Despite the relatively low seismicity, a large earthquake in the Waikato region is expected to have a high impact, when the fourth-largest regional population and economy and the high density critical infrastructure systems in this region are considered. Furthermore, Waikato has a deep soft sedimentary basin, which increases the regional seismic hazard due to trapping and amplification of seismic waves and generation of localized surface waves within the basin. This phenomenon is known as the “Basin Effect”, and has been attributed to the increased damage in several historic earthquakes, including the 2010-2011 Canterbury earthquakes. In order to quantitatively model the basin response and improve the understanding of regional seismic hazard, geophysical methods will be used to develop shear wave velocity profiles across the Waikato basin. Active surface wave methods involve the deployment of linear arrays of geophones to record the surface waves generated by a sledge hammer. Passive surface wave methods involve the deployment of two-dimensional seismometer arrays to record ambient vibrations. At each site, the planned testing includes one active test and two to four passive arrays. The obtained data are processed to develop dispersion curves, which describe surface wave propagation velocity as a function of frequency (or wavelength). Dispersion curves are then inverted using the Geopsy software package to develop a suite of shear wave velocity profiles. Currently, more than ten sites in Waikato are under consideration for this project. This poster presents the preliminary results from the two sites that have been tested. The shear wave velocity profiles from all sites will be used to produce a 3D velocity model for the Waikato basin, a part of QuakeCoRE flagship programme 1.
Earthquake-triggered soil liquefaction caused extensive damage and heavy economic losses in Christchurch during the 2010-2011 Canterbury earthquakes. The most severe manifestations of liquefaction were associated with the presence of natural deposits of clean sands and silty sands of fluvial origin. However, liquefaction resistance of fines-containing sands is commonly inferred from empirical relationships based on clean sands (i.e. sands with less than 5% fines). Hence, existing evaluation methods have poor accuracy when applied to silty sands. The liquefaction behaviour of Christchurch fines-containing (silty) sands is investigated through a series of Direct Simple Shear (DSS) tests. This type of test better resembles earthquake loading conditions in soil deposits compared to cyclic triaxial tests. Soil specimens are reconstituted in the laboratory with the water sedimentation technique. This preparation method yields soil fabrics similar to those encountered in fluvial soil deposits, which are common in the Christchurch area. Test results provide preliminary indications on how void ratio, relative density, preparation method and fines content influence the cyclic liquefaction behaviour of sand-silt mixtures depending on the properties of host sand and silt.
Well-validated liquefaction constitutive models are increasingly important as non-linear time history analyses become relatively more common in industry for key projects. Previous validation efforts of PM4Sand, a plasticity model specifically for liquefaction, have generally focused on centrifuge tests; however, pore pressure transducers installed at several free-field sites during the Canterbury Earthquake Sequence (CES) in Christchurch, New Zealand provide a relatively unique dataset to validate against. This study presents effective stress site response analyses performed in the finite difference software FLAC to examine the capability of PM4Sand to capture the generation of excess pore pressures during earthquakes. The characterization of the subsurface is primarily based on extensive cone penetration tests (CPT) carried out in Christchurch. Correlations based on penetration resistances are used to estimate soil parameters, such as relative density and shear wave velocity, which affect liquefaction behaviour. The resulting free-field FLAC model is used to estimate time histories of excess pore pressure, which are compared with records during several earthquakes in the CES to assess the suitability of PM4Sand.
©2019. American Geophysical Union. All Rights Reserved. Earthquakes have been inferred to induce hydrological changes in aquifers on the basis of either changes to well water-levels or tidal behavior, but the relationship between these changes remains unclear. Here, changes in tidal behavior and water-levels are quantified using a hydrological network monitoring gravel aquifers in Canterbury, New Zealand, in response to nine earthquakes (of magnitudes M w 5.4 to 7.8) that occurred between 2008 and 2015. Of the 161 wells analyzed, only 35 contain water-level fluctuations associated with “Earth + Ocean” (7) or “Ocean” (28) tides. Permeability reduction manifest as changes in tidal behavior and increased water-levels in the near field of the Canterbury earthquake sequence of 2010–2011 support the hypothesis of shear-induced consolidation. However, tidal behavior and water-level changes rarely occurred simultaneously (~2%). Water-level changes that occurred with no change in tidal behavior reequilibrated at a new postseismic level more quickly (on timescales of ~50 min) than when a change in tidal behavior occurred (~240 min to 10 days). Water-level changes were more than likely to occur above a peak dynamic stress of ~50 kPa and were more than likely to not occur below ~10 kPa. The minimum peak dynamic stress required for a tidal behavior change to occur was ~0.2 to 100 kPa.
In this paper we apply Full waveform tomography (FWT) based on the Adjoint-Wavefield (AW) method to iteratively invert a 3-D geophysical velocity model for the Canterbury region (Lee, 2017) from a simple initial model. The seismic wavefields was generated using numerical solution of the 3-D elastodynamic/ visco- elastodynamic equations (EMOD3D was adopted (Graves, 1996)), and through the AW method, gradients of model parameters (compression and shear wave velocity) were computed by implementing the cross-adjoint of forward and backward wavefields. The reversed-in-time displacement residual was utilized as the adjoint source. For inversion, we also account for the near source/ station effects, gradient precondition, smoothening (Gaussian filter in spatial domain) and optimal step length. Simulation-to-observation misfit measurements based on 191 sources at 78 seismic stations in the Canterbury region (Figure 1) were used into our inversion. The inversion process includes multiple frequency bands, starting from 0-0.05Hz, and advancing to higher frequency bands (0-0.1Hz and 0-0.2Hz). Each frequency band was used for up to 10 iterations or no optimal step length found. After 3 FWT inversion runs, the simulated seismograms computed using our final model show a good matching with the observed seismograms at frequencies from 0 - 0.2 Hz and the normalized least-squared misfit error has been significantly reduced. Over all, the synthetic study of FWT shows a good application to improve the crustal velocity models from the existed geological models and the seismic data of the different earthquake events happened in the Canterbury region.
