In the current climate change scenario, there is a shortage in the quantity and quality of rainfall information available in the basins. Satellite pluviometric information emerges as an alternative to carry out more detailed hydrological studies. The objective of this research is to validate satellite information of daily and monthly reticulated rainfall data for the period 1981–2014 in the Camaná river basin, Arequipa region, Peru, compared with rainfall information measured at 23 pluviometric stations of the National Service of Meteorology and Hydrology of Peru (SENAMHI). The methodology used 5 statistical methods for the validation of the precipitation data: (i) Mean Absolute Error, (ii) Mean Squared Error, (iii) Percentage Bias, (iv) Nash-Sutcliffe Efficiency Criterion (NSE), and (v) Pearson’s Correlation Coefficient (R2). Considering two time series cases: (i) The first case considers total time series including two extreme El Niño events (1982–1983 and 1997–1998), and (ii) the second case does not consider total time series, excluding two extreme El Niño events (1982–1983 and 1997–1998). The results indicate an adequate validation of the satellite pluviometric information by applying the Nash-Sutcliffe Efficiency (NSE) criterion considering daily and monthly information. Finally, the article concludes that for future hydrological studies in the Camana river basin, it is possible to use satellite information from gridded data, but carefully analyzing its application considering the climate change scenario.