Seismic Hazard Model for the Middle-East Region, Laurentiu Danciu, Swiss Seismological Service, ETH...

Seismic Hazard Model

For Middle-East Region

Laurentiu Danciu

Swiss Seismological Service,

ETH Zurich, Switzerland &

GEM Hazard Modeler

Karin Sesetyan

Mine Demircioglu

KANDILLI OBSERVATORY

and EARTHQUAKE RESEARCH

INSTITUTE,

Istanbul Turkey

EMME Final Meeting

September 30th – October 2nd

Istanbul, Turkey

Regional PSHA Model• Regional seismic hazard assessment

Regional PSHA Model• Harmonization across national-borders

Target

Stability

1. Provide assurance that the numerical hazard results will be stable for the next years (50 years ?)

2. Unless significant new seismic information, which could occur at any time, calls for a major revision

Consensus

What Consensus stands for?

• 1) there is not likely to be "consensus" (as the word is commonly understood) among the various experts and

• 2) no single interpretation concerning a complex earth - sciences issue is the "correct" one.

SSHAC : Recommendations for PSHA: Guidance on Uncertainty and Use

of Experts

Most likely for no consensus there is a consensus!

SHARE Project- DB Stats

• 3 source models• 960 End-Branches• 12 Intensity Measure Types• 7 Return Periods [50 to 10000Years]• Mean, Median and Four Quantile• 130 000 sites

‣ Hazard Maps: 504

‣ Hazard Curves: 9.36 mil

‣ Uniform Hazard Spectra: 5.46mil

‣ Disaggregation: ongoing

Dynamic ModelEMME Project- DB Stats

55

00

0

sites

Overview

• Earthquake Catalog

• Maximum Magnitude

• Seismic Source Models

– Area Source Model

– Fault source Model

– Spatially Smoothed Seismicity

EMME Earthquake Catalog• Historical part (-1900)

• Early and modern instrumental (~2006)

• Harmonized in terms of Mw

Total : 27174 events

EMME Earthquake Catalog

• Seismicity models require a – Declustered earthquake catalog of independent events

– Completeness intervals for estimating the Poissonian (time-independent) earthquake rates.

• Declustering Method. – Windowing approach based on windows provided by Grünt

hal (1985)• Gardner and Knopoff (1974)

– After Declustering: 10524 events

Declustered Earthquake Catalog

– After Declustering: 10524 events

EMME Earthquake Catalog• 18 Completeness super-zones

Completeness plots per super-zones

Completeness plots per super-zones

Completeness plots per super-zones

Maximum Magnitude

• Largest magnitudes that a seismogenic region iscapable of generating.

• Upper-bound magnitude to the earthquakerecurrence (frequency-magnitude) curve.

• Maximum Magnitude assessment (Super-Zones)– Historical seismicity record

– Location uncertainties

– Analogies to tectonic regions

– Added increment (0.30)

Maximum Magnitude

Weighted Mmax

Maximum Magnitude: Sensitivity

Maximum Magnitude: Sensitivity

5%

13%

18%

Yerevan City

Magnitude - DisaggregationMaximum Magnitude = 8.00

aGR = 4.00

bGR = 1.00

Maximum Magnitude: Sensitivity

• Maximum magnitude impacts the activity

computation –if used to anchor the expert

fitting

• 5 to 20% increased hazard values

• Return period dependent

• The pair of Maximum Magnitude

Recurrence rates to carefully be revised

Source Model Logic Tree

Area Source Model

• Classical area source zones based on the tectonic findings and their correlation and up-to-day seismicity

• Derived from seismicity patterns

– Ensure the zonation adequately reflect this pattern

• Surface projection of identified active faults (capable of generating earthquakes)

Model Construction: Phase One

• Country based models

• Phase one:– Overlapping sources at national borders

• [ trying to keep the original information]

– Remove duplicates (the same source defined within countries)

– Eliminate zones too small to be analyzed (spatially smooth seismicity take cares of it)

Model Construction: Phase Two

– Simplify unnecessary or artificial complex zonation

– Reshaping according to the known main seismogenic features (i.e known faults )

– Local experts feedback

– Reconcile different interpretations

– New sources re-defined after technical discussions among the national representatives/local experts

Area Source Model• 143 shallow crustal area source zones,

• 6 for modeling the deep seismicity, and

• 5 complex faults

Source Characterization

• Main Assumptions:

– Homogeneous, declustered catalogue

– Completeness defined for 18 super zones spanning the entire region

– Maximum likelihood approach (Weichert 1984)

– Truncated Guttenberg-Richter Magnitude Frequency Distribution

• 10a – annual number of events of magnitude greater or equal to zero

• b-value

• Truncated at each assigned maximum magnitude

• For each source three magnitude-frequency-distributions were derived

• A Matlab* toolbox was developed

Source Characterization: issues

• Sources with limited number of events

• Sources with less that 15 events were assigned with a default activity rate corresponding to each region

• 30 area source zones with less than 15 events

• Estimation stability achieved for more than 30 events/source

Source Characterization: issues

• Light color shows area sources with less than 15 events

Source Characterization: issues• Automated procedure was constantly under predicting the

occurrence rates of moderate to large magnitudes

Source Characterization: issues• Automated procedure was constantly under predicting the

occurrence rates of moderate to large magnitudes

Source Characterization: issues• Automated procedure was constantly under predicting the

occurrence rates of moderate to large magnitudes

Source Characterization: solution• Expert fitting/adjustments

automated

Source Characterization: solution• Expert fitting/adjustments

automated

bGR-value : Spatial Distribution

bGR-value is between 0.70 to 0.75

bGR-value is between 1.05 to 1.25

Sanity Check: aGR normalized:

• Yellow color shows area sources with very low annual activity per km2

Sanity Check: Seismic Moment

log(Mo) c dMw

c 16.05

d 1.5

Kanamori and Anderson (1975)

Sanity Check: Global Strain Rate

Courtesy of C.Kreemer

Area Sources vs Global Strain Rate

Seismic Moment vs.Global Strain Rate

Source Parameterization

• Depth Distribution (three values and the corresponding weights):

– Active shallow crust

– Nested Deep Seismicity

– Subduction Inslab

• Focal Mechanisms

– Rake Angle values (Aki’s definition)

– Percentage weights

• Ruptures Orientation

– Strike Angle (Azimuth)

– Dip Angle

• Rupture Properties

– Upper and Lower Seismogenic Depth

Complex Fault

Area Source [Single Rupture]

Depth Distribution

Dip-Angle Distribution

• Yellow color shows area sources with

• dip angles smaller than 30o

Source Model Logic Tree

EMME Faults Dataset• Fault source model derived from the faults database collected within WP02

– Total number: 3397 fault segments

– Total Km: 91551km

Fault Sources

• Criteria to select active faults to be used for hazard assessment:– Identified active faults [capable of earthquakes]: Northern

Anatolian Faults, Marmara Faults, Zagros Transform Faults

– At least 0.10mm/year (1m in 1000years - Neocene)

– Maximum magnitude equal to 6.20

– Fully parameterized:• Geometry

• Slip-rates

– Confidence Classes:• Class A: complete information provided by the compiler

• Class B: partial information provided by compiler

• Class C: limited information provided

• Class D: only top trace available

Fault Sources

• Confidence Classes:• Class A (red): complete information provided by the compiler

• Class B (green): partial information provided by compiler

• Class C (blue): limited information provided

Fault Sources-SHARE projects• Class A complete information provided by the compiler

Fault Sources- EMME• Class B partial information provided by the compiler

Fault Sources- EMME

?

Fault Sources- Class C• Class C fault trace and fault type info available

• Maximum magnitude – Estimated from faults size

– Slip rate

• First Slip Rate Estimated as proposed by USGS

• First Slip Rate Estimated as proposed by USGS

15.1

8.5

15.0

<31

5.0

9.2

16.8

11.4

16.86

.8

13.2

9.9

13

13

4

11±5

10±2

6±13±2

25±5

~4

20.0

05

10

15

20

5

5

15

20

Fault Sources- Class C -refinement

By Prof. Asif Khan

Active Faults

Active FaultsHow to characterize the seismic potential of the faults?- Convert slip-rates to seismicity

Fault Source Model Characterization

Procedure:1. Generate a buffer region of 20km

for each fault

Procedure:2. Remove earthquakes within buffer zone

3. Activity on faults computed from slip rates4. Activity on the background – based on the “outside” catalogue

Fault Source Model Characterization

Faults + Background Seismicity

Faults + Removed Earthquakes

3202 earthquakes removedMagnitude range: 4.00 to 7.90

Faults CharacterizationActivity rates are calculated from geologic information:

•Slip rate •Fault length / aspect ratio•Maximum Magnitude

Recurrence Rate Model:•Anderson & Luco (1983) Model 2:

•b-value assumed from the corresponding completeness super zones•Integration from Mmin = 5.00 to Faults Mmax

N2(M ) =d - b

b

æ

èçö

ø÷S

b

æ

èçö

ø÷eb-(Mmax-M -1éë

ùûe-((d /2)Mmax )

Activity Rates - Background

• Smoothed spatially with a variable Kernel

– r : epicentral distance

– di: Variable epicentral distance to next neighbor

nv

• Optimization for distance parameter with

retrospective tests

vsF (r,di ) c(di )(r2d

i

2 )1.5

Kernel Optimization: Retrospective Testing

Optimize kernel using a likelihood tests Split catalog in learning

and target period

Optimize on 5 year target period

Use best likelihood-value to generate model rates

Learning Period Target Period

1000 2002 2007

Activity Comparison

Fault Source Model

Combine seismicity from long term geological observations with observed seismicity

Fault Source Model

Source Parameterization

• Depth Distribution

• Focal Mechanisms

– Rake Angle values (Aki’s definition)

– Percentage weights

• Ruptures Orientation: Strike and Dip Angles

• Rupture Properties

– Upper and Lower Seismogenic Depth

Point Source [Single Rupture]

Simple Fault• Fault Top Trace

• Focal Mechanisms

– Rake Angle values (Aki’s definition)

• Ruptures Orientation: Strike and Dip Angles

• Rupture Properties

– Upper and Lower Seismogenic Depth

24th Sept 2013 Event in Pakistan

15Years Seismicity Mw >= 6.5

2013-09-24 Awaran Pakistan

2013-04-16 East of Khash Iran

2011-10-23 Eastern Turkey

2011-01-18 southwestern Pakistan

2010-12-20 southeastern Iran

2009-01-03 Hindu Kush region Afghanistan

2008-10-05 Kyrgyzstan

2005-12-12 Hindu Kush region Afghanistan

2005-10-08 Pakistan

2004-04-05 Hindu Kush region Afghanistan

2003-12-26 Southeastern Iran

2002-06-22 Western Iran

2002-03-03 Hindu Kush region Afghanistan

2002-02-03 western Turkey

2001-01-26 Gujarat India

2000-12-06 Turkmenistan

2000-11-25 Caspian Sea offshore Azerbaijan

1999-11-12 western Turkey

1999-11-08 Hindu Kush region Afghanistan

1999-08-17 Western Turkey

1999-03-04 Southern Iran

1998-05-30 Hindu Kush region Afghanistan

1998-03-14 Eastern Iran

Before 24th Sept 2013 Event in Pakistan

EMME Results, before the earthquake

Source Model Logic Tree

Spatially Smoothed Seismicity

• Based on the – Up-to-date seismicity

– Declustered catalogue

• Main Assumption:– Earthquake's self-similarity: earthquakes occur at near clusters of

previous smaller earthquakes.

– Derived equally spaced [10 x 10 km] cells

– 53300 non-overlapping cells

– the earthquake rates determined for cells are spatially smoothed using a one Gaussian smoothing kernel Frankel 1995]

– Kernel constant size equals to 25km

Smoothing Algorithms

Source Parameterization

• Depth Distribution (three values and the corresponding weights):

• Focal Mechanisms

– Rake Angle values (Aki’s definition)

– Percentage weights

• Ruptures Orientation

– Strike Angle (Azimuth)

– Dip Angle

• Rupture Properties

– Upper and Lower Seismogenic Depth

Point Source [Single Rupture]

Source Model Logic Tree

How do we weight them?

Summary•Building a regional seismic hazard model is a collective effort•Aim at generating the up-to-date , flexible and scalable database hat will permit continuous update, refinement, and analysis.

•Data will be parameterized and input into the database with a specific format.

Hazard

Software

“Black Box”

INPUT OUTPUT

“Easy Review” Box

Data

Interpretations

Assumptions

Summary•Transparent computational procedure, with all input files available as well as the software packages (Hazard Modeler Toolkit, OpenQuake)•Each dataset has certain degree of completeness, but there is room for improvements;•Specifically,

•The depth information of the events•Maximum magnitude definition•More parameterized faults•Velocities from GPS data

•Revision of all source models•What are the weakness points of each model?

•Road map to the final deliverable

Thank you!