Prognostic modelling provides an efficient means to analyse the coastal environment and provide effective knowledge for long term urban planning. This paper outlines how the use of SWAN and Xbeach numerical models within the ESRI ArcGIS interface can simulate geomorphological evolution through hydrodynamic forcing for the Greater Christchurch coastal environment. This research followed the data integration techniques of Silva and Taborda (2012) and utilises their beach morphological modelling tool (BeachMM tool). The statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 were examined to determine whether these requirements are currently being complied with when applying the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013), and it would appear that it does not meet those requirements. This is because coastal hazard risk has not been thoroughly quantified by the installation of the Canterbury Earthquake Recovery Authority (CERA) residential red zone. However, the Christchurch City Council’s (CCC) flood management area does provide an extent to which managed coastal retreat is a real option. This research assessed the effectiveness of the prognostic models, forecasted a coastline for 100 years from now, and simulated the physical effects of extreme events such as storm surge given these future predictions. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon similar to the CCC’s flood management area. There are complex interactions at the Waimakariri River mouth with very high rates of accretion and erosion within a small spatial scale due to the river discharge. There is domination of the marine environment over the river system determined by the lack of generation of a distinct river delta, and river channel has not formed within the intertidal zone clearly. The Avon-Heathcote ebb tidal delta aggrades on the innner fan and erodes on the outer fan due to wave domination. The BeachMM tool facilitates the role of spatial and temporal analysis effectively and the efficiency of that performance is determined by the computational operating system.
Predictive modelling provides an efficient means to analyse the coastal environment and generate knowledge for long term urban planning. In this study, the numerical models SWAN and XBeach were incorporated into the ESRI ArcGIS interface by means of the BeachMMtool. This was applied to the Greater Christchurch coastal environment to simulate geomorphological evolution through hydrodynamic forcing. Simulations were performed using the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013) to determine whether the statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 are consistent with central, regional and district designations. Our results indicate that current land use zoning in Greater
Christchurch is not consistent with these predictions. This is because coastal hazard risk has not been thoroughly quantified during the process of installing the Canterbury Earthquake Recovery Authority residential red zone. However, the Christchurch City Council’s flood management area does provide an extent to which managed coastal retreat is a real option. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon.
Predictive modelling provides an efficient means to analyse the coastal environment and generate knowledge for long term urban planning. In this study, the numerical models SWAN and XBeach were incorporated into the ESRI ArcGIS interface by means of the BeachMMtool. This was applied to the Greater Christchurch coastal environment to simulate geomorphological evolution through hydrodynamic forcing. Simulations were performed using the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013) to determine whether the statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 are consistent with central, regional and district designations. Our results indicate that current land use zoning in Greater Christchurch is not consistent with these predictions. This is because coastal hazard risk has not been thoroughly quantified during the process of installing the Canterbury Earthquake Recovery Authority residential red zone. However, the Christchurch City Council’s flood management area does provide an extent to which managed coastal retreat is a real option. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon.
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.
