Disaster recovery involves the restoration, repair and rejuvenation of both hard and soft infrastructure. In this report we present observationsfrom seven case studies of collaborative planning from post-earthquake Canterbury, each of which was selected as a means of better understanding ‘soft infrastructure for hard times’. Though our investigation is located within a disaster recovery context, we argue that the lessons learned are widely applicable. Our seven case studies highlighted that the nature of the planning process or journey is as important as the planning objective or destination. A focus on the journey can promote positive outcomes in and of itself through building enduring relationships, fostering diverse leaders, developing new skills and capabilities, and supporting translation and navigation. Collaborative planning depends as much upon emotional intelligence as it does technical competence, and we argue that having a collaborative attitude is more important than following prescriptive collaborative planning formulae. Being present and allowing plenty of time are also key. Although deliberation is often seen as an improvement on technocratic and expertdominated decision-making models, we suggest that the focus in the academic literature on communicative rationality and discursive democracy has led us to overlook other more active forms of planning that occur in various sites and settings. Instead, we offer an expanded understanding of what planning is, where it happens and who is involved. We also suggest more attention be given to values, particularly in terms of their role as a compass for navigating the terrain of decision-making in the collaborative planning process. We conclude with a revised model of a (collaborative) decision-making cycle that we suggest may be more appropriate when (re)building better homes, towns and cities.
Courage has remained an elusive concept to define despite having been in the English lexicon for hundreds of years. The Canterbury earthquake sequence that began in 2010 provided a unique context in which to undertake research that would contribute to further conceptualisation of courage. This qualitative study was undertaken in Christchurch, New Zealand, with adults over the age of 70 who experienced the Canterbury earthquakes and continued to live in the Canterbury region. The population group was chosen because it is an under researched group in post-disaster environments, and one that offers valuable insights because of members' length and breadth of life experiences, and likely reminiscent and reflective life stage. A constructivist grounded theory approach was utilised, with data collected through semi-structured focus groups and individual key informant interviews. The common adverse experience of the participants initially discussed was the earthquakes, which was followed by exploration of courage in their other lived experiences. Through an inductive process of data analysis, conceptual categories were identified, which when further analysed and integrated, contributed to a definition of courage. The definition was subsequently discussed with social work professionals who had remained working in the Canterbury region after experiencing the earthquakes. From the examples and the actions described within these, a process model was developed to support the application of courage. The model includes five steps: recognising an adverse situation, making a conscious decision to act, accessing sources of motivation, mastering emotion and taking action. Defining and utilising courage can help people to face adversity associated with everyday life and ultimately supports self-actualisation and self-development. Recommendations from the study include teaching about courage within social work education, utilising the process model within supervision, intentionally involving older adults in emergency management planning and developing specific social work tasks in hospital settings following a disaster.
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.
The supply of water following disasters has always been of significant concern to communities. Failure of water systems not only causes difficulties for residents and critical users but may also affect other hard and soft infrastructure and services. The dependency of communities and other infrastructure on the availability of safe and reliable water places even more emphasis on the resilience of water supply systems. This thesis makes two major contributions. First, it proposes a framework for measuring the multifaceted resilience of water systems, focusing on the significance of the characteristics of different communities for the resilience of water supply systems. The proposed framework, known as the CARE framework, consists of eight principal activities: (1) developing a conceptual framework; (2) selecting appropriate indicators; (3) refining the indicators based on data availability; (4) correlation analysis; (5) scaling the indicators; (6) weighting the variables; (7) measuring the indicators; and (8) aggregating the indicators. This framework allows researchers to develop appropriate indicators in each dimension of resilience (i.e., technical, organisational, social, and economic), and enables decision makers to more easily participate in the process and follow the procedure for composite indicator development. Second, it identifies the significant technical, social, organisational and economic factors, and the relevant indicators for measuring these factors. The factors and indicators were gathered through a comprehensive literature review. They were then verified and ranked through a series of interviews with water supply and resilience specialists, social scientists and economists. Vulnerability, redundancy and criticality were identified as the most significant technical factors affecting water supply system robustness, and consequently resilience. These factors were tested for a scenario earthquake of Mw 7.6 in Pukerua Bay in New Zealand. Four social factors and seven indicators were identified in this study. The social factors are individual demands and capacities, individual involvement in the community, violence level in the community, and trust. The indicators are the Giving Index, homicide rate, assault rate, inverse trust in army, inverse trust in police, mean years of school, and perception of crime. These indicators were tested in Chile and New Zealand, which experienced earthquakes in 2010 and 2011 respectively. The social factors were also tested in Vanuatu following TC Pam, which hit the country in March 2015. Interestingly, the organisational dimension contributed the largest number of factors and indicators for measuring water supply resilience to disasters. The study identified six organisational factors and 17 indicators that can affect water supply resilience to disasters. The factors are: disaster precaution; predisaster planning; data availability, data accessibility and information sharing; staff, parts, and equipment availability; pre-disaster maintenance; and governance. The identified factors and their indicators were tested for the case of Christchurch, New Zealand, to understand how organisational capacity affected water supply resilience following the earthquake in February 2011. Governance and availability of critical staff following the earthquake were the strongest organisational factors for the Christchurch City Council, while the lack of early warning systems and emergency response planning were identified as areas that needed to be addressed. Economic capacity and quick access to finance were found to be the main economic factors influencing the resilience of water systems. Quick access to finance is most important in the early stages following a disaster for response and restoration, but its importance declines over time. In contrast, the economic capacity of the disaster struck area and the water sector play a vital role in the subsequent reconstruction phase rather than in the response and restoration period. Indicators for these factors were tested for the case of the February 2011 earthquake in Christchurch, New Zealand. Finally, a new approach to measuring water supply resilience is proposed. This approach measures the resilience of the water supply system based on actual water demand following an earthquake. The demand-based method calculates resilience based on the difference between water demand and system capacity by measuring actual water shortage (i.e., the difference between water availability and demand) following an earthquake.
