عطاالله ندیری

Iran's groundwater reservoirs have faced significant and related challenges in the past three decades. The simultaneous decrease in the volume and quality of these waters, which are increasingly contaminated with pollutants, renders them largely unusable for many uses. Therefore, there is an increasing emphasis on evaluating the quality of groundwater and identifying anthropogenic or geogenic factors that affect its quality more than ever before. In this study, the hydrogeochemical pollution caused by major, minor, and trace elements was identified by examining the water table against the electrical conductivity of water resources in Azarshahr plain. Long-term data on water levels and electrical conductivity were obtained from regional water resources in East Azerbaijan province. After initial examination, 33 samples were collected from wells and qanats in the area and transferred to the water laboratory of Tabriz University for analysis. The measured parameters included pH, electrical conductivity, major, minor, and trace elements.The results of chemical analysis showed that the concentrations exceeding the permissible drinking limit for nitrates and elements such as Arsenic, Lead, Nickel, and Chromium. Piper diagrams and Stiff diagrams were used to determine the water type in the area; it was found that the water type is mainly sulfate and bicarbonate-based. The origin of the available water is related to the geological formations in the area as a result of mixing and ion exchange.Furthermore, multivariate statistical analysis using factor analysis revealed four influential factor groups affecting water quality in the area; only the fourth factor was attributed to anthropogenic. In general, most of the trace elements in water sources are influenced by formations and aquifer-rock interactions.The overall trend of groundwater quantity over a 25-year period is relatively stable with a slight downward slope; however, the general trend of electrical conductivity is ascending with a much steeper slope indicating an increase in anthropogenic activities as well as the presence of saline layers, which leads to a decrease in the quality of groundwater. Most of the contaminated samples in terms of major and trace elements are located around Gowgan city at the end of the plain. The pollution at this end is related to dissolution trends along with movement paths of groundwater flow and density of pumping wells in this area.

Azarshahr plain is one of the wide plains in Lake Urmia basin which has an important source of groundwater and it is at risk of nitrate pollution due to the agricultural prosperity in this plain. Therefore, it is necessary to protect these groundwater resources using the most suitable and inexpensive solutions by identifying the areas exposed to the risk of pollution. In this study, in order to investigate the inherent vulnerability and risk of contamination, geological data, hydrogeological information and geophysical data were used as well as the digital elevation map of SRTM satellite with a spatial accuracy of 30 meters. Also the concentration of nitrate contaminant sampled from 35 different sources with appropriate distribution was used for validation. The pollution risk of Azarshahr plain aquifer was investigated using "Source-Pathway- Receptor" method. In this method, after identifying the source of pollution, the aquifer vulnerability was considered as a pathway. Improved DRASTIC method by SFL, M5P and RS models were used to evaluate the aquifer vulnerability, then the vulnerability map to nitrate contaminant was obtained. Based on the highest correlation (r = 0.87) and the lowest error (RMSE = 0.06), the M5P model was selected as the best model for vulnerability assessment. Finally, the risk map of nitrate pollution was obtained by multiplying the vulnerability of the aquifer (based on the M5P model) and the velocity of the groundwater. The results showed that the pollution risk of aquifer to nitrate pollutant is high in the central part of the aquifer.

Various factors affect the location of the scour hole formed by the falling flow. Among these factors, we can mention the tailwater depth, the height of the falling flow, the velocity of the flow, the cross-section of the flow and the amount of air entering the flow. In the present study, the location of the formation of scour holes was investigated in the hydraulic laboratory of Tabriz University. Also, the ability of artificial neural networks (ANN) and tree models (M5P tree model) in estimating the location of scour holes downstream of dams was investigated using laboratory data and the results of these two models have been compared with the multivariate nonlinear regression method. The results showed that all three methods, the artificial neural network, the M5 tree model and regression method provide relatively accurate results in predicting the location of scour hole. RMSE value for ANN=1.75, M5=3.75 and Regression=3.89, but due to providing simple linear relationships by the M5 tree model, this method can be used as a practical method to determine the location of scour hole. The analysis of the M5 tree model showed that 4 equations with different linear equations model the pattern of changes in the location of scour hole. In addition, the analysis of the laboratory results showed that the regression equations presented in the present study compared to the common method (using projectile equations) have much less error when predicting the location of scour hole. Also, the laboratory results showed that the head passing through the structure is the most effective parameter in the formation of the scour hole.

Marand plain is one of the fertile plains in the province of East Azarbaijan which its aquifer provides drinking, agricultural, industrial water demands of the area. Therefore, the evaluation and protection of the quantity and quality of these water resources is extremely The purpose of this research is the qualitative zoning of Marand plain groundwater in terms of drinking، agriculture and industry. For this purpose, 91 samples were taken from operational wells in June 2019. Hydrogeochemical characteristics and concentration of major and minor ions and some heavy metals were measured by means of standard methods. The usefulness of the Plain groundwater for various consumptions was investigated using graphical methods and quality criteria of Schuler, Wilcox, and Langelier classification. In this regard, the final maps of quality zoning were prepared after creating the raster layers of the effective parameters, classification, and integration using GIS and the geostatistical interpolation method. The industrial, agricultural and drinking water quality were evaluated by using langelier scaling, Wilcox and Schuler methosd, respectively. Analyzing and Interpreting of zoning maps with geological information, land use, distribution of industrial units was carried out in the plain and the results show that the quality of groundwater is inappropriate mainly in the northern, central, western parts of the plain due to the precens of salty and gypsum formations in northen and western part of the plain.

In order to investigate the quality of groundwater in September 2022, 35 samples were collected from various groundwater sources in the Azarshahr plain, and the main elements, nitrates, and trace elements such as chromium, cadmium, nickel, lead, and arsenic, as well as two types of pesticides such as imidacloprid and chlorpyrifos, were analyzed and compared to drinking water standards. The drinking water quality index for the study area was calculated based on the concentration of parameters in the samples, and the health risk of cancerous and non-cancerous diseases for two age groups, children and adults, was calculated using the criteria of the United States Environmental Protection Agency (USEPA). According to the findings of the studies, the region's water quality index is average, and the non-carcinogenic risk index for children and adults is less than one. It is hazardous, but the risk of carcinogenesis in the entire region is greater than 10-4, and its consumption poses health hazards due to skin contact. The health risk of cancer is many times higher in the region's south, in the cities of Azarshahr and Gogan, as well as the adjacent villages. The correlation between the GQI map and the health risk maps revealed that the correlation of carcinogenic risk is greater than the correlation of non-carcinogenic risk, and based on the correlation between the parameters in the region's groundwater, the elements influencing the health risk of carcinogenesis caused by geogenic factors and human activities do not play a significant role.

With the fast development of metropolitans, the huge production of construction and demolish waste has become a challenge for sustainable development of the cities. Although some efforts have been made to promote re-use and recycling of construction wastes. However, landfilling of waste, remained the most common method for the mentioned disposal. Therefore, site selection and finding a suitable place, is one of the most important steps in the management of the wastes. Due to the destructive environmental effects of the landfill, the selection of the suitable site should be done with accuracy and through a scientific process. In this study, considering geological criteria (fault, lithology, morphology and slope), environmental criteria (hydrology, geohydrology, groundwater depth and protected areas) and socio-economic criteria (residential areas, airports, industrial areas, communication lines, mines, transmission lines and land use) through the capabilities of GIS software and using a combination of Buckley fuzzy hierarchical analysis process methods and the ideal option, suitable locations has been selected for disposal of healthy and unhealthy construction waste in Tabriz city. Based on the obtained results, three places in the north, south and east of the Tabriz city have been selected separately for the disposal of healthy and unhealthy construction waste and demolish.

Nitrate is one of the pollutants of drinking water sources in the Maku-Bazargan-Poldasht region as a result of human and agricultural activity. Investigations show that the maximum nitrate content in the water resources of the Maku-Bazargan-Poldasht region has increased from 33 mg/liter to 167 mg/liter at the regional level since 2000, or 15 years ago. Is. This area's drinking water is sourced from a variety of poorly maintained wells, springs, aqueducts, and surface water bodies. The results of this analysis, which collected samples from a number of water sources, show the area's high level of water source pollution. This study is the first to assess the carcinogenic risk of nitrate, which is present at high amounts in the study area. This study is the first to assess whether nitrate, nitrite, and ammonium are carcinogenic due to the high amounts of nitrogen compounds in the study area. The goal of the current study was to evaluate the levels of nitrate, nitrite, and ammonium in the drinking water sources of the Maku-Bazargan-Poldasht region and investigate any potential health issues related to nitrate and nitrite. This was done in compliance with USEPA regulations. An effort was made in this study to present a nitrogen compound risk map that is not carcinogenic, and if such a risk exists, future research by scientists should focus on it and determine the best course of action.

Salmas plain aquifer is one of the aquifers in West Azerbaijan province, which is exposing to contamination risk of various contaminants from geogenic origin such as arsenic. This is due to hot springs and geological conditions of the area. Therefore, it is necessary to assess the contamination risk to arsenic contaminant and identification of high-risk areas in this aquifer. In this study, the contamination risk of Salmas aquifer was investigated using OSPRC method. In OSPRC method, the contamination risk investigated by considering the origin, source, pathways, receptor and consequence. In this method, the source of contamination was identified then specific vulnerability to arsenic contaminants as pathway was investigated using GMDH neural network model and six parameters of SPECTR method. The parameters of SPECTR method are slope, pH, electrical conductivity, hydraulic conductivity, water table and recharge. The testing RMSE and r values of the GMDH neural network model were 0.036 and 0.902, respectively. The contamination risk map was obtained by multiplying the specific vulnerability in the groundwater velocity. This map showed that the risk of contamination to arsenic contaminant is higher in the western and southwestern parts of the aquifer than the other parts of the aquifer. In general, the contamination risk of Salmas aquifer to the arsenic contaminants is very low.

Permeability is one of the parameters affecting water flow in porous environments such as rock and soil mass and is of special importance in geotechnical studies, e.g., the location of important structures such as urban trains. Accordingly, determination of permeability is one of the main goals in geotechnical studies. Also, it is an important parameter in solving geotechnical problems such as seepage, settlement measurement, stability analysis, etc. Due to fact that direct methods (field and laboratory) of measuring permeability are expensive, highly specialized, time-consuming and unreliable, and due to the nonlinear behavior and heterogeneous and anisotropic conditions in hydrogeological environments which cause inherent uncertainty in the methods of direct measurement of this parameter, various artificial intelligence methods which work more accurately than the above methods  have recently been proposed  to compensate for some of these shortcomings. In this study, two individual artificial intelligence methods including Least-Squares Support Vector Machine (LSSVM) and Wavelet-Artificial Neural Network (WANN) were used on lines 1 and 2 of Tabriz Urban Train to predict hydraulic conductivity based on grain size data; then the results of these two individual models were combined by an Artificial Neural Network (ANN) and improved the results under the name of Supervised Intelligent Committee Machine (SICM). Comparison of test step results of the three models presented in this study showed that all the three models had a relatively good performance in predicting hydraulic conductivity, but SICM model with Root Mean Squared Error (RMSE)= 0.000161 cm/sec and Determination Coefficient (R2)= 0.83 provided better results than the individual models.

Varzeqan plain is exposed to extensive agricultural and mining activities, as well as the presence of nitrate and arsenic anomalies in the water resources and supplying drinking water from groundwater resources need to asess the groundwater quality. The results of the analysis of groundwater resources in Varzeqan plain in 39 sampling points for 13 effective parameters including major, minor and trace elements, physical and chemical properties, were used to determine drinking water quality. Results of health risk for groundwater consumers and according to the standards of the World Health Organization (WHO) and the Iranian Industrial Research Standard (ISIRI), show that the most effective of these parameters in the quality of drinking water is nitrate and arsenic. In this study, GQI and GWQI indicators were used for evaluation, and according to the output maps of these two indicators, which show the difference in determining the quality of drinking water in the region, It was not possible to select one of these two indicators to determine the drinking ability of water resources in the region, In order to achieve a single map that more accurately expresses the quality categories of drinking water in the area, the unsupervised method was introduced and used, and the results show that the unsupervised method with a higher CI than the results of the two indicators is a more ideal method for assessing the quality of water resources in the region and it is more accurate to determine the drinkability categories of these resources.

Marand aquifer is one of the large plains with extensive agricultural and industrial activities and it is categorized in critical aquifer class. One of the problems of groundwater decline is groundwater quality changes that affect how they are used and managed. Therefore, in this study, using 46 water samples from wells, qanats and springs in June 2014 and June 2017 and analyzing the parameters of main, secondary and rare ions to calculate the GQI and GWQI groundwater quality indices. According to the output maps of these two indicators, which show the difference in determining the quality of drinking water in the region, it was not possible to choose one of these two indicators to determine the drinking water capacity of the region. The two indicators used, in order to achieve a single map, the method of unsupervised combination was introduced and used. The results indicate that a higher CI than the results of the two indicators. The results showed that Marand plain is in the middle and acceptable classes in terms of GWQI and GQI index. The highest and lowest GWQI and GQI indices were observed in the south and northwest of the plain, respectively. Comparison of drinking water quality index maps of the study area in 2014 and 2017 shows that in 2017 the area of plain, indicates a decrease in water quality over the last 5 years.

Excessive water extraction from aquifers in arid and semi-arid areas poses a serious threat to natural resources and the environment. Damghan's critical forbidden plain has faced a drop in groundwater level in recent years. In this study, the agent-based model has been used to simulate the behavior of effective stakeholders in the region. First, the agent-based model is considered based on the key stakeholders of the region (farmers are the most important consumers of groundwater in the region, Regional Water Company and Agriculture- Jahad), characteristics, behavior, characteristics of the environment, how the interaction between the agents and the environment (Damghan aquifer). Information about exploitation wells and characteristics of the dominant cultivation in the region is related to 1397. To identify the behavior and characteristics of the agents, a visit to the area and interviews with experts and farmers have been done. The characteristics, behaviors, and interactions of agents are expressed by if-then rules or logical operators or by formulated equations. Then, management scenarios in the study area have been studied for 10 years. The results show that the simultaneous implementation of four projects of installing smart meters, modifying well licenses, promoting new irrigation systems, and establishing production cooperatives while maintaining farmers' net incomes will reduce water withdrawal 44% compared to the base scenario. Also, as a result of the implementation of these four projects, the irrigation method of 4000 hectares of agricultural lands will be changed to pressurized irrigation.

Hajilar chai basin located in the western part of varzegan and it may expose to potential of water resources contamination due to placement of Zarrin Dagh Astarkan gold extraction factory in this area. In order to monitor the water sources of the Hajilar chai basin, 12 water samples collected and analyzed in March 2021. The results showed that the concentration of Co, Pb and As are higher than permissible limit of WHO standard for drinking water in some places and probably the source of trace element related to geological formations and water rock interaction. The aim of this study is to evaluate the hydrchemical characteristics and source of contamination of water sources using graphical methods, multivariate statistical techniques such as factor analysis and hierarchical cluster analysis. The result of the graphical methods showed that the most of the water samples have bicarbonate calcium dominate type. The result of the factor analysis show that four factors were affecting the quality of water source. The first, third and fourth components result from affecting of formation on water resources and water rock interaction. The second component show evidences of the anthropogenic activities in the study area. Also, hierarchical cluster analysis classifies the data into three categories. The first cluster data have similar geochemical process and less trace element. In second cluster hydrochemcial equilibrium is not established, which is probably due to the impact of factory activities. In third cluster, the concentration of arsenic is high and probably is originated from geological formation.

Khoy plain is one of the main industrial and agricultural centers in West Azerbaijan province that the water requirement for agriculture, industry and drinking water is generally supplied by groundwater. Therefore, the quality of available water seems very important in this area. Groundwater quality is generally dependent on hydrogeochemical processes that regnant the water resources system. For this purpose, in order to better understand the hydrochemical processes in Khoy plain aquifer, graphical and multi-variable statistical methods were used to interpret the results obtained from the analysis of 54 samples taken in September 2016 from groundwater resources. The results of the Piper diagram and the expanded Durov diagram shows that the groundwater type in the region is mostly calcium and magnesium carbonate, sodium chloride and the mixed type. In hierarchical cluster analysis, the samples are placed in two main clusters and five sub-clusters. The Stiff graphs identified eight general groups with saline, calcareous, basaltic, igneous and calcareous composition, Saline shale composition, shale and lime composition (Marne) and mixed type. The results of the factor analysis method suggested a three-component model for the data. In the first component, sodium, chloride, sulfate, bicarbonate, calcium and magnesium were interdependent; in the second component, nitrate and arsenic were linked; while in the third component, iron was partially related to the others. The first and third factors have geogenic sources and the second factor shows both geogenic and anthropogenic sources for groundwater contaminants.

Investigation of Contamination Potential in the area of Ahar Mazareh Copper Mine and Determination of their Origin.IntroductionInvestigating the quality of water resources in an area is one of the most fundamental issues in the study of contamination. The term “trace elements” generally refers to elements that are present in the environment in small concentrations and can be hazardous at concentrations above the permitted standard of drinking. The origin of these elements can be geogenic or anthropogenic. The geogenic origin of these elements is the earth's crust, and the anthropogenic origin can also be due to industrial, agricultural, and mining activities. One of the strategic tasks in the field of water resources is to provide chemical information in a way that it can be visually reconstructed. Mazraeh mine is one of the copper mines in Iran that uses a lot of water daily to concentrate copper through flotation, which along with other contaminates is directed to the tailings dam, Therefore, it is necessary to study the affected factors to the hydrochemical evolution and quality of surface and groundwater resources and to investigate the relationship between elements and contaminates and its impact on the quality of water resources and most importantly the origin of these elements and their relationship with mining and tailings dams. In this study, Hydrochemical study of water resources in the study area has been done by plotting methods such as Piper and Stiff diagrams. Multivariate statistical methods such as factor and cluster analysis were used to evaluate the origin of the trace elements.Materials and MethodsMazraeh copper mine is located 5 km from Mazraeh, and 120 km from Tabriz. It is located in the north of East Azarbaijan. Geologically, the study area is part of the Alborz-Azarbaijan structural unit. The geological map of the study area shows that the oldest geological units in the study area belong to the Cretaceous. Mazraeh copper mine reserves are of the iron and copper skarn index type. In general, in this study, on average, about 16 water samples were collected monthly from surface and groundwater resources in the area of the Mazraeh copper mine; The samples include 8 water samples from piezometers in the area, 1 sample from tailings dam, 1 sample from overflow of the tailings dam, 1 sample from water well of the village near the mine, and 5 samples from springs. Discussion of ResultsThe amount of electrical conductivity also varies between 254 and 1774 μS / cm. The amount of the concentrations of the major cations and anions in terms of the median are "potassium ConclusionsBased on the results, the Piper and Stiff diagrams plotted for water, the water type was mainly divided into two groups of sulfate and bicarbonate; the resource of water in the area corresponds to the geological formations of the area. The results of chemical analysis of about 290 water samples showed that some trace elements such as cadmium, lead, and cobalt have more concentrations than the standard of drinking water. The results of factor analysis showed that 4-factor groups were effective in the quality of water resources in the Mazraeh copper mine area. The second and the third factors were geogenic and the first and the fourth factors were affected by both geogenic and anthropogenic factors. The majority of trace elements in water resources are affected by the impact of formations and water-rock interaction. In the clustering method, amount of EC, sulfate, and calcium in the first cluster is more than in the second one, which indicates the effect of dissolution of sulfide minerals such as pyrite and chalcopyrite in the area. The amount of zinc and iron in the second cluster is more than the first cluster.

In recent studies in Iran, arsenic anomalies have shown in excess of the WHO standard (10 ppb) in water resources that the use this water has irreparable effects on human health. Therefore, it is necessary to offer a solution for reducing the arsenic anomalies. In recent years, nanoparticles have been used to reduce the arsenic concentration in water resources at syntheses samples. However, the performance of these nanoparticles to reduce the arsenic concentration in groundwater resources, which generally have different complexes, has not been investigated. In this study, iron oxide nanoparticles have been used to reduce the arsenic anomalies from groundwater resources. Previous studies on iron oxide nanoparticles have been to isolate arsenic added in the laboratory, but the main challenge of this study is the separation of arsenic from groundwater sample. The results of investigation the effective various parameters such as pH, temperature, filtration time and the adsorbent amount on the separation of arsenic from groundwater showed that the highest separation is the temperature conditions above ambient temperature, low pH, time 5 to 15 minutes and the adsorbent amount 0.3 g. Finally, Sugeno fuzzy model was used to simulate and model the process of removing arsenic pollutants from groundwater sources. The fuzzy model results showed this model is very efficient for approximate prediction of arsenic adsorption by iron oxide nanoparticles with NRMSE = 0.03 and R2 = 0.8.

Recently, land subsidence has become one of the serious environmental problems due to increased agricultural and industrial activities. Population growth have caused to groundwater over abstraction and land subsidence in some parts of country such as Ardabil plain. Therefore, identifying, control and management of high potential subsidence areas may help to better understand this complex phenomenon and avoiding the possible damages. In this research, a new framework suggested using seven effective parameters on subsidence to determine areas that are vulnerable to land subsidence and its capability is evaluated in Ardabil plain aquifer. In this framework seven effective parameters on land subsidence including groundwater level decline, aquifer media, recharge, pumping, land use, alluvium thickness and fault are prepared in raster layer format and weights and rates assigned for layers to calculate Subsidence Potential Index (SPI). The SPI for Ardabil plain aquifer was obtained from 80 to 154. According to inherently uncertainty of the assigned weights by expert, genetic algorithm adopted to optimize given weights. The results were compared with subsidence value obtained from radar images and it indicated that optimized framework have relatively better results. The southern and southeastern parts of the Plain shows higher SPI.

In recent years, population growth, urban community development, and consequently increased demand for various water uses such as household and agricultural uses have severely threatened groundwater resources. This issue is highly sensitive in our country due to the arid climate. Therefore, understanding the hydro geological conditions of the aquifers, understanding the groundwater flow and estimating the parameters affecting the ground water flow, such as hydraulic conductivity, is of particular importance in the management, protection, recovery, and exploitation of groundwater. In this study, the hydraulic conductivity was estimated by using artificial intelligence models (artificial neural networks (ANNs), adaptive neuro-fuzzy inference system(ANFIS), and support vector machine(SVM)). For this purpose, the results of geophysical (geoelectric) studies in Maragheh-Bonab plain were analyzed as inputs of the models. Based on the results, the support vector machine showed better performance than the other models with RMSE =1.08 and R ^ 2 = 0.97 in the test phase.

Nitrate is one of the most common contaminants that originates from fertilizers, pesticides or domestic and industrial wastewater. This non-point source contaminant exposes the Salmas plain aquifer to groundwater pollution due to extensive agricultural activity. Therefore, it is necessary to assess the contamination risk of aquifer to high nitrate concentration and identify the high-risk areas in this aquifer. In this research, the contamination risk of Salmas plain aquifer was investigated using DRASTIC-L framework and groundwater velocity. For this purpose, after constructing of DRASTIC-L framework, the weights of eight layers of the framework optimized by genetic algorithm to obtain the aquifer vulnerability map to nitrate contaminant. Finally, the contamination risk map to nitrate was achieved from multiplying the aquifer vulnerability and groundwater velocity. The results showed that against to the eastern and central parts of the aquifer, the contamination risk of the aquifer is high in the western part of the aquifer.

Water resources contaminated with arsenic results from industrial or agricultural activities that causes many environmental problems. One of the mechanisms for arsenic removal from aqueous media is the surface adsorption process. In this study, walnut shell chemically activated by zinc chloride, sulfuric acid, potassium permanganate was used for optimization. Powdered activated carbon produced by iron oxide nanoparticles, and Fe3O4 magnetite were prepared by depositing iron on activated carbon to remove the toxic metal arsenic from aqueous media.

Procedure: 

The synthesis of PAC-AC/Fe3O4 was prepared by chemical co- precipitation method and the physical and structural properties of the adsorbent were analyzed by FESEM-EDX, TEM and FT-IR techniques. Then the effect of pH changes (2-10), contact time (15-240 minutes), amount of adsorbent (0.02-0.1 g), initial concentration of arsenic (2-12 mg.1) were examined and optimized; isotherm and reaction synthetics were also determined.

The optimal conditions for arsenic removal contained magnetic adsorbent pH=2, and 0.02 g of adsorbent at a 6 mg/l concentration at medium temperature. Also, fit diagrams, Freundlich and quasi-quadratic models were determined as isothermal and kinetic optimal models, respectively. The Freundlich model (R2 = 0.999) yielded the maximum absorption of 33.44 mg.g and second order equation of (R2 = 1).

The present study suggested that the synthesized adsorbent had a high potential for the removal of arsenic contaminants. Walnut shell can be used as a suitable adsorbent because of its waste in the country.

Considering the quality of drinking water in human health, an important role should be given to the quality of aquifers as the main source of water supply required for rehabilitation experiences. The purpose of this study was to investigate the groundwater quality required for drinking in the northeast of Bijar plain with GQI index using GIS software. Study area of Bijar plain aquifer is one of the aquifers of Kurdistan province, which is the source of drinking water in part of Bijar city and affects more than 12 villages.. Drinking water quality index was prepared using four methods GQI, GQI-GA, GQI-FL-GA and GQI-FG for this aquifer and then the correlation coefficient and RMSE were used to validate and compare the results of the four methods. Based on the obtained results, GQI-FL-GA method with correlation coefficient of 0.89 and RMSE 0.01 showed the best results and GQI-FG method with correlation coefficient of 0.86 and RMSE 0.11 presented the weakest results. According to this method, about 8.8 and 91.2 percent of the plain has acceptable and suitable quality, respectively, that most of the northeastern parts that are the output of the plain have lower quality than other areas.

Land subsidence due to groundwater over-exploitation is a man-made hazard, and identifying those areas vulnerable to subsidence is of undeniable significance. The present study applies the ALPRIFT method to assess the vulnerability of land subsidence in the Marand plain located in East Azerbaijan province in Iran, which has been at the risk of subsidence in recent years. In the framework of this method that has been developed recently, seven incorporated data layers comprise aquifer media, land use, groundwater pumping, net recharge, aquifer thickness, distance from fault, and water table decline. The data layers were prepared by GIS processing, and the prescribed rates were assigned to the data layers. Then, the data layers were prioritized based on the recommended weights, and the vulnerability map of the region was delineated. In this paper, with respect to the significance of water table decline, two strategies were used in the process of preparing this data layer. In the first strategy, the difference in water levels was used in the first and the last months of a specific year. Based on this strategy, the decline of water table was prepared during 2011-2018. In the second strategy, the trend or slope of water table decline during the same period was used to prepare this data layer. The goodness-of-fit for the vulnerability map and InSAR processing were evaluated by ROC curve. The comparison of the results showed that the estimation of subsidence vulnerability by the first strategy varied for different years; however, the second strategy provided the vulnerability to subsidence regardless of seasonal and temporal fluctuations. Moreover, the result revealed that the southeast and southwest parts of the plain, the Marand city and the Yamchi and Kushksaray residential areas were located in the vulnerable area to subsidence. Moreover, the average subsidence in this plain is 2 cm based on the results of InSAR processing during 2017-2018. The results of this research can be utilized in the planning and management of groundwater abstraction to control subsidence.

The estimation of hydraulic conductivity is one of the most important part of hydrogeological studies which is important in groundwater management. But due to practical, time or cost constraints, direct measurement is difficult. Hence, the using artificial intelligence models with low cost and high performance can be an appropriate alternative for this purpose. Since input data and different training techniques in these models are the most important source of uncertainty, the effect of various sources of uncertainty in output should be considered. In this research a Bayesian Model Averaging (BMA) are developed which includes the model combination of artificial neural network, fuzzy logic and neuro-fuzzy to estimate hydraulic conductivity and uncertainty analysis. In the BMA model, the weight of the models is determined by the Bayesian information criterion (BIC), and the within-model variance, steam from the uncertainty of input data and the between-model variance steam from uncertainty associated with the nature of the artificial intelligence model are calculated. In this study, the developed method has been applied to estimate the hydraulic conductivity in the Urmia aquifer. The results show that although the determination coefficient of BMA is not higher than the determination coefficient of the best model, the output of the BMA is the result of assigning weights that take into account the uncertainty between the models and the input data. Also, the effect of groundwater level variation on estimated hydraulic conductivity from pumpage test up to 2015 was evaluated and the result indicated an insignificant changes in hydraulic conductivity.

The purpose of the present study was to identify the irrigation canals of the spring springs in the city of Sarein and the impact of construction on the hot springs. In this regard, field studies were carried out based on geophysical experiments in the area with geoelectric and ground-penetrating radar devices and hot water mapping was prepared. Based on the results of these experiments, the hot-water trajectory penetrates the ground surface through vertical disruptions at elevated depths through vertical aquifers at specific depths, causing source springs to form. To determine resistivity parameters, soil type and depth of soil, two log wells were drilled at 25 and 30 m depths and groundwater level at 1.5 m depth. For numerical modeling of three modes without building and land alone, the building is present in 5, 10, 15, 20 and 25 stories at 10 to 210 m intervals with 10 m incremental step in static and dynamic modes. The analysis was done. For dynamical analysis, the Turkmanchai earthquake mapping was used and the analysis was performed in Plexis software. The dead and live loads are based on hotel-use buildings. Based on the results above, up to 70 m in the zoned map of the report indicated in red, construction was not permitted and within 80 m of the red border edge, shown in brown Given, it was detected for buildings up to 5 floors and 50 meters later for 10 floors and 30 meters later for 15 floors and then up to 20 floors.

Ahar aquifer is one of the most active agricultural and livestock areas. The development of these activities has led to an increase in the use of chemical and natural fertilizers. Therefore, in this research, groundwater vulnerability in Ahar aquifer has been investigated using three frameworks; DRASTIC, SINTACS and GODS to identify vulnerable areas and prevent groundwater resources from more contamination. To use the simultaneous advantage of all three frameworks, two unsupervised and supervised combination techniques were applied to combine them. Invalidation step, nitrate concentration data and its correlation coefficient with the vulnerability index were used. The results show that the artificial neural networks (ANNs) model has better performance with a better determination coefficient (R2) and correlation coefficient (CI) than other techniques. Therefore, the supervised method has a higher ability than the weighted averaging method and can be used to determine the vulnerability of other areas.