This article is part of our special report Can space technologies improve drinking water quality?.
Predictive management and process optimisation in water utilities mean less usage of chemicals, which results in a positive environmental footprint as well as less operational costs for the industry, an expert told EURACTIV.com.
Apostolos Tzimas, project coordinator of SPACE-O, an EU-funded project which aims to help water managers improve potable water operations, said that predictive water management also made it easier for the industry to implement water safety plans and build-up trust with consumers.
Funded by Horizon 2020, the SPACE-O project introduced predictive management into everyday decision-making of water professionals.
The project focuses on two levels. At the reservoir level, managers are able to get timely information about low-quality water possibility and mitigate its impact. At the users’ level, the project focused on drinking water.
It basically aspires to provide water professionals with water quality forecasts. For this reason, advanced space technologies are used to implement that, Tzimas said.
Through satellite imagery from Copernicus and advanced models, the researchers have created a water information system, which produces short-term forecasting (up to 10 days) about water quality and quantity in lakes and reservoirs.
“Coupled modelling tools, starting from hydrology and going down to hydrodynamic and ecological modelling into reservoirs, are forced with short-term weather forecasts, generating water quality forecasts; earth observations are used to improve the forecast capabilities of this service line,” he said.
The cost of inaction in water management
Tzimas said that providing operational analytics that combine past and current data with predictive simulations, helps water managers be informed about complex operational and business decisions.
Citing practical examples, Tzimas said in case of harmful algae blooms in a lake, water utilities could be forced to cut the water supply.
Water disruption in a small city of 100.000 people for one day, he said, can incur more than €300,000 in costs to consumers.
“This amount does not include the costs in the water utilities from loss of sales and reputational costs, not to mention possible costs incurred in tourism, fisheries, aquaculture, property values, livestock and public health,” he said.
“With the water quality forecasting services that SPACE-O delivers operationally, bulk water managers can at the least mitigate the impact of an algae bloom, by implementing predictive water management in the reservoir like water blending or lake water treatment ” Tzimas said.
Economic and environmental benefits
“At the utility level, SPACE-O employs machine learning models in order to optimise the chemical and energy nexus of the treatment process, without compromising drinking water quality.”
“Trained with historical operational datasets, these machine learning models provide a reliable way to evaluate alternative operating scenarios and, hence, indicate cost-saving opportunity windows,” he noted,
“We created tools that describe how a water treatment plant works with algorithms and by putting it in the forecasting mode, we can tell the operator earlier what the optimum chemicals’ dose should be, increasing his responsiveness, ” Tzimas noted.
“We tested it in two water treatment plants, and even in well-functioning plants, there is a potential for coagulants reduction of up to 10%, which means direct economic benefit and positive environmental footprint.
The coagulants help the solids in the water come close together and consequently become heavier and fall down.
“Water utilities can more efficiently build trust with consumers and have reputational gains. The utilities that use so advanced techniques and tools basically build up trust with their customers and claim leadership within the industry,” he added.