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
Surface-rupturing earthquakes can trigger the sudden avulsion of river channels, causing rapid and persistent coseismic flooding of previously unaffected areas. This phenomenon, known as fault-rupture-induced river avulsion (FIRA), occurs when fault displacement significantly alters river channel topography. The importance of understanding FIRA as a secondary seismic hazard was highlighted by events during the 2010 Darfield and 2016 Kaikoura earthquakes in New Zealand. This thesis develops a national model to identify and quantify FIRA susceptibility across New Zealand by integrating hydrological datasets (NIWA RiverMaps and Flood Statistics) with active fault information (NZ Active Faults Database and RSQSim earthquake simulations). The methodology applies the F-index framework proposed by McEwan et al. (2023), which quantifies FIRA potential based on the ratio of fault throw plus discharge-dependent depth to bank full depth at each fault-river intersection. The model successfully identified 3,796 potential FIRA-susceptible fault-river intersections nationwide, with 451 involving waterways equal to or larger than the Hororata River. Regional analysis revealed higher concentrations of FIRA-susceptible sites in the Bay of Plenty, Canterbury, and Marlborough regions. Validation against historical events showed the model effectively located known FIRA occurrences from the Kaikoura and Darfield earthquakes, though with some limitations in accurately predicting F-index values due to complex fault displacement patterns and challenges in modelling bank full depths of large, braided rivers. This research establishes New Zealand's first nationwide assessment of fault-induced river avulsion susceptibility. The approach creates a structured methodology for identifying high-risk fault-river intersections and determining which sites require thorough localised examination. The methodology developed offers a template for similar assessments in other tectonically active regions and contributes to improving earthquake hazard assessment and disaster preparedness planning.
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
Effective management of waste and debris generated by a disaster event is vital to ensure rapid and efficient response and recovery that supports disaster risk reduction (DRR). Disaster waste refers to any stream of debris that is created from a natural disaster that impacts the environment, infrastructure, and property. This waste can be problematic due to extensive volumes, environmental contamination and pollution, public health risks, and the disruption of response and recovery efforts. Due to the complexities in dealing with these diverse and voluminous materials, having disaster waste management (DWM) planning in place pre-event is crucial. In particular, coordinated, interagency plans that have been informed by estimates of waste volumes and types are vital to ensure management facilities, personnel, and recovery resources do not become overwhelmed. Globally, a priority when formulating DWM plans is the robust estimation of disaster waste stream types and volumes. This is a relatively under-researched area, despite the growing risk of natural disasters and increasingly inadequate waste management facilities. In Aotearoa New Zealand, a nation-wide DWM planning tool has been proposed for local government use, and waste amounts from events such as the Christchurch Earthquakes have been estimated. However, there has been little work undertaken to estimate waste types and volumes with a region-specific, multi-hazard focus, which is required to facilitate detailed regional DWM planning. This research provides estimates of potential disaster waste volumes and types in the Waitaha-Canterbury region of the South Island (Te Waipounamu) for three key hazard scenarios: a M8.0 Alpine Fault earthquake with a south-to-north rupture pattern, a far-sourced tsunami using a maximum credible event model for a Peru-sourced event, and major flooding using geospatial datasets taken from available local government modelling. Conducted in partnership with Environment Canterbury and Canterbury CDEM, this estimation work informed stakeholder engagement through multi-agency workshops at the district level. This research was comprised of two key parts. The first was enhancing and extending a disaster waste estimation model used in Wellington and applying it to the Canterbury region to quantify waste volumes and types. The second part was using this model and its estimates to inform engagement with stakeholders in multi-agency, district-level workshops in Kaikōura, Hurunui, and Waimakariri. In these workshops, the waste estimates were used to catalyse discussion around potential issues associated with the management of disaster waste. Regionally, model estimates showed that the earthquake scenario would generate the highest total volume of disaster waste (1.94 million m³), compared to the tsunami scenario (1.89 million m³) and the flood scenario (173,900 m³). Flood waste estimates are likely underrepresented due to limited flood modelling coverage, but still provide a valuable comparison. Whilst waste estimates differ significantly between districts, waste volumes were shown to be not solely dependent on building/population density. The district-level workshops showed that DWM challenges revolved around logistical constraints, public concerns, governance complexities, and environmental issues. Future work should further enhance this estimation model and apply it to other regions of Aotearoa New Zealand, to help develop a set of cohesive DWM plans for each region. The waste estimation model could also be adapted and applied internationally. The findings from this research provide a foundation for advancing DWM planning and stakeholder engagement in the Waitaha-Canterbury region. By offering region-specific waste estimates across multiple hazard scenarios, this work supports district councils and emergency managers in developing informed, proactive strategies for disaster preparedness and response. The insights gained from district-level workshops highlight key challenges that must be addressed in future planning. These outcomes contribute to a broader research agenda for DWM in Aotearoa New Zealand, and offer a framework adaptable to international contexts.
According to TS 1170.5, designing a building to satisfy code-prescribed criteria (e.g., drift limit, member safety, P-Δ stability) at the ultimate limit state and relying on the inherent margins within the design code would lead to an acceptable mean annual frequency of collapse (λ꜀) in the range of 10−⁴ to 10−⁵. Modern performance objectives, such as λ꜀ and expected annual loss (EAL), are not explicitly considered. Although buckling-restrained braced frame (BRBF) buildings were widely adopted as lateral load-resisting systems for office and car park buildings in the Christchurch rebuild following the Canterbury earthquakes in New Zealand, there are currently no official guidelines for their design. The primary focus of this study is to develop a risk-targeted design framework for BRBF buildings that can achieve the performance objectives desired by stakeholders. To this extent, key factors influencing λ꜀ and EAL of BRBF buildings are identified. These factors include gusset plate design, number of storeys, design drift limit, BRBF beam-column connection, brace configuration, brace angle, brace material grade, and analysis method (equivalent lateral force vs. modal response spectrum). A novel 3D BRBF modelling approach capable of simulating out-of-plane buckling failure of buckling-restrained brace (BRB) gusset plates is developed. Prior experimental studies on sub-assemblies conducted elsewhere have demonstrated that gusset plates and end zones may buckle out of plane prematurely, before BRBs reach their maximum axial compression load carrying capacity. Current 2D BRBF macro models, typically used in research, cannot simulate this failure mode. A conventional 2D BRBF model underestimates the λ꜀ of a case-study 4-storey super-X configured steel BRBF building (designed according to NZS-3404) by a factor of two compared to the estimate from the proposed 3D model. These findings suggest that the current NZS-3404 gusset plate design method may undersize gusset plates and that using a 2D BRBF model in this case can significantly underestimate λ꜀. Three improved alternative gusset plate design methods that are easy to implement in practice are identified from the literature. Gusset plates in two case-study 4-storey steel BRBF buildings with super-X and diagonal configurations are designed using both the NZS-3404 method and alternative methods. All three alternative design methods are found to be conservative, resulting in an almost three-fold lower λ꜀ for both case-study BRBF buildings compared to those designed using the NZS-3404 method. Analysis results indicate that (i) bidirectional interaction has no significant effect on gusset plate buckling and (ii) mid-span gusset plates are more susceptible to buckling than corner gusset plates. A framework for seismic loss assessment using incremental dynamic analysis (IDA), called loss-oriented hazard-consistent incremental dynamic analysis (LOHC-IDA), is developed. IDA can be conducted with a generic record set, eliminating the arduous site-specific record selection required to conduct multiple stripe analysis (MSA). Traditional IDA, however, is limited in producing hazard-consistent estimates of engineering demand parameters (EDPs), which LOHC-IDA overcomes. LOHC-IDA improves upon existing methods by: (i) incorporating correlations among engineering demand parameters across intensity levels and (ii) using peak ground acceleration (PGA) to predict peak floor acceleration (PFA). For two case-study steel BRBF buildings, LOHC-IDA estimates the EAL and loss distributions conditioned on the intensity level that closely match the MSA results, with an average absolute error of 5%. The influence of factors beyond gusset plate design on the λ꜀ and EAL of 26 case-study steel BRBF buildings (designed in accordance with TS 1170.5) is examined. Hazard-consistent λ꜀ and EAL for these buildings are estimated using the FEMA P-58 loss and risk assessment framework. Among the 26 case-study buildings, 23 satisfy the maximum code-specified λ꜀ limit of 10−⁴. The EAL, normalised by the total building replacement cost, is highest for 2-storey BRBFs (0.22% on average), followed by 4-storey BRBFs (0.16% on average) and 8-storey BRBFs (0.11% on average). Reducing the design drift limit has the most significant effect on lowering λ꜀ (all BRBF designs were drift governed), followed by transitioning from pinned to moment-resisting beam-column connections, reducing the brace angle, and increasing brace strength. BRBF buildings designed using the equivalent lateral force method, on average, have a lower λ꜀ compared to those designed using the modal response spectrum method. Diagonally configured BRBFs exhibit the lowest λ꜀, followed by super- X and chevron configured BRBFs. Most design variables, apart from drift limit and beam-column connection, have limited influence on EAL. A simple method for EDP-targeted design of steel BRBF buildings is proposed. For this purpose, linear regression and CatBoost machine learning models are developed to predict steel BRBF building EDPs using peak storey drift ratio (PSDR) and PFA estimates from the 26 case-study buildings at intensity levels ranging from 80% to 0.5% probability of exceedance in 50 years. The R²ₐₔⱼ of these models is around 0.98, while the average prediction error is less than 10%. Fundamental period (T₁), total building height (Hₜ), and pseudospectral acceleration at T₁, denoted as Sₐ(T₁), are selected as the features to predict PSDR, while T₁, Hₜ, and PGA are the features selected to predict PFA. The EDP-targeted design has three steps: (i) for a given Hₜ value, the PSDR prediction model is used to identify a suitable T₁ that can achieve a desired PSDR target at the design intensity, (ii) a force-based design is then conducted iteratively to achieve the target T₁ by using an appropriate ductility factor and design drift limit, and (iii) based on the T₁ in the final design iteration, the PFA demand estimated by the PFA prediction models is used as a conservative input for the design of acceleration-sensitive non-structural elements. An equation to predict λ꜀ at the design stage is proposed for collapse risk-targeted seismic design of buildings. This equation comprises three principal components: reserve building strength, a proxy for effective structural stiffness, and reserve building deformation capacity. This equation is calibrated for the collapse risk-targeted design of BRBF buildings in New Zealand using results from 26 case-study BRBF buildings. The validity of this equation is demonstrated with three design verification examples designed to specific λ꜀ targets. Considering λ꜀ from hazard-consistent incremental dynamic analysis as the benchmark, the mean absolute percentage error in the design-stage prediction of λ꜀ of the verification buildings is approximately 10%.
In their everyday practice, social workers support those experiencing distress, poverty, oppression, and marginalisation in recovering from past and present crises and trauma. This expertise and knowledge is highly relevant in the aftermath of disasters, which disproportionately impact those on the margins of society. This research examines the experiences of social workers who responded to two major disaster events in Ōtautahi Christchurch, Aotearoa New Zealand: the Canterbury earthquakes of 2010 and 2011, and the Christchurch mosque attacks of 2019. This qualitative study was interpreted through a theoretical framework comprised of posttraumatic growth (PTG), ecological systems theory, the notion of ‘place’, and social capital. Data for this research was collected in two phases; individual interviews with 23 registered social workers who practised through both disaster sequences, and two focus groups which reviewed the findings of the interviews and contributed further reflections on their experiences. The data was analysed through a reflexive thematic analysis (RTA). Analysis of the data revealed three major themes from the individual interviews, and one overall theme from the focus groups. The first theme from the interviews explored participants’ feelings around the challenges associated with disaster practice and how these had enhanced their practice skills, expanded their knowledge, and aided in the development of new skills. The second theme investigated participants’ new understandings of trauma. This theme included a greater appreciation for the negative toll of trauma and how it can manifest, and the unexpected positive changes which can occur as a result of reflecting on traumatic experiences. The third theme from the individual interviews examined how participants felt their sense of resilience was connected to their experiences of support. Through the focus groups, participants contributed further data and knowledge. Participants in the focus groups identified and discussed principles that they felt were necessary for disaster practice, including being trauma attuned, culturally aware, and adaptable individually and organisationally to the changing needs of disaster. These findings have important implications for social work disaster practice and everyday work, both in Aotearoa New Zealand and internationally. The participants’ experiences and perspectives were analysed to develop a model for disaster practice.
The North Canterbury and Marlborough regions of Aotearoa | New Zealand were severely impacted by almost 30,000 landslides triggered during the 2016 Kaikōura Earthquake. Of these landslides approximately 200 dammed rivers. In the study area near Waiau, rupture of The Humps and Leader faults (and associated ground motions) initiated at least 42 co-seismic landslides. The Leader Landslide is the largest of these landslides, with an area of approximately 600,000 m2 and a volume of 6-8 million m3. The landslide buried approximately 980 m of active Leader River bed length and dammed the river. The dam produced four lakes, with two remaining today and two having been breached by partial landslide collapse and knickpoint migration in the year following the earthquake. As of 2025, the landslide dam has not been completely breached and Lake Rebekah remains. The Leader Landslide dam presents a unique opportunity to chart the evolution of the active riverbed pre- and post-earthquake, for up to 2 km downstream of Lake Rebekah. The river’s evolutionary timeline was observed using LiDAR, satellite aerial imagery, and drone surveys from 2001 to 2024 to develop maps and topographic difference models. Key timeframes for riverbed change events were also constrained with information and dated photography gathered from previous communications with the landowners at Woodchester Station, where the landslide is located. Finally, Schmidt Hammer testing of the Pliocene-Miocene Greta Siltstone Formation was conducted to investigate the role of bedrock strength on the rate of riverbed erosion. I present the history of evolution of the Leader River, pre- and post-earthquake, and consider factors impacting riverbed morphology changes. Despite the stability of Lake Rebekah, these data show that the position and morphology of the Leader River has changed significantly in response to the landslide, with the formation of two knickpoint waterfalls up to 14 m-high, four waterbodies, and diversion of the river around the landslide toe. Evolution of the river is characterised by longer periods of stasis (e.g., months to years) punctuated by rapid changes in riverbed morphology (e.g., hours to weeks) associated with incision and aggradation. In particular, the knickpoints migrated upstream at variable spatial and temporal rates. Factors controlling the rates of processes include; rain-storm events, partial lake outburst flooding, spatial changes in Pliocene-Miocene siltstone bed induration and landowner intervention to stabilise the landslide dam. An overarching conclusion of this thesis is that landforms can develop rapidly (i.e., hours to weeks) and in the absence of historical accounts, could be interpreted to have formed over hundreds to thousands of years.
