Author(s)

A. Bonafe, G. Galeati & M. Sforna

Abstract

A neural network is developed to model the rainfall-runoff behaviour of the Tiber River basin. Performances of the neural network are then compared with the ones gained through an autoregressive model with exogenus input (ARX) and via the persistence hypothesis. The comparison shows that the neural scheme is able to provide very accurate discharge forecasts and performances quite superior to the other two approaches. 1. Introduction The subject of rainfall-runoff modelling affects a wide spectrum of topics ranging from water resources management to areal flooding and dam safety analysis. Fundamental to each topic is the problem of how to accurately compute runoff at a point from meteorological data consisting mainly of rainfall and temperature measurements over the catchment area. The fact that there is no single unive

Keywords