earthquakes
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The Meeberrie earthquake is the largest known onshore Australian earthquake. Its magnitude was ML 7.2 and it was felt over a wide area of Western Australia as shown on the isoseismal map below, from Port Hedland in the north to Albany and Norseman in the south. Damage from the earthquake was small because of the low population density in the epicentral region, but the shaking at Meeberrie homestead was very severe; all the walls of the homestead were cracked, several rainwater tanks burst, and widespread cracking of the ground occurred. Minor non-structural damage was reported in Perth more than 500km away from the epicentre.
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A 'shake-map' represents the spatial distribution of macroseismic intensity resulting from an earthquake. These maps are often used to determine potential humanitarian consequences from scenario earthquakes, or in near-real time following the detection of an event. In the absence of dense strong-motion networks to calibrate real-time ground-shaking in many of the most vulnerable regions of the world, shake-maps are commonly generated using either Intensity Prediction Equations (IPEs) or Ground-Motion Prediction Equations (GMPEs) combined with Ground-Motion to Intensity Conversion Equations (GMICEs). There are several empirical models available to estimate the spatial distribution of intensity for an earthquake of given magnitude and location. However, these models can predict very different estimates of shaking intensity given the same input parameters; particularly at near-source distance ranges - the most critical distances for impact assessments. Consequently, the application of different shaking hazard model inputs can result in significantly different impacts. High-dimensional information visualisation techniques are used to study the mutual differences among different empirical intensity prediction models. We applied the Self-Organising Map (SOM) technique to project empirical prediction models onto a two-dimensional 'map' to visually compare the similarities and differences between models. The results clearly demonstrate the sensitivity of ground shaking to the selection of intensity prediction models. The effects of these sensitivities on earthquake impact assessments are investigated using a scenario event in Sumatra region, Indonesia.
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Legacy product - no abstract available
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Legacy product - no abstract available
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Legacy product - no abstract available
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Abstract is too large to be pasted here. See TRIM link: D2011-144613
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Australia boasts arguably the richest Quaternary faulting record of all the world's SCR crust. Extensive consultation with the earth science community, and recent advances in digital elevation model coverage, have allowed the compilation of an inventory of over 200 landscape features consistent with fault scarps relating to Quaternary surface breaking earthquakes. This record, together with a growing database of palaeoseismicity data, permits analysis of the long term behaviour of SCR faults in different geologic settings. Details of variations in palaeoearthquake magnitude (including maximum magnitude), recurrence characteristics (given appropriate scaling relations and assumptions relating to landscape modification rates) and spatial relationships between scarps in different deforming regions are recoverable. A common characteristic across Australia appears to be the temporal clustering of large earthquakes. Active periods of earthquake activity comprising a finite number of large events are separated by much longer periods of seismic quiescence. This episodic behaviour poses problems for probabilistic seismic hazard assessments (PSHAs) in that it implies that recurrence of large earthquake events is not random (Poisson). The points critical to understanding the hazard posed by such faults, and modelling this hazard probabilistically, become: 1) is the SCR fault in question about to enter an active period, in the midst of an active period, or in a quiescent period, 2) how many large events might constitute an active period, and how many previous ruptures has the fault generated in its current active period (should it be in one), and 3) what is the 'average' recurrence interval in an active period, and what is the variability around this average. This 'average' can be incorporated statistically into PSHAs, and must be considered when palaeoearthquake catalogues are combined with historic records.
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Legacy product - no abstract available
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The recently released ISC-GEM catalogue was a joint product of the International Seismological Center (ISC) and the Global Earthquake Model (GEM). In a major undertaking it collated, from a very wide range of sources, the surface and body wave amplitude-period pairs from the pre digital era; digital MS, mb and Mw; collated Mw values for 970 earthquakes not included in the Global CMT catalogue; used these values to determine new non-linear regression relationship between MS and Mw and mb and Mw. They also collated arrival picks, from a very wide range of sources, and used these to recompute the location, initially using the EHB location algorithm then revised using the ISC location algorithm (which primarily refined the depth). The resulting catalogues consists of 18871 events that have been relocated and assigned a direct or indirect estimate of Mw. Its completeness periods are, Ms - 7.5 since 1900, Ms - 6.25 1918 and Ms - 5.5 1960. This catalogue assigns, for the first time, an Mw estimate for several Australian earthquakes. For example the 1968 Meckering earthquake the original ML, mb and MS were 6.9, 6.1 and 6.8, with empirical estimates of Mw being 6.7 or 6.8. The ISC-GEM catalogue assigns an Mw of 6.5. We will present a poster of the Australian events in this ISC_GEM catalogue showing, where available, the original ML, mb, Ms, the recalculated mb and Ms, and the assigned Mw. We will discuss the implications of this work for significant Australian earthquakes.
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A dataset comprising some 400 seismograph and accelerograph records for 67 events from the Burakin 2001-02 earthquake swarm was compiled to develop a regional ground-motion model for the Yilgarn Craton, southwestern Western Australia (WA). Events range in size from moment magnitude 2.2 < M < 4.5. The decay of horizontal-component spectral amplitudes can be approximated by a geometrical spreading coefficient of R-1.04 within 80 km of the source. The associated regional seismic quality factor can be expressed as Q(f) = 885 f0.46. Given the relatively large value of the intrinsic quality factor, it appears that the loss of seismic energy through anelastic and scattering processes is not significant, particularly at low frequencies. These attenuation parameters are subsequently used to evaluate average source parameters for the 67 earthquakes (e.g. seismic moment M0, corner frequency fc, and stress drop ??). Average corner frequencies for events with magnitude M > 3.0, do not vary significantly with M0, chiefly ranging between 2-3 Hz. Corner frequencies increase slightly for earthquakes M < 3.0, however, are still characteristically low. This gives rise to anomalously low stress drops for lower magnitude events (M < 4.0) which increase at larger magnitudes. Fourier spectral amplitudes corrected for geometric spreading and anelastic attenuation were regressed with M to obtain quadratic attenuation coefficients. Modelled horizontal-component displacement spectra fit the observed data well. Amplitude residuals (predicted ? observed amplitudes) are, on average, relatively small and do not vary significantly with hypocentral distance. When compared to eastern North American (ENA) models, source spectra are consistent at low frequencies (f less than approximately 2 Hz) indicating that our moment magnitudes are consistent with that used in ENA for the observed magnitude range. Source spectra for the WA model, however, have lower spectral amplitudes with increasing frequency as a result of the low stress drop events. This is particularly apparent for the smaller magnitudes. WA and ENA ground-motion models begin to converge with increasing magnitude. Since these events were recorded from an earthquake swarm, we have reason to suspect that the spectral shapes we observe may not be characteristic of isolated crustal earthquakes, particularly at low magnitudes. We are therefore concerned that a model based on such events (i.e. swarm events or aftershocks) may have limited application for predicting ground-motions, particularly at frequencies greater than 2 Hz. This gives added impetus for the need to include more data in our work and to expand this research into different seismotectonic regions within the Australian continent. Nonetheless, this paper provides an important framework for developing ground-motion relations in Australia. Regional attenuation parameters will provide key inputs for the generation of stochastic WA ground-motion models.