Investigation of Spatial Structure of Groundwater Quality Using Geostatistical Approach in Mehran Plain, Iran
Journal: Pollution (Vol.2, No. 1)Publication Date: 2016-01-01
Authors : Hassan Khosravi; Kamran Karimi; Sara Nakhaee nejadfard; Tayebeh Mesbahzadeh;
Page : 57-65
Keywords : geostatistical; Groundwater; Mehran plain; spatial variations modeling;
Abstract
Groundwater is a major source of water for domestic, industrial, and agricultural sectors in many countries. The main objective of this research was to provide an overview of present groundwater quality using parameters such as calcium, magnesium, sodium, chloride, sulfate, pH, and electrical conductivity (EC) in the Mehran plain, Ilam province using GIS and geostatistical techniques. A total of 23 deep and semi-profound wells were selected based on the classified randomized sampling method. The sampling locations were obtained by GPS. Plastic containers were used for the collection of water samples. These samples were transferred to the laboratory for analyzing water quality parameters. Statistical characteristics, qualitative data interpolation, and zoning were investigated using SPSS 20 ?GS+5.3 and ArcGIS10.1. Kolmogorov?Smirnov test were used to test data normality. In order to normalize parameters, logarithm, and 1/x were used for sulfate, EC, cation, and anion. Then the variogram analysis was performed to select the appropriate model. Results showed that co-kriging is the best method for cation and anion, whereas local polynomial interpolation is suitable for sulfate. The results of the interpolation of groundwater quality factors showed that there is approximately good adaption among groundwater factors and geomorphology and topology of the region. Because of inappropriate irrigation system, the highest concentration is in the northwest and western parts of the region, where there is the minimum height and maximum agricultural land. Growth of arable land and agricultural activities has caused increasing concentrations of studied elements, especially EC.
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Last modified: 2016-07-02 01:33:48