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.
This paper presents on-going challenges in the present paradigm shift of earthquakeinduced ground motion prediction from empirical to physics-based simulation methods. The 2010-2011 Canterbury and 2016 Kaikoura earthquakes are used to illustrate the predictive potential of the different methods. On-going efforts on simulation validation and theoretical developments are then presented, as well as the demands associated with the need for explicit consideration of modelling uncertainties. Finally, discussion is also given to the tools and databases needed for the efficient utilization of simulated ground motions both in specific engineering projects as well as for near-real-time impact assessment.
This report presents the simplified seismic assessment of a case study reinforced concrete (RC) building following the newly developed and refined NZSEE/MBIE guidelines on seismic assessment (NZSEE/MBIE, semi-final draft 26 October 2016). After an overview of the step-by-step ‘diagnostic’ process, including an holistic and qualitative description of the expected vulnerabilities and of the assessment strategy/methodology, focus is given, whilst not limited, to the implementation of a Detailed Seismic Assessment (DSA) (NZSEE/MBIE, 2016c). The DSA is intended to provide a more reliable and consistent outcome than what can be provided by an initial seismic assessment (ISA). In fact, while the Initial Seismic Assessment (ISA), of which the Initial Evaluation Procedure is only a part of, is the more natural and still recommended first step in the overall assessment process, it is mostly intended to be a coarse evaluation involving as few resources as reasonably possible. It is thus expected that an ISA will be followed by a Detailed Seismic Assessment (DSA) not only where the threshold of 33%NBS is not achieved but also where important decisions are intended that are reliant on the seismic status of the building. The use of %NBS (% New Building Standard) as a capacity/demand ratio to describe the result of the seismic assessment at all levels of assessment procedure (ISA through to DSA) is deliberate by the NZSEE/MBIE guidelines (Part A) (NZSEE/MBIE 2016a). The rating for the building needs only be based on the lowest level of assessment that is warranted for the particular circumstances. Discussion on how the %NBS rating is to be determined can be found in Section A3.3 (NZSEE/MBIE 2016a), and, more specifically, in Part B for the ISA (NZSEE/MBIE 2016b) and Part C for the DSA (NZSEE/MBIE 2016c). As per other international approaches, the DSA can be based on several analysis procedures to assess the structural behaviour (linear, nonlinear, static or dynamic, force or displacement-based). The significantly revamped NZSEE 2016 Seismic Assessment Guidelines strongly recommend the use of an analytical (basically ‘by hand’) method, referred to the Simple Lateral Mechanism Analysis (SLaMA) as a first phase of any other numerically-based analysis method. Significant effort has thus been dedicated to provide within the NZSEE 2016 guidelines (NZSEE/MBIE 2016c) a step-by-step description of the procedure, either in general terms (Chapter 2) or with specific reference to Reinforced Concrete Buildings (Chapter 5). More specifically, extract from the guidelines, NZSEE “recommend using the Simple Lateral Mechanism Analysis (SLaMA) procedure as a first step in any assessment. While SLaMA is essentially an analysis technique, it enables assessors to investigate (and present in a simple form) the potential contribution and interaction of a number of structural elements and their likely effect on the building’s global capacity. In some cases, the results of a SLaMA will only be indicative. However, it is expected that its use should help assessors achieve a more reliable outcome than if they only carried out a detailed analysis, especially if that analysis is limited to the elastic range For complex structural systems, a 3D dynamic analysis may be necessary to supplement the simplified nonlinear Simple Lateral Mechanism Analysis (SLaMA).” This report presents the development of a full design example for the the implementation of the SLaMA method on a case study buildings and a validation/comparison with a non-linear static (pushover) analysis. The step-by-step-procedure, summarized in Figure 1, will be herein demonstrated from a component level (beams, columns, wall elements) to a subassembly level (hierarchy of strength in a beam-column joint) and to a system level (frame, C-Wall) assuming initially a 2D behaviour of the key structural system, and then incorporating a by-hand 3D behaviour (torsional 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.
