Performance of Slab Geometry Constraints on Rapid Geodetic Slip Models, Tsunami Amplitude, and Inundation Estimates in Cascadia

Authors

  • Kevin Kwong University of Washington, Department of Earth and Space Sciences, Seattle, Washington, USA; California State Polytechnic University,Pomona, Geological Sciences Department, Pomona, CA, USA
  • Brendan Crowell The Ohio State University, School of Earth Sciences, Columbus, Ohio, USA https://orcid.org/0000-0001-7096-601X
  • Amy Williamson Berkeley Seismology Laboratory, University of California, Berkeley, California, USA https://orcid.org/0000-0003-1481-725X
  • Diego Melgar University of Oregon, Department of Earth Sciences,Eugene, Oregon, USA; Cascadia Region Earthquake Science Center, Eugene, Oregon, USA
  • Yong Wei University of Washington, Cooperative Institute forClimate, Ocean, & Ecosystem Studies, Seattle, Washington, USA; NOAA/Pacific Marine Environmental Lab, Seattle, WA, USA https://orcid.org/0000-0002-6908-1342

DOI:

https://doi.org/10.26443/seismica.v2i4.1406

Abstract

Tsunamigenic megathrust earthquakes along the Cascadia subduction zone present a major hazard concern. We can better prepare to model the earthquake source in a rapid manner by imbuing fault geometry constraints based on prior knowledge and by evaluating the capabilities of using existing GNSS sensors. Near-field GNSS waveforms have shown promise in providing rapid coarse finite-fault model approximations of the earthquake rupture that can improve tsunami modeling and response time. In this study, we explore the performance of GNSS derived finite-fault inversions and tsunami forecasting predictions in Cascadia that highlights the impact and potential of geodetic techniques and data in operational earthquake and tsunami monitoring. We utilized 1300 Cascadia earthquake simulations (FakeQuakes) that provide realistic (M7.5-9.3) rupture scenarios to assess how feasibly finite-fault models can be obtained in a rapid earthquake early warning and tsunami response context. A series of fault models with rectangular dislocation patches spanning the Cascadia megathrust area is added to the GFAST inversion algorithm to calculate slip for each earthquake scenario. Another method used to constrain the finite-fault geometry is from the GNSS-derived CMT fault plane solution. For the Cascadia region, we show that fault discretization using two rectangular segments approximating the megathrust portion of the subduction zone leads to improvements in modeling magnitude, fault slip, tsunami amplitude, and inundation. In relation to tsunami forecasting capabilities, we compare coastal amplitude predictions spanning from Vancouver Island (Canada) to Northern California (USA). Generally, the coastal amplitudes derived using fault parameters from the CMT solutions show an overestimation bias compared to amplitudes derived from the fixed slab model. We also see improved prediction values of the run-up height and maximum amplitude at 10 tide gauge stations using the fixed slab model as well.

References

Allen, R. M., & Ziv, A. (2011). Application of real-time GPS to earthquake early warning. Geophysical Research Letters, 38(16). https://doi.org/https://doi.org/10.1029/2011GL047947

An, C., Sepúlveda, I., & Liu, P. L.-F. (2014). Tsunami source and its validation of the 2014 Iquique, Chile, earthquake. Geophysical Research Letters, 41(11), 3988–3994. https://doi.org/https://doi.org/10.1002/2014GL060567

Barnhart, W. D., & Lohman, R. B. (2010). Automated fault model discretization for inversions for coseismic slip distributions. Journal of Geophysical Research: Solid Earth, 115(B10). https://doi.org/https://doi.org/10.1029/2010JB007545

Berger, M. J., George, D. L., LeVeque, R. J., & Mandli, K. T. (2011). The GeoClaw software for depth-averaged flows with adaptive refinement. Advances in Water Resources, 34(9), 1195–1206. https://doi.org/https://doi.org/10.1016/j.advwatres.2011.02.016

Bird, P. (2003). An updated digital model of plate boundaries. Geochemistry, Geophysics, Geosystems, 4(3). https://doi.org/https://doi.org/10.1029/2001GC000252

Blaser, L., Krüger, F., Ohrnberger, M., & Scherbaum, F. (2010). Scaling Relations of Earthquake Source Parameter Estimates with Special Focus on Subduction Environment. Bulletin of the Seismological Society of America, 100(6), 2914–2926. https://doi.org/10.1785/0120100111

Blewitt, G., Kreemer, C., Hammond, W. C., Plag, H.-P., Stein, S., & Okal, E. (2006). Rapid determination of earthquake magnitude using GPS for tsunami warning systems. Geophysical Research Letters, 33(11). https://doi.org/https://doi.org/10.1029/2006GL026145

Brudzinski, M. R., & Allen, R. M. (2007). Segmentation in episodic tremor and slip all along Cascadia. Geology, 35(10), 907–910. https://doi.org/10.1130/G23740A.1

Colombelli, S., Allen, R. M., & Zollo, A. (2013). Application of real-time GPS to earthquake early warning in subduction and strike-slip environments. Journal of Geophysical Research: Solid Earth, 118(7), 3448–3461. https://doi.org/https://doi.org/10.1002/jgrb.50242

Crempien, J. G., Urrutia, A., Benavente, R., & Cienfuegos, R. (2020). Effects of earthquake spatial slip correlation on variability of tsunami potential energy and intensities. Scientific Reports, 10(1), 8399. https://doi.org/https://doi.org/10.1038/s41598-020-65412-3

Crowell, B. W., Bock, Y., & Melgar, D. (2012). Real-time inversion of GPS data for finite fault modeling and rapid hazard assessment. Geophysical Research Letters, 39(9). https://doi.org/https://doi.org/10.1029/2012GL051318

Crowell, B. W., Schmidt, D. A., Bodin, P., Vidale, J. E., Gomberg, J., Renate Hartog, J., Kress, V. C., Melbourne, T. I., Santillan, M., Minson, S. E., & others. (2016). Demonstration of the Cascadia G-FAST geodetic earthquake early warning system for the Nisqually, Washington, earthquake. Seismological Research Letters, 87(4), 930–943. https://doi.org/https://doi.org/10.1785/0220150255

González, F., LeVeque, R., Varkovitzky, J., Chamberlain, P., Hirai, B., & George, D. (2011). GeoClaw results for the NTHMP tsunami benchmark problems. Results of the 2011 NTHMP Model Benchmarking Workshop.

Grapenthin, R., Johanson, I. A., & Allen, R. M. (2014). Operational real-time GPS-enhanced earthquake early warning. Journal of Geophysical Research: Solid Earth, 119(10), 7944–7965. https://doi.org/https://doi.org/10.1002/2014JB011400

Grapenthin, Ronni, West, M., & Freymueller, J. (2017). The Utility of GNSS for Earthquake Early Warning in Regions with Sparse Seismic Networks. Bulletin of the Seismological Society of America, 107(4), 1883–1890. https://doi.org/10.1785/0120160317

Hayes, G. P., Moore, G. L., Portner, D. E., Hearne, M., Flamme, H., Furtney, M., & Gregory M. Smoczyk. (2018). Slab2, a comprehensive subduction zone geometry model. Science, 362(6410), 58–61. https://doi.org/10.1126/science.aat4723

Hayes, G. P., Rivera, L., & Kanamori, H. (2009). Source Inversion of the W-Phase: Real-time Implementation and Extension to Low Magnitudes. Seismological Research Letters, 80(5), 817–822. https://doi.org/10.1785/gssrl.80.5.817

Hayes, G. P., Wald, D. J., & Johnson, R. L. (2012). Slab1.0: A three-dimensional model of global subduction zone geometries. Journal of Geophysical Research: Solid Earth, 117(B1). https://doi.org/https://doi.org/10.1029/2011JB008524

Hoshiba, M., & Ozaki, T. (2014). Earthquake Early Warning and Tsunami Warning of the Japan Meteorological Agency, and Their Performance in the 2011 off the Pacific Coast of Tohoku Earthquake (Mw 9.0). In F. Wenzel & J. Zschau (Eds.), Early Warning for Geological Disasters: Scientific Methods and Current Practice (pp. 1–28). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-12233-0_1

Kanamori, H. (1993). W phase. Geophysical Research Letters, 20(16), 1691–1694. https://doi.org/https://doi.org/10.1029/93GL01883

Kawamoto, S., Hiyama, Y., Ohta, Y., & Nishimura, T. (2016). First result from the GEONET real-time analysis system (REGARD): the case of the 2016 Kumamoto earthquakes. Earth, Planets and Space, 68, 1–12. https://doi.org/https://doi.org/10.1186/s40623-016-0564-4

LeVeque, R. J., Waagan, K., González, F. I., Rim, D., & Lin, G. (2017). Generating Random Earthquake Events for Probabilistic Tsunami Hazard Assessment. In E. L. Geist, H. M. Fritz, A. B. Rabinovich, & Y. Tanioka (Eds.), Global Tsunami Science: Past and Future, Volume I (pp. 3671–3692). Springer International Publishing. https://doi.org/10.1007/978-3-319-55480-8_2

Lynett, P. J., Gately, K., Wilson, R., Montoya, L., Arcas, D., Aytore, B., Bai, Y., Bricker, J. D., Castro, M. J., Cheung, K. F., David, C. G., Dogan, G. G., Escalante, C., González-Vida, J. M., Grilli, S. T., Heitmann, T. W., Horrillo, J., Kânoğlu, U., Kian, R., … Zhang, Y. J. (2017). Inter-model analysis of tsunami-induced coastal currents. Ocean Modelling, 114, 14–32. https://doi.org/https://doi.org/10.1016/j.ocemod.2017.04.003

Melgar, D., Crowell, B. W., Bock, Y., & Haase, J. S. (2013). Rapid modeling of the 2011 Mw 9.0 Tohoku-oki earthquake with seismogeodesy. Geophysical Research Letters, 40(12), 2963–2968. https://doi.org/https://doi.org/10.1002/grl.50590

Melgar, D., Crowell, B. W., Geng, J., Allen, R. M., Bock, Y., Riquelme, S., Hill, E. M., Protti, M., & Ganas, A. (2015). Earthquake magnitude calculation without saturation from the scaling of peak ground displacement. Geophysical Research Letters, 42(13), 5197–5205. https://doi.org/https://doi.org/10.1002/2015GL064278

Melgar, D., LeVeque, R. J., Dreger, D. S., & Allen, R. M. (2016). Kinematic rupture scenarios and synthetic displacement data: An example application to the Cascadia subduction zone. Journal of Geophysical Research: Solid Earth, 121(9), 6658–6674. https://doi.org/https://doi.org/10.1002/2016JB013314

Melgar, D., Melbourne, T. I., Crowell, B. W., Geng, J., Szeliga, W., Scrivner, C., Santillan, M., & Goldberg, D. E. (2019). Real‐Time High‐Rate GNSS Displacements: Performance Demonstration during the 2019 Ridgecrest, California, Earthquakes. Seismological Research Letters, 91(4), 1943–1951. https://doi.org/10.1785/0220190223

Minson, S. E., Murray, J. R., Langbein, J. O., & Gomberg, J. S. (2014). Real-time inversions for finite fault slip models and rupture geometry based on high-rate GPS data. Journal of Geophysical Research: Solid Earth, 119(4), 3201–3231. https://doi.org/https://doi.org/10.1002/2013JB010622

Murray, J. R., Crowell, B. W., Grapenthin, R., Hodgkinson, K., Langbein, J. O., Melbourne, T., Melgar, D., Minson, S. E., & Schmidt, D. A. (2018). Development of a geodetic component for the US West Coast earthquake early warning system. Seismological Research Letters, 89(6), 2322–2336. https://doi.org/https://doi.org/10.1785/0220180162

Murray, J. R., Crowell, B. W., Murray, M. H., Ulberg, C. W., McGuire, J. J., Aranha, M. A., & Hagerty, M. T. (2023). Incorporation of Real‐Time Earthquake Magnitudes Estimated via Peak Ground Displacement Scaling in the ShakeAlert Earthquake Early Warning System. Bulletin of the Seismological Society of America, 113(3), 1286–1310. https://doi.org/10.1785/0120220181

Nuyen, C. P., & Schmidt, D. A. (2021). Filling the Gap in Cascadia: The Emergence of Low-Amplitude Long-Term Slow Slip. Geochemistry, Geophysics, Geosystems, 22(3), e2020GC009477. https://doi.org/https://doi.org/10.1029/2020GC009477

Okada, Y. (1985). Surface deformation due to shear and tensile faults in a half-space. Bulletin of the Seismological Society of America, 75(4), 1135–1154. https://doi.org/https://doi.org/10.1785/BSSA0750041135

Peters, R., Jaffe, B., & Gelfenbaum, G. (2007). Distribution and sedimentary characteristics of tsunami deposits along the Cascadia margin of western North America. Sedimentary Geology, 200(3), 372–386. https://doi.org/https://doi.org/10.1016/j.sedgeo.2007.01.015

Satake, K., Wang, K., & Atwater, B. F. (2003). Fault slip and seismic moment of the 1700 Cascadia earthquake inferred from Japanese tsunami descriptions. Journal of Geophysical Research: Solid Earth, 108(B11). https://doi.org/https://doi.org/10.1029/2003JB002521

Synolakis, C. E., Bernard, E. N., Titov, V. V., Kânoğlu, U., & González, F. I. (2009). Validation and Verification of Tsunami Numerical Models. In P. R. Cummins, K. Satake, & L. S. L. Kong (Eds.), Tsunami Science Four Years after the 2004 Indian Ocean Tsunami: Part I: Modelling and Hazard Assessment (pp. 2197–2228). Birkhäuser Basel. https://doi.org/10.1007/978-3-0346-0057-6_11

Tang, L., Titov, V. V., & Chamberlin, C. D. (2009). Development, testing, and applications of site-specific tsunami inundation models for real-time forecasting. Journal of Geophysical Research: Oceans, 114(C12). https://doi.org/https://doi.org/10.1029/2009JC005476

Titov, V., Kânoğlu, U., & Costas Synolakis. (2016). Development of MOST for Real-Time Tsunami Forecasting. Journal of Waterway, Port, Coastal, and Ocean Engineering, 142(6), 03116004. https://doi.org/10.1061/(ASCE)WW.1943-5460.0000357

Wei, Y., Bernard, E. N., Tang, L., Weiss, R., Titov, V. V., Moore, C., Spillane, M., Hopkins, M., & Kânoğlu, U. (2008). Real-time experimental forecast of the Peruvian tsunami of August 2007 for U.S. coastlines. Geophysical Research Letters, 35(4). https://doi.org/https://doi.org/10.1029/2007GL032250

Williamson, A. L., Melgar, D., Crowell, B. W., Arcas, D., Melbourne, T. I., Wei, Y., & Kwong, K. (2020). Toward Near-Field Tsunami Forecasting Along the Cascadia Subduction Zone Using Rapid GNSS Source Models. Journal of Geophysical Research: Solid Earth, 125(8), e2020JB019636. https://doi.org/https://doi.org/10.1029/2020JB019636

Wright, T. J., Houlié, N., Hildyard, M., & Iwabuchi, T. (2012). Real-time, reliable magnitudes for large earthquakes from 1 Hz GPS precise point positioning: The 2011 Tohoku-Oki (Japan) earthquake. Geophysical Research Letters, 39(12). https://doi.org/https://doi.org/10.1029/2012GL051894

Published

2025-02-13

How to Cite

Kwong, K., Crowell, B., Williamson, A., Melgar, D., & Wei, Y. (2025). Performance of Slab Geometry Constraints on Rapid Geodetic Slip Models, Tsunami Amplitude, and Inundation Estimates in Cascadia. Seismica, 2(4). https://doi.org/10.26443/seismica.v2i4.1406

Issue

Section

Special Issue: the Cascadia Subduction Zone