The 14 November 2016 Kaikōura earthquake had major impacts on New Zealand's transport system. Road, rail and port infrastructure was damaged, creating substantial disruption for transport operators, residents, tourists, and business owners in the Canterbury, Marlborough and Wellington regions, with knock-on consequences elsewhere. During both the response and recovery phases, a large amount of information and data relating to the transport system was generated, managed, analysed, and exchanged within and between organisations to assist decision making. To improve information and data exchanges and related decision making in the transport sector during future events and guide new resilience strategies, we present key findings from a recent post-earthquake assessment. The research involved 35 different stakeholder groups and was conducted for the Ministry of Transport. We consider what transport information was available, its usefulness, where it was sourced from, mechanisms for data transfer between organisations, and suggested approaches for continued monitoring.
Numerous rockfalls released during the 2010–2011 Canterbury earthquake sequence affected vital road sections for local commuters. We quantified rockfall fatality risk on two main routes by adapting a risk approach for roads originally developed for snow avalanche risk. We present results of the collective and individual fatality risks for traffic flow and waiting traffic. Waiting traffic scenarios particularly address the critical spatial-temporal dynamics of risk, which should be acknowledged in operational risk management. Comparing our results with other risks commonly experienced in New Zealand indicates that local rockfall risk is close to tolerability thresholds and likely exceeds acceptable risk.
Natural catastrophes are increasing worldwide. They are becoming more frequent but also more severe and impactful on our built environment leading to extensive damage and losses. Earthquake events account for the smallest part of natural events; nevertheless seismic damage led to the most fatalities and significant losses over the period 1981-2016 (Munich Re). Damage prediction is helpful for emergency management and the development of earthquake risk mitigation projects. Recent design efforts focused on the application of performance-based design engineering where damage estimation methodologies use fragility and vulnerability functions. However, the approach does not explicitly specify the essential criteria leading to economic losses. There is thus a need for an improved methodology that finds the critical building elements related to significant losses. The here presented methodology uses data science techniques to identify key building features that contribute to the bulk of losses. It uses empirical data collected on site during earthquake reconnaissance mission to train a machine learning model that can further be used for the estimation of building damage post-earthquake. The first model is developed for Christchurch. Empirical building damage data from the 2010-2011 earthquake events is analysed to find the building features that contributed the most to damage. Once processed, the data is used to train a machine-learning model that can be applied to estimate losses in future earthquake events.
Our poster will present on-going QuakeCoRE-founded work on strong motion seismology for Dunedin-Mosgiel area, focusing on ground motion simulations for Dunedin Central Business District (CBD). Source modelling and ground motion simulations are being carried out using the SCEC (Southern California Earthquakes Center) Broad Band simulation Platform (BBP). The platform computes broadband (0-10 Hz) seismograms for earthquakes and was first implemented at the University of Otago in 2016. As large earthquakes has not been experienced in Dunedin in the time of period of instrumental recording, user-specified scenario simulations are of great value. The Akatore Fault, the most active fault in Otago and closest major fault to Dunedin, is the source focused on in the present study. Simulations for various Akatore Fault source scenarios are run and presented. Path and site effects are key components considered in the simulation process. A 1D shear wave velocity profile is required by SCEC BBP, and this is being generated to represent the Akatore-to-CBD path and site within the BBP. A 3D shear velocity model, with high resolution within Dunedin CBD, is being developed in parallel with this study (see Sangster et al. poster). This model will be the basis for developing a 3D shear wave velocity model for greater Dunedin-Mosgiel area for future ground motion simulations, using Canterbury software (currently under development).
On 14 November 2016, a magnitude (Mw) 7.8 earthquake struck the small coastal settlement of Kaikōura, Aotearoa-New Zealand. With an economy based on tourism, agriculture, and fishing, Kaikōura was immediately faced with significant logistical, economic, and social challenges caused by damage to critical infrastructure and lifelines, essential to its main industries. Massive landslips cut offroad and rail access, stranding hundreds of tourists, and halting the collection, processing and distribution of agricultural products. At the coast, the seabed rose two metres, limiting harbour-access to high tide, with implications for whale watching tours and commercial fisheries. Throughout the region there was significant damage to homes, businesses, and farmland, leaving owners and residents facing an uncertain future. This paper uses qualitative case study analysis to explore post-quake transformations in a rural context. The aim is to gain insight into the distinctive dynamics of disaster response mechanisms, focusing on two initiatives that have emerged in direct response to the disaster. The first examines the ways in which agriculture, food harvesting, production and distribution are being reimagined with the potential to enhance regional food security. The second examines the rescaling of power in decision-making processes following the disaster, specifically examining the ways in which rural actors are leveraging networks to meet their needs and the consequences of that repositioning on rural (and national) governance arrangements. In these and other ways, the local economy is being revitalised, and regional resilience enhanced through diversification, capitalising not on the disaster but the region's natural, social, and cultural capital. Drawing on insights and experience of local stakeholders, policy- and decision-makers, and community representatives we highlight the diverse ways in which these endeavours are an attempt to create something new, revealing also the barriers which needed to be overcome to reshape local livelihoods. Results reveal that the process of transformation as part of rural recovery must be grounded in the lived reality of local residents and their understanding of place, incorporating and building on regional social, environmental, and economic characteristics. In this, the need to respond rapidly to realise opportunities must be balanced with the community-centric approach, with greater recognition given to the contested nature of the decisions to be made. Insights from the case examples can inform preparedness and recovery planning elsewhere, and provide a rich, real-time example of the ways in which disasters can create opportunities for reimagining resilient futures.
