Evaluasi dan Koreksi Bias Curah Hujan Cmip6 Ssp5-8.5 Tahun 2025–2050 di Dta Waduk Sutami

Abdul Razaq; Mahendra Andiek Maulana; Anak Agung Ngurah Satria Damar Negara

doi:10.55681/armada.v4i10.4639

Authors

Abdul Razaq Postgraduate Student at Institute Teknologi Sepuluh Nopember, Surabaya, Indonesia
Mahendra Andiek Maulana Institute Teknologi Sepuluh Nopember, Surabaya, Indonesia
Anak Agung Ngurah Satria Damar Negara Institute Teknologi Sepuluh Nopember, Surabaya, Indonesia

DOI:

https://doi.org/10.55681/armada.v4i10.4639

Keywords:

Curah Hujan, NEX-GDDP-CMIP6, Quantile Mapping, SSP5-8.5, Waduk Sutami

Abstract

Evaluasi dan koreksi bias curah hujan diperlukan untuk mendukung pemodelan sumber daya air dan pengelolaan sedimentasi di Daerah Tangkapan Air Waduk Sutami. Penelitian ini mengevaluasi lima model iklim CMIP6 dan memproyeksikan curah hujan terkoreksi berdasarkan skenario SSP5-8.5 periode 2025–2050. Data kosong observasi enam stasiun hujan periode 2012–2014 dilengkapi menggunakan Inverse Distance Weighting (IDW), sedangkan curah hujan wilayah dihitung dengan Poligon Thiessen. Kinerja model dievaluasi pada skala harian dan bulanan menggunakan rata-rata, korelasi, RMSE, dan MAE sebelum serta sesudah koreksi Quantile Mapping (QM). Hasil menunjukkan bahwa QM meningkatkan kesesuaian statistik pada skala bulanan dengan korelasi hingga 0,94, tetapi korelasi harian tetap rendah (0,19–0,33). Proyeksi ansambel menunjukkan rata-rata curah hujan tahunan sebesar 1.290,93 mm, menurun 3,90% dibandingkan kondisi historis sebesar 1.343,35 mm. Temuan ini mendukung analisis neraca air, simulasi hidrologi, dan mitigasi sedimentasi dengan mempertimbangkan ketidakpastian antarmodel.

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References

Arif Rafhida, S., Nurdiati, S., Budiarti, R., & Khoirun Najib, M. (2025). Bias correction of CMIP6 rainfall projection for the Lake Toba region, Indonesia, using quantile delta mapping with monthly distribution fitting. Vietnam Journal of Earth Sciences, 48(1), 89–112. https://doi.org/10.15625/2615-9783/23833

Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937–1958. https://doi.org/10.5194/gmd-9-1937-2016

Fidari, J. S., Bisri, M., & Suhartanto, E. (2013). Studi pendugaan sisa usia guna Waduk Sutami dengan pendekatan sedimentasi. Jurnal Teknik Pengairan: Journal of Water Resources Engineering, 4(2).

Hidayat, R., & Taufik, M. (2025). Bias correction of CMIP6 models for assessment of wet and dry conditions over Sumatra. Agromet, 39(1), 33–39. https://doi.org/10.29244/j.agromet.39.1.33-39

Hidayati, F., Iriawan, N., Kuswanto, H., & Sopaheluwakan, A. (2026). Improving local rainfall projections in Bali through bias correction of CMIP6 data: A contribution to hydro-meteorological disaster mitigation. IOP Conference Series: Earth and Environmental Science, 1607(1), Article 012045. https://doi.org/10.1088/1755-1315/1607/1/012045

Hutauruk, R. C. H., Rahmanto, E., Al Habib, A. H., Yoku, P. W., Giriharta, I. W. G., Trilaksono, N. J., & Hadi, T. W. (2025). Evaluation of bias correction method for monthly rainfall prediction of ECMWF SEAS5 in Indonesia. Jurnal Meteorologi dan Geofisika, 25(2), 103–112. https://doi.org/10.31172/jmg.v25i2.1124

Kurniadi, A., Weller, E., Kim, Y.-H., & Min, S.-K. (2023). Evaluation of Coupled Model Intercomparison Project Phase 6 model-simulated extreme precipitation over Indonesia. International Journal of Climatology, 43(1), 174–196. https://doi.org/10.1002/joc.7744

Kurniadi, A., Firmansyah, Wati, T., Nazarudin, L., Puspita, N. C. I., Fauziyah, A. R., Meisda, D. F., Wicaksono, A., Kadarsah, Hadi, A. S., & Radjab, A. F. (2026). Evaluating NEX-GDDP CMIP6 models for extreme wet and dry events over Indonesia. International Journal of Climatology, 46(10), Article e70437. https://doi.org/10.1002/joc.70437

Lange, S. (2019). Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0). Geoscientific Model Development, 12(7), 3055–3070. https://doi.org/10.5194/gmd-12-3055-2019

Lehner, F., Nadeem, I., & Formayer, H. (2023). Evaluating skills and issues of quantile-based bias adjustment for climate change scenarios. Advances in Statistical Climatology, Meteorology and Oceanography, 9, 29–43. https://doi.org/10.5194/ascmo-9-29-2023

Maraun, D., Shepherd, T. G., Widmann, M., Zappa, G., Walton, D., Gutierrez, J. M., Hagemann, S., Richter, I., Soares, P. M., Hall, A., & Mearns, L. O. (2017). Towards process-informed bias correction of climate change simulations. Nature Climate Change, 7(11), 764–773. https://doi.org/10.1038/nclimate3418

Mardwiono, F., Sedyowati, L., & Wibisono, G. (2022). Integrated sediment management as a sustainable effort of reservoir function: A case study on the Sengguruh and Sutami reservoirs. International Journal of Innovative Science and Research Technology, 7(2), 492–500. https://doi.org/10.5281/zenodo.6333773

O’Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., & Sanderson, B. M. (2016). The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geoscientific Model Development, 9(9), 3461–3482. https://doi.org/10.5194/gmd-9-3461-2016

Padulano, R., Gomez-Mogollon, L. A., Napolitano, L., & Rianna, G. (2025). Quantile-based bias-correction of extreme rainfall: Pros & cons of popular methods for climate signal preservation. Journal of Hydrology, 653, Article 132814. https://doi.org/10.1016/j.jhydrol.2025.132814

Pimonsree, S., Kamworapan, S., Gheewala, S. H., Thongbhakdi, A., & Prueksakorn, K. (2023). Evaluation of CMIP6 GCMs performance to simulate precipitation over Southeast Asia. Atmospheric Research, 282, Article 106522. https://doi.org/10.1016/j.atmosres.2022.106522

Potter, N. J., Chiew, F. H. S., Charles, S. P., Fu, G., Zheng, H., & Zhang, L. (2020). Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections. Hydrology and Earth System Sciences, 24, 2963–2979. https://doi.org/10.5194/hess-24-2963-2020

Prasetya, R., Djuhana, D., Saputro, A. H., & Permana, D. S. (2026). Evaluation and ranking of NEX-GDDP-CMIP6 models based on monthly precipitation climatology over Indonesia. Frontiers in Climate, 8, Article 1748663. https://doi.org/10.3389/fclim.2026.1748663

Primartono, D. Y., Hidayat, R., Supari, Prasetia, R., & Taufik, M. (2025). A spatially distributed rainfall dataset for West Java, Indonesia. Data in Brief, 62, Article 111974. https://doi.org/10.1016/j.dib.2025.111974

Putra, M., Rosid, M. S., & Handoko, D. (2024). A review of rainfall estimation in Indonesia: Data sources, techniques, and methods. Signals, 5(3), 542–561. https://doi.org/10.3390/signals5030030

Rajulapati, C. R., & Papalexiou, S. M. (2023). Precipitation bias correction: A novel semi-parametric quantile mapping method. Earth and Space Science. https://doi.org/10.1029/2023EA002823

Rodríguez González, C. A., Rodríguez-Pérez, Á. M., López, R., Hernández-Torres, J. A., & Caparrós-Mancera, J. J. (2023). Sensitivity analysis in mean annual sediment yield modeling with respect to rainfall probability distribution functions. Land, 12(1), Article 35. https://doi.org/10.3390/land12010035

Sisinggih, D., Wahyuni, S., Juwono, P. T., & Hidayat, F. (2023). Discharging sediment downstream: The opportunities and challenges of sediment management in Sutami Reservoir, Indonesia. International Journal of Sustainable Development and Planning, 18(2), 541–548. https://doi.org/10.18280/ijsdp.180223

Teutschbein, C., & Seibert, J. (2012). Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods. Journal of Hydrology, 456–457, 12–29. https://doi.org/10.1016/j.jhydrol.2012.05.052

Thrasher, B., Wang, W., Michaelis, A., Melton, F., Lee, T., & Nemani, R. (2022). NASA Global Daily Downscaled Projections, CMIP6. Scientific Data, 9, Article 262. https://doi.org/10.1038/s41597-022-01393-4

Zhang, H., Chapman, S., Trancoso, R., Toombs, N., & Syktus, J. (2024). Assessing the impact of bias correction approaches on climate extremes and the climate change signal. Meteorological Applications, 31(3), Article e2204. https://doi.org/10.1002/met.2204