Crustal Structure in Southern Korea from Joint ... - GeoScienceWorld

Bulletin of the Seismological Society of America, Vol. 95, No. 4, pp. 1516–1534, August 2005, doi: 10.1785/0120040080

Crustal Structure in Southern Korea from Joint Analysis of Teleseismic Receiver Functions and Surface-Wave Dispersion by Sung-Joon Chang and Chang-Eob Baag

Abstract We estimated crustal structures under 18 broadband stations in southern Korea by combining receiver functions and surface-wave dispersion with the genetic algorithm (GA). Estimated crustal structures were analyzed together with previously determined structures under four stations (GKP, INCN, SNU, and TJN) in Chang et al. (2004). The trend of Moho depths estimated from the GA inversion generally coincides with the surface topography, ranging from 26 km to 36 km in the inland. However, the Moho depth distribution does not agree with the topography in the region around the Chugaryeong fault, which extends approximately north-northeast– south-southwest in the central Korean Peninsula. The shallow Moho depth under this region may be related to consequential crustal thinning processes along the fault caused by extensional tectonic movements. Another discrepancy is found in the Gyeongsang basin formed in a retroarc setting by the subduction of the Izanagi Plate in the early Cretaceous. A thick crust observed in the basin may be caused by two factors—maturity of the basin and underplating of magma materials. Average crustal velocities vary from 6.02 km/sec to 6.51 km/sec in southern Korea. This variation indicates that crustal structures in southern Korea involve diverse velocity profiles that change rapidly with distance. Remarkably, a clear velocity discontinuity is observed at the depth range of 8–10 km under several stations. Introduction Crustal structure is a basic and important subject in seismology because it is often required as a priori information for various geological and geophysical research. It can be estimated from various geophysical data acquired on the surface of the Earth. In particular, seismic data are most useful for the reconstruction of fine crustal structures. However, several obstacles have prevented estimation of the crustal structure from seismic data in southern Korea, namely, a lack of data due to low seismicity and no available broadband seismographs until the mid-1990s. Therefore, previous studies on the crustal structure in southern Korea were restricted to travel-time inversions (e.g., Kim and Kim, 1983; Kim, 1995). There might be, however, accuracy problems in picking phases and determining source parameters in these previous studies, because of low signal-to-noise ratios (SNRs) in seismic data acquired by sparsely distributed seismic networks. In addition, most such data were from analog-type instruments not equipped with Global Positionig System (GPS) time measurement. All the results in the previous studies were one-dimensional (1D) crustal models. Since 1995, broadband seismographs have been installed at over 20 stations in southern Korea; thus, we have been able to estimate the crustal structure more accurately using broadband waveforms than was possible with the pre-

vious results derived by the travel-time inversions. Among various waveform analyses, we have adopted the receiver function analysis to estimate the crustal structure for following reasons. First, the receiver function analysis can be effectively applied in low-seismicity regions such as southern Korea because it utilizes teleseismic data. Second, a preliminary 3D crustal structure in southern Korea can be constructed by summing up all the local crustal structures under the more than 20 stations. The tomography analysis, a standard in estimating 2D or 3D crustal structures, can be hardly utilized in southern Korea owing to the low seismicity. As an alternative, large-scale refraction or reflection explorations for the crustal structure estimation can be utilized, but they cost a lot. Therefore, the receiver function analysis is the most useful and practical tool to be applied to construct a rough 3D crustal structure in southern Korea. It is well known that there is a velocity–depth trade-off that gives rise to a model nonuniqueness problem in resolving the crustal structure, since the receiver function does not include information on absolute travel times of seismic phases, but rather relative travel times (Ammon et al., 1990). ¨ zalaybey et Previous researchers (e.g., Last et al., 1997; O al., 1997; Julia` et al., 2000) have combined data sets of receiver functions and surface-wave dispersion measure-

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Crustal Structure in Southern Korea from Joint Analysis of Teleseismic Receiver Functions and Surface-Wave Dispersion

ments when estimating subsurface structures to overcome the nonuniqueness problem. The two data sets complement each other since the receiver functions are sensitive to shearwave velocity contrasts in layered structures, while the surface-wave dispersion estimates are sensitive to averages of shear-wave velocities. In addition to this, we adopted the genetic algorithm (GA), a global optimization technique, which has following advantages on the linearized matrix inversion in common use. The GA does not strongly depend on an initial velocity model, because it is performed with many initial velocity models randomly generated within prescribed velocity ranges. It should be useful in regions such as southern Korea where there is little a priori information about local velocity structures. In addition, we can obtain model parameter statistics by performing the GA inversion several times with different initial models to provide a quantitative measure of the quality of the result. We applied this technique to data recorded at 18 seismic stations in southern Korea. We performed the joint inversion five times with randomizing seed values to verify the stability of estimated crustal structures. Finally, we presented crustal structures under 18 seismic stations in southern Korea and analyzed the results together with previously determined structures under four stations, GKP, INCN, SNU, and TJN, specified in Chang et al. (2004).

Data Sets We utilized digital data from almost all the broadband seismic stations (Table 1) in southern Korea except for stations located adjacent to others. Locations of the broadband seismic stations are shown on a simple geologic map of southern Korea in Figure 1. The geology of southern Korea consists of two Archaean to Proterozoic massifs (the Gyeonggi massif to the northwest and the Yeongnam massif to the southeast) separated by a fold belt (the Okcheon belt) with an N40⬚E trend. A Cretaceous sedimentary basin (the Gyeongsang basin) lies on the southeastern part of the Yeongnam massif. The Imjingang belt is an east–westtrending fold-and-thrust zone consisting of metasedimentary rocks and volcaniclastics (Devonian–Carboniferous), underlain unconformably by Proterozoic basement rocks (Chough et al., 2000). Receiver Functions Receiver functions are formed by deconvolving a vertical component of a teleseismic P wave from its horizontal components (Langston, 1979). High frequencies are excluded by using a Gaussian filter; a water-level parameter is used for deconvolution stability (Langston, 1979; Ammon, 1991). We set the water-level value to 0.01, and the parameter a of the Gaussian filter to 2.5, which gives an effective high-frequency limit of about 0.5 Hz in the P-wave data. The deconvolution process was performed by spectral division. We also utilized true amplitudes of the receiver func-

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tions without normalization to obtain information about shallow velocity structures (Ammon, 1991). We assigned a P-wave incident angle at the base of the model according to the epicentral distance of each station as an input parameter in the computational process (Ben-Menahem and Singh, 1981). We could investigate lateral heterogeneity or dipping layered structures by analyzing the receiver functions obtained from various backazimuths at a single station (e.g., Langston, 1979; Zhang and Langston, 1995; Baker et al., 1996). However, we assumed a horizontally layered velocity model for the local crustal structure, because the fact that most transverse receiver functions have small amplitudes means that lateral heterogeneity or dipping layered structures are rare in the crustal structure. The transverse receiver functions at only two stations, HDB and ULL, have variations in amplitude and polarity as a function of backazimuth, implying the existence of dipping layers. Based on Cassidy (1992), we estimated the crustal structures under the two stations using the receiver functions with tight bounds of less than 10⬚ in both the backazimuth and the epicentral distance. The strike direction of a dipping layer that could be predicted by the variation of the transverse receiver functions was chosen as the direction of backazimuth of the receiver function because modeling radial receiver functions along the strike of a planar dipping structure with the flat-layered assumption can produce a reasonable solution (Zhang and Langston, 1995). Most of the earthquakes used for receiver function estimations occurred to the south or southeast of Korea at teleseismic distances and with magnitudes larger than or equal to Mw 6.1. On the other hand, earthquakes, used for the receiver function estimations at stations CHJ and KWJ, occurred to the west of Korea with magnitudes larger than or equal to Mw 5.9. We stacked receiver functions with the backazimuth difference less than 25⬚ and with the epicentral distance difference less than 10⬚. Earthquakes used for the receiver functions or phase velocity estimations are listed in Table 2; earthquakes and computational parameters associated with each station are specified in Table 3. Surface-Wave Dispersions Surface-wave dispersions are less sensitive to rapid vertical variations or discontinuities of velocity in the subsurface structure than the receiver functions; however, they are useful for obtaining averages of shear-wave velocities in the crust. Phase velocities usually increase monotonically with period, while group velocities have local minima over a frequency band near the Airy phase. Therefore, the phase velocities of surface waves are more sensitive to changes in shear-wave velocity of the subsurface structure than the group velocities. A conventional two-station method was employed to estimate Rayleigh-wave phase velocities for the period range of 10–25 sec with a 5-sec interval. Each station pair is on

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S.-J. Chang and C.-E. Baag

Table 1 List of Broadband Seismic Station Locations Station Name

BGD BRD CHC CHJ CHNB DGY GKP GSU HDB HKU HSB INCN KAN KSA KWJ NPR PUS SES SNU TJN ULC ULL

Latitude

Longitude

Elevation (m)

Network*

34.1569⬚N 37.9743⬚N 37.7775⬚N 36.8730⬚N 38.2685⬚N 37.6904⬚N 35.8863⬚N 35.1521⬚N 35.7307⬚N 36.6102⬚N 36.5525⬚N 37.4833⬚N 37.7525⬚N 38.5926⬚N 35.1599⬚N 36.0395⬚N 35.1010⬚N 36.7893⬚N 37.4509⬚N 36.3775⬚N 36.9918⬚N 37.4736⬚N

126.5575⬚E 124.7160⬚E 127.8145⬚E 127.9748⬚E 127.1185⬚E 128.6742⬚E 128.6083⬚E 128.0991⬚E 129.4012⬚E 127.3602⬚E 126.6380⬚E 126.6333⬚E 128.8893⬚E 128.3538⬚E 126.9910⬚E 126.8685⬚E 129.0338⬚E 126.4531⬚E 126.9566⬚E 127.3638⬚E 129.4133⬚E 130.9008⬚E

5.7 51.2 245.0 227.0 193.3 791.0 46.5 ⳮ12.1 84.7 67.0 ⳮ7.5 420.0 25.9 102.6 213.0 19.1 69.2 99.1 161.1 52.0 77.1 218.3

KIGAM KIGAM KMA KMA KIGAM KMA KIGAM KIGAM KIGAM KIGAM KIGAM KMA KMA KIGAM KMA KIGAM KMA KMA KIGAM KIGAM KMA KMA

Remark

Borehole (141⬚)† Borehole (178⬚)† Borehole (156⬚)† Closed in 2001

Closed in 2001

Closed in 2000

*KIGAM (Korea Institute of Geoscience and Mineral Resources) and KMA (Korea Meteorological Administration) are institutions operating seismic stations. † Borehole seismometers were installed at stations GSU, HDB, and HSB. Angles in parentheses are adjustment values to fit the two horizontal components to the north and east directions.

the path of a great circle. We calculated phase velocities using a cross-correlation technique for successively narrowband-filtered seismograms in the time domain, which is similar to the multiple filter technique of Dziewonski et al. (1969). The path length between two stations was determined by the difference in radial distances of the stations from an event (Last et al., 1997). At each station, computed phase velocities were averaged for each period. Average phase velocities at the stations are shown in Figure 2 for five different geologic areas. We used phase velocity data as constraints in adjusting velocity models obtained by the GA inversion with the receiver function. We excluded any velocity model if one of the phase velocities calculated from a GA velocity model showed a discrepancy from the corresponding observed phase velocity of 0.1 km/sec or greater. If not, the velocity model was accepted without weighting in the GA inversion process.

Inversion Method Figure 1.

Distribution of 22 seismic stations plotted on a simplified geologic map of southern Korea. Stations are indicated by solid inverted triangles, and geologic areas are denoted in italic type. A thick straight line in the upper central part of the map illustrates the Chugaryeong fault.

We followed the GA inversion process proposed by Chang et al. (2004). During the GA inversion, tens of initial models are randomly generated by a Monte Carlo technique, and individual models are paired, based on their fitness values. Models with higher fitness values are more likely to get selected than those with lower fitness values. Then, an ex-


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Table 2 Event Source Parameters Date (mm/dd/yy)

Time (UT) (hh:mm:ss.s)

Latitude

Longitude

03/14/99 03/28/99 05/08/99a 05/08/99b 06/02/99 06/15/00 07/16/00 07/20/00 08/04/00 08/07/00 08/28/00 09/10/00 10/03/00 10/06/00 11/13/00 11/16/00a 11/16/00b 11/17/00 12/09/00 01/10/01 01/16/01 02/24/01 03/19/01 03/23/01 03/24/01 04/04/01 04/14/01 04/17/01 05/25/01 06/05/01 06/14/01 06/15/01 08/13/01 09/01/01 10/19/01 11/20/01 11/23/01 11/24001 12/23/01 01/13/02 02/05/02 02/28/02 03/04/02 03/05/02 03/17/02 03/25/02 03/31/02 04/12/02 04/16/02 07/08/02 08/10/02 08/20/02 09/13/02 09/20/02 10/10/02 11/02/02 12/12/02 01/20/03 02/19/03 02/24/03

11:31:05.6 03:39:42.1 23:11:45.9 23:17:18.4 09:12:23.3 11:10:46.2 03:57:45.6 18:39:18.8 21:13:02.7 14:33:55.9 15:05:47.9 08:54:46.0 04:13:30.5 04:30:19.1 15:57:21.6 04:54:56.7 07:42:16.9 21:01.56.5 09:51:00.0 16:02:44.2 13:25:09.8 07:23:48.7 05:52:15.8 11:30:10.5 06:27:53.5 07:44:11.2 23:27:26.6 21:54:02.6 00:40:50.6 09:00:05.3 02:35:25.8 06:17:45.3 20:11:23.4 13:08:11.9 03:28:44.4 21:08:18.4 20:43:03.5 07:10:31.6 22:52:54.3 14:10:56.5 13:27:24.6 01:50:48.9 20:21:21.4 21:16:09.1 00:26:31.6 14:56:33.8 06:52:50.4 04:00:23.7 22:52:40.8 19:01:51.2 12:47:35.4 10:59:32.0 22:28:29.4 15:43:35.4 10:50:20.5 01:26:10.7 08:30:42.7 08:43:06.0 03:32:36.3 02:03:41.4

37.5⬚N 37.5⬚N 37.7⬚N 36.2⬚N 35.9⬚N 29.37⬚N 7.75⬚S 36.51⬚N 48.79⬚N 7.02⬚S 4.11⬚S 24.01⬚N 40.28⬚N 35.46⬚N 42.49⬚N 3.98⬚S 5.23⬚S 5.50⬚S 36.5⬚N 57.08⬚N 4.02⬚S 1.27⬚N 4.03⬚S 44.07⬚N 34.08⬚N 5.18⬚S 30.09⬚N 51.24⬚N 44.27⬚N 6.88⬚S 24.51⬚N 18.83⬚N 41.05⬚N 47.36⬚N 4.10⬚S 6.88⬚S 36.39⬚N 36.7⬚N 9.61⬚S 5.6⬚5S 5.35⬚S 5.69⬚S 28.51⬚N 6.03⬚N 38.1⬚N 36.06⬚N 24.28⬚N 35.96⬚N 40.5⬚N 35.9⬚N 35.1⬚N 30.99⬚N 13.04⬚N 1.68⬚S 1.76⬚S 2.82⬚N 4.79⬚S 10.49⬚S 53.65⬚N 39.61⬚N

130.4⬚E 130.2⬚E 130.5⬚E 130.5⬚E 129.3⬚E 132.08⬚E 150.92⬚E 140.98⬚E 142.25⬚E 123.36⬚E 127.39⬚E 121.53⬚E 143.12⬚E 133.13⬚E 144.76⬚E 152.17⬚E 153.10⬚E 151.78⬚E 130.0⬚E 153.21⬚W 101.78⬚E 126.25⬚E 128.02⬚E 148.05⬚E 132.53⬚E 132.37⬚E 141.77⬚E 179.78⬚W 148.39⬚E 146.39⬚E 122.03⬚E 146.98⬚E 142.31⬚E 142.52⬚E 123.91⬚E 128.92⬚E 71.51⬚E 129.9⬚E 159.53⬚E 151.07⬚E 151.25⬚E 151.26⬚E 143.32⬚E 124.25⬚E 124.3⬚E 69.32⬚E 122.18⬚E 69.42⬚E 128.5⬚E 129.6⬚E 123.4⬚E 141.97⬚E 93.07⬚E 134.23⬚E 134.30⬚E 96.09⬚E 153.28⬚E 160.77⬚E 164.64⬚W 77.23⬚E

Depth (km)

10.0 10.0 47.1 10.0 648.5 16.0 34.8 33.0 10.0 33.0 33.0 30.0 33.0 33.0 28.0 35.0 33.0 33.0 50.0 33.0 10.0 33.0 33.0 10.0 32.1 33.0 38.0 10.0 33.0 33.0 106.5 16.0 43.6 39.0 40.2 33.0 31.0 8.0 32.8 10.0

9.0 21.0 10.0 10.0 30.0 34.0 33.0 19.0 11.0

Magnitude

D (deg)

BAZ (deg)

Rayleigh Wave Phase Velocity

ML 3.2 ML 3.0 ML 3.1 ML 3.1 ML 3.4 MW 6.1 MW 6.6 MW 6.0 MW 6.8 MW 6.5 MW 6.8 MW 5.8 MW 6.3 MW 6.7 MW 6.0 MW 8.0 MW 7.8 MW 7.8 ML 3.7 MW 7.1 MW 6.8 MW 7.1 MW 6.5 MW 6.0 MW 6.8 MW 6.4 MW 6.0 MW 6.0 MW 6.7 MW 6.4 MW 5.9 MW 6.0 MW 6.4 MB 5.7 MW 7.5 MW 6.2 MW 6.0 ML 4.1 MW 6.8 MW 6.3 MW 6.6 MW 6.2 MB 5.6 MW 7.5 ML 3.9 MW 6.1 MW 7.1 MW 5.9 ML 3.9 ML 3.8 ML 4.0 MW 6.1 MW 6.5 MW 6.4 MW 7.6 MW 7.4 MW 6.6 MW 7.3 MW 6.6 MW 6.4

1.6 1.6 1.7 5.3 2.4 6.7 47.9 9.3 15.7 43.1 40.5 14.0 12.1 3.4 13.2 45.8 48.0 47.3 2.8 54.7 47.2 35.9 40.7 15.9 5.2 43.2 14.0 39.9 16.2 47.4 12.5 24.5 12.7 14.9 40.7 42.5 44.4 2.6 54.1 47.3 46.7 47.4 15.9 31.1 3.4 45.9 13.1 45.9 3.3 2.2 3.8 13.6 37.8 38.4 39.1 44.0 47.0 56.1 48.4 40.4

70 102 93 260 167 154.8 149.8 93.6 34.0 188.1 181.6 209.6 68.2 115.9 62.7 149.6 146.9 148.9 49 40.7 215.1 184.0 177.6 58.2 116.8 173.2 113.2 51.3 57.3 152.5 200.9 133.7 59.8 41.1 187.5 180.7 288.5 63 144.2 148.4 151.5 146.9 118.4 187.7 292 287.9 204.1 287.2 23 104 250 111.3 242.8 169.6 169.3 229.2 143.9 141.4 47.4 290.6

O O O O O O O O O

Receiver Function

O O O O O O O

O O O

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

O O O

O O

O (continued)

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Table 2 Continued Date (mm/dd/yy)

Time (UT) (hh:mm:ss.s)

Latitude

Longitude

03/14/03 03/17/03 03/22/03 03/25/03 03/30/03 04/17/03 05/05/03a 05/05/03b 05/26/03a 05/26/03b 06/07/03

07:06:13.3 16:36:17.3 20:38:41.0 02:53:25.0 11:10:52.8 00:48:38.5 15:50:08.4 23:04:45.6 19:23:27.9 23:13:29.7 00:32:45.5

0.41⬚S 51.27⬚N 35.0⬚N 8.29⬚S 37.8⬚N 37.53⬚N 0.22⬚N 3.72⬚N 2.35⬚N 6.76⬚N 5.10⬚S

132.95⬚E 177.98⬚E 124.6⬚E 120.74⬚E 123.7⬚E 96.48⬚E 127.35⬚E 127.95⬚E 128.86⬚E 123.71⬚E 152.5⬚E

Depth (km)

33.0 33.0 33.0 14.0 123.6 56.0 31.0 565.8 33.0

Magnitude

D (deg)

BAZ (deg)

MW 6.3 MW 7.0 ML 4.9 MW 6.5 ML 5.0 MW 6.4 MW 6.4 MW 6.1 MW 7.0 MW 6.8 MW 6.6

37.9 37.8 3.0 43.6 3.5 24.8 36.4 33.5 34.0 31.6 48.1

168.3 52.2 240 189.5 279 281.9 180.0 176.1 176.0 185.3 144.6

Rayleigh Wave Phase Velocity

Receiver Function

O O O O O O

O

O O O O O

Source parameters were acquired from the Data Management Center (DMC) of the Incorporated Research Institutions for Seismology (IRIS) and the Korea Meteorological Administration (KMA).

Table 3 Earthquakes and Computational Parameters Associated with Each Seismic Station in Estimations of Receiver Functions and Phase Velocities of Rayleigh Waves

Station

Earthquakes for Receiver Function Estimation (mm/dd/yy)

Earthquakes for Phase Velocity Estimation (mm/dd/yy)

Smoothness Trade-off Parameter

Teleseismic P-Wave Incident Angle

BGD

09/20/02, 05/26/03a

12/09/00, 09/13/02, 11/02/02, 03/25/03

0.2

36.8⬚

BRD

03/14/03, 05/05/03b, 05/26/03a, 05/26/03b

11/24/01

0.3

36.1⬚

CHC

09/20/02, 10/10/02

03/17/02, 03/31/02, 08/10/02, 09/20/02, 02/19/03, 03/17/03, 03/30/03, 04/17/03

0.2

35.3⬚

CHJ

03/25/02, 04/12/02, 02/24/03

03/04/02, 03/17/02, 03/25/02, 03/31/02, 04/12/02, 08/10/02, 08/20/02, 09/20/02, 02/19/03, 02/24/03, 03/22/03, 03/30/03

0.4

34.1⬚

CHNB

09/20/02, 05/05/03a

03/05/02, 03/31/02, 04/16/02, 03/22/03

0.3

35.2⬚

DGY

09/20/02, 10/10/02

01/13/02, 03/17/02, 03/31/02, 11/02/02, 01/20/03, 03/30/03, 04/17/03

0.07

35.3⬚

GSU

10/19/01, 03/25/03, 05/05/03a

12/09/00, 01/10/01, 01/13/02, 02/28/02, 03/31/02, 08/10/02, 09/13/02, 11/02/02, 12/12/02, 02/24/03, 03/22/03, 03/30/03, 04/17/03

0.3

35.3⬚

HDB

02/24/01, 10/19/01, 11/20/01

01/10/01, 11/24/01, 03/05/02, 03/17/02, 03/31/02

0.2

35.4⬚

HKU

05/05/03a, 05/26/03a

01/13/02, 02/28/02, 03/17/02, 03/31/02, 08/10/02, 11/02/02, 02/19/03, 03/22/03, 04/17/03, 06/07/03

0.07

36.3⬚

HSB

05/05/03a, 05/05/03b, 05/26/03a

07/08/02, 03/30/03, 04/17/03, 06/07/03

0.2

36.6⬚

KAN

08/07/00, 10/19/01

03/14/99, 03/28/99, 05/08/99a, 06/02/99, 07/20/00, 11/16/00b

0.2

33.4⬚

KSA

05/26/03a, 05/26/03b

06/02/99

0.3

35.8⬚

KWJ

11/23/01, 03/25/02

03/23/01, 04/17/01, 05/25/01, 06/14/01, 08/13/01, 03/31/02, 09/20/02, 02/24/03, 04/17/03

0.1

33.6⬚

NPR

10/10/02, 03/14/03

08/10/02, 09/13/02, 09/20/02, 10/10/02, 03/22/03, 03/25/03, 03/30/03, 04/17/03, 06/07/03

0.2

35.9⬚

PUS

08/07/00, 08/28/00, 10/19/01

06/15/00, 07/16/00, 11/24/01

0.1

34.5⬚

SES

03/19/01, 06/05/01

01/16/01, 03/24/01, 04/14/01, 06/14/01, 03/17/02, 03/25/02, 03/31/02, 04/12/02, 04/16/02, 08/10/02, 08/20/02, 09/20/02, 10/10/02, 11/02/02, 03/17/03, 03/30/03, 04/17/03

0.1

34.1⬚

ULC

11/16/00b, 11/17/00

03/14/99, 05/08/99b, 08/04/00, 09/10/00, 10/03/00, 10/06/00, 11/13/00, 11/16/00b

0.07

33.1⬚

ULL

11/16/00a, 12/23/01, 02/05/02

05/08/99b, 07/20/00, 11/13/00, 03/23/01, 05/25/01, 02/24/03

0.4

32.7⬚


Figure 2. Average Rayleigh-wave phase velocities at stations in five geologic areas: (a) the Imjingang belt, (b) the Gyeonggi massif, (c) the Okcheon belt, (d) the Yeongnam massif, and (e) islands. Symbols and corresponding station names are given in each legend.

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change of some information between paired models generates new pairs of models. These steps produce one generation, and the steps iterate up to the predetermined maximum number of generations. Details on the GA are given in Sen and Stoffa (1995). Unlike the linearized matrix inversion, the GA does not strongly depend on an initial model; thus, it should be useful in regions such as southern Korea where there is little a priori information about local velocity structures. In addition, we can obtain model parameter statistics and evaluate the stability of the solution ensemble by performing the GA inversion several times with different initial models to provide a quantitative measure of the quality of the result. We can quantitatively observe a reduction trend of the nonuniqueness in the joint inversion by utilizing the GA statistics. Carroll (1996) demonstrated that a micro-GA (Krishnakumar, 1989) with uniform crossover (Syswerda, 1989) provides a good performance. Carroll (1996) recommended that the probability of crossover should be set at 0.5 when a uniform crossover is adopted in the micro-GA. Based on Carroll (1996), we used a uniform crossover micro-GA in the joint inversion, putting the same value to the probability of crossover. Detailed explanations are given in Chang et al. (2004). In order to solve the problem of rapid velocity variations in crustal models with depth, which frequently occurred in the receiver function analysis, we adopted a smoothness constraint (Ammon et al., 1990), which minimizes the second difference of the model, the roughness norm, within limits of the possibility. The roughness norm is described by nⳮ2

Roughness ⳱

兺 i⳱1

|␣i ⳮ 2␣iⳭ1 Ⳮ ␣iⳭ2| (n ⳮ 2)

(1)

where ␣i is the P-wave velocity of the ith layer, and n is the total number of layers in the velocity model. In order to compromise properly a trade-off between the roughness norm and the waveform fit, we followed the criterion of Ammon et al. (1990). The criterion is to find a value that produces a root mean square (rms) error of the waveform fit approximately equal to the rms of presignal noise in a receiver function stack. The fitness function for the GA inversion is defined by Fitness ⳱ C ⳮ

冤冪兺 (O ⳮ S )

2

j

j

j

冥

Ⳮ w ⳯ roughness

(2)

where Oj is the observed receiver function amplitude at the jth sampling time, Sj the synthetic receiver function at the same time, and w the smoothness trade-off parameter. In order to make this fitness function increase as the model converges, we subtracted the two terms in the brackets from an arbitrary constant C. Although we combined the receiver functions and the surface-wave dispersions to overcome the nonuniqueness in

the receiver functions, the nonuniqueness was not completely removed, but rather decreased, as revealed in the GA results of Chang et al. (2004). Therefore, we think that it is more reasonable to construct an averaged model provided with an indication of variation from the range of standard deviations than to present one best-fit model generated from one initial model. Another advantage of the averaged model is that we can get a more realistic model by averaging possible models, because the averaging process depresses extreme velocity values in each individual model. We generated the averages and standard deviations of estimated velocities at each depth interval for five individual models estimated by randomizing seed values.

Inversion Results We utilized a velocity model that consists of 23 layers, with those at depths from the surface to 6 km being 1-km thick, and the rest of layers down to 40 km being 2-km thick. We assumed a Poisson solid yielding 23 model parameters for P-wave velocities. A total of 18 velocity models corresponding to locations of seismic stations distributed across southern Korea were produced by the joint inversion method. The models were spatially grouped into five regions: the Imjingang belt, the Gyeonggi massif, the Okcheon belt, the Yeongnam massif, and islands (Fig. 1) listed in order roughly from northwest to southeast. There were various crustal velocity distributions with depth in the models at different stations; we classified shapes of the distributions in the upper and lower crustal parts of the velocity models into three and four simplified types, respectively, as shown in Figure 3. Imjingang Belt Among several data sets with different backazimuths in the Imjingang belt, data with southern backazimuths were less contaminated by noise. Amplitudes of transverse receiver functions were quite small, implying that models of crustal structures in this region can be assumed to be horizontally layered. Therefore, we estimated horizontally layered crustal structures with receiver functions with southern backazimuths for this region. The estimated crustal structure and corresponding synthetic and observed receiver functions at station CHNB are presented in Figure 4a. The P-wave velocity profile in the upper crust corresponds to the UC2 type in Figure 3, and the velocity distribution in the lower crust to the LC1 type. Discontinuities in the velocity profile are shown at about 18 km and 28 km depth. The former corresponds to a small peak at 1.75 sec in the observed receiver function, and the latter to a peak at 3.50 sec, which is interpreted to be the Ps wave converted at the Moho. The Moho depth is determined by subtracting the station elevation from the crustal thickness. We identified the crust–mantle transition at the Moho depth from the velocity profile by searching for a local depth


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Figure 3. The classification of velocity distributions in the upper and lower crustal parts in the velocity models. The velocity shapes of the upper crust part are grouped into three types according to following characteristics: (a) Type UC1 with a gradual increase of velocity with depth, (b) Type UC2 with a gradual increase and a midcrustal discontinuity, and (c) Type UC3 with a low-velocity zone and a mid-crustal discontinuity. The shapes of the lower crust part are classified into four types according to characteristics at depths around the Moho: (d) Type LC1 with the sharp Moho discontinuity, (e) Type LC2 with a gradual increase of velocity right above the Moho, (f) Type LC3 with the ambiguous Moho depth implying a continuous rate of velocity increase across the depth, and (g) Type LC4 with a low-velocity zone above the Moho. Here, the definitions of upper and lower crusts are qualitative, and the approximate depth boundary between them depends on the shape of the velocity distribution with depth.

distribution of velocity with a sharp or rapid increase finally reaching a maximum value equal to or greater than 7.5 km/ sec. If there is no sharp or rapid increase of velocity near the suspicious depths, we define the Moho depth as the top of the layer in which the P-wave velocity exceeds 7.5 km/sec, ¨ zalaybey et al. (1997). Thus, the based on the criterion of O Moho depth at station CHNB was determined to be at 27.8 km, which is very shallow compared with those at other inland stations, shown later. Standard deviations of five estimated velocities, indicated by thin solid lines, are well confined except in the upper crust. This observation shows that the nonuniqueness in the receiver function is significantly depressed by the combination of information from the receiver function and the surface-wave dispersion, and that the nonuniqueness can be quantitatively estimated by using the GA. The estimated crustal structure and associated synthetic

and observed receiver functions at station KSA are presented in Figure 4b. The P-wave velocity profile in the upper crust corresponds to the UC3 type, and the velocity distribution in the lower crust to the LC3 type. The velocity does not exceed 6.0 km/sec down to about 8 km depth, where a large velocity jump appears to form a discontinuity. The Moho is picked at 25.9 km depth according to the criterion described above. Standard deviations of the estimated velocities are small except for those around the Moho depth. Gyeonggi Massif Among the computational results in the Gyeonggi massif, those for stations INCN and SNU have already been presented by Chang et al. (2004). We estimated receiver functions using data with southern backazimuths, because the data were less contaminated by noise and amplitudes of

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Figure 4.

Estimated velocity models and corresponding receiver functions at stations (a) CHNB and (b) KSA in the Imjingang belt. Thick solid lines in velocity profiles (top) represent the distribution of the estimated average P-wave velocity (Vp), and thin solid lines indicate Ⳳ1 standard deviation of the mean value in each layer. Dash-dotted lines represent prescribed upper and lower limits of the velocity range in which model parameters are allowed to be changed during the computational process. Arrows indicate the Moho depths estimated in this study. In the bottom part of the figure, the receiver function from the velocity model (dashed line) is compared with the observed receiver function (solid line).

transverse receiver functions were quite small compared with other data with different backazimuths at stations in this region. The estimated crustal structure and corresponding receiver functions at station SES are illustrated in Figure 5a. The P-wave velocity profiles in the upper and lower crusts correspond to the UC3 and LC2 types, respectively. There is a clear velocity discontinuity at about 10 km depth beneath a low-velocity zone. The velocity increases slowly from the depth of the discontinuity to about 26 km depth. The Moho is estimated to be at 29.9 km depth. The estimated crustal structure and corresponding receiver functions at station HSB are shown in Figure 5b. The velocity profile in the upper crust corresponds to the UC3 type, and the velocity distribution in the lower crust to the LC2 type. There is a clear discontinuity at 14 km depth. The Moho is estimated to be at 30.0 km depth. For station CHC, the estimated crustal structure and corresponding receiver functions are shown in Figure 5c. The velocity profiles in the upper and lower crusts correspond to

the UC2 and LC2 types, respectively. The velocity fluctuates in the midcrust, and there is a low-velocity zone at around 15 km depth. The Moho depth is estimated as 31.8 km, where the velocity increases gradually. Standard deviations of the estimated velocities are small except in the upper crust. Computational results at station DGY are presented in Figure 5d. The shapes of the velocity profiles in the upper and lower crusts correspond to the UC3 and LC2 types, respectively. A clear discontinuity of the velocity appears at about 9 km depth beneath a low-velocity zone. The Moho depth is estimated as 33.2 km, where the velocity increases gradually. The estimated crustal structure and corresponding receiver functions at station KAN are presented in Figure 5e. The P-wave velocity profiles in the upper and lower crusts correspond to the UC1 and LC3 types, respectively. The Pwave velocity gradually increases with an almost constant slope. This gradual increase of the velocity above the Moho can also be seen under station KSA. Both stations KAN


Figure 5.

Estimated velocity models and corresponding receiver functions at stations (a) SES, (b) HSB, (c) CHC, (d) DGY, and (e) KAN in the Gyeonggi massif. All symbols and panels are the same as those given in Figure 4. (continued)

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correspond to the UC2 and LC1 types, respectively. There are fluctuations of the velocity with large standard deviations in the midcrust. The Moho is clearly shown at 31.9 km depth. The estimated crustal structure and corresponding receiver functions at station CHJ are illustrated in Figure 6d. The P-wave velocity profiles in the upper and lower crusts correspond to the UC2 and LC2 types, respectively. The velocity is barely more than 5.5 km/sec down to about 8 km depth, where a clear discontinuity appears. Another two weak discontinuities are shown at about 16 km and 28 km depth, and the Moho is estimated to be at 31.8 km depth. Yeongnam Massif

Figure 5. Continued. and KSA are located on the shore of the East Sea (Sea of Japan). Okcheon Belt Computational results for station TJN in the Okcheon belt have been presented by Chang et al. (2004). We estimated receiver functions using data with southern backazimuths except at stations CHJ and KWJ, where data with western backazimuths were used. For station NPR, the estimated crustal structure and corresponding receiver functions are presented in Figure 6a. The P-wave velocity profiles in the upper and lower crusts correspond to the UC3 and LC4 types, respectively. A discontinuity appears at 20 km depth, and the Moho is estimated to be at 32.0 km depth, where the velocity increases gradually. The estimated crustal structure and receiver functions at station KWJ are presented in Figure 6b. The shapes of the velocity profiles in the upper and lower crusts correspond to the UC2 and LC2 types, respectively. The velocity stays around 5.5 km/sec down to about 10 km depth, where a sharp discontinuity appears. The Moho is estimated to be at 33.8 km depth. Standard deviations of the P-wave velocity below the Moho depth are relatively large. Computational results at station HKU are shown in Figure 6c. The velocity profiles in the upper and lower crusts

Among the computational results for the Yeongnam Massif, those at station GKP were presented by Chang et al. (2004). We estimated receiver functions using data with southern backazimuths, except at station ULC, where data with southeastern backazimuths were used. For station GSU, the estimated crustal structure and corresponding receiver functions are presented in Figure 7a. The shapes of the velocity profiles in the upper and lower crusts correspond to the UC3 and LC1 types, respectively. The velocity suddenly increases at 10 km depth, generating a low-velocity zone above. There is a peak of velocity around 25 km depth, which causes a peak and trough of around 3.0 sec in the observed receiver function. The Moho is estimated to be at 34.0 km depth, and standard deviations are relatively large in the upper crust. The estimated crustal structure and corresponding receiver functions at station PUS are presented in Figure 7b. The P-wave velocity profiles in the upper and lower crusts correspond to the UC1 and LC1 types, respectively. There is a peak of velocity around 23 km depth, which is similar to that under station GSU. The Moho is clearly seen at 31.9 km depth. There may be a dipping interface under station HDB because transverse receiver functions show variations in amplitude and polarity as a function of backazimuth. We supposed that the interface has a westward dip, taking into consideration the variations in the transverse receiver functions. Thus, we estimated the receiver function using data with southern backazimuths, which is identical to the strike direction of a dipping structure used to model a reasonable solution (Zhang and Langston, 1995). Computational results at station HDB are shown in Figure 7c. The velocity profiles in the upper and lower crusts correspond to the UC1 and LC2 types, respectively. The Moho is observed at 27.9 km depth. Standard deviations are small except in the upper mantle. For station ULC, computational results are presented in Figure 7d. The P-wave velocity profiles in the upper and lower crusts correspond to the UC2 and LC1 types, respectively. The velocity suddenly increases from 3.6 km/sec at the surface to 6.4 km/sec at about 3 km depth, and it in-


Figure 6.

Estimated velocity models and corresponding receiver functions at stations (a) NPR, (b) KWJ, (c) HKU, and (d) CHJ in the Okcheon belt. All symbols and panels are the same as those given in Figure 4.

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Figure 7.

Estimated velocity models and corresponding receiver functions at stations (a) GSU, (b) PUS, (c) HDB, and (d) ULC in the Yeongnam massif. All symbols and panels are the same as those given in Figure 4.


creases again at around 10 km depth. There are low-velocity zones at the depth range of around 18–22 km in the midcrust and at 34–38 km in the upper mantle. The Moho is estimated to be at 29.9 km depth, where the velocity suddenly increases. Standard deviations are small except in the upper crust. Islands Computational results at station BRD are presented in Figure 8a. The shapes of P-wave velocity profiles in the upper and lower crusts correspond to the UC3 and LC2 types, respectively. A peak velocity value at the depth interval 5–6 km is observed, below which a sudden decreasing trend in velocity indicates a low-velocity zone. At about 12 km depth, the velocity suddenly increases and maintains a gradually increasing trend to 33.9 km depth, which is interpreted as the Moho. Standard deviations are well confined except in the lower crust and upper mantle. The estimated crustal structure and corresponding receiver functions at station BGD are shown in Figure 8b. The P-wave velocity profiles in the upper and lower crusts correspond to the UC1 and LC3 types, respectively. The velocity gradually increases down to the Moho, with a slight change of gradient at 20 km depth. There is a low-velocity zone at the depth of 8–10 km. The Moho is estimated to be at 36.0 km depth, which, along with that under station GKP, is the deepest in southern Korea. The Moho depths under stations BGD and BRD are similar to those under inland stations, because the two stations are installed on islands on the continental shelf. Standard deviations are well confined. From the variations in amplitude and polarity of the transverse receiver functions at station ULL, we presume that the dipping interface has a northwestern dip with a strike of about N30⬚E. Receiver functions should be estimated using data with a backzimuth identical to the strike direction of a dipping layer to model a reasonable solution (Zhang and Langston, 1995); however, we estimated the receiver function using data with southeastern backazimuths as the second best choice, because data with southeastern backazimuths had low SNR. The estimated crustal structure and corresponding receiver functions at station ULL are presented in Figure 8c. The P-wave velocity profiles in the upper and lower crusts correspond to the UC3 and LC2 types, respectively. The velocity is barely more than 6.0 km/sec down to about 12 km depth, where a sharp discontinuity appears. The Moho is clearly seen at 17.8 km depth, which is very shallow compared with other results for island stations. Standard deviations are generally larger than the others owing to poor data quality.

Conclusions and Discussion We estimated crustal structures under 18 stations in southern Korea based on a joint analysis combining receiver functions and surface-wave dispersions with the GA. The GA

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should be useful in regions such as southern Korea where there is little a priori information about local velocity structures, because the GA does not depend on an initial model strongly, unlike a linearized matrix inversion. We could estimate variances in the inversion model by performing the GA inversion five times with different initial seed values and then calculating the model statistics for the ensemble to provide a quantitative measure of the quality of the results. This implies that the nonuniqueness could be quantitatively estimated by using the GA. The fact that standard deviations of estimated velocities are well confined means that the nonuniqueness in the receiver function is significantly depressed by being combined with surface-wave dispersion. We constructed a contour map of the Moho depths by interpolation of estimated values at stations using kriging, as shown in Figure 9. The topography of southern Korea is characterized by a mountainous region on the eastern side of the peninsula near the shore of the East Sea (Sea of Japan) extending from south to north, as shown in Figure 10. There is also a mountainous region in the midsouthern part of Korea. These surface topographic features generally coincide with the estimated Moho depths: deeper Moho depths at higher surface topography. This correspondence might be caused by a crustal adjustment to fit the Airy isostasy (Kwon and Yang, 1985; Choi and Shin, 1996). A previous study by Shin and Baag (2000) shows that the trend of the Moho depths in northern Korea also coincides with the surface topography. There are, however, two regions where the Moho depths are not consistent with the trend of the topography on the surface. One of the two regions covers an area along the Chugaryeong fault, which extends approximately northnortheast–south-southwest, from the East Sea (Sea of Japan) to the north to the Yellow Sea to the south, as shown in Figure 1. We cannot hastily propose a reason for the difference in trends between the Moho depth and topography because of a lack of data from northern Korea. However, it can be said that the Moho depths in the region around the Chugaryeong fault, including stations CHNB and KSA, are somewhat shallower than those of nearby regions, although the surface topography of the region does not show a large difference from that of adjacent regions. This thin-crust feature extends linearly to stations HSB and SES, located near the western shore of Korea across a bay from stations INCN and SNU. The lineation coincides with the extrapolation of the Chugaryeong fault, a normal fault caused by extensional movements. As an explanation for this phenomenon, it is supposed that there has been consequential crustal thinning along the fault by extensional tectonic movements in this area. We present a distribution of average crustal velocities, illustrated in Figure 11, as evidence supporting this supposition. The average crustal velocities around the Chugaryeong fault are relatively low compared with those in adjacent regions, and we think that the low velocities might result from fractures or a density decrease caused by extensional forces that caused the crustal thinning process.

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Figure 8. Estimated velocity models and corresponding receiver functions at stations (a) BRD, (b) BGD, and (c) ULL in the islands around southern Korea. All symbols and panels are the same as those given in Figure 4.


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Figure 9. Distribution of the Moho depths in southern Korea. Contours in kilometers were constructed by the interpolation of estimated values at stations. Dashed lines imply uncertain contours owing to the scarce distribution of stations.

Figure 10.

Map of the surface topography in southern Korea.

The other region is within the Gyeongsang basin, which was formed in a retroarc setting by the subduction of the Izanagi Plate in the early Cretaceous (Chough et al., 2000). Therefore, the Moho depth under the Gyeongsang basin is predicted to be relatively shallow compared with that under

other inland regions. However, the Moho depth distribution shows that the Moho depth of the central Gyeongsang basin is the deepest in southern Korea. We cannot definitely conclude that the crust under the Gyeongsang basin is thick because it would be a premature judgment based on data

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Figure 11. Contour map of average crustal P-wave velocities in km/sec drawn by interpolation of estimated values at stations. Dashed lines imply uncertain contours caused by the scarce distribution of stations.

from only one station in the basin. Nevertheless, we attempt here to explain why the crust is thickened. The estimated crustal structure under station GKP and the corresponding synthetic and observed receiver functions are presented in Figure 12. There is an unusual high-velocity zone from 31 km to 36 km depth, indicated by a dotted circle in the velocity profile. The high velocity reaches 7.5 km/sec at a depth of 31 km, which we could define as the depth of the beginning of the mantle, that is, the depth of the Moho based on the predetermined criterion. However, the high-velocity zone in this depth interval corresponds to a low-gradient slope just before a large peak at 4.45 sec in the receiver function. This peak corresponds to a converted Ps phase caused by the velocity jump at the depth of 36 km. Therefore, we define the Moho at a depth of 36 km rather than at 31 km. The high-velocity zone in the lower crust, we think, could have been generated by underplating of magma materials after the closure of the extensional process of the basin. This assumption is supported by Cho et al. (2004), who discovered a lower crustal unit with high velocity at the southeastern Korean margin near station GKP from tomographic inversion and interpreted the high-velocity structure as magmatic underplating by comparing the observed magmatic anomaly with synthetics. We consider this process might have caused the crust to thicken. In addition, the maturity of the basin could be another reason for the thickening of the crust. The depth of the crust–mantle transition under the shore stations (DGY, KAN, KSA, and ULC) along the East Sea (Sea of Japan) are not clear owing to the gradual velocity

Figure 12.

The estimated velocity model and corresponding receiver functions at station GKP in the Gyeongsang basin. All symbols and panels are the same as those given in Figure 4. The dotted circle in the velocity model indicates the high-velocity zone mentioned in the text. The arrow in the plot of the receiver function (bottom) indicates the waveform caused by the high-velocity zone.


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Figure 13. Velocity discontinuities observed in the upper crust under several stations. Discontinuities were found at 8 km depth under stations BRD, CHJ, and KSA (a) and at 10 km depth under stations DGY, GSU, KWJ, SES, and SNU (b).

increase. In contrast, the crustal structures under the shore stations (HDB and PUS) adjacent to the continental shelf in the southeastern area have a relatively sharp boundary at depths around the Moho. These different properties of the velocity distribution around the Moho depth might be related to crustal characteristics in the adjacent area. Another characteristic feature of the estimated crustal structures is that there is a discontinuity at the depth range of 8–10 km under several stations. It is usually associated with a low-velocity zone. Crustal structures with an 8-km depth discontinuity (BRD, CHJ, and KSA) and with a 10km depth discontinuity (DGY, GSU, KWJ, SES, and SNU) are presented in Figure 13a and 13b, respectively. Most of these discontinuities are considered to be boundaries, where properties of the rocks change. More investigation is needed to explain this phenomenon. Also, weak discontinuities are observed at the midcrust under a few stations (CHJ, CHNB, GKP, HSB, and NPR).

Acknowledgments We are grateful to Moonsup Cho for discussions on the tectonic history and interpretations of southern Korea. We also thank the Incorporated Research Institutions for Seismology (IRIS), the Korea Institute of Geoscience and Mineral Resources (KIGAM), and the Korea Meteorological Administration (KMA) for providing their broadband data. This work was supported in part by the Korea Science and Engineering Foundation (KOSEF) through the Korea Earthquake Engineering Research Center (KEERC) at Seoul National University under Grant Number R11-1997045-13001-0 and by the project Crustal Velocity Structure of the Korean Peninsula, one of the Meteorological and Earthquake R&D programs funded by the KMA. This is a contribution to the BK21 project funded by the Ministry of Education and Human Resources Development, Korea.

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School of Earth and Environmental Sciences Seoul National University Seoul 151-747, South Korea [email protected]

Manuscript received 6 May 2004.