Discharge Simulation Evaluations of ISIMIP3a Global Hydrological Models in the Yangtze River Basin

Global hydrological models (GHMs) are essential for assessing water resources and flood risk, yet systematic evaluations of ISIMIP3a models remain limited. We evaluated eight standard ISIMIP3a GHM configurations against observed discharge at four principal Yangtze mainstem gauges using a multi-metric framework covering daily and monthly discharge, the seasonal cycle (defined as the mean annual cycle of monthly discharge), flow percentiles, and annual peak discharge. Metric-based model performance generally increased from daily to monthly and seasonal-cycle scales, partly reflecting the smoothing of short-term errors through temporal aggregation, whereas annual peak discharge remained more difficult to reproduce. WaterGAP2-2e achieved the strongest overall performance across the daily, monthly, and seasonal-cycle evaluations. However, this result was not fully independent of its inherited global discharge calibration, because three evaluation gauges (Yichang, Hankou, and Datong) spatially coincide with gauges in its calibration-station dataset. WaterGAP2-2e also systematically overestimated peak flows, with peak-flow Relative Bias (RBpeak) reaching 30.14%. Among the remaining configurations, WEB-DHM-SG showed the strongest overall performance and a relatively small station-averaged absolute peak-flow bias (|RBpeak| = 15.52%). However, this advantage did not extend to low-flow conditions. H08 and ORCHIDEE-MICT showed the weakest overall performance, with negative NSE values down to −3.61 and peak-flow biases reaching −99.10%, whereas MIROC-INTEG-LAND, CWatM, HydroPy, and JULES-W2-DDM30 showed intermediate performance. Overall, model suitability depended on temporal scale and flow regime, and apparent rankings should be interpreted in light of inherited calibration and configuration differences. These results provide a diagnostic basis for model selection and targeted improvement in regional discharge simulation and peak-flow-related applications.