The understanding of spatial and seasonal variability in soil water retention properties is critical for careful management of soil water in agricultural production in semi-arid regions. The main objectives of this study were to spatially predict and prepare distribution maps of the field capacity and permanent wilting point in semi-arid terrestrial ecosystem region by using regression kriging and cokriging, and kriging models in order to predict soil water budget with limited data. Capability of the models was compared, including the use of descriptive statistics, semivariogram and cross-semivariogram. For this aim, 287 disturbed and 167 undisturbed soil samples (0 - 20cm) were collected in grid system and used for this research. Overall results showed that regression kriging produced smaller mean absolute error (MAE) and mean square error (MSE) than kriging and cokriging for field capacity, but cokriging was superior for the interpolation of permanent wilting point in terms of smaller MAE and MSE obtained at the sampling point. Consequently, the final maps and calculated results can also be used in the decision processes for land and water managements and soil conservation practices by authorities, as well as by farmers for irrigated fields in semi-arid areas.