BAYESIAN-ESTIMATION OF UNCERTAINTY IN RUNOFF PREDICTION AND THE VALUEOF DATA - AN APPLICATION OF THE GLUE APPROACH

This paper addresses the problem of evaluating the predictive uncertai nty of TOPMODEL using the Bayesian Generalised Likelihood Uncertainty Estimation (GLUE) methodology in an application to the small Ringelbac h research catchment in the Vosges, France. The wide range of paramete r sets giving acceptable simulations is demonstrated, and uncertainty bands are presented based on different likelihood measures. It is show n how the distributions of predicted discharges are non-Gaussian and v ary in shape through time and with discharge. Updating of the likeliho od weights using Bayes equation is demonstrated after each year of rec ord and it is shown how the additional data can be evaluated in terms of the way they constrain the uncertainty bands.