The author followed five primary (elementary) schools over three years as they responded to and began to recover from the 2010–2011 earthquakes in and around the city of Christchurch in the Canterbury region of New Zealand. The purpose was to capture the stories for the schools themselves, their communities, and for New Zealand’s historical records. From the wider study, data from the qualitative interviews highlighted themes such as children’s responses or the changing roles of principals and teachers. The theme discussed in this article, however, is the role that schools played in the provision of facilities and services to meet (a) physical needs (food, water, shelter, and safety); and (b) emotional, social, and psychological needs (communication, emotional support, psychological counseling, and social cohesion)—both for themselves and their wider communities. The role schools played is examined across the immediate, short-, medium-, and long-term response periods before being discussed through a social bonding theoretical lens. The article concludes by recommending stronger engagement with schools when considering disaster policy, planning, and preparation http://www.schoolcommunitynetwork.org/SCJ.aspx
Quick and reliable assessment of the condition of bridges in a transportation network after an earthquake can greatly assist immediate post-disaster response and long-term recovery. However, experience shows that available resources, such as qualified inspectors and engineers, will typically be stretched for such tasks. Structural health monitoring (SHM) systems can therefore make a real difference in this context. SHM, however, needs to be deployed in a strategic manner and integrated into the overall disaster response plans and actions to maximize its benefits. This study presents, in its first part, a framework of how this can be achieved. Since it will not be feasible, or indeed necessary, to use SHM on every bridge, it is necessary to prioritize bridges within individual networks for SHM deployment. A methodology for such prioritization based on structural and geotechnical seismic risks affecting bridges and their importance within a network is proposed in the second part. An example using the methodology application to selected bridges in the medium-sized transportation network of Wellington, New Zealand is provided. The third part of the paper is concerned with using monitoring data for quick assessment of bridge condition and damage after an earthquake. Depending on the bridge risk profile, it is envisaged that data will be obtained from either local or national seismic monitoring arrays or SHM systems installed on bridges. A method using artificial neural networks is proposed for using data from a seismic array to infer key ground motion parameters at an arbitrary bridges site. The methodology is applied to seismic data collected in Christchurch, New Zealand. Finally, how such ground motion parameters can be used in bridge damage and condition assessment is outlined. AM - Accepted manuscript
