Assessment of soil property spatial variation based on the geostatistical simulation

The main objective in the present study was to assess the spatial variation of chemical and physical soil properties and then use this information to select an appropriate area to install a pasture rehabilitation experiment in the Zereshkin region, Iran. A regular 250 m grid was used for collecting a total of 150 soil samples (from 985 georeferenced soil pits) at 0 to 30, and 30 to 60 cm layers. Soil samples were analyzed for pH, EC, N, K, P, Na, Ca, Mg and SAR. Conventional statistical methods and geostatistics were performed in order to analyze soil properties spatial dependence. Mean, standard deviation, skewness, and kurtosis for all measured variables were evaluated. All variograms generally were well structured with a relatively large nugget effect. Soil properties such as pH, P semivariograms were best fitted by spherical models, while SAR, Na were best fitted by spherical models. In the beginning kriging were performed in order to analyze spatial variation of chemical and physical soil properties, then for enhancing estimation accuracy and comparing results we used cokriging technique. Comparison of the results using statistical techniques showed that kriging technique has acceptable accuracy in characterizing the spatial variability. Also results showed that although kriging technique has acceptable accuracy in characterizing the spatial variability of soil properties but if higher accuracy is needed, cokriging is preferred to kriging particularly when the extra variable has been used.