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Articles, UC QuakeStudies

The Canterbury earthquakes destroyed the Christchurch CBD and caused massive disruption to business across the region. There was an urgent need to support business survival and foster economic recovery. Recover Canterbury is a hub providing seamless support for businesses affected by the earthquakes, giving them easy access to government and commercial expertise in a one-stop shop.

Videos, UC QuakeStudies

A video of a tractor on a farm near River Road in Lincoln. The tractor is pulling a power harrow over a liquefaction blister. This was one of several soil-remediation techniques tested on farms affected by the 4 September 2010 earthquake.

Videos, UC QuakeStudies

A video of a tractor on a farm near River Road in Lincoln. The tractor is pulling a power harrow over a liquefaction blister. This was one of several soil-remediation techniques tested on farms affected by the 4 September 2010 earthquake.

Videos, UC QuakeStudies

A video of a tractor on a farm near River Road in Lincoln. The tractor is making several passes over a liquefaction blister with a rotary hoe. This was one of several soil-remediation techniques tested on farms affected by the 4 September 2010 earthquake.

Videos, UC QuakeStudies

A video of a tractor on a farm near River Road in Lincoln. The tractor is making a second pass over a liquefaction blister with a power harrow. This was one of several soil-remediation techniques tested on farms affected by the 4 September 2010 earthquake.

Videos, UC QuakeStudies

A video of a tractor on a farm near River Road in Lincoln. The tractor is making a several passes over a sand volcano with a rotary hoe. This was one of several soil-remediation techniques tested on farms affected by the 4 September 2010 earthquake.

Videos, UC QuakeStudies

A video of a tractor on a farm near River Road in Lincoln. The tractor is passing over a large sand volcano with a power harrow. This was one of several soil-remediation techniques tested on farms affected by the 4 September 2010 earthquake.

Research papers, The University of Auckland Library

The sequence of earthquakes that has affected Christchurch and Canterbury since September 2010 has caused damage to a great number of buildings of all construction types. Following post-event damage surveys performed between April 2011 and June 2011, the damage suffered by unreinforced stone masonry buildings is reported and different types of observed failures are described. A detailed technical description of the most prevalently observed failure mechanisms is provided, with reference to recognised failure modes for unreinforced masonry structures. The observed performance of existing seismic retrofit interventions is also provided, as an understanding of the seismic response of these interventions is of fundamental importance for assessing the vulnerability of similar strengthening techniques when applied to unreinforced stone masonry structures.

Images, UC QuakeStudies

A photograph of a temporary sign set up at the entrance to Cowles Stadium by Civil Defence. The stadium was set up as temporary accommodation for citizens displaced by the 4 September 2010 earthquake. The sign reads, "Welcome to Cowles Stadium. Earthquake affected people only - you must register with Red Cross to receive help. Other help go to Winz Office, 154 Aldwins Road, Linwood. Please, no alcohol, no drugs on site. Food and drinks only in designated areas".

Research papers, University of Canterbury Library

The level of destruction from the 2011 Christchurch earthquakes led to changes in the New Zealand seismic building code. The destruction showed that the NZ building codes did not fully performed to expectation and needed Improvement to ensure that impact of future earthquakes would be minimised. The building codes have been amended to improve buildings resilience to earthquake and other related extreme loading conditions. Rebuilding Christchurch with the new modifications in the seismic building code comes with its own unique challenges to the entire system. This project investigates the impact of rebuilding Christchurch with the new seismic Building codes in terms of how the new changes affected the building industry and the management of construction.

Images, UC QuakeStudies

A notice on the fence outside the CTV site on Madras Street. The notice reads, "Please respect this site. In recognition of the special significance this site holds for the people of our city and all those affected by the earthquakes, the Christchurch City Council is working with Canterbury Museum to preserve aspects of our remembering. Tributes may be left at this site. Older tributes will be removed for archiving by the Canterbury Museum to become part of the city's memory of the Canterbury Earthquakes. Organic materials will be composted and used in the city's gardens. Canterbury Museum. Christchurch City Council".

Images, UC QuakeStudies

A photograph of the entrance to Cowles Stadium on Pages Road. The stadium was set up by Civil Defence to serve as temporary accommodation for people displaced by the 4 September 2010 earthquake. Signs on the door read, "Civil Defence", "If you are unwwell with flu or cold, please go to the doctor and not enter" and "Welcome to Cowles Stadium. Earthquake affected people only - you must register with Red Cross to receive help. Other help go to Winz office, 154 Aldwins Road, Linwood. Please, no alcohol, no drugs on site. Food and drinks only in designated areas".

Research papers, University of Canterbury Library

We measure the longer-term effect of a major earthquake on the local economy, using night-time light intensity measured from space, and investigate whether insurance claim payments for damaged residential property affected the local recovery process. We focus on the destructive Canterbury Earthquake Sequence (CES) 2010 -2011 as our case study. Uniquely for this event, more than 95% of residential housing units were covered by insurance, but insurance payments were staggered over 5 years, enabling us to identify their local impact. We find that night-time luminosity can capture the process of recovery and describe the recovery’s determinants. We also find that insurance payments contributed significantly to the process of economic recovery after the earthquake, but delayed payments were less affective and cash settlement of claims were more effective than insurance-managed repairs in contributing to local recovery.

Research papers, The University of Auckland Library

The rapid classification of building damage states or placards after an earthquake is vital for enabling an efficient emergency response and informed decision-making for rehabilitation and recovery purposes. Traditional methods rely heavily on inspector-led on-site surveys, which are often time-consuming, resource-intensive, and susceptible to human error. This study introduces a machine learning-supported surrogate model designed to streamline the assessment of building damage, focusing on the automated assignment of damage placards within the context of New Zealand's post-earthquake evaluation frameworks. The study evaluates two key safety evaluation protocols—Rapid Building Assessment (RBA) and Detailed Damage Evaluation (DDE)—and integrates corresponding databases derived from the 2010–2011 Canterbury Earthquake Sequence (CES) in Christchurch. Six ML classifiers—Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gradient Boosting Classifier (GBC), and Gradient Bagging (GBag)—were rigorously tested across both databases. The results indicate that the RF-based surrogate model outperforms the other classifiers across both RBA and DDE protocols. Two distinct sets of critical predictors have been further identified for each protocol, allowing for the rapid retrieval of essential data for future on-site surveys, while retaining the RF model's predictive accuracy. The developed surrogate model provides a pragmatic tool for practising engineers to rapidly assign placards to damaged structures and for policymakers and building owners to make informed recovery decisions for earthquake-affected buildings.

Research papers, University of Canterbury Library

Many buildings with relatively low damage from the 2010-2011 Canterbury were deemed uneconomic to repair and were replaced [1,2]. Factors that affected commercial building owners’ decisions to replace rather than repair, included capital availability, uncertainty with regards to regional recovery, local market conditions and ability to generate cash flow, and repair delays due to limited property access (cordon). This poster provides a framework for modeling decision-making in a case where repair is feasible but replacement might offer greater economic value – a situation not currently modeled in engineering risk analysis.

Research papers, The University of Auckland Library

This thesis presents the application of data science techniques, especially machine learning, for the development of seismic damage and loss prediction models for residential buildings. Current post-earthquake building damage evaluation forms are developed for a particular country in mind. The lack of consistency hinders the comparison of building damage between different regions. A new paper form has been developed to address the need for a global universal methodology for post-earthquake building damage assessment. The form was successfully trialled in the street ‘La Morena’ in Mexico City following the 2017 Puebla earthquake. Aside from developing a framework for better input data for performance based earthquake engineering, this project also extended current techniques to derive insights from post-earthquake observations. Machine learning (ML) was applied to seismic damage data of residential buildings in Mexico City following the 2017 Puebla earthquake and in Christchurch following the 2010-2011 Canterbury earthquake sequence (CES). The experience showcased that it is readily possible to develop empirical data only driven models that can successfully identify key damage drivers and hidden underlying correlations without prior engineering knowledge. With adequate maintenance, such models have the potential to be rapidly and easily updated to allow improved damage and loss prediction accuracy and greater ability for models to be generalised. For ML models developed for the key events of the CES, the model trained using data from the 22 February 2011 event generalised the best for loss prediction. This is thought to be because of the large number of instances available for this event and the relatively limited class imbalance between the categories of the target attribute. For the CES, ML highlighted the importance of peak ground acceleration (PGA), building age, building size, liquefaction occurrence, and soil conditions as main factors which affected the losses in residential buildings in Christchurch. ML also highlighted the influence of liquefaction on the buildings losses related to the 22 February 2011 event. Further to the ML model development, the application of post-hoc methodologies was shown to be an effective way to derive insights for ML algorithms that are not intrinsically interpretable. Overall, these provide a basis for the development of ‘greybox’ ML models.

Research papers, The University of Auckland Library

Disasters, either man-made or natural, are characterised by a multiplicity of factors including loss of property, life, environmental degradation, and psychosocial malfunction of the affected community. Although much research has been undertaken on proactive disaster management to help reduce the impacts of natural and man-made disasters, many challenges still remain. In particular, the desire to re-house the affected as quickly as possible can affect long-term recovery if a considered approach is not adopted. Promoting recovery activities, coordination, and information sharing at national and international levels are crucial to avoid duplication. Mannakkara and Wilkinson’s (2014) modified “Build Back Better” (BBB) concept aims for better resilience by incorporating key resilience elements in post-disaster restoration. This research conducted an investigation into the effectiveness of BBB in the recovery process after the 2010–2011 earthquakes in greater Christchurch, New Zealand. The BBB’s impact was assessed in terms of its five key components: built environment, natural environment, social environment, economic environment, and implementation process. This research identified how the modified BBB propositions can assist in disaster risk reduction in the future, and used both qualitative and quantitative data from both the Christchurch and Waimakariri recovery processes. Semi-structured interviews were conducted with key officials from the Christchurch Earthquake Recovery Authority, and city councils, and supplemented by reviewing of the relevant literature. Collecting data from both qualitative and quantitative sources enabled triangulation of the data. The interviewees had directly participated in all phases of the recovery, which helped the researcher gain a clear understanding of the recovery process. The findings led to the identification of best practices from the Christchurch and Waimakariri recovery processes and underlined the effectiveness of the BBB approach for all recovery efforts. This study contributed an assessment tool to aid the measurement of resilience achieved through BBB indicators. This tool provides systematic and structured approach to measure the performance of ongoing recovery.

Research papers, Victoria University of Wellington

The standard way in which disaster damages are measured involves examining separately the number of fatalities, of injuries, of people otherwise affected, and the financial damage that natural disasters cause. Here, we implement a novel way to aggregate these separate measures of disaster impact and apply it to two catastrophic events from 2011: the Christchurch (New Zealand) earthquakes and the Greater Bangkok (Thailand) flood. This new measure, which is similar to the World Health Organization's calculation of Disability Adjusted Life Years (DALYs) lost due to the burden of diseases and injuries, is described in detail in Noy [7]. It allows us to conclude that New Zealand lost 180 thousand lifeyears as a result of the 2011 events, and Thailand lost 2644 thousand lifeyears. In per capita terms, the loss is similar, with both countries losing about 15 days per person due to the 2011 catastrophic events in these two countries. © This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

Research papers, The University of Auckland Library

As damage and loss caused by natural hazards have increased worldwide over the past several decades, it is important for governments and aid agencies to have tools that enable effective post-disaster livelihood recovery to create self-sufficiency for the affected population. This study introduces a framework of critical components that constitute livelihood recovery and the critical factors that lead to people’s livelihood recovery. A comparative case study is employed in this research, combined with questionnaire surveys and interviews with those communities affected by large earthquakes in Lushan, China and in Christchurch and Kaikōura, New Zealand. In Lushan, China, a framework with four livelihood components was established, namely, housing, employment, wellbeing and external assistance. Respondents considered recovery of their housing to be the most essential element for livelihood diversification. External assistance was also rated highly in assisting with their livelihood recovery. Family ties and social connections seemed to have played a larger role than that of government agencies and NGOs. However, the recovery of livelihood cannot be fully achieved without wellbeing aspects being taken into account, and people believed that quality of life and their physical and mental health were essential for livelihood restoration. In Christchurch, New Zealand, the identified livelihood components were validated through in-depth interviews. The results showed that the above framework presenting what constitutes successful livelihood recovery could also be applied in Christchurch. This study also identified the critical factors to affect livelihood recovery following the Lushan and Kaikōura earthquakes, and these include community safety, availability of family support, level of community cohesion, long-term livelihood support, external housing recovery support, level of housing recovery and availability of health and wellbeing support. The framework developed will provide guidance for policy makers and aid agencies to prioritise their strategies and initiatives in assisting people to reinstate their livelihood in a timely manner post-disaster. It will also assist the policy makers and practitioners in China and New Zealand by setting an agenda for preparing for livelihood recovery in non-urgent times so the economic impact and livelihood disruption of those affected can be effectively mitigated.