Evidence for the occurrence of hydrogeochemical processes in the groundwater of Khoy plain,northwestern Iran,using ionic ratios and geochemical modeling

Rapid population growth, industrialization, and agricultural expansion in the Khoy area (northwestern Iran) have led to its dependence on groundwater and degradation of groundwater quality. This study attempts to decipher the major processes and factors that degrade the groundwater quality of the Khoy plain. For this purpose, 54 groundwater samples from unconfined and confined aquifers of the plain were collected in July 2017 and analyzed for major cations and anions (Na, K, Ca, Mg, HCO₃, SO_4, and Cl), minor ions (NO₃ and F), and Al. Magnesium and bicarbonate were identified as the dominant cation and anion, respectively. Several ionic ratios and geochemical modeling using PHREEQC indicated that the most important hydrogeochemical processes to affect groundwater quality in the plain were weathering and dissolution of evaporitic and silicate minerals, mixing, and ion exchange. There were smaller effects from evaporation and anthropogenic factors (e.g., industries). Results showed that the high salinity of the groundwater in the northeast area of the plain was due to the high solubility of the evaporitic minerals, e.g., halite and gypsum. Reverse ion exchange and the contribution of mineral dissolution were more significant than ion exchange in the northeastern part of the plain. Elevated salinity of the groundwater in the southeast was attributed mostly to reverse ion exchange and somewhat to evaporation.     

Chemical evolution of a gas-capped deep aquifer,southwest of Iran

The Kangan Aquifer (KA) is located below a gas reservoir in the crest of the Kangan Anticline, southwest of Iran. This aquifer is composed of Permo-Triassic limestone, dolomite, sandstone, anhydrite and shale. It is characterized by a total dissolved solid of about 332,000 mg/L and Na–Ca–Cl-type water. A previous study showed that the source of the KA waters is evaporated seawater. Chemical evolution of the KA is the main objective of this study. The major, minor and trace element concentrations of the KA waters were measured. The chemical evolution of KA waters occurred by three different processes: evaporation of seawater, water–rock and water–gas interactions. Due to the seawater evaporation process, the concentration of all ions in the KA waters increased up to saturation levels. In comparison to the evaporated seawater, the higher concentrations of Ca, Li, Sr, I, Mn and B and lower concentrations of Mg, SO₄ and Na and no changes in concentrations of Cl and K ions are observed in the KA waters. Based on the chemical evolution after seawater evaporation, the KA waters are classified into four groups: (1) no evolution (Cl, K ions), (2) water–rock interaction (Na, Ca, Mg, Li and Sr ions), (3) water–gas interaction (SO₄ and I ions) and (4) both water–rock and water–gas interactions (Mn and B ions). The chemical evolution processes of the KA waters include dolomitization, precipitation, ion exchange and recrystallization in water–rock interaction. Bacterial reduction and diagenesis of organic material in water–gas interaction also occur. A new type of chart, Ca_excess versus Mg_deficit, is proposed to evaluate the dolomitization process.     

Surfactants in the sea-surface microlayer and their contribution to atmospheric aerosols around coastal areas of the Malaysian peninsula

A study was done to determine the concentrations of surfactants on the sea-surface microlayer and in atmospheric aerosols in several coastal areas around the Malaysian peninsula. The concentrations of surfactants from the sea-surface microlayer (collected using rotation drum) and from aerosols (collected using HVS) were analyzed as methylene blue active substances and disulphine blue active substances through the colorimetric method using a UV-vis spectrophotometer. The results of this study showed that the average concentrations of surfactants in the sea-surface microlayer ranged between undetected and 0.36 ± 0.34 μmol L⁻¹ for MBAS and between 0.11 ± 0.02 and 0.21 ± 0.13 μmol L⁻¹ for DBAS. The contribution of surfactants from the sea-surface microlayer to the composition of surfactants in atmospheric aerosols appears to be very minimal and more dominant in fine mode aerosols.     

Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River,Iran

The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels of northwest Iran’s Aji-Chay River was assessed. The models were calibrated, validated and tested using different subsets of monthly records (October 1983 to September 2011) of individual solute (Ca²⁺, Mg²⁺, Na⁺, SO₄ ^2? and Cl^?) concentrations (input parameters, meq L^?1), and electrical conductivity-based salinity levels (output parameter, µS cm^?1), collected by the East Azarbaijan regional water authority. Based on the statistical criteria of coefficient of determination (R²), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency coefficient (NSC) and threshold statistics (TS) the ANFIS model was found to outperform the ANN model. To develop coupled wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies, Symlet or Haar mother wavelets of different lengths (order), each implemented at three levels. To predict salinity input parameter series were used as input variables in different wavelet order/level-AI model combinations. Hybrid wavelet-ANFIS (R² = 0.9967, NRMSE = 2.9 × 10^?5 and NSC = 0.9951) and wavelet-ANN (R² = 0.996, NRMSE = 3.77 × 10^?5 and NSC = 0.9946) models implementing the db4 mother wavelet decomposition outperformed the ANFIS (R² = 0.9954, NRMSE = 3.77 × 10^?5 and NSC = 0.9914) and ANN (R² = 0.9936, NRMSE = 3.99 × 10^?5 and NSC = 0.9903) models.     

Tracing subsurface migration of contaminants from an abandoned municipal landfill

This paper aims at determining of inorganic leachate contamination for a capped unsanitary landfill in the absence of hydrogeological data. The 2D geoelectrical resistivity imaging, soil physicochemical characterization, and surface water analysis were used to determine contamination load and extent of selective heavy metal contamination underneath the landfill. The positions of the contaminated subsoil and groundwater were successfully delineated in terms of low resistivity leachate plumes of <10 Ωm. Leachate migration towards the reach of Kelang River could be clearly identified from the resistivity results and elevated concentrations of Fe in the river downslope toe of the site. Concentration of Fe, Mn, Ca, Na, K, Mg, Cu, Cr, Co, Ni, Zn, and Pb was measured for the subsoil samples collected at the downslope (BKD), upslope (BKU), and the soil-waste interface (BKI), of the landfill. The concentration levels obtained for most of the analyzed heavy metals significantly exceed the normal range in typical municipal solid waste landfill sites. The measured heavy metal contamination load in the subsoil is in the following order Fe ? Mn > Zn > Pb > Cr > Cu. Taking into consideration poor physical and chemical characteristics of the local soil, these metals first seem to be attenuated naturally at near surface then remobilize unavoidably due to the soil acidic environment (pH 4.2-6.18) which in turn, may allow an easy washing of these metals in contact with the shallow groundwater table during the periodic fluctuation of the Kelang River. These heavy metals are believed to have originated from hazardous industrial waste that might have been illegally dumped at the site.     

Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model

Stochastic Environmental Research and Risk Assessment - Water quality monitoring is an important component of water resources management. In order to predict two water quality variables, namely...     

Characterization of hydrogeologic properties of the Tabriz plain multilayer aquifer system,NW Iran

A detailed hydrogeological investigation was carried out in the Tabriz plain in Iran using conventional hydrogeological field investigations and hydrochemistry. The study was carried out because the aquifers are of particular importance as they are more or less the only source of water supply available to the rural population and for agricultural and industrial activities. Analytical and numerical methods were applied to the constant rate pumping test data from the Tabriz airport and the Tabriz Power Station well fields. Two types of aquifers of different water quality were identified in the study area: an unconfined aquifer that extends over the plain and confined aquifers that are found in the deeper layers of the multilayered sediment terraces of the Aji-Chay River course. Therefore, the central part of the Tabriz plain contains both unconfined and confined aquifers, while close to the highlands, there is only an unconfined aquifer. There was evidence of minor leakage in the confined aquifers when the numerical method was used for analysis. The groundwater in the area can be identified by three main geochemical facies: Na-Cl, Ca-HCO₃, and mixed Ca-Mg-Cl-SO₄. The processes responsible for the hydrochemical evolution in the area fall into five categories: dissolution of evaporate minerals, precipitation of carbonate minerals, evaporation, ion exchange, and anthropogenic activity.     

Assessing the hydrogeochemistry and water quality of the Aji-Chay River,northwest of Iran

Aji-Chay River is one of the most important surface reservoirs of northwest of Iran, because it passes through Tabriz city and discharges to Urmia Lake, one of the largest permanent salty lakes in the world. The main objectives of the present study are to evaluate its overall water quality and to explore its hydrogeochemical characteristics, including the potential contamination from heavy metals and metalloids such as Co, Pb, Zn, Cd, Cu, Cr, Al and As. For this purpose, 12 water samples were collected from the main river body and its tributaries within Tabriz plain. The Piper diagram classified water samples mainly into Na–Cl and secondary into Ca–HCO₃ and mixed Ca–Mg–Cl types, denoting a profound salinization effect. The cross-plots showed that natural geochemical processes including dissolution of minerals (e.g., carbonates, evaporites and silicates), as well as ion exchange, are the predominant factors that contribute to fluvial hydrogeochemistry, while anthropogenic activities (industrial and agricultural) impose supplementary effects. Cluster analysis classified samples into two distinct clusters; samples of cluster B appear to have elevated electrical conductivity (EC) values and trace metals concentrations such as Co, Pb and Cd, while SiO₂ and Zn are low in comparison with the samples of the cluster A. The main processes controlling Aji-Chay River hydrogeochemistry and water quality were identified to be salinization and rock weathering. Both are related with geogenic sources which enrich river system with elevated values of Na⁺, Cl^?, Ca²⁺, Mg²⁺, K⁺, SO₄ ^2? and EC as a direct effect of evaporites leaching and elevated values of Pb and Cd as an impact from the weathering process of volcanic formations. According to the US salinity diagram, all of the water samples are unsuitable for irrigation as having moderate to bad quality.     

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