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13 April 2023

Intelligent technology must help prevent a repeat of the floods of 2011 and 2013  

Denmark must prepare for more extreme weather in the future. By using machine learning and artificial intelligence, researchers will effectively be able to prevent floods.

In January 2023, Denmark experienced the wettest month ever recorded – attributed to climate change. In the future, there is a need to prepare for handling even larger amounts of rain and wastewater.

New research from a project at the National Centre for Digital Technology (DIREC) could help Denmark prepare for more extreme weather conditions. Researchers are working to improve the capabilities to understand and manage water in urban areas. The project is a collaboration between researchers from institutions such as Aalborg University, IT University of Copenhagen, HOFOR, and Aarhus Vand.

Currently, we do not fully exploit the potential of digital technologies when it comes to optimizing our water management. In the project, researchers will attempt to control the flow of rainwater in the wastewater system and reduce the risk of overflow and flooding. This is done by combining existing mathematical models of water movement with data-driven machine learning.

According to the researchers, it is possible to measure, control, and regulate water intelligently with a digital approach. Advanced machine learning can identify the best solution to guide rainwater and wastewater to the right places, especially during heavy rain and storm surges when water systems are pushed to their limits.

Machine learning gears the system for extreme weather

One of the project partners is HOFOR, the utility company for the Greater Copenhagen area. Project Manager Gitte Rosenkranz is involved in the project, which is still in its early stages.

– We want to avoid situations like in 2011 and 2013, where the sewage system was overloaded, and Copenhagen, in particular, was heavily affected by floods. During periods of intense and sudden rainfall, the system comes under extreme pressure, and it can be challenging to account for different scenarios. It requires advanced coordination, and that’s where machine learning and artificial intelligence come into play. Machine learning can help identify the best solution in the situation and, based on advanced calculations, ensure that rainwater and wastewater are directed to the right places, explains Gitte Rosenkranz.

An exciting project for all parties involved

– Ongoing research projects like this one can help place Denmark on the world map as a future leader in water technology, and the utility sector internationally is already gearing up systems for future more extreme weather situations, says Gitte Rosenkranz.

– The challenges we face are not going away, which is why the utility sector internationally is evolving.

The strength of the DIREC project is that it involves specialists from various fields – both IT experts and water management experts, according to Gitte Rosenkranz.

– It’s a huge strength to work across disciplines, and everyone simultaneously finds the project important, fun, and exciting.

Visit at HOFOR on September 22, 2022 with participants from AAU, ITU, DHI, Biofos and HOFOR


The rapidly growing use of machine learning techniques in cyber-physical systems leads to better solutions and products with improved adaptability, performance, efficiency, functionality, and user-friendliness. In the project, the water system is considered a cyber-physical system, consisting of a physical reality – the water itself – and the infrastructure monitored and controlled by connected software and hardware elements.

Together with external partners, Aarhus Vand, HOFOR, Grundfos, and Seluxit, researchers from AAU and ITU aim to develop methods and tools that can, for example, control the discharge of water in rainwater basins into watercourses using advanced machine learning.

Project participants:

Professor Kim Guldstrand Larsen, AU
Professor Thomas Dyhre Nielsen, AAU
Professor Andrzej Wasowski, ITU
Postdoc Martijn Goorden, AAU
PhD student Esther Hahyeon, AAU
PhD Student Mohsen Ghaffari, ITU
Associate Professor Martin Zimmermann, AAU
Assistant Professor Christian Schilling, AAU
Head of Analytics and AI Thomas Asger Hansen, Grundfos
CEO Daniel Lux, Seluxit
Chief Innovation Officer, Kasten Lumbye, Aarhus Vand
Project Manager Kristoffer Tønder Nielsen, Aarhus Vand
Research and Business Lead Malte Skovby Ahm, Aarhus Vand
Engineer Mathias Schandorff Arberg, Aarhus Vand
Project Manager Gitte Rosenkranz, HOFOR
Senior Specialist Lone Bo Jørgensen

Read more about the project