SOURCE MODEL OF THE 2010 ELAZIGKOVANCILAR EARTHQUAKE (Mw 6.1) FOR
BROADBAND GROUND MOTION SIMULATION
Mehmet Baykal∗
MEE10509

Supervisor:

Hiroe Miyake∗∗

ABSTRACTOn 8 March 2010, an earthquake of Mw=6.1 occurred in Elazig and Kovancilar in Turkey. This event is
known as the 2010 Elazig Kovancilar earthquake. It caused massive destruction in the rural areas
affected and claimed lives.
We performed the empirical Green's function method to simulate the strong ground motionof this event and the largest aftershock recorded with magnitude Mw=5.5, utilizing strong groundmotion data from strong motion and broadband velocity stations. We then converted these records intoa uniform sampling frequency to carry out the simulation. Amplitude spectral analysis was used to findan estimation of parameters used in the empirical Green’s function method.
The focal mechanism determined by Tan et al. (2011) was used for the simulation of themainshock and the largest aftershock. The best source model was estimated by fitting the synthetic
acceleration, velocity and displacement to the observed seismograms.
The obtained size of the estimated strong ground motion generation area was calculated as
2.80 km in length by 2.00 km in width for both the mainshock and the aftershock. The rupture starting
point was found to be at northeast and southwest of the estimated strong ground motion area for themainshock and the largest aftershock, respectively. We determined the scaling parameter for themainshock as 2 and the stress drop correction factor is 3.5. The determined scaling parameter for thelargest aftershock is 2 and the stress drop correction factor is 2.5.
The above analyses suggest that the stress drop correction factor of the strong motion
generation area for the mainshock is 1.4 times higher than that for the largest aftershock. The 2010
Elazig Kovancilar earthquake is characterized by shallow depth rupture with high stress drop. This fact
is considered to be one of the source effects to generate severe ground motion for the damaging
earthquake.

Keywords: Elazig Kovancilar earthquake, empirical Green’s function method, strong motion
generation area.
1. INTRODUCTION
The 2010 Elazig Kovancilar earthquake (Mw=6.1) at 02:32:30 (GMT) on 8 March, 2010 occurred at
the east part of the East Anatolian Fault Zone (EAFZ) in Turkey. The shaking was felt around Elazig,
Bingol, Tunceli, Mus, Diyarbakir, and Erzurum cities. The earthquake caused 42 death, 137 injured,
1695 heavily destroyed houses, and 978 partially destroyed houses around Elazig and Bingol cities
based on report of Disaster and Emergency Management Presidency of Turkey (DEMP).

∗

Disaster and Emergency Management Presidency, Turkey.
Earthquake Research Institute, University of Tokyo, Japan.

∗∗1Earthquake Department at DEMP reported the magnitude of this earthquake as ML=5.8 and Mw=6.0,
its epicentral coordinates as 38.7665N, 40.0712E which was located in Elazig city in Kovancilar
prefecture and with depth of about 5 km. According to the Centroid Moment Tensor solution of the
Global GMT Project, this earthquake
has a compressional axis on the strikeof 228°, dip with 83° and rake angle of-21°. The distribution of theaftershocks indicates that the main fault
should be about 25 – 30 km long and
12 – 15 km wide (Figure 1). On thesame day, another earthquake occurredat 07:47 (GMT) and the Earthquake
Department reported the epicenter
coordinates of the second earthquake as
38.7355N , 40.0090E which was
located in Elazig – Palu, and its
magnitude as ML=5.6 and the depthof 5 km. According to the Centroid
Moment Tensor solution of the Global
Figure 1. Location of the Kolazig-Kovancilar
CMT Project, this earthquake had aearthquake is denoted by the black star, the red andcompressional axis on the strike ofgreen dots are the aftershocks. The yellow triangles
231°, dip with 78°, and rake angle ofare the seismic stations.
-11°.
According to the recent developments based on waveform inversion of strong groundmotion data for estimating the rupture process during large earthquakes, strong ground motion isrelated to the slip heterogeneity rather than the average slip over the entire rupture area as studied by
Irikura and Miyake (2011).The strong ground motions at specific sites near the fault can be estimatedby using the empirical Green’s function technique. In order to calculate nonlinear dynamic analysis of
structures which are needed to design earthquake-resistant buildings, bridges and nuclear power plant,
this kind of techniques are used effectively. In addition, most strong motion predictions in earthquake
hazard analyses have been made by using empirical attenuation-distance curves for peak groundacceleration (PGA), peak ground velocity (PGV), and response spectra. This information is defined
only by magnitude and fault geometry. However, ground motions which caused damage aresometimes characterized by rupture directivity pulses like the 1995 Kobe and the 1999 Izmit
earthquakes.
2. DATAIn this study, we used acceleration data that are recorded by
National Strong Ground Motion Network (NSGMON) being
operated and maintained by the Disaster and Emergency
Management Presidency (DEMP), a governmental agency inTurkey. We also used velocity data recorded by Kandilli
Observation and Earthquake Research Institute (KOERI)
managed by Bogazici University
We selected two events. The first one is themainshock of the 2010 Elazig Kovancilar Earthquake (Mw=6.1)
and the other one is the largest aftershock (Mw=5.5. In addition,
we selected another aftershock in order to use as an element
earthquake (Mw=4.8) in empirical Green’s function method by
Tan et al. (2011). We used four acceleration data for themainshock which were retrieved from the stations nearest to themainshock; these stations are BNG, DYR, ERC, and PAL. The

2

Figure 2. Epicentral location of
the mainshock, largest aftershockand location of the stations.

records from the broadband velocity stations were not utilized since these records were clipped and forthis reason ERZN and DYBB records for the mainshock cannot be used for the computation of the
EGFM. As for the largest aftershock, the data used were from records of the stations BNG, PAL and
DYBB. For the element earthquake, records from BNG, PAL and ERC stations were used. Figure 2
shows the station distribution.
.
3. THEORY AND METHODOLOGYOne of the most effective methods for simulating strong ground motion that comes from a large
earthquake is to use observed records from small earthquakes occurring around the source area of alarge earthquake. Actual geological structure from a source to a site is generally more complex thanthat assumed in theoretical models. Actual ground motion is complicated as well not only by refraction
and reflection due to layer interfaces and ground surface but also by scattering and attenuation due tolateral heterogeneities and inelastic properties in the propagation path. However, main approach forthis purpose is to estimate strong ground motion for a large earthquake using the records of small
earthquakes which are considered as an empirical Green’s function (EGF) by Irikura (1986) andanother study by Irikura and Kamae (1994).
The empirical Green’s function method takes in on two scaling relations between a large
and a small earthquake. They are, a) scaling relations of source parameters, b) scaling relations ofsource spectra. In the first scaling relations, fault parameters studied by Kanamori andAnderson (1975) are expressed by the Eq(1):L W
T M o
=
= =


l
w τ
 mo 

1

3

= N,

(1)
(1

where L and l are fault length, W and w are fault width, T and τ are slip duration time, Mo and mo areseismic moment, and D and d are fault slip for small and large earthquakes, respectively. The scaling
is based on the idea of size independent stress-drop. The second scaling relations are represented bythe ω-2 source spectra scaling model studied by Aki (1967) and Brune (1970).
Then the spectral relationship between large and small events becomes Eq. (2) and (3)UoAoMo= CN ,== CN 3 ,
(2)
(3)
ao
uo
mo
where, Uo, uo, Ao and ao are flat levels of displacement spectra and flat level of acceleration spectra
for large and small events(a)(b)
respectively as shown in Figure 3.
The same figure shows thedisplacement and acceleration source
spectra for different sized events
predicted by the ω-2 model. WhereUo and uo
are flat levels ofdisplacement
spectraatlowfrequencies, fcm and fca are cornerfrequencies and Ao and ao are the flatlevels of acceleration spectra at highfrequencies between the cornerfrequency and the cut-off frequency

Figure 3. The schematic figures (a) displacement
amplitude spectra and (b) acceleration amplitude spectra.

3.1 Formulation for the Simulation
To perform the simulation of the strong ground motion from the large event using the record of a small
event as an empirical Green’s function, primarily the need to determine the parameters for C and N

3which are defined in relations from the Eq. (2) and (3):NNr
F ( t − t ij ) ∗ ( C ⋅ u ( t )),j = 1 rij

U (t ) = ∑ ∑i =1F ( t ) = δ ( t − t ij ) +1( N −1 ) n '

(4)
1

∑ [

t ij =

δ {t − t ij −rij − ro

β

+

ξ ij
Vr

,

(5)

( k − 1) T}].
( N − 1) n '(6)
1 k =1)eeObserved record from a small event is regarded as an empirical Green’s function, and it issummed by following Eq. (4) with time delay according to the scaling law and fault rapture process.
The formulation for the EGF method by Irikura (1983; 1986) is based on the deterministic kinematicn ' (1 −( k −1 )( N −1 ) n 'Figure 4. Schematic illustrations of the empiricalGreen's function method (left of the figure) andfiltering function (right of the figure) used in thisstudy.

source model. Ground motion from anearthquake can be expressed as aspace-time convolution of slip distribution
on the source effect with propagation patheffect.
The source effect of this model
is characterized by five parameters in the
Eq. (4) and (5): fault length (L and l), fault
width (W and w), final offset (r and rij)
(slip), rise time (t and tij) (slip duration),and rupture velocity (Vr). U(t) is thesimulated waveform for the large event,u(t) is the observed waveform waveform
for the small event, N and C

are the ratios of the fault dimensions and stress drops between the large and small events, respectively,
and the * indicates convolution. In the Eq. (6), F (t) is the filtering function (correction function) toadjust the difference in the slip velocity time functions between the large and the small events.
β and Vr are the S-wave velocity near the source area and the rupture velocity on the fault
plane, respectively. T is the rise time for the large event, and defined as duration of the filteringfunction F (t). It corresponds to the duration of slip time function on sub fault from the beginning to
the time before the tail starts. n’ is an appropriate integer to weaken artificial periodicity of n, and toadjust the interval of the tick to be the sampling rate.
4. RESULTS AND DISCUSSION
For the largest aftershock we determined the value of C equaled to 2.5 and N equaled to 2, thus thepossible estimated strong ground motion generation area of the fault was 2 x 2 (Table 1). For this, weTable 1. Calculated scale parameters N andstress drop correction factor C values for themainshock and the aftershock.

Mainshock
The largest
aftershock
Figure 5. Source parameters of the mainshockand the largest aftershock; the black dots
represent the rupture starting points.

4

fcm
(Hz)
0.51

fce
(Hz)
0.73

C

N

3.5

2

0.53

0.73

2.5

2

projected 4 cells for the aftershock andthe rupture starting point was best
located at cell (2, 2) this was provenby the good fit agreement of theobserved records and the synthesize
motion, which is shown in Figure 5.
Figures 6 and 7 compare the observed
waveform and synthesized motions.
We compared our results tothe scaling relationship of strong
motion generation area to seismic
moment (Miyake et al., 2003). Our
analysis shows that the largest
aftershock lies on the same estimatedstrong ground motion area.
Figure 6. Comparison of observed and synthetic
waveforms for the mainshock.
While the mainshock shows it
generated a relatively larger seismic
moment in comparison to the earthquakes
shown in the scaling of the strong motion
generation area to seismic moment as shownin Figure 8 (a). Additionally, Figure 8(b)shows the comparison of our results to thescaling relationship of rise time and seismic
moment. It suggests that the aftershockoccupies the same estimated strong groundmotion area. On the other hand, the rise of
the strong motion generation area for themainshock was shorter than the empiricalscaling relationship.

Figure 7. Comparison of observed and synthetic
waveforms for the largest aftershock.

Figure 8. The left graph indicates the scaling between strong motion generation area andseismic moment. The right graph shows the scaling between rise time and seismic moment(Miyake et al. 2003).

5

The mainshock generated seismic moment from the smaller part of the fault plane with a focal depthof 5 km. This might be the reason for the massive destruction caused by the 2010 Elazig Kovancilar
earthquake. Another possible reason why we obtained a M6-class earthquake where the absence of any
seismic activity recorded in the region.

5. CONCLUSIONSIn this study, we simulated ground motion of the mainshock (Mw =6.1) and that of the largest aftershock(Mw =5.5) for the 2010 Elazig Kovancilar earthquake using the empirical Green’s function method. For
the simulation, an aftershock with the magnitude Mw =4.8 was selected as an element earthquake. We
utilized the data from four acceleration stations and two broadband velocity station records. Using thefour strong motion records at the four stations, we calculated the source parameters of the mainshock.
The size of strong motion generation area for the mainshock is found to be 2.8 km in length by 2.0 km inwidth with the rupture starting point at the northeast bottom of the estimated strong ground motion
generation area with a depth 5 km and propagated from deep to south-westward with the velocity
representing 80% of shear wave velocity. Then we compared the observed records and synthesized
motions between acceleration, velocity, and displacement data. The comparison has a good agreement
to all the stations used except for the ERC station. We do not have any information about soil condition
around the station exactly. However, Erzincan city is located near the Firat river. So, the ERC station
might be influenced by some effects of the near surface soil. For this station also, we opted to use ERZN
velocity record as an element earthquake. The distance between these two stations is approximately 30
km.
We also simulated the largest aftershock of the Elazig Kovancilar earthquake using three
acceleration records and broadband velocity records. The size of the strong motion generation area forthe largest aftershock is determined at 2.8 km in length by 2.0 km in width in which the rupture
starting point is at southwest bottom part of the estimated strong ground motion generation area
towards the northeast with a depth of 7 km. The estimated strong ground motion generation area islocated southwest of the mainshock and 4 km away from its epicenter. The above analyses suggest thatthe stress drop correction factor of the strong motion generation area for the mainshock is 1.4 times
higher than that for the largest aftershock. The 2010 Elazig Kovancilar earthquake is characterized byshallow depth rupture with high stress drop. This fact is considered to be one of the source effects togenerate severe ground motion for the damaging earthquake.
AKNOWLEDGEMENT
I would like to express my deepest gratitude to my advisor Dr. Toshiaki Yokoi for giving me valuableadvises and suggestions.
REFERENCES
Aki, K., 1967, J. Geophys. Res., 72, 1217-1231.
Irikura, K., 1986, Proc. 7th Japan Earthq. Eng. Symp., 151–156,
Irikura, K. and Kamae, K., 1994, Annali Di Geofisica, Vol. XXXVII, N6, 1721-1743.
Irikura, K. and Miyake H., 2011, Pure and Applied Geophys., 168, 85-104.
Brune, J. N., 1970, J. Geophys. Res., 75, 4997-5009.
Kanamori, H. and Anderson, D., L., 1975, Bull. Seism. Soc. Am., 65, 1073-1095.
Miyake, H., Iwata T., and Irikura K., 2003, Bull. Seism. Soc. Am., 93, 2531–2545.
Tan, O., Pabuccu Z., Tapirdamaz M. C., Inan S., Ergintav S., Eyidogan H., Aksoy E., and Kuluozturk
F., 2011, Geophys. Res. Lett., 38, L11304, doi: 1029/2011GL047702.

6