<![CDATA[The increasing frequency of flooding in Jambi City, especially in the Asam Watershed, requires accurate hydrological analysis to predict flood discharge and support the planning of flood control infrastructure. However, limitations of rainfall data from rainfall stations, including a limited number, continuity, and spatial distribution, constrain long-term hydrological analysis. Therefore, satellite-based rainfall data can be utilized as an alternative due to its wider spatial coverage and long-term data availability. Nevertheless, satellite rainfall data require validation and correction to ensure better representation of local conditions. This study uses Global Precipitation Measurement (GPM) satellite rainfall data. The validation and correction processes were conducted using statistical analysis with correlation coefficient and Root Mean Square Error (RMSE) as evaluation parameters. The results indicate that the monthly rainfall correlation between GPM data and observations at the Sipin Rainfall Station reached 0.711. The RMSE value for daily rainfall correction was 0.621, while the RMSE for Annual Maximum Daily Rainfall (AMDR) decreased from 0.16 to 0.04 after correction. The corrected GPM rainfall data show trends consistent with observed rainfall, indicating that the dataset can be used as an alternative source for design rainfall analysis in the Asam Watershed.]]>
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