Simulation of ground motions for different Indian cities due to 25 th April 2015 main shock of M w 7.8 Nepal earthquake Kamatchi, P. *, Balaji Rao K.** *- Principal Scientist, ** - Chief Scientist, CSIR-Structural Engineering Research centre, CSIR Campus, Taramani, Chennai 600 113 Ground shaking was felt at different Indian cities during and after 25 th April 2015 main shock of M w 7.8 Nepal earthquake, whose epicenter was located at latitude 28.15 N and longitude 84.71 E. In the present study, artificial earthquake ground motions are generated for 14 Indian cities using extended finite source stochastic model for hard rock site condition. For this purpose, seismological parameters reported in literature for main shock are adopted. The average peak ground accelerations (PGA) computed from twenty five simulations are compared for different cities with (a) the design PGA as per existing seismic zone map of India IS 1893-2002, (b) PGA as per probabilistic seismic hazard analysis for mean return periods of 475 years and 2475 years for hard rock site conditions with average shear wave velocity of top 30 m equal to or greater than 1500 m/s. Average pseudo spectral acceleration spectra for different cities are also obtained for different cities. Pseudo spectral acceleration spectra for Kathmandu is generated and comparisons are made with Pseudo spectral acceleration spectra for a recorded ground motion. From the comparisons, importance of generation of site-specific surface level response spectra including the effect of depth of soil stratum has been demonstrated. INTRODUCTION As it is reported by seismologists (Bilham et al., 2001, Mitra et al., 2015) the rate of convergence of Indian plate with Tibetian plate at locked portion of Himalayan Arc is 20±3 mm per year. This has resulted in major earthquake of Moment magnitude (M w ) 7.8 at Nepal on 25th April 2015, followed by many aftershocks (41 in 26 hrs) with three events of M w greater than 6.5 (6.6,6.9 and 7.3). Seismological parameters of main shock is reported by different researchers (Mitra et al., 2015, Yagi and Okuwaki 2015, USGS 2015) and organizations as given in Table. 1. In the present study seismological parameters adopted from literature are used along with empirical models and strong ground motions are generated for different Indian cities using extended finite source stochastic model (Motazedian and Atkinson 2005) for hard rock level. Average peak ground acceleration (PGA) values from 25 earthquake simulations are obtained and comparisons 1
are made with design basis PGA as per Indian seismic code IS 1893-2002 (Part 1) and the PGA values corresponding to risk levels of 10% probability of exceedance in 50 years (mean return period 475 years) and 2% probability of exceedance in 50 years (mean return period 2475 years). Pseudo spectral acceleration spectra are also obtained for the different cities for hard rock site conditions. Pseudo spectral acceleration spectra for Kathmandu is generated and comparisons are made with Pseudo spectral acceleration spectra for a recorded ground motion for Kathmandu city. Table 1 Seismological parameters of 25 th April 2015, M w 7.8 Nepal earthquake (Main shock) Latitude Longitude M w Depth Strike Dip Seismic moment (N-m) USGS(2015) 28.147 N 84.708 E 7.8 15 295 10 8.1e20 Mitra et al (2015) Yagi and Okuwaki (2015) 28.14 N 84.7 E 7.8 17±3 299 5 1.30E21±1.98E20 280147 N 84.708 E 7.9 15 285 10 9.09E20 RECORDED GROUND MOTION AT KATMANDU Time history record of strong ground motion of main shock which struck Nepal on 25th April 2015 for KATNP (USGS station) located at city center of Kathmandu is published by EERI (2015) as shown in Fig. 1. Epicentral distance of the KATNP station is said to be 59.9 km. The depth of sediments above bedrock at Kathmandu city is reported to be 550 to 650 m. The average shear wave velocity of the site of KATNP station is reported to be 250 m/s. From the response spectra of the horizontal components of recorded earthquake from Fig. 1 two peaks can be observed, one in the short period region near 0.5 s and another in the long period region near 4 to 5 s. Peak in the long period region indicates the amplification of long period waves due to the deeper soil stratum/basin effect resulting in a scenario like 1985 Mexico city earthquake (Kramer, 1996). However, in Nepal no or not many structures are with the time period in the long period (4 to 5 s) range. Many of the structures were having time period less than 1 sec and 2
the peak in the short period range near 0.5 s might have caused major damage. Another important observation made by Goda et al., (2015) is that, the difference in amplitudes of 0 degree and 360 degree component of horizontal acceleration record which indicates the orientation dependency of peak displacement demand of near fault region. Fig. 1 Strong ground motion records for acceleration, velocity, displacement and comparison of response spectra with UBC design spectra for KATNP station at Kathmandu Nepal (EERI, 2015) 3
STOCHASTIC SIMULATION OF EARTHQUAKE GROUND MOTION Stochastic simulation procedure for ground motion generation based on seismological models using point source model has been proposed by Boore (1983, 2003). In this procedure the band limited Gaussian white noise is windowed and filtered in the time domain and transformed into frequency domain. The Fourier amplitude spectrum is scaled to the mean squared absolute spectra and multiplied by a Fourier amplitude spectrum obtained from source path effects. Then, the spectrum is transformed back to time domain and the time history is obtained. From the analysis of recorded ground motions, it has been reported (Beresnev and Atkinson., 1997) that point source models are not capable of reproducing the characteristic features of large earthquakes (Mw > 6) viz., long duration and radiation of less energy at low to intermediate frequencies (0.2-2 Hz). Simulation of strong ground motion from finite fault model has been developed by Beresnev and Atkinson (1997, 1998). In this model, fault rupture plane is represented with an array of sub-faults and the radiation from each sub-fault is modeled as a point source similar to Boore s model (1983). According to finite source model, the fault rupture initiates at the hypocenter and spreads uniformly along the fault plane radially outward with a constant rupture velocity triggering radiation from sub-faults in succession. The improved version of finite source model viz., extended finite source model (Motazedian and Atkinson 2005) which includes the effects of radiated energy on sub-fault size and dynamic corner frequency has been adopted for the generation of strong ground motion. However, in the present study corner frequency is assumed as static and pulsing percentage is assumed to be 50%. SEISMOLOGICAL PARAMETERS FOR SIMULATION OF ARTIFICIAL GROUND MOTIONS Mitra et al. (2015) have reported that fault rupture area for main shock to be 8376 km. USGS has reported the rupture dimension for finite fault to be 100 km x 80 km and sub fault dimension as 20 km in each direction. In the present study fault area (A) and sub-fault length (( l) are calculated corresponding to a moment magnitude of earthquake using empirical Eqs. 1 and 2(Beresnev and Atkinson 1998). Seismological parameters adopted in the present study for the generation of earthquake simulations are given in Table 2. log A M 4.0 (1) w log l 2 0. 4M w (2) 4
Table 2. Seismological Parameters adopted in the ground motion simulations Parameters Moment magnitude 7.8 Fault orientation Fault dimension along strike and dip (km) Strike 299 Dip 5 80 x 80 Depth of focus (km) 17 Stress drop (bars) 200 No. of sub-faults 7x7 Duration Model 1/f c +0.05R Quality factor 508f 0.48 Windowing function Tapered Boxcar f max (Hz) 15 Crustal shear wave velocity (km/s) 3.6 Crustal density (g/cm 3 ) 2.85 AVERAGE PEAK GROUND ACCELERATIONS FOR DIFFERENT CITIES Earthquake strong ground motions are generated for fourteen Indian cities with seismological parameters given in Table 2. Typically one simulation of ground motion for Gorakhpur, Patna, Lucknow, Kanpur, Ranchi and New Delhi are shown in Fig. 2. The average PGA for the fourteen cities obtained from twenty simulations are compared with the design PGA values corresponding to IS 1893-2002 (Part 1) and design PGA values are found to be conservative. However it may be noted that the simulations are for rock site conditions, hence the PGA values for soil sites will be 2 to 4 times more depending upon the nature of the soil site. Hence the difference in values between the simulations and design PGA values are justified. Further PGA values from simulations are compared with PGA values corresponding to Probabilistic Seismic Hazard Results (NDMA 2010) for risk levels of 10% probability of exceedance in 50 years (mean return period 475 years) and 2% probability of exceedance in 50 years (mean return period 2475 years) for hard rock site conditions with average shear wave 5
velocity of top 30 m equal to or greater than 1500 m/s. From the comparisons it is seen that for Goraphpur and Varanasi average PGA values obtained from simulations are higher than the PGA corresponding to mean return period of 475 years, however the for all the sites, average PGA from simulations are lesser than the values corresponding to 2475 years mean return period. PSEUDO SPECTRAL ACCELERATION SPECTRA FOR DIFFERENT CITIES AND KATNP SITE Pseudo spectral acceleration (PSA) spectra of different cities for hard rock site condition are obtained from simulations for different cities as given in Fig. 3(a) to 3(c). Further the comparison of PSA spectra obtained for one typical earthquake simulation for hard rock site condition for KATNP station latitude and longitude with the PSA spectra for the recorded ground motion of KATNP soil site is given in Fig. 3(d). As it is already stated, KATNP station is located in the basin of Kathmandu with average shear wave velocity 250 m/s and depth of soil stratum 550 to 660 m. Two predominant peaks in the recorded ground motion one in the 0,5 s time period range and another in the 4 to 5 s time period range indicates the importance on local soil effect on the damaging effect of earthquake. Hence generation of surface level site-specific ground motion including the effect of depth of soil stratum is found to be essential for getting realistic response spectra for a soil site. 6
(a) (b) (c) (d) (e) (f) Fig. 2 Typical one simulation of ground motion for different cities for due to 25 th April 2015 main shock of M w 7.8 Nepal earthquake(a)gorakhpur (b) Patna (c) Lucknow (d) Kanpur (e) Ranchi (f) New Delhi 7
Table 3 Comparison of average PGA from simulations with PGA values from IS 1893-2002 (Part 1) and risk consistent PGA values from PSHA results for 475 and 2475 years mean City PGA at hard rock level - average of 25 simulations (cm/s 2 ) return period PGA from IS 1893-2002 (Part 1) Design Basis Earthquake (cm/s 2 ) PGA from Probabilistic Seismic Hazard Analysis Results(NDMA, 2010) (cm/s 2 ) Mean return period 475 years Mean return period 2475 years 1 Gorakhpur 59.5 117.72 48.95 101.46 2 Patna 35.7 117.72 43.65 85.98 3 Lucknow 28.1 78.48 36.93 88.04 4 Varanasi 26.9 78.48 23.01 44.89 5 Gaya 23.5 78.48 26.19 48.15 6 Kanpur 20.2 78.48 30.39 76.37 7 Agra 10.8 78.48 53.62 132.24 8 Jabalpur 7.1 78.48 77.73 180.66 9 Ranchi 13.0 49.05 29.84 62.12 10 Kolkata 7.1 78.48 76.04 163.01 11 Jamshedpur 9.6 49.05 53.51 112.96 12 Bhubaneswar 4.5 78.48 23.61 39.87 13 Raipur 5.08 49.05 10.1 15.5 14 New Delhi 9.0 117.72 78.98 180.60 8
(a) (b) (c) (d) Fig. 3 (a) to 3(c) Pseudo spectral acceleration spectra for different Indian cities (d) Pseudo spectral acceleration spectra for rock level(simulated) and surface level(recorded) for Kathmandu SUMMARY In the present study, rock level earthquake ground motions due to April 25 th Nepal earthquake of M w 7.8 are generated for fourteen Indian cities using extended finite source stochastic models. The average PGA for the fourteen cities obtained from twenty simulations are compared with the design PGA values corresponding to IS 1893-2002 (Part 1) design basis earthquake and design PGA values are found to be conservative. Since there will be spectral amplification due to local soil effect upto the order of 2 to 4, conservativeness of Indian seismic code is justified. Further, 9
PGA values from simulations are compared with PGA values corresponding to Probabilistic Seismic Hazard Results (NDMA 2011) for mean return period 475 years and mean return period 2475 years for hard rock site conditions. From the comparisons it is observed that, for Goraphpur and Varanasi average PGA values obtained from simulations are higher than the PGA corresponding to mean return period of 475 years, however the for all the sites, average PGA from simulations are lesser than the values corresponding to 2475 years mean return period. Pseudo spectral acceleration (PSA) spectra of different cities for hard rock site condition are obtained from simulations for different cities. From the comparison of PSA spectra obtained for one typical earthquake simulation for hard rock site condition for KATNP station at Kathmandu with the PSA spectra for the recorded ground motion of KATNP site, the importance of generation of surface level site-specific ground motion including the effect of depth of soil stratum for getting realistic response spectra for a soil site is demonstrated. Acknowledgements This paper is being published with the kind permission of The Director, CSIR-Structural Engineering Research Centre, Chennai, India. The authors acknowledge the support extended by Dr. K. Ravisankar, Chief Scientist and Advisor (M) CSIR-Structural Engineering Research Centre, while carrying out the work reported in this paper. REFERENCES 1. Beresnev I.A, Atkinson G.M. (1997) Modeling finite fault radiation from the n spectrum Bull. Seism. Soc. Am., 87(1), 67-84. 2. Beresnev, I.A., Atkinson, G.M. (1998) FINSIM a FORTRAN program for simulating stochastic acceleration time histories from finite faults Seism. Res. Lr., 69(1), 27-32. 3. Bilham, R., Gaur, V.K., Molnar, P. (2001), Himalayan Seismic Hazard, Science, 293, 1442-1444. 4. Boore, D. M. (2003) Simulation of ground motion using the stochastic method Pure App. Geophy., 160(3-4), 635-676. 10
5. Boore, D. M. (1983) Stochastic simulation of high frequency ground motions based on seismological models of the radiated spectra, Bull. Seism. Soc. Am., 73(6), 1865-1894. 6. Earthquake Engineering research Institute EERI, (2015), Strong Ground Motion data from Nepal s mainshock and two larger aftershocks, Nepal Earthquake clearing house M 7.8, April 25, 2015 at 6:11:26 UTC. 7. Goda, K. Kiyota., T. Pokhrel, R.M., Chiaro G., Katagiri, T. Sharma K., Wilkinson, S. (2015), The 2015 Gorkha Nepal earthquake: insights from earthquake damage survey Frontiers in Built Environment, 1(8), doi:10.3389/fbuil.2015.0008. 8. Mitra, S., Paul, H. Kumar, A., Singh S. K, Dey S. and Powali, D. (2015), The 25 April 2015 Nepal earthquake and its aftershocks Current science,108(10), 1938-1943. 9. Motazedian, D., Atkinson, G.M.(2005) Stochastic Finite-Fault Modeling Based on a Dynamic Corner Frequency, Bull. Seism. Soc. Am., Vol. 95, No. 3, 995-1010. 10. National Disaster Mitigation Agency. (2010) Development of probabilistic seismic hazard map of India Technical report, New Delhi. 11. U.S. Geological Survey Earthquake information center, 25 June 2015, Earthquake Summary Poster, April-May 2015 Nepal Earthquakes, http://earthquake.usgs.gov/ 12. Yagi. Y and Okuwaki R. (2015) Integrated seismic source model of the 2015 Gorkha, Nepal, earthquake Geophysical research letters, 42(15), 6229 6235. 13. Kramer, S.L. (1996) Geotechnical Earthquake Engineering Prentice Hall International series in Civil Engineering and Engineering Mechanics, Washington. 11