Stochastic Extended Simulation (EXSIM) of M<sub>w</sub> 7.0 Kumamoto-Shi earthquake on 15 April 2016 in the Southwest of Japan using the SCEC Broadband Platform (BBP)

M.C. Raghucharan; Surendra Nadh Somala

doi:10.3934/geosci.2018.2.144

AIMS Geosciences, 2018, 4(2): 144-165. doi: 10.3934/geosci.2018.2.144. Research article

Export file:

Format

RIS(for EndNote,Reference Manager,ProCite)
BibTex
Text

Content

Citation Only
Citation and Abstract

Stochastic Extended Simulation (EXSIM) of M_w 7.0 Kumamoto-Shi earthquake on 15 April 2016 in the Southwest of Japan using the SCEC Broadband Platform (BBP)

M.C. Raghucharan, Surendra Nadh Somala

¹ Department of Civil Engineering, Indian Institute of Technology, Hyderabad, Kandi, Sangareddy-502285, Telangana, India
² Department of Civil Engineering, Indian Institute of Technology, Hyderabad, Telangana, India

Received: , Accepted: , Published:

Abstract Full Text(HTML) Figure/Table

Ground motions for M_w 7.0, 15 April 2016, Kumamoto-Shi earthquake of Japan are simulated employing Stochastic Extended Simulation (EXSIM) methodology within the Southern California Earthquake Centre (SCEC) Broadband Platform (BBP) version 15.3.0, utilizing the strong ground motion data from K-NET and KiK-net. Residuals [(ln(data/model)] are plotted as a function of hypocentral distance for a subset of eight periods. Trail simulations are run by varying stress drop until a better match of residuals is obtained. Validation exercise is run with a new data set to ascertain the accuracy of simulations. The results exhibit a close match between the recorded and predicted data. Adopting the validated seismological model of this study, ground motions are predicted at three important sites, which are devoid of strong-motion stations. These results can be used as inputs for conducting dynamic, response spectrum analysis of structures, liquefaction potential of soils, stability analysis and landslide runout estimation of slopes.

Figure/Table

Supplementary

Article Metrics

Keywords: Kumamoto-Shi earthquake; ground motion simulation; SCEC BBP; EXSIM; Goodness-of-Fit plots

Citation: M.C. Raghucharan, Surendra Nadh Somala. Stochastic Extended Simulation (EXSIM) of M_w 7.0 Kumamoto-Shi earthquake on 15 April 2016 in the Southwest of Japan using the SCEC Broadband Platform (BBP). AIMS Geosciences, 2018, 4(2): 144-165. doi: 10.3934/geosci.2018.2.144

References:

1. Zhao D, Ochi F, Hasegawa A, et al. (2000) Evidence for the location and cause of large crustal earthquakes in Japan. J Geophys Res Solid Earth 105: 13579–13594.
2. Sun A, Zhao D, Ikeda M, et al. (2008) Seismic imaging of southwest Japan using P and PmP data: Implications for arc magmatism and seismotectonics. Gondwana Res 14: 535–542.
3. Zhao D, Kanamori H, Negishi H, et al. (1996) Tomography of the source area of the 1995 Kobe earthquake: Evidence for fluids at the hypocenter? Science 274: 1891–1894.
4. Zhao D, Wang Z, Umino N, et al. (2007) Tomographic imaging outside a seismic network: Application to the northeast Japan arc. Bull Seismol Soc Am 97: 1121–1132.
5. EERI KUMAMOTO JAPAN EARTHQUAKE CLEARINGHOUSE: M7.0 APRIL 15, 2016 AT 16:25:06 UTC. Available from: http://www.eqclearinghouse.org/2016-04-15-kumamoto/2016/ 04/22/ground-motions-of-the-2016-kumamoto-earthquake/.
6. Yoshida Y, Abe K (1992) Source mechanism of the Luzon, Philippines earthquake of July 16, 1990. Geophys Res Lett 19: 545–548.
7. USGS Seismicity of the Earth 1900-2012, Philippine Sea plate and vicinity: Open-File Report 2010-1083-M. Available from: https://pubs.usgs.gov/of/2010/1083/m/.
8. Simutė S, Steptoe H, Cobden L, et al. (2016) Full-waveform inversion of the Japanese Islands region. J Geophys Res Solid Earth 121: 3722–3741.
9. Burks LS (2015) Ground motion simulations: Validation and application for civil engineering problems (Doctoral dissertation, Stanford University).
10. Bhattacharya S, Hyodo M, Nikitas G, et al. (2018) Geotechnical and infrastructural damage due to the 2016 Kumamoto earthquake sequence. Soil Dyn Earthquake Eng 104: 390–394.
11. Atkinson GM, Boore DM (1998) Ground-motion relations for eastern North America. Bull Seismol Soc Am 85: 17–30.
12. Hwang H, Huo JR (1997) Attenuation relations of ground motion for rock and soil sites in eastern United States. Soil Dyn Earthquake Eng 16: 363–372.
13. Toro GR, Abrahamson NA, Schneider JF (1997) Model of strong ground motions from earthquakes in central and eastern North America: Best estimates and uncertainties. Seismol Res Lett 68: 41–57.
14. Yoshita M, Okano M, Akiyama H, et al. (1999) A spectral analysis of the 21 May 1997, Jabalpur, India, earthquake (M_w = 5.8) and estimation of ground motion from future earthquakes in the Indian shield region. Bull Seismol Soc Am 89: 1620–1630.
15. Iyengar RN, Kanth SR (2004) Attenuation of strong ground motion in peninsular India. Seismol Res Lett 75: 530–540.
16. Saragoni GR, Hart FC (1974) Simulation of artificial earthquake accelerograms. Earthquake Eng Struct Dyn 2: 249–267.
17. Nau RF, Oliver RM, Pister KS (1982) Simulating and analyzing artificial nonstationary earthquake ground motions. Bull Seismol Soc Am 72: 615–636.
18. Kaul MK (1978) Spectrum-consistent time-history generation. J Eng Mech Div 104: 781–788.
19. Vanmarcke EH (1979) State-of-the-art for assessing earthquake hazards in the United States. Report 14, representation of earthquake ground motion: Scaled accelerograms and equivalent response spectra. Massachusetts Inst of Tech Cambridge Dept of Civil Engineering.
20. Gasparini DA, Vanmarcke EH (1976) Simulated earthquake motions compatible with prescribed response spectra. Massachusetts Institute of Technology, Department of Civil Engineering, Constructed Facilities Division.
21. Hartzell SH (1978) Earthquake aftershocks as Green's functions. Geophys Res Lett 5: 1–4.
22. Irikura K (1983) Semi-empirical estimation of strong ground motions during large earthquakes. Bull Disaster Prev Res Inst.
23. Zeng Y, Anderson JG, Yu G (1994) A composite source model for computing realistic synthetic strong ground motions. Geophys Res Lett 21: 725–728.
24. Schneider JF, Silva WJ, Stark C (1993) Ground motion model for the 1989 M 6.9 Loma Prieta earthquake including effects of source, path, and site. Earthquake Spectra 9: 251–287.
25. Beresnev IA, Atkinson GM (1997) Modeling finite-fault radiation from the ωn spectrum. Bull Seismol Soc Am 87: 67–84.
26. Hartzell S, Guatteri M, Mai PM, et al. (2005) Calculation of broadband time histories of ground motion, Part II: Kinematic and dynamic modeling using theoretical Green's functions and comparison with the 1994 Northridge earthquake. Bull Seismol Soc Am 95: 614–645.
27. Kristek J, Moczo P (2003) Seismic-wave propagation in viscoelastic media with material discontinuities: A 3D fourth-order staggered-grid finite-difference modeling. Bull Seismol Soc Am 93: 2273–2280.
28. Graves RW (1996) Simulating seismic wave propagation in 3D elastic media using staggered-grid finite differences. Bull Seismol Soc Am 86: 1091–1106.
29. Pitarka A (1999) 3D elastic finite-difference modeling of seismic motion using staggered grids with nonuniform spacing. Bull Seismol Soc Am 89: 54–68.
30. Aoi S, Fujiwara H (1999) 3D finite-difference method using discontinuous grids. Bull Seismol Soc Am 89: 918–930.
31. Moczo P, Kristek J, Vavrycuk V, et al. (2002) 3D heterogeneous staggered-grid finite-difference modeling of seismic motion with volume harmonic and arithmetic averaging of elastic moduli and densities. Bull Seismol Soc Am 92: 3042–3066.
32. Lee SJ, Chen HW, Huang BS (2008) Simulations of strong ground motion and 3D amplification effect in the Taipei Basin by using a composite grid finite-difference method. Bull Seismol Soc Am 98: 1229–1242.
33. Komatitsch D, Liu Q, Tromp J, et al. (2004) Simulations of ground motion in the Los Angeles basin based upon the spectral-element method. Bull Seismol Soc Am 94: 187–206.
34. Komatitsch D, Tromp J, Vilotte JP, et al. (2015) The spectral element method for elastic wave equations-application to 2-D and 3-D seismic problems. Int J Numer Methods Eng 45: 1139–1164.
35. Priolo E (2001) Earthquake ground motion simulation through the 2-D spectral element method. J Comput Acoust 9: 1561–1581.
36. Komatitsch D, Liu Q, Tromp J, et al. (2004) Simulations of ground motion in the Los Angeles basin based upon the spectral-element method. Bull Seismol Soc Am 94: 187–206.
37. Lee SJ, Chen HW, Liu Q, et al. (2008) Three-dimensional simulations of seismic-wave propagation in the Taipei basin with realistic topography based upon the spectral-element method. Bull Seismol Soc Am 98: 253–264.
38. Stupazzini M, Paolucci R, Igel H (2009) Near-fault earthquake ground-motion simulation in the Grenoble valley by a high-performance spectral element code. Bull Seismol Soc Am 99: 286–301.
39. Maechling PJ, Silva F, Callaghan S, et al. (2014) SCEC Broadband Platform: System architecture and software implementation. Seismol Res Lett 86: 27–38.
40. Graves R, Pitarka A (2015) Refinements to the Graves and Pitarka (2010) broadband ground-motion simulation method. Seismol Res Lett 86: 75–80.
41. Olsen K, Takedatsu R (2015) The SDSU broadband ground-motion generation module BBtoolbox version 1.5. Seismol Res Lett 86: 81–88.
42. Crempien JG, Archuleta RJ (2015) UCSB method for simulation of broadband ground motion from kinematic earthquake sources. Seismol Res Lett 86: 61–67.
43. Motazedian D, Atkinson GM (2005) Stochastic finite-fault modeling based on a dynamic corner frequency. Bull Seismol Soc Am 95: 995–1010.
44. Anderson JG (2015) The composite source model for broadband simulations of strong ground motions. Seismol Res Lett 86: 68–74.
45. Boore DM (1983) Stochastic simulation of high-frequency ground motions based on seismological models of the radiated spectra. Bull Seismol Soc Am 73: 1865–1894.
46. Boore DM (2003) Simulation of ground motion using the stochastic method. Pure Appl Geophys 160: 635–676.
47. Beresnev IA, Atkinson GM (1998) FINSIM-a FORTRAN program for simulating stochastic acceleration time histories from finite faults. Seismol Res Lett 69: 27–32.
48. Zonno G, Carvalho A (2006) Modeling the 1980 Irpinia earthquake by stochastic simulation. Comparison of seismic scenarios using finite-fault approaches. InFirst European Conference on Earthquake Engineering and Seismology.
49. Motazedian D, Moinfar A (2006) Hybrid stochastic finite fault modeling of 2003, M6.5, Bam earthquake (Iran). J Seismol 10: 91–103.
50. Moratto L, Vuan A, Saraò A (2015) A hybrid approach for broadband simulations of strong ground motion: The case of the 2008 Iwate-Miyagi Nairiku earthquake. Bull Seismol Soc Am 105: 2823–2829.
51. Ghofrani H, Atkinson G, Goda K, et al. (2012) Interpreting the 11th March 2011 Tohoku, Japan Earthquake Ground-Motions Using Stochastic Finite-Fault Simulations. Available from: https://www.researchgate.net/publication/281463795_Interpreting_the_11th_March_2011_Tohoku_Japan_Earthquake_Ground-Motions_Using_Stochastic_Finite-Fault_Simulations.
52. Raghucharan MC, Somala SN (2017) Simulation of strong ground motion for the 25 April 2015 Nepal (Gorkha) M_w 7.8 earthquake using the SCEC broadband platform. J Seismol 21: 777–808.
53. Atkinson GM, Assatourians K, Boore DM, et al. (2009) A guide to differences between stochastic point-source and stochastic finite-fault simulations. Bull Seismol Soc Am 99: 3192–3201.
54. Aki K (1967) Scaling law of seismic spectrum. J Geophys Res 72: 1217–1231.
55. Boore DM (2009) Comparing stochastic point-source and finite-source ground-motion simulations: SMSIM and EXSIM. Bull Seismol Soc Am 99: 3202–3216.
56. Atkinson GM, Assatourians K (2015) Implementation and validation of EXSIM (a stochastic finite-fault ground-motion simulation algorithm) on the SCEC broadband platform. Seismol Res Lett 86: 48–60.
57. Atkinson GM, Boore DM (2006) Earthquake ground-motion prediction equations for eastern North America. Bull Seismol Soc Am 96: 2181–2205.
58. Aoi S, Kunugi T, Fujiwara H (2004) Strong-motion seismograph network operated by NIED: K-Net and KiK-Net. J Jpn Assoc Earthquake Eng 4: 65–74.
59. Asano K, Iwata T (2016) Source rupture processes of the foreshock and mainshock in the 2016 Kumamoto earthquake sequence estimated from the kinematic waveform inversion of strong motion data. Earth Planets Space 68: 147.
60. Molkenthin C, Scherbaum F, Griewank A, et al. (2014) A study of the sensitivity of response spectral amplitudes on seismological parameters using algorithmic differentiation. Bull Seismol Soc Am 104: 2240–2252.
61. J-SHIS (Japan Seismic Hazard Information Station): Subsurface structure of entire Japan. Available from: www.j-shis.bosai.go.jp/map/JSHIS2/download.html?lang=en.
62. Edwards B, Rietbrock A (2009)A comparative study on attenuation and source-scaling relations in the Kantō, Tokai, and Chubu regions of Japan, using data from Hi-Net and KiK-Net. Bull Seismol Soc Am 99: 2435–2460.
63. Petukhin A, Kagawa T, Koketsu K, et al. (2011) Construction and waveform testing of the large scale crustal structure model for southwest Japan. InInternational Symposium on Disaster Simulation & Structural Safety in the Next Generation 2011 (DS'11), September 17–18, 2011, Univ. of Hyogo, Kobe, Japan 2011.
64. Huang HC, Teng TL (1999) An evaluation on H/V ratio vs. spectral ratio for site-response estimation using the 1994 Northridge earthquake sequences. Pure Appl Geophys 156: 631–649.
65. Yamazaki F, Ansary MA (1997) Horizontal-to-vertical spectrum ratio of earthquake ground motion for site characterization. Earthquake Eng Struct Dyn 26: 671–689.
66. Wen KL, Chang TM, Lin CM, et al. (2006) Identification of nonlinear site response using the H/V spectral ratio method. Terr Atmos Ocean Sci 17: 533.
67. Bozorgnia Y, Campbell KW (2016) Ground motion model for the vertical-to-horizontal (V/H) ratios of PGA, PGV, and response spectra. Earthquake Spectra 32: 951–978.
68. Raghukanth ST, Somala SN (2009) Modeling of strong-motion data in northeastern India: Q, stress drop, and site amplification. Bull Seismol Soc Am 99: 705–725.
69. Chen SZ, Atkinson GM (2002) Global comparisons of earthquake source spectra. Bull Seismol Soc Am 92: 885–895.
70. Wald DJ, Earle PS, Allen TI, et al. (2008) Development of the US Geological Survey's PAGER system (prompt assessment of global earthquakes for response). J Autom Chem 1: 40–42.
71. Boore DM (2010) Orientation-independent, nongeometric-mean measures of seismic intensity from two horizontal components of motion. Bull Seismol Soc Am 100: 1830–1835.
72. Abrahamson NA, Silva WJ, Kamai R (2014) Summary of the ASK14 ground motion relation for active crustal regions. Earthquake Spectra 30: 1025–1055.
73. Boore DM, Stewart JP, Seyhan E, et al. (2014) NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Earthquake Spectra 30: 1057–1085.
74. Campbell KW, Bozorgnia Y (2014) NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra. Earthquake Spectra 30: 1087–1115.
75. Chiou BS, Youngs RR (2014) Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra. Earthquake Spectra 30: 1117–1153.
76. Zhang L, Chen G, Wu Y, et al. (2016) Stochastic ground-motion simulations for the 2016 Kumamoto, Japan, earthquake. Earth Planets Space 68: 184.

show all references

Reader Comments

your name: * your email: *

Download full text in PDF

Associated material

Metrics