Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China
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Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58 % of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and 3-h precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions.
KeywordsDaily streamflow Hourly rainfall Regional downscaling Huai River SWAT
The authors gratefully acknowledge the financial support provided by Chinese Natural Science Foundation (41201191), Chinese Ministry of Education New Faculty Fund (20120071120034), Fudan University Tyndall Center Project (FTC98503B04), and Chinese Natural Science Foundation (41201394). We also acknowledge the CORDEX-East Asia Databank, which is responsible for the CORDEX dataset, and we thank the National Institute of Meteorological Research (NIMR), three universities in the Republic of Korea (Seoul National University, Yonsei University, Kongju National University) and other cooperative research institutes in East Asia region for producing and making available their model output.
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