Despite the relatively low seismicity, a large earthquake in the Waikato region is expected to have a high impact, when the fourth-largest regional population and economy and the high density critical infrastructure systems in this region are considered. Furthermore, Waikato has a deep soft sedimentary basin, which increases the regional seismic hazard due to trapping and amplification of seismic waves and generation of localized surface waves within the basin. This phenomenon is known as the “Basin Effect”, and has been attributed to the increased damage in several historic earthquakes, including the 2010-2011 Canterbury earthquakes. In order to quantitatively model the basin response and improve the understanding of regional seismic hazard, geophysical methods will be used to develop shear wave velocity profiles across the Waikato basin. Active surface wave methods involve the deployment of linear arrays of geophones to record the surface waves generated by a sledge hammer. Passive surface wave methods involve the deployment of two-dimensional seismometer arrays to record ambient vibrations. At each site, the planned testing includes one active test and two to four passive arrays. The obtained data are processed to develop dispersion curves, which describe surface wave propagation velocity as a function of frequency (or wavelength). Dispersion curves are then inverted using the Geopsy software package to develop a suite of shear wave velocity profiles. Currently, more than ten sites in Waikato are under consideration for this project. This poster presents the preliminary results from the two sites that have been tested. The shear wave velocity profiles from all sites will be used to produce a 3D velocity model for the Waikato basin, a part of QuakeCoRE flagship programme 1.
School travel is a major aspect of a young person’s everyday activity. The relationship between the built environment that youth experience on their way to and from school, influences a number of factors including their development, health and wellbeing. This is especially important in low income areas where the built environment is often poorer, but the need for it to be high quality and accessible is greater. This study focusses on the community of Aranui, a relatively low income suburb in Christchurch, New Zealand. It pays particular attention to Haeata Community Campus, a state school of just under 800 pupils from year one through to year thirteen (ages 5-18). The campus opened in 2017 following the closure of four local schools (three primary and one secondary), as part of the New Zealand Government’s Education Renewal scheme following the Christchurch earthquakes of 2010/11. Dedicated effort toward understanding the local built environment, and subsequent travel patterns has been argued to be insufficiently considered. The key focus of this research was to understand the importance of the local environment in encouraging active school travel. The present study combines geospatial analysis, quantitative survey software Maptionnaire, and statistical models to explore the features of the local environment that influence school travel behaviour. Key findings suggest that distance to school and parental control are the most significant predictors of active transport in the study sample. Almost 75% of students live within two kilometres of the school, yet less than 40% utilise active transport. Parental control may be the key contributing factor to the disproportionate private vehicle use. However, active school travel is acknowledged as a complex process that is the product of many individual, household, and local environment factors. To see increased active transport uptake, the local environment needs to be of greater quality. Meaning that the built environment should be improved to be youth friendly, with greater walkability and safe, accessible cycling infrastructure.
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.
