Ernie Nograles Bañares, Muhammad Shafqat Mehboob
Climate change cause increasing threats to global water resources, underscoring the need to understand its hydrological impacts for effective water management. This study quantifies climate input uncertainty in water balance projections for the Libmanan-Pulantuna Watershed (LPW) in the Bicol River Basin, Philippines. Using the Water Evaluation and Planning (WEAP) model, we simulated streamflow under climate projections (CPs) from both CMIP5 and CMIP6 datasets, incorporating four Global Circulation Models (GCMs) and three bias correction methods (BCMs): Linear Scaling (LS), Quantile Mapping (QM), and Detrended Quantile Mapping (DQM). Results show that CMIP6 more accurately captures historical climate trends, particularly in temperature. Bias correction significantly improves the accuracy of both temperature and precipitation inputs, with DQM performing best. Flow-duration curve analysis reveals a trend of increasing low flows and decreasing high flows toward the end of the century, especially under high-emission scenarios, indicating a shift in hydrological regime and potential water shortages during critical periods. An Analysis of Variance (ANOVA) across different runoff percentiles (Q10, Q50, Q90, and mean) and timeframes—near-future (2030–2045), mid-future (2055–2070), and far-future (2080–2095)—shows that GCMs contribute the most to overall uncertainty (26.5 %–55.3 %), followed by CPs (17.4 %–31.3 %), while BCMs have the least impact (9 %–23.5 %). Uncertainty from GCMs is most significant under low-flow conditions, while CPs are more influential during high hydrological activity. These findings highlight the need for careful model selection and robust bias correction to improve the reliability of water resources planning in climate-sensitive regions. © 2025 The Author(s)
Engineering Graduate Program, School of Engineering, University of San Carlos, Cebu, 6000, Philippines; College of Engineering and Architecture, Sorsogon State University, Sorsogon, 4700, Philippines; Department of Civil Engineering, School of Engineering, University of San Carlos, Cebu, 6000, Philippines
