Highlights from the 19th International Computing & Control for the Water Industry Conference

Navigating the Water Futures

The 19th International Computing & Control for the Water Industry (CCWI) Conference, held this year at De Montfort University in Leicester, provided attendees with a thorough overview of the latest developments in the water industry. Covering diverse sessions ranging from design and modelling to digital transformation and water quality, the event attracted professionals and researchers eager to shape the future of water.

As PhD students representing the ERC Water-Futures project, our research revolves around the future transition of Water Distribution Systems. Hence, it perfectly fits this conference’s aim and gives us a fantastic opportunity to share the two years of advances in the project. Lydia, who is focusing on long-term planning, presented her work titled Reinforcement Learning for Adaptive Water Distribution Network Planning: Exploring its Feasibility and Potential. This exploratory research into alternative Machine Learning techniques for the optimization of water networks drew the attention of many and won the “Best Student Paper and Presentation” award. Dennis’s work on operation was showcased during his presentation titled “Operational considerations for the long-term design of Water Distribution Systems”. Konstantinos’s research focuses on the dynamics of biofilm in water distribution networks and his presentation “Towards a Digital Twin for expanding the capabilities of Water Distribution Networks: The case study of the TUBES experimental network

In this blog post, we explore our takeaways from CCWI and their significance in relation to our individual research efforts in the Water-Futures project.

Designing water distribution systems of the future

Planning the future of urban water networks effectively is a complex task that demands holistic approaches balancing short-term needs with long-term growth expectations. Comprehensive methods like staged optimization enable systematic planning but often require increased computational requirements.

One paradigm that holds the potential to address this challenge is the utilization of graph neural networks (GNNs). Researchers at CCWI have harnessed GNNs for a diverse set of problems, including state estimation (Zanfei et al.) and urban drainage metamodels (Garzon et al.). By incorporating inductive biases, such as the inherent graph structure of a water network, GNNs promise faster hydraulic simulations and enhanced transferability. These attributes become particularly significant when aiming to speed up simulations during the optimization of water network designs. Therefore, embracing GNNs could represent a significant step forward, simplifying processes and opening new possibilities in optimizing water infrastructure.

When it comes to navigating the extensive scenario space needed to address uncertainty in water network design, we were particularly intrigued by the presentation from Magini et al. Their robust multi-objective optimization model for designing water distribution networks under uncertainty, along with an approach to reduce the number of scenarios involved, offers a promising method for managing extensive future scenario sets.

Finally, as our field embraces digital transformation, it was inevitable that discussions around AI models and other cutting-edge technologies took center stage at CCWI. However, it’s crucial to acknowledge that in our quest to develop state-of-the-art solutions, we sometimes create approaches that prove to be overly complex for practitioners. One presentation that resonated with us for this very reason was the one by Oberascher et al., which introduced a simple and practical framework that effectively leveraged easily measurable variable and open-source data, showcasing the importance of prioritizing accessible solutions. Such initiatives truly strike a chord with us, underlining the importance of bridging the gap between innovation and practicality in the water industry.

Operation for design and design for operation

Regarding the optimal management of WDS, along with the design of the infrastructures, the operations and the control of the active elements (e.g., pumps and valves) play a significant role. In the specific session about operations, the research team from Technion (Haifa, Israel) has proved once again to be at the forefront of this field by testing a fascinating methodology for the robust optimization of the control decision variables. Adjustable robust optimization allows future control actions linked to the observed data through the optimization of a policy, and it provides more robust solutions when the realization of the uncertainty (water demand, in this case) differs from the expected value. The main takeaway from the session and for our project Water Futures is the renewed importance of the Linear Programming framework for optimizing the controllable elements, methodology used in the described work, and several others, such as the inspiring talk of Professor Ulanicki. Designing robust and flexible WDS from the point of view of operations is of the utmost importance for the next generation of urban water systems.

Water quality and biofilm challenges

For research on the intricate world of biofilm in water distribution networks, staying at the forefront of scientific advancements is paramount.

First, a team of experts from Queen’s University and the National Research Council in Canada unveiled a novel. They addressed the significant challenges of biofilm studies, emphasizing the microscopic nature of these formations and the complexity of factors influencing their growth. Their innovative approach involved using granular activated charcoal filters to accumulate microorganisms from local drinking water, followed by controlled pipe systems for biofilm cultivation. Quantifying biofilm growth with Adenosine-triphosphate (ATP) techniques, they showcased a versatile framework for researchers aiming to unravel the mysteries of drinking water biofilms. This approach resonated with both past KWR experience with ATP, as well as current Water Futures research in validating a new biofilm measurement technique.

Second, researchers from Technion Israel Institute of Technology and Eberhard Karl University of Tübingen introduced a systems biology approach to dissect the cause-and-effect dynamics of water quality fluctuations in distribution systems. They highlighted the limitations of traditional modeling and the need for a more sophisticated understanding of complex molecular interactions within distribution pipes. By adapting concepts from computational systems biology, they proposed a novel modeling approach that could revolutionize the study of water quality dynamics.

In pursuing biofilm research within water distribution networks, these presentations offer a treasure trove of insights and methodologies. From innovative experimental frameworks to cutting-edge modeling techniques and advanced water quality indices, these resources empower researchers to tackle the complexities of biofilm measurement and modeling with higher confidence and precision. By embracing the knowledge shared in these sessions, research in the Water Futures project is better positioned to contribute to the ever-evolving field of water quality management in distribution systems.


Attending a conference is always an inspiring experience. We found this to be true, especially at the 19th International CCWI Conference, and for this reason, we are already planning to participate in next year’s edition. All the talks attended provided us with incredible insights and countless sources of inspiration. Lydia’s award is an additional motivation for the whole team involved in the project to keep pushing the boundary of research, reminding us that there is always space for innovation and exciting results to discover. Next year’s edition will feature a new challenge: the Battle of the Network Forecast Demand. We aim to address it as a Water-Futures team collaborating with our partners, Bielefeld University, the University of Cyprus, and Athens Univ. of Economics and Business.