Geospatial liquefaction models aim to predict liquefaction using data that is free and readily-available. This data includes (i) common ground-motion intensity measures; and (ii) geospatial parameters (e.g., among many, distance to rivers, distance to coast, and Vs30 estimated from topography) which are used to infer characteristics of the subsurface without in-situ testing. Since their recent inception, such models have been used to predict geohazard impacts throughout New Zealand (e.g., in conjunction with regional ground-motion simulations). While past studies have demonstrated that geospatial liquefaction-models show great promise, the resolution and accuracy of the geospatial data underlying these models is notably poor. As an example, mapped rivers and coastlines often plot hundreds of meters from their actual locations. This stems from the fact that geospatial models aim to rapidly predict liquefaction anywhere in the world and thus utilize the lowest common denominator of available geospatial data, even though higher quality data is often available (e.g., in New Zealand). Accordingly, this study investigates whether the performance of geospatial models can be improved using higher-quality input data. This analysis is performed using (i) 15,101 liquefaction case studies compiled from the 2010-2016 Canterbury Earthquakes; and (ii) geospatial data readily available in New Zealand. In particular, we utilize alternative, higher-quality data to estimate: locations of rivers and streams; location of coastline; depth to ground water; Vs30; and PGV. Most notably, a region-specific Vs30 model improves performance (Figs. 3-4), while other data variants generally have little-to-no effect, even when the “standard” and “high-quality” values differ significantly (Fig. 2). This finding is consistent with the greater sensitivity of geospatial models to Vs30, relative to any other input (Fig. 5), and has implications for modeling in locales worldwide where high quality geospatial data is available.
The 14 November 2016 Kaikōura earthquake had major impacts on New Zealand's transport system. Road, rail and port infrastructure was damaged, creating substantial disruption for transport operators, residents, tourists, and business owners in the Canterbury, Marlborough and Wellington regions, with knock-on consequences elsewhere. During both the response and recovery phases, a large amount of information and data relating to the transport system was generated, managed, analysed, and exchanged within and between organisations to assist decision making. To improve information and data exchanges and related decision making in the transport sector during future events and guide new resilience strategies, we present key findings from a recent post-earthquake assessment. The research involved 35 different stakeholder groups and was conducted for the Ministry of Transport. We consider what transport information was available, its usefulness, where it was sourced from, mechanisms for data transfer between organisations, and suggested approaches for continued monitoring.
Natural catastrophes are increasing worldwide. They are becoming more frequent but also more severe and impactful on our built environment leading to extensive damage and losses. Earthquake events account for the smallest part of natural events; nevertheless seismic damage led to the most fatalities and significant losses over the period 1981-2016 (Munich Re). Damage prediction is helpful for emergency management and the development of earthquake risk mitigation projects. Recent design efforts focused on the application of performance-based design engineering where damage estimation methodologies use fragility and vulnerability functions. However, the approach does not explicitly specify the essential criteria leading to economic losses. There is thus a need for an improved methodology that finds the critical building elements related to significant losses. The here presented methodology uses data science techniques to identify key building features that contribute to the bulk of losses. It uses empirical data collected on site during earthquake reconnaissance mission to train a machine learning model that can further be used for the estimation of building damage post-earthquake. The first model is developed for Christchurch. Empirical building damage data from the 2010-2011 earthquake events is analysed to find the building features that contributed the most to damage. Once processed, the data is used to train a machine-learning model that can be applied to estimate losses in future earthquake events.
After the Christchurch earthquakes, the government declared about 8000 houses as Red Zoned, prohibiting further developments in these properties, and offering the owners to buy them out. The government provided two options for owners: the first was full payment for both land and dwelling at the 2007 property evaluation, the second was payment for land, and the rest to be paid by the owner’s insurance. Most people chose the second option. Using data from LINZ combined with data from StatNZ, this project empirically investigates what led people to choose this second option, and what were the implications of these choices for the owners’ wealth and income.
Nowadays the telecommunication systems’ performance has a substantial impact on our lifestyle. Their operationality becomes even more substantial in a post-disaster scenario when these services are used in civil protection and emergency plans, as well as for the restoration of all the other critical infrastructure. Despite the relevance of loss of functionality of telecommunication networks on seismic resilience, studies on their performance assessment are few in the literature. The telecommunication system is a distributed network made up of several components (i.e. ducts, utility holes, cabinets, major and local exchanges). Given that these networks cover a large geographical area, they can be easily subjected to the effects of a seismic event, either the ground shaking itself, or co-seismic events such as liquefaction and landslides. In this paper, an analysis of the data collected after the 2010-2011 Canterbury Earthquake Sequence (CES) and the 2016 Kaikoura Earthquake in New Zealand is conducted. Analysing these data, information gaps are critically identified regarding physical and functional failures of the telecommunication components, the timeline of repair/reconstruction activities and service recovery, geotechnical tests and land planning maps. Indeed, if these missing data were presented, they could aid the assessment of the seismic resilience. Thus, practical improvements in the post-disaster collection from both a network and organisational viewpoints are proposed through consultation of national and international researchers and highly experienced asset managers from Chorus. Finally, an outline of future studies which could guide towards a more resilient seismic performance of the telecommunication network is presented.
This research aims to explore how business models of SMEs revolve in the face of a crisis to be resilient. The business model canvas was used as a tool to analyse business models of SMEs in Greater Christchurch. The purpose was to evaluate the changes SMEs brought in their business models after hit by a series of earthquake in 2010 and 2011. The idea was to conduct interviews of business owners and analyse using grounded theory methods. Because this method is iterative, a tentative theoretical framework was proposed, half way through the data collection. It was realised that owner specific characteristics were more prominent in the data than the elements business model. Although, SMEs in this study experienced several operational changes in their business models such as change of location and modification of payment terms. However, the suggested framework highlights how owner specific attributes influence the survival of a small business. Small businesses and their owners are extremely interrelated that the business models personify the owner specific characteristics. In other words, the adaptation of the business model reflects the extent to which the owner possess these attributes. These attributes are (a) Mindsets – the attitude and optimism of business owner; (b) Adaptive coping – the ability of business owner to take corrective actions; and (c) Social capital – the network of a business owner, including family, friends, neighbours and business partners.
Research following the 2010-2011 Canterbury earthquakes investigated the minimum vertical reinforcement required in RC walls to generate well distributed cracking in the plastic hinge region. However, the influence of the loading sequence and rate has not been fully addressed. The new minimum vertical reinforcement limits in NZS 3101:2006 (Amendment 3) include consideration of the material strengths under dynamic load rates, but these provisions have not been validated at a member or system level. A series of tests were conducted on RC prisms to investigate the effect of loading rate and sequence on the local behaviour of RC members. Fifteen axially loaded RC prisms with the designs representing the end region of RC walls were tested under various loading rates to cover the range of pseudo-static and earthquake loading scenarios. These tests will provide substantial data for understanding the local behaviour of RC members, including hysteretic load-deformation behaviour, crack patterns, failure mode, steel strain, strain rate and ductility. Recommendations will be made regarding the effect of loading rate and reinforcement content on the cracking behaviour and ductility of RC members.
Reinforced concrete buildings that satisfied modern seismic design criteria generally behaved as expected during the recent Canterbury and Kaikoura earthquakes in New Zealand, forming plastic hinges in intended locations. While this meant that life-safety performance objectives were met, widespread demolition and heavy economic losses took place in the aftermath of the earthquakes.The Christchurch central business district was particularly hard hit, with over 60% of the multistorey reinforced concrete buildings being demolished. A lack of knowledge on the post-earthquake residual capacity of reinforced concrete buildings was a contributing factor to the mass demolition.Many aspects related to the assessment of earthquake-damaged reinforced concrete buildings require further research. This thesis focusses on improving the state of knowledge on the post earthquakeresidual capacity and reparability of moderately damaged plastic hinges, with an emphasis on plastic hinges typical of modern moment frame structures. The repair method focussed on is epoxy injection of cracks and patching of spalled concrete. A targeted test program on seventeen nominally identical large-scale ductile reinforced concrete beams, three of which were repaired by epoxy injection following initial damaging loadings, was conducted to support these objectives. Test variables included the loading protocol, the loading rate, and the level of restraint to axial elongation.The information that can be gleaned from post-earthquake damage surveys is investigated. It is shown that residual crack widths are dependent on residual deformations, and are not necessarily indicative of the maximum rotation demands or the plastic hinge residual capacity. The implications of various other types of damage typical of beam and column plastic hinges are also discussed.Experimental data are used to demonstrate that the strength and deformation capacity of plastic hinges with modern seismic detailing are often unreduced as a result of moderate earthquake induced damage, albeit with certain exceptions. Special attention is given to the effects of prior yielding of the longitudinal reinforcement, accounting for the low-cycle fatigue and strain ageing phenomena. A material-level testing program on the low-cycle fatigue behaviour of grade 300E reinforcing steel was conducted to supplement the data available in the literature.A reduction in stiffness, relative to the initial secant stiffness to yield, occurs due to moderate plastic hinging damage. This reduction in stiffness is shown to be correlated with the ductility demand,and a proposed model gives a conservative lower-bound estimate of the residual stiffness following an arbitrary earthquake-type loading. Repair by epoxy injection is shown to be effective in restoring the majority of stiffness to plastic hinges in beams. Epoxy injection is also shown to have implications for the residual strength and elongation characteristics of repaired plastic hinges.
Asset management in power systems is exercised to improve network reliability to provide confidence and security for customers and asset owners. While there are well-established reliability metrics that are used to measure and manage business-as-usual disruptions, an increasing appreciation of the consequences of low-probability high-impact events means that resilience is increasingly being factored into asset management in order to provide robustness and redundancy to components and wider networks. This is particularly important for electricity systems, given that a range of other infrastructure lifelines depend upon their operation. The 2010-2011 Canterbury Earthquake Sequence provides valuable insights into electricity system criticality and resilience in the face of severe earthquake impacts. While above-ground assets are relatively easy to monitor and repair, underground assets such as cables emplaced across wide areas in the distribution network are difficult to monitor, identify faults on, and repair. This study has characterised in detail the impacts to buried electricity cables in Christchurch resulting from seismically-induced ground deformation caused primarily by liquefaction and lateral spread. Primary modes of failure include cable bending, stretching, insulation damage, joint braking and, being pulled off other equipment such as substation connections. Performance and repair data have been compiled into a detailed geospatial database, which in combination with spatial models of peak ground acceleration, peak ground velocity and ground deformation, will be used to establish rigorous relationships between seismicity and performance. These metrics will be used to inform asset owners of network performance in future earthquakes, further assess component criticality, and provide resilience metrics.
