Hydrochemical characteristics and irrigation suitability of surface water in the Syr Darya River, Kazakhstan

Zhang, Weiyan; Ma, Lingling; Abuduwaili, Jilili; Ge, Yingzi; Issanova, Gulnura; Saparov, Galymzhan

doi:10.1007/s10661-019-7713-8

Cited by 49 publications

(35 citation statements)

References 40 publications

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“…The chemistry of surface water based on hydrochemical benchmarks supplies updated knowledge on water types, diverse geochemical processes and water classifications [12][13][14][15]. Therefore, the integration of surface water chemistry and geochemical characteristics offers a valuable context for analysing trends, identifying unique environmental problems, and exchanging information about water sources, geochemical processes, water quality and water susceptibility to contamination [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

Elsayed

Hussein

Moghanm

et al. 2020

Water

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Under sustainable development conditions, the water quality of irrigation systems is a complex issue which involves the combined effects of several surface water management parameters. Therefore, this work aims to enhance the surface water quality assessment and geochemical controlling mechanisms and to assess the validation of surface water networks for irrigation using six Water Quality Indices (WQIs) supported by multivariate modelling techniques, such as Principal Component Regression (PCR), Support Vector Machine Regression (SVMR) and Stepwise Multiple Linear Regression (SMLR). A total of 110 surface water samples from a network of surface water cannels during the summers of 2018 and 2019 were collected for this research and standard analytical techniques were used to measure 21 physical and chemical parameters. The physicochemical properties revealed that the major ions concentrations were reported in the following order: Ca2+ > Na+ > Mg2+ > K+ and alkalinity > SO42− > Cl− > NO3− > F−. The trace elements concentrations were reported in the following order: Fe > Mn > B > Cr > Pb > Ni > Cu > Zn > Cd. The surface water belongs to the Ca2+-Mg2+-HCO3− and Ca2+-Mg2+-Cl−-SO42− water types, under a stress of silicate weathering and reverse ion exchange process. The computation of WQI values across two years revealed that 82% of samples represent a high class and the remaining 18% constitute a medium class of water quality for irrigation use with respect to the Irrigation Water Quality (IWQ) value, while the Sodium Percentage (Na%) values across two years indicated that 96% of samples fell into in a healthy class and 4% fell into in a permissible class for irrigation. In addition, the Sodium Absorption Ratio (SAR), Permeability Index (PI), Kelley Index (KI) and Residual Sodium Carbonate (RSC) values revealed that all surface water samples were appropriate for irrigation use. The PCR and SVMR indicated accurate and robust models that predict the six WQIs in both datasets of the calibration (Cal.) and validation (Val.), with R2 values varying from 0.48 to 0.99. The SMLR presented estimated the six WQIs well, with an R2 value that ranged from 0.66 to 0.99. In conclusion, WQIs and multivariate statistical analyses are effective and applicable for assessing the surface water quality. The PCR, SVMR and SMLR models provided robust and reliable estimates of the different indices and showed the highest R2 and the highest slopes values close to 1.00, as well as minimum values of RMSE in all models.

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Section: Introductionmentioning

confidence: 99%

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

Elsayed

Hussein

Moghanm

et al. 2020

Water

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“…Piper diagram is widely used for water type classification and characterization 30 , 31 ; it enables identifying the hydrochemical facies of natural water. As shown by the Piper diagram (Fig.…”

Section: Resultsmentioning

confidence: 99%

Hydrochemistry of sediment pore water in the Bratsk reservoir (Baikal region, Russia)

Poletaeva

Tirskikh

Pastukhov

2021

Sci Rep

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This study aimed to identify the factors responsible for the major ion composition of pore water from the bottom sediments of the Bratsk water reservoir, which is part of the largest freshwater Baikal-Angara water system. In the Bratsk reservoir, the overlying water was characterized as HCO3–Ca–Mg type with the mineralization ranging between 101.2 and 127.7 mg L−1 and pore water was characterized as HCO3–SO4–Ca, SO4–Cl–Ca–Mg and mixed water types, which had mineralization varying from 165.9 to 4608.1 mg L−1. The ionic composition of pore waters varied both along the sediment depth profile and across the water area. In pore water, the difference between the highest and lowest values was remarkably large: 5.1 times for K+, 13 times for Mg2+, 16 times for HCO3−, 20 times for Ca2+, 23 times for Na+, 80 times for SO42−, 105 times for Cl−. Such variability at different sites of the reservoir was due to the interrelation between major ion concentrations in the pore water and environmental parameters. The major factor responsible for pore water chemistry was the dissolution of sediment-forming material coming from various geochemical provinces. In the south part of the reservoir, Cl−, Na+ and SO42− concentrations may significantly increase in pore water due to the effect of subaqueous flow of highly mineralized groundwater.

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“…The coefficient of variation (CV) is the percent standard deviation of each element in relation to its average value and reflects the degree of variability with respect to the metal concentrations (51% ≤ CV ≤ 100% high; moderate; CV > 100%; CV ≤ 20%, low; 21% ≤ CV ≤ 50%, is exceptionally high variability) [46]. The results revealed that all ions had CVs more than 10%, with CO 3 2− having a CV of almost 100%; in particular, CO 3 2− has a CV of above 100%, which indicated strong spatial variability, showing that these ions are sensitive variables that change with the ecosystem [44].…”

Section: Chemical Compositionmentioning

confidence: 92%

“…The contents of major ions govern the basic hydrochemical properties of surface water [44]. Except for Cl − and HCO 3 − , the mean levels of all ions in water samples are above the WHO [43] guidelines, as indicated in Table 4 Around 60% of the TDS is made up of major cations.…”

Section: Chemical Compositionmentioning

confidence: 99%

Hydrochemical Assessment of the Irrigation Water Quality of the El-Salam Canal, Egypt

El‐Amier

Kotb

Bonanomi

et al. 2021

Water

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The El-Salam canal in Egypt is considered an important stream of fresh water for the agricultural sector that extends from the Nile River to Sinai, while it is subjected to several anthropogenic stresses. In this study, five-georeferenced stations (named from S1 to S5) were monitored along the El-Salam Canal before El-Sahara of the Suez Canal, via the estimation of the WQ index based on major cations and anions analysis including salinity hazard, permeability index, residual sodium carbonate, magnesium hazard, sodium percentage, sodium adsorption ratio, Kelley index, potential salinity, total hardness, and irrigation water quality index (IWQI). The sequence of average concentration of cations in water were Na+ > Ca2+ > Mg2+ > K+. The major cations constitute around 60% of the total dissolved salts. While the sequence of major anions in water were SO42− > HCO3− > Cl− > CO32−. These cations and anions showed an increasing trend from S1 (intake of the canal) to S5 (before El-Sahara) of the El-Salam Canal. Moreover, the order of heavy metals was Zn < Cd < Cr < Ni < Fe < Mn < Co < Cu < Pb. According to the US EPA (1999) guidelines, the levels of Fe and Zn in the El-Salam Canal are within the permissible limits for drinking and irrigation purposes, while Mn, Pb, Cu, Co, Ni, Cr, and Cd were detected at higher concentrations than those recommended. The value of IWQI in water samples varied from 40.26 to 114.82. The samples of S1 showed good water, the samples of region S2 (after mixing with Faraskour drainage) showed poor water quality, samples of regions S3 (after mixing with the El-Serw drain waters) and S5 (before El-Sahara) fell under the very poor water category and samples of region S4 (after mixing with the Hadous drainage) showed unsuitable water. Croplands irrigated with such water will not be exposed to any alkaline risks but will be exposed to the risk of salinity, which is more severe after mixing at the S3 and S4 sites. It is recommended to treat the drainage water before mixing with the irrigation water of El-Salam Canal to raise the suitability of irrigation water for crops, particularly for the Hadous drain.

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Hydrochemical characteristics and irrigation suitability of surface water in the Syr Darya River, Kazakhstan

Cited by 49 publications

References 40 publications

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

Hydrochemistry of sediment pore water in the Bratsk reservoir (Baikal region, Russia)

Hydrochemical Assessment of the Irrigation Water Quality of the El-Salam Canal, Egypt

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