Regression analysis on ground motion parameters for the earthquakes (Mw≥4.0) in NE India with special emphasis on 3 Jan 2016 M6.7, Tamenglong earthquake. (February 2023)

• Record Type: Journal Article
• Authors: Gogoi, Ashim; Baruah, Saurabh; Sharma, Sangeeta
• Is Part Of: Physics and chemistry of the earth. Volume 129(2023)
• Publication Date: 2023-02
• Subjects: Peak ground acceleration (PGA) -- Ground motion parameters (GMPs) -- GMPEs -- Pseudo spectral acceleration -- Regression analysis; Geophysics -- Periodicals; Geochemistry -- Periodicals; Earth sciences -- Periodicals; Geodesy -- Periodicals; Astrophysics -- Periodicals; 550
• DOI: 10.1016/j.pce.2022.103316
• Languages: English
• ISSNs: 1474-7065

Abstract

Abstract: In the present study, ground motion parameters (GMPs) are estimated by processing 26 earthquake events containing 125 accelerogram records with 375 components that originated in NE, India, and its vicinity with special emphasis on the Jan 3, 2016, M6.7, Tamenglong Earthquake. Moreover, Ground Motion Prediction Equations were developed through multiple regression analysis on observed data of 8 GMPs namely, Peak Ground Acceleration, Peak Ground Velocity, Arias Intensity, Characteristics Intensity, Housner Intensity, Cumulative Absolute Velocity, Effective Design Acceleration, and Acceleration Spectrum Intensity. The developed equations are representative of statistics on changes in amplitudes of parameters with varying distances and magnitude in connection to Northeast India. Besides, newly developed GMPEs can be applied to 4–6.8 magnitude earthquakes and valid up to 525 km of distance. In the case of January 3, 2016, Mw = 6.7, Tamenglong earthquake, a total of 25 parameters are estimated from ground motion recordings. The highest Peak Ground Acceleration (PGA) of 0.05 (g) has been experienced by Kohima station along with Pseudo Spectral Acceleration of 0.2802 (g) at the frequency of 1.72 Hz. The peak pseudo-spectral accelerations for each recording site of the Tamenglong earthquake are perceived within the periods of 0.2s and 0.5s. These estimations help in the characterization of ground motion with varying distances and magnitude which is a prime input to rate damage potential of ground motion and seismic hazard analysis in Northeast India. Highlights: Northeast India is highly seismically active with frequent occurrence of earthquake. Past earthquakes records are utilized to estimate various Ground motion parameters. Amplitude of Ground motion parameters are used in multiple regression analysis. Through analysis Ground motion Prediction Equations (GMPEs) are developed. GMPEs facilitate to characterize ground motion concerning magnitude and distance.