Seasonal water resource forecasts play an increasingly important role in decision-making systems, especially in the agriculture and water sectors. Along with the rapid development of science and technology, seasonal forecasting has made progress in recent years, and global ensemble prediction systems provide increasingly accurate and reliable seasonal forecasting with up to 6–9 months’ lead time. This study focuses on evaluating the applicability of seasonal precipitation re-forecasts from the new ECMWF seasonal forecast system 5 (ECMWF-System5) for the Tra Khuc river basin at six-monthly lead times over the period 1993-2016. In addition, two calibration methods are used to bias correct the seasonal ensemble precipitation forecasts, including the scaling method and the regression-based method. A comparative evaluation of both raw and bias-corrected reforecasts is performed using mean absolute error (MAE) and correlation coefficient (R). According to MAE, both bias correction methods are able to reduce the MAE value from over 50mm/month to less than 10mm/month averaged over the basin and the forecasted months considered. In terms of the R evaluation metric, the scaling method decreases the R-value from 0.63 (for the raw reforecasts) to 0.55 (for the calibrated reforecasts) on average, while the regression-based method does not change this coefficient significantly...
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