Can We Predict Earthquakes?

1
Can We Predict Earthquakes?

• Andrea Nemeth
• Advisor Dr. Mark Schilling

2
Earthquake Prediction

• location
• time
• magnitude
• probability of
• occurrence
• reliable
• accurate

The collapse of part of Jefferson Junior High
School in Long Beach in 1933.(Photo Portland
Cement Association)
3
Methods Employed In Earthquake Prediction

• statistical probability
• physical measurements
• geochemical observations
• observations of animal behavior

Seismicity of California (USGS)
4
Real Data or Simulated?
5
Popular media statements

• the Big One is overdue
• the longer it waits, the bigger it will be

(USGS)
6
Statistical Models

• time-independent
• Poisson (exponential)
• model
• time-dependent
• Gaussian
• gamma
• log-normal
• Weibull distributions
• Brownian Passage
• Time

7
Poisson Model Weibull Model

• Magnitudes of EQs and the time intervals between
  EQs are each assumed to be independently
  distributed.
• memoryless

• The probability of rupture is a function of the
  accumulated strain.

8
Parkfield and Wrightwood

• Parkfield area
• medium-sized EQs occur here fairly regularly
• Wrightwood area
• long term data is available

LA
(USGS)
9
The Experiment

• 1857, 1881, 1901, 1922, 1934, 1966
• USGS prediction
• an earthquake of M6 would occur in Parkfield
  between 1983 and 1993

10
So how regular are the recurrence times of these
earthquakes?
The intervals between these EQs 24, 20, 21, 12,
32, 38

• Mean
• 24.5 years
• Standard deviation
• 9.25 years.

11
Probability Plots
12
Can we rule out the possibility that even EQs at
Parkfield are random in time?
24 7 3 10 25 31
20 20 25 29 7 53
21 4 5 27 20 5
12 13 9 7 47 18
32 17 16 32 2 22
38 11 41 27 39 12
9.25 5.79 14.59 10.63 17.75 16.93

• Result 8.8 of all simulated interval sequences
  had standard deviation less than 9.25.
• Conclusion
• This sequence is somewhat regular, but not
  extremely unusual.

13
Wrightwood
534, 634, 697, 722, 781, 850, 1016, 1116, 1263,
1360, 1470, 1536, 1610, 1690, 1812, 1857
14
The Recurrence Times of the EQs at Wrightwood

• The time intervals between successive EQs
• 100, 63, 25, 59, 69, 166, 100, 147, 97, 110, 66,
  74, 80, 122, and 45 years.
• mean
• 88.2 years
• standard
• deviation
• 37.8 years.

15
Probability Plots
16
Simulation for the Wrightwood area

• Result
• Only 1.5 of all simulated interval sequences
  had standard deviation less than 37.8 years.
• Conclusion
• This sequence of 16 EQs at Wrightwood is more
  regular than the Parkfield sequence.

17
Summary

• Several factors make EQ prediction difficult
• the cycle of EQs is long
• the fundamental physics of EQ faulting is not yet
  understood
• no clearly recognizable precursor has been
  observed
• EQ history is short for most faults

18
Potential Future Work

• Further investigation of the Wrightwood data
• Analysis of other data sets from the
• San Andreas Fault
• Study of other statistical models with our data

19
Acknowledgments

• This project was sponsored by the NASA/JPL PAIR
  program.
• I thank Dr. Carol Shubin for her continuous
  support, interest and encouragement.
• Im very grateful to Dr. Mark Schilling, my
  advisor, for his comments on the data analysis
  and preparation, for his valuable insights
  andobservations.