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Prediction of Stream Flow on Probability Distributed Model using Multi-objective Function  

Ahn, Sang-Eok (충북대학교 대학원 토목공학과)
Lee, Hyo-Sang (충북대학교 공과대학 토목공학부)
Jeon, Min-Woo (충북대학교 공과대학 토목공학부)
Publication Information
Journal of the Korean Society of Hazard Mitigation / v.9, no.5, 2009 , pp. 93-102 More about this Journal
Abstract
A prediction of streamflow based on multi-objective function is presented to check the performance of Probability Distributed Model(PDM) in Miho stream basin, Chungcheongbuk-do, Korea. PDM is a lumped conceptual rainfall runoff model which has been widely used for flood prevention activities in UK Environmental Agency. The Monte Carlo Analysis Toolkit(MCAT) is a numerical analysis tools based on population sampling, which allows evaluation of performance, identifiability, regional sensitivity and etc. PDM is calibrated for five model parameters by using MCAT. The results show that the performance of model parameters(cmax and k(q)) indicates high identifiability and the others obtain equifinality. In addition, the multi-objective function is applied to PDM for seeking suitable model parameters. The solution of the multi-objective function consists of the Pareto solution accounting to various trade-offs between the different objective functions considering properties of hydrograph. The result indicated the performance of model and simulated hydrograph are acceptable in terms on Nash Sutcliffe Effciency*(=0.035), FSB(=0.161), and FDBH(=0.809) to calibration periods, validation periods as well.
Keywords
Multi-objective function; PDM; Pareto solution; Monte Carlo;
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Times Cited By KSCI : 4  (Citation Analysis)
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