عنوان مقاله [English]
Soil characteristics have spatial variations. Understanding spatial variations of soil characteristics is among the effective factors in sustainable land management. A better understanding the effects of management factors on soil characteristics need to quantify their heterogeneity and variability. This research was conducted with the aim of investigating spatial variations of some soil characteristics such as soil texture (clay, silt and sand), calcium carbonate (CaCo3), soil acidity (pH), and soil salinity using geostatistic methods. For this purpose, 252 soil samples (from 0 to 20 cm depth) were prepared from the study area and physical and chemical properties of soil were measured. After normalizing the data, the half-shift of each of the studied characteristics was calculated and the best model was fitted to them. Then, the characteristics of the study were estimated through different methods of conventional Kriging, simple Kriging, discrete Kriging and Inverse Distance Weighted (IDW) using ArcGIS software. The accuracy of the estimation was evaluated using the mean absolute error (MAE), the mean bias error (MBE), and the root mean square error (RMSE). The results showed that the best model for the acidity was the spherical model and for the other measured variables was the exponential model. Moreover, the conventional CoKriging method for clay, calcium carbonate and acidity (pH), IDW method for silt and soil salinity, and conventional Kriging method for sand were better than other methods used and provided more accurate estimates.
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