Can modelling be used to predict the movement of pathogens in coastal environments? A team from Bangor University worked with water and subsurface specialists Deltares and Exeter University to create a real-time risk alert system.

The River Camel in Cornwall is one of the three case studies in this project. The Camel rises on Bodmin Moor, and runs for 48km into the Celtic Sea. It has a catchment (the surrounding area where rainwater collects) of 413 km2, and the water flowing into the river suffers from wastewater pollution and agricultural run-off. The poor water quality significantly affects its thriving recreational and shellfishing industries.

What are we doing?

We want to be able to determine how pathogens in coastal environments are impacted by environmental factors, including climate change. To do this, the team is developing a modelling approach that can predict the risk of pathogen exposure.

As well as predicting future problems, the model will be combined with live data (such as weather and waste discharge rates) to create a public health real-time risk alert system.

We’re producing catchment-to-coast modelling for three case study areas, including the River Camel.

The aim? A risk mapping model that enables river users to actively manage the problems caused by pathogen pollution.

Timeline

Here’s what’s happening:

Why is this important?

The movement of bacteria and viruses in coastal environments is notoriously difficult to measure, but essential to know. Exciting recent advances in mathematical modelling and tech mean that we can now create effective prediction models.

There are two really innovative strands to this project. One, we’re combining the flow of both coastal and catchment water in one model, so we have a better idea of how bacteria and viruses move from inland sources to the coast.

Secondly, by combining the models with live data, we can create a real-time risk alert system, which will be invaluable for river users. We’re also linking to the latest climate predictions to enable more accurate forecasting. This can inform everything from modelling extreme weather events to looking at the impact of future housing development.