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Stress, rigidity and sediment strength control megathrust earthquake and tsunami dynamics

Abstract

Megathrust faults host the largest earthquakes on Earth, which can trigger cascading hazards such as devastating tsunamis. Determining characteristics that control subduction-zone earthquake and tsunami dynamics is critical to mitigate megathrust hazards but is impeded by structural complexity, large spatio-temporal scales and scarce or asymmetric instrumental coverage. Here we use high-performance computing multi-physics simulations to show that tsunami genesis and earthquake dynamics are controlled by along-arc variability in regional tectonic stresses together with depth-dependent variations in rigidity and yield strength of near-fault sediments. We aim to identify dominant regional factors controlling megathrust hazards. To this end, we demonstrate how to unify and verify the required initial conditions for geometrically complex, multi-physics earthquake–tsunami modelling from interdisciplinary geophysical observations. We present large-scale computational models of the 2004 Sumatra–Andaman earthquake and Indian Ocean tsunami that reconcile near- and far-field seismic, geodetic, geological, and tsunami observations and reveal tsunamigenic trade-offs between slip to the trench, splay faulting and bulk yielding of the accretionary wedge. Our computational capabilities render possible the incorporation of present and emerging high-resolution observations into dynamic-rupture-tsunami models and will be applicable to other large megathrust earthquakes. Our findings highlight the importance of regional-scale structural heterogeneity to decipher megathrust hazards.

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Fig. 1: Key subduction characteristics constraining a 3D dynamic-rupture model of a megathrust earthquake.
Fig. 2: Dynamics and kinematics of the observationally constrained dynamic-rupture model of the 2004 Sumatra–Andaman earthquake.
Fig. 3: Source properties of the dynamic-rupture scenario and comparison with previously published kinematic models.
Fig. 4: Off-fault yielding and tsunami genesis.

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Data availability

The authors declare that all data supporting the findings of this study are available within the paper and its Methods section. In particular, all data required to reproduce the earthquake scenario can be downloaded from https://doi.org/10.5281/zenodo.5541271. We use the following projection: WGS 84 / UTM Mercator 46N (EPSG:32646). We use SeisSol, commit tagged 202103_Sumatra, available on GitHub at https://github.com/SeisSol/SeisSol. The procedure to download, compile and run SeisSol is described in its documentation (https://seissol.readthedocs.io). All data required to reproduce the tsunami scenarios can be downloaded from https://doi.org/10.5281/zenodo.5541510. We use the GeoClaw92,93, v5.8.0, available on GitHub at https://github.com/clawpack/geoclaw. Sea surface height anomalies derived from the Jason-1 data record are available at ftp://podaac-ftp.jpl.nasa.gov/allData/jason1/L2/j1_ssha/c109/.

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Acknowledgements

We thank L. Rannabauer, S. Vater and J. Kim for their support in setting up tsunami simulations. We thank S. Wollherr, C. Uphoff, M. Bader, S. Rettenberger, C. Pranger, T. Lay and J. Behrens for fruitful discussion. We thank M. Chlieh for providing his kinematic model of the Sumatra–Andaman event. We acknowledge funding from the Volkswagen Foundation (project ASCETE, grant no. 88479), the European Union’s Horizon 2020 research and innovation programme (ChEESE project, grant agreement no. 823844; TEAR ERC starting grant no. 852992), the German Research Foundation (DFG) (GA 2465/2-1, GA 2465/3-1), by KAUST-CRG (GAST, grant no. ORS-2016-CRG5-3027 and FRAGEN, grant no. ORS-2017-CRG6 3389.02), by KONWIHR—the Bavarian Competence Network for Technical and Scientific High Performance Computing (project NewWave), and by BayLat—the Bavarian University Centre for Latin America. Computing resources were provided by the Institute of Geophysics of LMU Munich109 and the Leibniz Supercomputing Centre (LRZ, projects no. pr63qo and pr45fi).

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Modelling was conducted by T.U. under the supervision of A.-A.G. A.-A.G. initiated the project. E.H.M. designed the splay faults model. The manuscript was written jointly by T.U., A.-A. G. and E.H.M.

Corresponding author

Correspondence to Thomas Ulrich.

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Nature Geoscience thanks Eric Dunham and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Stefan Lachowycz; Simon Harold.

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Extended data

Extended Data Table 1 Contribution of plastic moment to the total seismic moment in the base scenario and the two scenario designed with alternative visco-elastic parameters as shown in Fig. 1, yielding weaker or stronger sediments. M0,p: seismic moment due to off-fault plastic strain, Mw,p: seismic moment magnitude corresponding to M0,p, M0,e seismic moment due to slip on the fault, Mw,e: seismic moment magnitude corresponding to M0,e, M0,t = M0,e + M0,p: total seismic moment, Mw,t: total seismic moment magnitude

Extended Data Fig. 1 The importance of convergence-rate modulated regional driving stresses.

(a) Fault slip of the base scenario (left) and alternative scenario without regional along-arc prestress modulation (right). (b) Comparison of synthetic horizontal ground displacements (blue: scenario without along-arc prestress modulations, orange and magenta: geodetic observations). Note the different scaling applied in the far-field.

Extended Data Fig. 2 The importance of strongly depth-dependent rigidity.

(a) Fault slip and (b) rupture speed of the base scenario (left) and of the alternative dynamic rupture scenario based on a PREM model73, (right). Slip rates of the PREM model are provided as supplementary animation (Supplementary Video 2). (c) Synthetic moment rate release of the PREM earthquake scenario compared with the base scenario and observational inferences from teleseismic data. (d),(e) Comparison of synthetic horizontal (d) and vertical (e) ground displacements (blue: base scenario, orange and magenta: PREM scenario). Note the different scaling applied in the far-field.

Extended Data Fig. 3 Teleseismic waveforms.

(a) Comparison of synthetic (red and blue) and observed (black) teleseismic waveforms. Red waveforms are computed using the base scenario, while blue waveforms correspond to the model featuring less off-fault yielding and more slip to the trench, yet, indistinguishable synthetics, shown in Fig. 4. A 150-500 s band-pass filter is applied to all traces. Synthetics are generated using Instaseis103 and the PREM model including anisotropic effects and a maximum period of 10 s. (b) Locations at which synthetic data are compared with observed records.

Extended Data Fig. 4 Comparison of synthetic ground displacements in the base scenario and geodetic observations.

Synthetics are shown in blue, geodetic observations in orange and magenta. In the far-field a different scaling is applied. (a) Horizontal ground displacements. (b) Vertical ground displacements. The complete uplift and subsidence resulting from the dynamic rupture scenario (in m) is shown in red to blue including noticeable splay faulting signatures.

Extended Data Fig. 5 Fault slip and tsunami induced sea surface height anomalies of the stronger sediments scenario compared to a fully elastic scenario.

(a) Fault slip. Note that the color scale saturates for the fully-elastic scenario which has a maximum fault slip of 52 m near the trench. (b) Sea surface height anomaly (blue, ssha (m)), recorded by the Jason-1 satellite about 2 hours after the mainshock compared with tsunami synthetics dynamically sourced by the base (black), stronger sediments (orange), and fully-elastic (green) scenario.

Extended Data Fig. 6 Comparison of synthetic ground displacements in the base scenario and in the two scenarios with alternative visco-elastic parameters shown in Fig. 4, yielding weaker or stronger sediments.

A different scaling is applied to highlight smaller scale distant ground displacements. In all panels, blue is the preferred scenario and orange (or magenta, depending on the scaling) is either the scenario with stronger (a, b) or weaker (c, d) sediments. (a,c): horizontal displacements. (b,d): vertical displacements. The distribution of vertical surface displacements of the scenario with stronger sediments is shown in red to blue in (b), and with weaker sediments in (d). Note the saturated color scale, synthetic vertical displacements range between -4.7 m and 12.4 m (-9.3 m and 14.4 m, respectively) for the scenario with stronger (weaker, respectively) sediments.

Extended Data Fig. 7 Sensitivity of rupture speed and moment rate release with respect to the strength of near-fault sediments.

(a),(b) Along arc-variation of rupture velocity of two scenarios yielding stronger (a) or weaker (b) sediments compared to observational inferences from Rayleigh48 and acoustic waves49. (c) Comparison of moment rate release of the base scenario, two scenarios yielding weaker or stronger sediments and observational inferences from teleseismics17,47.

Extended Data Fig. 8 Off fault plasticity.

(a) Depth dependence of bulk cohesion C(z) (Eq. 6, blue) and of the failure criterion CF (Eq. 7, warm colors) at four locations along the trench (from south to north, the curves are colored in gold, orange, brown and black). Different line styles refer to different scenarios. (b) and (c) Off-fault plastic strain (quantified as η, Eq. 10) accumulated in the base and 2 alternative earthquake scenarios with differing visco-elastic characteristics yielding stronger or weaker sediments. We use a linear scale, cut off at η > 10−5. The red line is the vertical seafloor uplift (not to scale, amplified × 200). The locations of the southern (b) and northern (c) cross-sections are illustrated beneath. The distribution of η across the central rupture region is shown in the main text Fig. 4a.

Extended Data Fig. 9 Ratio of initial shear stress τ over effective normal stress \({\sigma }_{{{{\rm{n}}}}}^{\prime}\).

(a) \(\tau /{\sigma }_{{{{\rm{n}}}}}^{\prime}\) distribution plotted with a colormap covering the whole range of variation of \(\tau /{\sigma }_{{{{\rm{n}}}}}^{\prime}\). (b) \(\tau /{\sigma }_{{{{\rm{n}}}}}^{\prime}\) distribution plotted over a much narrower colourmap range, highlighting the (limited) variation of \({\tau/\sigma}^\prime_{\mathrm{n}}\) across the earthquake rupture area.

Supplementary information

Supplementary Information

Supplementary Information, Table 1, Fig. 1 and references.

Supplementary Video 1

Animation showing the rupture dynamics of three earthquake scenarios discussed in terms of absolute slip rate (m s–1) across the fault network, side by side (left: base; middle: stronger sediments; right: weaker sediments scenario).

Supplementary Video 2

Animation showing the rupture dynamics of the base and PREM earthquake scenarios in terms of absolute slip rate (m s–1) across the fault network, side by side (left: base; right: PREM scenario).

Supplementary Video 3

Animation showing the rupture dynamics of the base scenario in terms of absolute slip rate (m s–1) across the fault network.

Supplementary Video 4

Animation showing the rupture dynamics of the stronger sediments scenario in terms of absolute slip rate (m s–1) across the fault network.

Supplementary Video 5

Animation showing the rupture dynamics of the weaker sediments scenario in terms of absolute slip rate (m s–1) across the fault network.

Supplementary Video 6

Animation of the tsunami scenario associated with the base earthquake scenario. The tsunami animations show the predicted evolution of the sea surface height amplitudes (in metres).

Supplementary Video 7

Animation of the tsunami scenario associated with the stronger sediments earthquake scenario. The tsunami animations show the predicted evolution of the sea surface height amplitudes (in metres).

Supplementary Video 8

Animation of the tsunami scenario associated with the weaker sediments earthquake scenario. The tsunami animations show the predicted evolution of the sea surface height amplitudes (in metres).

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Ulrich, T., Gabriel, AA. & Madden, E.H. Stress, rigidity and sediment strength control megathrust earthquake and tsunami dynamics. Nat. Geosci. 15, 67–73 (2022). https://doi.org/10.1038/s41561-021-00863-5

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