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Pure and Applied Geophysics

, Volume 176, Issue 8, pp 3567–3592 | Cite as

Characterization of Strong Motion Generation Regions of Earthquake Slip Using Extreme Value Theory

  • Anjali C. DhabuEmail author
  • Sangeetha Sugumar
  • S. T. G. Raghukanth
Article
  • 107 Downloads

Abstract

This article characterizes the regions of earthquake slip that are responsible for strong motion generation (SMG), using extreme value theory (EVT). A three-step iterative procedure involving Zipf plot, mean excess function plot and moment ratio plot is used to define the threshold value for a slip model. This threshold slip demarcates the region of SMG in the slip model. The iterative procedure ensures that slip values above the threshold slip follow generalized Pareto distribution (GPD). The regions where slip is greater than the corresponding threshold slip are defined as regions of SMG. A total of 159 slip samples filtered from the SRCMOD catalogue are analyzed in this paper. In order to identify the region of SMG, the first step is to obtain effective slip dimensions. A novel method based on strong motion duration (SMD) is proposed to obtain the effective dimensions of slip model. In the next step, the iterative procedure is employed to obtain threshold slip and the regions of SMG for all the slip samples. The corresponding area of SMG is estimated from the number of sub-faults in the region of SMG and the sub-fault dimensions. Regression analysis is carried out to establish source scaling relationships for the rupture parameters with respect to seismic moment. The considered rupture parameters are effective length, effective width, effective area, effective mean slip, threshold slip and area of SMG of the slip model. On a logarithmic scale, these rupture parameters are observed to follow a linearly increasing trend with the seismic moment. The proposed equations can be used to estimate the rupture parameters for future earthquake events.

Keywords

Effective rupture dimensions region of strong motion generation generalized Pareto distribution 

Notes

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Civil Engineering DepartmentIndian Institute of Technology MadrasChennaiIndia

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