earthquakes
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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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Legacy product - no abstract available
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The seismicity of the Australian continent is low to moderate by world standards. However, the seismic risk is much higher for some types of Australian infrastructure due to an incompatibility of structural vulnerability with local earthquake hazard. The earthquake risk in many regional neighbours is even higher due to high hazard, community exposure and vulnerability. The Risk and Impact Analysis Group is a multidisciplinary team at Geoscience Australia that is actively engaged in research to better understand earthquake risk in Australia and to assist agencies in neighbouring countries develop similar knowledge. In this presentation aspects of this work will be described with a particular focus on engineering vulnerability, post disaster information capture and how both can point to effective mitigation options. Risk is the combination of several components (hazard, exposure, vulnerability and impact) that combine to provide measures that can be very useful for decision makers. Vulnerability is the key link that translates hazard exposure to consequence. Vulnerability is typically expressed in physical terms but includes interdependent utility system vulnerability, economic activity vulnerability and the social vulnerability of communities. All four vulnerability types have been the subject of research at GA but the physical vulnerability is the primary link to the others. Vulnerability research for Australian infrastructure will be presented in the context of a holistic risk framework. Furthermore, the work in the Philippines to develop a first order national suite of models will also be presented. Post disaster survey data is invaluable for understanding the nature of asset vulnerability, developing empirical models and validating analytical models based on structural models. Geoscience Australia has developed a range of tools to assist with damage capture that have been used for several hazard types, including earthquake. Tools include portable street view imagery capture, GPS technology and hand-held computers. Experience with the application of these tools and the information that has been derived will be described along with current activity to improve their utility.
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The Mount Lofty and Flinders Ranges of South Australia are bound on the east and the west by reverse faults that thrust Proterozoic and/or Cambrian basement rocks over Quaternary sediment. These faults range from a few tens to almost one hundred kilometres in length and tend to be spaced significantly less than a fault length apart. In the few instances where the thickness of overthrust sediment can be estimated, total neotectonic throws are in the order of 100-200 m. Slip rates on individual faults range from 0.02-0.17 mm/a, with one unconfirmed estimate as high as 0.7 mm/a. Taking into account the intermittent nature of faulting in Australia, it has been suggested that 30-50% of the present-day elevation of the Flinders and Mount Lofty Ranges relative to adjacent piedmonts has developed in the last 5 Ma. Uplifted last interglacial shorelines (ca. 120 ka) along the southern coastline of the Mount Lofty Ranges indicate that deformation is ongoing. Palaeoseismological investigations provide important insight into the characteristics of the large earthquakes responsible for deformation events. Single event displacements of 1.8 m have been measured on the Williamstown-Meadows Fault and the Alma Fault, with the former relating to a surface rupture length of a least 25 km. Further to the south in Adelaide's eastern suburbs, a 5 km section of scarp, potentially relating to a single event slip on the Eden-Burnside Fault, is preserved in ca. 120 ka sediments. Where the Eden-Burnside Fault meets the coast at Port Stanvac 20 kilometres south, the last interglacial shoreline is uplifted by 2 m relative to its expected position. At Normanville, on the uplifted side of the Willunga Fault, the last interglacial shoreline is over 10 m above its expected position, implying perhaps five or more surface rupturing events in the last ca. 120 ka on this >50 km long fault. On the eastern range front, a very large single event displacement of 7 m is inferred on the 54 km long Milendella Fault, and the 79 km long Encounter Fault displaces last interglacial shorelines by up to 11 m. There is abundant evidence for large surface-breaking earthquakes on many faults within 100 km of the Adelaide CBD. Slip rates are low by plate margin standards, implying a low rate of recurrence for M7+ events on individual faults (perhaps 10,000 years or more). However, a proximal moderate-sized event or even a large event at distance has the potential to cause significant damage to Adelaide, particularly given its construction types and local site conditions.
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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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An assumption of probabilistic seismic hazard assessment is that within each source zone the random earthquakes of the past are considered a good predictor of future seismicity. Random earthquakes suggest a Poisson process. If the source zone does not follow a Poisson process then the resulting PSHA might not be valid. The tectonics of a region will effect its spatial distributions. Earthquakes occurring on a single fault, or uniformly distributed, or clustered or random will each have a distinctive spatial distribution. Here we describe a method for both identifying and delineating earthquake clusters and then characterising them. We divide the region into N cells and by counting the number of earthquakes in each cell we obtain a distribution of the number of cells versus the number of earthquakes per cell. This can then be compared to the theoretical Poisson distribution. Areas which deviate from the theoretical Poisson distribution, can then be delineated. This suggests a statistically robust method for determining source zones. Preliminary results suggest that areas of clustering (eg. SWSZ) can also be modelled as a Poisson process which differs from the larger regional Poisson process. The effect of aftershocks and swarms are also investigated.