On 22 February 2011，a magnitude Mw 6.3 earthquake occurred with an epicenter located near Lyttelton at about 10km from Christchurch in Canterbury region on the South Island of New Zealand (Figure 1). Since this earthquake occurred in the midst of the aftershock activity which had continued since the 4 September 2010 Darfield Earthquake occurrence, it was considered to be an aftershock of the initial earthquake. Because of the short distance to the city and the shallower depth of the epicenter, this earthquake caused more significant damage to pipelines, traffic facilities, residential houses/properties and multi-story buildings in the central business district than the September 2010 Darfield Earthquake in spite of its smaller earthquake magnitude. Unfortunately, this earthquake resulted in significant number of casualties due to the collapse of multi-story buildings and unreinforced masonry structures in the city center of Christchurch. As of 4 April, 172 casualties were reported and the final death toll is expected to be 181. While it is extremely regrettable that Christchurch suffered a terrible number of victims, civil and geotechnical engineers have this hard-to-find opportunity to learn the response of real ground from two gigantic earthquakes which occurred in less than six months from each other. From geotechnical engineering point of view, it is interesting to discuss the widespread liquefaction in natural sediments, repeated liquefaction within short period and further damage to earth structures which have been damaged in the previous earthquake. Following the earthquake, an intensive geotechnical reconnaissance was conducted to capture evidence and perishable data from this event. The team included the following members: Misko Cubrinovski (University of Canterbury, NZ, Team Leader), Susumu Yasuda (Tokyo Denki University, Japan, JGS Team Leader), Rolando Orense (University of Auckland, NZ), Kohji Tokimatsu (Tokyo Institute of Technology, Japan), Ryosuke Uzuoka (Tokushima University, Japan), Takashi Kiyota (University of Tokyo, Japan), Yasuyo Hosono (Toyohashi University of Technology, Japan) and Suguru Yamada (University of Tokyo, Japan).
The extent of liquefaction in the eastern suburbs of Christchurch (Aranui, Bexley, Avonside, Avonhead and Dallington) from the February 22 2011 Earthquake resulted in extensive damage to in-ground waste water pipe systems. This caused a huge demand for portable toilets (or port-a-loos) and companies were importing them from outside Canterbury and in some instances from Australia. However, because they were deemed “assets of importance” under legislation, their allocation had to be coordinated by Civil Defence and Emergency Management (CDEM). Consequently, companies supplying them had to ignore requests from residents, businesses and rest homes; and commitments to large events outside of the city such as the Hamilton 400 V8 Supercars and the Pasifika Festival in Auckland were impacted. Frustrations started to show as neighbourhoods questioned the equity of the port-a-loos distribution. The Prime Minister was reported as reassuring citizens in the eastern suburbs in the first week of March that1 “a report about the distribution of port-a-loos and chemical toilets shows allocation has been fair. Key said he has asked Civil Defence about the distribution process and where the toilets been sent. He said there aren’t enough for the scale of the event but that is quickly being rectified and the need for toilets is being reassessed all the time.” Nonetheless, there still remained a deep sense of frustration and exclusion over the equity of the port-a-loos distribution. This study took the simple approach of mapping where those port-a-loos were on 11-12 March for several areas in the eastern suburbs and this suggested that their distribution was not equitable and was not well done. It reviews the predictive tools available for estimating damage to waste water pipes and asks the question could this situation have been better planned so that pot-a-loo locations could have been better prioritised? And finally it reviews the integral roles of communication and monitoring as part of disaster management strategy. The impression from this study is that other New Zealand urban centres could or would also be at risk and that work is need to developed more rational management approaches for disaster planning.
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.
