Utilization of CORDEX-SEA Rainfall Data for Rainfall Projections Using the RCP 4.5 Secenario in the Beringin Sila Dam Catchment Area Sumbawa Regency

Climate change poses significant challenges to water resource management, particularly in regions dependent on reservoirs. This study evaluates the performance of CORDEX-SEA rainfall data in the Beringin Sila watershed and applies a bias correction using the Linear Scaling (LS) method. Historical analysis for 2001–2022 revealed that the raw CORDEX-SEA output overestimated rainfall, with a mean of 147.88 mm/month compared to 93.10 mm/month observed (PBIAS = 35.5%, Willmott’s d = 0.03). After applying LS, model accuracy improved substantially, yielding an adjusted mean of 100.30 mm/month, PBIAS of 3.07%, Willmott’s d of 0.748, and correlation coefficient of 0.580. These results confirm that LS effectively reduces systematic bias. The corrected dataset was then used to project rainfall for 2023–2050 under the RCP 4.5 scenario. Projections indicate an average of 98.49 mm/month, or 5.8% higher than the historical baseline, with considerable interannual variability ranging from less than 50 mm in dry years to more than 300 mm in wet years. Such findings highlight both the potential for modestly increased water availability and the need for adaptive reservoir operation to manage variability across wet and dry seasons. The results provide a valuable reference for future water balance studies and operational strategies in newly constructed reservoirs such as Beringin Sila.

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Publication Details

Journal
Jurnal Penelitian Pendidikan IPA
Published
2025-09-25
DOI
https://doi.org/10.29303/jppipa.v11i9.12744
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Utilization of CORDEX-SEA Rainfall Data for Rainfall Projections Using the RCP 4.5 Secenario in the Beringin Sila Dam Catchment Area Sumbawa Regency

Sumiadi, Sri Wahyuni, Iwin Satria
Jurnal Penelitian Pendidikan IPA
Data Mining and Machine Learning Applications
article

Utilization of CORDEX-SEA Rainfall Data for Rainfall Projections Using the RCP 4.5 Secenario in the Beringin Sila Dam Catchment Area Sumbawa Regency

Sumiadi, Sri Wahyuni, Iwin Satria
article en

Abstract

Climate change poses significant challenges to water resource management, particularly in regions dependent on reservoirs. This study evaluates the performance of CORDEX-SEA rainfall data in the Beringin Sila watershed and applies a bias correction using the Linear Scaling (LS) method. Historical analysis for 2001–2022 revealed that the raw CORDEX-SEA output overestimated rainfall, with a mean of 147.88 mm/month compared to 93.10 mm/month observed (PBIAS = 35.5%, Willmott’s d = 0.03). After applying LS, model accuracy improved substantially, yielding an adjusted mean of 100.30 mm/month, PBIAS of 3.07%, Willmott’s d of 0.748, and correlation coefficient of 0.580. These results confirm that LS effectively reduces systematic bias. The corrected dataset was then used to project rainfall for 2023–2050 under the RCP 4.5 scenario. Projections indicate an average of 98.49 mm/month, or 5.8% higher than the historical baseline, with considerable interannual variability ranging from less than 50 mm in dry years to more than 300 mm in wet years. Such findings highlight both the potential for modestly increased water availability and the need for adaptive reservoir operation to manage variability across wet and dry seasons. The results provide a valuable reference for future water balance studies and operational strategies in newly constructed reservoirs such as Beringin Sila.

Jurnal Penelitian Pendidikan IPAVol. 11(9)
University of Brawijaya (ID)
Openalex Percentile: Top 58%
Data Mining and Machine Learning Applications
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