Comparison of non-Gaussian multicomponent and periodic autoregressive models for river flow

Abstract

The Non-Gaussian Multicomponent model for river flow (NGM) of Vandewiele and Dom is modified in order to facilitate maximum likelihood estimation. It is also generalized so that a wider variety of river flows at a diversity of time steps can be modeled. This model is applied to two basins in Belgium and France with very different areas, both at monthly and weekly time scale. Results on the quality of forecasting and simulation (especially simulation of low and high flow volumes) are compared with those of classical Periodic Autoregressive models (PAR). Results with NGM are always better, in most cases considerably better. This is due to the fact that NGM models explicitly take into consideration the presence of so called flow components, like baseflow and direct flow recession, which are phenomena well known to hydrologists.