The role of belonging in post-disaster environments remains an under-theorised concept, particularly regarding refugee populations. This paper presents a qualitative study with 101 refugee-background participants from varying communities living in Christchurch, New Zealand, about their perspectives and responses to the Canterbury earthquakes of 2010–11. Participants spoke of how a sense of belonging as individuals and as a wider community was important in the recovery effort, and highlighted the multiple ways in which they understood this concept. Their comments demonstrate how belonging can have contextual, chronological and gendered dimensions that can help inform effective and resonant disaster responses with culturally and linguistically diverse populations. This analysis also illustrates how the participants' perspectives of belonging shifted over time, and discusses the corresponding role of social work in supporting post-disaster recovery through the concepts of civic, ethno and ethnic-based belonging AM - Accepted Manuscript
As part of a seismic retrofit scheme, surface bonded glass fiber-reinforced polymer (GFRP) fabric was applied to two unreinforced masonry (URM) buildings located in Christchurch, New Zealand. The unreinforced stone masonry of Christchurch Girls’ High School (GHS) and the unreinforced clay brick masonry Shirley Community Centre were retrofitted using surface bonded GFRP in 2007 and 2009, respectively. Much of the knowledge on the seismic performance of GFRP retrofitted URM was previously assimilated from laboratory-based experimental studies with controlled environments and loading schemes. The 2010/2011 Canterbury earthquake sequence provided a rare opportunity to evaluate the GFRP retrofit applied to two vintage URM buildings and to document its performance when subjected to actual design-level earthquake-induced shaking. Both GFRP retrofits were found to be successful in preserving architectural features within the buildings as well as maintaining the structural integrity of the URM walls. Successful seismic performance was based on comparisons made between the GFRP retrofitted GHS building and the adjacent nonretrofitted Boys’ High School building, as well as on a comparison between the GFRP retrofitted and nonretrofitted walls of the Shirley Community Centre building. Based on detailed postearthquake observations and investigations, the GFRP retrofitted URM walls in the subject buildings exhibited negligible to minor levels of damage without delamination, whereas significant damage was observed in comparable nonretrofitted URM walls AM - Accepted Manuscript
The supply of water following disasters has always been of significant concern to communities. Failure of water systems not only causes difficulties for residents and critical users but may also affect other hard and soft infrastructure and services. The dependency of communities and other infrastructure on the availability of safe and reliable water places even more emphasis on the resilience of water supply systems. This thesis makes two major contributions. First, it proposes a framework for measuring the multifaceted resilience of water systems, focusing on the significance of the characteristics of different communities for the resilience of water supply systems. The proposed framework, known as the CARE framework, consists of eight principal activities: (1) developing a conceptual framework; (2) selecting appropriate indicators; (3) refining the indicators based on data availability; (4) correlation analysis; (5) scaling the indicators; (6) weighting the variables; (7) measuring the indicators; and (8) aggregating the indicators. This framework allows researchers to develop appropriate indicators in each dimension of resilience (i.e., technical, organisational, social, and economic), and enables decision makers to more easily participate in the process and follow the procedure for composite indicator development. Second, it identifies the significant technical, social, organisational and economic factors, and the relevant indicators for measuring these factors. The factors and indicators were gathered through a comprehensive literature review. They were then verified and ranked through a series of interviews with water supply and resilience specialists, social scientists and economists. Vulnerability, redundancy and criticality were identified as the most significant technical factors affecting water supply system robustness, and consequently resilience. These factors were tested for a scenario earthquake of Mw 7.6 in Pukerua Bay in New Zealand. Four social factors and seven indicators were identified in this study. The social factors are individual demands and capacities, individual involvement in the community, violence level in the community, and trust. The indicators are the Giving Index, homicide rate, assault rate, inverse trust in army, inverse trust in police, mean years of school, and perception of crime. These indicators were tested in Chile and New Zealand, which experienced earthquakes in 2010 and 2011 respectively. The social factors were also tested in Vanuatu following TC Pam, which hit the country in March 2015. Interestingly, the organisational dimension contributed the largest number of factors and indicators for measuring water supply resilience to disasters. The study identified six organisational factors and 17 indicators that can affect water supply resilience to disasters. The factors are: disaster precaution; predisaster planning; data availability, data accessibility and information sharing; staff, parts, and equipment availability; pre-disaster maintenance; and governance. The identified factors and their indicators were tested for the case of Christchurch, New Zealand, to understand how organisational capacity affected water supply resilience following the earthquake in February 2011. Governance and availability of critical staff following the earthquake were the strongest organisational factors for the Christchurch City Council, while the lack of early warning systems and emergency response planning were identified as areas that needed to be addressed. Economic capacity and quick access to finance were found to be the main economic factors influencing the resilience of water systems. Quick access to finance is most important in the early stages following a disaster for response and restoration, but its importance declines over time. In contrast, the economic capacity of the disaster struck area and the water sector play a vital role in the subsequent reconstruction phase rather than in the response and restoration period. Indicators for these factors were tested for the case of the February 2011 earthquake in Christchurch, New Zealand. Finally, a new approach to measuring water supply resilience is proposed. This approach measures the resilience of the water supply system based on actual water demand following an earthquake. The demand-based method calculates resilience based on the difference between water demand and system capacity by measuring actual water shortage (i.e., the difference between water availability and demand) following an earthquake
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
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
