فهرست مطالب زهرا صدقی

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.

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.

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.

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.

Nowadays, the issue of freshwater supply is the main concern of researchers in the arid and semi-arid countries like Iran. Available water resources are necessary to be protected against pollution due to arid climate and frequent droughts and lack of water resources. One of the ways to protect groundwater against pollutants is to identify the areas with high potential of pollution. The quality of groundwater and surface water resources of Varzeqan plain can also be affected by the wastewater from the Sungun Copper Mine, which is impounding in tailing dam the north of Varzeqan plain. The groundwater flow direction is from west to east which thought to coincide with the surface water flow direction. The theory of groundwater vulnerability was first introduced in the 1960s in France to create an alertness of groundwater contamination. Several studies were carried out in different parts of the world to assess the pollution and vulnerability of groundwater. Many approaches have been developed to evaluate aquifer vulnerability. They include process-based methods, statistical methods, and overlay and index methods. One of the most common frameworks for assessing the vulnerability is the DRASTIC and SINTACS. The DRASTIC framework was developed by the National Groundwater Association (NGWA) in collaboration with the United States Environmental Protection Agency (USEPA). The SINTACS method used in this study was developed to evaluate relative groundwater pollution vulnerability using seven hydrogeologic parameters. In this paper, to assessment aquifer intrinsic vulnerability, a point count system framework called SINTACS and DRASTIC was selected, Also, in this study, the Corrected SINTACS framework has been introduced for the first time in assessing the vulnerability of confined aquifer.

Hydrogeological, geological characteristics of the study area The results of geophysical study and exploratory wells, piezometer and observation logs prepare evidence to identify two types of aquifers: alluvium aquifer including unconfined (with approx. 150 km2) and confined (with approx. 57 km2) aquifers. Confined aquifers surrounding by the unconfined aquifer and hence multiple aquifers and just alluvium aquifer located in the plain. The aquifers within the study area are a complex system and comprise two confined aquifers, surrounded by one unconfined aquifer. Varzeqan alluvium aquifers classified into three main hydraulic conductivity sections (i) High hydraulic conductivity (about 90 m/d) area in the eastern part of the plain composed of coarse-grain size sedimentary; and (ii) Moderate hydraulic conductivity (about 25 m/d) area in the central part of the plain composed of sand, gravel, and silt grains; and (iii) Low hydraulic conductivity (about 8 m/d) area in the western part of the plain composed of silt, clay and slightly sand. DRASTIC framework DRASTIC is an acronym of seven hydrogeological parameters comprises depth of groundwater (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of vadose zone (I) and hydraulic conductivity (C). Each of these parameters is assigned a rate and a weight according to their relative importance. To prepare a vulnerability map, the required data of various parameters are given to ArcGIS software package in order to perform GIS processing, then, the vulnerability map is prepared. The overall DRASTIC vulnerability index (DVI) is calculated using Eq. 1. As follows, DVI = DwDr + RwRr+ AwAr + SwSr + TwTr + IwIr + CwCr (1) Where D, R, A, S, T, I, and C represent the DRASTIC parameters, and the r and w subscripts correspond to the rates and weights respectively. SINTACS framework SINTACS is an updated model of DRASTIC frameworks and includes seven parameters such as water table depth (S), net recharge (I), unsaturated zone (vadose zone) (N), soil media (T), aquifer media (A), hydraulic conductivity (C) and topographic slope (S).The SINTACS is similar in type and number of parameters to the DRASTIC model, but the rates and weights of this framework are different from the DRASTIC. Vulnerability index is calculated using Eq. 2. ISINTACS= ∑7 i=1 Pi*Wi (2) Where ISINTACS is the SINTACS vulnerability index, Pi is the rating of each parameter and Wi is the relative weight of SINTACS parameters. Corrected SINTACS framework In this study, Corrected SINTACS framework is presented for the first time to assess the vulnerability of confined aquifer that mechanism of this framework is derived from DRASTIC in the evaluation of confined aquifer and how to rate and assign the weight of the proposed framework, such as SINTACS in unconfined aquifer. DRASTIC and SINTACS differ from Corrected SINTACS for confined aquifer in the process of preparing the layers and the difference in rating for this framework.

Results of DRASTIC, SINTACS and Corrected SINTACS frameworks The objectives formed for the present study involve carrying out intrinsic vulnerability assessment using DRASTIC and SINTACS frameworks to priorities area according to their vulnerability to contamination. After preparing the raster layers of the frameworks, these layers were combined using the Raster Calculator command in the ArcGIS software and final vulnerability map was obtained. The vulnerability index based on DRASTIC in unconfined aquifer, varied in the range of 91 to 160 and for confined aquifer of 48 to 93, That's unconfined aquifer 33, 59, 8% of the study area is located in areas with low, medium and high vulnerability, respectively and for confined aquifer, 26%, 53%, 21%, respectively, are located in areas with low, medium and high vulnerability. The results of the evaluation with SINTACS framework for unconfined aquifer showed a number between 123-188, based on this, 12, 53 and 35% of the plain are located in areas with low, medium and high vulnerability, respectively. In assessing the confined aquifer using corrected SINTACS, the vulnerability index range was between 80-133. Validation In order to find out more accurately and compare the frameworks in this study, the correlation coefficient between vulnerability maps and nitrate data was calculated. Nitrate concentration data were used to validate the frameworks used in the study area separately for both types of aquifers, that is for unconfined aquifer, the results show a relative correlation with the value of R2 equal to 0.59 and 0.24 for DRASTIC and SINTACS, respectively. The value of the correlation coefficient in confined aquifer, for Corrected SINTACS and DRASTIC is 0.55 and 0.3, respectively. The CI between vulnerability maps and nitrate concentration were used for validation of the frameworks. The results show that DRASTIC and Corrected SINTACS have higher CI for the unconfined and confined aquifer, respectively. To more accurately assess and select the best vulnerability assessment framework for both types of aquifer, the (CI) method was used.

The purpose of this study was to determine the intrinsic vulnerability in multiple aquifer of Varzeqan plain using DRASTIC and SINTACS frameworks and finally, to compare the efficiency between them. In this study, simultaneous assessment of the intrinsic vulnerability of two aquifers confined and unconfined of Varzeqan plain and the determination of areas with contamination potential based on the hydrogeological conditions of the study area has been investigated. In this study, Corrected SINTACS has been proposed to assess the vulnerability of confined aquifer. Varzeqan multiple aquifer vulnerability index indicates that this aquifer is classified the capability of the contamination potential is in the medium to high range that in the unconfined aquifer due to the low water table depth, lower thickness of the unsaturated region and high hydraulic conductivity and for the confined aquifer due to the thickness of the impermeable layer. To assess the ability of frameworks in both aquifer, in fact, (R2) and (CI) were used to validate the frameworks. The results showed that DRASTIC with higher correlation coefficient (R2) and correlation index (CI) values than SINTACS values is the better framework to vulnerability assessment of unconfined aquifer in Varzeqan plain. However, Corrected SINTACS have higher performance than DRASTIC for confined aquifer. In determining the vulnerable points of the confined aquifer, the most important factor is the thickness of the impermeable layer (clay and silt), whatever this layer is thicker, the possibility of contaminant transfer is less and as a result, the vulnerability index values will decrease.

  Population growth and the development of the agriculture and industry and the excessive use of groundwater resources have caused a drop in the water level. In arid and semi-arid areas, aquifer water management plays an appropriate role within human health of river basins and, therefore, their protection from anthropogenic contamination sources can be managed by proactive tools based on the aquifer vulnerability indices. The groundwater system does not respond quickly to contaminants. The arrival and diffusion of pollutants to groundwater occurs over time. Groundwater contamination is identified using the aquifer to provide water. Consequently, complete elimination of pollution is a long and often impossible process.The concept of vulnerability was first introduced in the late 1960s in France to provide information on groundwater contamination. The SINTACS framework is a suitable prescriptive approach but despite its popularity, it is susceptible to the need for expert judgment on assigning weights and rates for each parameter, which expose the output vulnerability maps to uncertainties in the same study area. Among different AI techniques, the current study was based on Mamdani Fuzzy Logic (MFL) to remove the expert opinion applied to SINTACS indices. The Bilverdi sub-basin, with an area of 289 km2, is located approximately in 65 km of Tabriz city, East Azerbaijan, Iran. There is a vallilu arsenic mine to the north of Bilverdi plain. There are 208 wells, 7 springs, and 17 qanats in the study area.There is a possibility that the mine drainage leaks into the water resources and also extensive agricultural activities in the region increase the need to evaluate the vulnerability of the Bilverdi plain. In this study, SINTACS methods were used for the assessment of the inherent vulnerability of the Bilverdi plain aquifer. The SINTACS method is a PCMS which was developed by Civita and De Maio(2004) in order to assess the intrinsic vulnerability of groundwater with an increasing weight parameters and the wider range of ratings than the DRASTIC method. The acronym SINTACS originates from Italian words. The SINTACS method uses seven effective environmental parameters including Soggiacenza (depth of water), Infiltrazione efficace (effective infiltration), Non saturo (vadose zone), Tipologia della copertura (soil cover), Acquifero (aquifer), Conducibilità idraulica (hydraulic conductivity), and Superficie topografica (slope of topographic surface) to assess the vulnerability of the aquifer. After assigning weight and rate in the ArcGIS software, it was prepared as raster layers. Then SINTACS optimization was performed using Mamdani Fuzzy Logic (MFL). In this research, for the first time, the SINTACS method was optimized with artificial intelligence methods. Seven layers of the SINTACS method as an input and the SINTACS index corrected with nitrate were selected as the output model.


The SINTACS vulnerability Index Obtain by overlaying these seven layers and the Mamdani Fuzzy Logic (MFL) were used to optimize the SINTACS method and the data was divided into two categories of train and test. After model training, the model results were evaluated by the nitrate concentration through coefficient of determination (R2) and correlation index (CI) criteria. The results are as follows: The SINTACS Vulnerability Index was estimated to be between 70 and 169, of which 30, 67 and 3% of the study area were respectively located in low, medium, and high vulnerability zones.The results of the validation of the vulnerability maps with measured nitrate concentrations showed a correlation index (CI = 29). The results of the Mamdani Fuzzy Logic (MFL) were respectively R2 = 0.9, RMSE = 5.1 and R2 = 0.85, RMSE = 7.79 in the training and testing stages. The Vulnerability map of the numerical index is between 167.23 and 88.94 and the correlation index was (CI = 31). This study used the SINTACS framework to assess groundwater vulnerability for Bilverdi basin, East Azerbaijan, Iran. The combined use of the SINTACS method and the geographical information system (GIS) produced a useful groundwater vulnerability map. The SINTACS index was calculated from 70 to 169. The poor determination coefficient calculated by the basic SINTACS framework made a research case for the application of Mamdani Fuzzy Logic. The results showed that Mamdani Fuzzy Logic (MFL) model showed high capability to improve the results of the general SINTACS and reduced the subjectivity of the model. The most vulnerable areas were in the northeast and southwest plain. The high vulnerability area needed to adopt strategic plans and policies to prevent the pollution of aquifers.

Due to population growth and agricultural development and mining activities in the plain Varzeqan where nitrate concentration exceeds from 5 times the standard World Health Organization (WHO). So, Evaluation of vulnerability and protection of groundwater resources are very important in this area. The DRASTIC method uses seven effective environmental parameters on assessment of aquifer vulnerability such as Depth to groundwater level, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and hydraulic Conductivity, as seven layers were prepared separately for unconfined and confined aquifer by corresponded the rate and weighting. The DRASTIC index value was evaluated for unconfined, confined aquifer 92-163 and 48-93 respectively. The artificial neural network model was used to optimize the DRASTIC method. In these model the DRASTIC parameters were considered as input, and conditioned DRASTIC index were used as output, and the data were divided into two categories of train and test. After model training, the model results were evaluated by the nitrate concentration through coefficient of determination (R2) and correlation index (CI) creteria. The results showed that artificial neural network model show high capability to improve the results of general DRASTIC and reduce subjectivity of model, especially in multiple aquifer.