Salinity Assessment and Ground Water Quality Mapping Using Principle Component Analysis, Case study: Khafr Plain

Subject Areas : Article frome a thesis

Homa Razmkhah ¹ , Easa Mohammadi ² , Amin Rostami Ravary ³ , Alireza Fararoui ⁴

1 - Associate Prof. of Water Science and Engineering Department, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.
2 - Former M.Sc. Student of Irrigation and Drainage, Water Science and Engineering Department, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.
3 - Associate Prof. of Water Science and Engineering Department, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.
4 - Associate Prof. of Water Science and Engineering Department, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.

Received: 2020-12-28 Accepted : 2021-09-01 Published : 2022-10-23

Keywords: Interpolation, Principal Component Analysis, Kriging, Ground water quality mapping,

Abstract :

Abstract
Introduction: Assessment of groundwater quality and quantity variation in drought and semi-drought region are of most interest especially in Iran. This research is going to analysis salinity reasons by ground water quality mapping in the Khafr plain.
Methods: To do this the principal components of water quality extracted in spring and autumn seasons. Then Spline, IDW and Kriging interpolation techniques were fitted and evaluated for mapping. Finally, the best model was determined and ground water quality mapped using principle components.
Findings: Kriging recognized as the best model for autumn. The first component with high coefficients on TH, K, Mg, Ca, SO4, TDS, EC showed maximum values in the center and eastern south of the region. For the second component (SAR, Cl, Na) maximum values observed at the eastern south as well. The third component (PH) increased from center to the north and western north and decreased from center to the south and eastern south, and for the Forth (HCO3) maximum observed at the north and minimum in the eastern south. Spline method recognized as the best model in spring season. The first component (SAR, Cl, Na) showed maximum values in the eastern south of the region. The second (Th, Mg, Ca) maximum values observed at the center and the third component (PH) maximums in the west. Forth component (HCO3) maximum valued observed in the center and western north. Finally, the reasons of spatial and temporal variation of the components analyzed.

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