Hydrology
Soraya Nouri -Sangarab; Asghar Asghari - Moghaddam; Nasser Jabraeeli-Andrian
Abstract
Recently, due to the trend of decreasing rainfall and increasing groundwater pumping rate, there have been concerns about the risks caused by the decrease in the volume of aquifer reserves and the drop in the groundwater level, and as a consequence the land subsidence. Also, in Ajabshir plain due to ...
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Recently, due to the trend of decreasing rainfall and increasing groundwater pumping rate, there have been concerns about the risks caused by the decrease in the volume of aquifer reserves and the drop in the groundwater level, and as a consequence the land subsidence. Also, in Ajabshir plain due to a gradual decrease in the water level, it is necessary to estimate the subsidence and investigate the subsidence potential to prevent its harmful risks in the future. For this purpose, using the ALPRIFT framework, which includes seven layers of parameters affecting subsidence, the subsidence potential map was zoned. The subsidence potential index was obtained in low and moderate ranges. In the next step, using Sentinel-1 satellite images, the subsidence during the years 2020-2021 was estimated to be 2.4 cm, which had a significant correlation with the groundwater level of the water year 2020-2021 and subsidence potential. In addition, artificial intelligence optimization methods including fuzzy logic (Sugeno) and genetic algorithm were used in order to fix the defects of applying expert opinions and increase the correlation between subsidence (Insar) and ALPRIFT, among these models, Sugeno's fuzzy method provided the best correlation between the two subsidence maps and ALPRIFT. The correlation between subsidence with ALPRIFT, ALPRIFT-GA and ALPRIFT-SFL was obtained as 0.46, 0.62 and 0.72 respectively.
Hydrology
Asghar Asgharai Moghaddam; Ata Allah Nadiri; Faiba Sadeghi Aghdam
Abstract
Naqadeh plain located in the southwestern part of Urmia Lake has suitable water resources. In recent years, agricultural development and increasing industrial units, in addition to inadequate disposal of urban, industrial and agricultural wastewater to the Gedar River, increase the risk of groundwater ...
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Naqadeh plain located in the southwestern part of Urmia Lake has suitable water resources. In recent years, agricultural development and increasing industrial units, in addition to inadequate disposal of urban, industrial and agricultural wastewater to the Gedar River, increase the risk of groundwater contamination. In order to monitor the groundwater resources of this plain, 33 water samples from exploitation wells were collected during July 2016. Hydrochemical parameters and the concentration of the major, minor and heavy metals elements of collected samples were analyzed. In order to identify the origin of heavy metals and the related geogenic and anthropogenic pollution sources of them, hydrochemical diagrams, statistical analysis, spatial distribution maps and geological interpretations were used. The results indicate the concentration of some parameters including EC, and heavy metals include, Fe, Mn, and Al are higher than the international standard limits. HPI was used to understand the drinking quality of groundwater resources in regard to the concentrations of six heavy metals. Classification results show a good quality for 70% and inadequate quality for 30% of the samples. The total HPI index of Naqadeh plain is 23.24, which is lower than its critical values(100). Also, the highest HPI of sampling points with values of 161,220 and 871 threaten human health. High concentrations of heavy metals can be related to the dissolution of geological formations, mining of iron ore, and the activity of industrial units and the condensation of elements in groundwater due to high evaporation in areas with a low depth of groundwater.
Hydrology
Shahrokh Norallahi; A. Asghari Moghaddam; Fijani Elham; Rahim Barzegar
Abstract
In recent decades, due to growth of population and qancequently increasing demand for drinking, agriculture and industry purposes has led to consider the groundwater as the most important resource of water in the area. Therefore, it is necessary to pay attention to the quality of the groundwater in the ...
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In recent decades, due to growth of population and qancequently increasing demand for drinking, agriculture and industry purposes has led to consider the groundwater as the most important resource of water in the area. Therefore, it is necessary to pay attention to the quality of the groundwater in the area, along with its quantity. The objectives of this study are to investigate the possible origin of some heavy metals in the groundwater of Mashgin-Shahr plain using multivariate statistical methods including cluster analysis and factor analysis along with correlation coefficient as well as identification of factors affecting groundwater quality in the area. For this purpose, 25 groundwater samples were collected in October 2016, and measured with respect to pH, electrical conductivity, major (calcium, magnesium, sodium, potassium, chloride, sulfate, carbonate, and bicarbonate) and minor (nitrate, fluoride and silica) ions and some heavy metals/metalloid such as iron, manganese, aluminum, zinc, chromium, copper, cadmium, lead and arsenic. The analyzes show that processes such as weathering and dissolution of evaporatic and silicate formations, ion exchange and agricultural activities are effective on the groundwater quality of the area. The results of multivariate analysis show that most of the heavy are originated from volcanic formations in the area and salinity and acidity play an important role in releasing them into the groundwater. Factor analysis indicates that geogenic processes with a total of 79.9 % of variance and anthropogenic factors with a total of 6.6 % of variance control the groundwater chemistry.
Hydrology
Somayeh Esmaeili; Rahim Barzegar; Naeimeh Kazemian
Abstract
Qareh-Ziaeddin plain is located in the West Azarbaijan province, Northwest of Iran. The aim of this study is to investigate the effective factors and processes on the groundwater chemical quality of Qareh-Ziaeddin plain. For this purpose, 20 water samples were collected from groundwater resources in ...
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Qareh-Ziaeddin plain is located in the West Azarbaijan province, Northwest of Iran. The aim of this study is to investigate the effective factors and processes on the groundwater chemical quality of Qareh-Ziaeddin plain. For this purpose, 20 water samples were collected from groundwater resources in November 2016 and the concentration of the major ions, nitrate and silica was measured. Also, the pH and electrical conductivity of the samples were measured in the field. In this study, different bivariate and hydrochemical diagrams, chloro-alkaline index, saturation index and inverse modeling were used to achieve the mentioned goal. The results of the bivariate diagrams show that the saltwater intrusion from irrigation return flows, cation exchange, weathering and dissolution of rock minerals specially carbonates, silicates, gypsum and halite, and evaporation process, in a small amount, are the effective factors on the chemical quality of the groundwater in the study area. The calculated Chloro-alkaline indices indicate that these indices are negative in all samples, which reveal the normal ion exchange. The water samples are super-saturated with regards to the carbonate and quartz minerals, whereas are under-saturated with respect to the sulfate and halite minerals. The results of inverse geochemical modeling confirm weathering and dissolution of the carbonate, sulfate and halite minerals and ion exchange in different parts of the aquifer.
A Asghari Moghaddam; L Jalali
Abstract
The KhoyPlain is located in the north of West Azarbaijan province, northwest of Iran. The study area has a cold and arid climate with the annual mean precipitation of about 344 mm. The purpose of this study is evaluating of hydrochemical properties of groundwater and determination of arsenic contamination ...
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The KhoyPlain is located in the north of West Azarbaijan province, northwest of Iran. The study area has a cold and arid climate with the annual mean precipitation of about 344 mm. The purpose of this study is evaluating of hydrochemical properties of groundwater and determination of arsenic contamination at this plain. According to the hydrochemical analysis of 36 collected groundwater samples, in some zones of the area, arsenic contamination is exceed the world health organization (WHO) standard for drinking water. The arsenic concentrations of the water samples were increased in the east and southeast part of the study area. Based on the cluster analysis, the samples were posed in three clusters. Each of the clusters divided into subgroups based on heavy metals contain such as arsenic and iron. There is a positive correlation relationship between arsenic and iron, copper, sodium, chlorine, sulfate and EC. The high correlation of arsenic with iron and copper show the high impact of oxides and hydroxides of these elements in absorbing and accompanying in the sediments and consequently in the groundwater. The most saturation indices of arsenic were for FeAsO4:2H2O and Ca3 (AsO4)2:4H2O compounds, showing that change of saturation indices for these two compounds is similar and increasing from recharge to discharge area. Based on factor analysis method, three main effective factors were distinguished on hydrochemistry of the study area. In the first factor, chlorine, sodium, potassium, arsenic, copper, iron and electrical conductivity are effective elements, which have geogenic origin. Consequently, the origin of arsenic can be geogenicthatis related to geological factors, rocks and sediments that come from alteration of geological formations. Therefore, dissolution of minerals from the Miocene deposits such as marl, shale, sandstone and red conglomerate and the Pliocene conglomerate, and interbedded marl and sandstone are the effective sources of arsenic in the aquifer.
A Asghari Moghaddam; E Fijani; A Nadiri
Abstract
Aquifer vulnerability assessment to define critical zones of pollution risk is an important method for groundwater resource management. By applying the DRASTIC model in this study, groundwater vulnerability in the Maragheh-Bonab Plain aquifer was evaluated. The DRASTIC model uses seven environmental ...
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Aquifer vulnerability assessment to define critical zones of pollution risk is an important method for groundwater resource management. By applying the DRASTIC model in this study, groundwater vulnerability in the Maragheh-Bonab Plain aquifer was evaluated. The DRASTIC model uses seven environmental parameters (Depth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity) as seven layer in GIS media and finally a groundwater vulnerability map was created by overlaying the available hydrogeological data and categorized to low, moderate, and high risk. The DRASTIC index value was evaluated 81 to 116 for the study area. The vulnerability map created by DRASTIC is compared to nitrate data and the results indicate a relative correlation between the nitrate level and vulnerability index. In order to improve the model, four artificial intelligence (AI) models are adopted by optimizing the weights of the DRASTIC parameters. The four AI models are the Sugeno fuzzy logic (SFL), the Mamdani fuzzy logic (MFL), the artificial neural network (ANN), and the neurofuzzy (NF). For this purpose, the AI model input (the DRASTIC parameters), output (the vulnerability index), and nitrate concentration data was divided into two categories for training and test steps. The output of model in training step was corrected by related nitrate concentration, and after model training, the output of model in test step was verified by nitrate concentration. The results show that the four AI models are applicable to improve the correlation between nitrate level and vulnerability index using DRASTIC model for groundwater vulnerability assessment. The NF model by taking advantage of FL and ANN has the best results that high nitrate level at observation well location has high vulnerable index and was selected as a final model. According to the final model, the western areas of the aquifer are classified as high pollution risk. In conclusion, the AI approach proved to be an effective way to improve the DRASTIC model and provides a confident estimate of pollution risk for the study area.
