TITLE:
The Study of Processes Affecting Groundwater Hydrochemistry by Multivariate Statistical Analysis (Case Study: Coastal Aquifer of Ghaemshahr, NE-Iran)
AUTHORS:
Homayoun Moghimi
KEYWORDS:
Caspian Sea, Multivariate Analysis, Principal Component Analysis (PCA), Factor Analysis (FA)
JOURNAL NAME:
Open Journal of Geology,
Vol.7 No.6,
June
15,
2017
ABSTRACT: To assess the quality of groundwater resources, samples were collected from 22 points for mean annual water years of 2003 and 2015 (mean minimum and maximum water table), and 19 parameters were examined and calculated. One of the objectives of this study was to evaluate the groundwater quality of the Ghaemshahr plain which includes the study of spatial and temporal changes of groundwater quality in different sectors and factors affecting it. In this study, combining statistical methods such as Pearson correlation coefficient, factor analysis, principal component analysis, and combined diagrams with hydrochemical methods are used to assess the chemical quality of groundwater. Samples were categorized by using cluster method and then the same samples were identified. Accordingly, samples were classified in four categories which represent the quality of groundwater in different districts. Factor analysis was used to identify the factors affecting the geochemical processes of the aquifer. Statistical methods showed that they can be used to complete the conventional methods in hydro-geochemistry as well as very precise results can be achieved. Based on the obtained results, saturation index of Ghaemshahr groundwater was super-saturated; and groundwater quality control of Ghaemshahr plain is hold by processes such as dissolution of halide (salt water intrusion of Caspian Sea and brackish fossil aquifers), calcite and dolomite (dissolution of limestone, dolomite, and marl in height), weathering sodium-rich plagioclases (clay minerals), and ion exchange.