EU-funded project harnesses potential of data to improve water management

Europe’s waterways are under immense pressures, ranging from agricultural and industrial activities to the challenges of increased urbanisation. Digital technologies are acknowledged for their ability to help improve water management. However, a lack of business cases and tangible evidence of their benefits, combined with underutilised digital solutions, hinders their uptake.

“In this context, the EU-funded DWC project aimed to boost the integrated management of water systems in five major European cities – Berlin, Milan, Copenhagen, Paris and Sofia – by leveraging the potential of data and smart digital technologies,” explains Nicolas Caradot, project coordinator. Led by Kompetenzzentrum Wasser Berlin gGmbH, a research centre specialising in urban water systems, 24 partners from 10 countries have developed and demonstrated the benefits of a panel of innovative digital solutions to address major water-related challenges.

Real-time water quality monitoring and early warning

These solutions include new technologies for fully automated water quality monitoring. The ALERT system, for instance, is an accurate sensor for assessing public health risk linked to contact with potentially contaminated water. “It halves response times and minimises handling and transportation while providing a similar accuracy to the laboratory,” outlines Caradot.

The project has also brought SWIM:AI to market, a machine learning early warning system for bathing water management. It can predict days of insufficient water quality with up to 95 % accuracy.

Sewer monitoring and wastewater treatment plant (WWTP) management

A new low-cost monitoring solution for combined sewer outflow was also developed. It allows utilities to precisely monitor a vast number of combined sewer control outlets.

Additionally, DWC highlighted the relevance of sensors to tackle illicit connections – incorrect connections between the sanitary sewage system and the storm sewer system. “The new DWC methodology has proven to be 10 times more efficient and cost effective than conventional visual inspection to narrow down hotspots of illicit connections in the network,” confirms Caradot.

DWC further highlighted the relevance of machine learning for sewer flow modelling. “The potential of sensors and machine learning has been embedded in a new real-time control solution for the integrated management of sewer networks and WWTP. About 25 % of sewer bypass volume and 20 % of nitrogen emissions can be saved,” outlines Caradot.

Another digital solution that was developed is a wastewater treatment tool. It can support the reuse of treated wastewater for agricultural irrigation in real-time within the framework of risk assessment and management provided by Regulation (EU) No 741/2020.

To foster water reuse from the farming side, DWC also developed a new drone solution and a web-based application to manage demand for treated wastewater for agricultural irrigation.

Interoperability and cybersecurity

To achieve semantic interoperability between data, model and systems, DWC proposed new ontology extensions to the European Telecommunications Standards Institute to consider DWC requirements and to contribute to the development of global and widely applied ontologies. “We also enhanced the FIWARE ecosystem by providing semantic interoperability software as a standalone component and compatible solutions,” concludes Caradot.

Regarding cybersecurity, DWC built on the results of the H2020 project STOP-IT, which focused on increasing cyber and physical protection of the water sector.

Source: CORDIS