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.
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.
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.
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%.
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.
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 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.
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.
The city of Christchurch and its surrounds experienced widespread damage due to soil liquefaction induced by seismic shaking during the Canterbury earthquake sequence that began in September 2010 with the Mw7.1 Darfield earthquake. Prior to the start of this sequence, the city had a large network of strong motion stations (SMSs) installed, which were able to record a vast database of strong ground motions. This paper uses this database of strong ground motion recordings, observations of liquefaction manifestation at the ground surface, and data from a recently completed extensive geotechnical site investigation program at each SMS to assess a range of liquefaction evaluation procedures at the four SMSs in the Christchurch Central Business District (CBD). In general, the characteristics of the accelerograms recorded at each SMS correlated well with the liquefaction evaluation procedures, with low liquefaction factors of safety predicted at sites with clear liquefaction identifiers in the ground motions. However, at sites that likely liquefied at depth (as indicated by evaluation procedures and/or inferred from the characteristics of the recorded surface accelerograms), the presence of a non-liquefiable crust layer at many of the SMS locations prevented the manifestation of any surface effects. Because of this, there was not a good correlation between surface manifestation and two surface manifestation indices, the Liquefaction Potential Index (LPI) and the Liquefaction Severity Number (LSN).
The 2010-2011 Canterbury earthquake sequence was extremely damaging to structures in Christchurch and continues to have a large economic and social impact on the city and surrounding regions. In addition to strong ground shaking (Bradley and Cubrinovski 2011 SRL; Bradley 2012 SDEE), extensive liquefaction was observed, particularly in the 4 September 2010 Darfield earthquake and the 22 February 2011 Christchurch earthquake (Cubrinovski et al. 2010 BNZSEE; 2011 SRL). Large observed vertical ground motion amplitudes were recorded in the events in this sequence, with vertical peak ground accelerations of over 2.2g being observed at the Heathcote Valley Primary School during the Christchurch earthquake, and numerous other vertical motions exceeding 1.0g (Bradley and Cubrinovski 2011 SRL; Bradley 2012 SDEE; Fry et al 2011 SRL). Vertical peak ground accelerations of over 1.2g were observed in the Darfield earthquake.
This dissertation addresses a diverse range of applied aspects in ground motion simulation validation via the response of complex structures. In particular, the following topics are addressed: (i) the investigation of similarity between recorded and simulated ground motions using code-based 3D irregular structural response analysis, (ii) the development of a framework for ground motion simulations validation to identify the cause of differences between paired observed and simulated dataset, and (iii) the illustration of the process of using simulations for seismic performance-based assessment. The application of simulated ground motions is evaluated for utilisation in engineering practice by considering responses of 3D irregular structures. Validation is performed in a code-based context when the NZS1170.5 (NZS1170.5:2004, 2004) provisions are followed for response history analysis. Two real buildings designed by engineers and physically constructed in Christchurch before the 2010-2011 Canterbury earthquake sequence are considered. The responses are compared when the buildings are subjected to 40 scaled recorded and their subsequent simulated ground motions selected from 22 February 2011 Christchurch. The similarity of recorded and simulated responses is examined using statistical methods such as bootstrapping and hypothesis testing to determine whether the differences are statistically significant. The findings demonstrate the applicability of simulated ground motion when the code-based approach is followed in response history analysis. A conceptual framework is developed to link the differences between the structural response subjected to simulated and recorded ground motions to the differences in their corresponding intensity measures. This framework allows the variability to be partitioned into the proportion that can be “explained” by the differences in ground motion intensity measures and the remaining “unexplained” variability that can be attributed to different complexities such as dynamic phasing of multi-mode response, nonlinearity, and torsion. The application of this framework is examined through a hierarchy of structures reflecting a range of complexity from single-degree-of-freedom to 3D multi-degree-of-freedom systems with different materials, dynamic properties, and structural systems. The study results suggest the areas that ground motion simulation should focus on to improve simulations by prioritising the ground motion intensity measures that most clearly account for the discrepancies in simple to complex structural responses. Three approaches are presented to consider recorded or simulated ground motions within the seismic performance-based assessment framework. Considering the applications of ground motions in hazard and response history analyses, different pathways in utilising ground motions in both areas are explored. Recorded ground motions are drawn from a global database (i.e., NGA-West2 Ancheta et al., 2014). The NZ CyberShake dataset is used to obtain simulations. Advanced ground motion selection techniques (i.e., generalized conditional intensity measure, GCIM) are used for ground motion selection at a few intensity levels. The comparison is performed by investigating the response of an example structure (i.e., 12-storey reinforced concrete special moment frame) located in South Island, NZ. Results are compared and contrasted in terms of hazard, groundmotion selection, structural responses, demand hazard, and collapse risk, then, the probable reasons for differences are discussed. The findings from this study highlight the present opportunities and shortcomings in using simulations in risk assessment. i
Generalized conditional intensity measure (GCIM) method is extended to ground motion selection for scenario ruptures. Using different rupture scenarios and site conditions, various aspects of the GCIM methodology are scrutinized, including: (i) implementation of different weight vectors and the composition of the IM vector; (ii) quantifying the importance of replicate selections for different number of desired ground motions; and (iii) the effect of considering bounds on the implicit causal parameters of the prospective ground motions. Using the extended methodology, representative ground motion ensembles for several major earthquake scenarios in New Zealand are developed. Cases considered include representative ground motions for the occurrence of Alpine, Hope, and Porters Pass earthquakes in Christchurch city, and the occurrence of Wellington, Wairarapa, and Ohariu fault ruptures in Wellington city. Challenges in the development of ground motion ensembles for subduction zone earthquakes are also highlighted. The selected 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?”
Generalized conditional intensity measure (GCIM) method is extended to ground motion selection for scenario ruptures. Using different rupture scenarios and site conditions, various aspects of the GCIM methodology are scrutinized, including: (i) implementation of different weight vectors and the composition of the IM vector; (ii) quantifying the importance of replicate selections for different number of desired ground motions; and (iii) the effect of considering bounds on the implicit causal parameters of the prospective ground motions. Using the extended methodology, representative ground motion ensembles for several major earthquake scenarios in New Zealand are developed. Cases considered include representative ground motions for the occurrence of Alpine, Hope, and Porters Pass earthquakes in Christchurch city, and the occurrence of Wellington, Wairarapa, and Ohariu fault ruptures in Wellington city. Challenges in the development of ground motion ensembles for subduction zone earthquakes are also highlighted. The selected 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?”
A preliminary case study assessing the seismic sustainability of two reinforced concrete structures, a frame structure and a wall structure, was conducted to determine which structural system is more seismically sustainable. The two structures were designed to the same standards and were assumed to be located in Christchurch, New Zealand. A component-based probabilistic seismic loss assessment, considering direct losses only, was conducted for two ground motion records, regarded to approximately represent a 1 in 500 year earthquake event and a 1 in 2500 year earthquake event, respectively. It is shown that the wall structure results in lower direct losses than the frame structure in the less severe ground motion scenario. However, in the more severe ground motion scenario, the frame structure results in lower direct losses. Hence, this study demonstrates that which structural system has the lower direct losses depends on the ground motion intensity level.
This study examines the performance of nonlinear total-stress wave-propagation site response analysis 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 3-dimensional ground motion phenomena at the regional scale, as well as detailed site effects and soil nonlinearity 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).
This dissertation addresses a diverse range of topics in the physics-based broadband ground motion simulation, with a focus on New Zealand applications. In particular the following topics are addressed: the methodology and computational implementation of a New Zealand Velocity Model for broadband ground motion simulation; generalised parametric functions and spatial correlations for seismic velocities in the Canterbury, New Zealand region from surface-wave-based site characterisation; and ground motion simulations of Hope Fault earthquakes. The paragraphs below outline each contribution in more detail. A necessary component in physics-based ground motion simulation is a 3D model which details the seismic velocities in the region of interest. Here a velocity model construction methodology, its computational implementation, and application in the construction of a New Zealand velocity model for use in physics-based broadband ground motion simulation are presented. The methodology utilises multiple datasets spanning different length scales, which is enabled via the use of modular sub-regions, geologic surfaces, and parametric representations of crustal velocity. A number of efficiency-related workflows to decrease the overall computational construction time are employed, while maintaining the flexibility and extensibility to incorporate additional datasets and re- fined velocity parameterizations as they become available. The model comprises explicit representations of the Canterbury, Wellington, Nelson-Tasman, Kaikoura, Marlborough, Waiau, Hanmer and Cheviot sedimentary basins embedded within a regional travel-time tomography-based velocity model for the shallow crust and provides the means to conduct ground motion simulations throughout New Zealand for the first time. Recently developed deep shear-wave velocity profiles in Canterbury enabled models that better characterise the velocity structure within geologic layers of the Canterbury sedimentary basin to be developed. Here the development of depth- and Vs30-dependent para-metric velocity and spatial correlation models to characterise shear-wave velocities within the geologic layers of the Canterbury sedimentary basin are presented. The models utilise data from 22 shear-wave velocity profiles of up to 2.5km depth (derived from surface wave analysis) juxtaposed with models which detail the three-dimensional structure of the geologic formations in the Canterbury sedimentary basin. Parametric velocity equations are presented for Fine Grained Sediments, Gravels, and Tertiary layer groupings. Spatial correlations were developed and applied to generate three-dimensional stochastic velocity perturbations. Collectively, these models enable seismic velocities to be realistically represented for applications such as 3D ground motion and site response simulations. Lastly the New Zealand velocity model is applied to simulate ground motions for a Mw7.51 rupture of the Hope Fault using a physics-based simulation methodology and a 3D crustal velocity model of New Zealand. The simulation methodology was validated for use in the region through comparison with observations for a suite of historic small magnitude earthquakes located proximal to the Hope Fault. Simulations are compared with conventionally utilised empirical ground motion models, with simulated peak ground velocities being notably higher in regions with modelled sedimentary basins. A sensitivity analysis was undertaken where the source characteristics of magnitude, stress parameter, hypocentre location and kinematic slip distribution were varied and an analysis of their effect on ground motion intensities is presented. It was found that the magnitude and stress parameter strongly influenced long and short period ground motion amplitudes, respectively. Ground motion intensities for the Hope Fault scenario are compared with the 2016 Kaikoura Mw7.8 earthquake, it was found that the Kaikoura earthquake produced stronger motions along the eastern South Island, while the Hope Fault scenario resulted in stronger motions immediately West of the near-fault region. The simulated ground motions for this scenario complement prior empirically-based estimates and are informative for mitigation and emergency planning purposes.
This paper provides a brief discussion of observed strong ground motions from the 14 November 2016 Mw7.8 Kaikoura earthquake. Specific attention is given to examining observations in the near-source region where several ground motions exceeding 1.0g horizontal are recorded, as well as up to 2.7g in the vertical direction at one location. Ground motion response spectra in the near-source, North Canterbury, Marlborough and Wellington regions are also examined and compared with design levels. Observed spectral amplitudes are also compared with predictions from empirical and physics-based ground motion modelling.
In this paper, we perform hybrid broadband (0-10 Hz) ground motion simulations for the ten most significant events (Mw 4.7-7.1) in the 2010-2011 Canterbury earthquake sequence. Taking advantage of having repeated recordings at same stations, we validate our simulations using both recordings and an empirically-developed ground motion prediction equation (GMPE). The simulation clearly captures the sedimentary basin amplification and the rupture directivity effects. Quantitative comparisons of the simulations with both recordings and the GMPE, as well as analyses of the total residuals (indicating model bias) show that simulations perform better than the empirical GMPE, especially for long period. To scrutinize the ground motion variability, we partitioned the total residuals into different components. The total residual appears to be unbiased, and the use of a 3D velocity structure reduces the long period systematic bias particularly for stations located close to the Banks Peninsula volcanic area.
This paper presents an overview of the soil profile characteristics at strong motion station (SMS) locations in the Christchurch Central Business District (CBD) based on recently completed geotechnical site investigations. Given the variability of Christchurch soils, detailed investigations were needed in close vicinity to each SMS. In this regard, CPT, SPT and borehole data, and shear wave velocity (Vs) profiles from surface wave dispersion data in close vicinity to the SMSs have been used to develop detailed representative soil profiles at each site and to determine site classes according to the New Zealand standard NZS1170.5. A disparity between the NZS1170.5 site classes based on Vs and SPT N60 investigation techniques is highlighted, and additional studies are needed to harmonize site classification based on these techniques. The short period mode of vibration of soft deposits above gravels, which are found throughout Christchurch, are compared to the long period mode of vibration of the entire soil profile to bedrock. These two distinct modes of vibration require further investigation to determine their impact on the site response. According to current American and European approaches to seismic site classification, all SMSs were classified as problematic soil sites due to the presence of liquefiable strata, soils which are not directly accounted for by the NZS1170.5 approach.
Since the early 1980s seismic hazard assessment in New Zealand has been based on Probabilistic Seismic Hazard Analysis (PSHA). The most recent version of the New Zealand National Seismic Hazard Model, a PSHA model, was published by Stirling et al, in 2012. This model follows standard PSHA principals and combines a nation-wide model of active faults with a gridded point-source model based on the earthquake catalogue since 1840. These models are coupled with the ground-motion prediction equation of McVerry et al (2006). Additionally, we have developed a time-dependent clustering-based PSHA model for the Canterbury region (Gerstenberger et al, 2014) in response to the Canterbury earthquake sequence. We are now in the process of revising that national model. In this process we are investigating several of the fundamental assumptions in traditional PSHA and in how we modelled hazard in the past. For this project, we have three main focuses: 1) how do we design an optimal combination of multiple sources of information to produce the best forecast of earthquake rates in the next 50 years: can we improve upon a simple hybrid of fault sources and background sources, and can we better handle the uncertainties in the data and models (e.g., fault segmentation, frequency-magnitude distributions, time-dependence & clustering, low strain-rate areas, and subduction zone modelling)? 2) developing revised and new ground-motion predictions models including better capturing of epistemic uncertainty – a key focus in this work is developing a new strong ground motion catalogue for model development; and 3) how can we best quantify if changes we have made in our modelling are truly improvements? Throughout this process we are working toward incorporating numerical modelling results from physics based synthetic seismicity and ground-motion models.
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.
This study investigates the uncertainty of simulated earthquake ground motions for smallmagnitude events (Mw 3.5 – 5) in Canterbury, New Zealand. 148 events were simulated with specified uncertainties in: event magnitude, hypocentre location, focal mechanism, high frequency rupture velocity, Brune stress parameter, the site 30-m time-averaged shear wave velocity (Vs30), anelastic attenuation (Q) and high frequency path duration. In order to capture these uncertainties, 25 realisations for each event were generated using the Graves and Pitarka (2015) hybrid broadband simulation approach. Monte-Carlo realisations were drawn from distributions for each uncertainty, to generate a suite of simulation realisations for each event and site. The fit of the multiple simulation realisations to observations were assessed using linear mixed effects regression to generate the systematic source, path and site effects components across all ground motion intensity measure residuals. Findings show that additional uncertainties are required in each of the three source, path, and site components, however the level of output uncertainty is promising considering the input uncertainties included.
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