<![CDATA[Precipitation variability significantly impacts water resource management, especially in regions like the Wonogiri Reservoir, which relies heavily on stable precipitation for agriculture, flood control, and water supply. This study investigates precipitation projections for the Wonogiri Reservoir area using CORDEX-SEA simulations under RCP 4.5 and RCP 8.5 scenarios for 2024–2050. Bias correction using Artificial Neural Networks is applied to improve the accuracy of the projections by aligning them with historical observations (1991-2005). The effectiveness of bias correction in 2006-2023 was evaluated using statistical metrics, including Pearson correlation coefficient (R), Percent Bias (PBIAS), and Mean Absolute Error (MAE). The results indicate significant improvements after bias correction. Correlation (R) increased by 13.75% and 17.63% for RCP 4.5 and RCP 8.5, respectively. As measured by PBIAS, systematic bias decreased by 61.09% (RCP 4.5) and 59.85% (RCP 8.5). Similarly, 61.12% and 59.84% MAE reductions were observed for the two scenarios. Post-correction, RCP 4.5 projections align more closely with historical observations, suggesting more stable precipitation patterns under moderate emission scenarios. In contrast, RCP 8.5 displays more significant interannual variability, with pronounced peaks and troughs, indicating increased risks of extreme precipitation under high-emission pathways. The study highlights the importance of integrating corrected precipitation projections into regional water resource planning and adaptation strategies to enhance resilience against future climate impacts. Further research is recommended to explore seasonal precipitation dynamics and extreme event frequencies under both scenarios.]]>
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