Computational Geodynamics and Earthquake Prediction

1
Computational Geodynamics and Earthquake
Prediction as Research Tools for Seismic Hazard
and Risk Analysis
Alik Ismail-Zadeh
International Union of Geodesy and
Geophysics Commission on Geophysical Risk and
Sustainability www. iugg-georisk.org Geophysikal
isches Institute, Universität Karlsruhe,
Germany ?????? / Intl Institute of Earthquake
Prediction Theory and Math Geophysics, Russian
Academy of Sciences, Moscow, Russian
Federation     Institute de Physique du Globe de
Paris, France
International IGOS Geohazards Workshop, 28 June,
BRGM, Orleans, France
2
Contributors
Jean-Louis Le Mouel (1) Vladimir Keilis-Borok
(2) Vlad Kossobokov (1, 3) Giuliano Panza
(4, 5) Gerald Schubert (2)
Pierre Shebalin (1, 3) Alexander Soloviev
(3) Paul Tapponnier (1) Inessa Vorobieva
(3) Friedemann Wenzel (6)

• (1) Institute de Physique du Globe de Paris,
  France
• (2) Department of Earth Space Sciences, UCLA,
  USA
• (3) ?????? / Russian Academy of Sciences, Moscow,
  Russia
• Department of Earth Sciences, University of
  Trieste, Italy
• (5) Abdus Salam International Centre for
  Theoretical Physics, Italy
• (6) Geophysikalisches Institute, Universität
  Karlsruhe, Germany

3
I dedicate the talk to Professor Kei Aki
(1930-2005), a founder of Quantitave Seismology
4
Great advances in understanding of the complex
Earth system and in computational tools,
permitting accurate numerical modelling and
forecasting, are transforming the geoscience.
These advances have a strong impact on the
studies of geohazards and risks such as
earthquakes, landslides, tsunamis, and volcanic
eruptions and show significant potentials to be
applied to serve the sustainable development of
society.
The Earth Simulator Center, Japan
5
Quantitative Scientific Approach to
Understanding the Earths Dynamics
Computational Geodynamics is a blending of the
three areas to obtain a better understanding of
some phenomena through a judicious match between
the problem, a computer architecture, and
algorithms.
6
Societal Approach to Understanding the Earths
Dynamics
Sustainable Development is development that meets
the needs of the present without compromising
the ability of future generations to meet their
own needs. World Commission on Environment and
Development (1987)
7
"Can sustainable development be successful
without taking into account the risk of natural
hazards and their impacts? Can the planet afford
the increasing costs and losses due to so-called
natural disasters?   Disaster reduction policies
and measures need to be implemented to build
disaster resilient societies and communities,
with a two-fold aim to reduce the level of risk
in societies, while ensuring, on the other hand,
that development efforts do not increase the
vulnerability to hazards but instead reduce such
vulnerability.   Disaster and risk reduction is
therefore emerging as an important requisite for
sustainable development ..."   ("Understanding
the links between vulnerability and risk to
disasters related to development and
environment", background paper by UN
International Strategy for Disaster Reduction,
2003).
8
How Quantitative Geoscience Can Contribute to
Understanding the Geodynamics and Associated
Geohazards ?
9
Computational Modeling Of Earthquakes
10
Block-and-Fault Dynamics Model Basic
Principles(Gabrielov et al., 1990 Soloviev and
Ismail-Zadeh, 2003)

• Lithosphere is presented as a set of rigid
  blocks.
• The blocks are separated by fault planes with
  arbitrary angles of dip.
• Deformations and forces take place in the fault
  planes. Deformation is visco-elastic.
• Driving forces are applied to the boundaries of
  block structure and the underlying visco-elastic
  medium.

11
Block-and-Fault Dynamics Model Geometry
12
Block-and-Fault Dynamics Model Dynamics
Relative displacement of the blocks
Displacements of blocks are determined by the
condition of quasi-static equilibrium For each
block the total force and the total moment of
the forces acting on it are equal to zero.
Earthquake and creep
For each fault the following three values of ?
are considered
13
Sequences of Earthquakes and Earthquake Parameters

• Each fault plane is divided into a number of
  cells
• Epicentral co-ordinates and the source depth are
  the weighted sums of the co-ordinates and depths
  of the cells included in the earthquake
• Magnitude is calculated from M D log10S E,
  where D and E are constants and S is the sum of
  the squares of the cells (in km2) included in the
  earthquake.

14
SE-Carpathians Vrancea
15
(No Transcript)
16
(No Transcript)
17
March 4, 1977
Bucharest
18
Seismic-tomographic image of the 2 high P-wave
velocity anomaly
Martin et al., 2005
19
Observed seismicity
Modelled seismicity
20
BAFD Model for the VranceDescending Slab
Ismail-Zadeh et al., 1999, 2000
21
Past and Present of Descending Slab in
Vrancea(analytical model of corner flowby
Ismail-Zadeh, 2003)
Flow field induced by the descending slab and
maximum tectonic shear stress
22
Tibetan Plateau Himalayan
23
Substantial part of the deformation of the crust
is localized on long and relatively narrow faults
and shear zones separating rigid crustal blocks
e.g., Tapponnier et al., 1982, 2001 Peltzer and
Saucier, 1996. Many of these zones cut the base
of the crust, and some extend to the base of the
lithosphere.
24
Eurasia
Eurasia
Replumaz and Tapponnier, 2003
25
Ismail-Zadeh et al., 2005
Tibetan BAFD model
The model structure contains 41 fault planes and
12 blocks in total. The fault planes consist of
63 segments. We consider that an average
thickness of the rigid crustal block is 30 km,
and assign H 30 km between the upper and lower
planes (boundaries) of the model structure.
26
Numerical Experiments
Effects of the elastic properties and viscosity
of fault zones on slip rates
A change in the stress and/or fluid pressure on a
cracked material of the fault zones will result
in the distortion of the cracks, which will in
its turn alter the effective elastic parameters
of the faults zone Hudson, 2000 Tod, 2002.
Also a presence of water can greatly reduce the
viscosity of the fault zones Chopra and
Paterson, 1984.
27
Observed seismicity for 1900-2000 with Mgt7
28
Earthquake clustering
Synthetic seismicity for 2000 years with Mgt7
(exp. 3.3)
29
Earthquake clustering
Synthetic seismicity for 2000 years with Mgt7
(exp. 3.6)
30
Earthquake clustering
Synthetic seismicity for 2000 years with Mgt7
(exp. 4.1)
31
Earthquake clustering
Synthetic seismicity for 2000 years with Mgt7
(exp. 4.2)
32
Fault plane solutions
33
Fault plane solutions
34
Fault slip rates
35
Sumatera
36
26/12/2004 Mw9.3 Great Asian Mega Earthquake
37
BAFD model of the Sunda Arc (geometry)
Soloviev and Ismail-Zadeh, 2003
38
Observed seismicity, Mgt6
Modelled seismicity, Mgt7
39
Quantitative Earthquake Prediction
40

• The extreme catastrophic nature of earthquakes is
  known for centuries due to resulted devastation
  in many of them.
• The abruptness along with apparent irregularity
  and infrequency of earthquake occurrences
  facilitate formation of a common perception that
  earthquakes are random unpredictable phenomena.
• The challenging questions remain pressing. One of
  them
• Why, Where and When do earthquakes occur?

November 14, 2001, Kokoxili Earthquake (along the
Kunlun fault in Tibet)
41
V. Keilis-Borok
K. Aki
42
Major features of critical transitions in
nonlinear systems
(Keilis-Borok, 1999)
43
Definition of earthquake prediction

• The United States National Research Council,
  Panel on Earthquake Prediction of the Committee
  on Seismology suggested the following definition
  (1976, p.7)
• An earthquake prediction must specify the
  expected magnitude range, the geographical area
  within which it will occur, and the time interval
  within which it will happen with sufficient
  precision so that the ultimate success or failure
  of the prediction can readily be judged. Only by
  careful recording and analysis of failures as
  well as successes can the eventual success of the
  total effort be evaluated and future directions
  charted. Moreover, scientists should also assign
  a confidence level to each prediction.
• Allen, C.R. (Chaiman), W. Edwards, W.J. Hall, L.
  Knopoff, C.B. Raleigh, C.H. Savit, M.N. Toksoz,
  and R.H. Turner, 1976. Predicting earthquakes A
  scientific and technical evaluation with
  implications for society. Panel on Earthquake
  Prediction of the Committee on Seismology,
  Assembly of Mathematical and Physical Sciences,
  National Research Council, U.S. National Academy
  of Sciences, Washington, D.C.

44
Intermediate-term Earthquake prediction (M8) by
Kossobokov Keilis-Borok
45
M8 algorithm

• This intermediate-term earthquake prediction
  method was designed by retroactive analysis of
  dynamics of seismic activity preceding the
  greatest, magnitude 8.0 or more, earthquakes
  worldwide, hence its name.
• Its prototype (Keilis-Borok and Kossobokov, 1984)
  and the original version (Keilis-Borok and
  Kossobokov, 1987) were tested retroactively. The
  original version of M8 is subject to the on-going
  real-time experimental testing. After twelve
  years the results confirm predictability of the
  great earthquakes beyond any reasonable doubt.
• The algorithm is based on a simple physical
  scheme

46
General scheme
47
Criterion in the phase space

• The algorithm M8 uses traditional description of
  a dynamical system adding to a common phase space
  of rate (N) and rate differential (L)
  dimensionless concentration (Z) and a
  characteristic measure of clustering (B).
• The algorithm recognizes criterion, defined by
  extreme values of the phase space coordinates, as
  a vicinity of the system singularity. When a
  trajectory enters the criterion, probability of
  extreme event increases to the level sufficient
  for its effective provision.

48
Worldwide performance of earthquake prediction
algorithms M8 Magnitude 8.0.
To drive the achieved confidence level below 95,
the Test should encounter four failures-to-predict
in a row.
49
Real-time monitoring ( http//www.mitp.ru or
http//www.phys.ualberta.ca/mirrors/mitp )
50
Reverse Tracing of Precursors (RTP) by Shebalin
Keilis-Borok
51
(No Transcript)
52
(No Transcript)
53
(No Transcript)
54
(No Transcript)
55
(No Transcript)
56
(No Transcript)
57
(No Transcript)
58
Seismic Roulette

• Consider a roulette wheel with as many sectors
  as the number of events in a sample catalog, a
  sector per each event.
• Make your bet according to prediction determine,
  which events are inside area of alarm, and put
  one chip in each of the corresponding sectors.
• Nature turns the wheel.
• If seismic roulette is not perfect
• then systematically you can win! ?
• and lose ?
• If you are smart enough and your predictions are
  effective ------
• the first will outscore the second! ? ? ? ? ? ?
  ? ? ? ?

59
Conclusion Seismic Roulette is not perfect

• Are these predictions useful?
• Yes, if used in a knowledgeable way.
• Their accuracy is already enough for undertaking
  low-key earthquake preparedness measures, which
  would prevent a considerable part of damage and
  human loss,
• although far from the total.
• The methodology linking prediction with disaster
  management strategies does exist (Molchan, 1997).
• There are no luxury of postponing usage of the
  existing data on earthquakes to the benefit of
  population living in seismic regions.
• and the quantitative earthquake prediction
  methodologies are neither unique nor optimal.
  There is a wide horizons of future work and
  challenging questions to answer.