Water Resources Management

, Volume 23, Issue 7, pp 1325–1349

GLUE Based Assessment on the Overall Predictions of a MIKE SHE Application



The generalised likelihood uncertainty estimation (GLUE) approach was applied to assess the performance of a distributed catchment model and to estimate prediction limits after conditioning based on observed catchment-wide streamflow. Prediction limits were derived not only for daily streamflow but also for piezometric levels and for extreme events. The latter analysis was carried out considering independent partial duration time series (PDS) obtained from the observed daily streamflow hydrograph. Important data uncertainties were identified. For streamflow the stage-discharge data analysis led to estimate an average data uncertainty of about 3 m3 s − 1. For piezometric levels, data errors were estimated to be in the order of 5 m in average and 10 m at most. The GLUE analysis showed that most of the inspected parameters are insensitive to model performance, except the horizontal and vertical components of the hydraulic conductivity of one of the geological layers that have the most influence on the streamflow model performance in the application catchment. The study revealed a considerable uncertainty attached to the simulation of both high flows and low flows (i.e., in average terms 5 m3 s − 1 before the Bayesian updating of the prediction limits). Similarly, wide prediction intervals were obtained for the piezometric levels in relevant wells, in the order of 3.3 and 1.5 m before and after the Bayesian updating of the prediction limits, respectively. Consequently, the results suggest that, in average terms, the model of the catchment predicts overall outputs within the limitations of the errors in the input variables.


MIKE SHE Likelihood Uncertainty Prediction limits Monte Carlo simulations GLUE Partial duration time series Extreme value analysis Piezometers 


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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Unidad HidráulicaTécnica y Proyectos S.A. (TYPSA)BarcelonaSpain
  2. 2.Centre for Research on Environmental Systems and Statistics, Institute for Environmental and Biological SciencesLancaster UniversityLancasterUK
  3. 3.Department Landbeheer-en Economie, Division Soil and Water ManagementK.U. LeuvenHeverleeBelgium

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