Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4145-2018
https://doi.org/10.5194/hess-22-4145-2018
Research article
 | 
03 Aug 2018
Research article |  | 03 Aug 2018

Improvement of model evaluation by incorporating prediction and measurement uncertainty

Lei Chen, Shuang Li, Yucen Zhong, and Zhenyao Shen

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Latest update: 14 Jul 2024
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Short summary
In this study, the cumulative distribution function approach (CDFA) and the Monte Carlo approach (MCA) were used to develop two new approaches for model evaluation within an uncertainty framework. These proposed methods could be extended to watershed models to provide a substitution for traditional model evaluations within an uncertainty framework.