Bayesian inference of earthquake rupture models using polynomial chaos expansion

Cruz-Jiménez, Hugo; Li, Guotu; Mai, Paul Martin; Hoteit, Ibrahim; Knio, Omar M.

doi:https://doi.org/10.5194/gmd-11-3071-2018

Articles | Volume 11, issue 7

https://doi.org/10.5194/gmd-11-3071-2018

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

https://doi.org/10.5194/gmd-11-3071-2018

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

Articles | Volume 11, issue 7

Methods for assessment of models

|

31 Jul 2018

Methods for assessment of models |

| 31 Jul 2018

Bayesian inference of earthquake rupture models using polynomial chaos expansion

Hugo Cruz-Jiménez, Guotu Li, Paul Martin Mai, Ibrahim Hoteit, and Omar M. Knio

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Final revised paper (published on 31 Jul 2018)
Preprint (discussion started on 05 Feb 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Standard deviation of observations (GMPE) vs standard deviation of the surrogate (PC)', Anonymous Referee #1, 22 Mar 2018
RC2: 'Referee comments', Anonymous Referee #2, 26 Mar 2018
RC3: 'General comments', Anonymous Referee #1, 05 Apr 2018
EC1: 'Code availability', Thomas Poulet, 21 Apr 2018
AC1: 'Authors' response to editor and referees' comments on the manuscript of "Bayesian inference of earthquake rupture models using polynomial chaos expansion"', Guotu Li, 16 May 2018

Peer-review completion

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

AR by Guotu Li on behalf of the Authors (13 Jun 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (15 Jun 2018) by Thomas Poulet

RR by Anonymous Referee #2 (21 Jun 2018)

RR by Anonymous Referee #1 (26 Jun 2018)

ED: Publish as is (30 Jun 2018) by Thomas Poulet

AR by Guotu Li on behalf of the Authors (08 Jul 2018) Author's response Manuscript

Short summary

One of the most important challenges seismologists and earthquake engineers face is reliably estimating ground motion in an area prone to large damaging earthquakes. This study aimed at better understanding the relationship between characteristics of geological faults (e.g., hypocenter location, rupture size/location, etc.) and resulting ground motion, via statistical analysis of a rupture simulation model. This study provides important insight on ground-motion responses to geological faults.