###### Abstract  
The Sao Francisco River basin is one of the largest in the Brazilian territory. This basin has enormous economic, social and cultural importance for the country. Its water is used for human and animal supply, irrigation and energy production. This basin is located in an area with different climatic characteristics (humid and semiarid) and studies related to precipitation are very important in this region. In this scenario, the objective of this investigation is to present an assessment of rainfall estimated through the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) product compared with rain gauges over the Sao Francisco river basin in Brazil. For that, a period from of 20 years and 18 surface weather stations were used to evaluate the product. Based on different evaluation techniques, the study found that the IMERG is appropriate to represent precipitation over the basin. According to the results, the performance of the IMERG product depends on the location where the rain occurs. The bias ranged from \(-1.67\) to \(0.34\) mm, the RMSE ranged from \(5.36\) to \(10.36\) mm and the values of the correlation coefficients between the daily data from the IMERG and rain gauge ranged from \(0.28\) to \(0.61\). The results obtained by Student \(t\)-test, density curves and regression analysis, in general, show that the IMERG is able to satisfactorily represent rain gauge data. The exception is the eastern portion of the basin, where the product, on average, underestimates the precipitation (\(p\)-value \(<0.05\)) and presents the worst statistical metrics. precipitation; semiarid; Northeast Brazil; San Francisco River basin; remote sensing data; rainfall +
Footnote †: journal: water  
irrigated agriculture, water resource management and monitoring areas of hydrological disaster risk, among others. The availability of reliable precipitation data, with a high spatial and temporal resolution, is essential for studies in these areas [1; 2]. Rain gauges measure the amount of rain accurately and immediately, although it has been reported that raw precipitation amounts are usually underestimated due to wind-induced undercatch, wetting and evaporation losses, trace amount of precipitation, and equipment design [3]. However, hydrometeorological monitoring in some countries is deficient, especially in developing or underdeveloped countries [4; 5]. In Brazil, most river basins have low rainfall. Additionally, the precipitation database in general suffers from a high percentage of missing data. For example, in Northeast Brazil (NEB), the percentage of failures per weather station can reach 23% in 30-year climatological series [6]. In the Amazon Basin (AMZ), the percentage of failures is highly variable, but even in the case of data previously filtered based on the standards of the World Meteorological Organization (WMO), the failures usually reach values above 6% for annual series [7]. Thus, satellite precipitation products are alternatives for hydrometeorological monitoring [5; 8]. In particular, the rainfall estimated from the tropical rainfall measuring mission (TRMM) algorithms [9] and more recently the global precipitation measurement (GPM) has been widely used in regional and global meteorological and climatological studies [8; 10; 11; 12; 13; 14; 15]. In this context, several studies have been performed to evaluate the precipitation estimates from the TRMM and GPM satellites in different regions of Brazil [5; 16; 17; 18; 19]. Overall, the results of these studies suggest that the accuracy of satellite precipitation estimates depends on factors such as terrain, type of precipitation and local climate. In the tropical portion of South America, the rainfall estimated by the TRMM algorithms were analyzed for their ability to represent precipitation in the AMZ from the high-frequency variability, represented by the diurnal precipitation cycle [1; 20], up to the modes of seasonal and interannual variability [20; 21; 22].