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?
Where do we expect
earthquakes?
When do we expect
earthquakes?
What will happen in those
earthquakes?
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 50100 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
GSC
“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
Present Study
HUNGARY:
ALTERNATIVE
HAZARD MAPS
Peak Ground Acceleration
10% probability of exceedance
in 50 years
(once in 500 yr)
Diffuse hazard inferred
incorporating geology
Concentrated
hazard
inferred from
historic
seismicity
alone
Toth et al., 2004
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
Sieh et al., 1989
Extend earthquake history with
paleoseismology
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, log-normal, 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
log10 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
Direct paleoseismic study:
Magnitude overestimated, recurrence
underestimated
Events missed, recurrence
overestimated
CHARACTERISTIC
Earthquake Rate
Undersampling:
record comparable to or shorter than
mean recurrence Usually find too-short recurrence time.
Can also miss largest events
UNCHARACTERISTIC
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 Tav, 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 (Mmax, 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