CORDIS
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CORDIS

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Development and application of Novel, Integrated Tools for monitoring and managing Catchments

Project information

Grant agreement ID: 689341

Status

Closed project

  • Start date

    1 June 2016

  • End date

    31 January 2020

Funded under:

H2020-EU.3.5.4.

  • Overall budget:

    € 8 770 935

  • EU contribution

    € 7 570 335

Coordinated by:

BRUNEL UNIVERSITY LONDON

English EN

User-friendly boats seek out water pollutants in European rivers and lakes

Billions are spent on testing water quality. Current water quality monitoring approaches lack spatial and temporal resolution, which means pollution is not sufficiently detected or addressed.

Digital Economy
Industrial Technologies
Food and Natural Resources
© Tymos Lytras

Water quality is a crucial indicator of the health of river ecosystems, yet a large number of European water bodies do not meet a ‘good ecological status’. Reliable, real-time water quality data from sensors serves as an evidence base to enable effective tackling of pollution at a catchment-wide basis. The EU-funded INTCATCH project exploited advances in monitoring technology to develop cost-effective, user-friendly, automated ‘smart’ boats equipped with multi-parameter sensors. The technology is not built from scratch, but rather uses commercially available boats with low-cost sensors.

Dealing with water in a smart way

Conventional water quality monitoring strategies usually involve an officer going to site and sending a sample to a lab, where tests are run with the results available two or three weeks later. This approach can help map local pollution but has limited impact in improving water quality across a larger area. “INTCATCH’s hi-tech approach takes floating ‘smart labs’ out to rivers and lakes to test water quality, making it easier to monitor and trace pollution,” notes project coordinator Mark Scrimshaw. “Rather than relying on experts, ordinary citizens will be able to use the boats to collect evidence themselves and find out just how healthy their local river is,” adds Scrimshaw. The autonomous and radio-controlled boats (controlled by a handheld device) provide better access and coverage of water bodies. Innovative sensors enable mobile, real-time water quality monitoring and mapping – for example they detect Escherichia coli and pesticides. Next-generation DNA test kits provide fast and accurate analysis of the genome of the bacteria in the water. All the evidence collected are then transferred to the cloud and can be processed by decision support software to help communities and authorities make decisions about when, where and how to best help the river.

Catching up with INTCATCH technology

Demonstration activities focused on analysing the health and quality of the strategic water reservoir Lake Yliki in Greece, surface waters in Berlin, urban rivers in London, and the river Ter in Spain. Algal blooms, suspended solids and turbidity in Lake Yliki are just some of the challenges that need to be addressed. The high urban runoff carrying pollutants such as oil, dirt, chemicals, directly to the urban rivers seriously harms water quality. Increased conductivity caused by surface mining activities adversely affects water quality in the river Ter. Other potential sources of pollution that affect catchments are wastewater from kitchen sinks and washing machines or even from industrial drainage erroneously connected to the surface water drain. These pollutants cause high concentrations of ammonia, phosphate and nitrate to build up in the rivers. The data generated on water quality will be stored in an online database that can be accessed by anyone using a web or mobile interface. People will also be able to query the database to improve their knowledge about the aquatic ecosystems in their vicinity. This knowledge base will prove invaluable to stakeholders in effective water management.

Keywords

INTCATCH, water quality, river, pollution, sensors, drone, radio-controlled boat, decision support software

Project information

Grant agreement ID: 689341

Status

Closed project

  • Start date

    1 June 2016

  • End date

    31 January 2020

Funded under:

H2020-EU.3.5.4.

  • Overall budget:

    € 8 770 935

  • EU contribution

    € 7 570 335

Coordinated by:

BRUNEL UNIVERSITY LONDON

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