The Resilient Shorelines study at University of Canterbury (UC) is using the Avon Heathcote Estuary Ihutai to investigate ecosystem-based approaches to conservation planning and adaptation in response to environmental change. In particular, the study is using a novel opportunity to understand effects of the Canterbury earthquakes that may be similar to impacts of sea level rise. These result from topographic and bathymetry changes in and around the estuary and associated waterways (Beaven et al., 2012; Cochran et al., 2014) that have driven changes in hydrodynamics (Measures et al., 2011). Therefore the wider context for the work reported here is to develop methodologies for modelling the impacts of sea level rise on estuaries and coastal river mouths using the Avon-Heathcote Estuary/Ihutai as a case study. Initial objectives have included establishing the magnitude of earthquake-induced changes. Subsequent steps will include establishing the relationships between strong physical drivers such as water levels and salinity, and the spatial pattern of estuarine ecosystems. There is particular focus on understanding salinity changes in the upper estuarine ecosystem in the vicinity of the freshwater-saltwater interface. In these areas, species, habitats and ecosystems that are adapted to brackish conditions are expected to migrate in response to the inland penetration of salt water under sea level rise. An example is the location of īnanga spawning habitat that is associated with the inland extent of salt water intrusion on spring tides (Taylor, 2002). It is expected to be strongly affected by sea level rise. To facilitate the development of ecosystem-based scenario models for sea level rise, a salinity model with resolution at ecological meaningful scales was required. An existing fine scale hydrodynamic model was available using Delft3D software (Deltares, 2012) that had been developed for ECan and MBIE following the earthquakes (Measures & Bind, 2013). However, it had not been calibrated for salinity. A collaborative project was designed between UC and NIWA to calibrate the model and develop a scenario modelling approach for sea level rise at a level of resolution sufficient for understanding sea level rise impacts on īnanga (whitebait) spawning habitat. The project was allocated funding from Brian Mason Scientific and Technical Trust and commenced in late 2015. The purpose of this report is to provide a description of the model development process and an illustration of model outputs from an initial set of modelled scenarios for sea level rise.
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.
