As part of the joint research project "InSchuKa4.0 - Combined infrastructure and environmental protection through AI-based sewer network management", a consortium of six partners, including the Institute for Water and Energy Management at Hof University of Applied Sciences (iwe), aims to make the sewer network flexible, resilient and efficient for extreme weather conditions. The project, which is funded by the Federal Ministry of Education and Research (BMBF), started in February 2022 and will run for three years.

Climate change presents society in general and water management in particular with enormous challenges. Floods or inundations caused by heavy rainfall are occurring more and more frequently in Germany and often cause major damage to people and the environment, for example due to the uncontrolled discharge of untreated wastewater into watercourses when sewers are full. On the other hand, more dry periods are also to be expected in the future. For the operators of combined sewers, longer periods of drought can have serious negative consequences for the operation of the network. One of the most important aspects is sediment removal, which is more difficult during prolonged drought and the associated lower flow due to less water than during regular rainfall, which takes over part of the regular sediment removal in the sewer. Precipitation-related flow fluctuations have a far greater influence on sewer deposits than, for example, structural boundary conditions such as gradient or pipe material. Despite high expenditure on manual flushing, unwanted deposits and the associated negative effects such as unpleasant odours occur time and again. In addition, if a heavy rainfall event occurs immediately after a long dry period, a sewer system fills up within a very short time and the existing deposits enter the waterways untreated with the excess water from the sewer system.

Adapting the water industry to these effects of climate change and a realistic path to climate neutrality are therefore issues of crucial importance.

The location and timing of extreme weather events have so far been difficult to predict. Wastewater network operators can only counter these with dynamic and flexible solutions. This is where "InSchuKa4.0" comes in. The aim is to develop a sewer management solution based on artificial intelligence that utilises innovative sewer sensors and state-of-the-art sewer equipment and incorporates historical and predictive weather data to ensure flexible, resilient and efficient operation of the sewer network.

The municipal partner JenaWasser is making a section of the Jena sewer network available for this purpose. Based on the previous sewer network calculations, including historical rain data, the first step is to use the simulation of various weather extremes to analyse what storage capacities the section has, how the sewer behaves in different situations and what additional volume can be used. The results provide the basis for the necessary development of an innovative AI-based management solution. Modern control elements (gate/weir systems and IT automation) and sensors for detecting sediment will then be installed and connected to the AI-based management solution. The subsequent trial operation will show what possibilities the new system offers and how it can be transferred to other applications.

The project partners at a glance

  • Institute for Water and Energy Management at Hof University of Applied Sciences (iwe)
  • Magdeburg-Stendal University of Applied Sciences, Department of Water, Environment, Building and Safety Professorship of Urban Water Management - specialising in wastewater
  • HST Systemtechnik GmbH & Co. KG (HST)
  • Pegasys Gesellschaft für Automation und Datensysteme mbH (Pegasys)
  • Nivus GmbH (Nivus)
  • JenaWasser (JeWa).

The Federal Ministry of Education and Research (BMBF) is funding the joint project "InSchuKa 4.0" for the "WAX" funding measure as part of the federal programme "Water: N". Water: N is part of the BMBF's "Research for Sustainability (FONA)" strategy.