The main objective of this research is to assess the daily rainfall data from the Tropical Rainfall Measurement Mission (TRMM-3B42 V7) and Global Precipitation Measurement (GPM) products with rain gauge data and Comparison the performance of two widely-used models for spatial assessment over the semiarid climate of Khorasan Razavi Province, Iran. Measured rainfall data from 13 rain gauge stations for the period of 2 years, starting from Feb 2015 to Dec 2016 were collected and compared with the available annual GPM and TRMM-3B42 V7 data. In order to assess the efficiency of Kriging and Inverse Distance Weighting (IDW) models for annual precipitation zoning, the statistical Root Mean Square Error (RMSE) and Mean Error (ME) methods were used in the Arc GIS software version 10.1.The results of statistical analysis comparing the two methods with the satellite production data showed that at the annual scale the results of the TRMM satellite data are close to the GPM satellite data. However, TRMM satellite simulates precipitation data with slightly higher correlation coefficient and lower relative bias than GPM satellite. The results also showed that in all three precipitation data, Kriging method performs more accurately than the inverse Distance Weighting (IDW) method. In both interpolation methods, zoning was performed with much less error in the GPM data. This study showed that the average annual precipitation of both TRMM and GPM satellite precipitation products can be used to estimate precipitation and could potentially be one of the reliable sources for hydrological modeling.This study showed that the average annual precipitation of both TRMM and GPM satellite precipitation products can be used to estimate precipitation and could potentially be one of the reliable sources for hydrological modeling.This study showed that the average annual precipitation of both TRMM and GPM satellite precipitation products can be used to estimate precipitation and could potentially be one of the reliable sources for hydrological modeling.