VALIDASI DATA HUJAN SATELIT TERHADAP DATA GROUND UNTUK ESTIMASI DEBIT ANDALAN DI KOTA SURAKARTA

<p><em>Rainfall plays a critical role in the hydrological cycle, affecting various sectors such as water resource management, agriculture, and disaster mitigation. The Global Precipitation Measurement (GPM) satellite is a significant innovation in global rainfall measurement. The availability of GPM satellite data is particularly beneficial for regions with limited ground-based rainfall station data. This study validates rainfall data from the Global Precipitation Measurement (GPM) satellite against ground observation data to calculate dependable flow in Pepe River, Surakarta, using the National Rural Electric Cooperative Association (NRECA) method. The analysis spans data from 2004 to 2024. Validation results show a strong correlation (R = 0,7315) but notable deviations with Root Mean Square Error (RMSE) = 0,415 and NSE = 0,667. Post-calibration (coefficient 0,856), the correlation improves significantly (R = 1, RMSE = 0,016, NSE = 0,758). Dependable flow analysis identifies February as the month with the highest average discharge (1,163 m<sup>3</sup>/s) and highlights 2017 as the year with a Q80% value of 4,578 m3/s using the Weibull Basic Month method. Comparison of Q<sub>80% </sub>results with field discharge data, obtained through rating curve conversion, shows that the Q80% value falls within the standard deviation range of field discharge, validating the calculated results. The results of this study are expected to provide insights into the quality of GPM satellite rainfall data for dependable flow estimation.</em></p>