<![CDATA[An alternative solution to the availability of inadequate rain data as hydrological data input is with the help of Global Precipitation Measurement (GPM) satellite rainfall data using remote sensing technology (satellite). The purpose of this study was to find correlations and corrections of data and validate GPM satellite data with rainfall data at rain stations and observation data in the Jelai watershed. The corrected GP M rain data validation results in Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE), Correlation Coefficient (R), and Relative Error (KR). The validation results resulted in NSE values of 0.33, RMSE 48.54, Correlation Coefficient (R) of 0.75, and Relative Error of 0.19 for 2019 and yielded NSE values of -0.14, RMSE 100.24, Correlation Coefficient (R) of -0.36, and Relative Error of 0.23 for 2020. The overall analysis shows that GPM data can be used as an alternative to rain data if in a watershed there is a small number of rain posts that do not meet the WMO criteria. As a suggestion for further research, it is necessary to calibrate and validate by distinguishing between rain data in wet years and dry years]]>
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