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Abstract: Land use change has significant impacts on hydrologic processes at the watershed level. This paper combines an empirical land use change model and an event-scale, rainfall-runoff model to quantify the impacts of potential land use change on the storm-runoff generation in the Xitiaoxi basin upstream of Taihu Lake watershed. The HEC–HMS rainfall-runoff model is calibrated and validated for 7 storm events in the study area, and the results show good consistency between the simulated and measured hydrographs at the outlet of the basin with Nash–Sutcliff efficiency ranging from 75% to 95%. Then two future land use scenarios for the year 2050 are forecasted using the CLUE-s model based on the land use of 2002: (1) scenario A with an increase in urban area from 9.2% to 17% of the entire watershed and (2) scenario B with an increase from 9.2% to 14%. Finally, the calibrated HEC–HMS model is applied for these future land use scenarios under designed storms with different recurrence intervals to assess the potential land use impacts on the storm-runoff generation. The results indicate that the future land use scenarios are projected to increase the total runoff as well as the peak discharge, and that the magnitude of increment relates to the expansion rate of built-up area. In the case of rainstorms with recurrence intervals of 10, 50 and 100 years, the simulated peak discharges increase by 3.8%, 2.6% and 2.3% under scenario A, and by 2.8%, 1.9% and 1.7% under scenario B, respectively; while the total runoff is projected to increase by 4.7%, 3.4% and 3.0% under scenario A, and by 3.3%, 2.5% and 2.1% under scenario B. It can be concluded that the sensitivity of hydrologic response to land use change tends to increase as the recurrence interval of rainfall events decreases. Additionally, remarkable spatial variations of the land use changes and its impacts can be observed at the subbasin level, and the most sensitive subbasin is closeby the city. The results of this paper can provide useful support for land use planning and management, and the methods applied here have proved a useful tool for land use impact studies. [Copyright &y& Elsevier]

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]