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The hydrological response to the potential future climate change in Yangtze River Basin (YRB), China, was assessed by using an ensemble of 54 climate change simulations. The Coupled Model Intercomparison Project 5 simulations under two new Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios were downscaled and used to drive the Variable Infiltration Capacity hydrological model. This study found that the range of temperature changes is homogeneous for almost the entire region, with an average annual increase of more than 2 °C under RCP4.5 and even more than 4 °C under RCP8.5 in the end of the twenty first century. The warmest period (June-July-August) of the year would experience lower changes than the colder ones (December-January-February). Overall, mean precipitation was projected to increase slightly in YRB, with large dispersion among different global climate models, especially during the dry season months. These phenomena lead to changes in future streamflow for three mainstream hydrological stations (Cuntan, Yichang, and Datong), with slightly increasing annual average streamflows, especially at the end of twenty first century. Compared with the percentage change of mean flow, the high flow shows (90th percentile on the probability of no exceedance) a higher increasing trend and the low flow (10th percentile) shows a decreasing trend or lower increasing trend. The maximum daily discharges with 5, 10, 15, and 30-year return periods show an increasing trend in most sub-basins in the future. Therefore, extreme hydrological events (e.g., floods and droughts) will increase significantly, although the annual mean streamflow shows insignificant change. The findings of this study would provide scientific supports to implement the integrated adaptive water resource management for climate change at regional scales in the YRB. [ABSTRACT FROM AUTHOR]

ABSTRACT Given the availability of a new generation of general circulation model simulations from the Coupled Model Intercomparison Project Phase 5 ( CMIP5) archive, we attempt to evaluate the model output by using three variants of the transformed Mielke measure to assess (1) the performance of the models in simulating historical surface temperature and precipitation, (2) the climate change response of the models to future greenhouse gases ( GHGs) scenarios, and (3) the consistency of the projected change of each model with that of the multi-model ensemble ( MME) mean. Most models exhibited varying degrees of skills, depending on the region and season, whereas a few models were identified as performing well globally, including the CMCC models, IPSL-CM5A-MR, and BCC-CSM1.1M. Models with the highest and lowest climate sensitivities, as well as those that project future climate changes most resembling the MME mean, were identified. The future precipitation and temperature changes projected by the MPI models and NCAR-CESM1 models were found to best resemble the overall MME. Finer resolution was found to improve model performance in simulating historical climate in most regions and seasons, particularly for temperature; however, it does not have a significant effect on the response of model climates to future GHGs scenarios. We found that no model can simultaneously exhibits good performance in simulating historical climate and in projecting a future climate that is close to the MME mean. Determining the 'best' overall model is difficult because 'best' is dependent on the specific applications for which a model will be used. Evaluating climate models is an important step to build confidence in their application for impact assessment. Our study provides a basis for concerned groups choosing climate models for their subsequent studies. [ABSTRACT FROM AUTHOR]