Analysis of CHIRPS and GPM-IMERG and Discharge Modeling with Transfer Function-GRU in Gembong Watershed, Pasuruan

Rain gauges in Indonesia are often unevenly distributed, with significant gaps in data availability. As an alternative, satellite precipitation products (SPPE), such as CHIRPS and GPM-IMERG, are increasingly used for precipitation estimates. Additionally, discharge data is frequently unavailable for extended periods, making rainfall-discharge modeling essential. This study aims to evaluate the performance of two SPPEs, CHIRPS and GPM-IMERG, in the Gembong watershed and identify the best rainfall-discharge model. The study focuses on black-box models, using precipitation as input and discharge as output, without discussing model uncertainty. The two SPPEs were compared using continuous statistics, categorical metrics, and volumetric indices. CHIRPS was found to outperform GPM-IMERG. Three models were then tested: the transfer function (TF) model, SARIMAX(1,0,0)(0,1,1)12(1,0), a hybrid SARIMAX-GRU model, and a standalone GRU model. The models were validated using correlation (r), Nash-Sutcliffe efficiency (NSE), and the ratio of root mean square error to standard deviation (RSR). The GRU model demonstrated the best performance, achieving r = 0.876 (very strong), NSE = 0.752 (very good), and RSR = 0.498 (very good). This research underscores the importance of accurate discharge prediction for water resource management in Indonesia. By applying innovative modeling techniques, the study contributes to improved water management strategies, with potential applications in flood management, agriculture, infrastructure planning, and policy development, ultimately supporting Indonesia’s broader sustainability goals.