• The first three layers of modeling are used to determine the long-term, or Time Independent, estimates of the magnitude, location, and frequency of potentially damaging earthquakes
  in California.

• In balancing these various factors it also provides an estimate of how much seismicity is not accounted for in the fault model, possibly in faults not yet discovered.

• For example, there is difficulty fitting paleoseismic data and slip rates on the southern San Andreas Fault, resulting in estimates of seismicity that run about 25% less than
  seen in the paleoseismic data.

• The largest increase in such likelihood is on the Calaveras fault (see main faults map for location), where the mean (most likely) value is now set at 25%.

• The probability model estimates how close (ready) each fault segment is to rupturing given how much stress has accumulated since its last rupture.

• [37] There are a number of sources of uncertainty, such as insufficient knowledge of fault geometry (especially at depth) and slip rates,[38] and there is considerable challenge
  in how to balance the various elements of the model to achieve the best fit with the available observations.

• C21 from Appendix C.[28] Plots of slip rates on two parallel faults (the San Andreas and the San Jacinto) as determined by three deformation models, and a “geologic” model
  based entirely on observed slip rates, showing variations along each segment.

• [39] An important result is that the generally accepted Gutenberg-Richter (GR) relationship (that the distribution of earthquakes shows a certain relationship between magnitude
  and frequency) is inconsistent with certain parts of the current UCERF3 model.

• Deformation models determine the slip rates and related factors for each fault section, how much strain accumulates before a fault ruptures, and how much energy is then released.

• [34] There are a number of assumptions in the Time Independent model,[35] while the final (Time Dependent) model explicitly “assumes elastic rebound dominates other known
  and suspected processes that are not included in the model.

• Combining this with ground motion models produces estimates of the severity of ground shaking that can be expected during a given period (seismic hazard), and of the threat
  to the built environment (seismic risk).

• [23] The various alternatives (see diagram), taken in different combinations, form a logic tree of 1440 branches for the Time Independent model, and, when the four probability
  models are factored in, 5760 branches for the Time Dependent model.

• [30] The result is a model (set of values) that best fits the available data.

• [31] Assessment While UCERF3 represents a considerable improvement over UCERF2,[32] and the best available science to-date for estimating California’s earthquake hazard,[33]
  the authors caution that it remains an approximation of the natural system.

• The data does fit if a certain constraint (the regional Magnitude-Frequency Distribution) is relaxed, but this brings back the problem over-predicting moderate events.

• [6] The rate of earthquakes of magnitude (M[7]) 6.7 and greater (over the entire state) is now believed to be about one in 6.3 years, instead of one in 4.8 years.

• The fault model database has been revised and expanded to cover over 350 fault sections, up from about 200 for UCERF2, and new attributes added to better characterize the
  faults.

• The previous under-estimate is believed to be due mostly to not modeling multifault ruptures, which limited the size of many ruptures.

• In theory, this should produce some regularity in the earthquakes on a given fault, and knowing the date of the last rupture is a clue to how soon the next one can be expected.

• This compares to less than 8,000 ruptures considered in UCERF2, and reflects the high connectivity of California’s fault system.

• The Time Dependent model is based on the theory of elastic rebound, that after an earthquake releases tectonic stress there will be some time before sufficient stress accumulates
  to cause another earthquake.

• In practice this is not so clear, in part because slip rates vary, and also because fault segments influence each other, so a rupture on one segment triggers rupturing on
  adjacent segments.

• [4] Highlights A major achievement of UCERF3 is use of a new methodology that can model multifault ruptures such as have been observed in recent earthquakes.

 

Works Cited

[‘Field et al. 2013, p. 2.
2. ^ For a list of evaluation metrics available as of 2013 see Table 11 in Field et al. 2013, p. 52.
3. ^ Following standard seismological practice, all earthquake magnitudes here are per the moment magnitude scale. This
is generally equivalent to the better known Richter magnitude scale.
4. ^ Field et al. 2013, p. 2.
5. ^ Field et al. 2015, p. 512.
6. ^ Field 2015, pp. 2–3.
7. ^ Unless otherwise noted, all earthquake magnitudes herein are according to the
moment magnitude scale, per Field et al. 2015, p. 512.
8. ^ Field 2015.
9. ^ Field 2015.
10. ^ Field et al. 2013, pp. xiii, 11.
11. ^ Field et al. 2013.
12. ^ Figure 4 in Field et al. 2015, p. 520.
13. ^ Field et al. 2015, pp. 525–526;
Field 2015.
14. ^ Field et al. 2015, pp. 525–526; Field.
15. ^ Dozer et al. 2009, pp. 1746–1759
16. ^ Yeats 2012, p. 92
17. ^ Hartzell & Heaton 1986, p. 649
18. ^ Oppenheimer et al. 2010
19. ^ Parsons et al. 2013, p. 57, Table C7.
20. ^
Parsons et al. 2013, p. 54.
21. ^ Figure 3 from Field et al. 2015, p. 514.
22. ^ Field et al. 2013, p. 5.
23. ^ Field et al. 2015, p. 513.
24. ^ Field et al. 2015, p. 521.
25. ^ Field et al. 2013, p. 27.
26. ^ Field et al. 2013, p. 3;
Field 2015, p. 2.
27. ^ Field et al. 2013, pp. 27–28, 51.
28. ^ Parsons et al. 2013
29. ^ Field 2015, p. 5; Field et al. 2013, pp. 3, 27–28. See Page et al. 2014 for details.
30. ^ Field et al. 2013, p. 51.
31. ^ Page et al. 2014, pp. 44–45,
Fig. C16.
32. ^ Field et al. 2013, p. 90.
33. ^ Field et al. 2015, p. 541.
34. ^ Field et al. 2015, pp. 512, 539. In an earlier report Field et al. (2013, p. 7) call it a “crude approximation”.
35. ^ See Table 16 in Field et al. 2013, p. 89,
which lists 15 key assumptions.
36. ^ Field et al. 2015, p. 541.
37. ^ Field et al. 2015, p. 512.
38. ^ Field et al. 2013, p. 87.
39. ^ Field et al. 2013, pp. 88–89. Discussion at pp 55–56.
40. ^ Field et al. 2013, pp. 86–87. Specifically,
GR consistency seems to require one or more of the following: “(1) a higher degree of creep both on and off faults; (2) higher long-term rate of earthquakes over the whole region (and significant temporal variability on faults such as the SAF); (3)
more fault connectivity throughout the state (for example, ~M8 anywhere); and (or) (4) lower shear rigidity.”
41. ^ Field et al. 2013, p. 87.
• Dozer, D. I.; Olsen, K. B.; Pollitz, F. F.; Stein, R. S.; Toda, S. (2009), “The 1911 M∼6.6 Calaveras
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• Field,
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• Field, Edward H.; Arrowsmith, Ramon J.; Biasi, Glenn P.; Bird, Peter; Dawson, Timothy E.; Felzer, Karen R.;
Jackson, David D.; Johnson, Kaj M.; Jordan, Thomas H.; Madden, Christopher; Michael, Andrew J.; Milner, Kevin R.; Page, Morgan T.; Parsons, Tom; Powers, Peter M.; Shaw, Bruce E.; Thatcher, Wayne R.; Weldon, Ray J., II; Zeng, Yuehua (June 2014), “Uniform
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A New Earthquake Forecast for California’s Complex Fault System” (PDF), U.S. Geological Survey, Fact Sheet 2015–3009, doi:10.3133/fs20153009, ISSN 2327-6932.
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• Hartzell, S. H.; Heaton, T. H. (1986), “Rupture
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• Oppenheimer, D. H.; Bakun, W. H.; Parsons, T.; Simpson, R. W.; Boatwright,
J. B.; Uhrhammer, R. A. (2010), “The 2007 M5.4 Alum Rock, California, earthquake: Implications for future earthquakes on the central and southern Calaveras Fault”, Journal of Geophysical Research, 115 (B8), doi:10.1029/2009jb006683.
• Page, Morgan
T.; Field, Edward H.; Milner, Kevin R.; Powers, Peter M. (June 2014), “The UCERF3 Grand Inversion: Solving for the Long-Term Rate of Ruptures in a Fault System” (PDF), Bulletin of the Seismological Society of America, 104 (3): 1181–1204, doi:10.1785/0120130180.
• Parsons,
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Photo credit: https://www.flickr.com/photos/anneh632/5083072098/’]