Earthquake Report: M 7.4 Japan

A couple weeks ago there was a sequence of earthquakes offshore of the east coast of Japan.

https://earthquake.usgs.gov/earthquakes/eventpage/us6000sri7/executive

This 4/20 magnitude M 7.4 earthquake occurred in the aftershock region from the 2011 Great East Japan M 9.0 earthquake.

The 7.4 earthquake has a thrust earthquake mechanism. This, combined with the depth, places this earthquake on the megathrust subduction zone earthquake fault.

There was a cluster of earthquake aftershocks near the mainshock and there was a cluster of seismicity to the northwest of this main cluster. It is probable that they are related given the closeness in time and space.

In December 2025 there was an M 7.6 earthquake in the region of the seismicity cluster to the northwest. So this northwest cluster represents aftershocks from that slip patch. It is possible that this 7.6 sequence (and the 2011 earthquake) increased the stress on the fault where the 20 April 2026 M 7.4 earthquake happened (?).

We also observed a small tsunami on tide gages in Japan.

The Japanese government put the nation into an aftershock advisory, suggesting that people be aware that there may be a large aftershock (or that this 7.4 was a foreshock to a much larger earthquake).

This advisory system was created in response to a M~7 foreshock to the 2011 M 9.0 mainshock. There is generally a 5% chance that any given earthquake may be followed by a larger magnitude earthquake.

It is smart to have people with a heightened awareness following these large earthquakes. For example, it might be prudent to postpone a sailboat regatta.

If one is in a small sailboat about 1 kilometer from the beach and a large subduction zone earthquake happens, one has a difficult choice to make. Do they move further out to sea or do they attempt to get to land? There really is not enough time to do either.

Going offshore, one needs to get to a safe water depth. Typically, this depth is tens of kilometers offshore.

Going onshore, one needs to get to the beach, then get out of the boat, then get to high ground.

If this person is directly overlying the subduction zone, a tsunami may reach the coast within 10-15 minutes (possibly during the earthquake).

It is probably not possible to travel 1-km to the beach, then walk uphill to high ground, before the tsunami arrives.

Better yet, postpone the sailboat regatta and avoid the tsunami hazard.

Below is my interpretive poster for this earthquake

  • I plot the seismicity from the past month, with diameter representing magnitude (see legend). I include earthquake epicenters from 1926-2026 with magnitudes M ≥ 7.0 in one version.
  • I plot the USGS fault plane solutions (moment tensors in blue and focal mechanisms in orange), possibly in addition to some relevant historic earthquakes.
  • A review of the basic base map variations and data that I use for the interpretive posters can be found on the Earthquake Reports page. I have improved these posters over time and some of this background information applies to the older posters.
  • Some basic fundamentals of earthquake geology and plate tectonics can be found on the Earthquake Plate Tectonic Fundamentals page.

    I include some inset figures. Some of the same figures are located in different places on the larger scale map below.

  • Here is the map with a month’s seismicity plotted.

Tsunami

Tsunami can be caused by a variety of processes, including earthquakes, volcanic eruptions, landslides, and meteorological phenomena. Earthquakes, eruptions, and landslides cause tsunami when these processes displace water in some way. We may typically associate tsunami with subduction zone earthquakes because these earthquakes are the type that generate vertical land motion along the sea floor.

  • Here is a great illustration of how a subduction zone earthquake can generate a tsunami (Atwater et al., 2005).


We think that the earthquake slipped at least 50 meters (165 feet) during several minutes. This is the largest coseismic measurement of any subduction zone earthquake (so far).

When the fault slipped, it caused the seafloor to deform and move. This motion also displaced the overlying water column.

As the water column is elevated, it gains potential energy. As this uplifted water expends this energy by oscillating up and down, it radiates energy in the form of tsunami waves.

Tsunami were observed across the entire Pacific Basin, causing extensive damage and casualties in Japan, but also in other places too. There was about $100 million damage to coastal infrastructure in California alone.

This is an animated model of the Great East Japan tsunami of ten years ago. The warmer the colors, the larger the wave. The first surges reached the closest Japan coasts in about 25 minutes. The first surges reached Crescent City in 9.5 hours. (modified text from Dr. Lori Dengler)

    Here are the tide gage data from Ofunato, Japan.

    Time is represented by the horizontal axis and elevation is represented on the vertical axis. The darker blue line in this image represents NOAA’s tidal forecast. The data recorded by the tide gage are represented by the light blue colored lines. Wave height is the distance measured between the wave crest and trough. Wave amplitude is the level of water above sea level.

    These data came from the European Union sea level monitoring website.

    Additional data are available from the IOC sea level monitoring website.


Other Report Pages

Shaking Intensity

  • Here is a figure that shows a more detailed comparison between the modeled intensity and the reported intensity. Both data use the same color scale, the Modified Mercalli Intensity Scale (MMI). More about this can be found here. The colors and contours on the map are results from the USGS modeled intensity. The DYFI data are plotted as colored dots (color = MMI, diameter = number of reports).
  • In the upper panel is the USGS Did You Feel It reports map, showing reports as colored dots using the MMI color scale. Underlain on this map are colored areas showing the USGS modeled estimate for shaking intensity (MMI scale).
  • In the lower panel is a plot showing MMI intensity (vertical axis) relative to distance from the earthquake (horizontal axis). The models are represented by the green and orange lines. The DYFI data are plotted as light blue dots. The mean and median (different types of “average”) are plotted as orange and purple dots. Note how well the reports fit the green line (the model that represents how MMI works based on quakes in California).
  • Below the map and the lower plot is the USGS MMI Intensity scale, which lists the level of damage for each level of intensity, along with approximate measures of how strongly the ground shakes at these intensities, showing levels in acceleration (Peak Ground Acceleration, PGA) and velocity (Peak Ground Velocity, PGV).


Potential for Ground Failure

  • Below are a series of maps that show the potential for landslides and liquefaction. These are all USGS data products.
    There are many different ways in which a landslide can be triggered. The first order relations behind slope failure (landslides) is that the “resisting” forces that are preventing slope failure (e.g. the strength of the bedrock or soil) are overcome by the “driving” forces that are pushing this land downwards (e.g. gravity). The ratio of resisting forces to driving forces is called the Factor of Safety (FOS). We can write this ratio like this:

    FOS = Resisting Force / Driving Force

  • When FOS > 1, the slope is stable and when FOS < 1, the slope fails and we get a landslide. The illustration below shows these relations. Note how the slope angle α can take part in this ratio (the steeper the slope, the greater impact of the mass of the slope can contribute to driving forces). The real world is more complicated than the simplified illustration below.


  • Landslide ground shaking can change the Factor of Safety in several ways that might increase the driving force or decrease the resisting force. Keefer (1984) studied a global data set of earthquake triggered landslides and found that larger earthquakes trigger larger and more numerous landslides across a larger area than do smaller earthquakes. Earthquakes can cause landslides because the seismic waves can cause the driving force to increase (the earthquake motions can “push” the land downwards), leading to a landslide. In addition, ground shaking can change the strength of these earth materials (a form of resisting force) with a process called liquefaction.
  • Sediment or soil strength is based upon the ability for sediment particles to push against each other without moving. This is a combination of friction and the forces exerted between these particles. This is loosely what we call the “angle of internal friction.” Liquefaction is a process by which pore pressure increases cause water to push out against the sediment particles so that they are no longer touching.
  • An analogy that some may be familiar with relates to a visit to the beach. When one is walking on the wet sand near the shoreline, the sand may hold the weight of our body generally pretty well. However, if we stop and vibrate our feet back and forth, this causes pore pressure to increase and we sink into the sand as the sand liquefies. Or, at least our feet sink into the sand.
  • Below is a diagram showing how an increase in pore pressure can push against the sediment particles so that they are not touching any more. This allows the particles to move around and this is why our feet sink in the sand in the analogy above. This is also what changes the strength of earth materials such that a landslide can be triggered.


  • Here Dr. Bohon demonstrates the phenomena of liquefaction.
    • @drwendyrocksit #Liquefaction is a process by which water-saturated sediment temporarily loses strength and acts as a fluid. This can happen during #earthquake shaking. #geophysics #geology ♬ Quicksand – Hatchie

  • And, another video demonstration.

  • Below is a diagram based upon a publication designed to educate the public about landslides and the processes that trigger them (USGS, 2004). Additional background information about landslide types can be found in Highland et al. (2008). There was a variety of landslide types that can be observed surrounding the earthquake region. So, this illustration can help people when they observing the landscape response to the earthquake whether they are using aerial imagery, photos in newspaper or website articles, or videos on social media. Will you be able to locate a landslide scarp or the toe of a landslide? This figure shows a rotational landslide, one where the land rotates along a curvilinear failure surface.


  • Below is the liquefaction susceptibility and landslide probability map (Jessee et al., 2017; Zhu et al., 2017). Please head over to that report for more information about the USGS Ground Failure products (landslides and liquefaction). Basically, earthquakes shake the ground and this ground shaking can cause landslides.
  • I use the same color scheme that the USGS uses on their website. Note how the areas that are more likely to have experienced earthquake induced liquefaction are in the valleys. Learn more about how the USGS prepares these model results here.


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Some Relevant Discussion and Figures

    Social Media

    References:

    Basic & General References

  • Frisch, W., Meschede, M., Blakey, R., 2011. Plate Tectonics, Springer-Verlag, London, 213 pp.
  • Hayes, G., 2018, Slab2 – A Comprehensive Subduction Zone Geometry Model: U.S. Geological Survey data release, https://doi.org/10.5066/F7PV6JNV.
  • Holt, W. E., C. Kreemer, A. J. Haines, L. Estey, C. Meertens, G. Blewitt, and D. Lavallee (2005), Project helps constrain continental dynamics and seismic hazards, Eos Trans. AGU, 86(41), 383–387, , https://doi.org/10.1029/2005EO410002. /li>
  • Jessee, M.A.N., Hamburger, M. W., Allstadt, K., Wald, D. J., Robeson, S. M., Tanyas, H., et al. (2018). A global empirical model for near-real-time assessment of seismically induced landslides. Journal of Geophysical Research: Earth Surface, 123, 1835–1859. https://doi.org/10.1029/2017JF004494
  • Kreemer, C., J. Haines, W. Holt, G. Blewitt, and D. Lavallee (2000), On the determination of a global strain rate model, Geophys. J. Int., 52(10), 765–770.
  • Kreemer, C., W. E. Holt, and A. J. Haines (2003), An integrated global model of present-day plate motions and plate boundary deformation, Geophys. J. Int., 154(1), 8–34, , https://doi.org/10.1046/j.1365-246X.2003.01917.x.
  • Kreemer, C., G. Blewitt, E.C. Klein, 2014. A geodetic plate motion and Global Strain Rate Model in Geochemistry, Geophysics, Geosystems, v. 15, p. 3849-3889, https://doi.org/10.1002/2014GC005407.
  • Meyer, B., Saltus, R., Chulliat, a., 2017. EMAG2: Earth Magnetic Anomaly Grid (2-arc-minute resolution) Version 3. National Centers for Environmental Information, NOAA. Model. https://doi.org/10.7289/V5H70CVX
  • Müller, R.D., Sdrolias, M., Gaina, C. and Roest, W.R., 2008, Age spreading rates and spreading asymmetry of the world’s ocean crust in Geochemistry, Geophysics, Geosystems, 9, Q04006, https://doi.org/10.1029/2007GC001743
  • Pagani,M. , J. Garcia-Pelaez, R. Gee, K. Johnson, V. Poggi, R. Styron, G. Weatherill, M. Simionato, D. Viganò, L. Danciu, D. Monelli (2018). Global Earthquake Model (GEM) Seismic Hazard Map (version 2018.1 – December 2018), DOI: 10.13117/GEM-GLOBAL-SEISMIC-HAZARD-MAP-2018.1
  • Silva, V ., D Amo-Oduro, A Calderon, J Dabbeek, V Despotaki, L Martins, A Rao, M Simionato, D Viganò, C Yepes, A Acevedo, N Horspool, H Crowley, K Jaiswal, M Journeay, M Pittore, 2018. Global Earthquake Model (GEM) Seismic Risk Map (version 2018.1). https://doi.org/10.13117/GEM-GLOBAL-SEISMIC-RISK-MAP-2018.1
  • Storchak, D. A., D. Di Giacomo, I. Bondár, E. R. Engdahl, J. Harris, W. H. K. Lee, A. Villaseñor, and P. Bormann (2013), Public release of the ISC-GEM global instrumental earthquake catalogue (1900–2009), Seismol. Res. Lett., 84(5), 810–815, doi:10.1785/0220130034.
  • Zhu, J., Baise, L. G., Thompson, E. M., 2017, An Updated Geospatial Liquefaction Model for Global Application, Bulletin of the Seismological Society of America, 107, p 1365-1385, https://doi.org/0.1785/0120160198

    • Specific References

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