Model complexity control for hydrologic prediction

  title={Model complexity control for hydrologic prediction},
  author={Gerrit H W Schoups and Nick van de Giesen and Hubert H. G. Savenije},
[1] A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore needed. We compare three model complexity control methods for hydrologic prediction, namely, cross validation (CV), Akaike’s information criterion (AIC), and structural risk minimization (SRM… CONTINUE READING
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