Many different elements contribute to coastal change, from polar ice sheet melt to erosion, from vertical land movement to sedimentation, from changes in wave formation to earthquakes. All of these have different probabilities and effects. We aim to understand the combination and inter-reaction of these elements to better identify and assess coastal hazards as they evolve under changing sea level.
To do this we will establish and implement a framework to incorporate projections of coastal change into a statistical network modelling framework.
Generate a national map of total water level under the range of sea-level rise projections
Using the data generated in this project, we will use a parametric approach to project future total water levels (sea-level rise + storm surge + tide + wave contributions) around the Aotearoa New Zealand coastline. Our approach will account for uncertainties in the value of the beach slope using a Bayesian approach and calculations will be made available to the public and to users through our visualisation tools. This dataset will provide critical information on where and when flooding will impact infrastructure and properties and will help implementation of adaptation measures.
Model groundwater inundation in response to SLR projections nationally
Develop a national scale forecasting model that provides estimates of spatial and temporal aspects of groundwater changes that may lead to inundation in response to SLR projections. Groundwater modelling science will be extended to characterise groundwater level rise, at a national scale, in the context of long term and rapid vertical land movement. This will provide forecasts of the rate and magnitude of groundwater rise across the coastal areas of New Zealand to facilitate a comprehensive assessment of national scale risks to existing land use under SLR projections. We will leverage outputs from three MBIE funded studies that focus on SLR:
- initial probabilistic explorations of the spatial variations in groundwater inundation risks in South Dunedin (NZ SeaRise)
- long term equilibrium modelling of salination and coastal squeeze (Future Coasts Aoteoroa)
- the GNS National Groundwater Age model developed in Te Whakaheke O Te Wai.
Groundwater hazard evolution and the efficacy of mitigation options at a local scale in the context of SLR projections
We will evaluate groundwater inundation risks in areas where groundwater hazards occur at or in proximity to the coast. We will develop rapid downscaling tools to build groundwater models that allow localised hazards to be identified at a scale and resolution required to process data and evaluate local scale risks and to explore mitigation scenarios. Groundwater modelling science will be extended to provide rapid and detailed support for risk-based decision making for groundwater hazards of national concern. We will focus on at least one detailed case study, including an assessment of the risk of groundwater inundation of the hazardous waste buried at the Tiwai point aluminium smelter at Bluff.
Utilise statistical models (BN’s) to evaluate evolving coastal hazards at regional scale
We will use a Bayesian networks to integrate and evaluate multiple hazards (coastal inundation, groundwater inundation, and landslides) as they evolve through time. We will work with the datasets generated through the other research aims and include structured experts and mātauranga Māori. We are still finalising our case studies.
Our Team
Annemarie Christophersen, Earth Sciences New Zealand (formally GNS Science), is an expert in Bayesian Networks and expert elicitation. She will lead the hazard and risk assessment case studies with support from Liz Keller, Earth Sciences New Zealand (formally GNS Science), and early career research from Shannon Bengtson, Earth Sciences New Zealand (formally GNS Science). Catherine Moore and Wes Kitlasten, Earth Sciences New Zealand (formally GNS Science), are world-class groundwater modellers. Wes Kitlasten is developing the national groundwater model. Case studies will be coordinated by Richard Topham (Waka Kotahi), Jenny Christie (DoC), and Janet Hodgetts (Murihiku Regeneration).