Abstract
Groundwater resources along with surface-water meet the needs of urban, industrial, and agricultural sectors, and therefore, their quality should be examined. Water quality indices are useful tools for aquifer management. In this research, the groundwater quality of the Miandoab Plain in the province of West Azerbaijan, northwest Iran, for agricultural purposes was investigated. For this purpose, the concentrations of the ions Mg2+, Ca2+, Na+, HCO3−, SO42−, Cl− and the pH level were measured. The indices effective salinity and potential salinity as well as sodium adsorption ratio and electrical conductivity were analyzed to evaluate the salinity. The geostatistical analysis was performed using the GS+ software, and the zoning maps of salinity hazard were prepared using ArcGIS. To prepare the maps, electrical conductivity (EC), effective salinity (ES), potential salinity (PS), and sodium adsorption ratio (SAR) as well as Mg2+, Ca2+, Na+, HCO3−, SO42, and Cl− were selected based on the semi-variogram values and cross-validation technique. The Cl− map was considered as the basis for preparing the groundwater quality maps of the region. The results showed that the groundwater quality in the east of the plain is suitable, in the central part can be recommended under constant supervision, and in the west is unsuitable for agriculture. In other words, according to the geography of the plain, the recharge area is the low-risk part of the plain and the salinity hazard increases toward the discharge area. The results can pave the way for the relevant organizations to plan for the agricultural and environmental sectors.
Highlights
Optimum use of groundwater requires proper management of exploitation which in turn needs scientific and principled knowledge of water resources in a region
The results revealed that the groundwater quality was mainly controlled by the sodium and bicarbonate ions which defined the composition of the water type to be Na HCO3
The chloride semi-variogram obtained by the Gaussian model displayed the best spatial distribution of electrical conductivity (EC), effective salinity (ES), potential salinity (PS), and sodium adsorption ratio (SAR) as well as Hco3and Na+ in the plain
Summary
Optimum use of groundwater requires proper management of exploitation which in turn needs scientific and principled knowledge of water resources in a region. Limited studies have been conducted on the groundwater of the Miandoab Plain: Emami et al (2018) predicted the groundwater level of the Miandoab Plain using the artificial neural network (ANN), and the election (EA) and genetic (GA) algorithms They concluded that the EA, with a root mean square error (RMSE) of 0.027, coefficient of correlation (R2) of 0.93, and Nash-Sutcliffe efficiency coefficient (NSE) of 0.74, had a better performance in predicting the groundwater level than the ANN and GA. The results showed that out of the water no longer pumped, respectively 34 and 41 mcm flow out of the downstream area toward Lake Urmia as underground stream. Respectively 40 and 51 mcm discharge into the surface-water resources, and the remains are stored in the plain. They stated that the continuation of this condition for five years would lead the middle lands of the plain to be swamped. The optimized map showed that about 18, 11, 28, 26, and 17 percent of the plain are located in the very low, low, medium, high, and very high vulnerable areas, respectively
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