2012
DOI: 10.1002/hyp.9264
|View full text |Cite
|
Sign up to set email alerts
|

All that glitters is not gold: the case of calibrating hydrological models

Abstract: All that glitters is not gold is one of those universal truths that also applies to hydrology, and particularly to the issue of model calibration, where a glittering mathematical optimum is too often mistaken for a hydrological optimum. This commentary aims at underlining the fact that calibration difficulties have not disappeared with the advent of the latest search algorithms. While it is true that progress on the numerical front has allowed us to quasi-eradicate miscalibration issues, we still too often und… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
75
0

Year Published

2014
2014
2018
2018

Publication Types

Select...
8
1

Relationship

2
7

Authors

Journals

citations
Cited by 91 publications
(75 citation statements)
references
References 33 publications
0
75
0
Order By: Relevance
“…Although these models require profile data, long data series of profile data are still rare and satellite measurements can be useful to provide long-term data for the study at hand. The value of the calibration parameters depends on the available data (Andréassian et al, 2012;Prats and Danis, 2017) and it is interesting to test the long-term performance of a model, especially if it will be used to predict the effects of climate change or similar long-term effects. Satellite measurements have been used to assess the long-term performance of a hydrodynamic model of the reservoir of Bimont (Prats et al, 2018b).…”
Section: Applicationsmentioning
confidence: 99%
“…Although these models require profile data, long data series of profile data are still rare and satellite measurements can be useful to provide long-term data for the study at hand. The value of the calibration parameters depends on the available data (Andréassian et al, 2012;Prats and Danis, 2017) and it is interesting to test the long-term performance of a model, especially if it will be used to predict the effects of climate change or similar long-term effects. Satellite measurements have been used to assess the long-term performance of a hydrodynamic model of the reservoir of Bimont (Prats et al, 2018b).…”
Section: Applicationsmentioning
confidence: 99%
“…Although the calibrated models may then adequately reproduce the output variable, model equifinality (e.g. Savenije, 2001) will lead to many apparently feasible solutions that do not sufficiently well reproduce system-internal dynamics as they are mere artefacts of the mathematical optimization process rather than suitable representations of reality (Gharari et al, 2013;Hrachowitz et al, 2013b;Andréassian et al, 2012;Beven, 2006;Kirchner, 2006). The realisation that there is a need for multivariable and multiobjective model evaluation strategies to identify and discard solutions that do not satisfy all evaluation criteria applied is therefore gaining ground (e.g.…”
Section: Introductionmentioning
confidence: 99%
“…Model performance depends on the characteristics of the calibration period (Van Straten and Keesman, 1991;Andréassian et al, 2012). Long term satellite data showed the long-term stability of the simulation performance (Fig.…”
Section: Evaluation Of Model Performancementioning
confidence: 98%