TOPIC 3: HOW WELL CAN WE PREDICT EARTHQUAKE
HAZARDS?
Predictions are important for hazard mitigation policy
How much should we believe them?

HAZARD ASSESSMENT IS HARD
It has been described as "a game of chance of which we still don't know all the rules”
Lomnitz, 1989
AND WHAT GOES INTO A MAP IS OFTEN NOT
EXPLAINED OR EXPLAINED BADLY
Its "simplicity is deeply veiled by user-hostile notation, antonymous jargon, and proprietary software"
Hanks and Cornell, 1994

How is the hazard defined?
Hazard isn’t a physical thing we measure.
It’s something mapmakers define on policy grounds.
How they define hazard is the largest factor in determining the hazard.
Different choices lead to different predicted hazards and thus favor different policies.

Algermissen et al., 1982
Hazard redefined from maximum acceleration predicted at
10% probability in 50 yr
(1/ 500 yr ) to much higher
2% in 50 yr
(1/2500 yr)
Frankel et al., 1996

New Madrid hazard higher than
California results largely from redefining hazard as largest shaking expected every
2500 yr:
Not so for 500 yr
500 yr
500 yr
2500 yr
Searer & Freeman, 2002
2500 yr

ASSUMED HAZARD DEPENDS ON DEFINITION TIME WINDOW
Over 100 years,
California site much more likely to be shaken strongly than
NMSZ one
Over 1000 years, more NMSZ sites shaken strongly once; many in
California shaken many times
Short time relevant for buildings with 50-
100 yr life Shaken areas MMI > VII
Random seismicity simulation including seismicity & ground motion differences

Where do we expect earthquakes?
Can use
Earthquake history
Plate motions
Geology
GPS
On plate boundaries, these agree.
In other places, we have to chose which to use
Different choices lead to different predicted hazards

Long record needed to see real hazard
1933
M 7.3
1929
M 7.2
Swafford & Stein, 2007

Map depends greatly on assumptions & thus has large uncertainty
“Our glacial loading model suggests that earthquakes may occur anywhere along the rifted margin which has been glaciated.”
Stein et al., 1979
1985
Concentrated hazard bull's-eyes at historic earthquake sites
2005
Diffuse hazard along margin
GSC

Diffuse hazard inferred incorporating geology
Toth et al., 2004
Concentrated hazard inferred from historic seismicity alone
Present Study HUNGARY:
ALTERNATIVE
HAZARD MAPS
Peak Ground Acceleration
10% probability of exceedance in 50 years
(once in 500 yr)
GSHAP (1999)

When do we expect earthquakes?
When we have a long history , we can estimate the average recurrence time but there’s a lot of scatter
When we have a short history , we estimate the recurrence time of large earthquakes from small ones, but this can be biased
In either case, we have to assume either that the probability of large earthquakes stays constant with time, or that it changes
Different choices lead to different predicted hazards

EARTHQUAKE RECURRENCE IS HIGHLY VARIABLE
Extend earthquake history with paleoseismology
Sieh et al., 1989
M>7 mean 132 yr s
105 yr
Estimated probability in 30 yrs 7-51%

When we have a long history , we can estimate the average recurrence time but there’s a lot of scatter
Mean 132 s 105 Mean 180 s 72
We can describe these using various distributions -
Gaussian, lognormal, Poisson but it’s not clear that one is better than another

When we have a short history , we estimate the recurrence time of large earthquakes from small ones, but this can be biased
Gutenberg Richter relationship log
10
N = a -b M
N = number of earthquakes occurring ≥ M a = activity rate (y-intercept) b = slope
M = Magnitude

POSSIBLE BIASES IN ESTIMATING THE MAGNITUDE AND
RECURRENCE TIME OF LARGE EARTHQUAKES FROM
THE RATE OF SMALL ONES
Undersampling : record comparable to or shorter than mean recurrence -
Usually find too-short recurrence time.
Can also miss largest events
CHARACTERISTIC
UNCHARACTERISTIC
Direct paleoseismic study:
Magnitude overestimated, recurrence underestimated
Events missed, recurrence overestimated
Stein & Newman, 2004

SIMULATIONS
10,000 synthetic earthquake histories for G-R relation with slope b=1
Gaussian recurrence times for M> 5, 6, 7
Various history lengths given in terms of T av
, mean recurrence for M>7
Short history: often miss largest earthquake or find a too-short recurrence time
Stein & Newman, 2004

Long history: Can still find too-short or too-long recurrence time
Stein & Newman, 2004

RESULTS VARY WITH AREA SAMPLED
Increasing area around main fault adds more small earthquakes
Stein et al., 2005

ASSUMED HAZARD
DEPENDS ON
EARTHQUAKE
PROBABILITY
ASSUMPTION
Constant since last event: time independent (can’t be “overdue”)
Small after last event, then grows: time dependent
Time dependent lower until ~2/3 mean recurrence
Details depend on model
& parameters
Hebden & Stein, 2008

RELATIVE PREDICTED HAZARD DEPENDS
ON POSITION IN EARTHQUAKE CYCLE
Time dependent lower until ~2/3 mean recurrence
Charleston &
New Madrid early in their cycles so time dependent predicts lower hazard
Southern San Andreas broke in
1857 M 7.7 Fort Tejon, late in cycle so time-dependent predicts higher hazard (“overdue”)
Hebden & Stein, 2008

California
Timedependant probabilities
Increased on southern San
Andreas

CHARLESTON
At present, time dependent predicts
~50% lower hazard
Still less in
2250
2% in 50 yr
(1/2500 yr)
Hebden & Stein, 2008

What will happen in large earthquakes?
Major unknowns are magnitude of the earthquake and the ground shaking it will produce
Tradeoff between these two parameters
Different choices lead to different predicted hazards

EFFECTS OF
ASSUMED
GROUND MOTION
MODEL
Effect as large as one magnitude unit
Frankel model predicts significantly greater shaking for
M >7
Frankel M 7 similar to other models’ M 8
Newman et al., 2001

Assumed maximum magnitude of largest events has largest effect near main fault
Assumed ground motion model has regional effect because it also applies to small earthquakes off main fault
Newman et al., 2001

When we look at a hazard map, remember that it is just one of a large number of quite different and equally likely maps one could make, depending on model assumptions
How is the hazard defined?
Where do we expect earthquakes?
When do we expect earthquakes?
What will happen in those earthquakes?
Often the last (M max
, ground motion model) is discussed the most but the other assumptions are more important

Comparing maps made for different assumptions shows which features are best constrained
(robust)

We use these maps, but It’s hard to say how good they are
Won’t know for 100s or 1000s of years, when we have enough experience to see how good their predictions were.
Where the data are good, the assumptions and thus predictions are probably pretty good. Where the data are poorer, the predictions are probably poorer.
Our best bet is probably to look at any given map, ask whether the prediction makes sense, and act accordingly.

New Madrid: 200 years into hypothesized
500 year recurrence
%106
154%
2% in 50 yr
(1/2500 yr)
Large uncertainty in maps
54% effect in
Memphis