Rainfall-Runoff Simulation in the Navrood River basin using Truncated Volterra Model and Artificial Neural Networks

This study evaluates the performance of the linear first-order Volterra model for simulating nonlinear rainfall-runoff process. For this end, fifteen storm events over the Navrood River basin were collected. 70% and 30% of the events were used to calibrate and test the suitability of the model. Finally, the performance of the model was compared with the artificial neural networks (multilayer perceptron (MLP)) using five performance criteria namely coefficient of efficiency, root mean square error, error of total volume, relative error of peak discharge and error of time for peak to arrive. Results indicated that the intelligent MLP models outperformed the Volterra model. The linear Volterra model was not more effective in simulating the rainfall-runoff process. It needs to be extended to higher orders and also the number of the parameters should be reduced.