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Prediction of SWAT Stream Flow Using Only Future Precipitation Data  

Lee, Ji Min (Department of Regional Infrastructures Engineering, Kangwon National University)
Kum, Donghyuk (Department of Regional Infrastructures Engineering, Kangwon National University)
Kim, Young Sug (Korea Institute of Construction Technology)
Kim, Yun Jung (POSCO E&C, R&D Center)
Kang, Hyunwoo (Department of Regional Infrastructures Engineering, Kangwon National University)
Jang, Chun Hwa (Department of Regional Infrastructures Engineering, Kangwon National University)
Lee, Gwan Jae (Department of Regional Infrastructures Engineering, Kangwon National University)
Lim, Kyoung Jae (Department of Regional Infrastructures Engineering, Kangwon National University)
Publication Information
Journal of Korean Society on Water Environment / v.29, no.1, 2013 , pp. 88-96 More about this Journal
Abstract
Much attention has been needed in water resource management at the watershed due to drought and flooding issues caused by climate change in recent years. Increase in air temperature and changes in precipitation patterns due to climate change are affecting hydrologic cycles, such as evaporation and soil moisture. Thus, these phenomena result in increased runoff at the watershed. The Soil and Water Assessment Tool (SWAT) model has been used to evaluate rainfall-runoff at the watershed reflecting effects on hydrology of various weather data such as rainfall, temperature, humidity, solar radiation, wind speed. For bias-correction of RCP data, at least 30 year data are needed. However, for most gaging stations, only precipitation data have been recorded and very little stations have recorded other weather data. In addition, the RCP scenario does not provide all weather data for the SWAT model. In this study, two scenarios were made to evaluate whether it would be possible to estimate streamflow using measured precipitation and long-term average values of other weather data required for running the SWAT. With measured long-term weather data (scenario 1) and with long-term average values of weather data except precipitation (scenario 2), the estimate streamflow values were almost the same with NSE value of 0.99. Increase/decrease by ${\pm}2%$, ${\pm}4%$ in temperature and humidity data did not affect streamflow. Thus, the RCP precipitation data for Hongcheon watershed were bias-corrected with measured long-term precipitation data to evaluate effects of climate change on streamflow. The results revealed that estimated streamflow for 2055s was the greatest among data for 2025s, 2055s, and 2085s. However, estimated streamflow for 2085s decreased by 9%. In addition, streamflow for Spring would be expected to increase compared with current data and streamflow for Summer will be decreased with RCP data. The results obtained in this study indicate that the streamflow could be estimated with long-term precipitation data only and effects of climate change could be evaluated using precipitation data as shown in this study.
Keywords
Future precipitation; RCP8.5 scenario; Runoff simulation; SWAT;
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Times Cited By KSCI : 3  (Citation Analysis)
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