In the present study, an accurate ground motion model (GMM) for the Korean Peninsula is developed by considering local seismological characteristics, including source, site, and three-dimensional (3D) path effects. An existing GMM for rock site conditions is adopted as the base model. To enhance the accuracy of this model and incorporate local seismological features, residuals between the observed and predicted intensity measures (IMs), such as peak ground acceleration () and pseudo-spectral acceleration (), are computed. These residuals are further disaggregated into components associated with specific seismological characteristics: , , and . Regression analyses are conducted to develop empirical equations for , , and based on the calculated residuals. These correction terms are subsequently integrated into the existing GMM to establish the improved model. A practical example is provided to illustrate the application of the proposed GMM. The accuracy and reliability of the improved model are validated by comparing the observed IM values with those predicted by the proposed GMM.
AbrahamsonNAKuehnNWallingM (2017) Probabilistic seismic hazard in California using non-ergodic ground-motion models. Poster at PSHA Workshop: Future directions for probabilistic seismic hazard assessment at a local, national, and transnational scale, 5–7 September, Lenzburg. DOI: 10.1785/0120190030.
2.
AkiK (1967) Scaling law of seismic spectrum. Journal of Geophysical Research Atmospheres72: 1217–1231.
3.
AkkarSSandıkkayaMABommerJJ (2014) Empirical ground-motion models for point- and extended-source crustal earthquake scenarios in Europe and the Middle East. Bulletin of Earthquake Engineering12: 359–387.
4.
AndersonJGBruneJN (1999) Probabilistic seismic hazard analysis without the ergodic assumption. Seismological Research Letters70(1): 19–28.
5.
AtkinsonGMBooreDM (2014) The attenuation of Fourier amplitudes for rock sites in Eastern North America. Bulletin of the Seismological Society of America104(1): 513–528.
6.
BakerJWBradleyBA (2017) Intensity measure correlations observed in the NGA-West2 database, and dependence of correlations on rupture and site parameters. Earthquake Spectra33(1): 145–156.
7.
BazzurroPCornellCA (2004) Nonlinear soil-site effects in probabilistic seismic-hazard analysis. Bulletin of the Seismological Society of America94(6): 2110–2123.
8.
BooreDM (2003) Simulation of ground motion using the stochastic method. Pure and Applied Geophysics160(3–4): 635–676.
9.
BruneJ (1970) Tectonic stress and the spectra of seismic shear waves. Journal of Geophysical Research-Atmospheres75: 4997–5009.
10.
BruneJ (1971) Correction: Tectonic stress and the spectra of seismic shear waves. Journal of Geophysical Research-Atmospheres76: 5002.
11.
Building Seismic Safety Council (BSSC) (1995) 1994 Edition NEHRP Recommended Provisions for Seismic Regulations for New Buildings, FEMA 222A/223A Vol. 1 (Provisions) and Vol. 2 (Commentary). Washington, DC: Federal Emergency Management Agency.
12.
Building Seismic Safety Council (BSSC) (1998) 1995 Edition NEHRP Recommended Provisions for Seismic Regulations for New Buildings and Other Structures, FEMA 302/303 Part 1 (Provisions) and Part 2 (Commentary). Washington, DC: Federal Emergency Management Agency.
13.
CampbellKWBozorgniaY (2008) NGA ground motion model for the geometric mean horizontal component of PGA, PGV, PGD, and 5% damped linear elastic response spectra for periods ranging from 0.01 to 10s. Earthquake Spectra24: 139–171.
14.
CampbellKWBozorgniaY (2014) NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra. Earthquake Spectra30(3): 1087–1115.
15.
ChiouBSJYoungsRR (2014) Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra. Earthquake Spectra30(3): 1117–1153.
16.
DawoodHRodriguez-MarekA (2013) An example using the Mw 9.0 Tohoku earthquake aftershocks. Bulletin of the Seismological Society of America103(2B): 1360-1372.
17.
De SienaLThomasCAsterR (2014) Multi-scale reasonable attenuation tomography analysis (MuRAT): An imaging algorithm designed for volcanic regions. Journal of Volcanology and Geothermal Research277: 22–35.
18.
DobryRBorcherdtRDCrouseCBIdrissIMJoynerWBMartinGRPowerMSRinneEESeedRB (2000) New site coefficients and site classification system used in recent building seismic code provisions. Earthquake Spectra16(1): 41–67.
19.
DouglasJBungumHScherbaumF (2006) Ground-motion prediction equations for southern Spain and southern Norway obtained using the composite model perspective. Journal of Earthquake Engineering10(1): 33–72.
20.
DrouetSCottonF (2015) Regional stochastic GMPEs in low-seismicity areas: Scaling and aleatory variability analysis—Application to the French Alps. Bulletin of the Seismological Society of America105(4): 140240.
21.
EmoloASharmaNFestaGZolloAConvertitoVParkJHChoiHCLimIS (2015). Ground-motion prediction equations for South Korea peninsula. Bulletin of the Seismological Society of America105(5): 2625–2640.
22.
FrankelA (1994) Implications of felt area-magnitude relations for earthquake scaling and the average frequency of perceptible ground motion. Bulletin of the Seismological Society of America84(2): 462–465.
23.
HaSJHanSW (2016a) An efficient method for selecting and scaling ground motions matching target response spectrum mean and variance. Earthquake Engineering and Structural Dynamics45(8): 1381–1387.
24.
HaSJHanSW (2016b) A method for selecting ground motions that considers target response spectrum mean and variance as well as correlation structure structural. Journal of Earthquake Engineering20(8): 1263–1277.
25.
HanSWChoiYS (2008) Seismic hazard analysis in low and moderate seismic region-Korean peninsula. Structural Safety30: 543–558.
26.
HanSWJeeHW (2020) A numerical model for simulating ground motions for the Korean peninsula. Applied Sciences10(4): 1254.
27.
HuangYNWhittakerASLucoN (2010) NEHRP site amplification factors and the NGA relationships. Earthquake Spectra26(2): 583–593.
28.
JeeHWHanSW (2022) Regional ground motion prediction Equation developed for the Korean peninsula using recorded and simulated ground motions. Journal of Earthquake Engineering26(10): 5384–5406.
29.
JoNDBaagCE (2001) Stochastic prediction of strong ground motions in Southern Korea. Journal of Earthquake Engineering Society of Korea5: 1726.
30.
JoNDBaagCE (2003) Estimation of spectrum decay parameter x and stochastic prediction of strong ground motions in southeastern Korea. Journal of Earthquake Engineering Society of Korea7(6): 59–70.
31.
JohnstonAC (1996). Seismic moment assessment of earthquakes in stable continental regions—I: Instrumental seismicity. Geophysical Journal International124: 381–414.
32.
JoshiA (2006) Use of acceleration spectra for determining the frequency-dependent attenuation coefficient and Source Parameters. Bulletin of the Seismological Society of America96(6): 2165–2180.
33.
JoshiATomerMLalSChopraSSinghSPrajapatiSSharmaMLSandeep (2016) Estimation of the source parameters of the Nepal earthquake from strong motion data. Natural Hazards83: 867–883.
34.
JunnJGJoNDBaagCE (2002) Stochastic prediction of ground motions in southern Korean. Geosciences Journal6: 203–214.
35.
KoketsuKSekineS (1998) Pseudo-bending method for three-dimensional seismic ray tracing in a spherical earth with discontinuities. Geophysical Journal International132: 427–434.
36.
Korea Meteorological Administration (KMA) (2015) A Basic Study on Building ShakeMap Database of Scenario Earthquakes in the Korean Peninsula. Seoul, Korea: Korea Meteorological Administration.
37.
KothaSRCottonFBindiD (2019) Empirical models of shear-wave radiation pattern derived from large datasets of ground-shaking observations. Scientific Reports9: 981.
38.
LandwehrNKuehnNMSchefferTAbrahamsonN (2016) A nonergodic ground-motion model for California with spatially varying coefficients. Bulletin of the Seismological Society of America106: 2574–2583.
39.
NohMHLeeKH (1994) Estimation of peak ground motions in the southeastern part of the Korean peninsula (I): Estimation of spectral parameters. Journal of Geological Society of Korea30: 297–306.
40.
NohMHLeeKH (1995) Estimation of peak ground motions in the southeastern part of the Korean peninsula (II): Development of predictive equations. Journal of the Geological Society of Korea31: 175–187.
41.
ParkDLeeJBaagCKimJ (2001) Stochastic prediction of strong ground motions and attenuation equations in the southeastern Korean peninsula. Journal of the Geological Society of Korea37(1): 21–30.
42.
ParkDHLeeJMKimSK (2000) Attenuation and source parameters of earthquakes in the southeastern part of the Korean Peninsula. Journal of Earthquake Engineering Society of Korea4(3): 99–105.
43.
PezeshkSZandiehACampbellKWTavakoliB (2018) Ground-motion prediction equations for central and eastern North America using the hybrid empirical method and NGA-West2 empirical ground-motion models. Bulletin of the Seismological Society of America108(4): 2278–2304.
44.
RietbrockAStrasserFEdwardsB (2013) A stochastic earthquake ground-motion prediction model for the United Kingdom. Bulletin of the Seismological Society of America103(1): 57–77.
45.
SahakianVJBaltayAHanksTCBuehlerJVernonFLKilbDAbrahamsonNA (2019). Ground motion residuals, path effects, and crustal properties: A pilot study in Southern California. Journal of Geophysical Research: Solid Earth124: 5738–5753.
46.
SandıkkayaMAAkkarSBardP (2019) A probabilistic procedure to describe site amplification factors for seismic design codes. Soil Dynamics and Earthquake Engineering126: 105068.
47.
SandikkayaMAAkkarSBardP (2013) A nonlinear site-amplification model for the next Pan-European ground-motion prediction equations. Bulletin of the Seismological Society of America103(1): 19–32.
48.
SchulteSMMooneyWD (2005) An updated global earthquake catalogue for stable continental regions: Reassessing the correlation with ancient rifts. Geophysical Journal International161(3): 707–721.
49.
SekineS (2005) Tomographic inversion of ground motion amplitudes for the 3-D attenuation structure beneath the Japanese Islands. Report of the National Research Institute for Earth Science and Disaster Prevention68: 137–174.
50.
SeyhanEStewartJP (2014) Semi-empirical nonlinear site amplification from NGA-West2 data and simulations. Earthquake Spectra30(3): 1241–1256.
51.
TaoKGrandSPNiuF (2018) Seismic structure of the upper mantle beneath eastern Asia from full waveform seismic tomography. Geochemistry, Geophysics, Geosystems19(8): 2732–2763.
52.
UmJThurberC (1987). A fast algorithm for two point seismic ray tracing. Bulletin of the Seismological Society of America77: 972–986.
53.
VillaniMAbrahamsonNA (2015) Repeatable site and path effects on the ground-motion sigma based on empirical data from southern California and simulated waveforms from the CyberShake platform. Bulletin of the Seismological Society of America105(5): 2681–2695.
54.
WallingMSilvaW (2008) Abrahamson, N, nonlinear site amplification factors for constraining the NGA models. Earthquake Spectra24(1): 243–255.
55.
WallingMKuehnNAbrahamsonNMazzoniS (2018) Regional ground motion duration prediction model for subduction regions. In: Proceedings of the 11th U.S. national conference on earthquake engineering, Los Angeles, CA, 25–29 June.
56.
ZafaraniHSoghratMR (2017) A selected dataset of the Iranian strong motion records. Natural Hazards86(3): 1307–1332.
57.
ZandiehAPezeshkS (2010) Investigation of geometrical spreading and quality factor functions in the new Madrid seismic zone. Bulletin of the Seismological Society of America100: 2185–2195.
