USING EARTHQUAKE SCIENCE TO PREDICT EARTHQUAKE HAZARDS AND

REDUCE EARTHQUAKE RISKS:

USING WHAT WE KNOW AND RECOGNIZING WHAT WE DON’T

Seth SteinDepartment of Earth & Planetary Sciences

Northwestern Universityseth@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

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.

HAZARDS VERSUS RISKS

Newman et al., 2001

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

$100M seismic retrofit of Memphis hospital, removing nine floors,

bringing it to California standard

Does this make sense?

How can we help society decide?

Mitigating hazard (reducing risk) from earthquakes or other natural disasters involves economic and policy issues as well as scientific

and engineering ones.

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)

Less mitigation decreases construction costs but increases expected loss and thus total cost

More mitigation gives less expected loss but higher total cost

Stein & Stein, 2012

For earthquake, mitigation level is construction codeLoss depends on earthquake & mitigation level

Including risk aversion & uncertainty

Consider marginal costs C’(n) & benefits Q’(n) (derivatives)

More mitigation costs more

But reduces loss

Optimum is where marginal curves are equal, n*

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

cost

Benefit

(loss reduction)

Stein & Stein, 2012

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

Bulge was an artifact of errors in referring the vertical

motions to sea level via a traverse across the San

Gabriel mountains.

Davidson et al 2002

USGS director McKelvey expressed his view that a great earthquake would occur in the area possibly within the next decade that might cause up to 12,000 deaths, 48,000 serious injuries, 40,000 damaged buildings, and up to $25 billion in damage.

PALMDALE BULGE UPLIFT

1975

PARKFIELD, CALIFORNIA SEGMENT OF SAN ANDREAS

In 1985, expected next in 1988; predicted at 95% confidence by

1993

M 5-6 earthquakes about every 22 years: 1857, 1881, 1901, 1922, 1934, and 1966

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

1993Didn’t occur till 2004

(16 years late)

Poor statistics: shifted 1934 event to improve fit & hence reduce uncertainty

2004

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

WHY SHORT-TERM PREDICTIONS DO POORLY

AAA simple

example of chaos

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

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”

WHY SHORT-TERM PREDICTIONS DO POORLY

LONG-TERM FORECASTS SOMETIMES DON’T DO WELL

Hazard map didn’t predict locations of future earthquakes

GSHAP

NUVEL-1Argus et al., 1989

GSHAP 1998

NUVEL-1Argus et al., 1989

2004

2003

LONG-TERM FORECASTS SOMETIMES DON’T DO WELL

Hazard map didn’t predict locations of future earthquakes

Years # of recurrence events time100 1 100

500 11 45

1000 20 50

2000 35 57

3000 56 54

4000 73 55

5oW 10oE Latitude

M > 7

PROBLEM: HAZARDMAP BASED ON LAST EARTHQUAKES

When recurrence time is long,short record

shows apparent

seismic gaps & high hazard

zones even if hazard

is uniformSwafford & Stein, 2007

2001 hazard map

http://www.oas.org/cdmp/document/seismap/haiti_dr.htm

2010 M7 earthquake shaking much greater than predicted

for next 500 years

6 mm/yr fault motion

USGS

2008 Wenchuan earthquake (Mw 7.9) was not expected: map showed low hazard

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

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”

Geller 2011

Tsunami runup approximately twice fault

slip (Plafker, Okal & Synolakis 2004)

M9 generates much larger tsunami

Planning assumed maximum magnitude 8 Seawalls 5-10 m high

CNN

NYTStein & Okal, 2011

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

UNTIL RECENTLY, EARTHQUAKE HAZARD STUDIES IN THE LOS ANGELES AREA FOCUSED ON THE

SAN ANDREAS FAULT

SAF broke in 1857: M 7.9

BECAUSE STRONG GROUND MOTION DECAYS RAPIDLY WITH DISTANCE

A SMALLER EARTHQUAKE NEARBY CAN DO MORE DAMAGE THAN A LARGER ONE FURTHER AWAY

M 7M 6

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