Groundwater modelling

ESR’s data scientists are helping to build a picture of how contaminants and pathogens survive and move through our groundwater systems and the impact this has on the quality and safety of the water we use.

Groundwater Drilling at Silverstream webcrop

Groundwater is one of Aotearoa New Zealand’s most valuable resources. It provides drinking water to 40% of the population, more than 30% of the water for the primary sector (such as farming and forestry), and a massive 80% of New Zealand’s springs, streams, and wetland baseflows.

At the same time, the impact of climate change, changing land use, and chemical pollutants are putting the safety and quality of our groundwater at risk. To build understanding of how contaminants move into and through aquifers, and how those contaminants are naturally filtered or bioremediated, ESR’s scientists carry out large scale field experiments and analyse the results using a combination of data science and numerical modelling.

Our groundwater modellers analyse pathogen, tracer, and nutrient experimental datasets alongside real-time groundwater sensor data from ESR’s experimental sites in Canterbury and sites across New Zealand. The team is also developing a set of visualisation tools to better demonstrate to our communities the outcomes of their work, how groundwater moves through aquifers, and how different contamination sources degrade the quality and safety of groundwater supplies and freshwater bodies.

Pathogen and nutrient movement in different groundwater systems

The team is designing encapsulated synthetic DNA to act as surrogate tracers that mimic and identify the pathways that microbes, harmful bacteria and contaminants take in aquifers. In one experiment, the DNA tracers will be simultaneously injected at several wells at ESR’s Canterbury testing site and their movement will be tracked with very intense sampling. The sampling results will be analysed numerically in 3D space and time. By mapping the movement of these synthetic tracers, the team will be able to better predict how real pathogens survive and how they’re transported through groundwater systems.

Merging Machine Learning and numerical tools

Regional councils know that carefully-mapped drinking well capture zones (the area around a drinking water well that contributes water – and potentially contaminants and pathogens - to the well) are essential to minimise public health risks and the economic impact on farmers. But building a picture of the complex geological structures under the ground is difficult. To address this, ESR scientists are developing efficient new methods to simulate well source protection zones, combining novel hybrid Deep Learning and numerical architectures.

Find out more about the expertise of some of our groundwater scientists