Khabur River Flow Modeling using Artificial Neural Networks

Abstract:Modeling a hydrologic time series has been one of the most complicated tasksowing to the wide range of data, the uncertainties in the parameters influencing thetime series and also due to the non availability of adequate data. Recently, ArtificialNeural Networks (ANNs) have become quite popular in time series forecasting invarious fields. This paper demonstrates the use of ANNs to forecast Khabur monthlyriver flows for flow data from January 1958 to December 1975. Using the feedforward network. The network is trained using the lagged or delayed variables fromSARIMA model as an input variables for the network. ANN model for mouthy flowgives better result in comparison with Traditional ANN models and SARIMA model.