Special Project 1
Leader: Liam Wotherspoon
Deputy Leader: Roger Fairclough
Industry Representative: Roger Fairclough
This project is a joint research programme with the National Science Challenge 10: Resilience to Nature's Challenges. The program is developing tools to assess the performance of spatially-distributed infrastructure networks subject to extreme natural hazards.
Updated September 2017
The resilience of the NZ built environment to natural hazards has historically focused on the robustness of individual physical assets (individual buildings, bridges etc), with less emphasis on an understanding of the dependencies between individual assets, as well as the performance of spatially-distributed infrastructure networks. The resilience of lifeline networks (electric power, transportation, telecommunications (ICT), potable water, stormwater/wastewater, and liquefied/gas fuels) and other distributed infrastructure (flood control networks) play a critical role in the ability of society to rapidly recover after a major disaster.
The research in this project will be directed toward developing tools to assess the performance of spatially-distributed infrastructure networks subject to extreme natural hazards. This research is funded under the Resilience to Nature's Challenges National Science Challenge (http://resiliencechallenge.nz/) and therefore has a focus on a range of extreme natural hazards along with earthquakes. Working closely with relevant stakeholders we will develop methodologies to quantify system-level performance of nationally critical infrastructure when subject to natural hazards and cascading impacts,
leading to improved resilience of communities through identification of multi-hazard related vulnerabilities in infrastructure critical for NZ society. Critical infrastructure asset owners do not currently have methods to fully quantify resilience of key components and trickle-down impacts of their disruption due to natural hazards. Nor are there consistent methods to measure and monitor infrastructure resilience within or across infrastructure types, organisations, or investment criteria to assess the merits of different options to improve resilience.
System-level resilience methodology outputs will be based on local (or component) level quantification of vulnerabilities, and mechanistic models for the interactions between the components of the network system. Uncertainties in such analyses can be significant, and the developed models and their implementation will utilize the most recent concepts of explicit uncertainty quantification; spatial correlation of uncertainties in demand, capacity and post-disaster response; stochastic event sets for efficiently considering numerous probabilistic scenarios; and low-rank methods for sensitivity analysis.