Problem
A significant number of water companies have started using Trunk Main Flow Monitoring Zones (also known as Water Balance Zones) to locate areas with leakage or unaccounted for water on the trunk mains. Data from these zones help direct leakage detection and consumption recovery efforts.
While some companies are at the maturity stage in their use of Trunk Main Flow Monitoring Zones (FMZs) others are just starting on the journey. There is no best practice or standard for the development or use of FMZs. Creating and maintaining a successful FMZ requires a high amount of effort, investment, time and energy. With future industry’s challenge to reduce leakage and UKWIR’s big question on zero leakage by 2050, it is high time a best practice is developed. The document would build on the UKWIR project: 15/WM/08/55 Leakage Upstream of District Meters, where FMZ’s are mentioned, but details on operational management of them is not.
Impact
This would result in an industry consistent approach to monitoring trunk main flow and efficient location of train main leaks.

The Water Industry has very little knowledge of the impact of reducing leakage levels on the numbers of repairs that need to be carried out each year, nor on the relative proportions of visible and invisible leaks.

Introduction of performance commitments and changes in SIM, with associated rewards and penalties, has increased focus on the customer service aspects of burst and leak repairs, whether it is unwanted contacts, interruptions to supply or associated discolouration contacts. Customer Service impact mitigation costs will add to the operational costs for repair and consequential damage.

Historic leakage strategy has focused on Sustainable Economic Level of Leakage (SELL). Leakage strategy now must consider the customer acceptability aspects of leakage. Most customer views are based on the impacts of visible or reported leaks and the impact of repairs on customer service.

Single company data is insufficient to discern any impact due to leakage level as it is masked by weather and relatively static targets. Pooled company data, combined with planned AMP6 reductions should provide a data set to understand any increases in repair frequency, changes in proportions of visible leaks and the time period for change.

This project will use recently developed flow estimation techniques to investigate these factors across a representative sample of household properties within several water companies.  

The data obtained will be used to provide greatly improved estimates of: 

• Plumbing losses, which are part of consumption
• Water running into storage at night, also part of consumption
• Background leakage on underground supply pipes, which is part of the total leakage KPI

Modern technology has made it possible to collect much greater quantities of data, and at higher resolution. Leakage analysis methods and leak detection technology have both made many advances in recent years, but data collection and manipulation processes have hardly changed. The basic principle of measuring minimum night flow into a DMA, and then subtracting estimates of household and non-household night use to give leakage, remains unchanged in the past 30 years.

However the recent growth in smart networks, and particularly the use of smart meters for revenue purposes, could offer many new opportunities for better leakage management. It is essential that these opportunities and benefits are identified now, so that water companies can take them into account when making their choices of which smart technologies to invest in.

No Further Information Currently Available.

Both Ofwat and the Environment Agency (EA) have said recently that they have some concerns with the current Sustainable Economic Level of Leakage (SELL) process for the setting of leakage targets.  The recent EA guidance on leakage for Water Resource Management Planning (WRMP19) says :

“There is increased realisation that SELL may not be the most effective way to plan leakage levels.  WRMP19 will be the final time that a leakage figure is derived from SELL.  We expect water companies to evolve and move away from SELL for WRMP24 and to innovate to reduce leakage beyond the current levels”.

 The Ofwat consultation document on outcomes for PR19 (February 2017) expresses a different view :

“Companies should report their SELL in business plans, explain their assumptions on future improvements in leakage reduction efficiency in the SELL, and explain how its Performance Commitment for leakage is appropriate in relation to SELL”. 

 There is a strong feeling amongst companies that leakage targets should continue to be based on a sound economic analysis.  However, the cost of leakage management relationship for SELL modelling is derived from analysis of the company’s own historical leakage management performance data.  It is therefore a valid criticism of this process that if a company has been historically inefficient, then this inefficiency becomes built into the SELL.

Leakage on customer supply pipes and communication pipes is estimated to be a significant proportion of the total leakage. At present leakage is only detectable on communication and supply pipes either if the property is metered, or if there is an acoustic device nearby or if it is picked up on an active leakage control sweep of the DMA. Even is a property is metered, unless AMI or frequent AMR is deployed, then the average leak run time on a supply pipe before discovery is likely to be three months (based on six monthly reads). As a result, although the volume of a leak on a supply pipe or communication pipe may be small, they will typically run for a significant length of time.

In recent years, the use of mains models to predict the likely location of a failure have increased. These models typically look at the previous failures within an area, the network model and mains materials and other environmental factors (weather, traffic loading, demand) in order to produce a “most likely” point of failure. This reduces the time spent sweeping the DMA by directing ALC responses to the optimum locations to search for a leak, and additionally can be used to drive mains replacement programmes.

At present, these solutions concentrate on mains failures. However, there would be considerable benefit to these solutions being extended to the prediction of supply and communication pipe failures. Validated models that proved successful at predicting failures would not only reduce location and leak run times but additionally allow more targeted replacement polices.

No Further Information Available.

No Further Information Available.

It is estimated that about 25% of the leakage within a water distribution network is located on a customer's property and occurs within the pipe that is not the responsibility of the Water Companies. However, this is still included in the leakage figures that water companies report to regulators.

The customers can be divided into household and non- household. For household customers, water companies offer a range of solutions from providing free advice to free repairs. There is limited understanding of how these different policies ultimately impact on reported leakage levels and overall cost to the business. For non household customers, water companies don't provide free repair services as a part of their standard customer leakage policy. However, with the opening of retail market, communication with non-household customers has become difficult, slowing down the leak repair and increasing the level of leakage.

Water Companies are also increasingly installing smart metering which identify leaks with very low flowrates. This has challenged the industry to find such small leaks, which are not cost effective to repair, and can be difficult to locate.

Distribution Maintenance staff at water companies know well that many leaks and bursts, once excavated, prove to be at the location of a previous repair, and occur as a result of a failure of the old repair. However it is not known how much data is collected on this, and there is no quantitative evidence of the magnitude or significance of this problem at national level. Nor has there been any study of the reasons for the failures, i.e. whether they are due to deterioration of the clamp or other repair materials over time, or whether they are caused by faulty workmanship at the time of the initial repair.

Many companies do record the types of failure within their records of mains and service bursts. However these descriptions are often very brief (e.g. “pin-hole”), and the fact that the failure was at a previous repair may not be recorded. This project will initially assess the availability of suitable data, in collaboration with participating water companies. The UKWIR National Mains Failure Database may also be a valuable source of data.

The UK water industry is aware that mains replacement programmes are not at the volume needed to create a healthy distribution network for future generations.

In building Mains Rehab business cases the industry must be able to make good decisions as to the engineering techniques employed.

In the 1990’s and 2000’s, mains renewal programmes were principally driven by the need to improve water quality in pipe networks, under the Section 19 undertakings.  More recently, mains renewals have been targeted more at improving serviceability, specifically burst frequencies and interruptions to supply. The selection of mains for renewal under these programmes was based first on data on water samples and water quality complaints, and later on data on burst frequencies.  As all of these types of data can be allocated to specific pipes, it was relatively simple to target individual pipes for renewal.

Now, with the current focus on reducing leakage levels, leakage has become a major driver for mains renewal, if not the principal driver.  However, leakage is not normally measured at the level of individual pipes, but only at DMA level.  In reality leakage is rarely uniformly distributed across a DMA, but instead some pipes leak more than others within the DMA.  In order to optimise the economics of a mains renewal programme driven by leakage reduction, a method is required to determine which pipes are leaking most in order to target the investment to maximise the benefits.

Currently, as such a method is not generally available, mains are selected on the basis of historical burst numbers, using burst frequency as a surrogate for leakage.  In reality, burst numbers are a poor indicator of leakage levels.