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This paper presents a comparative study of two data-driven modelling techniques in forecasting urban drainage stormwater discharge based on rainfall prediction. Both M5T and NARX (Nonlinear Autoregressive with eXogenous inputs) Neural Network are used for 30 minutes storm water forecasting. Data are collected from watershed area of 3315 ha, located in the city of Casablanca in Morocco. The results show that both models provide good results, but however with better performances of the NARX model.

Comparison of M5 Model Tree and Nonlinear Autoregressive with eXogenous inputs (NARX) Neural Network for urban stormwater discharge modelling