Abstract: Subseasonal to seasonal (S2S) precipitation prediction, characterized by its relatively long lead time, can serve as a reference over a longer temporal scale.When applied to the source region of Changjiang River, it can effectively extend the lead time of runoff prediction in Changjiang River basin.However, existing S2S precipitation prediction products often show large biases and coarse spatial resolution in the source region of Changjiang River.When employed to drive hydrological models with high demands for data quality, these products may introduce substantial biases.In order to rationally utilize S2S precipitation prediction products for runoff prediction, S2S prediction products from four global prediction centers (including the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts, Korea Meteorological Administration, and UK Meteorological Office) were selected to evaluate their precipitation prediction accuracy.A daily-scale bias correction method was adopted to correct the original precipitation prediction products.Furthermore, we analyzed the impact of bias correction on the performance of S2S precipitation prediction, as well as the roles of two correction strategies-correction of precipitation and temperature, and correction of runoff prediction-in S2S runoff prediction for the source region of the Changjiang River.The results indicated that: ① the S2S product from the European Centre for Medium-Range Weather Forecasts exhibited the best performance in precipitation prediction.Bias correction could significantly enhance the precipitation prediction capability of S2S products from different sources, which was specifically manifested in the reduction of errors between the predicted data and the observed data after bias correction, and the correction effect became more prominent with the extension of lead time; ② Considering both the correction effect and computational complexity, direct correction of runoff was more suitable for the bias correction of S2S runoff prediction in the source area of the Changjiang River.This study can provide reference for the operational prediction of S2S precipitation and runoff in Changjiang River Basin.