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Impact of topography on earthquake static slip estimates

Langer, Leah and Ragon, Théa and Sladen, Anthony and Tromp, Jeroen (2020) Impact of topography on earthquake static slip estimates. Tectonophysics, 791 . Art. No. 228566. ISSN 0040-1951. https://resolver.caltech.edu/CaltechAUTHORS:20200716-093438147

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Abstract

Our understanding of earthquakes is limited by our knowledge, and our description, of the physics of the Earth. When solving for subsurface fault slip, it is common practice to assume minimum complexity for characteristics such as topography, fault geometry and elastic properties. These characteristics are rarely accounted for because our knowledge of them is often partial and they can be difficult to include in simulations. However, topography and bathymetry are known all over the Earth's surface, and recently developed software packages such as SPECFEM-X have simplified the process of including them in calculations. Here, we explore the impact of topography on static slip estimates. We also investigate whether the influence of topography can be accounted for with a zeroth-order correction which accounts for variations in distance between subfaults and the surface of the domain. To this end, we analyze the 2015 M_w 7.5 Gorkha, Nepal, and the 2010 M_w 8.8 Maule, Chile earthquakes within a Bayesian framework. The regions affected by these events represent different types of topography. Chile, which contains both a deep trench and a major orogen, the Andes, has a greater overall elevation range and steeper gradients than Nepal, where the primary topographic feature is the Himalayan mountain range. Additionally, the slip of the continental Nepal event is well-constrained, whereas observations are less informative in a subduction context. We show that topography has a non-negligible impact on inferred slip models. Our results suggest that the effect of topography on slip estimates increases with limited observational constraints and high elevation gradients. In particular, we find that accounting for topography improves slip estimates where topographic gradients are large. When topography has a significant impact on slip, the zeroth-order correction is not sufficient.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.tecto.2020.228566DOIArticle
https://doi.org/10.5281/zenodo.1313201DOICode
ORCID:
AuthorORCID
Ragon, Théa0000-0002-1276-1910
Sladen, Anthony0000-0003-4126-0020
Tromp, Jeroen0000-0002-2742-8299
Additional Information:© 2020 Elsevier B.V. Received 19 February 2020, Revised 11 June 2020, Accepted 12 July 2020, Available online 16 July 2020. We are grateful to Raphael Grandin who shared his processed Sentinel 1 InSAR data (Grandin et al., 2015). This research used computational resources provided by the Princeton Institute for Computational Science & Engineering (PICSciE). The Bayesian simulations were performed with the AlTar package (https://github.com/AlTarFramework/altar), on the HPC-Regional Center ROMEO (https://romeo.univ-reims.fr) of the University of Reims Champagne-Ardenne (France). The Classic Slip Inversion (CSI) Python library (Jolivet et al., 2014; https://github.com/jolivetr/csi) created by Romain Jolivet was used to build inputs for the Bayesian algorithm, in particular to compute non-topographic Green's functions. 3D data were visualized using the open-source parallel visualization software ParaView/VTK (www.paraview.org). Figures were generated with the Matplotlib and Seaborn (doi:https://doi.org/10.5281/zenodo.1313201) Python libraries and with the Generic Mapping Tools library (Wessel et al., 2019). This study was partly supported by the French National Research Agency ANR JCJC E-POST (ANR-14-CE03-002-01JCJC 'E-POST') and partly by NSF grant 1644826. Théa Ragon was supported by a fellowship from the French Ministry of Higher Education and is supported by a fellowship from the Caltech GPS Division. We thank Romain Jolivet and two anonymous reviewers for their thorough and constructive remarks. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Group:Seismological Laboratory
Funders:
Funding AgencyGrant Number
Agence Nationale de la Recherche (ANR)ANR-14-CE03-002-01JCJC
NSFEAR-1644826
Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation (MESRI)UNSPECIFIED
Caltech Division of Geological and Planetary SciencesUNSPECIFIED
Subject Keywords:Earthquake source observations; Inverse theory; Probability distributions; Earthquake modeling; Topography; Maule earthquake; Gorkha earthquake
Record Number:CaltechAUTHORS:20200716-093438147
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200716-093438147
Official Citation:Leah Langer, Théa Ragon, Anthony Sladen, Jeroen Tromp, Impact of topography on earthquake static slip estimates, Tectonophysics, 2020, 228566, ISSN 0040-1951, https://doi.org/10.1016/j.tecto.2020.228566. (http://www.sciencedirect.com/science/article/pii/S0040195120302493)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104399
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:16 Jul 2020 17:42
Last Modified:30 Jul 2020 18:36

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