Evaluation of groundwater quality and assessment of scaling potential and corrosiveness of water supply networks, Iran

Mirzabeygi, Majid; Yousefi, Nader; Abbasnia, Abbas; Youzi, Hadi; Alikhani, Mahdi; Mahvi, Amir Hossein

doi:10.2166/aqua.2017.128

Cited by 41 publications

(24 citation statements)

References 20 publications

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“…In order to evaluate the microbial quality of drinking water in villages of Zahedan city, 168 villages were selected as a comprehensive sample of all villages in this city. Between 2014–2015, 1221 microbial samples were prepared from the water facilities installed in these villages, and the microbial test was performed by MPN, P-A or MF methods and turbidity, temperature, and HPC tests based on the standard method [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Microbiological dataset of rural drinking water supplies in Zahedan, Iran

et al. 2018

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The residual chlorine and microbial quality of drinking water in the Zahedan villages by a number of1221 samples from all 168 villages were collected between 2014–2015. Then the samples were evaluated using 9-tube fermentation methods and portable chlorine method test. Based on the microbial coliform and fecal coliform indices, the data indicated that the maximum and minimum controlling of the bacteria in the distribution network were in the winter (90.62%) and autumn (85.56%), respectively. Also in the reservoirs, the maximum and minimum controlling of the bacteria were in winter (93.49%) and autumn (87.35%), respectively. The residual chlorine was prepared in almost all of seasons.

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Microbiological dataset of rural drinking water supplies in Zahedan, Iran

et al. 2018

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“…Data on groundwater resources were collected a during the years 2010–2014 and water samples were analyzed following the standard methods for examination of water and waste water [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] in terms of estimation of sodium absorption ratio (SAR). A two-layer neural network with a tangent-sigmoid transfer function for the hidden layer and a linear transfer function for the output layer was used.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Data on estimation for sodium absorption ratio: Using artificial neural network and multiple linear regressions

et al. 2018

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In this article the data of the groundwater quality of Aras catchment area were investigated for estimating the sodium absorption ratio (SAR) in the years 2010–2014. The artificial neural network (ANN) is defined as a system of processor elements, called neurons, which create a network by a set of weights. In the present data article, a 3-layer MLP neural network including a hidden layer, an input layer and an output layer had been designed. The number of neurons in the input and output layers of network was considered to be 4 and 1, respectively, due to having four input variables (including: pH, sulfate, chloride and electrical conductivity (EC)) and only one output variable (sodium absorption ratio). The impact of pH, sulfate, chloride and EC were estimated to be 11.34%, 72.22%, 94% and 91%, respectively. ANN and multiple linear regression methods were used to estimate the rate of sodium absorption ratio of groundwater resources of the Aras catchment area. The data of both methods were compared with the model׳s performance evaluation criteria, namely root mean square error (RMSE), mean absolute error (%) and correlation coefficient. The data showed that ANN is a helpful and exact tool for predicting the amount SAR in groundwater resources of Aras catchment area and these results are not comparable with the results of multiple linear regressions.

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“…Calcium is the second most frequent component in most surface waters and is generally among the three or four most frequent ions in groundwater. The increase Ca 2+ concentration decreases water corrosivity (Mirzabeygi et al, 2017), since Ca 2+ is important for the formation of a passivation film on the surface of the pipe, decreasing corrosion. From the data recorded in Table 2 and Figure 2, the Ca 2+ concentration varied between 12.8 and 31.6 mg L -1 , with an average of 20.8 mg L -1 .…”

Section: Corrosion Monitoringmentioning

confidence: 99%

Estimation of corrosive and scaling trend in drinking water systems in the city of Azogues, Ecuador

García-Ávila¹,

Fernández²,

Zhindón-Arévalo³

2018

Rev. ambiente água

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The quality of drinking water flowing in a distribution network can possess corrosive characteristics that may cause the material degradation of pipes and accessories. This problem can result in reduction of the service life of pipes and create a major public health problem. The agreement between the physical-chemical water quality analysis and national standards are not enough to confirm the balance of the water quality in terms of corrosion. In order to predict pipe corrosion in water distribution system networks, the corrosive trend was evaluated using the Langelier (LSI), Ryznar (RSI), and Larson-Skold (LRI) indexes based on measurements of pH, temperature, total dissolved solids, alkalinity, calcium hardness, sulfate and chloride. This study was setup with 180 samples collected in six zones of the distribution network, from July to December of 2017, according to the standard methods for the analysis of drinking water. The results indicate a variation of the LSI from -1.22 to -1.68; RSI from 9.75 to 10.52 and LRI from 0.46 to 0.77. A linear model was fitted for each index to predict the corrosion with the water quality conditions of this study case. Therefore, the drinking water of the city of Azogues, Ecuador has a corrosive tendency from significant to severe. Corrosion indices were calculated to provide useful information on the water's corrosiveness. These results indicate the need to constantly monitor the corrosion rate in the distribution network and conduct a laboratory study to adjust effective parameters such as pH, in order to control corrosion.

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Evaluation of groundwater quality and assessment of scaling potential and corrosiveness of water supply networks, Iran

Cited by 41 publications

References 20 publications

Microbiological dataset of rural drinking water supplies in Zahedan, Iran

Microbiological dataset of rural drinking water supplies in Zahedan, Iran

Data on estimation for sodium absorption ratio: Using artificial neural network and multiple linear regressions

Estimation of corrosive and scaling trend in drinking water systems in the city of Azogues, Ecuador

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