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A novel approach to water quality monitoring

When species of naturally occurring algae multiply and appear in high numbers, often due to high nutrient levels in the water, they can develop into large blooms that are actually visible from space. Some species of algae bloom (approximately 2%) can cause negative impacts to other organisms through the production of natural toxins, and these are known as ‘Harmful Algal Blooms’ (HABs). HABs can be a risk to shellfish farms as they can contaminate shellfish and decrease the water quality.

ShellEye will extend the range of HAB species that can be detected from satellite data, specifically those species that can become HABs in UK coastal waters and impact shellfish farm water quality. This will be achieved through statistical analysis of historical satellite ocean colour data of UK coastal areas, at times when bloom events were known to have occurred, in combination with data from local monitoring. The satellite detection of HABs is supported by ShellEye's biotoxin model, which has been developed to help forecast times of increased risk of microbiological events, for example, from Escherichia coli.

As the project undertakes phase, it will also: expand the target regions to include more monitorable sites; enhance further the precision of near-coast satellite monitoring; increase the capability to include finfish and lobsters, and produce long-term HAB risk maps.

ShellEye will future proof these approaches by ensuring the developed methods can be exploited by the advanced capabilities of new satellite sensors that will be launched throughout the long-term EU Copernicus monitoring programme.

An early warning

Currents and tides can play a significant role in water quality changes, by transporting toxins and HABs through the sea. In addition, heavy rainfall and storm surges can also cause increased levels of pollutants and nutrients being transferred from the land to the sea, known as land runoff.

Combining meteorological data with satellite analysis and modelled outputs will allow ShellEye to understand how and when non-favourable environmental conditions will impact a location. This knowledge will be used to develop mechanisms and tools that can predict when a shellfish farm may be affected as well as informing farmers of the local conditions relevant to them and the likelihood of it harming their crop.