Media law developments have continued across many areas in the period to mid-2013. In defamation, the New Zealand courts have begun to consider the issue of third party liability for publication on the internet, with cases involving Google searches and comments on a Facebook page. A parliamentary inquiry into a case that restricted parliamentary privilege has recommended a Parliamentary Privilege Act containing a definition of ‘proceedings in Parliament’. A satirical website increased its popularity when it fought off threatened defamation proceedings. In breach of confidence, a government body, the Earthquake Commission, obtained an interim injunction prohibiting publication of information accidentally released that dealt with the repair of earthquake-damaged properties in Christchurch, and a blogger made the information available online in breach of the order.
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.
Welcome to the Recover issue 3 newsletter from the Marine Ecology Research Group (MERG) at the University of Canterbury. Recover is designed to keep you updated on our MBIE funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). In this third instalment we are looking into recent paua, whitebait, and … work our team has undertaken.
Welcome to the Recover newsletter Issue 4 from the Marine Ecology Research Group (MERG) of the University of Canterbury. Recover is designed to keep you updated on our MBIE-funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This 4th instalment covers recent work on seaweed recovery in the subtidal zone, ecological engineering in Waikoau / Lyell Creek, and a sneak preview of drone survey results!
Welcome to the Recover newsletter Issue 2 from the Marine Ecology Research Group (MERG) at the University of Canterbury. Recover is designed to keep you updated on our MBIE funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This second issue profiles some of the recent work done by our team out in the field!
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.
Welcome to the Recover newsletter Issue 6 from the Marine Ecology Research Group (MERG) of the University of Canterbury. Recover is designed to keep you updated on our MBIE-funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This 6th instalment features the ‘new land’ created by the earthquake uplift of the coastline, recreational uses of beaches in Marlborough, and pāua survey work and hatchery projects with our partners in Kaikōura.
Welcome to the first Recover newsletter from the Marine Ecology Research Group (MERG) at the University of Canterbury. Recover is designed to keep you updated on our MBIE funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Ecosystem Recovery). This first issue provides a summary of some of the big changes we’ve seen. In the next issue we’ll be profiling some of the current research as well as ways you can get involved!
Welcome to the Recover newsletter Issue 5 from the Marine Ecology Research Group (MERG) of the University of Canterbury. Recover is designed to keep you updated on our MBIE-funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This 5th instalment covers the question of how much of the coast uplifted how much, recent lab work on seaweed responses to stressors, and more on our drone survey work to quantify earthquake impacts and recovery along 130 km of coastline in the intertidal zone!
Predicting building collapse due to seismic motion is critical in design and more so after a major event. Damaged structures can appear sound, but collapse under following major events. There can thus be significant risk in decision making after a major seismic event concerning the safe occupation of a building or surrounding areas, versus the unknown impact of unknown major aftershocks. Model-based pushover analyses are effective if the structural properties are well understood, which is not valid post-event when this risk information is most useful. This research combines Hysteresis Loop Analysis (HLA) structural health monitoring (SHM) and Incremental Dynamic Analysis (IDA) methods to determine collapse capacity and probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. The nonlinear dynamic analysis method presented enables constant updating of building performance predictions using post-event SHM results. The resulting combined methods provide near real-time updating of collapse fragility curves as events progress, quantifying the change of collapse probability or seismic induced losses for decision-making - a novel, higher resolution risk analysis than previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model. Results show significant potential benefits and a clear evolution of risk. They also show clear need for extending SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010-2011 had significant post-event aftershocks after each main event. Finally, the overall method is generalisable to any typical engineering demand parameter.
A team of earthquake geologists, seismologists and engineering seismologists from GNS Science, NIWA, University of Canterbury, and Victoria University of Wellington have collectively produced an update of the 2002 national probabilistic seismic hazard (PSH) model for New Zealand. The new model incorporates over 200 new onshore and offshore fault sources, and utilises newly developed New Zealand-based scaling relationships and methods for the parameterisation of the fault and subduction interface sources. The background seismicity model has also been updated to include new seismicity data, a new seismicity regionalisation, and improved methodology for calculation of the seismicity parameters. Background seismicity models allow for the occurrence of earthquakes away from the known fault sources, and are typically modelled as a grid of earthquake sources with rate parameters assigned from the historical seismicity catalogue. The Greendale Fault, which ruptured during the M7.1, 4 September 2010 Darfield earthquake, was unknown prior to the earthquake. However, the earthquake was to some extent accounted for in the PSH model. The maximum magnitude assumed in the background seismicity model for the area of the earthquake is 7.2 (larger than the Darfield event), but the location and geometry of the fault are not represented. Deaggregations of the PSH model for Christchurch at return periods of 500 years and above show that M7-7.5 fault and background source-derived earthquakes at distances less than 40 km are important contributors to the hazard. Therefore, earthquakes similar to the Darfield event feature prominently in the PSH model, even though the Greendale Fault was not an explicit model input.
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Prediction of building collapse due to significant seismic motion is a principle objective of earthquake engineers, particularly after a major seismic event when the structure is damaged and decisions may need to be made rapidly concerning the safe occupation of a building or surrounding areas. Traditional model-based pushover analyses are effective, but only if the structural properties are well understood, which is not the case after an event when that information is most useful. This paper combines hysteresis loop analysis (HLA) structural health monitoring (SHM) and incremental dynamic analysis (IDA) methods to identify and then analyse collapse capacity and the probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. This nonlinear dynamic analysis enables constant updating of building performance predictions following a given and subsequent earthquake events, which can result in difficult to identify deterioration of structural components and their resulting capacity, all of which is far more difficult using static pushover analysis. The combined methods and analysis provide near real-time updating of the collapse fragility curves as events progress, thus quantifying the change of collapse probability or seismic induced losses very soon after an earthquake for decision-making. Thus, this combination of methods enables a novel, higher-resolution analysis of risk that was not previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model, thus providing a relatively simpler means of assessing collapse probability immediately post-event when such speed can provide better information for critical decision-making. Finally, the results also show a clear need to extend the area of SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010–2011 had significant post-event aftershocks.
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.
Recent surface-rupturing earthquakes in New Zealand have highlighted significant exposure and vulnerability of the road network to fault displacement. Understanding fault displacement hazard and its impact on roads is crucial for mitigating risks and enhancing resilience. There is a need for regional-scale assessments of fault displacement to identify vulnerable areas within the road network for the purposes of planning and prioritising site-specific investigations. This thesis employs updated analysis of data from three historical surface-rupturing earthquakes (Edgecumbe 1987, Darfield 2010, and Kaikoūra 2016) to develop an empirical model that addresses the gap in regional fault displacement hazard analysis. The findings contribute to understanding of • How to use seismic hazard model inputs for regional fault displacement hazard analysis • How faulting type and sediment cover affects the magnitude and spatial distribution of fault displacement • How the distribution of displacement and regional fault displacement hazard is impacted by secondary faulting • The inherent uncertainties and limitations associated with employing an empirical approach at a regional scale • Which sections of New Zealand’s roading network are most susceptible to fault displacement hazard and warrant site-specific investigations • Which regions should prioritise updating emergency management plans to account for post-event disruptions to roading. I used displacement data from the aforementioned historical ruptures to generate displacement versus distance-to-fault curves for various displacement components, fault types, and geological characteristics. Using those relationships and established relationships for along-strike displacement, displacement contours were generated surrounding active faults within the NZ Community Fault Model. Next, I calculated a new measure of 1D strain along roads as well as relative hazard, which integrated 1D strain and normalised slip rate data. Summing these values at the regional level identified areas of heightened relative hazard across New Zealand, and permits an assessment of the susceptibility of road networks using geomorphon land classes as proxies for vulnerability. The results reveal that fault-parallel displacements tend to localise near the fault plane, while vertical and fault-perpendicular displacements sustain over extended distances. Notably, no significant disparities were observed in off-fault displacement between the hanging wall and footwall sides of the fault, or among different surface geology types, potentially attributed to dataset biases. The presence of secondary faulting in the dataset contributes to increased levels of tectonic displacement farther from the fault, highlighting its significance in hazard assessments. Furthermore, fault displacement contours delineate broader zones around dip-slip faults compared to strike-slip faults, with correlations identified between fault length and displacement width. Road ‘strain’ values are higher around dip-slip faults, with notable examples observed in the Westland and Buller Districts. As expected, relative hazard analysis revealed elevated values along faults with high slip rates, notably along the Alpine Fault. A regional-scale analysis of hazard and exposure reveals heightened relative hazard in specific regions, including Wellington, Southern Hawke’s Bay, Central Bay of Plenty, Central West Coast, inland Canterbury, and the Wairau Valley of Marlborough. Notably, the Central West Coast exhibits the highest summed relative hazard value, attributed to the fast-slipping Alpine Fault. The South Island generally experiences greater relative hazard due to larger and faster-slipping faults compared to the North Island, despite having fewer roads. Central regions of New Zealand face heightened risk compared to Southern or Northern regions. Critical road links intersecting high-slipping faults, such as State Highways 6, 73, 1, and 2, necessitate prioritisation for site-specific assessments, emergency management planning and targeted mitigation strategies. Roads intersecting with the Alpine Fault are prone to large parallel displacements, requiring post-quake repair efforts. Mitigation strategies include future road avoidance of nearby faults, modification of road fill and surface material, and acknowledgement of inherent risk, leading to prioritised repair efforts of critical roads post-quake. Implementing these strategies enhances emergency response efforts by improving accessibility to isolated regions following a major surface-rupturing event, facilitating faster supply delivery and evacuation assistance. This thesis contributes to the advancement of understanding fault displacement hazard by introducing a novel regional, empirical approach. The methods and findings highlight the importance of further developing such analyses and extending them to other critical infrastructure types exposed to fault displacement hazard in New Zealand. Enhancing our comprehension of the risks associated with fault displacement hazard offers valuable insights into various mitigation strategies for roading infrastructure and informs emergency response planning, thereby enhancing both national and global infrastructure resilience against geological hazards.
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.
In September 2010 and February 2011, the Canterbury region experienced devastating earthquakes with an estimated economic cost of over NZ$40 billion (Parker and Steenkamp, 2012; Timar et al., 2014; Potter et al., 2015). The insurance market played an important role in rebuilding the Canterbury region after the earthquakes. Homeowners, insurance and reinsurance markets and New Zealand government agencies faced a difficult task to manage the rebuild process. From an empirical and theoretic research viewpoint, the Christchurch disaster calls for an assessment of how the insurance market deals with such disasters in the future. Previous studies have investigated market responses to losses in global catastrophes by focusing on the insurance supply-side. This study investigates both demand-side and supply-side insurance market responses to the Christchurch earthquakes. Despite the fact that New Zealand is prone to seismic activities, there are scant previous studies in the area of earthquake insurance. This study does offer a unique opportunity to examine and document the New Zealand insurance market response to catastrophe risk, providing results critical for understanding market responses after major loss events in general. A review of previous studies shows higher premiums suppress demand, but how higher premiums and a higher probability of risk affect demand is still largely unknown. According to previous studies, the supply of disaster coverage is curtailed unless the market is subsidised, however, there is still unsettled discussion on why demand decreases with time from the previous disaster even when the supply of coverage is subsidised by the government. Natural disaster risks pose a set of challenges for insurance market players because of substantial ambiguity associated with the probability of such events occurring and high spatial correlation of catastrophe losses. Private insurance market inefficiencies due to high premiums and spatially concentrated risks calls for government intervention in the provision of natural disaster insurance to avert situations of noninsurance and underinsurance. Political economy considerations make it more likely for government support to be called for if many people are uninsured than if few people are uninsured. However, emergency assistance for property owners after catastrophe events can encourage most property owners to not buy insurance against natural disaster and develop adverse selection behaviour, generating larger future risks for homeowners and governments. On the demand-side, this study has developed an intertemporal model to examine how demand for insurance changes post-catastrophe, and how to model it theoretically. In this intertemporal model, insurance can be sought in two sequential periods of time, and at the second period, it is known whether or not a loss event happened in period one. The results show that period one demand for insurance increases relative to the standard single period model when the second period is taken into consideration, period two insurance demand is higher post-loss, higher than both the period one demand and the period two demand without a period one loss. To investigate policyholders experience from the demand-side perspective, a total of 1600 survey questionnaires were administered, and responses from 254 participants received representing a 16 percent response rate. Survey data was gathered from four institutions in Canterbury and is probably not representative of the entire population. The results of the survey show that the change from full replacement value policy to nominated replacement value policy is a key determinant of the direction of change in the level of insurance coverage after the earthquakes. The earthquakes also highlighted the plight of those who were underinsured, prompting policyholders to update their insurance coverage to reflect the estimated cost of re-building their property. The survey has added further evidence to the existing literature, such as those who have had a recent experience with disaster loss report increased risk perception if a similar event happens in future with females reporting a higher risk perception than males. Of the demographic variables, only gender has a relationship with changes in household cover. On the supply-side, this study has built a risk-based pricing model suitable to generate a competitive premium rate for natural disaster insurance cover. Using illustrative data from the Christchurch Red-zone suburbs, the model generates competitive premium rates for catastrophe risk. When the proposed model incorporates the new RMS high-definition New Zealand Earthquake Model, for example, insurers can find the model useful to identify losses at a granular level so as to calculate the competitive premium. This study observes that the key to the success of the New Zealand dual insurance system despite the high prevalence of catastrophe losses are; firstly the EQC’s flat-rate pricing structure keeps private insurance premiums affordable and very high nationwide homeowner take-up rates of natural disaster insurance. Secondly, private insurers and the EQC have an elaborate reinsurance arrangement in place. By efficiently transferring risk to the reinsurer, the cost of writing primary insurance is considerably reduced ultimately expanding primary insurance capacity and supply of insurance coverage.
