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 • Testing Regions – ERI, Japan – California – ETH, Switzerland – Italy – GNS, New Zealand – Japan – SCEC, United States – Northwest Pacific – Southwest Pacific – New Zealand – Global

RELM tests, SRL 2007 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, European VEBSN stations, NERIES quality (reliability, accuracy etc.) and value (Murphy, 1993) 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