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