Multi-hazard risk assessment for roads: probabilistic  versus deterministic approaches

Oberndorfer, Stefan; Sander, Philip; Fuchs, Sven

doi:https://doi.org/10.5194/nhess-20-3135-2020

Articles | Volume 20, issue 11

https://doi.org/10.5194/nhess-20-3135-2020

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

https://doi.org/10.5194/nhess-20-3135-2020

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

Articles | Volume 20, issue 11

Research article

|

27 Nov 2020

Research article |

| 27 Nov 2020

Multi-hazard risk assessment for roads: probabilistic versus deterministic approaches

Stefan Oberndorfer, Philip Sander, and Sven Fuchs

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Final revised paper (published on 27 Nov 2020)
Preprint (discussion started on 10 Mar 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review comment', Anonymous Referee #1, 08 Apr 2020
- AC1: 'Authors comment referee #1', Stefan Oberndorfer, 27 Apr 2020
RC2: 'Interactive comments on the paper "Multi-hazard risk assessment for roads: Probabilistic versus deterministic approaches"', Anonymous Referee #2, 22 Jul 2020
- AC2: 'Authors Commend Referre#2', Stefan Oberndorfer, 19 Aug 2020

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (31 Aug 2020) by Thomas Glade

AR by Stefan Oberndorfer on behalf of the Authors (20 Sep 2020) Author's response Manuscript

ED: Publish as is (10 Oct 2020) by Thomas Glade

AR by Stefan Oberndorfer on behalf of the Authors (16 Oct 2020) Manuscript

Short summary

The article provides a comparison of a standard (deterministic) risk assessment approach for roads exposed to a multi-hazard environment with a probabilistic risk analysis method to show the potential bias in the results. A probabilistic approach enables the quantification of epistemic uncertainty and uses probability distributions to characterize data uncertainty of the input variables, while a deterministic computation uses single values with discrete values without uncertainty representation.