Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope

Botto, Anna; Belluco, Enrica; Camporese, Matteo

doi:https://doi.org/10.5194/hess-22-4251-2018

Articles | Volume 22, issue 8

https://doi.org/10.5194/hess-22-4251-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-22-4251-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 8

Research article

|

13 Aug 2018

Research article |

| 13 Aug 2018

Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope

Anna Botto, Enrica Belluco, and Matteo Camporese

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Final revised paper (published on 13 Aug 2018)
Preprint (discussion started on 31 Jan 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'inverse modelling, data assimilation, variably saturated flow', Anonymous Referee #1, 09 Mar 2018
- AC1: 'Reply to Referee 1', Anna Botto, 15 Mar 2018
RC2: 'Review: Mutli-source data assimilation for physically-based hydrological modeling of an experimantal hill by A. Botto, E. Belluco and M. Camporese', Anonymous Referee #2, 20 Mar 2018
- AC2: 'reply to Referee 2', Anna Botto, 12 Apr 2018
RC3: 'Referee comments', Anonymous Referee #3, 09 May 2018
- AC3: 'Reply to Referee 3', Anna Botto, 11 May 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to revisions (further review by editor and referees) (14 May 2018) by Harrie-Jan Hendricks Franssen

AR by Anna Botto on behalf of the Authors (25 May 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (01 Jun 2018) by Harrie-Jan Hendricks Franssen

RR by Anonymous Referee #3 (05 Jul 2018)

RR by Anonymous Referee #2 (20 Jul 2018)

ED: Publish as is (24 Jul 2018) by Harrie-Jan Hendricks Franssen

AR by Anna Botto on behalf of the Authors (24 Jul 2018) Author's response Manuscript

Short summary

We present a multivariate application of the ensemble Kalman filter (EnKF) in hydrological modeling of a real-world hillslope test case with dominant unsaturated dynamics and strong nonlinearities. Overall, the EnKF is able to correctly update system state and soil parameters. However, multivariate data assimilation may lead to significant tradeoffs between model predictions of different variables, if the observation data are not high quality or representative.