Comparison of parameter estimation algorithms in hydrological modelling

Roberta-Serena Blasone, Henrik Madsen, Dan Rosbjerg

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Local search methods have been applied successfully in calibration of simple groundwater models, but might fail in locating the optimum for models of increased complexity, due to the more complex shape of the response surface. Global search algorithms have been demonstrated to perform well for these types of models, although at a more expensive computational cost. The main purpose of this study is to investigate the performance of a global and a local parameter optimization algorithm, respectively, the Shuffled Complex Evolution (SCE) algorithm and the gradient-based Gauss-Marquardt-Levenberg algorithm (implemented in the PEST software), when applied to a steady-state and a transient groundwater model. The results show that PEST can have severe problems in locating the global optimum and in being trapped in local regions of attractions. The global SCE procedure is, in general, more effective and provides a better coverage of the Pareto optimal solutions at a lower computational cost.
Original languageEnglish
Title of host publicationCalibration and reliability in groundwater modelling: from uncertainty to decision making
EditorsM.F.P. Bierkens, H.C. Gehrels, K. Kovar
Place of PublicationOxfordshire, UK
PublisherIAHS Press
Publication date2006
ISBN (Print)978-1-901502-58-9
Publication statusPublished - 2006
EventModelCare 2005 Conference - The Hague, Netherlands
Duration: 1 Jan 2005 → …


ConferenceModelCare 2005 Conference
CityThe Hague, Netherlands
Period01/01/2005 → …
SeriesI A H S Proceedings and Reports


  • automatic calibration
  • hydrological modelling
  • MIKE SHE model
  • optimization algorithms
  • parameter estimation


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