Water vapor is the most important atmospheric greenhouse variable gas, both spatially and temporally. It involves a positive feedback loop in climate change. In addition, the atmospheric water vapor content is not only an important parameter to forecast precipitation and severe weather but also a central factor for studying the global water cycle. Therefore, in order to weather forecast and climate monitoring applications, study of spatio-temporal distribution of water vapor is valuable. Today, satellite sensors, due to their wide spectrum range, high -spatial resolution, and almost daily global coverage, have enabled them to observe the Earth's atmosphere and constantly monitor its changes. One of the atmospheric parameters measured by satellite sensors is water vapor. Among the various sensors that measure water vapor, the MODerate resolution Imaging Spectroradiometer (MODIS) is one of the most famous. MODIS offers water vapor in the form of two separate products, one is the near-infrared product and the other is the infrared product. In addition to satellite sensors, water vapor can also be accessed through observations of ground-based devices such as Global Position System (GPS) and Sunphotometer. In this research, among the MODIS water products, the near-infrared product was used and the data measured at the Aerosol RObotic NETwork (AERONET) site along with the computed values from GPS observations were used to validate the satellite water vapor data. In this research, the method of Point Precise Positioning (PPP) has been used to process GPS observations. The main goal of this research is the investigation of MODIS and AERONET water vapor data quality using GPS observations at Zanjan city. In this study, standard MODIS near-infrared level-2 Integrated Water Vapor (IWV) data product and AERONET IWW retrievals from sunhpotometer at Institute for Advanced Studies in Basic Sciences (IASBS) site, were evaluated using estimated data from GPS permanent station of IASBS from 2011 to 2013. Intercomparison results showed that AERONET-IWV and GPS-IWV had high correlation (R²=0.95). The mean values of an Root Mean Square (RMSE) and Bias between AERONET-IWV and GPS-IWV (AERONET-GPS) were about 3.2 mm and 2.2 mm, respectively. The MODIS IWV product showed slightly higher correlation coefficient (R² =0.92) with GPS-IWV compared with AERONET –IWV (R² =0.90). In addition, MODIS-NIR IWV showed approximately 2 times larger RMSE and 2.5 times larger Bias from AERONET -IWV (RMSE =5.48 mm, Bias =4.88 mm) compared with GPS IWV (RMSE =2.76 mm, Bias =2 mm). Finally, the results of the presented study provide good information about the overall quality of the MODIS and AERONET IWV data for the areas of atmospheric researches. The results of this study were comparable to previous studies conducted in Kanpur India and Beijing, China. The results obtained in this research provide valuable information to researchers in the fields of meteorology, climate, hydrology.