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Information Journal Paper

Title

Hydrogeochemistry evaluation of Salmas plain aquifer using multivariate statistical methods

Pages

  791-800

Abstract

 For better understand of hydrogeochemical processes in the Salmas plain aquifer, this study adopted graphical methods and multivariate statistical techniques to analyze Groundwater samples. The results of the Piper diagram and expanded Durov diagram reveals that the major Groundwater type is Ca-(Mg)-HCO3 and mixing Groundwater type exists in southeast of the Salmas plain. Hierarchical cluster analysis (HCA) identified five classes of Groundwater type (HC1 to HC5). The Hierarchical cluster analysis is able to show the influence of nitrate concentration in classification while the graphical methods cannot. The Stiff diagrams of five classes (HC1 to HC5) show three different sources of Groundwater samples. The HC1 to HC3 classes indicate Groundwater with limestone and dolomite origin. In HC4 class, Na+ and Clˉ are the dominate ions in Groundwater samples and shows saline waters. The HC5 shows mixing Groundwater. Using factor analysis (FA), we identified three factors that accounted for 85. 03% of the total variance of the dataset. Factors 1 and 2 are reflected the natural hydrogeochemical processes and factor 3 is anthropogenic in the Salmas plain.

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    APA: Copy

    NADERI, KEYVAN, NADIRI, ATA ALLAH, ASGHARI MOGHADDAM, ASGHAR, & KORD, MEHDI. (2018). Hydrogeochemistry evaluation of Salmas plain aquifer using multivariate statistical methods. IRANIAN JOURNAL OF ECOHYDROLOGY, 5(3 ), 791-800. SID. https://sid.ir/paper/254021/en

    Vancouver: Copy

    NADERI KEYVAN, NADIRI ATA ALLAH, ASGHARI MOGHADDAM ASGHAR, KORD MEHDI. Hydrogeochemistry evaluation of Salmas plain aquifer using multivariate statistical methods. IRANIAN JOURNAL OF ECOHYDROLOGY[Internet]. 2018;5(3 ):791-800. Available from: https://sid.ir/paper/254021/en

    IEEE: Copy

    KEYVAN NADERI, ATA ALLAH NADIRI, ASGHAR ASGHARI MOGHADDAM, and MEHDI KORD, “Hydrogeochemistry evaluation of Salmas plain aquifer using multivariate statistical methods,” IRANIAN JOURNAL OF ECOHYDROLOGY, vol. 5, no. 3 , pp. 791–800, 2018, [Online]. Available: https://sid.ir/paper/254021/en

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