Determination of Ground Profile and Peak Surface Acceleration (PSA) using single station microtremor Inversion method for earthquake hazard zonation of Lombok Island

Author:

Hakim A C,Pramono S,Warnana D D,Rochman J P G N,Rahmatullah F S

Abstract

Abstract There were two fairly destructive earthquake phenomena in 2018 of M 6.4 and M 7 at East Lombok District. However, severe damage occurred in the West Lombok District, Mataram City, and North Lombok District where the three locations were far from the earthquake epicenter. This proves that the potential for infrastructure damage does not only depend on the magnitude and the earthquake source distance, but rather the presence of local site effects. This study aims to determine the dynamic characteristics of the soil and the distribution of Peak Surface Acceleration (PSA). The method used are HVSR analysis (Horizontal to Vertical Spectral Ratio) and inversion of Rayleigh wave ellipticity curve from single station microtremor measurements. The results showed that West Lombok Regency, Mataram City, and the western part of North Lombok Regency were dominated by sedimentary layers which were softly and included in the SD (stiff soil / soft soil) site category. These regions are soil deformation vulnerable due to the earthquake. Based on PSA distribution, the southern part of Lombok Island and Mataram City have a relatively high PSA value. The high value of PSA has the potential to cause ground shaking hazard that are strong enough when an earthquake occurs. This research is expected to be a reference for the design of spectra response to minimize damage of building infrastructure at various levels due to earthquake events.

Publisher

IOP Publishing

Subject

General Engineering

Reference10 articles.

1. Vs30 Mapping and Soil Classification in The Southern Part of Kulon Progo Using Rayleigh Wave Ellipticity Inversion;Sunardi,2018

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3. Near-Surface Characterization from the H/V Spectral Curves along with the Joint Inversion of the Ellipticity and Dispersion Curves;Ullah,2017

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