Genetic Algorithm-Based NRECA Parameter Calibration for Rainfall-Discharge Modeling in Rejoso Watershed
DOI:
10.29303/jppipa.v11i6.11091Published:
2025-06-25Downloads
Abstract
The Rejoso watershed in Pasuruan Regency is a critical water resource that supports various sectors, including agriculture and domestic needs. However, the imbalance between water demand and availability, exacerbated by insufficient discharge measurement infrastructure, necessitates alternative approaches to determine river discharge. This study utilizes the NRECA method combined with Genetic Algorithms (GA) to estimate river discharge by calibrating key hydrological parameters, Percent Sub-Surface (PSUB) and Ground Water Flow (GWF). Data from seven rainfall stations and AWLR Winongan were analyzed for the 2004-2023 period. Calibration of the NRECA model was carried out using the Nash-Sutcliffe Efficiency (NSE) and correlation coefficient (R), both achieving values close to 1, indicating an excellent model fit. The study highlights the applicability of GA for optimizing hydrological parameters and demonstrates the potential of the NRECA-GA method in improving discharge predictions in watersheds with limited data. These findings contribute to more effective and sustainable water resource management in the Rejoso watershed.
Keywords:
Calibration, Discharge, Genetic algorithm (GA), GWF, PSUB, RainfallReferences
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