A Guide to Differences between Stochastic Point-Source and Stochastic Finite-Fault Simulations

Abstract

Why do stochastic point-source and finite-fault simulation models not agree on the predicted ground motions for moderate earthquakes at large distances? This question was posed by Ken Campbell, who attempted to reproduce the Atkinson and Boore (2006) ground-motion prediction equations for eastern North America using the stochastic point-source program SMSIM (Boore, 2005) in place of the finitesource stochastic program EXSIM (Motazedian and Atkinson, 2005) that was used by Atkinson and Boore (2006) in their model. His comparisons suggested that a higher stress drop is needed in the context of SMSIM to produce an average match, at larger distances, with the model predictions of Atkinson and Boore (2006) based on EXSIM; this is so even for moderate magnitudes, which should be well-represented by a pointsource model. Why? The answer to this question is rooted in significant differences between pointsource and finite-source stochastic simulation methodologies, specifically as implemented in SMSIM (Boore, 2005) and EXSIM (Motazedian and Atkinson, 2005) to date. Point-source and finite-fault methodologies differ in general in several important ways: (1) the geometry of the source; (2) the definition and application of duration; and (3) the normalization of finite-source subsource summations. Furthermore, the specific implementation of the methods may differ in their details. The purpose of this article is to provide a brief overview of these differences, their origins, and implications. This sets the stage for a more detailed companion article, "Comparing Stochastic Point-Source and Finite-Source Ground-Motion Simulations: SMSIM and EXSIM," in which Boore (2009) provides modifications and improvements in the implementations of both programs that narrow the gap and result in closer agreement. These issues are important because both SMSIM and EXSIM have been widely used in the development of ground-motion prediction equations and in modeling the parameters that control observed ground motions.

New predictive equations and site amplification estimates for the next-generation Swiss ShakeMaps

“…The model was calibrated against recorded weak-motion data for frequencies f ≥ 0.5 Hz and its validity extended through calibration at high magnitudes with the Swiss macroseismic intensity attenuation model used to determine historical earthquake magnitudes . The use of the effective distance in the EF13 model facilitates the simulation of average geometric finite-fault effects for random hypocentre and slip (Atkinson et al 2009;Boore 2009), that is, modelling of features such as the saturation of near-field ground motion with increasing magnitude and the magnitude dependence of the geometrical decay with distance.…”

Stochastic ground-motion simulations for the 2016 Kumamoto, Japan, earthquake

“…Compared with other ground-motion simulation methods, such as the deterministic or hybrid approach, the advantages of the stochastic method are its independence of small earthquake selection and good performance at both low and high frequencies (Motazedian and Atkinson 2005). In this method, near-field ground motions, including the acceleration time series, Fourier amplitude spectra (FAS) and 5%-damped pseudoacceleration response spectra (PSAs), can be synthesized at the frequency range of engineering interest (Atkinson et al 2009). In particular, the 5%-damped PSA represents the maximum acceleration caused by a linear oscillator with 5% damping and a specified natural period.…”

“…It also means the optimized value of the stress drop, 64 bars, is a reliable estimate for the mainshock of the 2016 Kumamoto earthquake, because the stress drop controls the spectral amplitude of highfrequency part (Motazedian and Atkinson 2005). Note that the stress drop is model dependent (Atkinson et al 2009). If another slip model is applied, the optimized value of the stress drop will be expected to change.…”

Probabilistic Seismic and Tsunami Hazard Analysis Conditioned on a Megathrust Rupture of the Cascadia Subduction Zone

“…While GMPEs are most often used for PSHA, it is worth noting that other methods for generating the IMs that involve the generation of synthetic ground motions have also been recently proposed, however, all involving extremely computational intensive methods. These methods that could serve as alternatives to the GMPEs include kinematic earthquake models (e.g., Olsen et al, 2008;Frankel et al, 2014;Pulido et al, 2015;Iwaki et al, 2016), stochastic finite-fault ground-motion methods (e.g., Atkinson et al, 2009), or hybrid broadband ground-motion methods (e.g., Atkinson et al, 2011;Skarlatoudis et al, 2015).…”