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Prediction of daily sediment discharge using a back propagation neural network training algorithm:A case study of the Narmada River,India

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International Journal of Sediment Research 2019年第2期34卷 125-135页

作者： Nibedita Bisoyi Harish Gupta Narayan Prasad Padhy govind joseph chakrapani Department of Humanities and Sciences College of Engineering Roorkee Department of Civil Engineering University College of Engineering Osmania University Department of Electrical Engineering Indian Institute of Technology Roorkee Department of Earth Sciences Indian Institute of Technology Roorkee

Most of the studies on Artificial Neural Network(ANN)models remain restricted to smaller rivers and *** this paper,an attempt has been made to correlate variability of sediment loads with rainfall and runoff through the application of the Back Propagation Neural Network(BPNN)algorithm for a large tropical *** algorithm and simulation are done through MATLAB *** methodology comprised of a collection of data on rainfall,water discharge,and sediment discharge for the Narmada River at various locations(along with time variables)and application to develop a threelayer BPNN model for the prediction of sediment *** training and validation purposes a set of549 data points for the monsoon(16 June-15 November)period of three consecutive years(1996-1998)was *** testing purposes,the BPNN model was further trained using a set of 732 data points of monsoon season of four years(2006-07 to 2009-10)at nine *** model was tested by predicting daily sediment load for the monsoon season of the year *** evaluate the performance of the BPNN model,errors were calculated by comparing the actual and predicted *** validation and testing results obtained at all these locations are tabulated and *** obtained from the model application are robust and encouraging not only for the sub-basins but also for the entire *** results suggest that the proposed model is capable of predicting the daily sediment load even at downstream locations,which show nonlinearity in the transportation ***,the proposed model with further training might be useful in the prediction of sediment discharges for large river basins.

关键词： Artificial neural network Back propagation Sediment discharge Prediction Error Narmada River

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Artificial neural network simulation for prediction of suspended sediment concentration in the River Ramganga,Ganges Basin,India

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International Journal of Sediment Research 2019年第2期34卷 95-107页

作者： Mohd Yawar Ali Khan Fuqiang Tian Faisal Hasan govind joseph chakrapani Institute of Hydrology and Water Resources Department of Hydraulic EngineeringSchool of Civil EngineeringTsinghua University Department of Earth Sciences Indian Institute of Technology Roorkee Department of Mechanical Engineering Aligarh Muslim University

The relation between the water discharge(Q) and suspended sediment concentration(SSC)of the River Ramganga at Bareilly,Uttar Pradesh,in the Himalayas,has been modeled using Artificial Neural Networks(ANNs).The current study validates the practical capability and usefulness of this tool for simulating complex nonlinear,real world,river system processes in the Himalayan *** modeling approach is based on the time series data collected from January to December(2008-2010)for Q and *** ANNs(T1-T3)with different network configurations have been developed and trained using the Levenberg Marquardt Back Propagation Algorithm in the Matlab *** were optimized using the enumeration technique,and,finally,the best network is used to predict the SSC values for the year *** values thus obtained through the ANN model are compared with the observed values of *** coefficient of determination(R2),for the optimal network was found to be *** study not only provides insight into ANN modeling in the Himalayan river scenario,but it also focuses on the importance of understanding a river basin and the factors that affect the SSC,before attempting to model *** the temporal variations in the study area,it is possible to model and successfully predict the SSC values with very simplistic ANN models.

关键词： ANN Water discharge Suspended sediment concentration prediction Ramganga River Himalayas

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