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Seismicity, Critical States of: From Models to Practical Seismic Hazard Estimates Space

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Extreme Environmental Events

Article Outline

Glossary

Definition of the Subject

Introduction

Modeling Seismicity in Real Fault Regions

Results

Summary and Conclusions

Future Directions

Acknowledgments

Bibliography

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Abbreviations

Bayesian analysis:

A model estimation technique that accounts for incomplete knowledge. Bayes' theorem is a mathematical formulation of how an a priori estimate of the probability of an event can be updated, if a new information becomes available.

Critical earthquake concept:

The occurrence of large earthquakes may be described in terms of statistical physics and thermodynamics. In this view, an earthquake can be interpreted as a critical phase transition in a system with many degrees of freedom. The preparatory process is characterized by acceleration of the seismic moment release and growth of the spatial correlation length as in the percolation model. This interpretation of earthquake occurrence is referred to as the critical earthquake process.

Earthquake forecast/prediction:

The forecast or prediction of an earthquake is a statement about time, hypocenter location, magnitude, and probability of occurrence of an individual future event within reasonable error ranges.

Fault model :

A fault model calculates the evolution of slip, stress, and related quantities on a fault segment or a fault region. The range of fault models varies from conceptual models of cellular automaton or slider‐block type to detailed models for particular faults.

Probability:

A quantitative measure of the likelihood for an outcome of a random process. In the case of repeating a random experiment a large number of times (e. g. flipping a coin), the probability is the relative frequency of a possible outcome (e. g. head). A different view of probability is used in the → Bayesian analysis.

Seismic hazard :

The probability that a given magnitude (or peak ground acceleration) is exceeded in a seismic source zone within a pre‐defined time interval, e. g. 50 years, is denoted as the seismic hazard.

Self‐organized criticality:

Self‐organized criticality (SOC) as introduced by Bak [2] is the ability of a system to organize itself in the vicinity of a critical point independently of values of physical parameters of the system and initial conditions. Self‐organized critical systems are characterized by various power law distributions. Examples include models of sandpiles and forest‐fires.

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Acknowledgments

We thank Jürgen Kurths, James R. Rice, Frank Scherbaum, Karin Dahmen, Donald L. Turcotte, and many others for useful discussions. GZ and MH acknowledge support from the collaborative research center “Complex Nonlinear Processes” (SFB 555) of the German Research Society (DFG). SH acknowledges support from the DFG‐project SCHE280/14 and the EU‐project SAFER. YBZ acknowledges support from the National Science Foundation, the United States Geological Survey, and the Southern California Earthquake Center. GZ and YBZ thank the Kavli Institute for Theoretical Physics, UC Santa Barbara, for hospitality during a 2005 program on Friction, Fracture and Earthquake Physics, and partial support based on NSF grant PHY99–0794. We thank James R. Holliday, Vladimir Keilis-Borok and Willie Lee for providing comments on the paper.

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Authors and Affiliations

  1. Institute of Mathematics and Centre for Dynamics of Complex Systems, University of Potsdam, Potsdam, Germany

    Gert Zöller & Matthias Holschneider

  2. GFZ German Research Centre for Geosciences, Potsdam, Germany

    Sebastian Hainzl

  3. Department of Earth Sciences, University of Southern California, Los Angeles, USA

    Yehuda Ben-Zion

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  1. Gert Zöller
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  2. Sebastian Hainzl
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    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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Zöller, G., Hainzl, S., Ben-Zion, Y., Holschneider, M. (2011). Seismicity, Critical States of: From Models to Practical Seismic Hazard Estimates Space. In: Meyers, R. (eds) Extreme Environmental Events. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7695-6_43

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