Download 7. probabilistic seismic hazard assessement

Probabilistic Sesmic Hazard Assessment for Chennai
IGC 2009, Guntur, INDIA
PROBABILISTIC SEISMIC HAZARD ASSESSMENT FOR CHENNAI
G. Kalyan Kumar
Research Scholar, Department of Civil Engineering, I.I.T. Madras, Chennai–600 036, India.
E-mail: [email protected]
U. Sreedhar
Formerly Research Scholar, Department of Civil Engineering, I.I.T. Madras, Chennai–600 036, India.
E-mail: [email protected]
G.R. Dodagoudar
Assistant Professor, Department of Civil Engineering, I.I.T. Madras, Chennai–600 036, India.
E-mail: [email protected]
ABSTRACT: The estimation of probabilistic seismic hazard in low seismicity regions such as stable continental regions has
to cope up with the difficulty in identification of active faults and with the low amount of available seismicity data. In this
paper, an attempt is made to carry out probabilistic seismic hazard analysis for low seismicity region like Chennai city, South
India. A new earthquake catalogue for Chennai, with unified moment magnitude scale has been prepared. The standard
Cornell-McGuire method has been used for hazard computation. Seismicity of the area around Chennai city has been
evaluated by defining ‘a’ and ‘b’ parameters of the Gutenberg-Richter recurrence relationship. The study demonstrated that
the hazard is dominated by the distributed local seismicity. The uniform hazard spectra of acceleration have been obtained for
different return periods and compared with the code specified design response spectra.
Seismic hazard is defined as the potential for earthquakeinduced natural phenomena such as ground motion, fault
rupture, soil liquefaction, landslides and tsunami with
adverse consequences to life and built environment at a
specific site (Cornell 1968, Reiter 1990). Seismic Hazard
Analysis (SHA) is the evaluation of potentially damaging
earthquake-related phenomena to which a facility may be
subjected during its useful lifetime. Seismic hazard studies
are needed for the preparation of earthquake loading
regulations, for determining the earthquake loadings for
projects requiring special study, for areas where no codes
exist, or for various earthquake risk management purposes.
This paper outlines the methodology based on the CornellMcGuire approach for probabilistic seismic hazard analysis
(PSHA), commencing from the compilation of a
comprehensive catalogue of earthquakes, proceeding to
processing of catalogue data, selection of seismogenic zones
and Ground Motion Prediction Equations (GMPEs). The
output of the PSHA consists of uniform hazard spectra at the
selected locations of the Chennai city for reference return
periods of 72, 224, 475, 975 and 2475 years.
Srivastava & Ramachandran (1985) and Jaiswal & Sinha
(2007) for the Peninsular India and Ornthammarath et al.
(2008) for the Chennai region, were used. A few historical
earthquake data prior to 1968 and the recent seismicity of the
region after the year 1991 have also been obtained from the
National Earthquake Information Centre (NEIC), USA.
The composite catalogue of the study area spanning from
1798 to 2008 A.D. (210 years) was used for evaluating the
seismicity of the Chennai region between 1000 to 1600 N
and 7700 to 81 00 E (within 300 km radial distance from
Chennai) with a total of 229 earthquake events. From Figure
1, it can be observed that the earthquake catalogue is largely
composed of a significant number of mild (with MW ≈ 3.5),
distant events and a small number of moderate, close events
from Chennai.
NumberofofEarthquakes
Earthquakes.
Number
1. INTRODUCTION
2. PROCESSING OF EARTHQUAKE CATALOGUE
70
60
<100 km
50
100-200 km
40
>200 km
30
20
10
0
3.5-3.99
In order to understand the seismic characteristics of the study
area, earthquake catalogue compiled by Rao & Rao (1984),
4.0-4.49
4.5-4.99
>5.0
MomentMagnitude
Magnitude(M
Moment
(Mw) w)
Fig. 1: Statistics of the Composite Earthquake Catalogue
517
Probabilistic Sesmic Hazard Assessment for Chennai
3. SEISMIC SOURCE ZONING
There have been several attempts to delineate and define the
seismic source zones for the Peninsular India (PI) in the past.
In the first zoning model, the entire circular area (i.e. 300 km
radius with Chennai as centre) has been considered as one
zone based on the dispersion of observed seismicity. This
part of the Tamil Nadu State has mostly been considered as
one seismic source zone (Chandra, 1977). Several other
seismic hazard studies, e.g. Parvez et al. (2003) and Gupta
(2006) have considered a single seismic source zone in this
area, a choice attributable to the low observed seismicity.
4. ANALYSIS OF CATALOGUE COMPLETENESS
For the recurrence relation to be meaningful sufficient number
of samples should be available at all possible magnitude
values. Since the number of samples in a catalogue refers to
the number of earthquakes in a given period of time T,
completeness can be characterized in terms of a magnitude
range and observed interval. No catalogue can be strictly
considered complete for all magnitudes and time period.
Analytical method for finding regional recurrence based on
incomplete catalogue has been developed notably by Stepp
(1972), Kijko & Sellevoll (1989, 1992) and Mulargia & Tinti
(1985). Stepp’s method was used in the present study to find
the completeness period for the Chennai region as depicted
in Figure 3.
The Stepp’s method gives unbiased estimate of mean rate for
occurrences for different magnitude groups. Figure 3 shows
that in the Chennai region for 3.5-3.99, 4.0-4.49, 4.5-4.99
and  5.0 magnitude groups the data is complete for 40, 40,
60 and 210 years, respectively. Table 1 gives the completeness
intervals along with the catalogue completeness periods.
1
3.5-3.99
4.0-4.49
Standard Deviation
A declustering algorithm is then applied to remove the
dependent earthquake events from the catalogue. Due to the
Poissonian assumption of earthquake occurrence intrinsic of
the Cornel-McGuire approach for PSHA, implying that
earthquake events are random and memoryless, foreshocks
and aftershocks have to be removed from the earthquake
catalogue. The declustering algorithm developed by Gardner
& Knopoff (1974), who claimed that foreshock and
aftershock events are dependent on the size of main
earthquake event, has been used. The time and distance
window parameters would be different based on the main
event’s magnitude. This approach is also called as the
dynamic time-spatial windowing method. Seismic events
with magnitude greater than 3.5 are only considered in the
preparation of the earthquake catalogue.
The data collected on the regional seismotectonics (GSI,
2000) and geological setting along with the observed
seismicity has led to the definition of the second seismogenic
scenario comprising of three source zones (SZ1, SZ2 and
SZ3 as in Figure 2).
4.5-4.99
>5.0
0.1
0.01
10
100
1000
Time (year)
Fig. 3: Completeness Analysis Using Stepp’s Method
Table 1: Completeness Interval for the Chennai Region
Magnitude
Completeness
Years
interval (Mw)
interval
3.5–3.99
1968–2008
40
4.0–4.49
1968–2008
40
4.5–4.99
1948–2008
60
1798–2008
210
Mw  5.0
5. RECURRENCE LAW
A recurrence law describes the frequency of occurrence of
earthquakes of a particular magnitude in a given period of
time. The recurrence period of a particular magnitude is
defined as the reciprocal of the mean annual rate of
exceedance of that magnitude. The frequency-magnitude
relationship proposed by Gutenberg & Richter (1954) is the
most widely used recurrence relationship. This is generally
stated in the form:
Fig. 2: Seismic Source Zone Scenario
Log10 (M) = a – bm
518
(1)
Probabilistic Sesmic Hazard Assessment for Chennai
where λM is the mean annual rate of exceedance of
magnitude M, a and b are the constants specific to the source
zone, and these can be estimated by a least square regression
analysis of the past seismicity data. Here, the 10a is mean
yearly number of earthquakes of magnitude greater than or
equal to zero and b describes the relative likelihood of large
and small earthquakes. The source specific values of a and b
are calculated (Figure 4) by grouping the catalogue into
magnitude ranges of say M = 0.5, in the time interval of 10
years. The magnitude ranges considered are: 3.5  Mw 
3.99; 4.0  Mw  4.49; 4.5  Mw  4.99 and Mw ≥ 5.0. The
average number of events per year in every magnitude range
is determined.
7. PROBABILISTIC SEISMIC HAZARD
ASSESSEMENT
CRISIS 2007 Version 1.1, a computer program for computing
seismic hazard, developed by Ordaz et al. (2007) has been
used in this study. The frequency-intensity curves are generated
by computing the annual probability of exceedance for a range
of ground motion intensities. The sources can be modelled as
point sources, line sources or area sources with the possibility of
depth being defined for the line and area sources. Figure 6
shows the mean hazard curves for the horizontal component
of acceleration for different seismic zones.
10
1
Annual Rate of Exceedance
1
Observed Value
0.5
Regression Fit
0
log(λM)
SZ1
SZ2
SZ3
Total Hazard
3
3.5
4
4.5
5
5.5
6
-0.5
0.1
RaghuKanth and Iyengar (2007)
0.01
475 years
1E-3
log(λ M) = 4.74 -1.1M w
R2 = 0.9492
-1
1E-4
1E-3
0.01
0.1
1
PGA (g)
-1.5
Fig. 6: Contribution of Hazard from All Seismic Sources
Magnitude (M w )
Fig. 4: Gutenberg-Richter Parameters
7.1 Uniform Hazard Spectrum
6. ATTENUATION RELATIONSHIPS
The attenuation relationship is a predictive equation relating
the magnitude, distance and the ground motion parameter
such as peak ground acceleration (PGA). Large numbers of
such equations are available as proposed by different authors
for specific regions of the world. However, five different
attenuation relationships are selected in this study and
compared for MW 5.7 Kutch aftershock (2001) and Jabalpur
(1997) recorded strong motion data (Fig. 5).
1
The uniform hazard spectra (UHS) for different reference
return periods (T = 72, 475, 975 and 2,475 years) for rock/
stiff site conditions have been computed using different
attenuation relationships. The spectral acceleration is calculated
for structural periods ranging from 0 to 2 seconds. The outcome
of the current PSHA study, in terms of mean UHS for the
horizontal component of acceleration for different return
periods on rock are plotted along with the Design Basis
Earthquake (DBE) and Maximum Considered Earthquake
(MCE) of the BIS (1893: 2002). These comparative plots are
depicted in Figure 7.
0.5
Raghu Kanth and
Iy engar (2007)
A brahamson and Silva
(1997)
Hw ang and Huo
(1997)
Campbell and
Boz orgnia (2003)
Kutch A f tershock
0.4
Spectral Accleration (g)
PGA (g)
0.1
72 years
224 years
475 years
975 years
2475 years
DBE,BIS(1893),Rock site
MCE,BIS(1893),Rock site
Jabalpur
0.01
0.3
0.2
0.1
0.0
0.001
0.0
10
100
1000
0.5
1.0
1.5
2.0
Structural Period (sec)
Hypoce ntra l Dista nce (km )
Fig. 7: Horizontal Components of UHS for Different Return
Periods
Fig. 5 Comparison of Attenuation Relationships (Mw = 5.7)
519
Probabilistic Sesmic Hazard Assessment for Chennai
7.2 Hazard Maps
REFERENCES
The seismic hazard map in the form of seismic hazard curve
is developed for the Chennai city using Poisson process
model to estimate the probabilities of exceedance of a
particular value of the peak ground acceleration y*, in a finite
time period. For Poisson process, the probability of
exceedance of y*, in a particular time period T years is given
by
Abrahamson N.A. and Silva W.J. (1997). “Empirical
Response Spectral Attenuation Relations for Shallow
Crustal Earthquakes”, Seismological Research Letters, 68:
94–127.
Campbell K.W. and Bozorgnia Y. (2003). “Updated NearSource Ground-Motion (attenuation) Relations for the
Horizontal and Vertical Components of Peak Ground
Acceleration and Acceleration Response Spectra”,
Bulletin of the Seismological Society of America, 93: 314–
331.
Chandra U. (1977). “Earthquakes of Peninsular India, A
Seismotectonic Study”, Bulletin of the Seismological
Society of America, 65: 1387–1413.
Cornell C.A. (1968). “Engineering Seismic Risk Analysis”,
Bulletin of the Seismological Society of America, 58:
1583–1606.
Gardner J.K. and Knopoff L. (1974). “Is the Sequence of
Earthquakes in Southern California, with Aftershocks
Removed, Poissonian?” Bulletin of the Seismological
Society of America, 64: 1363–1367.
GSI (2000). “Seismotectonic Atlas of India and Its
Environs”, Geological Survey of India, Kolkata, India.
Gupta I.D. (2006). “Delineation of Probable Seismic Sources
in India and Neighbourhood by a Comprehensive
Analysis of Seismotectonic Characteristics of the
Region”, Soil Dynamics and Earthquake Engineering, 26,
766–790.
Gutenberg B. and Richter C.F. (1954). “Seismicity of the
Earth and Related Phenomena”, Princeton University
Press, Princeton, New Jersey.
Hwang H. and Huo J.R. (1997). “Attenuation Relations of
Ground Motion for Rock and Soil Sites in Eastern United
States”, Soil Dynamics and Earthquake Engineering, 16:
363–372.
IS (1893: 2002). “Indian Standard, Criteria for Earthquake
Resistant Design of Structures”, Part-I; Bureau of Indian
Standard (BIS), New Delhi.
Jaiswal K. and Sinha R. (2007). “Probabilistic SeismicHazard Estimation for Peninsular India”, Bulletin of the
Seismological Society of America, 97: 318–330.
Kijko A. and Sellevoll M.A. (1989). “Estimation of Seismic
Hazard Parameters from Incomplete Data Files”. Part I:
Utilization of Extreme and Complete Catalogues with
Different Threshold Magnitudes, Bulletin of the
Seismological Society of America, 79: 645–654.
Kijko A. and Sellevoll M.A. (1992). “Estimation of Seismic
Hazard Parameters from Incomplete Data Files”, Part II:
Incorporation of Magnitude Heterogeneity, Bulletin of the
Seismological Society of America, 82: 120–134654.
Mulargia E. and Tinti S. (1985). “Seismic Sample Areas
Defined from Incomplete Catalogues: An Application to
P Y  y*   1  e
 * T
y
(2)
Figure 8 provides the contour plot of PGA values
corresponding to return period of 2475 years for the Chennai
region.
Fig. 8: Contours of Rock Level PGA for Chennai Region
(Return Period = 2475 Years)
8. CONCLUSIONS
The study presented in the paper was to define seismic input
for safety assessment of the structures to be built in Chennai,
based on the detailed PSHA. The PSHA performed for the
PGA (horizontal component) evaluation has predicted low
values of ground shaking for Chennai which are
characteristic of a site whose seismicity is controlled by
weak to moderate earthquakes with sources located at short
distances from the site. The horizontal PGA expected in
Chennai, on stiff ground, with a 10% probability of
exceedance in 50 years (which corresponds to a return period
of 475 years) is 0.125g, whereas that with a 2% probability
of exceedance in 50 years (return period = 2475 years) is
0.187g. The uniform hazard spectra can be used to select the
spectrum compatible acceleration time histories from the
published data base of the actual ground motions.
520
Probabilistic Sesmic Hazard Assessment for Chennai
the Italian Territory”, Physics of the Earth and Planetary
Interiors, 40: 273–300.
Ordaz M., Aguilar A. and Arboleda J. (2007). “CRISIS2007
– Ver. 1.1: Program for Computing Seismic Hazard”,
Instituto de Ingenieria, UNAM, Mexico.
Ornthammarath T. Lai C.G., Menon A. Corigliano M.
Dodagoudar G.R. and Gonavaram K.K. (2008). “Seismic
Hazard at the Historical Site of Kancheepuram in
Southern India”, The 14th World Conference on
Earthquake Engineering, Beijing, 07-132, 1–8.
Parvez I.A., Vaccari F. and Panza G.F. (2003). “A
Deterministic Seismic Hazard Map of India and Adjacent
Areas”, Geophysical Journal International, 155: 489–508.
Raghu Kanth S.T.G. and Iyengar R.N. (2007). “Estimation of
Seismic Spectral Acceleration in Peninsular India”,
Journal of Earth System Science, 116: 199–214.
Rao R.B. and Rao S.P. (1984). “Historical Seismicity of
Peninsular India”, Bulletin of the Seismological Society of
America, 74: 2519–2533.
Reiter L. (1990). “Earthquake Hazard Analysis: Issues and
Insights”, Columbia University Press, New York.
Srivastava H.N. and Ramachandran K. (1985). “New
Catalogue of Earthquakes of Peninsular India during
1839–1900”, Mausam, 36, 351–358.
Stepp J.C. (1972). “Analysis of Completeness in the
Earthquake Sample in the Puget Sound Area and its Effect
on Statistical Estimates of Earthquake Hazard”, Proc. Int.
Conf. Microzonation, Seattle, Washington.
521