The monitoring and analyzing of drought conditions is one of the main requirements for water resources management. In present paper, Standard Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were compared in order to assess the drought conditions in the Esfarayen-Sabzevar region. As in the aforementioned region sufficient long-term data is not available to assess the drought, reanalysis data of ERA-INTERIM were used to be combined with the observed data. For this purpose, climatic data of precipitation and temperature were extracted for each station in the statistical period of 1979-2016 using the web interfaces, Python script, ECMWF WebAPI and ArcGIS software. After correcting the bias of the data based on observational data, combined data of precipitation and temperature were obtained for the aforementioned period and used as the basis for calculating the drought. Finally, drought assessment and estimating the correlation of SPI and SPEI were conducted for three stations of Sarcheshme, Ghasemabad, and Jaghtay in the time scales of 3, 6, 12, 18, and 24 months. After generating data combination, the Root Mean Square Error (RMSE) and Bias were decreased from 0. 39 and 6. 69 to 0. 32 and 0. 24 respectively. Thus similar approach to data can be used for drought assessment in areas with lack of observed data. Results showed that in the short-term scales the frequency of dry and wet periods is high. By increasing the time scale, the frequency of the dry and wet period decreases but their duration increases. In most cases in the stations both indices showed coordination in the dry and wet periods. Based on the provided results regarding the correlation between SPI and SPEI indices, there is a positive and significant correlation between the above indices and the correlation is higher in the humid regions. As a result, the SPI index can be used in the regions with no temperature data with a precession similar to the SPEI index.

Precipitation is a major component of the hydrological cycle, which has significant spatial and temporal vriations. The lack of suitable data for this parameter causes a problem in hydrological forecasts. Since satellite data provides a new solution for estimating rainfall with spatial and temporal variation, this study evaluated the accuracy of some of these data types at the upstream of the Maroon Dam, including highresolution spatial data consist of ERA-INTERIM, CHIRPS and PERSIANN-CDR on daily, monthly and annual timescales. With respect to evaluation, gridded precipitation data and observational data from 2003 to 2014 were considered. The results showed that estimation of the annual rainfall data of the gridded precipitation models was underestimated so that the estimated average annual precipitation was evaluated less than the mean annual observational precipitation. In the estimation of monthly precipitation with regards to the Nash-Sutcliff coefficient at Dehno, Idenak and Margoon stations, the ERAInterim model and at the Ghale-Raeesi station CHIRPS model indicated the best performance compared to other models. In the daily rainfall estimation, like the monthly rainfall, the best estimate at the Idenak station was the ERA-INTERIM model, which had an NSE of 0. 63 and the best estimate of precipitation in all stations was by ERA-INTERIM. ERA-INTERIM had the best performance from the 3 gridded models in the correct detection of rainy days. The best performance of this model was in determining the correct rain days with POD = 0. 53 at Idenak station.