Water certainty in an uncertain future: The partners in the ERC Water Futures convene to develop future-proof, flexible and adaptive water solutions

To provide an update on a six-year, €10 million European Research Council (ERC) funded project, representatives from the UK, the Netherlands, Germany, Greece, and Cyprus met at the KIOS Research and Innovation Centre of Excellence at the University of Cyprus.

The ‘Smart Water Futures: Designing the Next Generation of Urban Drinking Water Systems’ team combines leading experience in water science, systems and control theory, economics and decision science, and machine learning.

By the end of this year, a total of 12 PhD students and 14 YY postdoctoral researchers will be working on the Smart Water Futures development.

“The future is unknown – we are talking about deep uncertainty. We are seeking robust solutions that perform well over many unexpected futures, not just optimal plan designs for a single future,” said Professor Dragan Savić, CEO of KWR Water Research Institute (KWR), the Netherlands and Professor of Hydroinformatics at the University of Exeter, UK.

Water Futures scope: four themes

Smart Water Futures is focusing on four interlinked synergistic themes across water distribution systems. Research is underway on the first theme involving decision-support tools for adaptive staged design, assessment and control of biofilms in networks, as well as the role of control in adaptive design.

A second theme aims to develop the theory and application of monitoring and control in urban water distribution systems.

“As smart water systems are developed, the number of sensors will continue to increase related to hydraulics, water quality and in the future, security,” said Professor Marios Polycarpou, Director of the KIOS Research and Innovation Center of Excellence and Professor of Electrical and Computer Engineering at the University of Cyprus.

Ongoing research includes interoperable event diagnosis in water distribution networks, smart water networks as cyber-physical-social systems and real-time water-quality control considering input time-delay uncertainty.

“One of our aims is to provide the framework to help automate water systems,” added Professor Polycarpou. “Networks in the future will provide real-time recommendations and decisions to operators and policymakers.”

The third theme addresses explainable and unbiased machine learning to support robust decision-making by data-driven technologies.

“One of our aims is to help better detect anomalies in water systems using AI and provide efficient data-driven decisions,” said Professor Barbara Hammer, Machine Learning Group at Bielefeld University, Germany.

The fourth theme focuses on the economics and human decision making including behavioural considerations.

Professor Phoebe Koundouri, Professor of Economics at the Athens University of Economics and Business, Greece, said: “Looking into scenario generation and decision making for the development of urban water systems under conditions of deep uncertainty, we are researching managers’ and consumers’ behavioural preferences to integrate them in the relevant optimisation models.”

Water Futures outcomes

Research conducted in Water-Futures will lead to the creation of new scientific theories and frameworks for modelling, monitoring, control, planning, investment and policy making for urban water drinking systems.

The European project has five main objectives:

  • Transitioning of urban water systems
  • Water monitoring & evolvable control
  • Learning for decision making
  • Rationality & eudaimonia
  • Integration & validation.

About Smart Water Futures

The Water-Futures project aims to develop a theoretical basis for designing smart water systems, which can provide a framework for the allocation and development decisions on drinking water infrastructure systems. The project has received funding from the ERC under grant number: 951424. The framework will integrate real-time monitoring and control with long-term robustness and flexibility, incorporating economic, social, ethical and environmental considerations for the sustainable transitioning of urban water systems. The project partners include water science, systems and control theory, economics and decision science, and machine learning methodologies to create an open-source research toolbox. The results will be applied to three case studies representing different types of urban water systems. For more information, please visit: