Keywords

Hydrologic complexity; robust model selection; complexity regularization

Location

Session C1: Complexity, Sensitivity, and Uncertainty Issues in Integrated Environmental Models

Start Date

16-6-2014 3:40 PM

End Date

16-6-2014 5:20 PM

Abstract

This paper uses a recently proposed measure of hydrological model complexity in a model selection exercise. It demonstrates that a robust hydrological model is selected by penalizing model complexity while maximizing a model performance measure. This especially holds when limited data is available. here by a robust model, we mean a model that predicts a variable of interest conditioned on future input forcing better than a model that is fitted on limited data. We demonstrate this on a rainfall-runoff model structure, SAC-SMA, using MOPEX data set of Guadalupe river basin.

 
Jun 16th, 3:40 PM Jun 16th, 5:20 PM

Complexity regularized hydrological model selection

Session C1: Complexity, Sensitivity, and Uncertainty Issues in Integrated Environmental Models

This paper uses a recently proposed measure of hydrological model complexity in a model selection exercise. It demonstrates that a robust hydrological model is selected by penalizing model complexity while maximizing a model performance measure. This especially holds when limited data is available. here by a robust model, we mean a model that predicts a variable of interest conditioned on future input forcing better than a model that is fitted on limited data. We demonstrate this on a rainfall-runoff model structure, SAC-SMA, using MOPEX data set of Guadalupe river basin.