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Advances in Meteorology
Volume 2016, Article ID 2485251, 12 pages
Research Article

Long-Term Simulation of Daily Streamflow Using Radar Rainfall and the SWAT Model: A Case Study of the Gamcheon Basin of the Nakdong River, Korea

1Water Resources Research Division, Korea Institute of Civil Engineering and Building Technology (KICT), Goyang 10223, Republic of Korea
2Department of Civil Engineering, Inha University, Incheon 22212, Republic of Korea
3Columbia Water Center, Earth Institute, Columbia University, New York, NY 10027, USA

Received 23 February 2016; Revised 17 June 2016; Accepted 19 July 2016

Academic Editor: Gwo-Fong Lin

Copyright © 2016 Huiseong Noh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In recent years, with the increasing need for improving the accuracy of hydrometeorological data, interests in rain-radar are also increasing. Accordingly, with high spatiotemporal resolution of rain-radar rainfall data and increasing accumulated data, the application scope of rain-radar rainfall data into hydrological fields is expanding. To evaluate the hydrological applicability of rain-radar rainfall data depending on the characteristics of hydrological model, this study applied and to a SWAT model in the Gamcheon stream basin of the Nakdong River and analyzed the effect of rainfall data on daily streamflow simulation. The daily rainfall data for , , and were utilized as input data for the SWAT model. As a result of the daily runoff simulation for analysis periods using and , the simulation which utilized reflected the rainfall-runoff characteristics better than the simulations which applied or . However, in the rainy or wet season, the simulations which utilized or were similar to or better than the simulation that applied . This study reveals that analysis results and degree of accuracy depend significantly on rainfall characteristics (rainy season and dry season) and QPE algorithms when conducting a runoff simulation with radar.