A photograph of a slow motion knob and shaft from the Townsend Telescope. The knob broke off the shaft during the 22 February 2011 earthquake.
This presentation discusses recent empirical ground motion modelling efforts in New Zealand. Firstly, the active shallow crustal and subduction interface and slab ground motion prediction equations (GMPEs) which are employed in the 2010 update of the national seismic hazard model (NSHM) are discussed. Other NZ-specific GMPEs developed, but not incorporated in the 2010 update are then discussed, in particular, the active shallow crustal model of Bradley (2010). A brief comparison of the NZ-specific GMPEs with the near-source ground motions recorded in the Canterbury earthquakes is then presented, given that these recordings collectively provide a significant increase in observed strong motions in the NZ catalogue. The ground motion prediction expert elicitation process that was undertaken following the Canterbury earthquakes for active shallow crustal earthquakes is then discussed. Finally, ongoing GMPE-related activities are discussed including: ground motion and metadata database refinement, improved site characterization of strong motion station, and predictions for subduction zone earthquakes.
A blog post from US Ambassador to New Zealand and Samoa, David Huebner, titled, "Christchurch Earthquake Teams in Motion".
A PDF copy of a notice of motion to the Spreydon-Heathcote Community Board on 21 October 2011 regarding hydraulic fracturing (fracking) in the Canterbury region. The speaker requested that the community board "go further than this motion as a board and call on the council, to call for a moratorium on fracking around Canterbury until a full independent review has taken place from PCE".
A photograph of a slow motion gear from the Townsend Telescope.
A photograph of a slow motion rod from the Townsend Telescope.
A photograph of a slow motion rod from the Townsend Telescope.
A photograph of a slow motion rod from the Townsend Telescope.
A photograph of the declination slow motion gear from the Townsend Telescope.
Background This study examines the performance of site response analysis via nonlinear total-stress 1D wave-propagation for modelling site effects in physics-based ground motion simulations of the 2010-2011 Canterbury, New Zealand earthquake sequence. This approach allows for explicit modeling of 3D ground motion phenomena at the regional scale, as well as detailed nonlinear site effects at the local scale. The approach is compared to a more commonly used empirical VS30 (30 m time-averaged shear wave velocity)-based method for computing site amplification as proposed by Graves and Pitarka (2010, 2015), and to empirical ground motion prediction via a ground motion model (GMM).
This paper develops representative ground motion ensembles for several major earthquake scenarios in New Zealand. Cases considered include representative ground motions for the occurrence of Alpine, Hope, and Porters Pass earthquakes in Christchurch, and the occurrence of Wellington, Wairarapa, and Ohariu, fault ruptures in Wellington. Challenges in the development of ground motion ensembles for subduction zone earthquakes are also highlighted. The ground motions are selected based on the generalized conditional intensity measure (GCIM) approach, ensuring that the ground motion ensembles represent both the mean, and distribution of ground motion intensity which such scenarios could impose. These scenario-based ground motion sets can be used to complement ground motions which are often selected in conjunction with probabilistic seismic hazard analysis, in order to understand the performance of structures for the question “what if this fault ruptures?”
This paper presents a methodology by which both site-specific and spatially distributed ground motion intensity can be obtained immediately following an earthquake event. The methodology makes use of both prediction models for ground motion intensity and its correlation over spatial distances. A key benefit of the methodology is that the ground motion intensity at a given location is not a single value but a distribution of values. The distribution is comprised of both a mean and also standard deviation, with the standard deviation being a function of the distance to nearby strong motion stations. The methodology is illustrated for two applications. Firstly, maps of conditional peak ground acceleration (PGA) have been developed for the major events in the Canterbury earthquake sequence. It is illustrated how these conditional maps can be used for post-event evaluation of liquefaction triggering criteria which have been adopted by the Department of Building and Housing (DBH). Secondly, the conditional distribution of response spectral ordinates is obtained at a specific location for the purposes of determining appropriate ground motion records for use in seismic response analyses of important structures at locations where direct recordings are absent.
The 2015 New Zealand strong-motion database provides a wealth of new strong motion data for engineering applications. An important component of this database is the compilation of new site metadata, describing the soil conditions and site response at GeoNet strong motion stations. We have assessed and compiled four key site parameters for the ~460 GeoNet stations that recorded significant historical ground motions. Parameters include: site classification (NZS1170.5), Vs30, fundamental site period (Tsite) and depth to bedrock (Z1.0, i.e. depth to material with Vs > 1000 m/s). In addition, we have assigned a quality estimate (Quality 1 – 3) to these parameters to provide a qualitative estimate of the uncertainty. New highquality Tsite estimates have largely been obtained from newly available HVSR amplification curves and spectral ratios from inversion of regional strong motion data that has been reconciled with available geological information. Good quality Vs30 estimates, typically in urban centres, have also been incorporated following recent studies. Where site-specific measurements of Vs30 are not available, Vs30 is estimated based on surface geology following national Vs30 maps. New Z1.0 values have been provided from 3D subsurface models for Canterbury and Wellington. This database will be used in efforts to guide development and testing of new and existing ground motion prediction models in New Zealand. In particular, it will allow reexamination of the most important site parameters that control and predict site response in a New Zealand setting. Furthermore, it can be used to provide information about suitable rock reference sites for seismological research, and as a guide to site-specific references in the literature. We discuss compilation of the database, preliminary insights so far, and future directions.
A photograph of a slow motion rod from the Townsend Telescope. The rod was bent out of shape during the 22 February 2011 earthquake.
This dissertation addresses several fundamental and applied aspects of ground motion selection for seismic response analyses. In particular, the following topics are addressed: the theory and application of ground motion selection for scenario earthquake ruptures; the consideration of causal parameter bounds in ground motion selection; ground motion selection in the near-fault region where directivity effect is significant; and methodologies for epistemic uncertainty consideration and propagation in the context of ground motion selection and seismic performance assessment. The paragraphs below outline each contribution in more detail. A scenario-based ground motion selection method is presented which considers the joint distribution of multiple intensity measure (IM) types based on the generalised conditional intensity measure (GCIM) methodology (Bradley, 2010b, 2012c). The ground motion selection algorithm is based on generating realisations of the considered IM distributions for a specific rupture scenario and then finding the prospective ground motions which best fit the realisations using an optimal amplitude scaling factor. In addition, using different rupture scenarios and site conditions, two important aspects of the GCIM methodology are scrutinised: (i) different weight vectors for the various IMs considered; and (ii) quantifying the importance of replicate selections for ensembles with different numbers of desired ground motions. As an application of the developed scenario-based ground motion selection method, ground motion ensembles are selected to represent several major earthquake scenarios in New Zealand that pose a significant seismic hazard, namely, Alpine, Hope and Porters Pass ruptures for Christchurch city; and Wellington, Ohariu, and Wairarapa ruptures for Wellington city. A rigorous basis is developed, and sensitivity analyses performed, for the consideration of bounds on causal parameters (e.g., magnitude, source-to-site distance, and site condition) for ground motion selection. The effect of causal parameter bound selection on both the number of available prospective ground motions from an initial empirical as-recorded database, and the statistical properties of IMs of selected ground motions are examined. It is also demonstrated that using causal parameter bounds is not a reliable approach to implicitly account for ground motion duration and cumulative effects when selection is based on only spectral acceleration (SA) ordinates. Specific causal parameter bounding criteria are recommended for general use as a ‘default’ bounding criterion with possible adjustments from the analyst based on problem-specific preferences. An approach is presented to consider the forward directivity effects in seismic hazard analysis, which does not separate the hazard calculations for pulse-like and non-pulse-like ground motions. Also, the ability of ground motion selection methods to appropriately select records containing forward directivity pulse motions in the near-fault region is examined. Particular attention is given to ground motion selection which is explicitly based on ground motion IMs, including SA, duration, and cumulative measures; rather than a focus on implicit parameters (i.e., distance, and pulse or non-pulse classifications) that are conventionally used to heuristically distinguish between the near-fault and far-field records. No ad hoc criteria, in terms of the number of directivity ground motions and their pulse periods, are enforced for selecting pulse-like records. Example applications are presented with different rupture characteristics, source-to-site geometry, and site conditions. It is advocated that the selection of ground motions in the near-fault region based on IM properties alone is preferred to that in which the proportion of pulse-like motions and their pulse periods are specified a priori as strict criteria for ground motion selection. Three methods are presented to propagate the effect of seismic hazard and ground motion selection epistemic uncertainties to seismic performance metrics. These methods differ in their level of rigor considered to propagate the epistemic uncertainty in the conditional distribution of IMs utilised in ground motion selection, selected ground motion ensembles, and the number of nonlinear response history analyses performed to obtain the distribution of engineering demand parameters. These methods are compared for an example site where it is observed that, for seismic demand levels below the collapse limit, epistemic uncertainty in ground motion selection is a smaller uncertainty contributor relative to the uncertainty in the seismic hazard itself. In contrast, uncertainty in ground motion selection process increases the uncertainty in the seismic demand hazard for near-collapse demand levels.
1. Background and Objectives This poster presents results from ground motion simulations of small-to-moderate magnitude (3.5≤Mw≤5.0) earthquake events in the Canterbury, New Zealand region using the Graves and Pitarka (2010,2015) methodology. Subsequent investigation of systematic ground motion effects highlights the prediction bias in the simulations which are also benchmarked against empirical ground motion models (e.g. Bradley (2013)). In this study, 144 earthquake ruptures, modelled as point sources, are considered with 1924 quality-assured ground motions recorded across 45 strong motion stations throughout the Canterbury region, as shown in Figure 1. The majority of sources are Mw≥4.0 and have centroid depth (CD) 10km or shallower. Earthquake source descriptions were obtained from the GeoNet New Zealand earthquake catalogue. The ground motion simulations were performed within a computational domain of 140km x 120km x 46km with a finite difference grid spacing of 0.1km. The low-frequency (LF) simulations utilize the 3D Canterbury Velocity Model while the high-frequency (HF) simulations utilize a generic regional 1D velocity model. In the LF simulations, a minimum shear wave velocity of 500m/s is enforced, yielding a maximum frequency of 1.0Hz.
This paper presents an examination of ground motion observations from 20 near-source strong motion stations during the most significant 10 events in the 2010-2011 Canterbury earthquake to examine region-specific systematic effects based on relaxing the conventional ergodic assumption. On the basis of similar site-to-site residuals, surfical geology, and geographical proximity, 15 of the 20 stations are grouped into four sub-regions: the Central Business District; and Western, Eastern, and Northern suburbs. Mean site-to-site residuals for these sub-regions then allows for the possibility of non-ergodic ground motion prediction over these sub-regions of Canterbury, rather than only at strong motion station locations. The ratio of the total non-ergodic vs. ergodic standard deviation is found to be, on average, consistent with previous studies, however it is emphasized that on a site-by-site basis the non-ergodic standard deviation can easily vary by ±20%.
A photograph of the right ascension slow motion gears from the Townsend Telescope. Some of the larger gear's teeth were damaged during the 22 February 2011 earthquake.
Ground motion observations from the most significant 10 events in the 2010-2011 Canterbury earthquake sequence at near-source sites are utilized to scrutinize New Zealand (NZ)-specific pseudo-spectral acceleration (SA) empirical ground motion prediction equations (GMPE) (Bradley 2010, Bradley 2013, McVerry et al. 2006). Region-specific modification factors based on relaxing the conventional ergodic assumption in GMPE development were developed for the Bradley (2010) model. Because of the observed biases with magnitude and source-to-site distance for the McVerry et al. (2006) model it is not possible to develop region-specific modification factors in a reliable manner. The theory of non-ergodic empirical ground motion prediction is then outlined, and applied to this 10 event dataset to determine systematic effects in the between- and within-event residuals which lead to modifications in the predicted median and standard deviation of the GMPE. By examining these systematic effects over sub-regions containing a total of 20 strong motion stations within the Canterbury area, modification factors for use in region-specific ground motion prediction are proposed. These modification factors, in particular, are suggested for use with the Bradley et al. (2010) model in Canterbury-specific probabilistic seismic hazard analysis (PSHA) to develop revised design response, particularly for long vibration periods.
This paper presents site-specific and spatially-distributed ground-motion intensity estimates which have been utilized in the aftermath of the 2010-2011 Canterbury, New Zealand earthquakes. The methodology underpinning the ground motion intensity estimation makes use of both prediction models for ground motion intensity and its within-event spatial correlation. A key benefit of the methodology is that the estimated ground motion intensity at a given location is not a single value but a distribution of values. The distribution is comprised of both a mean and standard deviation, with the standard deviation being a function of the distance to nearby observations at strong motion stations. The methodology is illustrated for two applications. Firstly, maps of conditional peak ground acceleration (PGA) have been developed for the major events in the Canterbury earthquake sequence, which among other things, have been utilized for assessing liquefaction triggering susceptibility of land in residential areas. Secondly, the conditional distribution of response spectral ordinates is obtained at the location of the Canterbury Television building (CTV), which catastrophically collapsed in the 22 February 2011 earthquake. The conditional response spectra provide insight for the selection of ground motion records for use in forensic seismic response analyses of important structures at locations where direct recordings are absent.
This report presents an overview of the soil profile characteristics at a number of strong motion station (SMS) sites in Christchurch and its surrounds. An extensive database of ground motion records has been captured by the SMS network in the Canterbury region during the Canterbury earthquake sequence. However in order to comprehensively understand the ground motions recorded at these sites and to be able to relate these motions to other locations, a detailed understanding of the shallow geotechnical profile at each SMS is required. The original NZS1170.5 (SNZ 2004) site subsoil classifications for each SMS site is based on regional geological information and well logs located at varying distances from the site. Given the variability of Christchurch soils, more detailed investigations are required in close vicinity to each SMS to better understand stratigraphy and soil properties, which are important in seismic site response. In this regard, CPT, SPT and borehole data, shear wave velocity (Vs) profiles, and horizontal to vertical spectral ratio measurements (H/V) in close vicinity to the SMS were used to develop representative soil profiles at each site. NZS1170.5 (SNZ 2004) site subsoil classifications were updated using Vs and SPT N60 criteria. Site class E boundaries were treated as a sliding scale rather than as a discrete boundary to account for locations with similar site effects potential, an approach which was shown to result in a better delineation between the site classes. SPT N60 values often indicate a stiffer site class than the Vs data for softer soil sites, highlighting the disparity between the two site investigation techniques. Both SPT N60 and Vs based site classes did not always agree with the original site classifications. This emphasises the importance of having detailed site‐specific information at SMS locations in order to properly classify them. Furthermore, additional studies are required to harmonize site classification based on SPT N60 and Vs. Liquefaction triggering assessments were carried out for the Darfield and Christchurch earthquakes, and compared against observed liquefaction surface manifestations and ground motions characteristics at each SMS. In general, the characteristics of the recorded ground motions at each site correlate well with the triggering analyses. However, at sites that likely liquefied at depth (as indicated by triggering analyses and/or inferred from the characteristics of the recorded surface acceleration time series), the presence of a non‐liquefiable crust layer at many of the SMS locations prevented the manifestation of any surface effects.
A photograph of the slow motion assembly on the lower end of the main tube from the Townsend Telescope. The tube was crushed and bent during the 22 February 2011 earthquake.
A stop motion video promoting the All Right? Hidden Strengths quiz. The video uses a culinary theme to depict kindness as a hidden strength. Alphabet pasta in a pan arranges itself to read, "Knowing your hidden strengths can boost your relationships," before being made into minestrone. All Right? uploaded the video to YouTube on 29 June, and posted the video to their Facebook Timeline on 30 June 2016 at 3:04pm.
A stop motion video promoting the All Right? Hidden Strengths quiz. The video uses a balloon theme to depict teamwork as a hidden strength. Red balloons materialize to read, "Knowing your hidden strengths can improve your life satisfaction," before the balloons are rearranged to read, "Teamwork." All Right? uploaded the video to Facebook Timeline on 27 June 2016 at 4:47pm. All Right? also uploaded the video to YouTube on 29 June 2016.
The 2010-2011 Canterbury earthquakes were recorded over a dense strong motion network in the near-source region, yielding significant observational evidence of seismic complexities, and a basis for interpretation of multi-disciplinary datasets and induced damage to the natural and built environment. This paper provides an overview of observed strong motions from these events and retrospective comparisons with both empirical and physics-based ground motion models. Both empirical and physics-based methods provide good predictions of observations at short vibration periods in an average sense. However, observed ground motion amplitudes at specific locations, such as Heathcote Valley, are seen to systematically depart from ‘average’ empirical predictions as a result of near surface stratigraphic and topographic features which are well modelled via sitespecific response analyses. Significant insight into the long period bias in empirical predictions is obtained from the use of hybrid broadband ground motion simulation. The comparison of both empirical and physics-based simulations against a set of 10 events in the sequence clearly illustrates the potential for simulations to improve ground motion and site response prediction, both at present, and further in the future.
This paper presents a critical evaluation of vertical ground motions observed in the Canterbury earthquake sequence. The abundance of strong near-source ground-motion recordings provides an opportunity to comprehensively review the estimation of vertical ground motions via the New Zealand Standard for earthquake loading, NZS1170.5:2004, and empirical ground motion prediction equations (GMPEs). An in-depth review of current GMPEs is carried out to determine the existing trends and characteristics present in the empirical models. Results illustrate that vertical ground motion amplitudes estimated based on NZS1170.5:2004 are significantly unconservative at short periods and near-source distances. While conventional GMPEs provide an improved prediction, in many instances they too underpredict vertical ground motion accelerations at short periods and near-source distances.
© 2017 The Royal Society of New Zealand. This paper discusses simulated ground motion intensity, and its underlying modelling assumptions, for great earthquakes on the Alpine Fault. The simulations utilise the latest understanding of wave propagation physics, kinematic earthquake rupture descriptions and the three-dimensional nature of the Earth's crust in the South Island of New Zealand. The effect of hypocentre location is explicitly examined, which is found to lead to significant differences in ground motion intensities (quantified in the form of peak ground velocity, PGV) over the northern half and southwest of the South Island. Comparison with previously adopted empirical ground motion models also illustrates that the simulations, which explicitly model rupture directivity and basin-generated surface waves, lead to notably larger PGV amplitudes than the empirical predictions in the northern half of the South Island and Canterbury. The simulations performed in this paper have been adopted, as one possible ground motion prediction, in the ‘Project AF8’ Civil Defence Emergency Management exercise scenario. The similarity of the modelled ground motion features with those observed in recent worldwide earthquakes as well as similar simulations in other regions, and the notably higher simulated amplitudes than those from empirical predictions, may warrant a re-examination of regional impact assessments for major Alpine Fault earthquakes.
This paper examines the consistency of seismicity and ground motion models, used for seismic hazard analysis in New Zealand, with the observations in the Canterbury earthquakes. An overview is first given of seismicity and ground motion modelling as inputs of probabilistic seismic hazard analysis, whose results form the basis for elastic response spectra in NZS1170.5:2004. The magnitude of earthquakes in the Canterbury earthquake sequence are adequately allowed for in the current NZ seismicity model, however the consideration of ‘background’ earthquakes as point sources at a minimum depth of 10km results in up to a 60% underestimation of the ground motions that such events produce. The ground motion model used in conventional NZ seismic hazard analysis is shown to provide biased predictions of response spectra (over-prediction near T=0.2s , and under-predictions at moderate-to-large vibration periods). Improved ground motion prediction can be achieved using more recent NZ-specific models.
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High-quality ground motion records are required for engineering applications including response history analysis, seismic hazard development, and validation of physics-based ground motion simulations. However, the determination of whether a ground motion record is high-quality is poorly handled by automation with mathematical functions and can become prohibitive if done manually. Machine learning applications are well-suited to this problem, and a previous feed-forward neural network was developed (Bellagamba et al. 2019) to determine high-quality records from small crustal events in the Canterbury and Wellington regions for simulation validation. This prior work was however limited by the omission of moderate-to-large magnitude events and those from other tectonic environments, as well as a lack of explicit determination of the minimum usable frequency of the ground motion. To address these shortcomings, an updated neural network was developed to predict the quality of ground motion records for all magnitudes and all tectonic sources—active shallow crustal, subduction intraslab, and subduction interface—in New Zealand. The predictive performance of the previous feed-forward neural network was matched by the neural network in the domain of small crustal records, and this level of predictive performance is now extended to all source magnitudes and types in New Zealand making the neural network applicable to global ground motion databases. Furthermore, the neural network provides quality and minimum usable frequency predictions for each of the three orthogonal components of a record which may then be mapped into a binary quality decision or otherwise applied as desired. This framework provides flexibility for the end user to predict high-quality records with various acceptability thresholds allowing for this neural network to be used in a range of applications.