Hosein Aalidadi; Zahra Karimi; Aliakbar Dehghan; Hamed Mohammadi; Maryam Paydar
Abstract
Background and Purpose : Heavy metals are among the most critical contaminants in drinking water, owing to their stability and accumulation capability in living tissues and the food chain. Consequently, this study was conducted to determine the carcinogenic and non-carcinogenic risk assessment indices ...
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Background and Purpose : Heavy metals are among the most critical contaminants in drinking water, owing to their stability and accumulation capability in living tissues and the food chain. Consequently, this study was conducted to determine the carcinogenic and non-carcinogenic risk assessment indices for heavy metals in the water sources of Torbat-e Jam City in 2023.Materials and Methods : Samples were collected from 16 groundwater sources and the surrounding soil of Torbat-e Jam City during the summer and autumn of 2023. Concentrations of five heavy metals - arsenic, mercury, lead, cadmium, and copper - were measured using a Varian atomic absorption spectrometer. Finally, the health risk levels for three different groups were calculated using indices provided by the Environmental Protection Agency (EPA) of the United States.Results: The average concentrations of heavy metals in water during summer were as follows: arsenic: 0.0027 ± 0.0035 mg/L, mercury: 0.00019 ± 0.00035 mg/L, lead: 0.0011 ± 0.0023 mg/L, cadmium: 0.0002 ± 0.0002 mg/L, and copper: 0.0046 ± 0.0078 mg/L. In autumn, the concentrations were arsenic: 0.0082 ± 0.0081 mg/L, mercury: 0.0018 ± 0.0008 mg/L, lead: 0.0056 ± 0.0058 mg/L, cadmium: 0.00084 ± 0.00083 mg/L, and copper: 0.0091 ± 0.0068 mg/L. In soil, the concentrations were arsenic: 0.011 ± 0.053 mg/L, mercury: 0.0086 ± 0.0068 mg/L, lead: 0.131 ± 0.186 mg/L, cadmium: 0.0002 ± 0.00047 mg/L, and copper: 0.12 ± 0.24 mg/L. The study found the non-carcinogenic risk levels of the examined heavy metals to be low. However, the carcinogenic risk level for arsenic was very high in both seasons, for cadmium was moderate in autumn, and for the other elements, it was within the standard limits.Conclusion : Given the high carcinogenic risk of arsenic for women, men, and children in both summer and autumn, continuous monitoring of arsenic levels should be a priority for regulatory agencies.
Mojtaba G.Mahmoodlu; Tara Sotoudehnia
Abstract
Background and Purpose: Groundwater serves as the primary drinking water source in Golestan Province. Therefore, this study aims to assess the non-cancerous health risks associated with nitrate and fluoride in the province's drinking water sources. Materials and Methods: Physicochemical data from ...
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Background and Purpose: Groundwater serves as the primary drinking water source in Golestan Province. Therefore, this study aims to assess the non-cancerous health risks associated with nitrate and fluoride in the province's drinking water sources. Materials and Methods: Physicochemical data from 139 drinking water wells were obtained from the Golestan Province Water and Wastewater Company during the spring and autumn. Significant ion variations were analyzed, and factors influencing the chemistry of drinking water sources in Golestan Province were investigated. Non-carcinogenic health risks posed by nitrate and fluoride were assessed using two indicators provided by the United States Environmental Protection Agency. Results: The maximum nitrate concentration in certain Golestan Province cities exceeds the Iranian drinking water standards (1053) and the World Health Organization's limits. However, fluoride levels in most cities fall below the range stipulated by domestic and international standards. The nitrate risk factor for children in select cities exceeds one, while it remains below one for other age groups. Notably, Khan Bebin City exhibits the lowest nitrate risk factor among the province's cities. Additionally, risk factor values show a slight increase during the autumn season. Non-cancerous health risk assessments for fluoride in drinking water sources across Golestan Province during spring and autumn indicate risk values below one for all age groups, including infants, children, teenagers, and adults. Conclusion: The health risk assessments for nitrates and fluorides indicate that children in certain cities face a higher risk from nitrates than adults. Moreover, the low fluoride levels in the province's drinking water sources increase the likelihood of tooth decay.
Mansour Baziar
Abstract
Background and Purpose: Nitrates have long been considered indicative of drinking water quality and a critical concern for human health. The evolution of advanced models for water quality management has spurred decision-makers to incorporate artificial intelligence technologies into water quality planning. ...
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Background and Purpose: Nitrates have long been considered indicative of drinking water quality and a critical concern for human health. The evolution of advanced models for water quality management has spurred decision-makers to incorporate artificial intelligence technologies into water quality planning. This study aims to employ the AdaBoost model, one of the cutting-edge models in water quality management, to predict nitrate concentrations in groundwater using pH and EC (Electrical Conductivity) as input variables.Materials and Methods: Initially, the study analyzed the Pearson correlation matrix and subsequently determined the input variables for multiple AdaBoost models with varying hyperparameters. A sensitivity and dependence analysis of the model's input variables was conducted to assess their impact on nitrate prediction.Results: The results obtained from the AdaBoost model reveal R-squared (R2) values of 0.915 for the training dataset and 0.924 for the test dataset. Additionally, the Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) scores for the training dataset were recorded as 1.02, 1.01, 0.823, and 7.3%, respectively. For the test dataset, these metrics were observed in the order of 0.228, 0.477, 0.375, and 3.2%. The model's sensitivity analysis identified the pH variable as the most influential factor in nitrate prediction.Conclusion: The model analysis demonstrates that the proposed method performs well in predicting nitrate concentrations. This approach holds significant potential for implementation as an intelligent system for forecasting water quality parameters.
Fariborz Bahrami; Aslan Egdernezhad
Abstract
Background and Purpose: Due to the complexities in the nature of ground water systems, it sounds like a demanding job to model either the time or the location of ground water. However, artificial neural networks have a high capability to model both complicated and non-linear models. Besides, Geostatistic ...
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Background and Purpose: Due to the complexities in the nature of ground water systems, it sounds like a demanding job to model either the time or the location of ground water. However, artificial neural networks have a high capability to model both complicated and non-linear models. Besides, Geostatistic Methods are, to a good extent, accurate in modelling ground water.Material and Methods: The aim of this study is to simulate groundwater quality parameters (SAR, TDS and EC) of Dezful Andimeshk plain using ANN-PSO and geostatistical models. For this purpose, information from 61 observation wells in Dezful-Andimeshk plain has been used. Neural network model inputs including qualitative parameters SO42- ، pH ، HCO32-، Na+، Mg2+، Ca2+، TDS، SAR and EC were considered.Results: The results of simulation with intelligent model showed that the highest accuracy of ANN-PSO model in simulation is related to EC, SAR and TDS parameters, respectively. The results of interpolation by geostatistical method showed that the highest accuracy of Kriging model in simulation is related to EC, TDS and SAR parameters, respectively. The general results obtained from the simulation of groundwater quality parameters showed that the ANN-PSO model is more accurate in simulating the groundwater quality parameters of the plain in Andimeshk than the Kriging model. So that the value of R2 for simulating SAR, TDS and EC parameters using ANN-PSO model in the test phase is 0.92, 0.918 and 0.955 respectively and using kriging model is 0.902. 0.915 and 0.931 were estimated.Conclusion: The results of this study also showed that the combination of intelligent models with optimization algorithms is used as a useful tool to simulate groundwater quality parameters.
Seyed Ali Mohammadi Nezhad; Aslan Egder Nezhad
Abstract
The present study stimulated the groundwater quality parameters of Zeidoun plain including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), Total Dissolved Solids (TDS), using ANN and ANN-GA models and in the end compare their results with measured data. The input data for TDS quality parameter ...
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The present study stimulated the groundwater quality parameters of Zeidoun plain including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), Total Dissolved Solids (TDS), using ANN and ANN-GA models and in the end compare their results with measured data. The input data for TDS quality parameter consist of Na, EC, Ca, Mg, SO4 and SAR, for SAR including the Na, TDS, Hco3, Ca and Mg and quality parameter of EC contains Ca, Mg, SO4, Na and SAR, gathered from 2011 to 2018.The results showed that in ANN and ANN-GA models, the highest accuracy of SAR simulation in the model with sigmoid tangent function, in EC simulator model, the highest accuracy in ANN and ANN-GA models, respectively, related to logarithm stimulus functions. Sigmoid and tangent is sigmoid. Also in ANN and ANN-GA models, the highest accuracy of TDS simulation was obtained in the model with sigmoid tangent stimulus and sigmoid logarithm, respectively. so that the MAE and RMSE statistics have the minimum and R^2 has the maximum value for the model. In general, according to the obtained results, the accuracy of ANN-GA model is higher than ANN model, to simulate the groundwater quality parameters of Zeidoun plain. Therefore, the use of artificial neural network model along with genetic algorithm is a good tool to simulate high quality groundwater quality parameters, without the need for measurement and laboratory work, which requires high time and cost.
Samira Rahnama; Hossein Khozeymehnezhad; Abbas KhasheiSiuki
Abstract
Background and Aim:Due to the increasing demands of the human population to groundwater, protection and prevention of these water resources from pollution are necessary. The purpose of this study was to evaluate the vulnerability of groundwater aquifer in Kuchesfahan- Astane plain located in Gilan province ...
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Background and Aim:Due to the increasing demands of the human population to groundwater, protection and prevention of these water resources from pollution are necessary. The purpose of this study was to evaluate the vulnerability of groundwater aquifer in Kuchesfahan- Astane plain located in Gilan province using DRASTIC method and nonparametric models. Materials and Methods:In this study, seven layers were prepared for parameters in GIS software, and after weighting and combining standard ranks, the groundwater vulnerability maps for the study area were prepared. Nitrate data were used to validate the model in this region. Subsequently, by using the nonparametric models, Instance-Based Learning with parameter K (IBK) and the Tree Decision M5, the amount of nitrate was estimated. Meanwhile, Gamma test was conducted to find the best combination of input parameters. ResultsThe results revealed that the vulnerability of groundwater aquifer in this plain has 4 classes including 18.56 % in low vulnerability, 51.29 % in low to medium vulnerability, 28.46% in medium to high vulnerability, and 1.67% in high vulnerability classes. Also, the results showed that both of the nonparametric models have suitable estimates of the nitrate content, but the M5 decision tree model yielded the best results (R2=0.98). Conclusion:The results showed that nonparametric models are efficient method to estimate the aquifer vulnerability and provide accurate results to estimate the potential of contamination in the study area.This demonstrates the superiority of the M5 model over other aquatic vulnerability assessment methods.
Seyed Mostafa Tabatabaei; Ali Shahidi
Abstract
Abstract
Background & objeftive: In the Rafsanjan region of Kerman province, some sites have been considered for landfill construction. Since groundwater resources are the only source of water supply to provide water requirements in this region, the leachate leakage from landfills into groundwater ...
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Abstract
Background & objeftive: In the Rafsanjan region of Kerman province, some sites have been considered for landfill construction. Since groundwater resources are the only source of water supply to provide water requirements in this region, the leachate leakage from landfills into groundwater resources is regarded as a serious threat. The aim of this research is to study the trend of changes in the contamination concentration obtained from leachate leakage in a hypothetical landfill based on the geological and hydrogeological conditions of Rafsanjan plain in order to represent the effect of leachate leakage and contamination spread on groundwater resources.
Methods and Materials: Transmission of contamination has been studied on the basis of changes in concentration at two initial and final points of landfill by MT3DMS model daily and for 22 years period. The concentration of leachates has been considered 2 and 4 g / l, and its diffusion rate has been assumed 1.5 and 3 cm per day.
Results: The slope of the concentration increase in the propagation process and delayed diffusion at the beginning of the landfill with 2 and 4 g/l concentration and 1.5 cm rate during 15 and 17 years have an increasing trend, respectively and later it would have a decreasing trend. At the end of landfill, 90% increase in contamination will occur for 2 g/l concentration in the first five years and 4 g/l concentration in the first 9 years and it will have a fixed trend over the next few years.
Conclusion: In the various transmission processes after the penetration of the infection into the aquifer, the concentration of contamination is initially low and increasing over time and if the concentration of the contamination penetrating source and penetrating intensity are constant, the maximum concentration of aquifer pollution is fixed at a certain value. The type of transmission process has a huge impact on this constant value. So that in the propagation-diffusion process, the average in the first 5 years of this value is fixed and in a delayed state, it reaches a constant value after close to 22 years.
kazhal kakaei; Ali reza Riyahi Bakhtiari; Mahdi Gholamali fard
Abstract
Background and purpose: Infiltration of leachate produced by municipal solid waste into the ground water poses a serious environmental hazard due to its high content of hydrocarbons and heavy metals. The leachate is the primary source of soil and water pollution. In this paper the risk of heavy metals ...
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Background and purpose: Infiltration of leachate produced by municipal solid waste into the ground water poses a serious environmental hazard due to its high content of hydrocarbons and heavy metals. The leachate is the primary source of soil and water pollution. In this paper the risk of heavy metals discharged from leachate in to groundwater in Hamadan landfill has been assessed using Industrial Waste Management Evaluation Model (IWEM). Methods: The concentrations of heavy metals (Cu,Pb,Ni and Cd) in leachate were determined by atomic absorption spectrophotometry and the risk of these metals discharge into groundwater was assessed by IWEM using Monte Carlo analysis. Results: Based on the obtained IWEM and EPACMTP results, geosynthetic cover was recommended for this matter. Conclusion:The most appropriate option for groundwater protection in Hamadan landfill was recommended to be geosynthetic cover (Composite linear). Owing to the high probability of leachate infiltration into groundwater, there is need to be made stricter management decisions in this regard. Also, it is necessary that IWEM is used for prevention of leachate infiltration into groundwater.
Javad Momeni Damaneh; Fatemeh Joulaei; Hosein Alidadi; Roya Peiravi
Abstract
Background & objective: Groundwater is one of the exploitation important resources in arid and semi-arid areas. Therefore, the spatial and temporal distribution of groundwater quality is very important. The purpose of this study was to evaluate the accuracy of spatial interpolation methods in order ...
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Background & objective: Groundwater is one of the exploitation important resources in arid and semi-arid areas. Therefore, the spatial and temporal distribution of groundwater quality is very important. The purpose of this study was to evaluate the accuracy of spatial interpolation methods in order to predict the spatial distribution of some groundwater quality parameters such as TH, Ca, pH, Mg and SO4-2. Materials & Methods: in this study data related to 44 exploitation wells in Gonabad plain was used. Then, methods of IDW, SK, OK, UK, RBF, LPI and GPI were investigated. After normalizing the data, QQ plot was drawn. Then, in order to select, an appropriate model for fitting, mutual evaluation methods and estimation errors were used that consisted of MBE, RMSE, MARE and MAPE. Finally, the most appropriate interpolation method was chosen. Zoning maps of the water parameters were prepared by using geostatistical methods in GIS software. Results: Final zoning model showed, in the center, the west south, and the west of plain concentration of surveyed parameters have been lower than their mean. By moving from the north, the east north, and the east towards the center, the south, and the west south, the parameters concentrations were decreased. Conclusion: The results showed that kriging method is preferred to other geostatistical methods for zoning of the water quality parameters