Mechanistic and scientific approaches to resilience assume that there is a “tipping point” at which a system can no longer absorb adversity; after this point, it is liable to collapse. Some of these perspectives, particularly those stemming from ecology and psychology, recognise that individuals and communities cannot be perpetually resilient without limits. While the resilience paradigm has been imported into the social sciences, the limits to resilience have often been disregarded. This leads to an overestimation of “human resourcefulness” within the resilience paradigm. In policy discourse, practice, and research, resilience seems to be treated as a “limitless” and human quality in which individuals and communities can effectively cope with any hazard at any time, for as long as they want and with any people. We critique these assumptions with reference to the recovery case in Ōtautahi Christchurch, Aotearoa New Zealand following the 2010-11 Canterbury earthquake sequence. We discuss the limits to resilience and reconceptualise resilience thinking for disaster risk reduction and sustainable recovery and development.
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.
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/
Detailed studies on the sediment budget may reveal valuable insights into the successive build-up of the Canterbury Plains and their modification by Holocene fluvialaction connected to major braided rivers. Additionally, they bear implications beyond these fluvial aspects. Palaeoseismological studies claim to have detected signals of major Alpine Fault earthquakes in coastal environments along the eastern seaboard of the South Island (McFadgen and Goff, 2005). This requires high connectivity between the lower reaches of major braided rivers and their mountain catchments to generate immediate significant sediment pulses. It would be contradictory to the above mentioned hypothesis though. Obtaining better control on sediment budgets of braided rivers like the Waimakariri River will finally add significant value to multiple scientific and applied topics like regional resource management. An essential first step of sediment budget studies Is to systematically map the geomorphology, conventionally in the field and/or using remote-sensing applications, to localise, genetically identify, and classify landforms or entire toposequences of the area being investigated. In formerly glaciated mountain environments it is also indispensable to obtain all available chronological information supporting subsequent investigations.
©2019. American Geophysical Union. All Rights Reserved. Earthquakes have been inferred to induce hydrological changes in aquifers on the basis of either changes to well water-levels or tidal behavior, but the relationship between these changes remains unclear. Here, changes in tidal behavior and water-levels are quantified using a hydrological network monitoring gravel aquifers in Canterbury, New Zealand, in response to nine earthquakes (of magnitudes M w 5.4 to 7.8) that occurred between 2008 and 2015. Of the 161 wells analyzed, only 35 contain water-level fluctuations associated with “Earth + Ocean” (7) or “Ocean” (28) tides. Permeability reduction manifest as changes in tidal behavior and increased water-levels in the near field of the Canterbury earthquake sequence of 2010–2011 support the hypothesis of shear-induced consolidation. However, tidal behavior and water-level changes rarely occurred simultaneously (~2%). Water-level changes that occurred with no change in tidal behavior reequilibrated at a new postseismic level more quickly (on timescales of ~50 min) than when a change in tidal behavior occurred (~240 min to 10 days). Water-level changes were more than likely to occur above a peak dynamic stress of ~50 kPa and were more than likely to not occur below ~10 kPa. The minimum peak dynamic stress required for a tidal behavior change to occur was ~0.2 to 100 kPa.
Background: Up to 6 years after the 2011 Christchurch earthquakes, approximately one-third of parents in the Christchurch region reported difficulties managing the continuously high levels of distress their children were experiencing. In response, an app named Kākano was co-designed with parents to help them better support their children’s mental health. Objective: The objective of this study was to evaluate the acceptability, feasibility, and effectiveness of Kākano, a mobile parenting app to increase parental confidence in supporting children struggling with their mental health. Methods: A cluster-randomized delayed access controlled trial was carried out in the Christchurch region between July 2019 and January 2020. Parents were recruited through schools and block randomized to receive immediate or delayed access to Kākano. Participants were given access to the Kākano app for 4 weeks and encouraged to use it weekly. Web-based pre- and postintervention measurements were undertaken. Results: A total of 231 participants enrolled in the Kākano trial, with 205 (88.7%) participants completing baseline measures and being randomized (101 in the intervention group and 104 in the delayed access control group). Of these, 41 (20%) provided full outcome data, of which 19 (18.2%) were for delayed access and 21 (20.8%) were for the immediate Kākano intervention. Among those retained in the trial, there was a significant difference in the mean change between groups favoring Kākano in the brief parenting assessment (F1,39=7, P=.012) but not in the Short Warwick-Edinburgh Mental Well-being Scale (F1,39=2.9, P=.099), parenting self-efficacy (F1,39=0.1, P=.805), family cohesion (F1,39=0.4, P=.538), or parenting sense of confidence (F1,40=0.6, P=.457). Waitlisted participants who completed the app after the waitlist period showed similar trends for the outcome measures with significant changes in the brief assessment of parenting and the Short Warwick-Edinburgh Mental Well-being Scale. No relationship between the level of app usage and outcome was found. Although the app was designed with parents, the low rate of completion of the trial was disappointing. Conclusions: Kākano is an app co-designed with parents to help manage their children’s mental health. There was a high rate of attrition, as is often seen in digital health interventions. However, for those who did complete the intervention, there was some indication of improved parental well-being and self-assessed parenting. Preliminary indications from this trial show that Kākano has promising acceptability, feasibility, and effectiveness, but further investigation is warranted. Trial Registration: Australia New Zealand Clinical Trials Registry ACTRN12619001040156; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377824&isReview=true
Welcome to the Recover newsletter Issue 2 from the Marine Ecology Research Group (MERG) at the University of Canterbury. Recover is designed to keep you updated on our MBIE funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This second issue profiles some of the recent work done by our team out in the field!
Welcome to the first Recover newsletter from the Marine Ecology Research Group (MERG) at the University of Canterbury. Recover is designed to keep you updated on our MBIE funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Ecosystem Recovery). This first issue provides a summary of some of the big changes we’ve seen. In the next issue we’ll be profiling some of the current research as well as ways you can get involved!
Welcome to the Recover newsletter Issue 6 from the Marine Ecology Research Group (MERG) of the University of Canterbury. Recover is designed to keep you updated on our MBIE-funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This 6th instalment features the ‘new land’ created by the earthquake uplift of the coastline, recreational uses of beaches in Marlborough, and pāua survey work and hatchery projects with our partners in Kaikōura.
Measurement of basement seismic resonance frequencies can elucidate shallow velocity structure, an important factor in earthquake hazard estimation. Ambient noise cross correlation, which is well-suited to studying shallow earth structure, is commonly used to analyze fundamental-mode Rayleigh waves and, increasingly, Love waves. Here we show via multicomponent ambient noise cross correlation that the basement resonance frequency in the Canterbury region of New Zealand can be straightforwardly determined based on the horizontal to vertical amplitude ratio (H/V ratio) of the first higher-mode Rayleigh waves. At periods of 1-3 s, the first higher-mode is evident on the radial-radial cross-correlation functions but almost absent in the vertical-vertical cross-correlation functions, implying longitudinal motion and a high H/V ratio. A one-dimensional regional velocity model incorporating a ~ 1.5 km-thick sedimentary layer fits both the observed H/V ratio and Rayleigh wave group velocity. Similar analysis may enable resonance characteristics of other sedimentary basins to be determined. © 2013. American Geophysical Union. All Rights Reserved.
We examine the role of business interruption (BI) insurance in business recovery following the Christchurch earthquake in 2011. First, we ask whether BI insurance increases the likelihood of business survival in the immediate (3-6 months) aftermath of a disaster. We find positive but statistically insignificant evidence that those firms that had incurred damage, but were covered by BI insurance, had higher likelihood of survival post-quake compared with those firms that did not have any insurance. For the medium-term (2-3 years) survival of firms, our results show a more explicit role for insurance. Firms with BI insurance experience increased productivity and improved performance following a catastrophe. Furthermore, we find that those organisations that receive prompt and full payments of their claims have a better recovery than those that had protracted or inadequate claims payments, but this difference between the two groups is not statistically significant. We find no statistically significant evidence that the latter group (inadequate payment) did any better than those organisations that had damage but no insurance coverage. In general, our analysis indicates the importance not only of adequate insurance coverage, but also of an insurance system that delivers prompt claim payments.
This is a post-peer-review, pre-copyedit version of an article published in 'The Geneva Papers on Risk and Insurance - Issues and Practice'. The final authenticated version is available online at: https://doi.org/10.1057/s41288-017-0067-y. The following terms of use apply: https://www.springer.com/gp/open-access/publication-policies/aam-terms-of-use.
This paper presents on-going challenges in the present paradigm shift of earthquakeinduced ground motion prediction from empirical to physics-based simulation methods. The 2010-2011 Canterbury and 2016 Kaikoura earthquakes are used to illustrate the predictive potential of the different methods. On-going efforts on simulation validation and theoretical developments are then presented, as well as the demands associated with the need for explicit consideration of modelling uncertainties. Finally, discussion is also given to the tools and databases needed for the efficient utilization of simulated ground motions both in specific engineering projects as well as for near-real-time impact assessment.
This is a joint Resilience Framework undertaken by the Electrical, Computer and Software Engineering Department of the University of Auckland in association with West Power and Orion networks and partially funded by the New Zealand National Science Challenge and QuakeCoRE. The Energy- Communication research group nearly accomplished two different researches focusing on both asset resilience and system resilience. Asset resilience research which covers underground cables system in Christchurch region is entitled “2010-2011 Canterbury Earthquake Sequence Impact on 11KV Underground Cables” and system resilience research which covers electricity distribution and communication system in West Coast region is entitled “NZ Electricity Distribution Network Resilience Assessment and Restoration Models following Major Natural Disturbance“. As the fourth milestone of the aforementioned research project, the latest outcome of both projects has been socialised with the stakeholders during the Cigre NZ 2019 Forum.
Observations in major earthquakes have shown that rockable structures suffered less to no damage. During rocking, that is, partial and temporary footing separations, the influx of seismic energy is interrupted and thus the impact of the base excitation is reduced. Rocking causes the structure to deform more rigid like. Consequently, the structure experiences less deformation along the height and thus a lower damage potential. Although many researchers have studied the influence of rockable footings, most of these are either analytical or numerical, and only a very few structures have been built with rockable footings worldwide, for example, the chimney at Christchurch Airport and the South Rangitikei Viaduct in New Zealand. Despite these studies, a thorough and understanding is not yet available, especially with respect to experimental validations. This work is the first to investigate the rocking behaviour of bridges with different slenderness using large‐scale shake table experiments. To limit the number of influence factors, a stiff footing support and the same fixed‐base fundamental frequency of the bridges were assumed. The result shows that the girder displacement and the footing rotation of the tall bridge do not always move in phase, which cannot be observed in the short bridge. The results demonstrate the important role of slenderness in the overall responses of rockable bridges. This behaviour cannot be observed in bridges with a commonly assumed fixed base since the slenderness effect cannot be activated.
On 15 August 1868, a great earthquake struck off the coast of the Chile-Peru border generating a tsunami that travelled across the Pacific. Wharekauri-Rekohu-Chatham Islands, located 800 km east of Christchurch, Aotearoa-New Zealand (A-NZ) was one of the worst affected locations in A-NZ. Tsunami waves, including three over 6 metres high, injured and killed people, destroyed buildings and infrastructure, and impacted the environment, economy and communities. While experience of disasters, and advancements in disaster risk reduction systems and technology have all significantly advanced A-NZ’s capacity to be ready for and respond to future earthquakes and tsunami, social memory of this event and other tsunamis during our history has diminished. In 2018, a team of scientists, emergency managers and communication specialists collaborated to organise a memorial event on the Chatham Islands and co-ordinate a multi-agency media campaign to commemorate the 150th anniversary of the 1868 Arica tsunami. The purpose was to raise awareness of the disaster and to encourage preparedness for future tsunami. Press releases and science stories were distributed widely by different media outlets and many attended the memorial event indicating public interest for commemorating historical disasters. We highlight the importance of commemorating disaster anniversaries through memorial events, to raise awareness of historical disasters and increase community preparedness for future events – “lest we forget and let us learn.”
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.
Tsunami events including the 2004 Indian Ocean Tsunami and the 2011 Tohoku Earthquake and Tsunami confirmed the need for Pacific-wide comprehensive risk mitigation and effective tsunami evacuation planning. New Zealand is highly exposed to tsunamis and continues to invest in tsunami risk awareness, readiness and response across the emergency management and science sectors. Evacuation is a vital risk reduction strategy for preventing tsunami casualties. Understanding how people respond to warnings and natural cues is an important element to improving evacuation modelling techniques. The relative rarity of tsunami events locally in Canterbury and also globally, means there is limited knowledge on tsunami evacuation behaviour, and tsunami evacuation planning has been largely informed by hurricane evacuations. This research aims to address this gap by analysing evacuation behaviour and movements of Kaikōura and Southshore/New Brighton (coastal suburb of Christchurch) residents following the 2016 Kaikōura earthquake. Stage 1 of the research is engaging with both these communities and relevant hazard management agencies, using a survey and community workshops to understand real-event evacuation behaviour during the 2016 Kaikōura earthquake and subsequent tsunami evacuations. The second stage is using the findings from stage 1 to inform an agent-based tsunami evacuation model, which is an approach that simulates of the movement of people during an evacuation response. This method improves on other evacuation modelling approaches to estimate evacuation times due to better representation of local population characteristics. The information provided by the communities will inform rules and interactions such as traffic congestion, evacuation delay times and routes taken to develop realistic tsunami evacuation models. This will allow emergency managers to more effectively prepare communities for future tsunami events, and will highlight recommended actions to increase the safety and efficiency of future tsunami evacuations.
