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
What does it mean to “be in a mood” at school? This question guides this thesis, which analyses the relationship between young people’s experiences of moods and the discourses and pedagogies of moods they encounter at school. The emotions and moods of young people in Christchurch, New Zealand, have, in recent years, come under considerable scrutiny. A national decline in rates of youth mental health and concern over the lasting psychological effects of the 2010-2011 Christchurch Earthquakes have justified increased attention to and funding for youth mental health promotion and school-based mental health education programs. Drawing on a year-long school ethnography at a public girl’s high school in Christchurch with 22 Year 10 students (age 14-15), this thesis examines how young people interact with state and psychiatric discourses of youth and mental health. It explores how young people integrate and transform these discourses in their experiences and knowledges of moods as they relate to mental health, education, friendships, and the (in)stability of the self in time. Additionally, this thesis proposes an anthropological reconsideration of moods. Developing insights from phenomenological and medical anthropology and bringing them into conversation with ethnographic analysis, the approach to moods in this thesis sees two necessarily interconnected ways in which moods become significant for understanding subjectivity and contemporary society. On the one hand, moods are an integral dimension of phenomenological experience in which it is possible to dwell in affective ambiguities, producing open-ended horizons of experience. On the other hand, young people’s experience of moods is refracted through moods’ medicalised formulation as experience that can be bounded, taxonomized, transformed into kinds of knowledge about the self, and thus acted on in distinct and morally situated ways. Attending to the experience of “being in a mood” at school reveals how medical and psychiatric knowledges are woven into moral experience in the everyday. This moral experience of moods has critical implications for how young people in New Zealand today situate the self in relationships, in the world, and in time, and therefore is particularly revealing for developing anthropological understandings of teenage subjectivity
Road networks are highly exposed to natural hazard events, which can lead to significant economic and social consequences. In New Zealand, events such as the 2011 Christchurch earthquake, the 2016 Kaikōura earthquake, and the Cyclone Gabrielle in 2023 have demonstrated the severe consequences of road network disruptions. Traditional post event economic assessments often focus solely on clean-up and repair costs, neglecting the broader and more enduring impacts these events can have. Furthermore, business cases for resilience investments usually fail when quantifying the economic benefits of mitigation strategies, due to the underestimation of road disruption consequences. Importantly, not all road link disruptions contribute equally to these consequences, making the identification of critical road links a key step in resilience focused investment prioritization. Furthermore, traditional transportation asset management typically evaluates the life cycle of roads under normal conditions, such as traffic loads and standard environmental factors, while neglecting the influence of natural hazards. However, these events can significantly alter road deterioration and increase maintenance costs, emphasizing the need for integrating risk and resilience into transportation asset management approaches. This thesis presents a methodology to evaluate road criticality by assessing the economic consequences of road disruptions in combination with a hazard model in a prioritization index. Initially, the consequences are quantified through increased travel time, higher vehicle operating costs, and increased gas emissions. Thereafter, a new consequence model is introduced to estimate the increase in maintenance costs on alternative routes that absorb diverted traffic following a disruption. These consequence models are initially applied in a 'full-scan' analysis approach, where each road link is removed in turn to quantify its potential impact and, therefore, its criticality. Subsequently, a hazard model is integrated to develop a road prioritization index that combines the expected impacts of road disruptions, the individual road link criticality, and the probability of occurrence of natural hazard events. This index is designed to help road agencies in prioritizing mitigation strategies. Furthermore, the proposed methodology can also be applied to quantify the indirect economic impacts of natural hazard events. The methodology is demonstrated using New Zealand’s South Island inter-urban network as a case study, incorporating an earthquake-induced landslide model, with Python based simulations, providing road agencies a valuable tool to quantify the economic benefits of resilience investments
Past earthquakes have consistently highlighted the vulnerabilities of the built environment. Current building codes, which focus primarily on life safety, fail to address the need for buildings to remain functional after a seismic event. The emerging concept of post-earthquake functional recovery aims to integrate recovery-based objectives into building codes. However, literature reveals a predominant focus on engineering parameters, with limited attention given to the perspectives of building users; a critical gap in understanding a building’s comprehensive functionality and path to functional recovery. Whilst structural integrity is essential, functionality following a disaster is not determined by physical stability alone. Thus, this study addresses this gap by exploring the perceptions and expectations of office building users (both tenants and property owners) regarding building functionality and post-earthquake functional recovery in New Zealand’s major urban centres: Wellington, Auckland, and Christchurch. A qualitative research strategy was employed, utilising interpretative phenomenological and grounded theory methods to develop insights from the lived experiences of twenty-six (26) participants. The study applied a systems thinking approach using a socio-technical systems (STS) framework to develop micro (single construct) and macro (multiple constructs) models of building-system functionality. The findings demonstrate that a building’s functionality is nuanced, multifaceted, and context dependent. It encompasses physical, economic, social, organisational, technical, regulatory, and environmental elements, and is ultimately determined by users’ specific needs and priorities. A key divergence emerged: whilst property owners prioritise economic and environmental factors, tenants focus on the socio-organisational aspect, viewing the physical workspace as an embodiment of corporate identity, culture, and values. Regarding expectations for post-earthquake functional recovery, the post-pandemic era has drastically reshaped outlooks. Unlike previous earthquakes, where tenants scrambled for any available space, there is now increased demand for flexibility due to the hybrid work model. The immediate return to an office following a major earthquake is now expected to support critical business functions, with essential services including power or a standby generator, technology to access files, water, as well as operations of air conditioning and elevators. By advancing socio-technical systems theory and elucidating building users’ perspectives for a building’s functionality and post-disaster functional recovery, this research provides evidence-based, social science insights to inform more holistic and effective risk governance in property and disaster risk management
The devastating consequences of past events, such as the 2004 Indian Ocean and 2011 Tōhoku tsunamis, emphasise the need for continued improvement in resilience measures. Given that 80% of magnitude 8+ earthquakes occur on the Pacific Rim, New Zealand's tsunami risk is significant. This research develops a novel tsunami inundation model. The proposed model applies equations based on hydraulic principles, including energy conservation (friction loss). While it does not fully replicate hydrodynamic models, it maintains a two-dimensional approach and offers significant improvements over currently implemented simplified methods. It retains excellent computational efficiency (seconds to minutes) while achieving a significant increase in accuracy that is comparable to traditional hydrodynamic models, which typically take hours to days. Calibration of the roughness input variables to hydrodynamic modelling at Gisborne and Christchurch, New Zealand, optimised the model to achieve similarity index values of above 84% for inundation extent, while 77% of inundation depths were within ±1 m and over 93% within ±2 m. This research then produces the first nationally consistent tsunami exposure assessment for New Zealand using a physics-based modelling method. Using probabilistic shoreline wave amplitude data, the study generates high-resolution (10 m) inundation maps for seven return periods (50th and 84th percentiles). These maps are integrated with land cover and infrastructure data to quantify exposure and identify the most vulnerable locations. The results highlight exposure not only to the commonly studied cities but also to several provincial areas. The identification of exposure is the foremost step towards practical resilience efforts; however, understanding specific infrastructure impacts ensures that countermeasures and risk reduction practices are implemented. Therefore, a detailed evaluation of the NZTA Bridge Manual is conducted. Comparisons are made between the NZTA methodology and the rapid model developed in this research. The results reveal a significant overestimation of bridge and culvert exposure by NZTA methods. The study further highlights critical exposure locations for bridge and culvert assets. Flow depths calculated at bridge locations are significantly overestimated using the NZTA method compared to results derived from hydrodynamic modelling and the rapid model. This research then conducts component-level modelling of culvert assets, due to their identified vulnerability in the transportation network. At a 1:15 geometrical scale, laboratory experiments evaluated the response of different culvert set-ups to tsunami bores. The findings provide a detailed description into overtopping, flow regimes and pressure distributions and give laboratory experiments as validation studies for future numerical modelling and design improvements. Overall, this research performs a multi-modal tsunami inundation assessment, uniting macro-level exposure modelling with micro-level component responses by integrating modelling, exposure analysis, and experimental validation. The findings support refining current tsunami guidelines, improving infrastructure planning, and enhancing community preparedness. Overall, the study’s multi-model approach strengthens many elements of New Zealand’s ability to mitigate and respond to future tsunami events
Though generally considered “natural” disasters, cyclones and earthquakes are increasingly being associated with human activities, incubated through urban settlement patterns and the long-term redistribution of natural resources. As society is becoming more urbanized, the risk of human exposure to disasters is also rising. Architecture often reflects the state of society’s health: architectural damage is the first visible sign of emergency, and reconstruction is the final response in the process of recovery. An empirical assessment of architectural projects in post-disaster situations can lead to a deeper understanding of urban societies as they try to rebuild. This thesis offers an alternative perspective on urban disasters by looking at the actions and attitudes of disaster professionals through the lens of architecture, situated in recent events: the 2010 Christchurch earthquake, the 2010 Haiti earthquake, and the 2005 Hurricane Katrina. An empirical, multi-hazard, cross-sectional case study methodology was used, employing grounded theory method to build theory, and a critical constructivist strategy to inform the analysis. By taking an interdisciplinary approach to understanding disasters, this thesis positions architecture as a conduit between two divergent approaches to disaster research: the hazards approach, which studies the disaster cycles from a scientific perspective; and the sociological approach, which studies the socially constructed vulnerabilities that result from disasters, and the elements of social change that accompany such events. Few studies to date have attempted to integrate the multi-disciplinary perspectives that can advance our understanding of societal problems in urban disasters. To bridge this gap, this thesis develops what will be referred to as the “Rittelian framework”—based on the work of UC Berkeley’s architecture professor Horst Rittel (1930-1990). The Rittelian framework uses the language of design to transcend the multiple fields of human endeavor to address the “design problems” in disaster research. The processes by which societal problems are addressed following an urban disaster involve input by professionals from multiple fields—including economics, sociology, medicine, and engineering—but the contribution from architecture has been minimal to date. The main impetus for my doctoral thesis has been the assertion that most of the decisions related to reconstruction are made in the early emergency recovery stages where architects are not involved, but architects’ early contribution is vital to the long-term reconstruction of cities. This precipitated in the critical question: “How does the Rittelian framework contribute to the critical design decisions in modern urban disasters?” Comparative research was undertaken in three case studies of recent disasters in New Orleans (2005), Haiti (2010) and Christchurch (2010), by interviewing 51 individuals who were selected on the basis of employing the Rittelian framework in their humanitarian practice. Contextualizing natural disaster research within the robust methodological framework of architecture and the analytical processes of sociology is the basis for evaluating the research proposition that architectural problem solving is of value in addressing the ‘Wicked Problems’ of disasters. This thesis has found that (1) the nuances of the way disaster agents interpret the notion of “building back better” can influence the extent to which architectural professionals contribute in urban disaster recovery, (2) architectural design can be used to facilitate but also impede critical design decisions, and (3) framing disaster research in terms of design decisions can lead to innovation where least expected. This empirical research demonstrates how the Rittelian framework can inform a wider discussion about post-disaster human settlements, and improve our resilience through disaster research
