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CURATOR
A pinboard by
Anna Riddell

An interest for science and the changing size and shape of the Earth piqued my curiosity and led me to do a degree in Surveying and Spatial Sciences at The University of Tasmania (UTas), Australia. Upon completion of my degree, I was successful in gaining a graduate placement at Geoscience Australia (GA). I am now completing a PhD at UTas.

I am currently undertaking a PhD in the field of Geodesy at the University of Tasmania, working with Prof. Matt King and Dr. Christopher Watson.

PINBOARD SUMMARY

Surface deformation caused by earthquakes occurs as two processes: instantaneous and ongoing change.

Co-seismic surface deformation occurs instantaneously at the time of an earthquake, whereas post-seismic deformation occurs either as a logarithmic or exponential type decay motion after the earthquake has occurred. These earthquake signals can bias GNSS estimates of position and location.

6 ITEMS PINNED

En échelon and orthogonal fault ruptures of the 11 April 2012 great intraplate earthquakes.

Abstract: The Indo-Australian plate is undergoing distributed internal deformation caused by the lateral transition along its northern boundary--from an environment of continental collision to an island arc subduction zone. On 11 April 2012, one of the largest strike-slip earthquakes ever recorded (seismic moment magnitude M(w) 8.7) occurred about 100-200 kilometres southwest of the Sumatra subduction zone. Occurrence of great intraplate strike-slip faulting located seaward of a subduction zone is unusual. It results from northwest-southeast compression within the plate caused by the India-Eurasia continental collision to the northwest, together with northeast-southwest extension associated with slab pull stresses as the plate underthrusts Sumatra to the northeast. Here we use seismic wave analyses to reveal that the 11 April 2012 event had an extraordinarily complex four-fault rupture lasting about 160 seconds, and was followed approximately two hours later by a great (M(w) 8.2) aftershock. The mainshock rupture initially expanded bilaterally with large slip (20-30 metres) on a right-lateral strike-slip fault trending west-northwest to east-southeast (WNW-ESE), and then bilateral rupture was triggered on an orthogonal left-lateral strike-slip fault trending north-northeast to south-southwest (NNE-SSW) that crosses the first fault. This was followed by westward rupture on a second WNW-ESE strike-slip fault offset about 150 kilometres towards the southwest from the first fault. Finally, rupture was triggered on another en échelon WNW-ESE fault about 330 kilometres west of the epicentre crossing the Ninetyeast ridge. The great aftershock, with an epicentre located 185 kilometres to the SSW of the mainshock epicentre, ruptured bilaterally on a NNE-SSW fault. The complex faulting limits our resolution of the slip distribution. These great ruptures on a lattice of strike-slip faults that extend through the crust and a further 30-40 kilometres into the upper mantle represent large lithospheric deformation that may eventually lead to a localized boundary between the Indian and Australian plates.

Pub.: 02 Oct '12, Pinned: 17 Aug '17

Retrieving real-time co-seismic displacements using GPS/GLONASS: a preliminary report from the September 2015 Mw 8.3 Illapel earthquake in Chile

Abstract: Compared with a single GPS system, GPS/GLONASS observations can improve the satellite visibility, optimize the spatial geometry and improve the precise positioning performance. Although the advantage over GPS-only methods in terms of positioning is clear, the potential contributions of GPS/GLONASS to co-seismic displacement determination and the subsequent seismic source inversion still require extensive study and validation. In this paper, we first extended a temporal point positioning model from GPS-only to GPS/GLONASS observations. Using this new model, the performance of the GPS/GLONASS method for obtaining co-seismic displacements was then validated via eight outdoor experiments on a shaking table. Our result reveals that the GPS/GLONASS method provides more accurate and robust co-seismic displacements than the GPS-only observations in a non-optimal observation environment. Furthermore, as a case study, observation data recorded during the September 2015 M w 8.3 Illapel earthquake in Chile were re-processed. At some stations, obvious biases were found between the co-seismic displacements derived from GPS-only and GPS/GLONASS observations. The subsequent slip distribution inversion on a curved fault confirms that the differences in the co-seismic displacements causes differences in the inversion results and that the slip distributions of the Illapel earthquake inferred from the GPS/GLONASS observations tend to be shallower and larger.

Pub.: 09 Jun '16, Pinned: 07 Aug '17

Variability of earthquake stress drop in a subduction setting, the Hikurangi Margin, New Zealand

Abstract: We calculate stress drops for 176 earthquakes (M2.6–M6.6) from four sequences of earthquakes in New Zealand. Two sequences are within the subducting Pacific plate (2014 Eketahuna and 2005 Upper Hutt), one in the over-riding plate (2013 Cook Strait) and one involved reverse faulting at the subduction interface (2015 Pongaroa). We focus on obtaining precise and accurate measurements of corner frequency and stress drop for the best-recorded earthquakes. We use an empirical Green's function (EGF) approach, and require the EGF earthquakes to be highly correlated (cross-correlation ≥ 0.8) to their respective main shocks. In order to improve the quality, we also stack the spectral ratios and source time functions obtained from the best EGF. We perform a grid search for each individual ratio, and each stacked ratio to obtain quantitative uncertainty measurements, and restrict our analysis to the well-constrained corner frequency measurements. We are able to analyse both P and S waves independently and the high correlation between these measurements strengthens the reliability of our results. We find that there is significant real variability in corner frequency, and hence stress drop, within each sequence; the range of almost 2 orders of magnitude is larger than the uncertainties. The four sequences have overlapping stress drop ranges, and the variability within a sequence is larger than any between different sequences. There is no clear systematic difference in the populations analysed here with tectonic setting. We see no dependence of the stress drop values on depth, time, or magnitude after taking the frequency bandwidth limitations into consideration. Small-scale heterogeneity must therefore exert a more primary influence on earthquake stress drop than these larger scale factors. We confirm that when fitting individual spectral ratios, a corner frequency within a factor of three of the maximum signal frequency is likely to be underestimated. Stacked ratios are smoother and more reliable near the frequency limits. We find that only corner frequencies within about a factor of two of the maximum signal frequency are likely to be underestimated.

Pub.: 18 Nov '16, Pinned: 07 Aug '17

Exploring the uncertainty range of coseismic stress drop estimations of large earthquakes using finite fault inversions

Abstract: A new finite fault inversion strategy is developed to explore the uncertainty range for the energy based average coseismic stress drop ($\overline {{\rm{\Delta }}{\tau _E}} $) of large earthquakes. For a given earthquake, we conduct a modified finite fault inversion to find a solution that not only matches seismic and geodetic data but also has a $\overline {{\rm{\Delta }}{\tau _E}} $ matching a specified value. We do the inversions for a wide range of stress drops. These results produce a trade-off curve between the misfit to the observations and $\overline {{\rm{\Delta }}{\tau _E}} $, which allows one to define the range of $\overline {{\rm{\Delta }}{\tau _E}} $ that will produce an acceptable misfit. The study of the 2014 Rat Islands M w 7.9 earthquake reveals an unexpected result: when using only teleseismic waveforms as data, the lower bound of $\overline {{\rm{\Delta }}{\tau _E}} $ (5–10 MPa) for this earthquake is successfully constrained. However, the same data set exhibits no sensitivity to its upper bound of $\overline {{\rm{\Delta }}{\tau _E}} $ because there is limited resolution to the fine scale roughness of fault slip. Given that the spatial resolution of all seismic or geodetic data is limited, we can speculate that the upper bound of $\overline {{\rm{\Delta }}{\tau _E}} $ cannot be constrained with them. This has consequences for the earthquake energy budget. Failing to constrain the upper bound of $\overline {{\rm{\Delta }}{\tau _E}} $ leads to the conclusions that (1) the seismic radiation efficiency determined from the inverted model might be significantly overestimated and (2) the upper bound of the average fracture energy EG cannot be constrained by seismic or geodetic data. Thus, caution must be taken when investigating the characteristics of large earthquakes using the energy budget approach. Finally, searching for the lower bound of $\overline {{\rm{\Delta }}{\tau _E}} $ can be used as an energy-based smoothing scheme during finite fault inversions.

Pub.: 08 Nov '16, Pinned: 07 Aug '17

Surface deformation associated with the 2015 Mw 8.3 Illapel earthquake revealed by satellite-based geodetic observations and its implications for the seismic cycle

Abstract: In this study, we present inter-, co- and post-seismic displacements observed in the 2015 Illapel earthquake area by Global Positioning System (GPS) and Synthetic Aperture Radar Interferometry (InSAR). RADARSAT-2, ALOS-2 and Sentinel-1A interferograms capture the co- and post-seismic displacements due to the Illapel earthquake. Based on a layered Earth structure, we modeled both co- and post-seismic faulting behaviors on the subduction interface of central Chile. The best-fit model shows that the coseismic rupture broke a 200 km×200 km200 km×200 km area with a maximum slip of 10 m at a depth of 20 km. Two distinct slip centers, likely controlled by local ramp-flat structure, are revealed. The total coseismic geodetic moment is <img height="13" border="0" style="vertical-align:bottom" width="100" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0012821X16306525-si3.gif">2.76×1021 Nm, equivalent to a moment magnitude 8.3. The accumulated afterslip in the first two months after the mainshock is observed on both sides of the coseismic rupture zone with both ascending and descending Sentinel-1A interferograms. A limited overlap zone between co- and post-seismic slip models can be observed, suggesting partitioning of the frictional properties within the Illapel earthquake rupture zone. The total afterslip releases <img height="13" border="0" style="vertical-align:bottom" width="103" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0012821X16306525-si20.gif">∼5.0×1020 Nm geodetic moment, which is equivalent to an earthquake of MwMw 7.7. The 2010 MwMw 8.8 Maule earthquake that occurred ∼400 km away from the Illapel earthquake epicenter could have exerted certain effects on the seismic cycle of the Illapel earthquake area. The seismic records from 2000 to 2015 imply that the rate of annual seismic moment release in the Illapel earthquake area dropped from 0.4 to <img height="16" border="0" style="vertical-align:bottom" width="112" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0012821X16306525-si23.gif">0.2×1019 Nm/yr after the Maule earthquake. Based on the forward modeling with the best-fit slip models determined in this study, we reproduce the local surface displacements before, during and after the Illapel earthquake. A rough deformation cycle, 105±29 yr105±29 yr, calculated by using the coseismic displacements and interseismic rate is basically identical with the revisit interval of M8 events in the adjacent areas of the Illapel earthquake, suggesting that elastic rebound theory is applicable for the long-term prediction in this region.

Pub.: 05 Dec '16, Pinned: 07 Aug '17