In 2010 and 2011 Christchurch, New Zealand experienced a series of earthquakes that caused extensive damage across the city, but primarily to the Central Business District (CBD) and eastern suburbs. A major feature of the observed damage was extensive and severe soil liquefaction and associated ground damage, affecting buildings and infrastructure. The behaviour of soil during earthquake loading is a complex phenomena that can be most comprehensively analysed through advanced numerical simulations to aid engineers in the design of important buildings and critical facilities. These numerical simulations are highly dependent on the capabilities of the constitutive soil model to replicate the salient features of sand behaviour during cyclic loading, including liquefaction and cyclic mobility, such as the Stress-Density model. For robust analyses advanced soil models require extensive testing to derive engineering parameters under varying loading conditions for calibration. Prior to this research project little testing on Christchurch sands had been completed, and none from natural samples containing important features such as fabric and structure of the sand that may be influenced by the unique stress-history of the deposit. This research programme is focussed on the characterisation of Christchurch sands, as typically found in the CBD, to facilitate advanced soil modelling in both res earch and engineering practice - to simulate earthquake loading on proposed foundation design solutions including expensive ground improvement treatments. This has involved the use of a new Gel Push (GP) sampler to obtain undisturbed samples from below the ground-water table. Due to the variable nature of fluvial deposition, samples with a wide range of soil gradations, and accordingly soil index properties, were obtained from the sampling sites. The quality of the samples is comprehensively examined using available data from the ground investigation and laboratory testing. A meta-quality assessment was considered whereby a each method of evaluation contributed to the final quality index assigned to the specimen. The sampling sites were characterised with available geotechnical field-based test data, primarily the Cone Penetrometer Test (CPT), supported by borehole sampling and shear-wave velocity testing. This characterisation provides a geo- logical context to the sampling sites and samples obtained for element testing. It also facilitated the evaluation of sample quality. The sampling sites were evaluated for liquefaction hazard using the industry standard empirical procedures, and showed good correlation to observations made following the 22 February 2011 earthquake. However, the empirical method over-predicted liquefaction occurrence during the preceding 4 September 2010 event, and under-predicted for the subsequent 13 June 2011 event. The reasons for these discrepancies are discussed. The response of the GP samples to monotonic and cyclic loading was measured in the laboratory through triaxial testing at the University of Canterbury geomechanics laboratory. The undisturbed samples were compared to reconstituted specimens formed in the lab in an attempt to quantify the effect of fabric and structure in the Christchurch sands. Further testing of moist tamped re- constituted specimens (MT) was conducted to define important state parameters and state-dependent properties including the Critical State Line (CSL), and the stress-strain curve for varying state index. To account for the wide-ranging soil gradations, selected representative specimens were used to define four distinct CSL. The input parameters for the Stress-Density Model (S-D) were derived from a suite of tests performed on each representative soil, and with reference to available GP sample data. The results of testing were scrutinised by comparing the data against expected trends. The influence of fabric and structure of the GP samples was observed to result in similar cyclic strength curves at 5 % Double Amplitude (DA) strain criteria, however on close inspection of the test data, clear differences emerged. The natural samples exhibited higher compressibility during initial loading cycles, but thereafter typically exhibited steady growth of plastic strain and excess pore water pressure towards and beyond the strain criteria and initial liquefaction, and no flow was observed. By contrast the reconstituted specimens exhibited a stiffer response during initial loading cycles, but exponential growth in strains and associated excess pore water pressure beyond phase-transformation, and particularly after initial liquefaction where large strains were mobilised in subsequent cycles. These behavioural differences were not well characterised by the cyclic strength curve at 5 % DA strain level, which showed a similar strength for both GP samples and MT specimens. A preliminary calibration of the S-D model for a range of soil gradations is derived from the suite of laboratory test data. Issues encountered include the influence of natural structure on the peak-strength–state index relationship, resulting in much higher peak strengths than typically observed for sands in the literature. For the S-D model this resulted in excessive stiffness to be modelled during cyclic mobility, when the state index becomes large momentarily, causing strain development to halt. This behaviour prevented modelling the observed re- sponse of silty sands to large strains, synonymous with “liquefaction”. Efforts to reduce this effect within the current formulation are proposed as well as future research to address this issue.
Natural hazard disasters often have large area-wide impacts, which can cause adverse stress-related mental health outcomes in exposed populations. As a result, increased treatment-seeking may be observed, which puts a strain on the limited public health care resources particularly in the aftermath of a disaster. It is therefore important for public health care planners to know whom to target, but also where and when to initiate intervention programs that promote emotional wellbeing and prevent the development of mental disorders after catastrophic events. A large body of literature assesses factors that predict and mitigate disaster-related mental disorders at various time periods, but the spatial component has rarely been investigated in disaster mental health research. This thesis uses spatial and spatio-temporal analysis techniques to examine when and where higher and lower than expected mood and anxiety symptom treatments occurred in the severely affected Christchurch urban area (New Zealand) after the 2010/11 Canterbury earthquakes. High-risk groups are identified and a possible relationship between exposure to the earthquakes and their physical impacts and mood and anxiety symptom treatments is assessed. The main research aim is to test the hypothesis that more severely affected Christchurch residents were more likely to show mood and anxiety symptoms when seeking treatment than less affected ones, in essence, testing for a dose-response relationship. The data consisted of mood and anxiety symptom treatment information from the New Zealand Ministry of Health’s administrative databases and demographic information from the National Health Index (NHI) register, when combined built a unique and rich source for identifying publically funded stress-related treatments for mood and anxiety symptoms in almost the whole population of the study area. The Christchurch urban area within the Christchurch City Council (CCC) boundary was the area of interest in which spatial variations in these treatments were assessed. Spatial and spatio-temporal analyses were done by applying retrospective space-time and spatial variation in temporal trends analysis using SaTScan™ software, and Bayesian hierarchical modelling techniques for disease mapping using WinBUGS software. The thesis identified an overall earthquake-exposure effect on mood and anxiety symptom treatments among Christchurch residents in the context of the earthquakes as they experienced stronger increases in the risk of being treated especially shortly after the catastrophic 2011 Christchurch earthquake compared to the rest of New Zealand. High-risk groups included females, elderly, children and those with a pre-existing mental illness with elderly and children especially at-risk in the context of the earthquakes. Looking at the spatio-temporal distribution of mood and anxiety symptom treatments in the Christchurch urban area, a high rates cluster ranging from the severely affected central city to the southeast was found post-disaster. Analysing residential exposure to various earthquake impacts found that living in closer proximity to more affected areas was identified as a risk factor for mood and anxiety symptom treatments, which largely confirms a dose-response relationship between level of affectedness and mood and anxiety symptom treatments. However, little changes in the spatial distribution of mood and anxiety symptom treatments occurred in the Christchurch urban area over time indicating that these results may have been biased by pre-existing spatial disparities. Additionally, the post-disaster mobility activity from severely affected eastern to the generally less affected western and northern parts of the city seemed to have played an important role as the strongest increases in treatment rates occurred in less affected northern areas of the city, whereas the severely affected eastern areas tended to show the lowest increases. An investigation into the different effects of mobility confirmed that within-city movers and temporary relocatees were generally more likely to receive care or treatment for mood or anxiety symptoms, but moving within the city was identified as a protective factor over time. In contrast, moving out of the city from minor, moderately or severely damaged plain areas of the city, which are generally less affluent than Port Hills areas, was identified as a risk factor in the second year post-disaster. Moreover, residents from less damaged plain areas of the city showed a decrease in the likelihood of receiving care or treatment for mood or anxiety symptoms compared to those from undamaged plain areas over time, which also contradicts a possible dose-response relationship. Finally, the effects of the social and physical environment, as well as community resilience on mood and anxiety symptom treatments among long-term stayers from Christchurch communities indicate an exacerbation of pre-existing mood and anxiety symptom treatment disparities in the city, whereas exposure to ‘felt’ earthquake intensities did not show a statistically significant effect. The findings of this thesis highlight the complex relationship between different levels of exposure to a severe natural disaster and adverse mental health outcomes in a severely affected region. It is one of the few studies that have access to area-wide health and impact information, are able to do a pre-disaster / post-disaster comparison and track their sample population to apply spatial and spatio-temporal analysis techniques for exposure assessment. Thus, this thesis enhances knowledge about the spatio-temporal distribution of adverse mental health outcomes in the context of a severe natural disaster and informs public health care planners, not only about high-risk groups, but also where and when to target health interventions. The results indicate that such programs should broadly target residents living in more affected areas as they are likely to face daily hardship by living in a disrupted environment and may have already been the most vulnerable ones before the disaster. Special attention should be focussed on women, elderly, children and people with pre-existing mental illnesses as they are most likely to receive care or treatment for stress-related mental health symptoms. Moreover, permanent relocatees from affected areas and temporarily relocatees shortly after the disaster may need special attention as they face additional stressors due to the relocation that may lead to the development of adverse mental health outcomes needing treatment.
