Yorkshire Water is using StormHarvester’s AI-powered monitoring to detect network issues earlier, reduce pollution risk and shift from reactive to proactive wastewater management.
Background
Yorkshire Water serves over 2.2 million households across a 53,000km sewer network spanning West Yorkshire, South Yorkshire, North Yorkshire, the East Riding of Yorkshire, and part of Derbyshire.
In 2024, Yorkshire Water and StormHarvester began working together after recognising that a reactive approach to alarms and incident management was no longer sustainable. Alarm noise was placing considerable strain on operational teams, limiting their capacity for proactive work. Yorkshire Water needed a solution that could scale with future requirements without adding complexity to an already evolving landscape.
Approach
Yorkshire Water are using StormHarvester across their network and seeing benefits in reducing storm overflows. This case study will focus on in-depth application and benefits relating to three modules: blockage detection, pump station alerting and customer sewer alarm (CSA) alerting. They required a solution that would help:
Detect developing blockages, failures and bursts before they escalate into pollution incidents.
Identify hotspot locations in the network that repeatedly experience blockages, pump failures, and burst rising mains.
Prioritise high-risk areas where the consequence of a blockage or overflow is greatest.
Transition from a reactive operational model to a scalable, proactive approach to network risk management.
Blockage Detection
Blockages are one of the most persistent and costly challenges that utilities face. Often detected after damage has occurred, they represent a significant operational burden and are a leading cause of sewer flooding and pollution incidents.
Over 17,000 Sewer Level Monitors (SLMs) have been installed across Yorkshire Water’s sewer network. StormHarvester continuously monitors the sewer network, combining live level data, hyperlocal rainfall, and machine learning to identify anomalies in sensor readings. High risk areas were identified across the network, based on their proximity to watercourses and the gradient of land around the manhole.
Early identification of anomalies has:
Enabled operations teams to prioritise alerts to investigate issues before they escalate.
Resulted in 691 blockages successfully cleared from the sewer network. Based on the asset type and the placement of the SLMs, if these blockages hadn’t been removed, it is likely they would have resulted in a pollution incident into nearby watercourses.
(See example)
Pump Station Alerting
StormHarvester’s Pump Station Alerting was deployed to provide Yorkshire Water with AI-driven insights into pump performance. The system analyses pump start/stop, wet well level, and performance trends and corelates them with live weather conditions, to detect anomalies before failure occurs.
Over 4,400 sensors have been implemented to Pump Stations across Yorkshire Water’s network, leading to an 85.6% positive intervention rate on issues detected by the StormHarvester platform. 1674 alerts have been sent by StormHarvester, helping Yorkshire Water’s operational teams prioritise jobs across their network.
CSA Alerting
Customer Sewer Alarms (CSAs) are installed across Yorkshire Water’s network to help detect blockages and reduce the risk of flooding at customer property level. StormHarvester’s CSA Alerting uses data from digital level monitors, including manhole and gully sensors.
If levels are elevated above a configured percentage threshold for a prolonged period, StormHarvester triggers an alert. This allows Yorkshire Water crews to investigate potential blockages or issues before sewage back up into homes, while significantly reducing false alarms caused by everyday water use.
In recent years, over 55,000 sewer alarms have been installed across the Yorkshire region. The development of the CSA Alerting module represents a true innovative partnership. Yorkshire Water provided the real-world data and operational insights needed to build and test this monitoring capability and will continue to support the refinement of the module.
What began as a collaborative innovation piece is now scaling into a network-wide expansion that will see 65,000 more monitors installed by 2030.
Conclusion
StormHarvester’s AI-powered monitoring solutions have delivered measurable operational, environmental and financial impact for Yorkshire Water across both their pump station and sewer network infrastructure. Year to date, over 3,700 jobs have been raised from alerts sent by StormHarvester, with a 99.2% positive intervention rate on triaged alerts. Over 900 blockages have been successfully removed across Yorkshire Water’s network.
StormHarvester has supported Yorkshire Water to:
Move toward a proactive approach to their wastewater network management
Detect issues before they escalate into more serious incidents
Reduce internal flooding into customer’s homes
Future Plans
Yorkshire Water are continuing to implement new sensors across their wastewater network, as well as extending the scope of the relationship including detection of inflow and infiltration and rising main alerting. They are actively looking to expand the use of technology to monitor their network and will have over 150,000 monitors installed across the network by the end of 2030.
Contact
Email: info@stormharvester.com                                                                Website: stormharvester.com
