ITG and Aqualia visit Moaña demosite to update the latest advancements and plan next steps

ITG and Aqualia visit Moaña demosite to update the latest advancements and plan next steps

On March 19, 2024, AQUALIA and ITG, partners of LIFE RESEAU, had a fruitful and collaborative visit at the pilot site in Moaña. It served to showcase the project’s steady progress towards achieving two key objectives: enhancing the sewer network intelligence through the strategic installation of sensors throughout the infrastructure and the full implementation of the retrofitting solution within the wastewater treatment plant (WWTP)


The power of data: building simulation models

Exploration began at Moaña’s wastewater network, the core of its sewer system which collects the water to be finally treated at the WWTP. Here, partners reviewed and discussed about the strategically placed sensors within manholes and pumping stations, which gather real-time data on parameters such as wastewater flow, level, pH or electric conductivity.

This data is being crucial for building a digital model which will allow to simulate the entire network performance under different conditions such as rainfall episodes. This model will help to monitor network behaviour, identify potential bottlenecks or predict overflows, amongst other features. The project is using numerical models, AI models and both combined (hybrid) to create a comprehensive and dynamic model of the wastewater system.


Transforming the WWTP of Moaña

During the tour, partners also visited the retrofitting works that are underway to enhance the plant’s treatment capacity. Upgrading the existing treatment processes using Advanced Biofilm Reactors will ensure effective wastewater treatment while preventing environmental pollution due to overflows during heavy precipitation events.

The Spanish demosite exemplifies the potential that RESEAU holds for the wastewater management in areas affected by heavy precipitation episodes by joining the advantages of retrofitting solutions, sensors and advanced modelling.