This paper analyses the city of Christchurch, New Zealand, which has been through dramatic changes since it was struck by a series of earthquakes of different intensities between 2010 and 2011. The objective is to develop a deeper understanding of resilience by looking at changes in green and grey infrastructures. The study can be helpful to reveal a way of doing comparative analysis using resilience as a theoretical framework. In this way, it might be possible to assess the blueprint of future master plans by considering how important the interplay between green and grey infrastructure is for the resilience capacity of cities.
Critical infrastructure networks are highly relied on by society such that any disruption to service can have major social and economic implications. Furthermore, these networks are becoming increasingly dependent on each other for normal operation such that an outage or asset failure in one system can easily propagate and cascade across others resulting in widespread disruptions in terms of both magnitude and spatial reach. It is the vulnerability of these networks to disruptions and the corresponding complexities in recovery processes which provide direction to this research. This thesis comprises studies contributing to two areas (i) the modelling of national scale in-terdependent infrastructure systems undergoing major disruptions, and (ii) the tracking and quantification of infrastructure network recovery trajectories following major disruptions. Firstly, methods are presented for identifying nationally significant systemic vulnerabilities and incorporating expert knowledge into the quantification of infrastructure interdependency mod-elling and simulation. With application to the interdependent infrastructures networks across New Zealand, the magnitudes and spatial extents of disruption are investigated. Results high-light the importance in considering interdependencies when assessing disruptive risks and vul-nerabilities in disaster planning applications and prioritising investment decisions for enhancing resilience of national networks. Infrastructure dependencies are further studied in the context of recovery from major disruptions through the analysis of curves measuring network functionality over time. Continued studies into the properties of recovery curves across a database of global natural disasters produce statistical models for predicting the trajectory and expected recovery times. Finally, the use of connectivity based metrics for quantifying infrastructure system functionality during recovery are considered with a case study application to the Christchurch Earthquake (February 22, 2011) wastewater network response.
Objectives • To develop a system dynamics model of Christchurch post-quake reconstruction process that captures all the critical dynamics influencing its pathway • To investigate the implications of current rebuild pathway • To build a reconstruction module to be integrated in MERIT (Measuring the Economics of Resilient Infrastructure Tool)
The term resilience‘’is increasingly being used in a multitude of contexts. Seemingly the latest buzz‘’word, it can mean many things to many people, in many different situations. In a natural hazard context, the terms sustainable planning‘’, and resilience‘planning are now’being used, often interchangeably. This poster provides an overview of resilience and sustainability within a land use planning and natural hazard context, and discusses how they are interrelated in the situation of the earthquake impacted city of Christchurch, New Zealand.
he 2016 Building (Earthquake Prone Building) Amendment Act aims to improve the system for managing earthquake-prone buildings. The proposed changes to the Act were precipitated by the Canterbury earthquakes, and the need to improve the seismic safety of New Zealand’s building stock. However, the Act has significant ramifications for territorial authorities, organisations and individuals in small New Zealand towns, since assessing and repairing heritage buildings poses a major cost to districts with low populations and poor rental returns on commercial buildings.
Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.
