USING EARTHQUAKE SCIENCE TO
PREDICT EARTHQUAKE HAZARDS AND
REDUCE EARTHQUAKE RISKS:
USING WHAT WE KNOW AND RECOGNIZING
WHAT WE DON’T
Seth Stein
Department of Earth & Planetary Sciences
Northwestern University
seth@earth.northwestern.edu
http://www.earth.northwestern.edu/people/seth/Export/CEA
Sources
WE CAN HAVE AS MUCH SEISMIC SAFETY
AS WE WANT TO PAY FOR
But it takes resources away from other needs
Need to understand earthquake hazards and risks
to decide what to do
HAZARDS VERSUS RISKS
Hazard is natural
occurrence of earthquakes
and the resulting ground
motion and other effects.
Risk is the danger the
hazard poses to life and
property.
High hazard areas can
have low risk because few
people live there, and
modest hazard areas can
have high risk due to large
populations and poor
construction.
Hazards can’t be reduced by
human actions but risks can.
Seismic hazard predicted shaking is not something we
measure or know
We define it on
policy grounds
We predict it based
on what we think
happened in the
past and what will
happen in the future
Different
assumptions predict
very different
hazards
Newman et
al., 2001
Mitigating hazard (reducing risk) from
earthquakes or other natural disasters involves
economic and policy issues as well as scientific
and engineering ones.
$100M seismic retrofit
of Memphis hospital,
removing nine floors,
bringing it to California
standard
Does this make sense?
How can we help
society decide?
Systems Analysis for Hazard Mitigation
What’s the hazard?
What do we know & not know?
What are we trying to accomplish?
What strategies are available?
What are the costs & benefits of each?
What is an optimum strategy given
uncertainty?
Our goal is to decide how much is enough.
Stochastic model
Optimal level of mitigation minimizes
total cost = sum of mitigation cost + expected loss
Expected loss = ∑ (loss in ith expected event
x assumed probability of that event)
For earthquake, mitigation level is construction code
Loss depends on earthquake & mitigation level
Less mitigation decreases
construction costs but increases
expected loss and thus total cost
Stein & Stein, 2012
More mitigation gives less
expected loss but higher total cost
Including risk aversion & uncertainty
Consider marginal costs C’(n) & benefits Q’(n) (derivatives)
More mitigation
costs more
Benefit
(loss reduction)
But reduces loss
Optimum is where
marginal curves
are equal, n*
cost
Stein & Stein, 2012
Uncertainty in hazard model & mitigation efficiency causes
uncertainty in expected loss. We are risk averse, so add risk
term R(n) proportional to uncertainty in loss, yielding higher
mitigation level n**
Crucial to consider hazard model uncertainty
QUESTIONS:
1) Why is predicting earthquake (or other
natural) hazards so hard?
2) How does the challenge differ between
plate boundary, plate boundary zone, and
intraplate earthquakes?
3) What are the difficulties in hazard
mapping?
4) What are the issues in cost-effective
hazard mitigation policy?
Some US experience may be useful in China
TOPIC 1:
Why is predicting earthquake (or other
natural) hazards so hard?
We have learned a lot about
earthquakes, but
In general, we have not done well at
short-term predictions (narrow window
in space and time)
We do better at long-term forecasting,
because of the wider window in space
and time, but often fail
WANT TO AVOID
False negative - unpredicted hazard
Fail to identify & prepare for real hazard
False positive - overpredicted hazard
Waste resources, public loses confidence
PREDICTING HAZARDS IS HARD BECAUSE
Scientific issues
- The earth is complicated
-There’s a lot we don’t know
Human issues
- Often we know less than we think we do
- We interpret data to fit wrong models
PREDICTING HAZARDS IS HARD BECAUSE
Scientific issues
- The earth is complicated
-There’s a lot we don’t know
- No adequate theory
- Rare events
- Short time history
PALMDALE
BULGE UPLIFT
1975
USGS director McKelvey expressed his Bulge was an artifact of errors
view that a great earthquake would occur
in referring the vertical
in the area possibly within the next
motions to sea level via a
decade that might cause up to 12,000
traverse across the San
deaths, 48,000 serious injuries, 40,000
Gabriel mountains.
damaged buildings, and up to $25 billion
in damage.
Davidson et al 2002
PARKFIELD, CALIFORNIA SEGMENT OF
SAN ANDREAS
M 5-6 earthquakes about every 22 years:
1857, 1881, 1901, 1922, 1934, and 1966
In 1985, expected next in 1988;
predicted at 95% confidence by
1993
2004
$20 million project set up seismometers, strainmeters,
creepmeters, GPS receivers, tiltmeters, water level
gauges, electromagnetic sensors, and video cameras
were set up to monitor what would happen before and
during the earthquake.
In 1985, expected next in 1988;
predicted at 95% confidence by
1993
Didn’t occur till 2004
(16 years late)
2004
Poor statistics: shifted 1934 event to improve fit &
hence reduce uncertainty
WHY SHORT-TERM PREDICTIONS DO POORLY
So far, no clear evidence for observable behavior before
earthquakes.
Maybe lots of tiny earthquakes happen frequently, but
only a few grow by random process to large earthquakes
In chaos theory, small perturbations can have
unpredictable large effects - flap of a butterfly's wings in
Brazil might set off a tornado in Texas
AA simple
A of chaos
example
Consider a system
whose evolution in time
is described by the
equation
x(t+1) = 2x(t)2-1
Runs starting off at time
t=0 with slightly
different values, x(0) =
0.750 and x(0) = 0.749,
yield curves that differ
significantly within a
short time.
The fact that small differences
grow is part of the reason why
weather forecasts get less
accurate as they project further
into the future - tomorrow's
forecast is much better than one
for the next five days.
An interesting thought
experiment, suggested by Lorenz
(1995), is to ask what the weather
would be like if it weren't chaotic.
In this case, weather would be
controlled only by the seasons, so
year after year storms would
follow the same tracks, making
planning to avoid storm damage
easy. In reality, storms are very
different from year to year
Tracks of North Atlantic hurricanes,
tropical storms, and depressions for two
very most active hurricane seasons
WHY SHORT-TERM PREDICTIONS DO
POORLY
If there’s nothing special about the tiny
earthquakes that happen to grow into large
ones, the time between large earthquakes and
their locations are highly variable and nothing
observable happens before them.
If so, earthquake prediction is either impossible
or nearly so.
“It’s hard to predict earthquakes, especially
before they happen”
NUVEL-1
Argus et al., 1989
LONG-TERM
FORECASTS
SOMETIMES DON’T
DO WELL
Hazard map didn’t
predict locations of
future earthquakes
GSHAP
NUVEL-1
Argus et al., 1989
LONG-TERM
FORECASTS
SOMETIMES DON’T
DO WELL
Hazard map didn’t
predict locations of
future earthquakes
2003
2004
GSHAP 1998
PROBLEM: HAZARD
MAP BASED ON
LAST
EARTHQUAKES
Years
When
recurrence
time is long,
short record
shows
apparent
seismic gaps
& high hazard
zones
even if hazard
is uniform
100
# of recurrence
events time
1
100
500
11
45
1000
20
50
2000
35
57
3000
56
54
4000
73
55
M>7
5oW
10oE
Latitude
Swafford & Stein, 2007
2001 hazard map
2010 M7 earthquake shaking
much greater than predicted
for next 500 years
http://www.oas.org/cdmp/document/seismap/haiti_dr.htm
6 mm/yr fault motion
2008 Wenchuan earthquake (Mw 7.9) was
not expected: map showed low hazard
USGS
Hazard map - assumed steady state - relied on lack
of recent seismicity
Didn’t use GPS data showing 1-2 mm/yr
Earthquakes prior to the 2008 Wenchuan event
Aftershocks of the Wenchuan event delineating the rupture zone
M. Liu
Japan seemed ideal
for hazard mapping
Geller
2011
Fast moving (80
mm/yr ) & seismically
very active plate
boundary with good
instrumentation &
long seismic history
But: 2011 M 9.1
Tohoku, 1995 Kobe M
7.3 & others in areas
mapped as low hazard
In contrast: map
assumed high hazard
in Tokai “gap”
Planning assumed maximum magnitude 8
Seawalls 5-10 m high
Stein & Okal, 2011
NYT
Tsunami runup
approximately twice fault
slip (Plafker, Okal &
Synolakis 2004)
M9 generates much
larger tsunami
CNN
UNTIL RECENTLY, EARTHQUAKE HAZARD STUDIES
IN THE LOS ANGELES AREA FOCUSED ON THE SAN
ANDREAS FAULT
SAF broke in 1857: M 7.9
Due to short history, didn’t recognize danger of
damaging earthquakes on closer but buried thrust faults
1994 Northridge M 6.7
58 deaths, $20B damage
BECAUSE STRONG GROUND MOTION DECAYS
RAPIDLY WITH DISTANCE
A SMALLER EARTHQUAKE NEARBY CAN DO MORE
DAMAGE THAN A LARGER ONE FURTHER AWAY
M6
M7
PREDICTING HAZARDS IS HARD BECAUSE
Human issues
- We often think we know more than we really do
- Rely on inadequate model
- Uncertainties are hard to assess and usually
underestimated
- Data selected or interpreted to fit existing idea
- Groups convince themselves
- Researchers go along with others even when
their data say otherwise (“Bandwagon”)
Hazard maps fail because of
- bad physics (incorrect description of
earthquake processes)
-bad assumptions (mapmakers’ choice
of poorly known parameters)
- bad data (lacking, incomplete, or
underappreciated)
- bad luck (low probability events)
and combinations of these
SUGGESTIONS
Do our best to assess hazards, but
Be realistic about what we know & what we don’t
Think carefully about what the evidence for conventional
ideas is
Try to realistically assess uncertainties & bear them in
mind
Don’t discard new data because they don’t fit model
Accept that the earth is more complicated than we know,
and may surprise us