Unreinforced masonry (URM) structures comprise a majority of the global built heritage. The masonry heritage of New Zealand is comparatively younger to its European counterparts. In a country facing frequent earthquakes, the URM buildings are prone to extensive damage and collapse. The Canterbury earthquake sequence proved the same, causing damage to over _% buildings. The ability to assess the severity of building damage is essential for emergency response and recovery. Following the Canterbury earthquakes, the damaged buildings were categorized into various damage states using the EMS-98 scale. This article investigates machine learning techniques such as k-nearest neighbors, decision trees, and random forests, to rapidly assess earthquake-induced building damage. The damage data from the Canterbury earthquake sequence is used to obtain the forecast model, and the performance of each machine learning technique is evaluated using the remaining (test) data. On getting a high accuracy the model is then run for building database collected for Dunedin to predict expected damage during the rupture of the Akatore fault.
Since the early 1980s seismic hazard assessment in New Zealand has been based on Probabilistic Seismic Hazard Analysis (PSHA). The most recent version of the New Zealand National Seismic Hazard Model, a PSHA model, was published by Stirling et al, in 2012. This model follows standard PSHA principals and combines a nation-wide model of active faults with a gridded point-source model based on the earthquake catalogue since 1840. These models are coupled with the ground-motion prediction equation of McVerry et al (2006). Additionally, we have developed a time-dependent clustering-based PSHA model for the Canterbury region (Gerstenberger et al, 2014) in response to the Canterbury earthquake sequence. We are now in the process of revising that national model. In this process we are investigating several of the fundamental assumptions in traditional PSHA and in how we modelled hazard in the past. For this project, we have three main focuses: 1) how do we design an optimal combination of multiple sources of information to produce the best forecast of earthquake rates in the next 50 years: can we improve upon a simple hybrid of fault sources and background sources, and can we better handle the uncertainties in the data and models (e.g., fault segmentation, frequency-magnitude distributions, time-dependence & clustering, low strain-rate areas, and subduction zone modelling)? 2) developing revised and new ground-motion predictions models including better capturing of epistemic uncertainty – a key focus in this work is developing a new strong ground motion catalogue for model development; and 3) how can we best quantify if changes we have made in our modelling are truly improvements? Throughout this process we are working toward incorporating numerical modelling results from physics based synthetic seismicity and ground-motion models.
Geologic phenomena produced by earthquake shaking, including rockfalls and liquefaction features, provide important information on the intensity and spatiotemporal distribution of earthquake ground motions. The study of rockfall and liquefaction features produced in contemporary well- instrumented earthquakes increases our knowledge of how natural and anthropogenic environments respond to earthquakes and improves our ability to deduce seismologic information from analogous pre-contemporary (paleo-) geologic features. The study of contemporary and paleo- rockfall and liquefaction features enables improved forecasting of environmental responses to future earthquakes. In this thesis I utilize a combination of field and imagery-based mapping, trenching, stratigraphy, and numerical dating techniques to understand the nature and timing of rockfalls (and hillslope sedimentation) and liquefaction in the eastern South Island of New Zealand, and to examine the influence that anthropogenic activity has had on the geologic expressions of earthquake phenomena. At Rapaki (Banks Peninsula, NZ), field and imagery-based mapping, statistical analysis and numerical modeling was conducted on rockfall boulders triggered by the fatal 2011 Christchurch earthquakes (n=285) and compared with newly identified prehistoric (Holocene and Pleistocene) boulders (n=1049) deposited on the same hillslope. A significant population of modern boulders (n=26) travelled farther downslope (>150 m) than their most-travelled prehistoric counterparts, causing extensive damage to residential dwellings at the foot of the hillslope. Replication of prehistoric boulder distributions using 3-dimensional rigid body numerical models requires the application of a drag-coefficient, attributed to moderate to dense slope vegetation, to account for their spatial distribution. Radiocarbon dating provides evidence for 17th to early 20th century deforestation at the study site during Polynesian and European colonization and after emplacement of prehistoric rockfalls. Anthropocene deforestation enabled modern rockfalls to exceed the limits of their prehistoric predecessors, highlighting a shift in the geologic expression of rockfalls due to anthropogenic activity. Optical and radiocarbon dating of loessic hillslope sediments in New Zealand’s South Island is used to constrain the timing of prehistoric rockfalls and associated seismic events, and quantify spatial and temporal patterns of hillslope sedimentation including responses to seismic and anthropogenic forcing. Luminescence ages from loessic sediments constrain timing of boulder emplacement to between ~3.0 and ~12.5 ka, well before the arrival of Polynesians (ca AD 1280) and Europeans (ca AD 1800) in New Zealand, and suggest loess accumulation was continuing at the study site until 12-13 ka. Large (>5 m3) prehistoric rockfall boulders preserve an important record of Holocene hillslope sedimentation by creating local traps for sediment aggradation and upbuilding soil formation. Sediment accumulation rates increased considerably (>~10 factor increase) following human arrival and associated anthropogenic burning of hillslope vegetation. New numerical ages are presented to place the evolution of loess-mantled hillslopes in New Zealand’s South Island into a longer temporal framework and highlight the roles of earthquakes and humans on hillslope surface process. Extensive field mapping and characterization for 1733 individual prehistoric rockfall boulders was conducted at Rapaki and another Banks Peninsula site, Purau, to understand their origin, frequency, and spatial and volumetric distributions. Boulder characteristics and distributions were compared to 421 boulders deposited at the same sites during the 2010-2011 Canterbury earthquake sequence. Prehistoric boulders at Rapaki and Purau are comprised of two dominant lithofacies types: volcanic breccia and massive (coherent) lava basalt. Volcanic breccia boulders are found in greatest abundance (64-73% of total mapped rockfall) and volume (~90-96% of total rockfall) at both locations and exclusively comprise the largest boulders with the longest runout distances that pose the greatest hazard to life and property. This study highlights the primary influence that volcanic lithofacies architecture has on rockfall hazard. The influence of anthropogenic modifications on the surface and subsurface geologic expression of contemporary liquefaction created during the 2010-2011 Canterbury earthquake sequence (CES) in eastern Christchurch is examined. Trench observations indicate that anthropogenic fill layer boundaries and the composition/texture of discretely placed fill layers play an important role in absorbing fluidized sand/silt and controlling the subsurface architecture of preserved liquefaction features. Surface liquefaction morphologies (i.e. sand blows and linear sand blow arrays) display alignment with existing utility lines and utility excavations (and perforated pipes) provided conduits for liquefaction ejecta during the CES. No evidence of pre-CES liquefaction was identified within the anthropogenic fill layers or underlying native sediment. Radiocarbon dating of charcoal within the youngest native sediment suggests liquefaction has not occurred at the study site for at least the past 750-800 years. The importance of systematically examining the impact of buried infrastructure on channelizing and influencing surface and subsurface liquefaction morphologies is demonstrated. This thesis highlights the importance of using a multi-technique approach for understanding prehistoric and contemporary earthquake phenomena and emphasizes the critical role that humans play in shaping the geologic record and Earth’s surface processes.
The research is funded by Callaghan Innovation (grant number MAIN1901/PROP-69059-FELLOW-MAIN) and the Ministry of Transport New Zealand in partnership with Mainfreight Limited. Need – The freight industry is facing challenges related to climate change, including natural hazards and carbon emissions. These challenges impact the efficiency of freight networks, increase costs, and negatively affect delivery times. To address these challenges, freight logistics modelling should consider multiple variables, such as natural hazards, sustainability, and emission reduction strategies. Freight operations are complex, involving various factors that contribute to randomness, such as the volume of freight being transported, the location of customers, and truck routes. Conventional methods have limitations in simulating a large number of variables. Hence, there is a need to develop a method that can incorporate multiple variables and support freight sustainable development. Method - A minimal viable model (MVM) method was proposed to elicit tacit information from industrial clients for building a minimally sufficient simulation model at the early modelling stages. The discrete-event simulation (DES) method was applied using Arena® software to create simulation models for the Auckland and Christchurch corridor, including regional pick-up and delivery (PUD) models, Christchurch city delivery models, and linehaul models. Stochastic variables in freight operations such as consignment attributes, customer locations, and truck routes were incorporated in the simulation. The geographic information system (GIS) software ArcGIS Pro® was used to identify and analyse industrial data. The results obtained from the GIS software were applied to create DES models. Life cycle assessment (LCA) models were developed for both diesel and battery electric (BE) trucks to compare their life cycle greenhouse gas (GHG) emissions and total cost of ownership (TCO) and support GHG emissions reduction. The line-haul model also included natural hazards in several scenarios, and the simulation was used to forecast the stock level of Auckland and Christchurch depots in response to each corresponding scenario. Results – DES is a powerful technique that can be employed to simulate and evaluate freight operations that exhibit high levels of variability, such as regional pickup and delivery (PUD) and linehaul. Through DES, it becomes possible to analyse multiple factors within freight operations, including transportation modes, routes, scheduling, and processing times, thereby offering valuable insights into the performance, efficiency, and reliability of the system. In addition, GIS is a useful tool for analysing and visualizing spatial data in freight operations. This is exemplified by their ability to simulate the travelling salesman problem (TSP) and conduct cluster analysis. Consequently, the integration of GIS into DES modelling is essential for improving the accuracy and reliability of freight operations analysis. The outcomes of the simulation were utilised to evaluate the ecological impact of freight transport by performing emission calculations and generating low-carbon scenarios to identify approaches for reducing the carbon footprint. LCA models were developed based on simulation results. Results showed that battery-electric trucks (BE) produced more greenhouse gas (GHG) emissions in the cradle phase due to battery manufacturing but substantially less GHG emissions in the use phase because of New Zealand's mostly renewable energy sources. While the transition to BE could significantly reduce emissions, the financial aspect is not compelling, as the total cost of ownership (TCO) for the BE truck was about the same for ten years, despite a higher capital investment for the BE. Moreover, external incentives are necessary to justify a shift to BE trucks. By using simulation methods, the effectiveness of response plans for natural hazards can be evaluated, and the system's vulnerabilities can be identified and mitigated to minimize the risk of disruption. Simulation models can also be utilized to simulate adaptation plans to enhance the system's resilience to natural disasters. Novel contributions – The study employed a combination of DES and GIS methods to incorporate a large number of stochastic variables and driver’s decisions into freight logistics modelling. Various realistic operational scenarios were simulated, including customer clustering and PUD truck allocation. This showed that complex pickup and delivery routes with high daily variability can be represented using a model of roads and intersections. Geographic regions of high customer density, along with high daily variability could be represented by a two-tier architecture. The method could also identify delivery runs for a whole city, which has potential usefulness in market expansion to new territories. In addition, a model was developed to address carbon emissions and total cost of ownership of battery electric trucks. This showed that the transition was not straightforward because the economics were not compelling, and that policy interventions – a variety were suggested - could be necessary to encourage the transition to decarbonised freight transport. A model was developed to represent the effect of natural disasters – such as earthquake and climate change – on road travel and detour times in the line haul freight context for New Zealand. From this it was possible to predict the effects on stock levels for a variety of disruption scenarios (ferry interruption, road detours). Results indicated that some centres rather than others may face higher pressure and longer-term disturbance after the disaster subsided. Remedies including coastal shipping were modelled and shown to have the potential to limit the adverse effects. A philosophical contribution was the development of a methodology to adapt the agile method into the modelling process. This has the potential to improve the clarification of client objectives and the validity of the resulting model.
