Topographic uncertainty quantification for flow-like landslide models via stochastic simulations

Zhao, Hu; Kowalski, Julia

doi:https://doi.org/10.5194/nhess-20-1441-2020

Articles | Volume 20, issue 5

https://doi.org/10.5194/nhess-20-1441-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-20-1441-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 5

Research article

|

26 May 2020

Research article |

| 26 May 2020

Topographic uncertainty quantification for flow-like landslide models via stochastic simulations

Hu Zhao and Julia Kowalski

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Final revised paper (published on 26 May 2020)
Preprint (discussion started on 02 Jan 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'comments', Anonymous Referee #1, 12 Feb 2020
- AC1: 'authors' reply to reviewer #1', Hu Zhao, 12 Mar 2020
RC2: 'Report on Topographic uncertainty quantiﬁcation for ﬂow-like landslide models via stochastic simulations', Anonymous Referee #2, 15 Feb 2020
- AC2: 'authors' reply to reviewer #2', Hu Zhao, 12 Mar 2020
  - RC3: '“Topographic uncertainty quantiﬁcation for ﬂow-like landslide models via stochastic simulations” by Hu Zhao and Julia Kowalski', Anonymous Referee #2, 14 Mar 2020
    - AC3: 'Thanks for the positive feedback of reviewer #2', Hu Zhao, 21 Mar 2020

Peer-review completion

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

ED: Publish subject to minor revisions (review by editor) (23 Mar 2020) by Paola Reichenbach

AR by Hu Zhao on behalf of the Authors (30 Mar 2020) Author's response Manuscript

ED: Publish as is (07 Apr 2020) by Paola Reichenbach

AR by Hu Zhao on behalf of the Authors (16 Apr 2020)

Short summary

We study the impact of topographic uncertainty on landslide run-out modeling using conditional and unconditional stochastic simulation. First, we propose a generic workflow and then apply it to a historic flow-like landslide. We find that topographic uncertainty can greatly affect landslide run-out modeling, depending on how well the underlying flow path is captured by topographic data. The difference between unconditional and conditional stochastic simulation is discussed in detail.