Concepts of information content and likelihood in parameter calibration for hydrological simulation models

Beven, Keith John and Smith, Paul James (2014) Concepts of information content and likelihood in parameter calibration for hydrological simulation models. Journal of Hydrologic Engineering, 20 (1): A4014010. ISSN 1084-0699

Full text not available from this repository.


There remains a great deal of uncertainty about uncertainty estimation in hydrological modeling. Given that hydrology is still a subject limited by the available measurement techniques, it does not appear that the issue of epistemic error in hydrological data will go away for the foreseeable future, and it may be necessary to find a way to allow for robust model conditioning and more subjective treatments of potential epistemic errors in prediction. In this paper an attempt is made to analyze how this is the result of the epistemic uncertainties inherent in the hydrological modeling process and their impact on model conditioning and hypothesis testing. Some ideas are proposed about how to deal with assessing the information in hydrological data and how it might influence model conditioning based on hydrological reasoning, with an application to rainfall-runoff modeling of a catchment in northern England, where inconsistent data for some events can introduce disinformation into the model conditioning process. A methodology is presented to make an assessment of the relative information content of calibration data before running a model that can then inform the evaluation of model runs and resulting prediction uncertainties.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Hydrologic Engineering
Uncontrolled Keywords:
?? rainfall-runoff modellinguncertainty estimationepistemic errordisinformationglueevent clusteringgeneral environmental sciencewater science and technologyenvironmental chemistrycivil and structural engineeringenvironmental science(all) ??
ID Code:
Deposited By:
Deposited On:
31 Aug 2016 15:26
Last Modified:
16 Jul 2024 10:14