Attenuation of strong earthquake ground motion – I: Dependence on geology along the wave path from the Hindu Kush subduction to Western Himalaya

2022

We present seismic microzonation maps of New Delhi, India, using the probabilistic seismic hazard analysis (PSHA) method with input seismic activity parameters estimated in Part-I of this two-part paper. Our calculations required three different attenuation equations for amplitude scaling of strong ground motion from three principal contributing sources: the National Capital Region (NCR), Northwestern Himalaya (NWH), and the Hindu Kush subduction (HKS). We show that uniform hazard spectral (UHS) amplitudes are dominated only by the local seismicity in the NCR at high frequencies beyond about 2 Hz. For intermediate and long periods, UHS amplitudes are dominated by contributions from the NWH and HKS earthquakes. Our results show that specifying strong motion amplitudes for use in engineering design by means of peak ground acceleration can lead to serious errors for buildings higher than four to five stories and hence should not be used. Our results also show that the shape of design spectra must depend on the nature of contributing earthquake sources, their relative activity, potential to create large magnitudes, and geographical placement relative to the site of interest, and thus a standard design-spectrum shape cannot satisfy all these requirements. We use local geological site condition parameters directly in all calculations and present hazard maps for three different soil site conditions ("rock," stiff soil sites, and deep soil sites). Thus, the user can extract the UHS amplitudes of pseudo relative velocity spectra at any site in the National Capital Territory by experimentally determining the local soil site conditions and then applying the corresponding maps shown in this paper. K E Y W O R D Scontribution from a large distant earthquake to the design strong motion amplitudes; computation of seismic hazard for earthquake sources, which follow different attenuation laws; microzonation maps that include a description of site geology and site soil properties

Section: Empirical Scaling Equationsmentioning

confidence: 97%

Seismic microzoning of the Delhi metropolitan area, India—II: Hazard computation and zoning maps

2022

“…Figure 3 shows the strong motion stations that recorded earthquakes for which two different attenuation equations were developed for this paper. All triangular stations recorded crustal events in the western Himalaya, with depths F I G U R E 3 (Top) Strong motion accelerograph stations (all triangles) in northwest Himalaya and vicinity that recorded strong motion accelerations used to develop attenuation equations for events in northwest Himalaya and from the Hindu Kush subduction zone, respectively (redrawn from Gupta and Trifunac 23 ). Solid triangles show stations that recorded deep events from the Hindu Kush zone.…”

Section: The Area Of Studymentioning

confidence: 99%

Seismic microzoning of the Delhi metropolitan area, India— I: Seismicity modeling

2022

Seismic activity parameters ( a $a$ and b $b$ values in a Gutenbdataer–Richter relationship, maximum magnitude M max ${M}_{\max }$, and predominant focal depths H $H$) have been estimated for a grid of square cells of size 0.1° in latitudes and longitudes covering a large region bound by 24°−33°N and 72°−82°E to define input seismicity for microzoning of the Delhi metropolitan area. For this purpose, seven area types of seismic sources are first identified from a detailed seismotectonic evaluation of the region. Two of these sources form part of the Northwestern Himalaya and the remaining five encompass the intraplate area including and surrounding the National Capital Region. The seismic activity parameters are then estimated for each source zone by compiling a comprehensive catalog of 4483 past earthquakes with magnitudes of 2.0 or more covering the 1720–2020 period. All the grid cells in each source are initially assigned the same values of parameters b $b$, M max ${M}_{\max }$, and H $H$ as those for the source zone; whereas parameter a $a$ has been redefined for each grid cell using the cumulative occurrence rate of earthquakes above the minimum magnitude of completeness for the source zone. To account for possible uncertainties in past earthquake locations, values of the activity parameters thus assigned to all the grid cells in the region are spatially smoothed using an elliptical Gaussian kernel with a major axis along the predominant strike direction for the source zone of each grid cell. The grid cells across the source zone boundaries are also included in the smoothing process to normalize the effects of any subjectivity introduced in defining the source zone boundaries. Our estimations of seismic activity parameters thus obtained can be considered in the development of a robust and physically realistic seismicity model for practical engineering applications, which was made possible by our use of a sufficiently long duration of the earthquake catalog along with complete reporting of data up to magnitudes very close to the expected maximum magnitude in each source zone. We have also estimated the seismic activity parameters for the Hindu Kush subduction zone, which is then idealized by a point source.

“…">Gupta and Trifunac 13,39 also developed the frequency‐dependent attenuation for the shallow crustal earthquakes in the northeast India region using a total of 148 three‐component accelerograms recorded from 36 earthquakes with magnitudes between 4.0 and 6.7 at epicentral distances within 350 km. Gupta and Trifunac 14 used a small set of only 19 strong motion records from six deep‐focus earthquakes in the HKS zone to modify the frequency‐dependent attenuation function in the relationship developed in (1) above to have a prediction equation for PSV amplitudes in western India from the Hindu Kush earthquakes at very long distances on the order of 1000 km. Gupta and Trifunac 40 used a set of 102 three‐component accelerograms recorded at 50 different stations in northeast India from 12 different earthquakes in the Burmese subduction zone with magnitude, focal depth, and distance ranges of 5.0−7.2, 80−120 km, and 157.8−560.0 km, respectively, to modify the frequency‐dependent attenuation function in the relationship developed in (2) above for a prediction equation for PSV amplitudes in northeast India from the Burmese subduction earthquakes. …”

Section: The Study Areamentioning

confidence: 99%

“…Gupta and Trifunac 14 used a small set of only 19 strong motion records from six deep‐focus earthquakes in the HKS zone to modify the frequency‐dependent attenuation function in the relationship developed in (1) above to have a prediction equation for PSV amplitudes in western India from the Hindu Kush earthquakes at very long distances on the order of 1000 km.…”

Section: The Study Areamentioning

confidence: 99%

“…The seismic sources and spatial distribution of the seismic activity parameters used in this study are the same that Gupta et al 5 detailed and used for the microzonation of the Delhi metropolitan area 6 . The modeling of the seismic activity for the local seismic sources covering the intraplate NCR area and its vicinity, as well as the north‐western Himalaya (NWH) plate boundary sources is described in Section 4, while those of the HKS source at distances of about 1000 km is described in Section 5 of Gupta et al 5 The method of describing seismicity is similar to that reported in Lee et al, 7,8 Lee and Trifunac, 9,10 and Gupta et al 11 The path‐dependent attenuation of spectral amplitudes has been accounted realistically using scaling equations based on attenuation models developed using strong motion data recorded from local events in the NCR of India, 12 events in the western part of the Himalayan Plate Boundary region recorded within the Himalaya and the adjacent Gangetic plains, 13 and from deep events in the HKS zone recorded at very long distances of around 1000 km in western Himalaya 14 …”

Section: Introductionmentioning

confidence: 99%

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Seismic zoning maps of the National Capital Region (NCR) of India

2022