Articles | Volume 26, issue 20
https://doi.org/10.5194/hess-26-5341-2022
https://doi.org/10.5194/hess-26-5341-2022
Research article
 | 
27 Oct 2022
Research article |  | 27 Oct 2022

Pitfalls and a feasible solution for using KGE as an informal likelihood function in MCMC methods: DREAM(ZS) as an example

Yan Liu, Jaime Fernández-Ortega, Matías Mudarra, and Andreas Hartmann

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Latest update: 25 Feb 2024
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Short summary
We adapt the informal Kling–Gupta efficiency (KGE) with a gamma distribution to apply it as an informal likelihood function in the DiffeRential Evolution Adaptive Metropolis DREAM(ZS) method. Our adapted approach performs as well as the formal likelihood function for exploring posterior distributions of model parameters. The adapted KGE is superior to the formal likelihood function for calibrations combining multiple observations with different lengths, frequencies and units.