The Gothenburg region is ready for the storm

A digital twin of the wastewater utility in Gothenburg and surrounding municipalities is helping to future-proof the region and make the most efficient use of existing infrastructure

Gothenburg has a vision of becoming the best city in the world when it rains. And this vision makes perfect sense as Gothenburg is one of the rainiest cities in Sweden. Add to that a growing population, an ageing infrastructure and increasingly extreme weather patterns due to climate change, and the city’s water utilities have their work cut out for them to protect both the city and the surrounding environment.

Client
Gryaab AB

Country
Sweden

Products and Services
Future City Flow

Downloads
Highlights flyer

Challenge

Heavy rainfall causes large loading variations to the Gothenburg region’s central treatment facility, the Rya water resource recovery facility (WRRF). Approximately 25% of the sewers in the City of Gothenburg are combined, which increases the risk of floods as stormwater and wastewater are transported in the same system. It also increases the risk of untreated wastewater being discharged into the surrounding ecosystem.

Furthermore, changing climate conditions combined with a growing population add further pressure to Gothenburg’s ageing infrastructure and make operations more complicated.

The main priority for Gryaab is to protect the citizens of Gothenburg from floods and to protect the ecosystems in the waterways and basins in the region from polluted wastewater. To do so, Gryaab has to ensure optimal management of the water flowing in and out of the city. They needed to find a more future-proof way to efficiently manage issues related to combined sewer overflows (CSOs) and to reduce storm weather impact on the WRRF. The traditional approach relied heavily on operator experience and judgement.

However, the Rya WRRF is only manned in the daytime on regular working days, and standby personnel operate the facilities from home the rest of the time. This puts a natural limit to the hours of monitoring and the amount of information which could be processed. It also leaves room for manual errors. Especially when high flows are expected, it is important for the operators to have as much information as possible so that they can make the right decisions and avoid critical situations, which could have negative impacts on the city and the environment.

The main challenges for Gryaab were:

Minimising the impact of flow variations in extreme weather
Improving the attenuation of inflow to the Rya WRRF as much as possible to reduce pressure on the system
Improving water quality in receiving water bodies
Controlling where the CSOs occur to minimise environmental impact

Water is an integral part of life in the Gothenburg region, and we have an important task in making sure that the water remains an asset and not a liability. The pressure on our infrastructure is increasing as the region grows and we continue to receive more violent cloudbursts, but now we are warned ahead of time and know which actions to take at which time. Our long-standing collaboration with DHI means that we stay ahead of the digital curve with solutions such as the Future City Flow digital twin. We are now ready for whatever weather patterns the future will bring, and we are in a stronger position to protect the receiving waters in and around Gothenburg.

‘‘

Åsa Magnusson, Process Engineer
Gryaab AB

About the client

Gryaab AB is a wastewater utility currently serving seven municipalities in the Gothenburg region on Sweden’s west coast with more than 800,000 citizens connected and another municipality, Bollebygd, to be connected around 2025.

Gryaab owns and operates the Rya water resource recovery facility (WRRF) and a 130 km tunnel system transporting wastewater from the connected municipalities to the central treatment facility. The Rya WRRF is one of Sweden’s largest water resource recovery facilities.

Solution

Gryaab has a history of using innovative and digital solutions to support them in managing the region’s wastewater infrastructure, and they quickly saw the potential in having a digital twin of the entire system to improve overview and management.

A digital twin is basically a dynamic digital representation in real-time of a physical object or a process, such as the Gothenburg region’s tunnel system and catchment. A digital twin can be compared to the co-pilot on a plane, and it uses analytics and predictive modelling to validate decisions and to automate time-consuming and manual technical or operational processes.

By implementing the Future City Flow (FCF) digital twin, Gryaab could get real-time information about events in the tunnels as well as accurate predictions of potential issues and peak pressure on the system as the FCF digital twin also incorporates weather forecasts in the modelling.

Gryaab is now able to accurately predict runoff, combined sewer overflows, tunnel water levels and discharges to the Rya WRRF. A four-day forecast is updated hourly or on demand from an interactive and user-friendly web interface. The hourly forecast is exported to the Rya WRRF’s supervisory control and data acquisition (SCADA) system and can be used by the control room as guidance for inflow or used as a signal to automatically change the set point for the inflow to Rya WRRF.

The project included:

Building detailed hydrological and hydrodynamic models of the tunnel system with detailed simulation of the 250 km² catchment
Incorporation of all controllable devices (e.g. gates, pumps) in the digital twin real-time control system
Development of Forecast-on-Demand features with the option of adjusting pre-suggested strategies and analysing historical events for training purposes
Development of an operational strategy to mitigate the risk of urban flooding

With the FCF digital twin, Gryaab can act early, and staff can make decisions based on comprehensive, real-time data and prognosis. They also use the digital twin for training in various scenarios so that the staff is better prepared for future critical situations and for making better, informed decisions. In short, the FCF digital twin is used for gaining better real-time control and for finding ways to improve the operation of the tunnel system, both today and in the future.

Results

Gryaab’s implementation of the Future City Flow digital twin means that they are now able to make the best use of Gothenburg’s existing infrastructure. They will also know where to focus future infrastructure investments. And most importantly, they make sure that the people of Gothenburg will be able to continue to enjoy the clean waters in and around Gothenburg, come rain or shine.

Reduced risk of flooding for peace of mind for both citizens and operators

Cost-efficient long-term planning of inflow and infiltration management for informed investment decisions and more efficient use of existing infrastructure

Improved water quality in the waters around Gothenburg and reduced environmental impact

Technology deep dive

Solution design
Operational aspects of the Gryaab utility are characterised by the large amount of inflow and infiltration, the operating constraints of the influent pumping station and the different jurisdictions. The FCF digital twin of the tunnel system and influent pumping station was developed to accurately predict the runoff, combined sewer overflows, tunnel water levels and discharges to the Rya WRRF. A four-day forecast is updated hourly or on demand from an interactive and user-friendly web interface. The hourly forecast is exported to the Rya WRRF’s SCADA system and can be used by the control room as guidance for inflow or used as a signal to automatically change the set point for the inflow to Rya WRRF. Facts about the FCF digital twin for Gryaab:

47 sub-catchments, which together simulate the Gryaab catchment. The sub-catchments cover more than 250 km2 of catchment surface, including 20 km2 impervious surface and 2,400 km of tunnels and pipes. Slow and fast runoff components are modelled in each sub-catchment
About 80 km of the tunnels are described in the hydrodynamic model
Configuration of 96-hour forecasting system simulation performed every hour
40 sewer overflow structures, 10 pump stations and 8 valves/gates
13 structures are controlled by 7 model sensors (incl. forecast)
7 pre-set weather situations with approximately 50 related control actions for optimal pumping operations
Includes infiltration and inflow of rainwater and groundwater to the system

Highlights of how we did it

Development of operation strategies based on a balance between the pump flow to the WRRF, tunnel and pipe volume utilisation, CSOs at tunnel inlets and retention chambers, depending on the actual situation and forecasted runoff

Weather forecasts include a hybrid between C-band radar and several weather models, where the most likely forecast is selected (KNEP forecast). The forecast horizon is 36 hours with hourly resolution and spatial resolution of 2 km. A new forecast is produced every hour. During the first few hours, primarily radar data is used while the weather model data gradually takes over. The data grid over the region is interpolated into each sub-catchment of the collection system model. This allows each sub-catchment to get its own unique rain series in the forecast horizon, which is combined with measured rainfall data

Development of Forecast-on-Demand features with the option of adjusting pre-suggested strategies and analysing historical events for training purposes

Key results

Simulations indicate that yearly CSOs may be reduced by 65% and bypass volume at the WRRF by 85% through dynamic operation of major CSO sites and increased utilisation of the tunnel volumes by installing additional sluice gates in the tunnels
Reduction of urban flooding incidents and overall optimisation of sewage system performance is observed
Simulations for the years 2035, 2050 and 2070 with various climate and population scenarios helped understand how and when to plan for expanding current WRRF capacity to service the city of Gothenburg and the surrounding municipalities

Let us help

Want to take the next step in solving your challenge?