Geostatistical Modelling of Spatial Changes in Groundwater Quality Using GIS and Wilcox Model (Case Study: Central and Kenark Districts, Chabahar)

Using unsuitable quality water for agricultural purposes has  negative consequences on plant growth and the soil physical properties. The aim of this study was to investigate the spatial changes in ground water quality with agricultural applicability in central Chabahar and Kenark Distircts. For this purpose, we first performed interpolation for EC and SAR parameters from 40 wells in the study area in 2019. Then we employed  inverse distance weighting , global polynomial, local polynomial, radial basis function and kriging with circular, spherical, exponential, gaussian, as well as quadratic equation semivariograms; the most suitable method for interpolation was selected baed on the Root Mean Square Error (RMSE) and coefficient of determination (R2) criteria. The research found that kriging interpolation method with a Gaussian variogram having RSME=13.85 and R2=0.77 was the most suitable methods for interolating with the SAR paramete and the kriging interpolation method with as spherical variogram having RSME=797.89 and R2=0.68 was considered as the most suitable methods for interpolating EC. Then, based on Wilcox method, the groundwater quality map for agricultural and irrigation uses was prepared using the spatial variation map of two parameters, EC and SAR. The results showed that the quality classification of the groundwater in the study area was: about 10% as good, 51% as fair, 16% as poor, and about 23% as unusable water.