Validation and Over-Parameterization—Experiences from Hydrological Modeling

  • Jan SeibertEmail author
  • Maria Staudinger
  • H. J. (Ilja) van Meerveld
Part of the Simulation Foundations, Methods and Applications book series (SFMA)


Models that simulate environmental processes by quantifying fluxes and states vary largely in their complexity and number of parameters. Most models suffer from over-parameterization, meaning that the available information does not allow identification of all model parameters. Over-parameterization is a serious problem in environmental modeling, as it might imply that a model works well, but could do so for the wrong reasons. This can lead to unreliable results when the model is used to make predictions. Model testing, or model validation, is therefore crucial. Usually, in more complex models more, internal variables are explicitly simulated, and, thus, there are more opportunities for model testing against observations than is the case for simple models. Increasing model complexity, however, comes at the cost of more parameters, and therefore the risk for over-parameterization increases as well. In this chapter, we discuss different ways to validate models, which simulate hydrological processes at the catchment scale, and the balance between model testability and over-parameterization.


Model validation Catchment modeling Model complexity Parameter identification 

Supplementary material


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Authors and Affiliations

  • Jan Seibert
    • 1
    Email author
  • Maria Staudinger
    • 1
  • H. J. (Ilja) van Meerveld
    • 1
  1. 1.Department of GeographyUniversity of ZurichZurichSwitzerland

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