Groundwater
sayyad Asghari Saraskanrood; Maryam Riahinia
Abstract
Today, due to population increase, industrial development, excessive exploitation, droughts, exploitation of underground water has multiplied. Therefore, identifying areas with underground water as one of the important sources for providing drinking water, agriculture, and various industries is considered ...
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Today, due to population increase, industrial development, excessive exploitation, droughts, exploitation of underground water has multiplied. Therefore, identifying areas with underground water as one of the important sources for providing drinking water, agriculture, and various industries is considered to be one of the important and necessary issues in water resources management. The purpose of this research is to investigate and zonate the areas with underground water in Khorram Abad plain located in Lorestan province using convolutional neural network method. For this purpose, maps of nine factors affecting underground water were first prepared in the ArcGist environment. In the convolution method, the number of samples was determined as the ratio between the training set and the test set was 70:30, and the convolution neural network framework was used as 2 convolution layers and 2 integration layers, 2 complete connections. layers and finally the sigmoid layer was used for classification from the 3-3 convolution kernel, the Relu function as the activation function and the cross entropy function as the loss function. The obtained maps were classified into 5 classes: very good, good, average, low and very low. Confusion matrix was also used to validate the results of the model. 30% of the real data was used for evaluation, which resulted in an overall accuracy of 92%, that is, the model was able to correctly identify 92% of the data as underground water and 93% as the absence of underground water. The analysis of the groundwater potential map of the convolutional neural network model shows that about 57% of the area is in low groundwater conditions and 43% of the area is in good groundwater conditions.
Groundwater
nasser jabraili andarian; Ata Allah Nadiri; Maryam Gharekhani
Abstract
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 ...
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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.
Groundwater
Sana Maleki; Vahid Nourani; Hessam Najafi
Abstract
Systems for assessing groundwater vulnerability are designed to protect groundwater resources from pollution. The DRASTIC method is a well-known approach for determining groundwater susceptibility. One drawback of the DRASTIC method is that it relies on expert judgment to rank parameters, which introduces ...
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Systems for assessing groundwater vulnerability are designed to protect groundwater resources from pollution. The DRASTIC method is a well-known approach for determining groundwater susceptibility. One drawback of the DRASTIC method is that it relies on expert judgment to rank parameters, which introduces uncertainty. This study used a new generation of Fuzzy Logic (FL), called the Z-number theory, to estimate the specific vulnerability of aquifers and address this uncertainty. The specific vulnerability of the Ardabil and Qorveh-Dehgolan aquifers was estimated using two scenarios: the DRASTIC parameters as inputs and nitrate concentration values as output. The vulnerability of the aquifer was also evaluated by comparing the results of the proposed models with those of the DRASTIC model, which served as a benchmark. The analysis showed that the Z-number Based Modeling (ZBM), which considered data reliability and weighted the rules appropriately, produced higher-quality results than the classic FL. In the Ardabil plain, the ZBM yielded results that were 53% better (using seven inputs) and 184% better (using four inputs) compared to the classic FL. In the Qorveh-Dehgolan Plain (QDP), the ZBM produced results that were 127% better (using seven inputs) and 311% better (using four inputs) than the classic FL. The irregularity and non-linearity of the data, such as the high coefficient of variation (CV) in the Ardabil plain compared to the QDP, may contribute to the high CV value in the plains. Therefore, in plains with high CV, the quality of the extracted Z-number-based rules may be lower.
Groundwater
Mohammad Hossain Motedayen; Mehrdad Esfandiari; Abolfazl Moeini; Ali Mohammadi Torkashvand
Abstract
In recent years, the irreversible phenomenon of land subsidence has led to environmental hazards in various plains of Iran including Gorgan. In general, the most important activities causing this phenomenon are inappropriate groundwater withdrawal and geological factors. The research method consists ...
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In recent years, the irreversible phenomenon of land subsidence has led to environmental hazards in various plains of Iran including Gorgan. In general, the most important activities causing this phenomenon are inappropriate groundwater withdrawal and geological factors. The research method consists of two sections: identifying subsidence areas and examining the effective factors and parameters and evaluating the impact of each. In identification section, radar interferometry technique was used to compare the phase taken from two radar sets from the same region at two different times and measurement of land surface changes over time can be achieved through interferogram, and in the effective factors analyzing section, the determination and analysis of effective parameters such as water level drop, texture and thickness of soil layers, especially fine-grained layers were investigated. The results of the satellite data analysis indicate that the region is steadily subsiding. The mean velocity map along the satellite line of sight obtained from time series analysis showed a subsidence rate of 14 mm / month (169 mm / year). The identified subsidence range is approximately eastern-western which is consistent with trends in structures such as the Caspian. Figures of water level and precipitation in this area during 2007 to 2009 show a decreasing trend despite of seasonal fluctuations, and analysis of effective parameters shows that the subsidence is due to the same drop in water level or the difference of same thickness of the fine-grained layer at different depths
