Reliable Leakage Data and how it facilitates reductions

The recently published Water UK's A Routemap for Leakage 2050 highlighted the importance of collecting and using quality data to assist with leakage analytics and strategic decisions. For over a decade, WaterNet from RPS has been trusted by the industry to collect, store, analyse and provide insight on the nations leakage data. With its predecessors before it (LMARS), UK water companies currently hold a vast amount of data on leakage.

Making the most of this data is a key to facilitate the achievements set out in the Route map. Background leakage and the natural rate of rise in leakage are vital to identify the opportunities for reduction, but also to ensure that you are on the correct adaptive path.

A number of our clients use the Natural Rate of Rise module in WaterNet, to ensure that they understand the amount of effort required to keep leakage at a stable level, before any reductions are possible. If leakage is not kept under control and the water network is not pro-actively replaced with new systems, leakage will increase due to the age of the pipes and the materials utilised in the past.

Understanding this value as well as the impacts of external factors like weather and resources availability, is vital in determining appropriate scenarios that can be used for forecasting. Understanding this data set at a DMA level can also assist in determining the impact of asset renewal, pressure management or any interventions that effect the rate of outbreak.

The policy minimum module allows companies to get an appreciation of their background leakage levels, not only at a company level, but with granular DMA detail. The module uses a large amount of the time series data and leak repair interventions, along with UKWIR based research to assist companies in identify the level of leakage that is not detectable with current technology.

It is important to recognise that sometime this level of leakage is artificially increased due to the fact that detection efforts were capped at a certain level (mainly due to economic factors). The module allows for this to be corrected ensuring that an appropriate estimate can be made. The level of background leakage in an area allows us to understand the point when a change of pathway is required, giving advanced warning when capital interventions are likely required to allow for further reductions.

The results often produce real insight into areas that have always been a large distance from the background prediction. This can inspire a fresh look on some DMA and where to focus on potential reductions or use some innovative technology.