Portals for Real-Time Earthquake Data and Forecasting

Challenges and Promise

John B RundleDistinguished Professor, University of California, Davis (www.ucdavis.edu)

Chairman, Open Hazards Group (www.openhazards.com)

Credit: NHK

Major Contributors

University of California:James Holliday (University of California)Mark Yoder (University of Calfornia)Steven Ward (and University of California)

Open Hazards Group:William Graves Paul Rundle

QuakeSim (NASA and Jet Propulsion Laboratory):Andrea DonnellanJay Parker

E-Decider (NASA and Jet Propulsion Laboratory):Maggi Glasscoe

Other:Marlon Pierce (IU)Geoffrey Fox (IU)Jun Wang (IU)

ImpactsLoss Trends (Munich Re, 2012)

The Four Phases of a Disaster

Disaster PhaseTypical Time

ScalesSolutions

Anticipation Months to DecadesScience:

Forecasting and Planning

Mitigation Months to YearsEngineering:

Structures and Lifelines

Response Seconds to Weeks Social, IT, Medical: Emergency Responders

Recovery Weeks to Years

Economics, Engineering: Finance and

Reconstruction

Forecasting vs. Prediction

Context Characteristic

Prediction A statement that can be validated or falsified with 1 observation

ForecastA statement for which multiple

observations are required to validate a probability density function within

prescribed error bounds

Challenges in Web-Based Forecasting

Data & Models Information

Delivery Meaning

Acquiring & validating data Automation What is probability?

Model building Web-based integration Visual presentation

Efficient algorithms UI GIS

Validating/verifying models Tools Correlations

Error reporting, correction, model

steering

Collaboration/social networks

Expert guidance/blogs

Building a Portal

Objectives Content APIsAccessibilit

y

Information Text PHP/HTML Desktop

Publishing Images MySQL Mobile

Networking Videos CSS Site Design

Apps Data Javascript Site Navigation

Advocacy Links Python Forms

QuakeSim A Resource for Researchers

OpenHazards A Resource for the

Public

E-Decider A Resource for

Responders

Web-Based Resources

For Risk Awareness and Management

Risk Management

Systemic-level risk is growing exponentially from a variety of natural hazards

Currently, risk management is done by big corporations for big corporations

Modern social networking technology together with web-based information and tools has

enabled a new era of Personal Risk Management

QuakeSim/E-DECIDERGoals• Reduce, Transform and Distribute NASA Earth Science Data in support of

Earthquake Research, Mitigation and Response• Produce results that have immediate utility for disaster response

12Simplified workflow

UICDS-Connected

ApplicationsUICDS-

Connected Applications

UICDS-Connected

ApplicationsUICDS-

Connected Applications

UICDS-Connected

Applications

Data Distribution Examples

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QuakeSim E-DECIDER

Hazard ViewerJapan Region

Spatial Contours of Forecast

Probabilities in the Japan Region

M>6.5 for the Next 1 Year beginning June 27, 2013

Chance of a Another Major or Great Earthquake in

Japan Region in the Near Future is High

1000 km Radius Circle Around

Tokyo

All Aftershocks Since M7.9 on March 11, 2011

Earthquake Forecasts (Probability in %): Eight CitiesProbability of Magnitude ≥ 7 -- Within 1 Year and Within 100 miles

Sendai

79%

Tokyo

58%

Shizuoka

38%

Osaka

18%Miyazaki

24%

Nagasaki

11%

Kyoto

18%

Niigata

23%6/26/2013

Earthquake Forecasts (Probability in %): Eight CitiesProbability of Magnitude ≥ 7 -- Within 1 Year and Within 100 miles

Sendai

42%

Tokyo

13%

Shizuoka

4%

Osaka

1%Miyazaki

4%

Nagasaki

1%

Kyoto

1%

Niigata

3%10/21/2013

Sendai Earthquake Forecast (Probability in % vs. Time)

Probability of Magnitude ≥ 7 -- Within 1 Year and Within 100 miles

May 24 M8.3 D600km Kamchatka Earthquake

Social Networkinghttp://social.openhazards.com

Communication and collaboration is critical to building global resilient communities

Social Networkinghttp://social.openhazards.com

Components of GIS Server• GeoServer: thematic mapping and data

distribution• Geospatial Database: storage and spatial analysis • Web Service API: simple use REST API for complex

GIS functionalities• Geoprocessing Tool: Python scripts to produce

standard-compliant data products

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GIS Server (Virtual Machine)

GeoServer

Geospatial

Database

Geoprocess Tool Other

Applications

Desktop GIS

3D Visualization

Web Service API

Web/Mobile GIS