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All Journal Teras Jurnal Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Teknologi dan Rekayasa Sumber Daya Air
Putri, Angelina Satya
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Education Engineering Environmental Science Materials Science & Nanotechnology Physics

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Journal : Jurnal Penelitian Pendidikan IPA (JPPIPA)

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Studi Kalibrasi Parameter NRECA Berbasis Algoritma Genetika untuk Pemodelan Curah Hujan-Debit di DAS Rejoso Putri, Angelina Satya; Suhartanto, Ery; Andawayanti, Ussy
Jurnal Penelitian Pendidikan IPA Vol 11 No 6 (2025): June
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i6.11091

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.
Validation of NRECA Parameters for Rainfall-to-Discharge Modeling in the Rejoso Watershed Putri, Angelina Satya; Suhartanto, Ery; Andawayanti, Ussy
Jurnal Penelitian Pendidikan IPA Vol 11 No 5 (2025): May
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i5.11107

Abstract

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.
Co-Authors Azhar Adi Darmawan Ery Suhartanto Jadfan Sidqi Fidari Rahmah Dara Lufira Ussy Andawayanti