Existing unreinforced masonry (URM) buildings are often composed of traditional construction techniques, with poor connections between walls and diaphragms that results in poor performance when subjected to seismic actions. In these cases the application of the common equivalent static procedure is not applicable because it is not possible to assure “box like” behaviour of the structure. In such conditions the ultimate strength of the structure relies on the behaviour of the macro-elements that compose the deformation mechanisms of the whole structure. These macroelements are a single or combination of structural elements of the structure which are bonded one to each other. The Canterbury earthquake sequence was taken as a reference to estimate the most commonly occurring collapse mechanisms found in New Zealand URM buildings in order to define the most appropriate macroelements.
Motivation This poster aims to present fragility functions for pipelines buried in liquefaction-prone soils. Existing fragility models used to quantify losses can be based on old data or use complex metrics. Addressing these issues, the proposed functions are based on the Christchurch network and soil and utilizes the Canterbury earthquake sequence (CES) data, partially represented in Figure 1. Figure 1 (a) presents the pipe failure dataset, which describes the date, location and pipe on which failures occurred. Figure 1 (b) shows the simulated ground motion intensity median of the 22nd February 2011 earthquake. To develop the model, the network and soil characteristics have also been utilized.
The term resilience‘’is increasingly being used in a multitude of contexts. Seemingly the latest buzz‘’word, it can mean many things to many people, in many different situations. In a natural hazard context, the terms sustainable planning‘’, and resilience‘planning are now’being used, often interchangeably. This poster provides an overview of resilience and sustainability within a land use planning and natural hazard context, and discusses how they are interrelated in the situation of the earthquake impacted city of Christchurch, New Zealand.
he 2016 Building (Earthquake Prone Building) Amendment Act aims to improve the system for managing earthquake-prone buildings. The proposed changes to the Act were precipitated by the Canterbury earthquakes, and the need to improve the seismic safety of New Zealand’s building stock. However, the Act has significant ramifications for territorial authorities, organisations and individuals in small New Zealand towns, since assessing and repairing heritage buildings poses a major cost to districts with low populations and poor rental returns on commercial buildings.
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Introduction In 2011 Christchurch city centre was partially destroyed by an earthquake. Government-led anchor projects were tasked with bringing Christchurch back from rubble. After a period of 7 years out of 16 proposed projects, 10 are already over time for their initial completion dates and the ones completed, are under scrutiny for failing to deliver their expected outcome.
INTRODUCTION This project falls under the Flagship 3: Wellington Coordinated Project. It supports other projects within FP3 to create a holistic understanding of risks posed by collapsed buildings due to future earthquake/s and the secondary consequences of cordoning in the short, mid and long term. Cordoning of the Christchurch CBD for more than two years and its subsequent implications on people and businesses had a significant impact on the recovery of Christchurch. Learning from this and experiences from the Kaikōura earthquake (where cordons were also established around selected buildings, Figure 3) have highlighted the need to understand the effects of cordons and plan for it before an earthquake occurs
To identify key ground characteristics that led to different liquefaction manifestations during the Canterbury earthquakes
We present initial results from a set of three-dimensional (3D) deterministic earthquake ground motion simulations for the northern Canterbury plains, Christchurch and the Banks Peninsula region, which explicitly incorporate the effects of the surface topography. The simu-lations are done using Hercules, an octree-based finite-element parallel software for solving 3D seismic wave propagation problems in heterogeneous media under kinematic faulting. We describe the efforts undertaken to couple Hercules with the South Island Velocity Model (SIVM), which included changes to the SIVM code in order to allow for single repetitive que-ries and thus achieve a seamless finite-element meshing process within the end-to-end ap-proach adopted in Hercules. We present our selection of the region of interest, which corre-sponds to an area of about 120 km × 120 km, with the 3D model reaching a depth of 60 km. Initial simulation parameters are set for relatively high minimum shear wave velocity and a low maximum frequency, which we are progressively scaling up as computing resources permit. While the effects of topography are typically more important at higher frequencies and low seismic velocities, even at this initial stage of our efforts (with a maximum of 2 Hz and a mini-mum of 500 m/s), it is possible to observe the importance of the topography in the response of some key locations within our model. To highlight these effects we compare the results of the 3D topographic model with respect to those of a flat (squashed) 3D model. We draw rele-vant conclusions from the study of topographic effects during earthquakes for this region and describe our plans for future work.
Abstract This study provides a simplified methodology for pre-event data collection to support a faster and more accurate seismic loss estimation. Existing pre-event data collection frameworks are reviewed. Data gathered after the Canterbury earthquake sequences are analysed to evaluate the relative importance of different sources of building damage. Conclusions drawns are used to explore new approaches to conduct pre-event building assessment.
The latest two great earthquake sequences; 2010- 2011 Canterbury Earthquake and 2016 Kaikoura Earthquake, necessitate a better understanding of the New Zealand seismic hazard condition for new building design and detailed assessment of existing buildings. It is important to note, however, that the New Zealand seismic hazard map in NZS 1170.5.2004 is generalised in effort to cover all of New Zealand and limited to a earthquake database prior to 2001. This is “common” that site-specific studies typically provide spectral accelerations different to those shown on the national map (Z values in NZS 1170.5:2004); and sometimes even lower. Moreover, Section 5.2 of Module 1 of the Earthquake Geotechnical Engineering Practice series provide the guidelines to perform site- specific studies.
Following a natural disaster, children are prone to various reactions and maladaptive responses as a result of exposure to a highly stressful and potentially traumatic event. Children’s responses can range from an acute stress response to post-traumatic-stress disorder or may fall somewhere in between. While responses to highly stressful events vary, a common finding is that children will develop sleep problems. This was found following the Christchurch September 2010 and February 2011 earthquakes. The purpose of this study was to investigate the context and phenomenology of the sleep problems of a small number of children experiencing these and the 2016 Kaikoura earthquakes, including possible mechanisms of effect. Participants were four families, including four mothers, one father and four children. The design of this study was unique. Interview data was subjected to a content analysis, extracted themes were organised according to an ecological-transactional framework and then the factors were subject to an analysis, based on the principles of clinical reasoning, in order to identify possible mechanisms of effect. Parents reported 16 different sleep problems across children, as well as other behaviours possibly indicative of post-traumatic stress response. In total, 34 themes and 26 interactions were extracted in relation to factors identified across participants about the children’s sleep and the families’ earthquake experiences. This demonstrated how complex it is to explore the development of sleep problems in the context of disaster. Key factors identified by parents that likely played a key role in the development and perpetuation of sleep problems included earthquake related anxiety, parental mental health and conflict, the child’s emotional and behavioural problems and other negative life events following the earthquakes. The clinical implications of the analysis included being aware that such families, may not have had access to specialized support around their children’s sleep. This was much needed due to the strain such problems place on the family, especially in a post-disaster community such as Christchurch.
Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.
Damage distribution maps from strong earthquakes and recorded data from field experiments have repeatedly shown that the ground surface topography and subsurface stratigraphy play a decisive role in shaping the ground motion characteristics at a site. Published theoretical studies qualitatively agree with observations from past seismic events and experiments; quantitatively, however, they systematically underestimate the absolute level of topographic amplification up to an order of magnitude or more in some cases. We have hypothesized in previous work that this discrepancy stems from idealizations of the geometry, material properties, and incident motion characteristics that most theoretical studies make. In this study, we perform numerical simulations of seismic wave propagation in heterogeneous media with arbitrary ground surface geometry, and compare results with high quality field recordings from a site with strong surface topography. Our goal is to explore whether high-fidelity simulations and realistic numerical models can – contrary to theoretical models – capture quantitatively the frequency and amplitude characteristics of topographic effects. For validation, we use field data from a linear array of nine portable seismometers that we deployed on Mount Pleasant and Heathcote Valley, Christchurch, New Zealand, and we compute empirical standard spectral ratios (SSR) and single-station horizontal-to-vertical spectral ratios (HVSR). The instruments recorded ambient vibrations and remote earthquakes for a period of two months (March-April 2017). We next perform two-dimensional wave propagation simulations using the explicit finite difference code FLAC. We construct our numerical model using a high-resolution (8m) Digital Elevation Map (DEM) available for the site, an estimated subsurface stratigraphy consistent with the geomorphology of the site, and soil properties estimated from in-situ and non-destructive tests. We subject the model to in-plane and out-of-plane incident motions that span a broadband frequency range (0.1-20Hz). Numerical and empirical spectral ratios from our blind prediction are found in very good quantitative agreement for stations on the slope of Mount Pleasant and on the surface of Heathcote Valley, across a wide range of frequencies that reveal the role of topography, soil amplification and basin edge focusing on the distribution of ground surface motion.
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 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.
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.
During the 2011 M7.8 Kaikōura earthquake, ground motions recorded near the epicentre showed a significant spatial variation. The Te Mara farm (WTMC) station, the nearest to the epicentre, recorded 1g and 2.7g of horizontal and vertical peak ground accelerations (PGA), respectively. The nearby Waiu Gorge (WIGC) station recorded a horizontal PGA of 0.8g. Interestingly, however, the Culverden Airlie Farm (CULC) station that was very closely located to WIGC recorded a horizontal PGA of only 0.25g. This poster demonstrates how the local geological condition could have contributed to the spatially variable ground motions observed in the North Canterbury, based on the results of recently conducted geophysical investigations. The surficial geology of this area is dominated by alluvial gravel deposits with traces of silt. A borehole log showed that the thickness of the sediments at WTMC is over 76 metres. Interestingly, the shear wave velocity (Vs) profiles obtained from the three strong motion sites suggest unusually high shear wave velocity of the gravelly sediments. The velocity of sediments and the lack of clear peaks in the horizontal-to-vertical (H/V) spectral ratio at WTMC suggest that the large ground motion observed at this station was likely caused by the proximity of the station to the causative fault itself; the site effect was likely insignificant. Comparisons of H/V spectral ratios and Vs profiles suggest that the sediment thickness is much smaller at WIGC compared with CULC; the high PGA at WIGC was likely influenced by the high-frequency amplification caused by the response of shallow sediments.
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.
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.
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.
A significant portion of economic loss from the Canterbury Earthquake sequence in 2010-2011 was attributed to losses to residential buildings. These accounted for approximately $12B of a total $40B economic losses (Horspool, 2016). While a significant amount of research effort has since been aimed at research in the commercial sector, little has been done to reduce the vulnerability of the residential building stock.
Knowing how to rapidly rebuild disaster-damaged infrastructure, while deciding appropriate recovery strategies and catering for future investment is a matter of core interest to government decision makers, utility providers, and business sectors. The purpose of this research is to explore the effects of decisions and outcomes for physical reconstruction on the overall recovery process of horizontal infrastructure in New Zealand using the Canterbury and Kaikoura earthquakes as cases. A mixed approach including a systematic review, questionnaire survey and semi-structured interviews is used to capture perspectives of those involved in reconstruction process and gain insights into the effect of critical elements on infrastructure downtime. Findings from this research will contribute towards advancements of a systems dynamics model considering critical decision-making variables across phases of the reconstruction process to assess how these variables affect the rebuild process and the corresponding downtime. This project will improve the ability to explore alternative resilience improvement pathways and test the efficacy of alternative means for facilitating a faster and better reconstruction process.
This research investigates the validation of simulated ground motions on complex structural systems. In this study, the seismic responses of two buildings are compared when they are subjected to as-recorded ground motions and simulated ones. The buildings have been designed based on New Zealand codes and physically constructed in Christchurch, New Zealand. The recorded ground motions are selected from 40 stations database of the historical 22 Feb. 2011 Christchurch earthquake. The Graves and Pitarka (2015) methodology is used to generate the simulated ground motions. The geometric mean of maximum inter-story drift and peak floor acceleration are selected as the main seismic responses. Also, the variation of these parameters due to record to record variability are investigated. Moreover, statistical hypothesis testing is used to investigate the similarity of results between observed and simulated ground motions. The results indicate a general agreement between the peak floor acceleration calculated by simulated and recorded ground motions for two buildings. While according to the hypothesis tests result, the difference in drift can be significant for the building with a shorter period. The results will help engineers and researchers to use or revise the procedure by using simulated ground motions for obtaining seismic responses.
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.
We measure the longer-term effect of a major earthquake on the local economy, using night-time light intensity measured from space, and investigate whether insurance claim payments for damaged residential property affected the local recovery process. We focus on the destructive Canterbury Earthquake Sequence (CES) 2010 -2011 as our case study. Uniquely for this event, more than 95% of residential housing units were covered by insurance, but insurance payments were staggered over 5 years, enabling us to identify their local impact. We find that night-time luminosity can capture the process of recovery and describe the recovery’s determinants. We also find that insurance payments contributed significantly to the process of economic recovery after the earthquake, but delayed payments were less affective and cash settlement of claims were more effective than insurance-managed repairs in contributing to local recovery.
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.
Earthquake-triggered soil liquefaction caused extensive damage and heavy economic losses in Christchurch during the 2010-2011 Canterbury earthquakes. The most severe manifestations of liquefaction were associated with the presence of natural deposits of clean sands and silty sands of fluvial origin. However, liquefaction resistance of fines-containing sands is commonly inferred from empirical relationships based on clean sands (i.e. sands with less than 5% fines). Hence, existing evaluation methods have poor accuracy when applied to silty sands. Also, existing methods do not quantify appropriately the influence on liquefaction resistance of soil fabric and structure, which are unique to a specific depositional environment. This study looks at the influence of fines content, soil fabric (i.e. arrangement of soil particles) and structure (e.g. layering, segregation) on the undrained cyclic behaviour and liquefaction resistance of fines-containing sandy soils from Christchurch using Direct Simple Shear (DSS) tests on soil specimens reconstituted in the laboratory with the water sedimentation technique. The poster describes experimental procedures and presents early test results on two sands retrieved at two different sites in Christchurch.
Background This study examines the performance of site response analysis via nonlinear total-stress 1D wave-propagation 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 3D ground motion phenomena at the regional scale, as well as detailed nonlinear site effects 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), and to empirical ground motion prediction via a ground motion model (GMM).
Introduction This poster presents the inferred initial performance and recovery of the water supply network of Christchurch following the 22 February 2011 Mw 6.2 earthquake. Results are presented in a geospatial and temporal fashion. This work strengthens the current understanding of the restoration of such a system after a disaster and quantifies the losses caused by this earthquake in respect with the Christchurch community. Figure 1 presents the topology of the water supply network as well as the spatial distribution of the buildings and their use.
