<![CDATA[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.]]>
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