This paper presents a discussion of the relationship between data used for hydrologic model calibration and the precision of model parameter estimates. The analysis is conducted within the framework of the maximum likelihood approach to model selection. The concept of "information" is discussed and the relationship between information and parameter uncertainty is examined. This analysis provides some interesting insights into the role that the quantity and quality of the data used play in the identification procedure. Based on this, a method for selecting data sets suitable for model calibration is suggested. The ideas discussed are illustrated by means of simulation studies using a conceptual-type rainfall-runoff model.
ASJC Scopus subject areas
- Water Science and Technology