, respectively, with standard deviation ranging from 1.42‰ to 3.18‰. Water-evaporation lines were compared within the same type of water body, and the water-evaporation lines of irrigation water, phreatic water, and farmland drainage water were δD = 3.10δ18O − 26.90, δD = 2.38δ18O − 29.06, and δD = 2.43δ18O − 29.70, respectively. Notably, the slopes of various water-evaporation lines were consistently proved to be lower than those of local atmospheric precipitation lines (δD = 7.17δ18O − 2.98). Furthermore, the water-evaporation line slope of the water body decreased in the following order: irrigation water, farmland drainage water, and phreatic water. This observation indicates that irrigation water and phreatic water underwent significant evaporation before winter irrigation, resulting in substantial isotope enrichment, Moreover, the impact of evaporation on phreatic water was greater than that on irrigation water [34].

3.2. Hydrochemical Characteristics

The hydrochemical characteristics of various water samples in the study area, excluding data with issues, are presented in Table 3. According to the pH (7.24~8.58) of irrigation water, phreatic water, and farmland drainage water, it was found that all types of water were weakly alkaline. The average of total dissolved solids (TDSEC) in irrigation water, phreatic water, and farmland drainage water was 0.59, 6.40, and 4.14 g/L, respectively. The experimental area was located in the arid region of northwest China, with an annual precipitation of 34.1 mm. In addition, during our experimental period, no rainfall occurred, allowing us to disregard the contribution of marine aerosols typically present in rainfall [35]. This indicated that phreatic water contained a large amount of salt compared to irrigation water, and the salt in soil mainly comes from the evaporation of phreatic water [36]. The dominant ions in irrigation water were Na+, Ca2+, HCO3, and SO42−, accounting for 38.2%, 37.1%, 59.1%, and 25.3% of the total cations or anions, respectively. Phreatic water and farmland drainage water exhibited dominance in Na+, SO42−, and Cl. In phreatic water, Na+ accounted for 65.8% of the total cations, and SO42− and Cl accounted for 42.6% and 39.6% of the total anions, respectively. Similarly, in farmland drainage water, Na+ accounted for 62.1% of the total cations, and SO42− and Cl accounted for 40.9% and 36.2% of the total anions, respectively.

3.3. Hydrochemical Type

As a method of hydrochemical analysis, the Piper trilinear diagram was first proposed by Piper in 1944 [37]. The diagram consists of two equilateral triangles and a diamond, and the percentage of milligram equivalent per liter of the main anions (Cl, SO42−, and HCO3+CO32−) and cations (Na++K+, Ca2+, and Mg2+) is the concentration unit. It is mainly used to reflect the hydrochemical types of various water samples, to analyze their possible hydrochemical evolution laws, and to judge whether there was mixing between different water bodies [38,39,40]. In this study, the Schukalev classification method [41] and the Piper trilinear diagram (Figure 4) were used to define the hydrochemical types of various water samples. From the data obtained using the Piper trilinear diagram, it is obvious that irrigation water belongs to the HCO3·SO4·Cl-Ca·Mg·Na water type in field 1 and field 3. In field 1, initial farmland drainage water, medium-term farmland drainage water, and final farmland drainage water belong to the Cl·SO4-Na·Mg water type. In field 3, phreatic water, initial farmland drainage water, medium-term farmland drainage water, and final farmland drainage water belong to the Cl·SO4-Na·Mg water type. In field 2, irrigation water belongs to the HCO3-Ca·Mg·Na water type, phreatic water and medium-term farmland drainage water belong to the Cl·SO4-Na·Mg water type, and final farmland drainage water belongs to the Cl·HCO3·SO4-Na·Mg water type.

3.4. Factors Controlling Dissolved Solutes

According to the correlation between total dissolved salt and Na+/(Na+ + Ca2+) and the correlation between total dissolved salt (TDS) and Cl/(Cl + HCO3), the Gibbs diagram can qualitatively judge the relative importance of natural factors (evaporation dominance, rock–water interaction dominance and precipitation dominance) controlling the hydrochemical characteristics [42] and is suitable for surface water and groundwater [43,44]. The Gibbs diagram shows that when the TDS exceeds 1000 mg/L and the value of Na+/(Na+ + Ca2+) or Cl/(Cl + HCO3) approaches 1, the water sample chemistry suggests evaporation dominance [45]; when the TDS is in the range of 70~300 mg/L and the value of Na+/(Na+ + Ca2+) or Cl/(Cl + HCO3) is close to 0.5, the chemistry of water samples points to rock–water interaction dominance [46]. Conversely, when TDS is less than 10 mg/L and the value of Na+/(Na+ + Ca2+) or Cl/(Cl + HCO3) is near 1, the chemistry of water samples indicates precipitation dominance [47].
According to Figure 5, the TDS of irrigation water in each field varies between 631.33 mg/L and 914.79 mg/L, with the value of Na+/(Na+ + Ca2+) or Cl/(Cl + HCO3) ranging from 0.1 to 0.6. This indicates that the chemistry of irrigation water samples falls under rock–water interaction dominance and evaporation dominance. In contrast, the TDS of phreatic water in each field was more than 1000 mg/L, with the value of Na+/(Na+ + Ca2+) or Cl/(Cl + HCO3) mostly around 0.8, This suggests that the chemistry of phreatic water samples is characterized by evaporation dominance. Since farmland drainage water samples in each field were a mixture of irrigation water and phreatic water, they align with both rock–water interaction dominance and evaporation dominance.

3.5. Origins of Major Ions

To identify salt types in each water sample, this study analyzed the sources of major ions in each sample. Throughout the hydrochemical evolution, various factors influence the major ions in water, with leaching, mixing, evaporation, and cation alternating adsorption being crucial mechanisms [48,49,50,51]. In this experiment, irrigation water and phreatic water were primarily influenced by long-term evaporation. Farmland drainage, a mixture of irrigation water and phreatic water, primarily sourced ions from these two water types, with a minor contribution from soil leaching.
The salt composition of the soil in the study area is shown in Table 4; the result shows that the cations were mainly Na+ + K+, accounting for 57.6% of the total cations, with an average of 18.25 meq/kg. The anions were mainly Cl and SO42−, accounting for 30.9% and 54.0% of the total anions, respectively, and their average values were 11.31 meq/kg and 19.76 meq/kg, respectively.
Analyzing the salt composition of the soil (Table 4) and referencing the classification standard of soil salinization types (Table 5) [52], we determined that the Cl/SO42− equivalent ratio was 0.57, categorizing the soil as the chloride-sulfate type. Additionally, the (Na+ + K+)/(Ca2+ + Mg2+) equivalent ratio and Mg2+/Ca2+ ratio were 1.36 and 0.86, respectively, classifying the soil as the calcium-sodium type.
Based on the soil salinization type and the major ion ratio relationship diagram (Figure 6) for various water samples in the study area, an analysis was conducted on the major ion sources and hydrochemical evolution process. If all Na+ and K+ ions in water samples come from the dissolution of NaCl, the equivalent ratio of Na+ + K+ to Cl should be 1:1 [53]. As shown in Figure 6a, both irrigation water samples and phreatic water samples were located outside the line of Cl=Na+ and tended towards the side of Na+. This suggests that Na+ and Cl of irrigation water and phreatic water mainly come from not only the dissolution of NaCl but also are affected by other sodium salts.
In previous studies, we established that Cl in phreatic water mainly comes from NaCl. According to Table 4, there is a minor presence of Mg2+ in the soil, and the salt in the soil mainly comes from the salt in phreatic water [54]. This implies the presence of Mg2+ in phreatic water. Figure 6b shows phreatic water samples were located outside the line of SO42− = Mg2+ and tended towards the side of SO42−. This suggests that Mg2+ in phreatic water mainly comes from the dissolution of MgSO4, while SO42− mainly comes from the dissolution of MgSO4, with potential additional sulfate sources. The irrigation water was located on the SO42− = Mg2+ line, indicating that the SO42− and Mg2+ in irrigation water mainly come from the dissolution of MgSO4.
As shown in Figure 6c, irrigation water samples were located near the Cl + SO42− = Na+ + Mg2+ line and tended towards the side of Na+ + Mg2+. Combined with Figure 6a,b, it can be seen that besides the dissolution of NaCl and MgSO4, irrigation water samples were also affected by other sodium salts. Phreatic water samples were located near the Cl + SO42− = Na+ + Mg2+ line. By integrating information from Figure 6a–c, it can be seen that Na+, Mg2+, Cl, and SO42− in phreatic water samples mainly come from the dissolution of NaCl, Na2SO4, and MgSO4.
According to Figure 6d–f, the result shows that the irrigation water samples were located on the Ca2+ side near the SO42− = Ca2+ line, on the HCO3 side near the HCO3 = Ca2+ line, and on the HCO3 + SO42− side near the HCO3 + SO42− = Ca2+ + Mg2+ line, indicating that the Ca2+ in the irrigation water mainly comes from the dissolution of CaCO3, and the HCO3 not only comes from the dissolution of CaCO3, but also has the influence of other carbonates. According to Figure 6g, the irrigation water samples were located near the Cl + HCO3 = Na+ + Ca2+ line, indicating that there was still dissolution of Na2CO3 in the irrigation water samples. The phreatic water samples were on the SO42− side of the SO42− and Ca2+ diagram (Figure 6d), near the HCO3 = Ca2+ line (Figure 6e), and on or near the HCO3 + SO42− = Ca2+ + Mg2+ line (Figure 6d), indicating that the Ca2+ in phreatic water mainly arises from the dissolution of CaCO3.
According to the above analysis, the salt in irrigation water mainly comes from rock salt dissolution, calcite dissolution, and gypsum dissolution. The salt in phreatic water mainly comes from rock salt dissolution and calcite dissolution.

4. Conclusions

It is of immense importance to elucidate the hydrochemical characteristics and potential influences on different water bodies during winter irrigation in saline lands. This understanding serves as a crucial prerequisite for analyzing the source composition of water and salt in farmland drainage, optimizing the efficiency of farmland salt discharge, and safeguarding the ecological environment in downstream salt-discharge regions. This study analyzed the hydrogen and oxygen stable isotopes as well as hydrochemical features of various water bodies during winter irrigation, leading to the following key conclusions:
In this study, the average d values in irrigation water and phreatic water were 4.13‰ and −3.75‰, respectively, both lower than the global atmospheric waterline (10‰), indicating significant hydrogen stable isotope enrichment due to evaporation. Notably, phreatic water exhibited greater enrichment than irrigation water. The dominant ions in irrigation water, including Na+, Ca2+, HCO3, and SO42−, classified its hydrochemical type as HCO3Ca·Mg·Na. Conversely, phreatic water and farmland drainage water, dominated by Na+, SO42−, and Cl, fell into the Cl·SO4-Na·Mg hydrochemical type.
The TDS of irrigation water ranged from 631.33 to 914.79 mg/L, with Na+/(Na+ + Ca2+) and Cl/(Cl + HCO3) ratios between 0.1 and 0.6, indicating rock–water interaction and evaporation dominance. Phreatic water, with TDS exceeding 1000 mg/L and Na+/(Na+ + Ca2+) and Cl/(Cl + HCO3) ratios around 0.8, demonstrated a dominance in evaporation. The study area’s soil salinity was classified as the chloride-sulfate type based on the chloride-to-sulfate equivalent ratio and the calcium-sodium type according to the cation equivalent ratio. The main sources of salt in irrigation water are rock salt dissolution, calcite dissolution, and gypsum dissolution. Phreatic water salt primarily derives from the dissolution of rock salt and calcite.

Author Contributions

Conceptualization, X.Z. (Xiaoping Zhou), X.Z. (Xinyu Zhao), Q.Z. and H.S.; methodology, X.Z. (Xiaoping Zhou), H.S. and Q.Z.; software, X.Z. (Xiaoping Zhou); validation, X.Z. (Xiaoping Zhou), X.Z. (Xinyu Zhao) and H.S.; formal analysis, X.Z. (Xiaoping Zhou); investigation, H.S., X.Z. (Xiaoping Zhou) and Q.Z.; resources, X.Z. (Xiaoping Zhou); data curation, X.Z. (Xinyu Zhao) and H.S.; writing—original draft preparation, X.Z. (Xinyu Zhao) and X.Z. (Xiaoping Zhou); writing—review and editing, H.S., X.Z. (Xinyu Zhao), X.Z. (Xiaoping Zhou) and Q.Z.; project administration, X.Z. (Xinyu Zhao) and H.S.; funding acquisition: X.Z. (Xinyu Zhao), X.Z. (Xiaoping Zhou) and Q.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by China Geological Survey, grant number DD20230116; Natural Science Foundation of Jiangxi Province, grant number 20202BABL204068; and Jiangxi Provincial Technology Innovation Center for Ecological Water Engineering in Poyang Lake Basin, grant number 20212BCD43002. The APC was funded by Nanjing Center, China Geological Survey.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the Institute’s data management regulations.

Acknowledgments

We would like to thank the reviewers and editors for their considerate work before this paper’s publication.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Figure 1. Location of the experiment site in the Xinjiang Province (top) of China (bottom left) and the layout of the fields.
Figure 1. Location of the experiment site in the Xinjiang Province (top) of China (bottom left) and the layout of the fields.
Water 15 03968 g001
Figure 2. Specific location of sampling points in each field. Note: the letters and numbers next to the sampling point are sample type and number, respectively.
Figure 2. Specific location of sampling points in each field. Note: the letters and numbers next to the sampling point are sample type and number, respectively.
Water 15 03968 g002
Figure 3. Relationship between δD and δ18O of various water samples in each field.
Figure 3. Relationship between δD and δ18O of various water samples in each field.
Water 15 03968 g003
Figure 4. Piper trilinear diagram of major ions of various water samples in each field. (a) Piper diagram of field 1, (b) Piper diagram of field 2, (c) Piper diagram of field 3 upstream, (d) Piper diagram of field 3 midstream, (e) Piper diagram of field 3 downstream.
Figure 4. Piper trilinear diagram of major ions of various water samples in each field. (a) Piper diagram of field 1, (b) Piper diagram of field 2, (c) Piper diagram of field 3 upstream, (d) Piper diagram of field 3 midstream, (e) Piper diagram of field 3 downstream.
Water 15 03968 g004aWater 15 03968 g004b
Figure 5. Gibbs diagram of the water samples collected in each field. (a) Field 1 cation Gibbs diagram, (b) field 1 anion Gibbs diagram, (c) field 2 cation Gibbs diagram, (d) field 2 anion Gibbs diagram, (e) field 3 upstream cation Gibbs diagram, (f) field 3 upstream anion Gibbs diagram, (g) field 3 midstream cation Gibbs diagram, (h) field 3 midstream anion Gibbs diagram, (i) field 3 downstream cation Gibbs diagram, (j) field 3 downstream anion Gibbs diagram. Note: TDS in the figure represents total dissolved salt.
Figure 5. Gibbs diagram of the water samples collected in each field. (a) Field 1 cation Gibbs diagram, (b) field 1 anion Gibbs diagram, (c) field 2 cation Gibbs diagram, (d) field 2 anion Gibbs diagram, (e) field 3 upstream cation Gibbs diagram, (f) field 3 upstream anion Gibbs diagram, (g) field 3 midstream cation Gibbs diagram, (h) field 3 midstream anion Gibbs diagram, (i) field 3 downstream cation Gibbs diagram, (j) field 3 downstream anion Gibbs diagram. Note: TDS in the figure represents total dissolved salt.
Water 15 03968 g005aWater 15 03968 g005b
Figure 6. Relationship of major ion ratios of various water samples in the study area.
Figure 6. Relationship of major ion ratios of various water samples in the study area.
Water 15 03968 g006aWater 15 03968 g006b
Table 1. Collection information of various water samples in each field.
Table 1. Collection information of various water samples in each field.
FieldTypeSample No.δD (‰)δ18O (‰)Sampling DateNote
Field 1Irrigation waterI1−47.1−6.521 November 2019
Phreatic waterGW1−43.2−5.720 November 2019*
Initial farmland drainage waterD1−44.2−5.927 November 2019
Medium-term farmland drainageD2−42.2−5.51 December 2019
Final farmland drainage waterD3−41.1−5.34 December 2019
Field 2Irrigation waterI2−47.0−6.519 November 2019
Phreatic waterGW2−40.7−4.917 November 2019
Initial farmland drainage waterD4−47.4−6.520 November 2019*
Medium-term farmland drainageD5−44.8−6.026 November 2019
Final farmland drainage waterD6−44.1−5.84 December 2019
Field 3Irrigation waterI3−45.5−6.023 November 2019
Upstream phreatic waterGW3−38.8−4.120 November 2019
Midstream phreatic waterGW4−42.8−4.720 November 2019*
Downstream phreatic waterGW5−43.3−5.020 November 2019*
Initial upstream farmland drainage waterD7−40.5−4.726 November 2019
Initial midstream farmland drainage waterD8−41.6−4.726 November 2019
Initial downstream farmland drainage waterD9−42.5−4.926 November 2019
Medium-term upstream farmland drainage waterD10−40.8−4.730 November 2019
Medium-term midstream farmland drainage waterD11−40.9−4.730 November 2019
Medium-term downstream farmland drainage waterD12−42.4−4.930 November 2019
Final upstream farmland drainage waterD13−40.8−4.93 December 2019
Final midstream farmland drainage waterD14−41.8−4.83 December 2019
Final downstream farmland drainage waterD15−42.3−4.93 December 2019
Note: * indicates that the sample cannot represent the actual leaching situation; see Section 3.1 for specific reasons.
Table 2. Statistical characteristics of δD, δ18O, and d of various water samples in the study area.
Table 2. Statistical characteristics of δD, δ18O, and d of various water samples in the study area.
TypeMax. (‰)Min. (‰)Mean (‰)SD (‰)
δDIrrigation water−45.50−47.10−46.530.73
Phreatic water−38.80−40.70−39.750.95
Farmland drainage water−40.50−44.80−42.141.33
δ18OIrrigation water−6.00−6.50−6.330.24
Phreatic water−4.10−4.90−4.500.40
Farmland drainage water−4.70−6.00−5.120.46
dIrrigation water5.002.504.131.42
Phreatic water−1.50−6.00−3.753.18
Farmland drainage water3.20−4.00−1.172.78
Note: d is deuterium excess, d = δD − 8δ18O.
Table 3. Hydrochemical characteristics of various water samples in the study area.
Table 3. Hydrochemical characteristics of various water samples in the study area.
TypeEigenvaluepHTDSEC
(g/L)
K+
(mg/L)
Ca2+
(mg/L)
Na+
(mg/L)
Mg2+
(mg/L)
Cl
(mg/L)
NO3
(mg/L)
SO42−
(mg/L)
HCO3
(mg/L)
Irrigation waterMaximum 8.580.669.0775.4085.5742.4997.350.71160.91507.18
Minimum 8.050.527.5973.7571.8840.2378.770.50128.68220.52
Average8.310.598.4974.6076.7541.0285.620.61139.53325.87
Phreatic waterMaximum 8.068.61104.37354.612099.03560.452275.33370.112434.25823.26
Minimum 7.484.2053.40214.39928.05287.981196.0868.601304.23294.02
Average 7.776.4078.88284.501513.54424.221735.70219.361869.24558.64
Farmland drainage waterMaximum 8.286.2269.41253.581381.48400.941673.45185.751986.77757.10
Minimum 7.241.1728.1594.14203.8276.48284.2719.40282.14371.20
Average 7.904.1456.14204.97860.17263.851105.3796.771249.03606.15
Note: TDS in the table represents total dissolved solids.
Table 4. Salt composition of the soil in the study area; unit: meq/kg.
Table 4. Salt composition of the soil in the study area; unit: meq/kg.
CO32−HCO3ClSO42−Ca2+Mg2+Na+ + K+
Maximum8.0016.9277.02128.88100.3837.8485.37
Minimum0.002.593.101.922.021.067.55
Average0.245.3011.3119.767.246.2018.25
Table 5. The division standard of soil salinization types.
Table 5. The division standard of soil salinization types.
Cl/SO42−Salinization Type(Na+ + K+)/(Ca2+ + Mg2+)Mg2+/Ca2+Salinization Type
>2Chloride>2 Sodium
1~2Sulfate-chloride1~2>1Magnesium-sodium
0.2~1Chloride-sulfate1~2<1Calcium-sodium
>0.2Sulfate<1>1Calcium-magnesium
Note: the ratios in the table are equivalent ratios.
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Zhou, X.; Zhao, X.; Zhang, Q.; Sang, H. Major Ion Chemistry of Waters and Possible Controls under Winter Irrigation in the Saline Land of Arid Regions. Water 2023, 15, 3968. https://doi.org/10.3390/w15223968

AMA Style

Zhou X, Zhao X, Zhang Q, Sang H. Major Ion Chemistry of Waters and Possible Controls under Winter Irrigation in the Saline Land of Arid Regions. Water. 2023; 15(22):3968. https://doi.org/10.3390/w15223968

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Zhou, Xiaoping, Xinyu Zhao, Qing Zhang, and Honghui Sang. 2023. "Major Ion Chemistry of Waters and Possible Controls under Winter Irrigation in the Saline Land of Arid Regions" Water 15, no. 22: 3968. https://doi.org/10.3390/w15223968

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