Validation of NRECA Parameters for Rainfall-to-Discharge Modeling in the Rejoso Watershed

The Rejoso Watershed in Pasuruan Regency is a water source for local needs and ecological balance. However, limited discharge data due to the absence of optimal measurement infrastructure poses a challenge for sustainable watershed management. This study aims to estimate river discharge using the NRECA method, with parameter optimization for PSUB and GWF achieved through a Genetic Algorithm. The novelty of this research lies in its integration of the NRECA method and Genetic Algorithm for improved discharge estimation in data-scarce regions. Calibration and validation were conducted using a 15:5 ratio, resulting in a Nash-Sutcliffe Efficiency (NSE) value of 0.5379, categorized as “Meets” based on the range defined (0.50–0.65), and a correlation coefficient of 0.7907, indicating a “Strong” linear relationship. Validation ensures the model's reliability beyond historical calibration data, addressing potential overfitting. These findings demonstrate the NRECA method's capability, supported by Genetic Algorithm optimization, as a practical alternative for discharge estimation in watersheds with limited data. Nevertheless, the model’s performance remains sensitive to input data quality, emphasizing the need for better rainfall data. This approach contributes to improving water resource management in Rejoso and similar watersheds facing data limitations.