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The objective of this study is to produce groundwater potential map (GPM) and its performance assessment using a data-driven evidential belief function (EBF) model. This study was carried out in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran. It’s conducted in three main stages such as data preparation, groundwater potential mapping using EBF and validation of constructed model using receiver operating characteristic (ROC) curve. At first, 864 groundwater data were collected from spring locations; out of that, 605 (70%) locations were selected for training/model building and the remaining 259 (30%) cases were used for the model validation. In the next step, 12 effective factors such as altitude, slope aspect, slope degree, slopelength (LS), topographic wetness index (TWI), plan curvature, land use, lithology, distance from rivers, drainage density, distance from faults and fault density were extracted from the spatial database. Subsequently, GPM was prepared using EBF model in ArcGIS environment. Finally, the ROC curve and area under the curves (AUC) were drawn for verification purposes. The validation of results showed that the AUC for EBF model is 81.72%. In general, this result can be helpful for planners and engineers in water resource management and land-use planning. [ABSTRACT FROM PUBLISHER]

Hydrogeochemical data of groundwater from the semi-confined aquifer of a coastal two-tier aquifer in Amol-Ghaemshahr plain, Mazandaran Province, Northern Iran reveal salinization of the fresh groundwater (FGW). The saline groundwater zone is oriented at an angle to both Caspian Sea coastline and groundwater flow direction and extends inland from the coastline for more than 40 km. Spearman's rank correlation coefficient matrices, factor analysis data, and values of C ratio, chloro-alkaline indices, and Na/Cl molar ratio indicate that the ionic load in the FGW is derived essentially from carbonic acid-aided weathering of carbonates and aluminosilicate minerals, relict connate saline water, and ion exchange reactions. Saline groundwater samples (SGWS) ( n = 20) can be classified into two groups. SGWS of group 1 ( n = 17) represent the saline groundwater zone below the Caspian Sea level, and salinization is attributed essentially to (1) lateral intrusion of Caspian seawater as a consequence of (a) excessive withdrawal of groundwater from closely spaced bore wells located in the eastern part of the coastal zone and (b) imbalance between recharge and discharge of the two-tier aquifer and (2) upconing of paleobrine (interfaced with FGW) along deep wells. SGWS of this group contain, on average, 7.9 % of saltwater, the composition of which is similar to that of Caspian seawater. SGWS of group 2 ( n = 3) belong to the saline groundwater zone encountered above the Caspian Sea level, and salinization of the groundwater representing these samples is attributed to irrigation return flow ( n = 2) and inflow of saline river water ( n = 1). [ABSTRACT FROM AUTHOR]

Hydrogeochemical investigations were carried out in the Dashtestan, the eastern part of Borazjan, with a focus on fluoride content. The study area is underlain by a complex geology that is dominated by three lithological units, namely marl, alluvial sediments, and carbonate rocks. To assess the major geochemical factors controlling the fluoride enrichment in water, 37 groundwater and 12 surface water samples were collected from the three lithological units. Fluoride concentrations ranged up to 3 mg/L, and average concentrations varied from 1.12 (in carbonate aquifers) to 1.73 (in alluvial aquifers) to 1.82 mg/L (in marl aquifers). To study the influence of rocks and soils on groundwater quality, an additional 41 soil and rock samples were also taken and analyzed for fluoride. The order of average fluoride content in both rocks and soils is: marl > alluvial sediments > limestone, which confirms that marl is a likely source of fluoride. [ABSTRACT FROM AUTHOR]

Prediction of groundwater depth and elevation is important in quantitative water management especially in arid areas. There are several basins in southwest of Iran, in Zagross Mountain, in which the water wells are distributed along a narrow elliptic ring band around the region. To find the most applicable interpolation method, both of the groundwater depth and elevation are predicted by different kriging methods. It is found that the groundwater elevation and depth can be predicted by different methods. Furthermore, it is found that the methods in which the trend is eliminated predicted the groundwater elevation and depth in central part of the region is with less standard error. Furthermore, the methods with no trend elimination, predicted the groundwater depths with less error near the water wells. Dividing the area to hydro-geologically homogeneous sub-areas improved the interpolation precision. [ABSTRACT FROM AUTHOR]

The article presents a study on the feasibility of using an artificial neural network (ANN) methodology for spatiotemporal groundwater level estimation in piezometers located in an aquifer at the Tabriz plain in north-western Iran. It examines the performances of various neural networks for groundwater level forecasting to determine an optimal ANN architecture that can simulate the piezometers water levels. Results of the experiments showed that accurate forecasts can be attained with a standard feedforward neural network trained using the Levenberg-Marquardt algorithm. It reveals that the ANNs yields the most accurate predictions compared with other models.

This study was conducted to evaluate factors regulating groundwater quality in an area with agriculture as main use. Thirty groundwater samples have been collected from Razan area (Hamadan, Iran) for hydrochemical investigations to understand the sources of dissolved ions and assess the chemical quality of the groundwater. The chemical compositions of the groundwater are dominated by Na+, Ca2+, HCO3 −, Cl− and SO4 2−, which have been derived largely from natural chemical weathering of carbonate, gypsum and anthropogenic activities of fertilizer’s source. The production of SO4 2− has multiple origins, mainly from dissolution of sulphate minerals, oxidation of sulphide minerals and anthropogenic sources. The major anthropogenic components in the groundwater include Na+, Cl−, SO4 2− and NO3 −, with Cl− and NO3 − being the main contributors to groundwater pollution in Razan area. [ABSTRACT FROM AUTHOR]