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This paper estimates the likely impacts of future climate change on streamflow, especially the hydrological extremes over the Yangtze River basin. The future climate was projected by the Coordinated Regional Climate Downscaling Experiment in East Asia (CORDEX-EA) initiative for the periods 2020–2049 under two representative concentration pathways (RCP) 4.5 and 8.5 emission scenarios. The bias corrected outputs from five regional climate models (RCMs) were used in conjunction with the variable infiltration capacity (VIC) macroscale hydrological model to produce hydrological projections. For the future climate of the Yangtze River basin, outputs from an ensemble of RCMs indicate that the annual mean temperature will increase for 2020–2049 by 1.81 °C for RCP4.5 and by 2.26 °C for RCP8.5. The annual mean precipitation is projected to increase by 3.62% under RCP4.5 and 7.65% under RCP8.5. Overall, increases in precipitation are amplified in streamflow, and the change in streamflow also shows significant temporal and spatial variations and large divergence between regional climate models. At the same time, the maximum streamflow in different durations are also projected to increase at three mainstream gauging stations based on flood frequency analysis. In particular, larger increases in maximum 1-day streamflow (+14.24% on average) compared to 5-day and 15-day water volumes (+12.79% and +10.24%) indicate that this projected extreme streamflow increase would be primarily due to intense short-period rainfall events. It is necessary to consider the impacts of climate change in future water resource management. [ABSTRACT FROM AUTHOR]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]