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http://dx.doi.org/10.3741/JKWRA.2012.45.6.607

Validation of Real-Time River Flow Forecast Using AWS Rainfall Data  

Lee, Byong-Ju (Hydrometeorological Resources Research Team, Applied Meteorology Research Division, National Institute of meteorological Research)
Choi, Jae-Cheon (Hydrometeorological Resources Research Team, Applied Meteorology Research Division, National Institute of meteorological Research)
Choi, Young-Jean (Applied Meteorology Research Division, National Institute of meteorological Research)
Bae, Deg-Hyo (Department of Civil and Environmental Engineering, Sejong University)
Publication Information
Journal of Korea Water Resources Association / v.45, no.6, 2012 , pp. 607-616 More about this Journal
Abstract
The objective of this study is to evaluate the valid forecast lead time and the accuracy when AWS observed rainfall data are used for real-time river flow forecast. For this, Namhan river basin is selected as study area and SURF model is constructed during flood seasons in 2006~2009. The simulated flow with and without the assimilation of the observed flow data are well fitted. Effectiveness index (EI) is used to evaluate amount of improvement for the assimilation. EI at Chungju, Dalcheon, Hoengsung and Yeoju sites as evaluation points show 32.08%, 51.53%, 39.70% and 18.23% improved, respectively. In the results of the forecasted values using the limited observed rainfall data in each forecast time before peak flow occur, the peak flow under the 20% tolerance range of relative error at Chungju, Dalcheon, Hoengsung and Yeoju sites can be simulated in forecast time-11h, 2h, 3h and 5h and the flow volume in the same condition at those sites can be simulated in forecast time-13h, 2h, 4h and 9h, respectively. From this results, observed rainfall data can be used for real-time peak flow forecast because of basin lag time.
Keywords
AWS observed rainfall; real-time river flow forecast; forecast lead time; SURF model;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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