real-time flood forecasting using a hydrological grey model in conjunction with a global optimization method
Publish place: Symposium on Uncertainty Assessment in Dam Engineering
Publish Year: 1384
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
SUADE01_037
تاریخ نمایه سازی: 15 آبان 1390
Abstract:
Real-time flood forecasting is the major element of a flood forecasting and control system that is a nonstructural method to reduce flood damage in flood prone areas. In this study, a hydrological grey model is developed to forecast runoff in real time, and the model’s applicability is evaluated by comparison with the observed and forecasted runoff. The model parameters are estimated with a global search method, the annealing-simplex method in conjunction with an objective function, HMLE. To forecast accurately runoff, the fifth order differential equation is adopted as the governing equation of the model. The statistic values between the observed and forecasted runoff in calibration and validation indicate that the simulated results are in good agreement with the observed. To evaluate the efficiency of the grey model, the results of the model are compared to these of an artificial neural networks (ANN) model. Comparing RMSE, R2, and REPF (Relative Error between the observed and forecasted Peak Flow) values of the ANN model and grey model results reveals that the grey model is a little superior to the ANN model.
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Authors
M. G KANG
Senior Researcher, Korea Institute of Water and Environment, Korea Water Resources Corporation (KOWACO), Daejon
S. W. PARK
Department of Agricultural Engineering, Seoul National University, Seoul, Korea
I. H. KO
Head Researcher Chief, Korea Institute of Water and Environment, Korea Water Resources Corporation (KOWACO
Y. J. NA
Korea Institute of Water and Environment, Korea Water Resources Corporation (KOWACO), Daejon, Korea,
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