DYNAMO

Combining reactive and proactive approaches to reduce reported leakage

Dynamo takes data from pressure and flow logging points and provides both reactive analysis for emerging network events and support for proactive investigations, giving clients a greater understanding of their network configuration, customer demand and leakage.


We have developed Dynamo with a leading UK water company and it is currently being used for the analysis of events in over 650 DMAs across multiple UK water companies. Dynamo uses over 8,000 permanent flow and pressure loggers installed on our clients’ network.

Dynamo is a software solution which receives data directly from clients' logger providers, ensuring we can deliver analysis in as close to real time as possible.

Reactive analysis

By using both recent and historical behaviour to establish a pattern of expected performance, we can compare live data from sensors to identify unexpected events. Our analysis correlates changes in flow profiles with pressure changes in the DMA to identify the root cause, for example an eruptive burst, network operation, or demand change. By accurately understanding and classifying this root cause, we can direct leakage teams to respond in the most direct and effective manner. 

Dynamo gives events a confidence rating, which helps users to prioritise their response and focus on the most critical events. This confidence rating is updated in real time as new data is received and is based on a number of factors identified by Dynamo. These factors include:

  • the flow change identified (i.e. the size of a burst) 

  • how long the event has been running for

  • the availability of supporting evidence from multiple data sources. 

Figure 1 shows our reactive analysis at work in a client DMA. The area of interest allowed the leakage technician to spend significantly less time locating the burst, rather than having to investigate the whole DMA. 

Dynamo has been proven to consistently deliver a 30% reduction in total time spent undertaking reactive leak detection activities. 

Figure 1: Our reactive analysis at work in a client DMA

Proactive analysis

We build hydraulic simulations of our clients' water networks and compare the outputs with the logged data coming from the permanent logging on the network. Whilst this has helped our clients to localise longstanding leaks on their networks, we have discovered a much greater benefit from working closely with our clients to resolve a wide range of causes for network anomalies, including network configuration and customer demand issues.


This anomaly investigation and resolution has included:

  • Identification of customer meters not included in corporate systems. Resolving these issues reduces reported leakage by increasing customer night use and demand allowances. 

  • Identification of open boundary valves. DMA integrity is important to ensure targeting is done effectively and that companies can react with confidence to network events, minimising customer impacts. 

  • Identification of incorrect GIS and valve status inside DMAs. It is not unusual for GIS to be slightly incorrect, ranging from abandoned mains which are still live, to valves temporarily closed during previous incidents which haven’t been properly reopened. Often these issues cause confusion when responding to an event and can impact the networks performance from a water quality and pressure perspective.

  • Identification of customer created network transients. Where customers are taking water from the network in an erratic manner, either through direct pumping or by filling a tank, they can cause transients to travel through the network. Our analysis allows us to identify underlying reasons for excessive bursts occurring in parts of DMAs. 

In the following example, the logged data identified a previously unmetered pumping station which fed three tower blocks. This investigation revealed a large network of private supply pipe which was unmetered and unmaintained, as well as a source of highly damaging pressure transients. Metering this network identified continuous leakage flow which the local leakage teams were able to work with the customer to resolve.

Figure 2: Onsite investigation identified a private supply feeding three tower blocks