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http://dx.doi.org/10.3741/JKWRA.2009.42.11.963

Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (II) : Application and Verification  

Lee, Byong-Ju (Dept. of Civil and Environmental Engrg., Sejong Univ)
Bae, Deg-Hyo (Dept. of Civil and Environmental Engrg., Sejong Univ)
Shamir, Eylon (Hydrologic Research Center)
Publication Information
Journal of Korea Water Resources Association / v.42, no.11, 2009 , pp. 963-972 More about this Journal
Abstract
The objective of this study is to evaluate an application of stochastic continuous storage function model with ensemble Kalman filter technique. The case study is performed at the upstream basin of Jibo streamflow gauge including Andong and Imha dam. Test period is for the rainy season during 2006 and 2007. Long term runoff analysis is feasible in the case of using deterministic model. Ensemble members for input data and parameters are generated using Monte Carlo simulation for the purpose of applying ensemble Kalman filter technique. The cumulative absolute errors of stochastic model to the deterministic one are improved for the amount of 17.5 %, 18.3 % and more than 40.0 % for Andong dam, Imha dam and Jibo station, respectively. The results indicate that the stochastic model improves the accuracy of the simulated discharge considerably.
Keywords
ensemble Kalman filter; stochastic continuous storage function model; Monte Carlo simulation; real-time flood forecast;
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