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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 8
Hydrol. Earth Syst. Sci., 20, 3289–3307, 2016
https://doi.org/10.5194/hess-20-3289-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 3289–3307, 2016
https://doi.org/10.5194/hess-20-3289-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Aug 2016

Research article | 12 Aug 2016

A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

Boujemaa Ait-El-Fquih et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (12 Apr 2016) by Mauro Giudici
AR by Boujemaa Ait-El-Fquih on behalf of the Authors (23 Apr 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (25 Apr 2016) by Mauro Giudici
RR by Anonymous Referee #1 (12 May 2016)
RR by Anonymous Referee #3 (03 Jun 2016)
ED: Publish subject to minor revisions (Editor review) (15 Jun 2016) by Mauro Giudici
AR by Anna Wenzel on behalf of the Authors (29 Jun 2016)  Author's response    Manuscript
ED: Publish subject to technical corrections (10 Jul 2016) by Mauro Giudici
AR by Boujemaa Ait-El-Fquih on behalf of the Authors (18 Jul 2016)  Author's response    Manuscript
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Short summary
We derive a new dual ensemble Kalman filter (EnKF) for state-parameter estimation. The derivation is based on the one-step-ahead smoothing formulation, and unlike the standard dual EnKF, it is consistent with the Bayesian formulation of the state-parameter estimation problem and uses the observations in both state smoothing and forecast. This is shown to enhance the performance and robustness of the dual EnKF in experiments conducted with a two-dimensional synthetic groundwater aquifer model.
We derive a new dual ensemble Kalman filter (EnKF) for state-parameter estimation. The...
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