Relationship between landform and soil salinity in the surface and subsurface soils (case study: Southeast of Fars Province, Iran)

Abstract

Forty surface and subsurface soil samples were collected from agricultural field of Darab, southern Iran. Some physicochemical properties and also EC were determined. Geostatistical analysis was done by using the Kriging method (including ordinary, simple, universal, indicator, probability and disjunctive models) in ArcGIS 10.2 software. The results of stepwise multiple regressions indicate that in the surface and subsurface soils, sand and silt contents respectively are the most influential soil characteristics that predict EC. The root mean square error (RMSE) analysis of the different models indicated that indicator model with RMSE value of 0.518 and probability model with RMSE 0.509 are the best models for the description of the spatial distribution of EC in the surface and subsurface soils, respectively. Finally, for determination of accuracy of the best models (indicator and probability models) in surface and subsurface soils, 10 sample points were used. The RMSE values for EC in the surface and subsurface soils were calculated 0.476 and 0.349, respectively. It is recommended that other interpolation methods such as co-Kriging and soil properties such as CEC and SAR are used in order to prepare precision maps in the future. Finally the relationship between landform classes and EC values were determined by using topography position index. The results show that the high EC value was shown in plain small for subsurface soil and surface soil in the study area. While the low EC value was seen in mountain top and stream for subsurface soil and surface soil that was indicative leaching of the soil.