Data assimilation with an improved particle filter and  its application in the TRIGRS landslide model

Xue, Changhu; Nie, Guigen; Li, Haiyang; Wang, Jing

doi:https://doi.org/10.5194/nhess-18-2801-2018

Articles | Volume 18, issue 10

https://doi.org/10.5194/nhess-18-2801-2018

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

https://doi.org/10.5194/nhess-18-2801-2018

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

Articles | Volume 18, issue 10

Research article

|

26 Oct 2018

Research article |

| 26 Oct 2018

Data assimilation with an improved particle filter and its application in the TRIGRS landslide model

Changhu Xue, Guigen Nie, Haiyang Li, and Jing Wang

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Final revised paper (published on 26 Oct 2018)
Supplement to the final revised paper
Preprint (discussion started on 02 Jan 2018)
Supplement to the preprint

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Comments to authors', Anonymous Referee #1, 06 Mar 2018
- AC2: 'Reply for the comment "nhess-2017-439-RC1"', Guigen Nie, 24 Apr 2018
RC2: 'Comments to nhess-2017-439', Anonymous Referee #2, 11 Mar 2018
- AC3: 'Reply for the comment "nhess-2017-439-RC2"', Guigen Nie, 24 Apr 2018
AC1: 'Reply for the comment "nhess-2017-439-RC1"', Guigen Nie, 24 Apr 2018

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (24 Apr 2018) by Thomas Glade

AR by Guigen Nie on behalf of the Authors (09 May 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (08 Jul 2018) by Thomas Glade

RR by Anonymous Referee #2 (18 Jul 2018)

RR by Anonymous Referee #1 (21 Jul 2018)

ED: Publish subject to minor revisions (review by editor) (10 Aug 2018) by Thomas Glade

AR by Guigen Nie on behalf of the Authors (18 Aug 2018) Author's response

ED: Publish as is (14 Oct 2018) by Thomas Glade

AR by Guigen Nie on behalf of the Authors (15 Oct 2018) Author's response Manuscript

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Short summary

Landslide is a common and sudden geological disaster, which is difficult to monitor and prevent efficiently. This paper introduces an improved algorithm of data assimilation that merges the observations into a landslide evolutionary model. A nonlinear model experiment is applied to verify the feasibility of the algorithm. An application of landslide simulation is carried out. Results show that the estimations of states can effectively correct the running offset after assimilation.