Spatial Analysis of Important Variables of Groundwater Quality Based on Geostatistical, Statistical Analysis and Structural Equation Modeling

Document Type : Research Article


1 PhD Candidate, Department of Arid And Mountainous Reclamation Regions, Faculty of Natural Resources, University of Tehran, Karaj, Iran

2 MSc Student, Echohydrology, Faculty of New Science and Technologies, University of Tehran, Iran

3 MSc in Environmental Health, Islamic Azad University, Tehran Medical Science Branch, Iran

4 Associate Professor, Faculty of New Science and Technologies, University of Tehran, Iran


Today, the quantitative and qualitative monitoring of fresh water resources in arid and semi-arid areas is one of the requirements of every management, monitoring, and monitoring system. However, the existence of many qualitative variables in international standards has led managers to consider only quantitative variables in terms of economic and temporal conditions. So, selecting this variable is important for assessment the water quality standard. Therefore, the purpose of this study was to determine the variables that are unique and affect the pollution of Qaleh Ghazi Plain of Hormozgan by statistical methods (Principle Components Analysis, Cluster Analysis, Piper diagrams, one way ANOVA, Structural Equation Modeling (SEM)) and Geostatistical. The results of cluster analysis showed that the wells are located in two clusters that can be distinguished by location. The results of PCA / FA showed that 72.77% of the data variance was justified in two factors, and the spatial analysis using Geostatistical showed that the interaction of water-rock in factor score 1 is an evidence of the effective role of evaporative formations on plain contamination. ANOVA results also showed a significant difference between the concentrations of factor score 1 and factor score 2 in factor analysis. Accordingly, the variables EC, Cl, SO42, Mg and Na were selected for review by SEM. The results of this method confirmed the findings of statistical methods.


Main Subjects

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Volume 5, Issue 4
January 2019
Pages 1385-1399
  • Receive Date: 21 June 2018
  • Revise Date: 29 September 2018
  • Accept Date: 29 September 2018
  • First Publish Date: 22 December 2018