On 14 November 2016, the Mw 7.8 Kaikōura earthquake caused widespread damage along the east coast of the South Island, New Zealand. Kaikōura town itself was isolated from the rest of the country by landslides blocking off major roads. While impacts from the Kaikōura earthquake on large, urban population centres have been generally well documented, this thesis aims to fill gaps in academic knowledge regarding small rural towns. This thesis investigates what, where and when critical infrastructure and lifeline service disruption occurred following the 2016 Kaikōura earthquake in a selection of small towns, and how the communities in these areas adapted to disruption. Following a robust review of literature and news media, four small rural towns were selected from North Canterbury (Culverden & Waiau) and Marlborough (Seddon & Ward) in the South Island, New Zealand. Semi-structured interview sessions with a special focus on these towns were held with infrastructure managers, emergency response and recovery officials, and organisation leaders with experience or expertise in the 2016 Kaikōura earthquake. Findings were supplemented with emergency management situation reports to produce hazard maps and infrastructure exposure maps. A more detailed analysis was conducted for Waiau involving interdependence analyses and a level of service timeline for select lifeline services. The earthquake impacted roads by blocking them with landslides, debris and surface rupture. Bridges where shaken off their abutments, breaking infrastructure links such as fibre landlines as they went. Water supplies and other forms of infrastructure relied heavily on the level of service of roads, as rough rural terrain left few alternatives. Adapting to an artificial loss of road service, some Waiau locals created their own detour around a road cordon in order to get home to family and farms. Performance of dwellings was tied to socioeconomic factors as much as proximity to the epicentre. Farmers who lost water access pulled out fences to allow stock to drink from rivers. Socioeconomic differences between farmland and township residents also contributed to resilience variations between the towns assessed in this study. Understanding how small rural towns respond and adapt to disaster allows emergency management officials and policy to be well informed and flexible with planning for multiple size classes of towns.
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.
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.
