Prediction limits of a catchment hydrological model using different estimates of ET_p

A joint deterministic-stochastic protocol based on Monte Carlo simulations (MCS) was applied to the modelling of a medium size catchment using two significantly different sets of potential evapotranspiration (ET_p) data, estimated through a Penman-based method. Modelling error was accounted using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. Both, water routing and water balance related parameters were considered in the analysis. The research revealed that the hypothesis of the less correct ET_p data set being appropriate for the current modelling could not be rejected since model parameters adjusted to compensate for the use of significantly different ET_p data sets. The GLUE analysis demonstrated that the model predictions exhibited some sensitivity to the hydraulic conductivity of one of the geological layers. Furthermore, the study revealed a considerable error attached to the simulation of both high and low flows, as well as, piezometric levels, for every ET_p data set, which was most likely magnified by the coarse time and spatial scales used in the current modelling.