Investigation of spatial and temporal variability of site response in the Arunachal Himalaya using ambient seismic noise and earthquake waveforms

Abstract

The Arunachal region that constitutes the easternmost segment of the Himalaya has experienced two great earthquakes in the past. This portion is geologically and seismo‐tectonically unique compared to the other parts of Himalaya. In this study, the ambient seismic noise and earthquake waveforms registered at 34 broadband seismograph stations with a flat frequency response between 120 and 0.02 seconds are analysed to understand the stability and reliability of the horizontal‐to‐vertical spectral ratio method. Also, we use the bootstrapping method to estimate the uncertainty and variations in the horizontal‐to‐vertical spectral ratio in different seasons. Although the predominant frequency does not show any seasonal variation, the amplitudes reveal a slight dependence. The predominant frequencies in the area mainly vary from 1.1 to 7.0 Hz. At a few sites, two peaks well separated in frequency, indicate shallower and deeper structures with impedance contrast. Our results show that the average predominant frequencies are around 3.5 Hz for the undifferentiated granite gneiss, 4.3 Hz for the Bomdila granite gneiss, 2.1 Hz for the Bomdila group of rocks (Paleoproterozoic), 2.8 Hz for the Gandise batholiths, 2.6 Hz for the Gondwana succession and 1.8 Hz for the Abor formation. The amplification estimated by the site‐to‐reference method varies between 1.5 and 6.2, which is lower than that obtained from the HVSR method. Validation of the results from ambient seismic noise was performed by comparing them with those from the earthquake waveforms and correlation with local geology.

Appraisal of seismic noise scenario at national seismological network of India in COVID-19 lockdown situation

“…The figure shows Z-component ground motion time series recorded at BBS stations; however, the analysis has been performed for all the three components (N-S, E-W and Z). The steps involved in performing Fourier transform on raw data include, (i) subdivision of data into smaller windows of time length 50 -60 s each with 10% overlap, (ii) each window is 5% cosine tapered and transformed into Fourier domain, and (iii) each spectrum smoothed prior to the calculation of spectrum using Konno and Ohmachi (1998) technique for a bandwidth coefficient 40, as the raw signal contained unusual spikes ( Singh et al 2019). Accordingly, the Fourier spectrums for three components are shown in Figure 4.…”

Estimation of earthquake local site effects using microtremor observations for the Garhwal–Kumaun Himalaya, India

“…This could be the reason for two peaks at a different scale, reflecting two large impedance contrast at different depths. These multi‐peaks reflect a large impedance contrast, probably representing shallow and thick strata (Bard and SESAME team, 2004; Singh et al ., 2019).…”

“…Ambient noise observations are feasible to the acquisition, analysis time and an appealing approach for evaluation of ground response in large areas; these make this method ideal for characterizing the dynamic behaviour of shallow subsurface (Singh et al ., 2019). In recent times, this method has been widely used to study site effects to provide critical inputs for seismic microzonation and learn local geology (Surve and Mohan, 2010; Panzera et al ., 2015, 2017b; Kumar and Kumar, 2018; Macau et al ., 2018; Vicêncio et al ., 2018; Singh et al ., 2019). The HVSR method has been used to identify the sediment thickness over the bedrock, glacier thickness and local site effects (Parolai et al ., 2002).…”

Seismic signatures and site characterization of an intermittent stream in dry and flood conditions: an implication for soil losses and landslide triggering

“…The waveform of dry and flooding conditions is selected consisting of ground motion records of N-S, E-W and Z components. "The steps include (i) subdivision of data into smaller windows of time length 50-60 s each with 10% overlap, (ii) each window is 5% cosine tapered and transformed into Fourier domain, and (iii) each spectrum smoothed prior to the calculation of spectrum for a bandwidth coefficient 40, as the raw signal contained unusual spikes [51,52] ".…”