Daily streamflow modelling using autoregressive moving average and artificial neural networks models: case study ofÇoruh basin,Turkey

Abstract

AbstractStreamflow modelling is a quite important issue for water resources system planning and management projects, such as dam construction, reservoir operation and flood control. This study demonstrates the application of artificial neural networks (ANN) and autoregressive moving average (ARMA) models for modelling daily streamflow inÇoruh basin,Turkey, where there are numerous highly critical power plants either under construction or being projected. Daily streamflow records from nine gauging stations located in the basin were used in this study. In the first phase of our study,ANNandARMAmodels were obtained using daily streamflow. In the second phase, 100 synthetic streamflow series were generated using previously determinedANNandARMAmodels in order to ensure the preservation of main statistical characteristics of the historical time series. The results have showed that the historical time series have similar statistical parameters to those of the generated time series at 95% confidence level.