Forecasting earthquakes:
the state of the art
Andrew Bell and Ian Main
School of GeoSciences,
University of Edinburgh
Uniform California Earthquake Rupture Forecast (2007)
http://www.scec.org/ucerf/
L’Aquila April 2009
Official Italian seismic classification map (2006)
http://www.protezionecivile.it/cms/attach/editor/Classificazione
Earthquake forecasting
• Earthquake prediction:
–
“the prediction of the location, time and magnitude of
an earthquake, in advance, within narrow limits, above
chance” Richter (1954)
• Types of forecast:
– Time-independent hazard
– Time-dependent hazard
– Earthquake forecasting
www.nature.com/nature/debates/earthquake/
• Forecast requirements:
– Data > Models > Tests
• Full quantification of
uncertainties
Time-independent hazard
• Data:
– Earthquake history, fault maps,
long-term deformation rates etc.
• Model:
– Random (Poisson) process with time
– Local smoothing parameters
– Path & site effects
• Output:
– Probability of exceeding certain
ground shaking in X years
ESC-SESAME map (2003)
http://www.ija.csic.es/gt/earthquakes/
Time-dependent hazard
• Includes non-random recurrence
time information
Shimazaki & Nakata (1980)
Uniform California Earthquake Rupture Forecast (2007)
http://www.scec.org/ucerf/
Statistical earthquake forecasting models
• Epidemic-Type Aftershock Model
(ETAS)
• Short-Term Earthquake Probability
(STEP)
California 24-Hour Aftershock Forecast Map
http://earthquake.usgs.gov/earthquakes/step/
Physical earthquake forecasting models
• Quantifiable physical perturbation
• Quantifiable Earth response
• e.g. Coulomb stress transfer +
rate & state friction
Coulomb stress changes fro Landers & Big Bear
earthquakes,1992, King et al. (1994)
Testing earthquake forecasts
http://www.cseptesting.org/
• Testing Centers
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RELM tests, SRL 2007
ERI, Japan
ETH, Switzerland
GNS, New Zealand
SCEC, United States
• Testing Regions
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–
–
–
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California
Italy
Japan
Northwest Pacific
Southwest Pacific
New Zealand
Global
Coming soon…
• Improved data quality/quantity
– e.g. NERIES, EPOS
• Model development
– Composite physical + statistical models
– Scenario modelling
– Improved uncertainty quantification
• Advanced testing protocols
– Global-scale model testing
– Quantification of forecast consistency,
quality (reliability, accuracy etc.) and
value (Murphy, 1993)
European VEBSN stations, NERIES
Is any of this practicable for DRR?
• Significant probability gains, but low absolute probabilities
• How can potentially small changes in probability be used?
–
Cost-benefit balance for actions based on potentially small probability gains?
L’Aquila, 2009. Photo: Daily Telegraph