Data availability is one of the challenges, especially for hydraulic data in water resources management. The expansion of satellite precipitation data has provided a solution with advantages in both spatial and temporal dimensions. This research aims to evaluate and validate satellite-based precipitation data such as GPM-IMERG and CHIRPS against observed. Data evaluation is needed to determine the suitability of satellite precipitation data usage. Correcting satellite precipitation data bias is conducted using regression, distribution mapping, and average ratio methods. The validation stage used the Root Mean Squared Error (RMSE) method, Nash-Sutcliffe Efficiency (NSE), Correlation Coefficient (R), and Relative Error Test (RE) as validation methods. The Lahor River basin is used as a case study due to the availability of adequate data. The research is conducted on monthly and daily data for each dataset with three calibration and validation periods, each spanning 19 years. The analysis results indicate that the validation of CHIRPS before and after correction is better than GPM-IMERG. The GPM-IMERG data is best corrected using the distribution mapping method with a linear intercept equation. Meanwhile, the most suitable method for the CHIRPS data is a regression with a polynomial intercept equation.

Satellite data, rainfall data, correction, validation