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.
This article presents a subset of findings from a larger mixed methods CEISMIC1 funded study of twenty teachers’ earthquake experiences and post-earthquake adjustment eighteen months after a fatal earthquake struck Christchurch New Zealand, in the middle of a school day (Geonet Science, 2011; O’Toole & Friesen, 2016). This earthquake was a significant national and personal disaster with teachers’ emotional self-management as first responders being crucial to the students’ immediate safety (O’Toole & Friesen, 2016). At the beginning of their semi-structured interviews conducted eighteen months later, the teachers shared their earthquake stories (O’Toole & Friesen, 2016). They recalled the moment it struck in vivid detail, describing their experiences in terms of what they saw (destruction), heard (sonic boom, screaming children) and felt (fright and fear) as though they were back in that moment similar to flashbulb memory (Brown & Kulik, 1977). Their memories of the early aftermath were similarly vivid (Rubin & Kozin, 1984). This article focuses on how the mood meter (Brackett & Kremenitzer, 2011) was then used (with permission) to further explore the teachers’ perceived affect to enlighten their lived experiences.
In the last two decades, New Zealand (NZ) has experienced significant earthquakes, including the 2010 M 7.2 Darfield, 2011 M 6.2 Christchurch, and 2016 M 7.8 Kaikōura events. Amongst these large events, tens of thousands of smaller earthquakes have occurred. While previous event and ground-motion databases have analyzed these events, many events below M 4 have gone undetected. The goal of this study is to expand on previous databases, particularly for small magnitude (M<4) and low-amplitude ground motions. This new database enables a greater understanding of regional variations within NZ and contributes to the validity of internationally developed ground-motion models. The database includes event locations and magnitude estimates with uncertainty considerations, and tectonic type assessed in a hierarchical manner. Ground motions are extracted from the GeoNet FDSN server and assessed for quality using a neural network classification approach. A deep neural network approach is also utilized for picking P and S phases for determination of event hypocentres. Relative hypocentres are further improved by double-difference relocation and will contribute toward developing shallow (< 50 km) seismic tomography models. Analysis of the resulting database is compared with previous studies for discussion of implications toward national hazard prediction models.
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 poster presents work to date on ground motion simulation validation and inversion for the Canterbury, New Zealand region. Recent developments have focused on the collection of different earthquake sources and the verification of the SPECFEM3D software package in forward and inverse simulations. SPECFEM3D is an open source software package which simulates seismic wave propagation and performs adjoint tomography based upon the spectral-element method. Figure 2: Fence diagrams of shear wave velocities highlighting the salient features of the (a) 1D Canterbury velocity model, and (b) 3D Canterbury velocity model. Figure 5: Seismic sources and strong motion stations in the South Island of New Zealand, and corresponding ray paths of observed ground motions. Figure 3: Domain used for the 19th October 2010 Mw 4.8 case study event including the location of the seismic source and strong motion stations. By understanding the predictive and inversion capabilities of SPECFEM3D, the current 3D Canterbury Velocity Model can be iteratively improved to better predict the observed ground motions. This is achieved by minimizing the misfit between observed and simulated ground motions using the built-in optimization algorithm. Figure 1 shows the Canterbury Velocity Model domain considered including the locations of small-to-moderate Mw events [3-4.5], strong motion stations, and ray paths of observed ground motions. The area covered by the ray paths essentially indicates the area of the model which will be most affected by the waveform inversion. The seismic sources used in the ground motion simulations are centroid moment tensor solutions obtained from GeoNet. All earthquake ruptures are modelled as point sources with a Gaussian source time function. The minimum Mw limit is enforced to ensure good signal-to-noise ratio and well constrained source parameters. The maximum Mw limit is enforced to ensure the point source approximation is valid and to minimize off-fault nonlinear effects.
The Canterbury earthquake and aftershock sequence in New Zealand during 2010-2011 subjected the city’s structures to a significant accumulated cyclic demand and raised significant questions regarding the low-cycle fatigue demands imposed upon the structures. There is a significant challenge to quantify the level of cumulative demand imposed on structures and to assess the percentage of a structure's fatigue life that has been consumed as a result of this earthquake sequence. It is important to be able to quantify the cumulative demand to determine how a building will perform in a subsequent large earthquake and inform repair and re-occupancy decisions. This paper investigates the cumulative fatigue demand for a structure located within the Christchurch Central Business District (CBD). Time history analysis and equivalent cycle counting methods are applied across the Canterbury earthquake sequence, using key events from September 4th 2010 and February 22nd , 2011 main shocks. The estimate of the cumulative fatigue demand is then compared to the expected capacity of a case study reinforced concrete bridge pier, to undertake a structure-specific fatigue assessment. The analysis is undertaken to approximate the portion of the structural fatigue capacity that has been consumed, and how much residual capacity remains. Results are assessed for recordings at the four Christchurch central city strong motion recording sites installed by the GeoNet programme, to provide an estimate of variation in results. The computed cyclic demand results are compared to code-based design methods and as assessment of the inelastic displacement demand of the reinforcing steel. Results are also presented in a fragility context where a de minimis (inconsequential), irreparable damage and full fatigue fracture are defined to provide a probabilistic assessment of the fatigue damage incurred. This methodology can provide input into the overall assessment of fatigue demands and residual capacity.
