Today in water and soil sciences, many attentions have been arisen on Geostatistical methods to estimate spatial parameter using some data (kriging) or using auxiliary variables (cokriging). The quality of ground water for agriculture is very important, however its measurement is time consuming and expensive. Therefore, finding solution to estimate such parameters from easily measurable parameters is essential. In this study, two estimation models (spatial and regression models) were used to estimate SAR1 and CL1 in Tehran region using Geostatistic theory and spatial parameter concept. In this regard, ArcGIS software was used to estimate these parameters. Multi-parameter estimate of cokriging was applied using water salinity as an auxiliary variable. In addition, different estimation methods, cokriging, kriging and regression models, were compared and evaluated by RMSE1 statistic index. The results of this study showed that cokriging method with high correlations coefficient and with Gaussian Semivariogram is more precise than kriging and the selected regression models in estimating SAR and CL.
