Stress, rigidity and sediment strength control megathrust earthquake and tsunami dynamics
Type
PreprintKAUST Grant Number
ORS-2016-CRG5-3027ORS-2017-CRG6 3389.02
Date
2020-07-31Permanent link to this record
http://hdl.handle.net/10754/664654
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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 show that tsunamigenesis 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 modeling 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. Our findings highlight the importance of regional-scale structural heterogeneity to decipher megathrust hazards.Citation
Ulrich, T., Gabriel, A.-A., & Madden, E. (2020). Stress, rigidity and sediment strength control megathrust earthquake and tsunami dynamics. doi:10.31219/osf.io/9kdhbSponsors
The authors 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) (projects KA 2281/4-1, 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 Munich (69) and the Leibniz Supercomputing Centre (LRZ, projects no. h019z, pr63qo, and pr45fi).Publisher
Center for Open ScienceAdditional Links
https://osf.io/9kdhbae974a485f413a2113503eed53cd6c53
10.31219/osf.io/9kdhb
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