Vol. 12 No. 5 (2026): In Progress
Open Access
Peer Reviewed

Evaluation and Bias Correction of CORDEX-SEA Precipitation for Future Rainfall Projection in the Sutami Reservoir Catchment, Indonesia

Authors

Dwi Anggraini , Sri Wahyuni , Mohammad Bisri

DOI:

10.29303/jppipa.v12i5.15055

Published:

2026-06-04

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Abstract

This study evaluates the performance of CORDEX-SEA precipitation data and applies bias correction for future rainfall projection in the Sutami Reservoir catchment, Indonesia, which has an important role in irrigation and flood control management. Observed rainfall data for 1995–2024 were compared with CORDEX-SEA outputs under the RCP 4.5 and RCP 8.5 scenarios to assess model performance during the present-day period. The model generally overestimated observed rainfall, with average 10-day rainfall values of 86.09 mm/10-day (RCP 4.5) and 89.49 mm/10-day (RCP 8.5), compared to 56.19 mm/10-day from observations. Bias correction was performed using the Linear Scaling (LS) and Quantile Mapping (QM) methods because of their robustness and effectiveness in reducing systematic bias in precipitation data while preserving the temporal characteristics of climate model outputs. The corrected results showed substantial improvement, with the correlation coefficient increasing to 0.95, Nash–Sutcliffe Efficiency reaching 0.90, RMSE-standard deviation ratio decreasing to 0.32, and Percent Bias reducing to approximately 2–3%. Rainfall projections for 2025–2030 indicate a decreasing rainfall trend under both scenarios. This study demonstrates that LS and QM can effectively improve CORDEX-SEA precipitation data reliability for watershed-scale climate change and water resources assessments in Indonesia.

Keywords:

Bias Correction Climate Change CORDEX-SEA Precipitation Projection Sutami Reservoir

References

Agaj, T., Janicka-kubiak, E., Budka, A., & Bytyqi, V. (2026). Urban Expansion and Flood-Relevant Runoff Responses in Data-Limited Catchments. Water, 1–25. https://doi.org/10.3390/w18050639 DOI: https://doi.org/10.3390/w18050639

Ahmad, B., Aslam, M., & Hayat, A. (2025). Speci fi c impacts of climate change on the hydrological patterns and land use dynamics in the Arghandab River Basin, Kandahar, Afghanistan. Natural Hazards Research, 5(2), 380–390. https://doi.org/10.1016/j.nhres.2024.12.007 DOI: https://doi.org/10.1016/j.nhres.2024.12.007

Anggraini, D., Wahyuni, S., & Bisri, M. (2025). Analisis Kesesuaian Data Curah Hujan Satelit CHIRPS Terhadap Data Curah Hujan Pengamatan di Kawasan Waduk Pacal. Jurnal Teknologi Dan Rekayasa Sumber Daya Air, 5(2), 1221–1228. https://doi.org/10.21776/ub.jtresda.2025.005.02.116 DOI: https://doi.org/10.21776/ub.jtresda.2025.005.02.116

Anindya, D. P., Suhartanto, E., & Fidari, J. S. (2022). Perbandingan Metode Alih Ragam Hujan Menjadi Debit dengan FJ . Mock dan NRECA di DAS. Jurnal Teknologi Dan Rekayasa Sumber Daya Air, 2(2), 286–299. https://doi.org/10.21776/ub.jtresda.2022.002.02.24 DOI: https://doi.org/10.21776/ub.jtresda.2022.002.02.24

Azman, A. H., Nadrah, N., Tukimat, A., & Malek, M. A. (2022). Analysis of Linear Scaling Method in Downscaling Precipitation and Temperature. Water Resources Management, 171–179. https://doi.org/10.1007/s11269-021-03020-0 DOI: https://doi.org/10.1007/s11269-021-03020-0

Baycan, A., & Sonmez, O. (2025). Climate Change Effects on Precipitation and Streamflow in the Mediterranean Region. Water, 17, 1–25. https://doi.org/10.3390/w17172556 DOI: https://doi.org/10.3390/w17172556

Chen, J., Yang, Y., & Tang, J. (2022). Bias correction of surface air temperature and precipitation in CORDEX East Asia simulation : What should we do when applying bias correction ? Atmospheric Research, 280(July), 106439. https://doi.org/10.1016/j.atmosres.2022.106439 DOI: https://doi.org/10.1016/j.atmosres.2022.106439

Derdour, S., Ghenim, A. N., Megnounif, A., & Tangang, F. (2022). Bias Correction and Evaluation of Precipitation Data from the CORDEX Regional Climate Model for Monitoring Climate Change in the Wadi Chemora Basin ( Northeastern Algeria ). Atmosphere, 13, 1876. https://doi.org/10.3390/atmos13111876 DOI: https://doi.org/10.3390/atmos13111876

Devi, U., Shekhar, M. S., Singh, G. P., Rao, N. N., & Bhatt, U. S. (2019). Methodological application of quantile mapping to generate precipitation data over Northwest Himalaya. International Journal of Climatology, February, 3160–3170. https://doi.org/10.1002/joc.6008 DOI: https://doi.org/10.1002/joc.6008

Diffenbaugh, N. S., & Giorgi, F. (2012). Climate change hotspots in the CMIP5 global climate model ensemble. 813–822. https://doi.org/10.1007/s10584-012-0570-x DOI: https://doi.org/10.1007/s10584-012-0570-x

Enayati, M., Bozorg-haddad, O., & Bazrafshan, J. (2021). Bias correction capabilities of quantile mapping methods for rainfall and temperature variables. Journal of Water and Climate Change, 12(2), 401-419. https://doi.org/10.2166/wcc.2020.261 DOI: https://doi.org/10.2166/wcc.2020.261

Gudmundsson, L., Bremnes, J. B., Haugen, J. E., & Skaugen, T. E. (2012). Technical Note : Downscaling RCM precipitation to the station scale using quantile mapping – a comparison of methods. Hydrology & Earth System Sciences Discussions, 9(5), 6185-6201. https://doi.org/10.5194/hessd-9-6185-2012 DOI: https://doi.org/10.5194/hessd-9-6185-2012

Hanifa, R., & Wiratmo, J. (2024). ENSO and IOD Influence on Extreme Rainfall in Indonesia : Historical and Future Analysis. 38(2), 78–87. https://doi.org/10.29244/j.agromet.38.2.78-87 DOI: https://doi.org/10.29244/j.agromet.38.2.78-87

Hariadi, M. H., Van Der Schrier, G., Steeneveld, G. J., Sutanto, S. J., Sutanudjaja, E., Ratri, D. N., Sopaheluwakan, A., & Klein Tank, A. (2024). A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia. Hydrology and Earth System Sciences, 28(9), 1935–1956. https://doi.org/10.5194/hess-28-1935-2024 DOI: https://doi.org/10.5194/hess-28-1935-2024

Hastina, Wahyuni, S., & Harisuseno, D. (2025). Projection of Precipitation in the Wonogiri Reservoir Based on CORDEX-SEA Model Output. Jurnal Teknik Pengairan: Journal of Water Resources Engineering, 16(1), 0–7. https://doi.org/10.21776/ub.pengairan.2024.016.01.1 DOI: https://doi.org/10.21776/ub.pengairan.2025.016.01.10

Holthuijzen, M., Beckage, B., Clemins, P. J., Higdon, D., & Winter, J. M. (2022). Robust bias-correction of precipitation extremes using a novel hybrid empirical quantile-mapping method Advantages of a linear correction for extremes. Theoretical and Applied Climatology, 863–882. https://doi.org/10.1007/s00704-022-04035-2 DOI: https://doi.org/10.1007/s00704-022-04035-2

Luo, X., Fan, X., Li, Y., & Ji, X. (2020). Bias correction of a gauge-based gridded product to improve extreme precipitation analysis in the Yarlung Tsangpo – Brahmaputra River basin. Nat. Hazards Earth Syst. Sci, 2243–2254. https://doi.org/10.5194/nhess-20-2243-2020 DOI: https://doi.org/10.5194/nhess-20-2243-2020

Ly, S., Sayama, T., & Try, S. (2023). Integrated impact assessment of climate change and hydropower operation on streamflow and inundation in the lower Mekong Basin. Progress in Earth and Planetary Science. https://doi.org/10.1186/s40645-023-00586-8 DOI: https://doi.org/10.1186/s40645-023-00586-8

Mahdaoui, K., Chafiq, T., Asmlal, L., & Tahiri, M. (2024). Assessing hydrological response to future climate change in the Bouregreg watershed , Morocco. Scientific African, 23(November 2023), e02046. https://doi.org/10.1016/j.sciaf.2023.e02046 DOI: https://doi.org/10.1016/j.sciaf.2023.e02046

Marzuki, M., Ramadhan, R., Yusnaini, H., Juneng, L., Tangang, F., Vonnisa, M., Afdal, A., Abdillah, M. R., & Hidayat, R. (2026). Future projections of extreme precipitation over Indonesia’s new capital under climate change scenario using CORDEX-SEA regional climate models. Atmospheric Research, 327(July 2025), 108389. https://doi.org/10.1016/j.atmosres.2025.108389 DOI: https://doi.org/10.1016/j.atmosres.2025.108389

Mendez, M., Maathuis, B., Hein-Griggs, D., & Gamboa, L. F. A. (2020). Performance Evaluation of Bias Correction Methods for Climate Change Monthly Precipitation Projections. Water. https://doi.org/10.3390/w12020482 DOI: https://doi.org/10.3390/w12020482

Moriasi, D. N., Arnold, J. G., Liew, M. W. Van, Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE, 50(3), 885–900. https://doi.org/10.13031/2013.23153 DOI: https://doi.org/10.13031/2013.23153

Moya, H., Althoff, I., Celis-diez, J. L., Huenchuleo-pedreros, C., & Reggiani, P. (2024). Impact of Future Climate Scenarios and Bias Correction Methods on the Achibueno River Basin. Water, 16, 1138. https://doi.org/10.3390/w16081138 DOI: https://doi.org/10.3390/w16081138

Nomleni, A., Suhartanto, E., & Harisuseno, D. (2021). Estimation of Flow Discharge Model at Temef Watershed - East Nusa Tenggara Using TRMM Satellite Data. Civil and Environmental Science Journal, 4(2), 115–126. https://doi.org/10.21776/ub.civense.2021.00402.2 DOI: https://doi.org/10.21776/ub.civense.2021.00402.2

Nurjani, E., Sekaranom, A. B., Setyaningrum, E., & Prabowo, A. A. (2025). Meteorological Water Scarcity Projection For 2021- 2035 Based On Cmip6 (Coupled Model Intercomparison Project Phase 6) Scenario In Daerah Istimewa Yogyakarta. Jurnal Meteorologi dan Geofisika, 25(1), 57-68. https://doi.org/10.31172/jmg.v25i1.1063 DOI: https://doi.org/10.31172/jmg.v25i1.1063

Pawitan, H. (2018). Climate change impacts on availability and vulnerability of Indonesia water resources. IOP Conference Series: Earth and Environmental Science, 200, 12003. https://doi.org/10.1088/1755-1315/200/1/012003 DOI: https://doi.org/10.1088/1755-1315/200/1/012003

Qian, W., & Chang, H. H. (2021). Projecting Health Impacts of Future Temperature : A Comparison of Quantile-Mapping Bias-Correction Methods. Int. J. Environ. Res. Public Health. https://doi.org/10.3390/ijerph18041992 DOI: https://doi.org/10.3390/ijerph18041992

Raj, B., Raj, T., Shu, L., Shrestha, S., Prasad, R., Dawadi, B., Baniya, B., & Prasad, Y. (2025). Evaluation of distributed and semi-distributed hydrological models in complex River Basin system , Nepal. HydroResearch, 8, 49–57. https://doi.org/10.1016/j.hydres.2024.09.006 DOI: https://doi.org/10.1016/j.hydres.2024.09.006

Saidah, H., Hanifah, L., Gede, I. D., & Negara, J. (2023). The Climate Change Impact on Drought Characteristics in North Lombok Regency. Jurnal Penelitian Pendidikan IPA, 9(5), 2332–2340. https://doi.org/10.29303/jppipa.v9i5.2380 DOI: https://doi.org/10.29303/jppipa.v9i5.2380

San, R., Pérez, J. L., González, R. M., Pecci, J., Garzón, A., & Palacios, M. (2016). Impacts of the 4 . 5 and 8 . 5 RCP global climate scenarios on urban meteorology and air quality : Application to Madrid , Antwerp , Milan , Helsinki and London. Journal of Computational and Applied Mathematics, 293, 192–207. https://doi.org/10.1016/j.cam.2015.04.024 DOI: https://doi.org/10.1016/j.cam.2015.04.024

Satria, I., Sumiadi, & Wahyuni, S. (2025). Utilization of CORDEX-SEA Rainfall Data for Rainfall Projections Using the RCP 4 . 5 Secenario in the Beringin Sila Dam Catchment Area Sumbawa Regency. Jurnal Penelitian Pendidikan IPA, 11(9), 787–795. https://doi.org/10.29303/jppipa.v11i9.12744 DOI: https://doi.org/10.29303/jppipa.v11i9.12744

Setiyowati, Y. A., Harisuseno, D., & Sajali, M. A. (2025). Comparison of Correlation , PBIAS and RSR between Monthly , Daily , and Hourly GPM Rainfall Data. Jurnal Penelitian Pendidikan IPA, 11(6), 615–624. https://doi.org/10.29303/jppipa.v11i6.11068 DOI: https://doi.org/10.29303/jppipa.v11i6.11068

Sobkowiak, L. (2025). Impacts of Climate Change on Water Resources : Assessment and Modeling — Second Edition. Water, 17, 3421. https://doi.org/10.3390/w17233421 DOI: https://doi.org/10.3390/w17233421

Sulistyani, K. F., & Irianto, D. B. (2024). Climate Change Impact on Water Availability and Water Balance on Sampit Cachtment, Central Kalimantan (Pengaruh Perubahan Iklim Terhadap Ketersediaan Air dan Neraca Air DAS Sampit, Kalimantan Tengah). Reka Buana : Jurnal Ilmiah Teknik Sipil Dan Teknik Kimia, 9(1), 109–120. https://doi.org/10.33366/reka DOI: https://doi.org/10.33366/rekabuana.v9i1.5627

Supari, Tangang, F., Juneng, L., Cruz, F., Chung, J. X., Ngai, S. T., Salimun, E., Mohd, M. S. F., Santisirisomboon, J., Singhruck, P., PhanVan, T., Ngo-Duc, T., Narisma, G., Aldrian, E., Gunawan, D., & Sopaheluwakan, A. (2020). Multi-model projections of precipitation extremes in Southeast Asia based on CORDEX-Southeast Asia simulations. Environmental Research, 184(March), 109350. https://doi.org/10.1016/j.envres.2020.109350 DOI: https://doi.org/10.1016/j.envres.2020.109350

Tangang, F., Chung, J. X., Supari, L. J., Salimun, E., & Tieh, S. (2020). Projected future changes in rainfall in Southeast Asia based on CORDEX – SEA multi ‑ model simulations. Climate Dynamics, 55(5), 1247–1267. https://doi.org/10.1007/s00382-020-05322-2 DOI: https://doi.org/10.1007/s00382-020-05322-2

Tieh, S., Juneng, L., Tangang, F., Xiang, J., & Supari, S. (2022). Projected mean and extreme precipitation based on bias-corrected simulation outputs of CORDEX Southeast Asia. Weather and Climate Extremes, 37(July), 100484. https://doi.org/10.1016/j.wace.2022.100484 DOI: https://doi.org/10.1016/j.wace.2022.100484

Tudaji, M., Tian, F., Zhang, K., & Lyu, H. (2025). Evaluation and Bias Correction of ECMWF Extended-Range Precipitation Forecasts over the Confluence of Asian Monsoons and Westerlies Using the Linear Scaling Method. Hydrology, 1–20. https://doi.org/10.3390/hydrology12080218 DOI: https://doi.org/10.2139/ssrn.4706973

Yersaw, B. T., & Chane, M. B. (2024). Regional climate models and bias correction methods for rainfall ‑ runoff modeling in Katar watershed , Ethiopia. Environmental Systems Research. https://doi.org/10.1186/s40068-024-00340-z DOI: https://doi.org/10.1186/s40068-024-00340-z

Yun, X., Tang, Q., Wang, J., Liu, X., Zhang, Y., Lu, H., Wang, Y., Zhang, L., & Chen, D. (2020). Impacts of climate change and reservoir operation on streamflow and flood characteristics in the Lancang-Mekong River Basin. Journal of Hydrology, 590(June), 125472. https://doi.org/10.1016/j.jhydrol.2020.125472 DOI: https://doi.org/10.1016/j.jhydrol.2020.125472

Author Biographies

Dwi Anggraini, Brawijaya University

Author Origin : Indonesia

Sri Wahyuni, Universitas Brawijaya

Author Origin : Indonesia

Mohammad Bisri, Universitas Brawijaya

Author Origin : Indonesia

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How to Cite

Anggraini, D., Wahyuni, S., & Bisri, M. (2026). Evaluation and Bias Correction of CORDEX-SEA Precipitation for Future Rainfall Projection in the Sutami Reservoir Catchment, Indonesia. Jurnal Penelitian Pendidikan IPA, 12(5), 569–577. https://doi.org/10.29303/jppipa.v12i5.15055