Reproducing the Spatial Characteristics of High-Frequency Ground Motions for the 1850 M 7.5 Xichang Earthquake

Reproducing the spatial characteristics of large historical earthquakes and predicting the strong ground motions of future destructive large earthquakes through actual small earthquakes have high-practical value. The empirical Green’s function method is a numerical simulation method that can impart real seismic information in synthetic ground motions. In this article, we use data from the 2018 M 5.1 Xichang earthquake to reproduce the ground-motion characteristics of the 1850 M 7.5 Xichang earthquake using the empirical Green’s function method. The uncertainties of the parameters, such as the number, area, and locations of asperities, are considered. The synthetic time histories, peak ground accelerations (PGAs), and response spectra are obtained through simulation. The main results are as follows. (1) The synthetic Xichang earthquake (such as the ground-motion intensity and attenuation characteristic of the PGA) matches well with the M 8.0 Wenchuan earthquake and M 7.3 Jiji earthquake. When the number of asperities is 1 or 2, the PGA characteristics of the Xichang earthquake match well not only with the Next Generation Attenuation-West2 (2014) ground-motion model in the range of 100 km but also with the seismic ground-motion parameter zonation map of China in the range of 20–100 km. (2) The prediction results based on the asperity source model are relatively reliable in the range of 20–100 km. The one-asperity and two-asperity models of the Xichang earthquake match better than the three-asperity and four-asperity models. (3) We can speculate that when the M 7.5 earthquake struck the Xichang area, the damage was relatively strong. The PGA may have exceeded 1.0g in the meizoseismal area, and the seismic intensity in the meizoseismal area may have reached or exceeded a degree of X–XI. Therefore, the synthesized M 7.5 Xichang earthquake has the strength characteristics of a large destructive earthquake.

Ambient Seismic Noise Cross - correlation of Ambon Island and Surrounding Area, Eastern Indonesia: Preliminary Result

The island of Ambon lies on complex tectonics, part of Banda Arc which is driven by the Australia – Eurasia collision. Historical earthquake data show that an earthquake resulting the greatest tsunami in Indonesia had occurred at Ambon Island. On 26 September 2019, Ambon was shaken by an M 6.5 earthquake at a depth of 10 km (BMKG). In this study, we use ambient noise data from 11 temporary stations deployed by ITB and 4 permanent stations owned BMKG which are recorded from October until December 2019. Here, we purely use the vertical component of seismogram to retrieve the Empirical Green’s Function of Rayleigh waves. Cross-correlations were obtained from the daily data series and stacked the day-by-day cross-correlation data into one inter-station cross-correlation. The Empirical Green’s Function is seen at the band period 1-15 s. As a part of our study, we analyze the Green’s Function with frequency-time analysis (FTAN) to get Rayleigh wave group velocity. The group velocity of Rayleigh waves varies from 1.04 km/s – 3.75 km/s. Low group velocity might be indicated the presence of sediment or volcanic deposits and high group velocity might be indicated metamorphic rocks. The result of this study might give a finer velocity model of the shallow crustal beneath Ambon Island and the surrounding area.

Simulation of Strong Ground Motion in the National Capital Region, India, from a Future 8.5 Magnitude Earthquake Using Two-Step Empirical Green’s Function Method

ABSTRACT In this study, I simulate high-frequency ground motions at five stations in the National Capital Region (NCR) of India for a large hypothetical Mw 8.5 earthquake in the Himalayan central seismic gap, at fault-distances of about 200–300 km. A smaller magnitude earthquake (22 July 2007 Mw 4.9 Kharsali) is used as the first-step empirical Green’s function (EGF) for the synthesis of an intermediate-sized earthquake of magnitude Mw 6.8 (1991 Uttarkashi earthquake). In the second step, the records of Mw 6.8 synthetics are further used as the EGF in the simulation of the postulated Mw 8.5 earthquake. Because the target region for the postulated earthquake is devoid of the necessary information on the geophysical constraints, I perform a suite of simulations for plausible scenarios of fault dimensions, stress-drop ratios, C, and scaling factor, N (between the EGF and target earthquake). This article uses heterogeneous slip distributions and variable stress drops on the rupture plane to simulate the target earthquake, based on the power spectral density of the von Karman correlation function. The estimated values of the ground-motion intensity measure (GMIM) such as peak ground acceleration, along with the engineering parameters such as the 5% damped, pseudospectral acceleration (Sa), Arias intensity (IA), and significant duration (TD), are compared for both the recorded and the simulated time histories. The estimated GMIMs of the Mw 6.8 synthetics are examined with those of the 1991 Mw 6.8 Uttarkashi earthquake, whereas the Mw 8.5 simulations are compared with those predicted by prevalent ground-motion prediction equations for rock sites. The Mw 8.5 earthquake scenarios indicate higher GMIMs and seismic hazard in the NCR, principally due to the area being underlain by sediment layers and fluvial deposits.

Testing an Empirical Green’s Function Method for Determining the Rupture Parameters of the 24 April 2014 Vancouver Island Earthquake

ABSTRACT In this article, we examine the 24 April 2014 Mw 6.4 earthquake offshore Vancouver Island using a surface-wave empirical Green’s function (EGF) deconvolution method and compare the results with SeaJade II double-difference aftershock locations. The 24 April event was well recorded and provides the first opportunity to evaluate the suitability of surface-wave EGF deconvolution to constrain rupture details for moderate-sized earthquakes in areas lacking dense seismic arrays. Our surface-wave EGF deconvolution results agree with the aftershock distribution and previously determined centroid moment tensor results. This agreement suggests that this technique is valid for events of this magnitude in a sparsely networked region. We used an Mw 5.3 earthquake about 21 km from the 24 April epicenter as the primary EGF source event and applied stacking to improve the signal-to-noise ratio. Our analysis used broadband seismic data from 105 regional and teleseismic stations. Given the small magnitudes of these events, an aftershock (Mw 4.8) was considered a secondary EGF source to verify key observations. The relative source time functions obtained from this study reveal an overall rupture direction of 143°±6°, extent of 28±2 km, and duration of 16.7±0.3 s. We also determined that the rupture occurred in multiple, distinct subevents, but the deconvolution was unable to determine the subevent parameters. Double-difference aftershock relocations using both onshore and offshore seismometers indicate a 32±2 km unilateral rupture with strike of 146°±2°. These independently determined rupture parameters agree with previously determined centroid moment tensor results with a nodal plane striking 150°±6°.

Simulation of Broadband Ground Motion by Superposing High-Frequency Empirical Green’s Function Synthetics on Low-Frequency Spectral-Element Synthetics

Seismic wave-propagation simulations are limited in their frequency content by two main factors: (1) the resolution of the seismic wave-speed structure of the region in which the seismic waves are propagated through; and (2) the extent of our understanding of the rupture process, mainly on the short length scales. For this reason, high-frequency content in the ground motion must be simulated through other means. Toward this end, we adopt a variant of the classical empirical Green’s function (EGF) approach of summing, with suitable time shift, recorded seismograms from small earthquakes in the past to generate high-frequency seismograms (0.5–5.0 Hz) for engineering applications. We superimpose these seismograms on low-frequency seismograms, computed from kinematic source models using the spectral element method, to produce broadband seismograms. The non-uniform time- shift scheme used in this work alleviates the over-estimation of high-frequency content of the ground motions observed. We validate the methodology by simulating broadband motions from the 1999 Hector Mine and the 2006 Parkfield earthquakes and comparing them against recorded seismograms.