M. Gharekhani; A. A. Nadiri; A. Asghari Moghaddam
Abstract
Due to the infiltration of contaminants from surface to underground water systems, groundwater pollution is one of the serious problems, especially in arid and semi-arid areas that encounter with lack of quality and quantity of water resources. Therefore, groundwater vulnerability evaluation is necessary ...
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Due to the infiltration of contaminants from surface to underground water systems, groundwater pollution is one of the serious problems, especially in arid and semi-arid areas that encounter with lack of quality and quantity of water resources. Therefore, groundwater vulnerability evaluation is necessary to manage the groundwater resources by identifying areas with high potential of contamination. In this study, groundwater vulnerability in Ardabil plain aquifer was evaluated by applying DRASTIC model. DRASTIC model was prepared by seven effective parameters on vulnerability, including groundwater depth, net recharge, aquifer media, soil media, topography, impact of vadose zone, and hydraulic conductivity. These parameters were prepared as seven raster layers, and DRASTIC index was then calculated after ranking and weighting. The DRASTIC index value was obtained between 82 to 151 for the Ardabil plain. The main problem of this model is the subjectivity in determining rates and weights of the parameters. Therefore, the purpose of this study is to improve DRASTIC model using 5 methods of artificial intelligence (AI), such as Feedforward network (FFN), Recurrent neural network (RNN), Sugeno fuzzy logic (SFL), Mamdani fuzzy logic (MFL), and Committee machine (CM) to obtain the most accurate results of vulnerability evaluation. Because of heterogeneity in the Ardabil Plain, it is divided into 3 sections including west, east and north, and each section needs an individual model. For this purpose, the DRASTIC parameters and the vulnerability index were defined as inputs data and output data respectively for models, and nitrate concentration data were divided into two categories for training and test steps. The output of model in training step was corrected by the related nitrate concentration, and after model training, the output of model in test step was verified by the nitrate concentration. The results show that all of the artificial intelligence methods are able to improve the DRASTIC model, but the supervised committee machine artificial intelligence (SCMAI) model had the best results. According to this model, the most of high pollution potential areas located in western and northern parts of the plain, and need more protection.
SH Safari; A Asghari Moghaddam; A Nadiri; K Siahcheshm
Abstract
Arsenic is one of the most toxic and dangerous soluble substances in natural water. It has long-term ill effects on human health. Arsenic-contaminated water resources have been reported from many parts of the world and Iran, particularly from the Kurdistan province in the west of the country. The aim ...
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Arsenic is one of the most toxic and dangerous soluble substances in natural water. It has long-term ill effects on human health. Arsenic-contaminated water resources have been reported from many parts of the world and Iran, particularly from the Kurdistan province in the west of the country. The aim of this study is to identify the source of arsenic and mechanisms of its release into groundwater resources of the Chahardoli plain aquifers. Groundwater resources in this plain supply much of the water needs for drinking, agriculture and industry. Therefore, 31 water samples were collected from the plain aquifer and chemically analyzed for major and minor ions in the Hydrology Laboratory of Earth Sciences Department of the Tabriz University. Also, the trace elements were analyzed in the Kurdistan Waste Water Organization Laboratory. The results show high arsenic concentrations in the groundwater of the area. The highest arsenic concentration (270 µg/L) is related to a well located in the northwest part of the area which supplies water for agricultural purposes of Delbaran sector. According to the results obtained from multi-variable and graphical methods, there is a meaningful correlation between arsenic and major ions such as Na and K as well as silica, indicating that the source of arsenic is from volcanic rocks. It is therefore a geogenic rather than an anthropogenic phenomenon. The mechanism of arsenic releases into the water can be related to competitive adsorption of dissolved SiO2 in adsorption sites such as oxides of iron, aluminium and manganese.
A Asghari Moghaddam; R Barzegar
Abstract
The Tabriz plain with an area of more than 700 km2 is extended from the eastern limit of Tabriz city to the salt flats of UrmiaLake. There are two types of aquifers in this plain with different quality of groundwater. The unconfined aquifer, which is extended all over the plain, in recharge areas near ...
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The Tabriz plain with an area of more than 700 km2 is extended from the eastern limit of Tabriz city to the salt flats of UrmiaLake. There are two types of aquifers in this plain with different quality of groundwater. The unconfined aquifer, which is extended all over the plain, in recharge areas near the plain margins has good quality water but in the central part of the plain along the Aji Chay river as well as in the west margin of the Plain is saline. The multi-layer confined aquifers, which lie down in central and western parts of the Plain bearing more or less good quality groundwater. The arsenic concentration of these aquifers is also different; the water samples analyzed from the chemical point of view especially with respect to concentration of arsenic show two different groups of groundwater. The aim of this study is considering of arsenic spatial distribution and factors controlling high arsenic concentration in the aquifers. For this purpose 16 water samples, with evenly distributed in the Plain, were collected from the aquifers, two water samples for each well, one for analyzing major ions and the other for trace elements. They were analyzed in hydrology lab at the TabrizUniversity. The arsenic concentration in unconfined aquifer and in recharge areas of the plain boundary is low and in confined and deep wells is high. Arsenic concentration compared on the basis of their dependency on hydrogeological conditions, nitrate and phosphate concentrations and pH and the results interpreted by factor analysis and hydrogeochemical methods. Attendance of nitrate and phosphate by positive factor and arsenic by negative factor can show the reduction conditions in groundwater system, which caused the arsenic mobilization. In spite of high arsenic concentrations in the water samples, the saturation index of arsenic minerals is very low and under saturation. The arsenic existing in groundwater resources of the area originate from the geological formations and its concentrations depend highly on the hydrogeological and environmental reduction conditions, residence time of water in underground layers and depth of the sampling wells.
