Please use this identifier to cite or link to this item:
https://hdl.handle.net/11147/2095
Title: | Predicting and forecasting flow discharge at sites receiving significant lateral inflow | Authors: | Tayfur, Gökmen Moramarco, Tommaso Singh, Vijay P. |
Keywords: | Artificial neural networks Floods Feed-forward back propagation Flood hydrograph Modified Muskingum method Forecasting |
Publisher: | John Wiley and Sons Inc. | Source: | Tayfur, G., Moramarco, T., and Singh, V. P. (2007). Predicting and forecasting flow discharge at sites receiving significant lateral inflow. Hydrological Processes, 21(14), 1848-1859. doi:10.1002/hyp.6320 | Abstract: | Two models, one linear and one non-linear, were employed for the prediction of flow discharge hydrographs at sites receiving significant lateral inflow. The linear model is based on a rating curve and permits a quick estimation of flow at a downstream site. The non-linear model is based on a multilayer feed-forward back propagation (FFBP) artificial neural network (ANN) and uses flow-stage data measured at the upstream and downstream stations. ANN predicted the real-time storm hydrographs satisfactorily and better than did the linear model. The results of sensitivity analysis indicated that when the lateral inflow contribution to the channel reach was insignificant, ANN, using only the flow-stage data at the upstream station, satisfactorily predicted the hydrograph at the downstream station. The prediction error of ANN increases exponentially with the difference between the peak discharge used in training and that used in testing. ANN was also employed for flood forecasting and was compared with the modified Muskingum model (MMM). For a 4-h lead time, MMM forecasts the floods reliably but could not be applied to reaches for lead times greater than the wave travel time. Although ANN and MMM had comparable performances for an 8-h lead time, ANN is capable of forecasting floods with lead times longer than the wave travel time. | URI: | http://doi.org/10.1002/hyp.6320 http://hdl.handle.net/11147/2095 |
ISSN: | 0885-6087 0885-6087 |
Appears in Collections: | Civil Engineering / İnşaat Mühendisliği Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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