Comparative analyses of covariance matrix adaptation and iterative ensemble smoother on high-dimensional inverse problems in high-resolution groundwater modeling

•Both CMA-ES and the ES-LM perform well for low dimensionality of unknown parameters.•ES-LM can underestimate uncertainty with small ensemble size.•CMA-ES is more computational demanding than ES-LM for high-dimensionality problems.•ES-LM outperforms the CMA-ES in calibrating high-resolution groundwa...

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Veröffentlicht in:	Journal of hydrology (Amsterdam) 2023-10, Vol.625, p.130075, Article 130075
Hauptverfasser:	Yang, Shuo, Tsai, Frank T.-C., Bacopoulos, Peter, Kees, Christopher E.
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian theory case studies Covariance matrix adaptation groundwater High-dimensional inverse problems High-resolution groundwater model hydrologic models Iterative ensemble smoother Louisiana Mississippi Parallel computing population size system optimization uncertainty variance covariance matrix
Online-Zugang:	Volltext
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