<![CDATA[The use of clean water is a basic necessity for the population in Indonesia, where it serves various purposes such as drinking, hydrology, and irrigation. Therefore, it is crucial in the infrastructure for providing clean water. Rainfall is one of the sources of water, and in the development planning of existing water resources, field discharge data is essential. Field data includes rainfall, climatology, and water level. Due to data limitations, accuracy becomes a challenge in hydrological modeling. Thus, the use of satellite rainfall data is deemed necessary as an alternative for hydrological modeling. In this case, Global Precipitation Measurement (GPM) satellite data is utilized. The modeling employs Mock and Rainrun models, and the results show that the Coefficient of Correlation (R) is significantly low for both Mock and Rainrun models. For Nash-Sutcliffe Coefficient (NSE), the Mock model yields scheme 1 = 0.506, scheme 2 = 0.555, scheme 3 = 0.578, and scheme 4 = 0.431, meeting the average criteria. The Rainrun model's NSE values are scheme 1 = 0.505, scheme 2 = 0.582, scheme 3 = 0.506, and scheme 4 = 0.501, also meeting the average criteria.]]>
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