The Canterbury Earthquake Sequence (CES), induced extensive damage in residential buildings and led to over NZ$40 billion in total economic losses. Due to the unique insurance setting in New Zealand, up to 80% of the financial losses were insured. Over the CES, the Earthquake Commission (EQC) received more than 412,000 insurance claims for residential buildings. The 4 September 2010 earthquake is the event for which most of the claims have been lodged with more than 138,000 residential claims for this event only. This research project uses EQC claim database to develop a seismic loss prediction model for residential buildings in Christchurch. It uses machine learning to create a procedure capable of highlighting critical features that affected the most buildings loss. A future study of those features enables the generation of insights that can be used by various stakeholders, for example, to better understand the influence of a structural system on the building loss or to select appropriate risk mitigation measures. Previous to the training of the machine learning model, the claim dataset was supplemented with additional data sourced from private and open access databases giving complementary information related to the building characteristics, seismic demand, liquefaction occurrence and soil conditions. This poster presents results of a machine learning model trained on a merged dataset using residential claims from the 4 September 2010.
The aim of this thesis was to examine the spatial and the temporal patterns of anxiety and chest pain resulting from the Canterbury, New Zealand earthquaeks. Three research objectives were identified: examine any spatial or termporal clusters of anxiety and chest pain; examine the associations between anxiety, chest pain and damage to neighbourhood; and determine any statistically significant difference in counts of anxiety and chest pain after each earthquake or aftershock which resulted in severe damage. Measures of the extent of liquefaction the location of CERA red-zones were used as proxy measures for earthquake damage. Cases of those who presented to Christchurch Public Hospital Emergency Department with either anxiety or chest pain between May 2010 and April 2012 were aggregated to census area unit (CAU) level for analysis. This thesis has taken a unique approach to examining the spatial and spatio-temporal variations of anxiety and chest pain after an earthquake and offers unique results. This is the first study of its kind to use a GIS approach when examining Canterbury specific earthquake damage and health variables at a CAU level after the earthquakes. Through the use of spatio-termporal scan modelling, negative and linear regression modelling and temporal linear modelling with dummy variables this research was able to conclude there are significant spatial and temporal variations in anxiety and chest pain resulting from the earthquakes. The spatio-termporal scan modelling identified a hot cluster of both anxiety and chest pain within Christchurch at the same time the earthquakes occurred. The negative binomial model found liquefaction to be a stronger predictor of anxiety than the Canterbury Earthquake Recovery Authority's (CERA) land zones. The linear regression model foun chest pain to be positively associated with all measures of earthquake damage with the exception of being in the red-zone. The temporal modelling identified a significant increase in anxiety cases one month after a major earthquake, and chest pain cases spiked two weeks after an earthquake and gradually decreased over the following five weeks. This research was limited by lack of control period data, limited measures of earthquake damage, ethical restrictions, and the need for population tracking data. The findings of this research will be useful in the planning and allocation of mental wellbeing resources should another similar event like the Canterbury Earthquakes occur in New Zealand.
Tsunami events including the 2004 Indian Ocean Tsunami and the 2011 Tohoku Earthquake and Tsunami confirmed the need for Pacific-wide comprehensive risk mitigation and effective tsunami evacuation planning. New Zealand is highly exposed to tsunamis and continues to invest in tsunami risk awareness, readiness and response across the emergency management and science sectors. Evacuation is a vital risk reduction strategy for preventing tsunami casualties. Understanding how people respond to warnings and natural cues is an important element to improving evacuation modelling techniques. The relative rarity of tsunami events locally in Canterbury and also globally, means there is limited knowledge on tsunami evacuation behaviour, and tsunami evacuation planning has been largely informed by hurricane evacuations. This research aims to address this gap by analysing evacuation behaviour and movements of Kaikōura and Southshore/New Brighton (coastal suburb of Christchurch) residents following the 2016 Kaikōura earthquake. Stage 1 of the research is engaging with both these communities and relevant hazard management agencies, using a survey and community workshops to understand real-event evacuation behaviour during the 2016 Kaikōura earthquake and subsequent tsunami evacuations. The second stage is using the findings from stage 1 to inform an agent-based tsunami evacuation model, which is an approach that simulates of the movement of people during an evacuation response. This method improves on other evacuation modelling approaches to estimate evacuation times due to better representation of local population characteristics. The information provided by the communities will inform rules and interactions such as traffic congestion, evacuation delay times and routes taken to develop realistic tsunami evacuation models. This will allow emergency managers to more effectively prepare communities for future tsunami events, and will highlight recommended actions to increase the safety and efficiency of future tsunami evacuations.
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.
Surface-rupturing earthquakes can trigger the sudden avulsion of river channels, causing rapid and persistent coseismic flooding of previously unaffected areas. This phenomenon, known as fault-rupture-induced river avulsion (FIRA), occurs when fault displacement significantly alters river channel topography. The importance of understanding FIRA as a secondary seismic hazard was highlighted by events during the 2010 Darfield and 2016 Kaikoura earthquakes in New Zealand. This thesis develops a national model to identify and quantify FIRA susceptibility across New Zealand by integrating hydrological datasets (NIWA RiverMaps and Flood Statistics) with active fault information (NZ Active Faults Database and RSQSim earthquake simulations). The methodology applies the F-index framework proposed by McEwan et al. (2023), which quantifies FIRA potential based on the ratio of fault throw plus discharge-dependent depth to bank full depth at each fault-river intersection. The model successfully identified 3,796 potential FIRA-susceptible fault-river intersections nationwide, with 451 involving waterways equal to or larger than the Hororata River. Regional analysis revealed higher concentrations of FIRA-susceptible sites in the Bay of Plenty, Canterbury, and Marlborough regions. Validation against historical events showed the model effectively located known FIRA occurrences from the Kaikoura and Darfield earthquakes, though with some limitations in accurately predicting F-index values due to complex fault displacement patterns and challenges in modelling bank full depths of large, braided rivers. This research establishes New Zealand's first nationwide assessment of fault-induced river avulsion susceptibility. The approach creates a structured methodology for identifying high-risk fault-river intersections and determining which sites require thorough localised examination. The methodology developed offers a template for similar assessments in other tectonically active regions and contributes to improving earthquake hazard assessment and disaster preparedness planning.
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.
1. Background and Objectives This poster presents results from ground motion simulations of small-to-moderate magnitude (3.5≤Mw≤5.0) earthquake events in the Canterbury, New Zealand region using the Graves and Pitarka (2010,2015) methodology. Subsequent investigation of systematic ground motion effects highlights the prediction bias in the simulations which are also benchmarked against empirical ground motion models (e.g. Bradley (2013)). In this study, 144 earthquake ruptures, modelled as point sources, are considered with 1924 quality-assured ground motions recorded across 45 strong motion stations throughout the Canterbury region, as shown in Figure 1. The majority of sources are Mw≥4.0 and have centroid depth (CD) 10km or shallower. Earthquake source descriptions were obtained from the GeoNet New Zealand earthquake catalogue. The ground motion simulations were performed within a computational domain of 140km x 120km x 46km with a finite difference grid spacing of 0.1km. The low-frequency (LF) simulations utilize the 3D Canterbury Velocity Model while the high-frequency (HF) simulations utilize a generic regional 1D velocity model. In the LF simulations, a minimum shear wave velocity of 500m/s is enforced, yielding a maximum frequency of 1.0Hz.
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.
The overarching goal of this dissertation is to improve predictive capabilities of geotechnical seismic site response analyses by incorporating additional salient physical phenomena that influence site effects. Specifically, multidimensional wave-propagation effects that are neglected in conventional 1D site response analyses are incorporated by: (1) combining results of 3D regional-scale simulations with 1D nonlinear wave-propagation site response analysis, and (2) modelling soil heterogeneity in 2D site response analyses using spatially-correlated random fields to perturb soil properties. A method to combine results from 3D hybrid physics-based ground motion simulations with site-specific nonlinear site response analyses was developed. The 3D simulations capture 3D ground motion phenomena on a regional scale, while the 1D nonlinear site response, which is informed by detailed site-specific soil characterization data, can capture site effects more rigorously. Simulations of 11 moderate-to-large earthquakes from the 2010-2011 Canterbury Earthquake Sequence (CES) at 20 strong motion stations (SMS) were used to validate simulations with observed ground motions. The predictions were compared to those from an empirically-based ground motion model (GMM), and from 3D simulations with simplified VS30- based site effects modelling. By comparing all predictions to observations at seismic recording stations, it was found that the 3D physics-based simulations can predict ground motions with comparable bias and uncertainty as the GMM, albeit, with significantly lower bias at long periods. Additionally, the explicit modelling of nonlinear site-response improves predictions significantly compared to the simplified VS30-based approach for soft-soil or atypical sites that exhibit exceptionally strong site effects. A method to account for the spatial variability of soils and wave scattering in 2D site response analyses was developed and validated against a database of vertical array sites in California. The inputs required to run the 2D analyses are nominally the same as those required for 1D analyses (except for spatial correlation parameters), enabling easier adoption in practice. The first step was to create the platform and workflow, and to perform a sensitivity study involving 5,400 2D model realizations to investigate the influence of random field input parameters on wave scattering and site response. Boundary conditions were carefully assessed to understand their effect on the modelled response and select appropriate assumptions for use on a 2D model with lateral heterogeneities. Multiple ground-motion intensity measures (IMs) were analyzed to quantify the influence from random field input parameters and boundary conditions. It was found that this method is capable of scattering seismic waves and creating spatially-varying ground motions at the ground surface. The redistribution of ground-motion energy across wider frequency bands, and the scattering attenuation of high-frequency waves in 2D analyses, resemble features observed in empirical transfer functions (ETFs) computed in other studies. The developed 2D method was subsequently extended to more complicated multi-layer soil profiles and applied to a database of 21 vertical array sites in California to test its appropriate- ness for future predictions. Again, different boundary condition and input motion assumptions were explored to extend the method to the in-situ conditions of a vertical array (with a sensor embedded in the soil). ETFs were compared to theoretical transfer functions (TTFs) from conventional 1D analyses and 2D analyses with heterogeneity. Residuals of transfer-function- based IMs, and IMs of surface ground motions, were also used as validation metrics. The spatial variability of transfer-function-based IMs was estimated from 2D models and compared to the event-to-event variability from ETFs. This method was found capable of significantly improving predictions of median ETF amplification factors, especially for sites that display higher event-to-event variability. For sites that are well represented by 1D methods, the 2D approach can underpredict amplification factors at higher modes, suggesting that the level of heterogeneity may be over-represented by the 2D random field models used in this study.
This document reviews research-based understandings of the concept of resilience. A conceptual model is developed which identifies a number of the factors that influence individual and household resilience. Guided by the model, a series of recommendations are developed for practices that will support individual and household resilience in Canterbury in the aftermath of the 2010-2011 earthquakes.
Earthquakes cause significant damage to buildings due to strong vibration of the ground. Levitating houses using magnets and electromagnets would provide a complete isolation of ground motion for protecting buildings from seismic damage. Two types of initial configuration for the electromagnet system were proposed with the same air gap (10mm) between the electromagnet and reluctance plate. Both active and passive controller are modelled to investigate the feasibility of using a vibration control system for stabilizing the magnetic system within the designed air gap (10mm) in the vertical direction. A nonlinear model for the magnetic system is derived to implement numerical simulation of structural response under the earthquake record in Christchurch Botanic Gardens on 21 February 2011. The performance of the uncontrolled and the controlled systems are compared and the optimal combination of control gains are determined for the PID active controller. Simulation results show both active PID controller with constant and nonlinear attracting force are able to provide an effective displacement control within the required air gap (+/-5mm). The maximum control force demand for the PID controller in the presence of nonlinear attracting force is 4.1kN, while the attracting force in equilibrium position is 10kN provided by the electromagnet. These results show the feasibility of levitating a house using the current electromagnet and PID controller. Finally, initial results of passive control using two permanent magnets or dampers show the structural responses can be effectively reduced and centralized to +/-1mm using a nonlinear centring barrier function.
This paper presents a seismic velocity model of Canterbury, New Zealand based on 3D geologic surfaces and velocities from a range of data sources. The model provides the 3D crustal structure in the region at multiple length scales for seismic wave propagation simulations, such as broadband ground motion and shallow site response analyses related to understanding the ground motions and site responses during the 2010- 2011 Canterbury earthquakes. Pre-Quaternary geologic horizons are calculated based on the reinterpretation of a comprehensive network of seismic reflection surveys from seven different campaigns over the past 50 years, as well as point constraints across an array of petroleum industry drill holes. Particular attention is given to a detailed representation of Quaternary stratigraphy, representing shallow (z<250m) near-surface layers in the model. Seismic velocities are obtained from seismic reflection processing (for Vp) and also recently performed active and passive surface wave analyses (for Vs). Over 1,700 water wells in the region are used to constrain the complex inter-bedded Quaternary stratigraphy (gravels, sands, silts, organics etc.) near the coastline, including beneath urban Christchurch, which has resulted from fluvial deposition and marine regression and transgression. For the near-surface Springston and Christchurch Formations in the Christchurch urban area (z<50m), high-spatial resolution seismic velocities (including Vs30 ) were obtained from over 13,000 cone penetration tests combined with a recently developed CPT-Vs correlation.
This presentation summarizes the development of high-resolution surficial soil velocity models in the Canterbury, New Zealand basin. Shallow (<30m) shear wave velocities were primarily computed based on a combination of a large database of over 15,000 cone penetration test (CPT) logs in and around Christchurch, and a recently-developed Christchurch-specific empirical correlation between soil shear wave velocity and CPT. Large active-source testing at 22 locations and ambient-wavefield surface wave and H/V testing at over 80 locations were utilized in combination with 1700 water well logs to constrain the inter-bedded stratigraphy and velocity of Quaternary sediments up to depths of several hundred meters. Finally, seismic reflection profiles and the ambient-wavefield surface wave data provide constraint on velocities from several hundred meters to several kilometres. At all depths, the high resolution data illustrates the complexity of the soil conditions in the region, and the developed 3D models are presently being used in broadband ground motion simulations to further interpret the observed strong ground motions in the 2010-2011 Canterbury earthquake sequence.
Our poster will present on-going QuakeCoRE-founded work on strong motion seismology for Dunedin-Mosgiel area, focusing on ground motion simulations for Dunedin Central Business District (CBD). Source modelling and ground motion simulations are being carried out using the SCEC (Southern California Earthquakes Center) Broad Band simulation Platform (BBP). The platform computes broadband (0-10 Hz) seismograms for earthquakes and was first implemented at the University of Otago in 2016. As large earthquakes has not been experienced in Dunedin in the time of period of instrumental recording, user-specified scenario simulations are of great value. The Akatore Fault, the most active fault in Otago and closest major fault to Dunedin, is the source focused on in the present study. Simulations for various Akatore Fault source scenarios are run and presented. Path and site effects are key components considered in the simulation process. A 1D shear wave velocity profile is required by SCEC BBP, and this is being generated to represent the Akatore-to-CBD path and site within the BBP. A 3D shear velocity model, with high resolution within Dunedin CBD, is being developed in parallel with this study (see Sangster et al. poster). This model will be the basis for developing a 3D shear wave velocity model for greater Dunedin-Mosgiel area for future ground motion simulations, using Canterbury software (currently under development).
The rapid classification of building damage states or placards after an earthquake is vital for enabling an efficient emergency response and informed decision-making for rehabilitation and recovery purposes. Traditional methods rely heavily on inspector-led on-site surveys, which are often time-consuming, resource-intensive, and susceptible to human error. This study introduces a machine learning-supported surrogate model designed to streamline the assessment of building damage, focusing on the automated assignment of damage placards within the context of New Zealand's post-earthquake evaluation frameworks. The study evaluates two key safety evaluation protocols—Rapid Building Assessment (RBA) and Detailed Damage Evaluation (DDE)—and integrates corresponding databases derived from the 2010–2011 Canterbury Earthquake Sequence (CES) in Christchurch. Six ML classifiers—Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gradient Boosting Classifier (GBC), and Gradient Bagging (GBag)—were rigorously tested across both databases. The results indicate that the RF-based surrogate model outperforms the other classifiers across both RBA and DDE protocols. Two distinct sets of critical predictors have been further identified for each protocol, allowing for the rapid retrieval of essential data for future on-site surveys, while retaining the RF model's predictive accuracy. The developed surrogate model provides a pragmatic tool for practising engineers to rapidly assign placards to damaged structures and for policymakers and building owners to make informed recovery decisions for earthquake-affected buildings
Seismic behaviour of typical unreinforced masonry (URM) brick houses, that were common in early last century in New Zealand and still common in many developing countries, is experimentally investigated at University of Canterbury, New Zealand in this research. A one halfscale model URM house is constructed and tested under earthquake ground motions on a shaking table. The model structure with aspect ratio of 1.5:1 in plan was initially tested in the longitudinal direction for several earthquakes with peak ground acceleration (PGA) up to 0.5g. Toppling of end gables (above the eaves line) and minor to moderate cracking around window and door piers was observed in this phase. The structure was then rotated 90º and tested in the transverse (short) direction for ground motions with PGA up to 0.8g. Partial out-of-plane failure of the face loaded walls in the second storey and global rocking of the model was observed in this phase. A finite element analysis and a mechanism analysis are conducted to assess the dynamic properties and lateral strength of the model house. Seismic fragility function of URM houses is developed based on the experimental results. Damping at different phases of the response is estimated using an amplitude dependent equivalent viscous damping model. Financial risk of similar URM houses is then estimated in term of expected annual loss (EAL) following a probabilistic financial risk assessment framework. Risks posed by different levels of damage and by earthquakes of different frequencies are then examined.
<jats:p>Social and natural capital are fundamental to people’s wellbeing, often within the context of local community. Developing communities and linking people together provide benefits in terms of mental well-being, physical activity and other associated health outcomes. The research presented here was carried out in Christchurch - Ōtautahi, New Zealand, a city currently re-building, after a series of devastating earthquakes in 2010 and 2011. Poor mental health has been shown to be a significant post-earthquake problem, and social connection has been postulated as part of a solution. By curating a disparate set of community services, activities and facilities, organised into a Geographic Information Systems (GIS) database, we created i) an accessibility analysis of 11 health and well-being services, ii) a mobility scenario analysis focusing on 4 general well-being services and iii) a location-allocation model focusing on 3 primary health care and welfare location optimisation. Our results demonstrate that overall, the majority of neighbourhoods in Christchurch benefit from a high level of accessibility to almost all the services; but with an urban-rural gradient (the further away from the centre, the less services are available, as is expected). The noticeable exception to this trend, is that the more deprived eastern suburbs have poorer accessibility, suggesting social inequity in accessibility. The findings presented here show the potential of optimisation modelling and database curation for urban and community facility planning purposes.</jats:p>
This thesis describes research into developing a client/server ar- chitecture for a mobile Augmented Reality (AR) application. Following the earthquakes that have rocked Christchurch the city is now changed forever. CityViewAR is an existing mobile AR application designed to show how the city used to look before the earthquakes. In CityViewAR 3D virtual building models are overlaid onto video captured by a smartphone camera. However the current version of CityViewAR only allows users to browse information stored on the mobile device. In this research the author extends the CityViewAR application to a client-server model so that anyone can upload models and annotations to a server and have this information viewable on any smartphone running the application. In this thesis we describe related work on AR browser architectures, the system we developed, a user evaluation of the prototype system and directions for future work.
Many buildings with relatively low damage from the 2010-2011 Canterbury were deemed uneconomic to repair and were replaced [1,2]. Factors that affected commercial building owners’ decisions to replace rather than repair, included capital availability, uncertainty with regards to regional recovery, local market conditions and ability to generate cash flow, and repair delays due to limited property access (cordon). This poster provides a framework for modeling decision-making in a case where repair is feasible but replacement might offer greater economic value – a situation not currently modeled in engineering risk analysis.
In this paper, the characteristics of near-fault ground motions recorded during the Mw7.1 Darfield and Mw 6.2 Christchurch earthquakes are examined and compared with existing empirical models. The characteristics of forward-directivity effects are first examined using a wavelet-based pulse-classification algorithm. This is followed by an assessment of the adequacy of empirical models which aim to capture the effect of directivity effects on amplifying the acceleration response spectra; and the period and peak velocity of the forward-directivity pulse. It is illustrated that broadband directivity models developed by Somerville et al. (1997) and Abrahamson (2000) generally under-predict the observed amplification of response spectral ordinates at longer vibration periods. In contrast, a recently developed narrowband model by Shahi and Baker (2011) provides significantly improved predictions by amplifying the response spectra within a small range of periods surrounding the directivity pulse period. Although the empirical predictions of the pulse period are generally favourable for the Christchurch earthquake, the observations from the Darfield earthquake are significantly under-predicted. The elongation in observed pulse periods is inferred as being a result of the soft sedimentary soils of the Canterbury basin. However, empirical predictions of the observed peak velocity associated with the directivity pulse are generally adequate for both events.
This study explicitly investigates uncertainties in physics-based ground motion simulation validation for earthquakes in the Canterbury region. The simulations utilise the Graves and Pitarka (2015) hybrid methodology, with separately quantified parametric uncertainties in the comprehensive physics and simplified physics components of the model. The study is limited to the simulation of 148 small magnitude (Mw 3.5 – 5) earthquakes, with a point source approximation for the source rupture representations, which also enables a focus on a small number of relevant uncertainties. The parametric uncertainties under consideration were selected through sensitivity analysis, and specifically include: magnitude, Brune stress parameter and high frequency rupture velocity. Twenty Monte Carlo realisations were used to sample parameter uncertainties for each of the 148 events. Residuals associated with the following intensity measures: spectral acceleration, peak ground velocity, arias intensity and significant duration, were ascertained. Using these residuals, validation was performed through assessment of systematic biases in site and source terms from mixed-effects regression. Based on the results to date, initial standard deviation recommendations for parameter uncertainties, based on the Canterbury simulations have been obtained. This work ultimately provides an initial step toward explicit incorporation of modelling uncertainty in simulated ground motion predictions for future events, which will improve the use of simulation models in seismic hazard analysis. We plan to subsequently assess uncertainties for larger magnitude events with more complex ruptures, and events across a larger geographic region, as well as uncertainties due to path attenuation, site effects, and more general model epistemic uncertainties.
The 2010-2011 Canterbury earthquakes were recorded over a dense strong motion network in the near-source region, yielding significant observational evidence of seismic complexities, and a basis for interpretation of multi-disciplinary datasets and induced damage to the natural and built environment. This paper provides an overview of observed strong motions from these events and retrospective comparisons with both empirical and physics-based ground motion models. Both empirical and physics-based methods provide good predictions of observations at short vibration periods in an average sense. However, observed ground motion amplitudes at specific locations, such as Heathcote Valley, are seen to systematically depart from ‘average’ empirical predictions as a result of near surface stratigraphic and topographic features which are well modelled via sitespecific response analyses. Significant insight into the long period bias in empirical predictions is obtained from the use of hybrid broadband ground motion simulation. The comparison of both empirical and physics-based simulations against a set of 10 events in the sequence clearly illustrates the potential for simulations to improve ground motion and site response prediction, both at present, and further in the future.
The increase of the world's population located near areas prone to natural disasters has given rise to new ‘mega risks’; the rebuild after disasters will test the governments’ capabilities to provide appropriate responses to protect the people and businesses. During the aftermath of the Christchurch earthquakes (2010-2012) that destroyed much of the inner city, the government of New Zealand set up a new partnership between the public and private sector to rebuild the city’s infrastructure. The new alliance, called SCIRT, used traditional risk management methods in the many construction projects. And, in hindsight, this was seen as one of the causes for some of the unanticipated problems. This study investigated the risk management practices in the post-disaster recovery to produce a specific risk management model that can be used effectively during future post-disaster situations. The aim was to develop a risk management guideline for more integrated risk management and fill the gap that arises when the traditional risk management framework is used in post-disaster situations. The study used the SCIRT alliance as a case study. The findings of the study are based on time and financial data from 100 rebuild projects, and from surveying and interviewing risk management professionals connected to the infrastructure recovery programme. The study focussed on post-disaster risk management in construction as a whole. It took into consideration the changes that happened to the people, the work and the environment due to the disaster. System thinking, and system dynamics techniques have been used due to the complexity of the recovery and to minimise the effect of unforeseen consequences. Based on an extensive literature review, the following methods were used to produce the model. The analytical hierarchical process and the relative importance index have been used to identify the critical risks inside the recovery project. System theory methods and quantitative graph theory have been used to investigate the dynamics of risks between the different management levels. Qualitative comparative analysis has been used to explore the critical success factors. And finally, causal loop diagrams combined with the grounded theory approach has been used to develop the model itself. The study identified that inexperienced staff, low management competency, poor communication, scope uncertainty, and non-alignment of the timing of strategic decisions with schedule demands, were the key risk factors in recovery projects. Among the critical risk groups, it was found that at a strategic management level, financial risks attracted the highest level of interest, as the client needs to secure funding. At both alliance-management and alliance-execution levels, the safety and environmental risks were given top priority due to a combination of high levels of emotional, reputational and media stresses. Risks arising from a lack of resources combined with the high volume of work and the concern that the cost could go out of control, alongside the aforementioned funding issues encouraged the client to create the recovery alliance model with large reputable construction organisations to lock in the recovery cost, at a time when the scope was still uncertain. This study found that building trust between all parties, clearer communication and a constant interactive flow of information, established a more working environment. Competent and clear allocation of risk management responsibilities, cultural shift, risk prioritisation, and staff training were crucial factors. Finally, the post-disaster risk management (PDRM) model can be described as an integrated risk management model that considers how the changes which happened to the environment, the people and their work, caused them to think differently to ease the complexity of the recovery projects. The model should be used as a guideline for recovery systems, especially after an earthquake, looking in detail at all the attributes and the concepts, which influence the risk management for more effective PDRM. The PDRM model is represented in Causal Loops Diagrams (CLD) in Figure 8.31 and based on 10 principles (Figure 8.32) and 26 concepts (Table 8.1) with its attributes.
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.
Probabilistic Structural Fire Engineering (PSFE) has been introduced to overcome the limitations of current conventional approaches used for the design of fire-exposed structures. Current structural fire design investigates worst-case fire scenarios and include multiple thermal and structural analyses. PSFE permits buildings to be designed to a level of life safety or economic loss that may occur in future fire events with the help of a probabilistic approach. This thesis presents modifications to the adoption of a Performance-Based Earthquake Engineering (PBEE) framework in Probabilistic Structural Fire Engineering (PSFE). The probabilistic approach runs through a series of interrelationships between different variables, and successive convolution integrals of these interrelationships result in probabilities of different measures. The process starts with the definition of a fire severity measure (FSM), which best relates fire hazard intensity with structural response. It is identified by satisfying efficiency and sufficiency criteria as described by the PBEE framework. The relationship between a fire hazard and corresponding structural response is established by analysis methods. One method that has been used to quantify this relationship in PSFE is Incremental Fire Analysis (IFA). The existing IFA approach produces unrealistic fire scenarios, as fire profiles may be scaled to wide ranges of fire severity levels, which may not physically represent any real fires. Two new techniques are introduced in this thesis to limit extensive scaling. In order to obtain an annual rate of exceedance of fire hazard and structural response for an office building, an occurrence model and an attenuation model for office fires are generated for both Christchurch city and New Zealand. The results show that Christchurch city is 15% less likely to experience fires that have the potential to cause structural failures in comparison to all of New Zealand. In establishing better predictive relationships between fires and structural response, cumulative incident radiation (a fire hazard property) is found to be the most appropriate fire severity measure. This research brings together existing research on various sources of uncertainty in probabilistic structural fire engineering, such as elements affecting post-flashover fire development factors (fuel load, ventilation, surface lining and compartment geometry), fire models, analysis methods and structural reliability. Epistemic uncertainty and aleatory uncertainty are investigated in the thesis by examining the uncertainty associated with modelling and the factors that influence post-flashover development of fires. A survey of 12 buildings in Christchurch in combination with recent surveys in New Zealand produced new statistical data on post-flashover development factors in office buildings in New Zealand. The effects of these parameters on temperature-time profiles are evaluated. The effects of epistemic uncertainty due to fire models in the estimation of structural response is also calculated. Parametric fires are found to have large uncertainty in the prediction of post-flashover fires, while the BFD curves have large uncertainties in prediction of structural response. These uncertainties need to be incorporated into failure probability calculations. Uncertainty in structural modelling shows that the choices that are made during modelling have a large influence on realistic predictions of structural response.
This study explored the experiences of 10 leaders in their intentional six-month implementation, during the 2010-2011Christchurch earthquakes, of an adapted positive leadership model. The study concluded that the combination of strategies in the model provided psychological and participative safety for leaders to learn and to apply new ways of working. Contrary to other studies on natural disaster, workplace performance increased and absenteeism decreased. The research contributes new knowledge to the positive leadership literature and new understanding, from the perspective of leaders, of the challenges of leading in a workplace environment of ongoing natural disaster events.
This research is a creative exploration of transmedia’s ability to offer up a model of distribution and audience engagement for political documentary. Transmedia, as is well known, is a fluid concept. It is not restricted to the activities of the entertainment industry and its principles also reverberate in the practice of political and activist documentary projects. This practice-led research draws on data derived from the production and circulation of Obrero, an independent transmedia documentary. The project explores the conditions and context of the Filipino rebuild workers who migrated to Christchurch, New Zealand after the earthquake in 2011. Obrero began as a film festival documentary that co-exists with two other new media iterations, each reaching its respective target audience: a web documentary, and a Facebook-native documentary. This study argues that relocating the documentary across new media spaces not only expands the narrative but also extends the fieldwork and investigation, forms like-minded publics, and affords the creation of an organised hub of information for researchers, academics and the general public. Treating documentary as research can represent a novel pathway to knowledge generation and the present case study, overall, provides an innovative model for future scholarship
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.
The article asks whether disasters that destroy life but leave the material infrastructure relatively intact tend to prompt communal coping focussing on loss, while disasters that destroy significant material infrastructure tend to prompt coping through restoration / re-building. After comparing memorials to New Zealand’s Christchurch earthquake and Pike River mine disasters, we outline circumstances in which collective restorative endeavour may be grassroots, organised from above, or manipulated, along with limits to effective restoration. We conclude that bereavement literature may need to take restoration more seriously, while disaster literature may need to take loss more seriously.
