The lived reality of the 2010-2011 Canterbury earthquakes and its implications for the Waimakariri District, a small but rapidly growing district (third tier of government in New Zealand) north of Christchurch, can illustrate how community well-being, community resilience, and community capitals interrelate in practice generating paradoxical results out of what can otherwise be conceived as a textbook ‘best practice’ case of earthquake recovery. The Waimakariri District Council’s integrated community based recovery framework designed and implemented post-earthquakes in the District was built upon strong political, social, and moral capital elements such as: inter-institutional integration and communication, participation, local knowledge, and social justice. This approach enabled very positive community outputs such as artistic community interventions of the urban environment and communal food forests amongst others. Yet, interests responding to broader economic and political processes (continuous central government interventions, insurance and reinsurance processes, changing socio-cultural patterns) produced a significant loss of community capitals (E.g.: social fragmentation, participation exhaustion, economic leakage, etc.) which simultaneously, despite local Council and community efforts, hindered community well-being in the long term. The story of the Waimakariri District helps understand how resilience governance operates in practice where multi-scalar, non-linear, paradoxical, dynamic, and uncertain outcomes appear to be the norm that underpins the construction of equitable, transformative, and sustainable pathways towards the future.
In this paper we apply Full waveform tomography (FWT) based on the Adjoint-Wavefield (AW) method to iteratively invert a 3-D geophysical velocity model for the Canterbury region (Lee, 2017) from a simple initial model. The seismic wavefields was generated using numerical solution of the 3-D elastodynamic/ visco- elastodynamic equations (EMOD3D was adopted (Graves, 1996)), and through the AW method, gradients of model parameters (compression and shear wave velocity) were computed by implementing the cross-adjoint of forward and backward wavefields. The reversed-in-time displacement residual was utilized as the adjoint source. For inversion, we also account for the near source/ station effects, gradient precondition, smoothening (Gaussian filter in spatial domain) and optimal step length. Simulation-to-observation misfit measurements based on 191 sources at 78 seismic stations in the Canterbury region (Figure 1) were used into our inversion. The inversion process includes multiple frequency bands, starting from 0-0.05Hz, and advancing to higher frequency bands (0-0.1Hz and 0-0.2Hz). Each frequency band was used for up to 10 iterations or no optimal step length found. After 3 FWT inversion runs, the simulated seismograms computed using our final model show a good matching with the observed seismograms at frequencies from 0 - 0.2 Hz and the normalized least-squared misfit error has been significantly reduced. Over all, the synthetic study of FWT shows a good application to improve the crustal velocity models from the existed geological models and the seismic data of the different earthquake events happened in the Canterbury region.
This dissertation addresses a diverse range of topics in the physics-based broadband ground motion simulation, with a focus on New Zealand applications. In particular the following topics are addressed: the methodology and computational implementation of a New Zealand Velocity Model for broadband ground motion simulation; generalised parametric functions and spatial correlations for seismic velocities in the Canterbury, New Zealand region from surface-wave-based site characterisation; and ground motion simulations of Hope Fault earthquakes. The paragraphs below outline each contribution in more detail. A necessary component in physics-based ground motion simulation is a 3D model which details the seismic velocities in the region of interest. Here a velocity model construction methodology, its computational implementation, and application in the construction of a New Zealand velocity model for use in physics-based broadband ground motion simulation are presented. The methodology utilises multiple datasets spanning different length scales, which is enabled via the use of modular sub-regions, geologic surfaces, and parametric representations of crustal velocity. A number of efficiency-related workflows to decrease the overall computational construction time are employed, while maintaining the flexibility and extensibility to incorporate additional datasets and re- fined velocity parameterizations as they become available. The model comprises explicit representations of the Canterbury, Wellington, Nelson-Tasman, Kaikoura, Marlborough, Waiau, Hanmer and Cheviot sedimentary basins embedded within a regional travel-time tomography-based velocity model for the shallow crust and provides the means to conduct ground motion simulations throughout New Zealand for the first time. Recently developed deep shear-wave velocity profiles in Canterbury enabled models that better characterise the velocity structure within geologic layers of the Canterbury sedimentary basin to be developed. Here the development of depth- and Vs30-dependent para-metric velocity and spatial correlation models to characterise shear-wave velocities within the geologic layers of the Canterbury sedimentary basin are presented. The models utilise data from 22 shear-wave velocity profiles of up to 2.5km depth (derived from surface wave analysis) juxtaposed with models which detail the three-dimensional structure of the geologic formations in the Canterbury sedimentary basin. Parametric velocity equations are presented for Fine Grained Sediments, Gravels, and Tertiary layer groupings. Spatial correlations were developed and applied to generate three-dimensional stochastic velocity perturbations. Collectively, these models enable seismic velocities to be realistically represented for applications such as 3D ground motion and site response simulations. Lastly the New Zealand velocity model is applied to simulate ground motions for a Mw7.51 rupture of the Hope Fault using a physics-based simulation methodology and a 3D crustal velocity model of New Zealand. The simulation methodology was validated for use in the region through comparison with observations for a suite of historic small magnitude earthquakes located proximal to the Hope Fault. Simulations are compared with conventionally utilised empirical ground motion models, with simulated peak ground velocities being notably higher in regions with modelled sedimentary basins. A sensitivity analysis was undertaken where the source characteristics of magnitude, stress parameter, hypocentre location and kinematic slip distribution were varied and an analysis of their effect on ground motion intensities is presented. It was found that the magnitude and stress parameter strongly influenced long and short period ground motion amplitudes, respectively. Ground motion intensities for the Hope Fault scenario are compared with the 2016 Kaikoura Mw7.8 earthquake, it was found that the Kaikoura earthquake produced stronger motions along the eastern South Island, while the Hope Fault scenario resulted in stronger motions immediately West of the near-fault region. The simulated ground motions for this scenario complement prior empirically-based estimates and are informative for mitigation and emergency planning purposes.
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.
