Abstract
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.
Highlights
In the northern Nile Delta (Egypt), surface water is the main water supply for agricultural use, and the ongoing growth of production requires additional fresh water for irrigation.Agriculture developments in Egypt mainly depend on supplying irrigation water through irrigation canals; farmers in the northern part of the Nile Delta are strongly using surface water networks to irrigate their fields because these networks are considered to be the only source of irrigation in the region [1,2,3]
The physicochemical parameters, including cations, anions and trace elements, at 110 surface water points during two years from the northern Nile Delta basin are presented in Table 2, along with the range, mean, and standard error values
The results of the physicochemical parameters across two years revealed that the pH values ranged from 7.1 to 8.7, indicating high alkalinity pH (>6.5), which means that these waters are validated for irrigation according to Ayers and Westcot [36]
Summary
In the northern Nile Delta (Egypt), surface water is the main water supply for agricultural use, and the ongoing growth of production requires additional fresh water for irrigation. Agriculture developments in Egypt mainly depend on supplying irrigation water through irrigation canals; farmers in the northern part of the Nile Delta are strongly using surface water networks to irrigate their fields because these networks are considered to be the only source of irrigation in the region [1,2,3]. Preliminary knowledge on water types, different geochemical processes, and water classification for irrigation is provided by surface water chemistry based on hydrochemical parameters. The chemistry of the water with respect to geochemical criteria offers basic knowledge on water facies, different geochemical processes, and water characterization for irrigation purposes
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