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Summary: The hydrological cycle has been substantially influenced by climate change and human activities. It is therefore of utmost importance to analyze the impact of climate change on hydrology, particularly on a regional scale, in order to understand potential future changes of water resources and water-related disaster, and provide support for regional water management. However, during the evaluation of climate change impact on hydrology or water resources, large uncertainty exists. In this paper, the Soil Water Assessment Tool (SWAT) model is used to investigate the potential impact of climate change on hydrology of the upper reaches of Qiantang River Basin, East China, for the future period 2011–2100. The uncertainty is considered by employing upgraded reliability ensemble averaged GCM climate projections under three emission scenarios A1B, A2 and B1 for three different stages of the future period. These projections are downscaled and used in the hydrological model. Impact of climate change on precipitation, potential evapotranspiraton and river runoff is then investigated. The model calibration and validation outcomes show reasonable performance of the SWAT model. The final results suggest that annual river runoff will likely decrease almost under all emission scenarios and time stages of the future period. Particularly, at Jinhua Station, substantial decrease of annual river runoff can be noticed, indicating less water resource possibly available for the region in future. Simulated monthly patterns show that the largest decrease will likely occur in winter while increases will occur in summer, implying possible more water-related disasters in this region. However, it is also noticed that the change signs/amount could be different under different emission scenarios and time stages, indicating large uncertainty involved in the impact analysis. [ABSTRACT FROM AUTHOR]

Summary: This paper aims to provide an enhanced understanding of the parameter sensitivities of the Soil and Water Assessment Tool (SWAT) using a variance-based global sensitivity analysis, i.e., Sobol′’s method. The Yichun River Basin, China, is used as a case study, and the sensitivity of the SWAT parameters is analyzed under typical dry, normal and wet years, respectively. To reduce the number of model parameters, some spatial model parameters are grouped in terms of data availability and multipliers are then applied to parameter groups, reflecting spatial variation in the distributed SWAT model. The SWAT model performance is represented using two statistical metrics – Root Mean Square Error (RMSE) and Nash–Sutcliffe Efficiency (NSE) and two hydrological metrics – RunOff Coefficient Error (ROCE) and Slope of the Flow Duration Curve Error (SFDCE). The analysis reveals the individual effects of each parameter and its interactions with other parameters. Parameter interactions contribute to a significant portion of the variation in all metrics considered under moderate and wet years. In particular, the variation in the two hydrological metrics is dominated by the interactions, illustrating the necessity of choosing a global sensitivity analysis method that is able to consider interactions in the SWAT model identification process. In the dry year, however, the individual effects control the variation in the other three metrics except SFDCE. Further, the two statistical metrics fail to identify the SWAT parameters that control the flashiness (i.e., variability of mid-flows) and overall water balance. Overall, the results obtained from the global sensitivity analysis provide an in-depth understanding of the underlying hydrological processes under different metrics and climatic conditions in the case study catchment. [ABSTRACT FROM AUTHOR]