Comparison between NARX-NN and HEC-HMS models to simulate Wadi Seghir catchment runoff events in Algerian northern

Abstract

ABSTRACT This paper presents a comparison between the black box Nonlinear Auto-Regressive with eXogenous inputs-Neural Network (NARX-NN) and the conceptual Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) Rainfall-Runoff models. The two models were applied on a small urban watershed to assess its response to fourteen hourly real storm events. The differences between the steps engaged in each model to reach the hydrograph were presented in detail. The estimation of the best parameters is carried out using a weighted average function during the calibration phase. A statistical evaluation was conducted to assess the model’s performance thereafter; a critical comparison was made to illustrate the differences and discuss the steps involved. The results indicate that both models successfully reflect the urban basin runoff. However, the NARX-NN outperforms in the testing phase owing to their strength generalization feature. The NARX-NN model has more strength to produce the shape bending of the hydrograph. Consequently, this model is better to highlight the curvatures resulting from the local peaks of rainfall.