Big Data & Difficult Data: The UC CEISMIC Canterbury Earthquakes Digital A…
Research papers, University of Canterbury Library
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Research on human behaviour during earthquake shaking has identified three main influences of behaviour: the environment the individual is located immediately before and during the earthquake, in terms of where the individual is and who the individual is with at the time of the earthquake; individual characteristics, such as age, gender, previous earthquake experience, and the intensity and duration of earthquake shaking. However, little research to date has systematically analysed the immediate observable human responses to earthquake shaking, mostly due to data constraints and/or ethical considerations. Research on human behaviour during earthquakes has relied on simulations or post-event, reflective interviews and questionnaire studies, often performed weeks to months or even years following the event. Such studies are therefore subject to limitations such as the quality of the participant's memory or (perceived) realism of a simulation. The aim of this research was to develop a robust coding scheme to analyse human behaviour during earthquake shaking using video footage captured during an earthquake event. This will allow systematic analysis of individuals during real earthquakes using a previously unutilized data source, thus help develop guidance on appropriate protective actions. The coding scheme was developed in a two-part process, combining a deductive and inductive approach. Previous research studies of human behavioral response during earthquake shaking provided the basis for the coding scheme. This was then iteratively refined by applying the coding scheme to a broad range of video footage of people exposed to strong shaking during the Canterbury earthquake sequence. The aim of this was to optimise coding scheme content and application across a broad range of scenarios, and to increase inter-coder reliability. The methodology to code data will enhance objective observation of video footage to allow cross-event analysis and explore (among others): reaction time, patterns of behaviour, and social, environmental and situational influences of behaviour. This can provide guidance for building configuration and design, and evidence-based recommendations for public education about injury-preventing behavioural responses during earthquake shaking.
The UC CEISMIC Canterbury Earthquakes Digital Archive was built following the devastating earthquakes that hit the Canterbury region in the South Island of New Zealand from 2010 – 2012. 185 people were killed in the 6.3 magnitude earthquake of February 22nd 2011, thousands of homes and businesses were destroyed, and the local community endured over 10,000 aftershocks. The program aims to document and protect the social, cultural, and intellectual legacy of the Canterbury community for the purposes of memorialization and enabling research. The nationally federated archive currently stores 75,000 items, ranging from audio and video interviews to images and official reports. Tens of thousands more items await ingestion. Significant lessons have been learned about data integration in post-disaster contexts, including but not limited to technical architecture, governance, ingestion process, and human ethics. The archive represents a model for future resilience-oriented data integration and preservation products.
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.
Decision making on the reinstatement of the Christchurch sewer system after the Canterbury (New Zealand) earthquake sequence in 2010–2011 relied strongly on damage data, in particular closed circuit television (CCTV). This paper documents that process and considers how data can influence decision making. Data are analyzed on 33,000 pipes and 13,000 repairs and renewals. The primary findings are that (1) there should be a threshold of damage per pipe set to make efficient use of CCTV; (2) for those who are estimating potential damage, care must be taken in direct use of repair data without an understanding of the actual damage modes; and (3) a strong correlation was found between the ratio of faults to repairs per pipe and the estimated peak ground velocity. Taken together, the results provide evidence of the extra benefit that damage data can provide over repair data for wastewater networks and may help guide others in the development of appropriate strategies for data collection and wastewater pipe decisions after disasters.
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.
Smart cities utilise new and innovative technology to improve the function of the city for governments, citizens and businesses. This thesis offers an in-depth discussion on the concept of the smart city and sets the context of smart cities internationally. It also examines how to improve a smart city through public engagement, as well as, how to implement participatory research in a smart city project to improve the level of engagement of citizens in the planning and implementation of smart projects. This thesis shows how to incentivise behaviour change with smart city technology and projects, through increasing participation in the planning and implementation of smart technology in a city. Meaningful data is created through this process of participation for citizens in the city, by engaging the citizens in the creation of the data, therefore the information created through a smart city project is created by and for the citizens themselves. To improve engagement, a city must understand its specific context and its residents. Using Christchurch, New Zealand, and the Christchurch City Council (CCC) Smart City Project as a case study, this research engages CCC stakeholders in the Smart City Project through a series of interviews, and citizens in Christchurch through a survey and focus groups. A thorough literature review has been conducted, to illuminate the different definitions of the smart city in academia, business and governments respectively, and how these definitions vary from one another. It provides details of a carefully selected set of relevant smart cities internationally and will discuss how the Christchurch Earthquake Sequence of 2010 and 2011 has affected the CCC Smart City Project. The research process, alongside the literature review, shows diverse groups of citizens in the city should be acknowledged in this process. The concept of the smart city is redefined to incorporate the context of Christchurch, its citizens and communities. Community perceptions of smart cities in Christchurch consider the post-disaster environment and this event and subsequent rebuild process should be a focus of the smart city project. The research identified that the CCC needs to focus on participatory approaches in the planning and implementation of smart projects, and community organisations in Christchurch offer an opportunity to understand community perspectives on new smart technology and that projects internationally should consider how the context of the city will affect the participation of its residents. This project offers ideas to influence the behaviour change of citizens through a smart city project. Further research should consider other stakeholders, for instance, innovation and technology-focused business in the city, and to fully engage citizens, future research must continue the process of participatory engagement, and target diverse groups in the city, including but not limited to minority groups, older and younger generations, and those with physical and mental disabilities.
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.
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.
INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather events. However, research on this subject is lacking in New Zealand, which is difficult to analyse as an overall nation due to its many micro-climates and regional differences.OBJECTIVES: The aim of this study and subsequent analysis is to explore the associations between environmental factors and poor mental health outcomes in New Zealand by region and predict the number of people with mental health-related illnesses corresponding to the environmental influence.METHODS: Data are collected from various public-available sources, e.g., Stats NZ and Coronial services of New Zealand, which comprised four environmental factors of our interest and two mental health indicators data ranging from 2016 up until 2020. The four environmental factors are air pollution, earthquakes, rainfall and temperature. Two mental health indicators include the number of people seen by District Health Boards (DHBs) for mental health reasons and the statistics on suicide deaths. The initial analysis is carried out on which regions were most affected by the chosen environmental factors. Further analysis using Auto-Regressive Integrated Moving Average(ARIMA) creates a model based on time series of environmental data to generate estimation for the next two years and mental health projected from the ridge regression.RESULTS: In our initial analysis, the environmental data was graphed along with mental health outcomes in regional charts to identify possible associations. Different regions of New Zealand demonstrate quite different relationships between the environmental data and mental health outcomes. The result of later analysis predicts that the suicide rate and DHB mental health visits may increase in Wellington, drop-in Hawke's Bay and slightly increase in Canterbury for the year 2021 and 2022 with different environmental factors considered.CONCLUSION: It is evident that the relationship between environmental and mental health factors is regional and not national due to the many micro-climates that exist around the nation. However, it was observed that not all factors displayed a good relationship between the regions. We conclude that our hypotheses were partially correct, in that increased air pollution was found to correlate to increased mental health-related DHB visits. Rainfall was also highly correlated to some mental health outcomes. Higher levels of rainfall reduced DHB visits and suicide rates in some areas of the country.
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.
The abundance of cone penetration test (CPT) data from subsurface explorations in Christchurch and the surrounding areas provides a useful source of information for a characterization of the near surface shear wave velocity ( ) profile for the region. A portion of the investigations were conducted using seismic CPT, enabling the comparison of measured shear wave velocity with CPT data, and subsequently the evaluation of existing CPT- correlations for applicability to Canterbury-specific soils. The existing correlations are shown to be biased, generally over-predicting the observed with depth, thus demonstrating the need for a Canterbury-specific CPT- correlation.
The Canterbury Earthquake Sequence (CES) of 2010-2011 produced large seismic moments up to Mw 7.1. These large, near-to-surface (<15 km) ruptures triggered >6,000 rockfall boulders on the Port Hills of Christchurch, many of which impacted houses and affected the livelihoods of people within the impacted area. From these disastrous and unpredicted natural events a need arose to be able to assess the areas affected by rockfall events in the future, where it is known that a rockfall is possible from a specific source outcrop but the potential boulder runout and dynamics are not understood. The distribution of rockfall deposits is largely constrained by the physical properties and processes of the boulder and its motion such as block density, shape and size, block velocity, bounce height, impact and rebound angle, as well as the properties of the substrate. Numerical rockfall models go some way to accounting for all the complex factors in an algorithm, commonly parameterised in a user interface where site-specific effects can be calibrated. Calibration of these algorithms requires thorough field checks and often experimental practises. The purpose of this project, which began immediately following the most destructive rupture of the CES (February 22, 2011), is to collate data to characterise boulder falls, and to use this information, supplemented by a set of anthropogenic boulder fall data, to perform an in-depth calibration of the three-dimensional numerical rockfall model RAMMS::Rockfall. The thesis covers the following topics: • Use of field data to calibrate RAMMS. Boulder impact trails in the loess-colluvium soils at Rapaki Bay have been used to estimate ranges of boulder velocities and bounce heights. RAMMS results replicate field data closely; it is concluded that the model is appropriate for analysing the earthquake-triggered boulder trails at Rapaki Bay, and that it can be usefully applied to rockfall trajectory and hazard assessment at this and similar sites elsewhere. • Detailed analysis of dynamic rockfall processes, interpreted from recorded boulder rolling experiments, and compared to RAMMS simulated results at the same site. Recorded rotational and translational velocities of a particular boulder show that the boulder behaves logically and dynamically on impact with different substrate types. Simulations show that seasonal changes in soil moisture alter rockfall dynamics and runout predictions within RAMMS, and adjustments are made to the calibration to reflect this; suggesting that in hazard analysis a rockfall model should be calibrated to dry rather than wet soil conditions to anticipate the most serious outcome. • Verifying the model calibration for a separate site on the Port Hills. The results of the RAMMS simulations show the effectiveness of calibration against a real data set, as well as the effectiveness of vegetation as a rockfall barrier/retardant. The results of simulations are compared using hazard maps, where the maximum runouts match well the mapped CES fallen boulder maximum runouts. The results of the simulations in terms of frequency distribution of deposit locations on the slope are also compared with those of the CES data, using the shadow angle tool to apportion slope zones. These results also replicate real field data well. Results show that a maximum runout envelope can be mapped, as well as frequency distribution of deposited boulders for hazard (and thus risk) analysis purposes. The accuracy of the rockfall runout envelope and frequency distribution can be improved by comprehensive vegetation and substrate mapping. The topics above define the scope of the project, limiting the focus to rockfall processes on the Port Hills, and implications for model calibration for the wider scientific community. The results provide a useful rockfall analysis methodology with a defensible and replicable calibration process, that has the potential to be applied to other lithologies and substrates. Its applications include a method of analysis for the selection and positioning of rockfall countermeasure design; site safety assessment for scaling and demolition works; and risk analysis and land planning for future construction in Christchurch.
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
Liquefaction-induced lateral spreading during the 2011 Christchurch earthquake in New Zealand was severe and extensive, and data regarding the displacements associated with the lateral spreading provides an excellent opportunity to better understand the factors that influence these movements. Horizontal displacements measured from optical satellite imagery and subsurface data from the New Zealand Geotechnical Database (NZGD) were used to investigate four distinct lateral spread areas along the Avon River in Christchurch. These areas experienced displacements between 0.5 and 2 m, with the inland extent of displacement ranging from 100 m to over 600 m. Existing empirical and semi-empirical displacement models tend to under estimate displacements at some sites and over estimate at others. The integrated datasets indicate that the areas with more severe and spatially extensive displacements are associated with thicker and more laterally continuous deposits of liquefiable soil. In some areas, the inland extent of displacements is constrained by geologic boundaries and geomorphic features, as expressed by distinct topographic breaks. In other areas the extent of displacement is influenced by the continuity of liquefiable strata or by the presence of layers that may act as vertical seepage barriers. These observations demonstrate the need to integrate geologic/geomorphic analyses with geotechnical analyses when assessing the potential for lateral spreading movements.
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 development of Digital City technologies to manage and visualise spatial information has increasingly become a focus of the research community, and application by city authorities. Traditionally, the Geographic Information Systems (GIS) and Building Information Models (BIM) underlying Digital Cities have been used independently. However, integrating GIS and BIM into a single platform provides benefits for project and asset management, and is applicable to a range of issues. One of these benefits is the means to access and analyse large datasets describing the built environment, in order to characterise urban risk from and resilience to natural hazards. The aim of this thesis is to further explore methodologies of integration in two distinct areas. The first, integration through connectivity of heterogeneous datasets where GIS spatial infrastructure data is merged with 3D BIM building data to create a digital twin. Secondly, integration through analysis whereby data from the digital twin are extracted and integrated with computational models. To achieve this, a workflow was developed to identify the required datasets of a digital twin, and develop a process of integrating those datasets through a combination of; semi-autonomous conversion, translation and extension of data; and semantic web and services-based processes. Through use of a designed schema, the data were streamed in a homogenous format in a web-based platform. To demonstrate the value of this workflow with respect to urban risk and resilience, the process was applied to the Taiora: Queen Elizabeth II recreation and sports centre in eastern Christchurch, New Zealand. After integration of as-built GIS and BIM datasets, targeted data extraction was implemented, with outputs tailored for analysis in an infrastructure serviceability loss model, which assessed potable water network performance in the 22nd February 2011 Christchurch Earthquake. Using the same earthquake conditions as the serviceability loss model, performance of infrastructure assets in service at the time of the 22nd February 2011 Christchurch Earthquake was compared to new assets rebuilt at the site, post-earthquake. Due to improved potable water infrastructure resilience resulting from installation of ductile piles, a decrease of 35.5% in the probability of service loss was estimated in the serviceability loss model. To complete the workflow, the results from the external analysis were uploaded to the web-based platform. One of the more significant outcomes from the workflow was the identification of a lack of mandated metadata standards for fittings/valves connecting a building to private laterals. Whilst visually the GIS and BIM data show the building and pipes as connected, the semantic data does not include this connectivity relationship. This has no material impact on the current serviceability loss model as it is not one of the defined parameters. However, a proposed modification to the model would utilise the metadata to further assess the physical connection robustness, and increase the number of variables for estimating probability of service loss. This thesis has made a methodological contribution to urban resilience analysis by demonstrating how readily available up-to-date building and infrastructure data can be integrated, and with tailored extraction from a Digital City platform, be used for disaster impact analysis in an external computational engine, with results in turn imported and visualised in the Digital City platform. The workflow demonstrated that translation and integration of data would be more successful if a regional/national mandate was implemented for the submission of consent documentation in a specified standard BIM format. The results of this thesis have identified that the key to ensuring the success of an integrated tool lies in the initial workflow required to safeguard that all data can be either captured or translated in an interoperable format.
The development of Digital City technologies to manage and visualise spatial information has increasingly become a focus of the research community, and application by city authorities. Traditionally, the Geographic Information Systems (GIS) and Building Information Models (BIM) underlying Digital Cities have been used independently. However, integrating GIS and BIM into a single platform provides benefits for project and asset management, and is applicable to a range of issues. One of these benefits is the means to access and analyse large datasets describing the built environment, in order to characterise urban risk from and resilience to natural hazards. The aim of this thesis is to further explore methodologies of integration in two distinct areas. The first, integration through connectivity of heterogeneous datasets where GIS spatial infrastructure data is merged with 3D BIM building data to create a digital twin. Secondly, integration through analysis whereby data from the digital twin are extracted and integrated with computational models. To achieve this, a workflow was developed to identify the required datasets of a digital twin, and develop a process of integrating those datasets through a combination of; semi-autonomous conversion, translation and extension of data; and semantic web and services-based processes. Through use of a designed schema, the data were streamed in a homogenous format in a web-based platform. To demonstrate the value of this workflow with respect to urban risk and resilience, the process was applied to the Taiora: Queen Elizabeth II recreation and sports centre in eastern Christchurch, New Zealand. After integration of as-built GIS and BIM datasets, targeted data extraction was implemented, with outputs tailored for analysis in an infrastructure serviceability loss model, which assessed potable water network performance in the 22nd February 2011 Christchurch Earthquake. Using the same earthquake conditions as the serviceability loss model, performance of infrastructure assets in service at the time of the 22nd February 2011 Christchurch Earthquake was compared to new assets rebuilt at the site, post-earthquake. Due to improved potable water infrastructure resilience resulting from installation of ductile piles, a decrease of 35.5% in the probability of service loss was estimated in the serviceability loss model. To complete the workflow, the results from the external analysis were uploaded to the web-based platform. One of the more significant outcomes from the workflow was the identification of a lack of mandated metadata standards for fittings/valves connecting a building to private laterals. Whilst visually the GIS and BIM data show the building and pipes as connected, the semantic data does not include this connectivity relationship. This has no material impact on the current serviceability loss model as it is not one of the defined parameters. However, a proposed modification to the model would utilise the metadata to further assess the physical connection robustness, and increase the number of variables for estimating probability of service loss. This thesis has made a methodological contribution to urban resilience analysis by demonstrating how readily available up-to-date building and infrastructure data can be integrated, and with tailored extraction from a Digital City platform, be used for disaster impact analysis in an external computational engine, with results in turn imported and visualised in the Digital City platform. The workflow demonstrated that translation and integration of data would be more successful if a regional/national mandate was implemented for the submission of consent documentation in a specified standard BIM format. The results of this thesis have identified that the key to ensuring the success of an integrated tool lies in the initial workflow required to safeguard that all data can be either captured or translated in an interoperable format.
We present the initial findings from a study of adaptive resilience of lifelines organisations providing essential infrastructure services, in Christchurch, New Zealand following the earthquakes of 2010-2011. Qualitative empirical data was collected from 200 individuals in 11 organisations. Analysis using a grounded theory method identified four major factors that aid organisational response, recovery and renewal following major disruptive events. Our data suggest that quality of top and middle-level leadership, quality of external linkages, level of internal collaboration, ability to learn from experience, and staff well-being and engagement influence adaptive resilience. Our data also suggest that adaptive resilience is a process or capacity, not an outcome and that it is contextual. Post-disaster capacity/resources and post-disaster environment influence the nature of adaptive resilience.
The objective of this project is to collect perishable seismic response data from the baseisolated Christchurch Women's Hospital. The strong and continuing sequence of aftershocks presents a unique opportunity to capture high-fidelity data from a modern base-isolated facility. These measurements will provide quantitative information required to assess the mechanisms at play in this and in many other seismically-isolated structures.
Live monitoring data and simple dynamic reduced-order models of the Christchurch Women’s Hospital (CWH) help explain the performance of the base isolation (BI) system of the hospital during the series of Canterbury earthquakes in 2011-2012. A Park-Wen-Ang hysteresis model is employed to simulate the performance of the BI system and results are compared to measured data recorded above the isolation layer and on the 6th story. Simplified single, two and three degree of freedom models (SDOF, 2DOF and 3DOF) show that the CWH structure did not behave as an isolated but as a fixed-base structure. Comparisons of accelerations and deflections between simulated and monitored data show a good match for isolation stiffness values of approximately two times of the value documented in the design specification and test protocol. Furthermore, an analysis of purely measured data revealed very little to no relative motion across the isolators for large events of moment magnitude scale (Mw) 5.8 and 6.0 that occurred within 3 hours of each other on December 23, 2011. One of the major findings is that the BI system during the seismic events on December 23, 2011 did not yield and that the superstructure performed as a fixed-base building, indicating a need to reevaluate the analysis, design and implementation of these structures.
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Recent tsunami events have highlighted the importance of effective tsunami risk management strategies (including land-use planning, structural and natural mitigation, warning systems, education and evacuation planning). However, the rarity of tsunami means that empirical data concerning reactions to tsunami warnings and evacuation behaviour is rare when compared to findings for evacuations from other hazards. More knowledge is required to document the full evacuation process, including responses to warnings, pre-evacuation actions, evacuation dynamics, and the return home. Tsunami evacuation modelling has the potential to inform evidence-based tsunami risk planning and response. However, to date, tsunami evacuation models have largely focused on the timings of evacuations, rather than behaviours of those evacuating. In this research, survey data was gathered from coastal communities in Banks Peninsula and Christchurch, New Zealand, relating to behaviours and actions during the November 14th 2016 Kaikōura earthquake tsunami. Survey questions asked about immediate actions following the earthquake shaking, reactions to tsunami warnings, pre-evacuation actions, evacuation dynamics and details on congestion. This data was analysed to characterise trends and identify factors that influenced evacuation actions and behaviour, and was further used to develop a realistic evacuation model prototype to evaluate the capacity of the roading network in Banks Peninsula during a tsunami evacuation. The evacuation model incorporated tsunami risk management strategies that have been implemented by local authorities, and exposure and vulnerability data, alongside the empirical data collected from the survey. This research enhances knowledge of tsunami evacuation behaviour and reactions to tsunami warnings, and can be used to refine evacuation planning to ensure that people can evacuate efficiently, thereby reducing their tsunami exposure and personal risk.
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.
This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
This research employs a deterministic seismic risk assessment methodology to assess the potential damage and loss at meshblock level in the Christchurch CBD and Mount Pleasant primarily due to building damage caused by earthquake ground shaking. Expected losses in terms of dollar value and casualties are calculated for two earthquake scenarios. Findings are based on: (1) data describing the earthquake ground shaking and microzonation effects; (2) an inventory of buildings by value, floor area, replacement value, occupancy and age; (3) damage ratios defining the performance of buildings as a function of earthquake intensity; (4) daytime and night-time population distribution data and (5) casualty functions defining casualty risk as a function of building damage. A GIS serves as a platform for collecting, storing and analyzing the original and the derived data. It also allows for easy display of input and output data, providing a critical functionality for communication of outcomes. The results of this study suggest that economic losses due to building damage in the Christchurch CBD and Mount Pleasant will possibly be in the order of $5.6 and $35.3 million in a magnitude 8.0 Alpine fault earthquake and a magnitude 7.0 Ashley fault earthquake respectively. Damage to non-residential buildings constitutes the vast majority of the economic loss. Casualty numbers are expected to be between 0 and 10.
The Porters Pass fault (PPF) is a prominent element of the Porters Pass-Amberley Fault Zone (PPAFZ) which forms a broad zone of active earth deformation ca 100 km long, 60-90 km west and north of Christchurch. For a distance of ca 40 km the PPF is defined by a series of discontinuous Holocene active traces between the Rakaia and Waimakariri Rivers. The amount of slip/event and the timing of paleoearthquakes are crucial components needed to estimate the earthquake potential of a fault. Movement was assumed to be, coseismic and was quantified by measuring displaced geomorphic features using either tape measure or surveying equipment. Clustering of offset data suggests that four to five earthquakes occurred on the PPF during the Holocene and these range between ca 5-7 m/event. Timing information was obtained from four trenches excavated across the fault and an auger adjacent to the fault. Organic samples from these sites were radiocarbon dated and used in conjunction with data from previous studies to identify the occurrence of at least four earthquakes at 8500 ± 200, 5300 ± 700, 2500 ± 200 and 1000 ± 100 years B.P. Evidence suggests that an additional event is also possible at 6200 ± 500 years B.P. The ~1000, 5300 and 6200 years B.P. paleoearthquakes were previously unrecognised, while the 500 year event previously inferred from rock-avalanche data has been discarded. The present data set produces recurrence intervals of ~2000-2500 years for the Holocene. The identification of only one Holocene PPF rupture to the west of Red Lakes indicates the presence of a segment boundary that prevents the propagation of rupture beyond this point. This is consistent with displacement data and results in slip rates of 0.5-0.7 mm/yr and 2.5-3.4 mm/yr to the west and east of Red Lakes respectively. It is possible that the nearby extensional Red Hill Fault influences PPF rupture propagation. The combination of geometric, slip rate and timing data has enabled the magnitude of prehistoric earthquakes on the PPF to be estimated. These magnitudes range from an average of between 6.9 for a fault rupture from Waimakariri River to Red Lakes, to a maximum of 7.4 that ruptures the entire length of the PPAFZ, including the full length of the PPF. These estimates are approximately consistent with previous magnitude estimates along the full length of the PPAFZ of between 7.0 and 7.5.
Deep shear wave velocity (Vs) profiles (>400 m) were developed at 14 sites throughout Christchurch, New Zealand using surface wave methods. This paper focuses on the inversion of surface wave data collected at one of these sites, Hagley Park. This site is located on the deep soils of the Canterbury Plains, which consist of alluvial gravels inter-bedded with estuarine and marine sands, silts, clays and peats. Consequently, significant velocity contrasts exist at the interface between geologic formations. In order to develop realistic velocity models in this complex geologic environment, a-priori geotechnical and geologic data were used to identify the boundaries between geologic formations. This information aided in developing the layering for the inversion parameters. Moreover, empirical reference Vs profiles based on material type and confining pressure were used to develop realistic Vs ranges for each layer. Both the a-priori layering information and the reference Vs curves proved to be instrumental in generating realistic velocity models that account for the complex inter-bedded geology in the Canterbury Plains.
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.