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http://dx.doi.org/10.21729/ksds.2022.15.1.1

Analysis of the Effect of Objective Functions on Hydrologic Model Calibration and Simulation  

Lee, Gi Ha (Dept. of Advanced Science and Technology Convergence, Kyungpook National University)
Yeon, Min Ho (Dept. of Advanced Science and Technology Convergence, Kyungpook National University)
Kim, Young Hun (Dept. of Advanced Science and Technology Convergence, Kyungpook National University)
Jung, Sung Ho (Dept. of Advanced Science and Technology Convergence, Kyungpook National University)
Publication Information
Journal of Korean Society of Disaster and Security / v.15, no.1, 2022 , pp. 1-12 More about this Journal
Abstract
An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.
Keywords
Rainfall-runoff modeling; Storage function model; Optimization; Objective functions;
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Times Cited By KSCI : 4  (Citation Analysis)
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