Gradual drying of Urmia Lake has left vast saline areas all around it, increasing the risk of salinization of agricultural lands next to the Lake. The current research was aimed to predict soil salinity and distinguish the boundary line between saline and agricultural lands by taking in to account the spatial variability of soil salinity in Bonab Plain, Iran. To do so, soil samples were taken from depth 0-25 cm in 78 points with spatial intervals of 500 m and were analyzed for their electrical conductivity in saturated paste extractions. Data analysis showed that soil salinity mean wasn’t stationary and was varying among dataset. Therefore to build up a variogram, the spatial components of the mean trend were computed and subtracted from laboratory measured ECe values, which resulted in residuals. The semi-variogram function was then calculated and modelled based on the residuals. Cross-validation results showed that kriging method along with modified semi-variogram, resulted in better predictions of soil salinity with ME and MSE equal to 0.12 and 0.3. Setting 4 dSm-1 as the limit between saline and non-saline soils in kriging algorithms resulted in a sharp boundary line between saline and non-saline lands in the study area. The presence of highly saline soils next to the agricultural lands in the area can increase the risk of secondary salinization of the Bonab Plain which is one of the important agricultural production centers in the area. Therefore, careful monitoring of lands near salinity boundary in the area should be of high priority.
