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Can We Predict Earthquakes?Can We Predict Earthquakes?

Andrea NemethAdvisor: Dr. Mark Schilling

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Earthquake PredictionEarthquake 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)

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Methods Employed In Methods Employed In Earthquake PredictionEarthquake Prediction

statistical probability

physical measurements

geochemical observations

observations of animal behavior

Seismicity of California (USGS)

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Real Data or Simulated?Real Data or Simulated?

Significant CA Earthquakes1 (1800-2003)(Magnitude M>=6)

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6.2

6.4

6.6

6.8

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7.2

7.4

7.6

7.8

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0 10 20 30 40 50 60 70 80

Significant CA Earthquakes 2 (1800-2003)(Magnitude M>=6)

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6.2

6.4

6.6

6.8

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7.2

7.4

7.6

7.8

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0 10 20 30 40 50 60 70 80

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Popular media statementsPopular media statements

“the Big One is overdue”

“the longer it waits, the bigger it will be”

(USGS)

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Statistical ModelsStatistical Modelstime-independent

Poisson (exponential)model

time-dependent Gaussian gamma log-normal Weibull distributionsBrownian Passage Time

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Poisson ModelPoisson Model Weibull 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.

F t e t( ) 1 F t e t n

( ) 1

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Parkfield and WrightwoodParkfield and Wrightwood

Parkfield area medium-sized EQs occur here fairly regularly

Wrightwood arealong term data is available

LA

(USGS)

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1857, 1881, 1901, 1922, 1934, 1966

USGS prediction:an earthquake of ~M6 would occur in Parkfield between 1983 and 1993

The The ExperimentExperiment

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So how regular are the recurrence So how regular are the recurrence times of these earthquakes?times of these earthquakes?

Mean:

24.5 years

Standard deviation:

9.25 years.

The Recurrence Times of the EQs in the Parkfield Experiment

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6 7

Tim

e (y

ears

)

The intervals between these EQs: 24, 20, 21, 12, 32, 38

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Probability PlotsProbability Plots

0 50 100 150 200 250

1030

506070

80

90

95

97

98

99

Data

Per

cen

t

Exponential Probability Plot for T in the PE

ML Estimates

Mean: 24.5

10 100

1

2

3

5

10

20

3040506070809095

99

Data

Per

cen

t

Weibull Probability Plot for T in the PE

ML Estimates

Shape:

Scale:

3.20754

27.4210

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Can we rule out the possibility that even Can we rule out the possibility that even EQs at Parkfield are random in time?EQs at Parkfield are random in time?

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.

T R 1 1ln ( ) 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

9.259.25 5.795.79 14.5914.59 10.6310.63 17.7517.75 16.9316.93

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WrightwoodWrightwood534, 634, 697, 722, 781, 850, 1016, 1116, 1263, 1360,

1470, 1536, 1610, 1690, 1812, 1857

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The Recurrence Times of the The Recurrence Times of the EQs at WrightwoodEQs 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.0

20

40

60

80

100

120

140

160

180

0 2 4 6 8 10 12 14 16

EQ Interval Index (1-15)

Tim

e (y

ears

)

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Probability PlotsProbability Plots

0 100 200 300 400 500 600

1030

506070

80

90

95

97

98

99

Data

Per

cen

t

between EQs at WrightwoodExponential Probability Plot for the Time Intervals

ML Estimates

Mean: 88.2000

10 100

1

2

3

5

10

20

3040506070809095

99

Data

Per

cen

t

Intervals between EQs at WrightwoodWeibull Probability Plot for the Time

ML Estimates

Shape:

Scale:

2.59754

99.4288

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Simulation for the Wrightwood Simulation for the Wrightwood areaarea

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.

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SummarySummary

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

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Potential Future WorkPotential 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

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AcknowledgmentsAcknowledgments

This project was sponsored by the NASA/JPL PAIR program.

I thank Dr. Carol Shubin for her continuous support, interest and encouragement.

I’m very grateful to Dr. Mark Schilling, my advisor, for his comments on the data analysis and preparation, for his valuable insights andobservations.