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.
The purpose of this thesis is to conduct a detailed examination of the forward-directivity characteristics of near-fault ground motions produced in the 2010-11 Canterbury earthquakes, including evaluating the efficacy of several existing empirical models which form the basis of frameworks for considering directivity in seismic hazard assessment. A wavelet-based pulse classification algorithm developed by Baker (2007) is firstly used to identify and characterise ground motions which demonstrate evidence of forward-directivity effects from significant events in the Canterbury earthquake sequence. The algorithm fails to classify a large number of ground motions which clearly exhibit an early-arriving directivity pulse due to: (i) incorrect pulse extraction resulting from the presence of pulse-like features caused by other physical phenomena; and (ii) inadequacy of the pulse indicator score used to carry out binary pulse-like/non-pulse-like classification. An alternative ‘manual’ approach is proposed to ensure 'correct' pulse extraction and the classification process is also guided by examination of the horizontal velocity trajectory plots and source-to-site geometry. Based on the above analysis, 59 pulse-like ground motions are identified from the Canterbury earthquakes , which in the author's opinion, are caused by forward-directivity effects. The pulses are also characterised in terms of their period and amplitude. A revised version of the B07 algorithm developed by Shahi (2013) is also subsequently utilised but without observing any notable improvement in the pulse classification results. A series of three chapters are dedicated to assess the predictive capabilities of empirical models to predict the: (i) probability of pulse occurrence; (ii) response spectrum amplification caused by the directivity pulse; (iii) period and amplitude (peak ground velocity, PGV) of the directivity pulse using observations from four significant events in the Canterbury earthquakes. Based on the results of logistic regression analysis, it is found that the pulse probability model of Shahi (2013) provides the most improved predictions in comparison to its predecessors. Pulse probability contour maps are developed to scrutinise observations of pulses/non-pulses with predicted probabilities. A direct comparison of the observed and predicted directivity amplification of acceleration response spectra reveals the inadequacy of broadband directivity models, which form the basis of the near-fault factor in the New Zealand loadings standard, NZS1170.5:2004. In contrast, a recently developed narrowband model by Shahi & Baker (2011) provides significantly improved predictions by amplifying the response spectra within a small range of periods. The significant positive bias demonstrated by the residuals associated with all models at longer vibration periods (in the Mw7.1 Darfield and Mw6.2 Christchurch earthquakes) is likely due to the influence of basin-induced surface waves and non-linear soil response. Empirical models for the pulse period notably under-predict observations from the Darfield and Christchurch earthquakes, inferred as being a result of both the effect of nonlinear site response and influence of the Canterbury basin. In contrast, observed pulse periods from the smaller magnitude June (Mw6.0) and December (Mw5.9) 2011 earthquakes are in good agreement with predictions. Models for the pulse amplitude generally provide accurate estimates of the observations at source-to-site distances between 1 km and 10 km. At longer distances, observed PGVs are significantly under-predicted due to their slower apparent attenuation. Mixed-effects regression is employed to develop revised models for both parameters using the latest NGA-West2 pulse-like ground motion database. A pulse period relationship which accounts for the effect of faulting mechanism using rake angle as a continuous predictor variable is developed. The use of a larger database in model development, however does not result in improved predictions of pulse period for the Darfield and Christchurch earthquakes. In contrast, the revised model for PGV provides a more appropriate attenuation of the pulse amplitude with distance, and does not exhibit the bias associated with previous models. Finally, the effects of near-fault directivity are explicitly included in NZ-specific probabilistic seismic hazard analysis (PSHA) using the narrowband directivity model of Shahi & Baker (2011). Seismic hazard analyses are conducted with and without considering directivity for typical sites in Christchurch and Otira. The inadequacy of the near-fault factor in the NZS1170.5: 2004 is apparent based on a comparison with the directivity amplification obtained from PSHA.
In this paper, the characteristics of near-fault ground motions recorded during the Mw7.1 Darfield and Mw 6.2 Christchurch earthquakes are examined and compared with existing empirical models. The characteristics of forward-directivity effects are first examined using a wavelet-based pulse-classification algorithm. This is followed by an assessment of the adequacy of empirical models which aim to capture the effect of directivity effects on amplifying the acceleration response spectra; and the period and peak velocity of the forward-directivity pulse. It is illustrated that broadband directivity models developed by Somerville et al. (1997) and Abrahamson (2000) generally under-predict the observed amplification of response spectral ordinates at longer vibration periods. In contrast, a recently developed narrowband model by Shahi and Baker (2011) provides significantly improved predictions by amplifying the response spectra within a small range of periods surrounding the directivity pulse period. Although the empirical predictions of the pulse period are generally favourable for the Christchurch earthquake, the observations from the Darfield earthquake are significantly under-predicted. The elongation in observed pulse periods is inferred as being a result of the soft sedimentary soils of the Canterbury basin. However, empirical predictions of the observed peak velocity associated with the directivity pulse are generally adequate for both events.
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.
The 2010 Darfield and 2011 Christchurch Earthquakes triggered extensive liquefaction-induced lateral spreading proximate to streams and rivers in the Christchurch area, causing significant damage to structures and lifelines. A case study in central Christchurch is presented and compares field observations with predicted displacements from the widely adopted empirical model of Youd et al. (2002). Cone penetration testing (CPT), with measured soil gradation indices (fines content and median grain size) on typical fluvial deposits along the Avon River were used to determine the required geotechnical parameters for the model input. The method presented attempts to enable the adoption of the extensive post-quake CPT test records in place of the lower quality and less available Standard Penetration Test (SPT) data required by the original Youd model. The results indicate some agreement between the Youd model predictions and the field observations, while the majority of computed displacements error on the side of over-prediction by more than a factor of two. A sensitivity analysis was performed with respect to the uncertainties used as model input, illustrating the model’s high sensitivity to the input parameters, with median grain size and fines content among the most influential, and suggesting that the use of CPT data to quantify these parameters may lead to variable results.
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.
Having a quick but reliable insight into the likelihood of damage to bridges immediately after an earthquake is an important concern especially in the earthquake prone countries such as New Zealand for ensuring emergency transportation network operations. A set of primary indicators necessary to perform damage likelihood assessment are ground motion parameters such as peak ground acceleration (PGA) at each bridge site. Organizations, such as GNS in New Zealand, record these parameters using distributed arrays of sensors. The challenge is that those sensors are not installed at, or close to, bridge sites and so bridge site specific data are not readily available. This study proposes a method to predict ground motion parameters for each bridge site based on remote seismic array recordings. Because of the existing abundant source of data related to two recent strong earthquakes that occurred in 2010 and 2011 and their aftershocks, the city of Christchurch is considered to develop and examine the method. Artificial neural networks have been considered for this research. Accelerations recorded by the GeoNet seismic array were considered to develop a functional relationship enabling the prediction of PGAs. http://www.nzsee.org.nz/db/2013/Posters.htm
Liquefaction-induced lateral spreading in Christchurch and surrounding suburbs during the recent Canterbury Earthquake Sequence (2010-2011) caused significant damage to structures and lifelines located in close proximity to streams and rivers. Simplified methods used in current engineering practice for predicting lateral ground displacements exhibit a high degree of epistemic uncertainty, but provide ‘order of magnitude’ estimates to appraise the hazard. We wish to compare model predictions to field measurements in order to assess the model’s capabilities and limitations with respect to Christchurch conditions. The analysis presented focuses on the widely-used empirical model of Youd et al. (2002), developed based on multi-linear regression (MLR) of case history data from lateral spreading occurrence in Japan and the US. Two issues arising from the application of this model to Christchurch were considered: • Small data set of Standard Penetration Test (SPT) and soil gradation indices (fines content FC, and mean grain size, D50) required for input. We attempt to use widely available CPT data with site specific correlations to FC and D50. • Uncertainty associated with the model input parameters and their influence on predicted displacements. This has been investigated for a specific location through a sensitivity analysis.
Globally, the maximum elevations at which treelines are observed to occur coincide with a 6.4 °C soil isotherm. However, when observed at finer scales, treelines display a considerable degree of spatial complexity in their patterns across the landscape and are often found occurring at lower elevations than expected relative to the global-scale pattern. There is still a
lack of understanding of how the abiotic environment imposes constraints on treeline patterns, the scales at which different effects are acting, and how these effects vary over large spatial extents. In this thesis, I examined abrupt Nothofagus treelines across seven degrees of
latitude in New Zealand in order to investigate two broad questions: (1) What is the nature and extent of spatial variability in Nothofagus treelines across the country? (2) How is this variation associated with abiotic variation at different spatial scales? A range of GIS, statistical, and atmospheric modelling methods were applied to address these two questions.
First, I characterised Nothofagus treeline patterns at a 15x15km scale across New Zealand using a set of seven, GIS-derived, quantitative metrics that describe different aspects of treeline position, shape, spatial configuration, and relationships with adjacent vegetation.
Multivariate clustering of these metrics revealed distinct treeline types that showed strong spatial aggregation across the country. This suggests a strong spatial structuring of the abiotic environment which, in turn, drives treeline patterns. About half of the multivariate treeline
metric variation was explained by patterns of climate, substrate, topographic and disturbance variability; on the whole, climatic and disturbance factors were most influential.
Second, I developed a conceptual model that describes how treeline elevation may
vary at different scales according to three categories of effects: thermal modifying effects, physiological stressors, and disturbance effects. I tested the relevance of this model for Nothofagus treelines by investigating treeline elevation variation at five nested scales (regional to local) using a hierarchical design based on nested river catchments. Hierarchical linear modelling revealed that the majority of the variation in treeline elevation resided at the broadest, regional scale, which was best explained by the thermal modifying effects of solar radiation, mountain mass, and differences in the potential for cold air ponding. Nonetheless, at finer scales, physiological and disturbance effects were important and acted to modify the regional trend at these scales. These results suggest that variation in abrupt treeline elevations
are due to both broad-scale temperature-based growth limitation processes and finer-scale stress- and disturbance-related effects on seedling establishment.
Third, I explored the applicability of a meso-scale atmospheric model, The Air
Pollution Model (TAPM), for generating 200 m resolution, hourly topoclimatic data for
temperature, incoming and outgoing radiation, relative humidity, and wind speeds. Initial assessments of TAPM outputs against data from two climate station locations over seven years showed that the model could generate predictions with a consistent level of accuracy for both sites, and which agreed with other evaluations in the literature. TAPM was then used to generate data at 28, 7x7 km Nothofagus treeline zones across New Zealand for January
(summer) and July (winter) 2002. Using mixed-effects linear models, I determined that both
site-level factors (mean growing season temperature, mountain mass, precipitation,
earthquake intensity) and local-level landform (slope and convexity) and topoclimatic factors (solar radiation, photoinhibition index, frost index, desiccation index) were influential in
explaining variation in treeline elevation within and among these sites. Treelines were
generally closer to their site-level maxima in regions with higher mean growing season
temperatures, larger mountains, and lower levels of precipitation. Within sites, higher
treelines were associated with higher solar radiation, and lower photoinhibition and
desiccation index values, in January, and lower desiccation index values in July. Higher treelines were also significantly associated with steeper, more convex landforms.
Overall, this thesis shows that investigating treelines across extensive areas at multiple study scales enables the development of a more comprehensive understanding of treeline variability and underlying environmental constraints. These results can be used to formulate new hypotheses regarding the mechanisms driving treeline formation and to guide the optimal choice of field sites at which to test these hypotheses.
