By now, you are probably unimpressed by probabilistic earthquake forecasting techniques. Although probabilistic estimates for well-known structures such as the Cascadia Subduction Zone and the San Andreas Fault are improving, it’s unlikely that we’ll be able to improve probability estimates for faults with low slip rates such as the Seattle and Portland Hills faults, unless we’re more successful with short-term precursors. Yet we continue in our attempts because insurance underwriters need this kind of statistical information to establish risks and premium rates. Furthermore, government agencies need to know if the long-term chances of an earthquake are high enough to require stricter building codes, thereby increasing the cost of construction. This chapter began with a discussion of earthquake prediction in terms of yes or no, but probabilistic forecasting allows us to quantify the “maybes” and to say something about the uncertainties. Much depends on how useful the most recent forecast for the San Francisco Bay Area is, as well as others for southern California. Will the earthquakes arrive on schedule, or will they be delayed, as the 1988 Parkfield Earthquake was, or will the next earthquake strike in an unexpected place?
Why are we not farther along in scientifically reliable earthquake forecasting? The answer may lie in our appraisal in Chapter 2 of the structural integrity of the Earth’s crust—not well designed, not up to code. Some scientists believe that the Earth’s crust is in a state of critical failure—almost, but not quite, ready to break. In this view, the Earth is not like a strong well-constructed building that one can predict with reasonable certainty will not collapse. The crust is more like a row of old tenements, poorly built in the first place with shoddy workmanship and materials, and now affected by rot and old age. These decrepit structures will probably collapse someday but which one will collapse first? Will the next one collapse tomorrow or ten years from now? This is the dilemma of the earthquake forecaster.
But society and our own scientific curiosity demand that we try.
Suggestions for Further Reading
Allen, R. W., and H. Kanamori, H. 2003. The potential for earthquake early warning in southern California. Science, v. 300, p. 786-89.
Benz, H., J. Gilson,W. Arabasz, L. Gee, and L. Wald. 2000. Advanced National Seismic System Info Sheet; see also http://geohazard.cr.usgs.gov/pubs/circ
Bolt, B. A. 2004. Earthquakes, 5th edition. New York: W.H. Freeman and Co., 378 p.
Clarke, T. 1996. California fault: searching for the spirit of state along the San Andreas. New York: Ballantyne Books, 417 p.
Crampin, S. 1999. Stress-forecasting earthquakes. Seismological Research Letters, v. 70, p. 291-93. Geller, R. J. 1997. Predictable publicity. Seismological Research Letters, v. 68, p. 477-80.
Harris, R. A. 1998. The Loma Prieta, California, earthquake of October 17, 1989—-forecasts. USGS Professional Paper 1550-B.
Jackson, D.D., Earthquake prediction and forecasting: American Geophysical Union Monograph 150, p. 335-348.
Jackson, D. D., Y. Kagan, and S. Uyeda. 1998. The VAN method of earthquake prediction. EOS, Transactions of the American Geophysical Union, v. 79, p. 573, 579-80. (Jackson and Kagan argue against, Uyeda argues for.)
Jordan, T.H., and Jones, L.M., 2010. Operational earthquake forecasting: Some thoughts on why and how: Seismological Research Letters, v. 81, p. 571-574.
Kanamori, H., E. Hauksson, and T. Heaton. 1997. Real-time seismology and earthquake hazard mitigation. Nature, v. 390, p. 481-84.
Lomnitz, C. 1994. Fundamentals of earthquake prediction. New York: John Wiley & Sons, 326 p.
Ma, Z., Z. Fu, Y. Zhang, C. Wang, G. Zhang, and D. Liu. 1990. Earthquake prediction: Nine major earthquakes in China (1966-1976). Beijing: Seismological Press, and Berlin: Springer-Verlag, 332 p.
Olson, R. S. 1989. The politics of earthquake prediction. Princeton, N.J.: Princeton University Press, 187 p. (Includes a description of the Brady earthquake prediction for Lima, Peru.)
Reiter, L. 1990. Earthquake hazard analysis: Issues and insights. New York: Columbia University Press.
Scholz, C. H. 1997. Whatever happened to earthquake prediction? Geotimes, v. 42, no. 3, p. 16-19. Spence, W., R. B. Herrmann, A. C. Johnston, and G. Reagor. 1993.\
Spence, W., R. B. Herrmann, A. C. Johnston, and G. Reagor. 1993. Response to Iben Browning’s prediction of a 1990 New Madrid, Missouri, earthquake. USGS Circular 1083, 248 p.
Stein, R. S. 2003. Earthquake conversations. Scientific American, v. 288, no. 1, p. 72-79.
Strauss, J., 2015, Vital seconds: The journey toward earthquake early warning for all: Earth, September/October 2015, p. 70-77, www.earthmagazine.org
Response to Iben Browning’s prediction of a 1990 New Madrid, Missouri, earthquake. USGS Circular 1083, 248 p. Stein, R. S. 2003. Earthquake conversations. Scientific American, v. 288, no. 1, p. 72-79.
Vere-Jones, D., D. Harte, and M. J. Kozuch. 1988. Operational requirements for an earthquake forecasting programme for New Zealand. Bulletin of the New Zealand Society for Earthquake Engineering, v. 31, no. 3, p. 194-205.
Whiteside, L. S. 1998. Earthquake prediction is possible. Seismological Research Letters, v. 69, p. 287-88
Working Group on California Earthquake Proabilities. 1999. Earthquake probabilities in the San Francisco Bay Region: 2000 to 2030—a summary of findings. USGS Circular 1189 and http://quake.usgs.gov/study/wg99/ of99-517/index.html
Yeats, R.S., 2001, Living with Earthquakes in California: A Survivor’s Guide. Oregon State University Press, 406 p.
Youngs, R. R., et al. 2003. A methodology for probabilistic fault displacement hazard analysis (PFDHA). Earthquake Spectra, v. 19, p. 191-219.