The Big Question: Leakage/NRW Management

Oct. 16, 2014
Reducing water loss due to leakage has been the focus of increasing effort during the last twenty years and the action taken has resulted in a significant improvement.

We ask technology companies: How far can leakage/ non-revenue water (NRW) be reduced using a complete asset management approach?

Taking a pro-active approach

James Dunning, CEO, Syrinix

Reducing water loss due to leakage has been the focus of increasing effort during the last twenty years and the action taken has resulted in a significant improvement.

Leakage is around 35% lower now than at its highest level in 1994 and 1995 – a reduction equal to the daily needs of nearly ten million domestic customers.

With the easiest problems effectively addressed, where should water companies and pipeline operators be directing their attention in order to continue this improvement?

Technology developed in the 1990s with further refinement in the last decade has enabled water companies to develop some degree of pro-active response to leaks as they occur.

Internal inspection techniques, a gold standard for effectiveness, incur large costs for deployment and traffic management together with increased contamination risks. So while a water company may wish to use internal methods, their practicality is limited.

The answer to this apparent dilemma is to bring in far more data from the network, analyse and interpret this data correctly. Pro-active methodologies detect and rank leakage as it develops, targeting the water company's limited repair resources in the most cost effective manner. Pre-emptive methodologies bring in pipeline age and condition information together with soil chemistry and stability data and historical leak occurrence data for a pipeline. This is then used to create a heat-map of areas of the network which are statistically likely to have leakage now or will have in the near future.

Recent advances in smart and automatic monitoring equipment offers a step-change in data acquisition. Algorithm-based software is being increasingly applied, aggregating data across a network to identify problems.

Creating a smart water network

Keith Hilson, Smart Water Team, Sensus

A survey of 184 water companies worldwide in 2012 showed potentially avoidable costs due to leakage of £5.6 billion globally. There are three areas that companies typically focus on; improving understanding of NRW, more effective asset management and better operational performance.

One of the greatest challenges is understanding how much of the water treated or purchased is actually delivered to customers. However, there are proven technologies in metrology, communications and analytics available now which add understanding and facilitate good business decision making.

Estimating NRW is a surrogate measure for asset condition and operational performance; it doesn't drive business improvement. However, by employing accurate network metering, end user consumption analysis, increasing the resolution of measurement data points and through smarter analysis, water utilities can improve the way they manage customer service, asset replacement, operational effectiveness, water resource planning, and financial planning and management. This approach of combining intelligent metrology, near real-time communications and data analytics is what many are now defining as a Smart Water Network. The industry is starting to recognise the quantified financial benefits by addressing leakage. We now need the regulators to step in and encourage innovation.

Understanding your existing system

Xiangjie Kong, director of research and development, Pure Technologies

While leaks on critical trunk mains are often a major contributor to NRW, operational inefficiencies can also lead to high water loss, and therefore wasted capital needed to treat and pump lost water. Many utilities around the world have successfully reduced NRW with an advanced inline leak detection program that targets large-diameter trunk mains. However, combining a leak detection program with an asset management strategy can even further reduce water loss.

An asset management approach targets water loss on a system-wide basis; completing a consumer meter reading analysis to determine consumption statistics and populate a hydraulic model is an important step in this process. If consumers are billed individually, this provides per consumptions statistics, which help identify potential metering problems that can be rectified.

Another component of an asset management strategy is a NRW study, which is done in conjunction with a metering analysis to develop future NRW strategies. By collecting existing metering data, utilities can perform water balances and identify areas where water is lost due to leaks or unauthorized consumption.

From there, a more targeted inline leak detection program can identify leaks and unauthorized consumption along specific trunk mains. By combining asset management and inspection, utilities can effectively allocate resources to maximize the benefits of leak detection programs.

After completing the initial analyses, an evaluation of the existing system's hydraulic performance allows for simulation analysis, which can be applied to optimize operations and service delivery.

This also allows utilities to complete "what if analyses". These can serve as a training tool for new operators and planners, as well as form the basis for optimized planning of future expansions to accommodate any anticipated growth in the supply area, which is a reality for many utilities.

By adopting an asset management approach, operators can better understand their existing system, along with any inefficiencies. This allows for immediate NRW reduction by eliminating inefficiency and improving service delivery. It also allows for a more strategic leak detection program that maximizes resources.

A combined approach

Asaf Aharoni, director of research, TaKaDu

A complete asset management approach, traditionally used for infrastructure-related planning and decision making, also has an indirect (albeit significant) effect over leakage and NRW reduction. Referring specifically to NRW, asset management reduces NRW in two ways:

Apparent losses, which include metering and billing issues, are often reduced.

The under registration of meters, inaccurate readings, and repeating meter or telemetry faults can result in inaccurate measurement and incur excess billing from the bulk supplier (paid by water utilities) or the utility side (paid by consumers).

Utilities taking a combined approach to data analytics and asset management have an advantage when it comes to avoiding this overpayment.

This is because this approach compares the meters' actual performance with the manufacturer's specifications, detecting any discrepancies stemming from meter misbehaviors.

Analysis also allows for a comparison between the manufacturer's recommended meter environment specifications and the actual environment setting. This enables informed decisions related to meter type selection, replacement, and billing.

Real losses refer to actual water loss and are, among other factors, a result of leakage, which can also be reduced by a complete asset management approach.

This approach can be applied to support pipe replacement and rehabilitation planning decisions, consequently reducing leakage. The combination of pipe attributes (e.g. material, diameter, age) and more extensive GIS information, actual field data (flow, pressure, pressure transients, etc.), repair logs and other historical issues (e.g. event history of a water monitoring system), and field information (soil type, proximity to train lines, etc.) is extremely powerful.

A comprehensive analysis that incorporates these infrastructure and system elements can be used to make educated replacement/rehabilitation prioritization decisions.

The analysis also optimizes the suggested new pipes' attributes in regard to field conditions that they will have to endure (considering relevant costs). The overall effect of this approach is a reduction in leakage events and background leakage.

The combination of real network data, repair logs, and asset management information from multiple operational networks is integral to such data analytics developments.

It allows for smarter asset management and, consequently, reduced NRW.

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