Error evolution patterns in multi-step ahead streamflow forecasting

Multi-step ahead streamflow forecasting is of practical interest. We examine the error evolution in multi-step ahead forecasting by conducting six simulation experiments. Within each of these experiments we compare the error evolution patterns created by 16 forecasting methods, when the latter are applied to 2 000 time series. Our findings suggest that the error evolution can differ significantly from the one forecasting method to the other and that some forecasting methods are more useful than others. However, the errors computed at each time step of a forecast horizon for a specific single-case study strongly depend on the case examined and can be either small or large, regardless of the used forecasting method and the time step of interest. This fact is illustrated with a comparative case study using 92 monthly time series of streamflow.