Assessment of water balance components of GLDAS-2 and GLDAS-2.1 inQazvin province

Due to problems such as human error, financial problems, lack of access to all areas of interest and atmospheric problems in recorded meteorological data, need to access to remote sensing models mentioned problems to solve and give users high accurate data is undeniable. The Global Land Data Assimilation System (GLDAS) is an important data source for global water cycle research. Using ground-based measurements GLDAS-2 has two components: one forced entirely with the Princeton meteorological forcing data (GLDAS-2.0), and the other forced with a combination of model and observation based forcing datasets (GLDAS-2.1). In this research, GLDAS-2 model and two components of it have been studied. This paper aims at evaluating data, air temperature, soil temperature, rainfall, runoff and evaporation potential of two components of GLDAS-2 by data of synoptic stations and hydrometric observations were carried out. The results showed that in Qazvin station, air temperature and soil temperature, precipitation and evaporation potential of the model GLDAS with a coefficient of 0.9, 0.7 and 0.8 as well as total annual volume of runoff data of GLDAS model in Barajin stations and Bagh Kalaye station with a coefficient of determination 0.49 and 0.55 have a good correlation with the observed data. The results show that the current temperature data, runoff, evaporation potential and precipitation (except Avaj station) of GLDAS-2.0 model have more accurate than the GLDAS-2.1 model. Given that the accuracy of the model GLDAS in the mountainous region of Avaj is lower than other areas so it may be because it is the local climate and altitude (2034.9) more than other areas. Finally, due to the low accuracy of runoff data from the GLDAS model, using it in estimating the amount of flood runoff is not recommended.