Determining nightline leakage and usage
Every water company has a top hit list of problem DMAs the ones with huge nightlines which elude all efforts to track down leakage, writes Charles Harris and Roger Ironmonger of Primayer. These invariably include unmeasured trade users the number one headache for leakage practitioners.
Socrates from Primayer is a new, patented tool for analysing DMA nightlines,
specifically designed for discriminating between areas of high use and high
Socrates is much more than a conventional data logger. Its statistical
processing capability holds the key to teasing out the elusive boundary
between legitimate night use and leakage on a site by site basis. It has
applications in DMA demand analysis, consumption monitoring, control system
fault diagnosis and in leakage reporting.
Nightlines water flows into DMAs during periods of low use by consumers
are monitored extensively by the water industry to estimate leakage levels.
This is carried out using data loggers or telemetry devices attached to flow
Conventionally, average values (usually via accumulated pulse counts) are
recorded over 15 minute intervals. This period has been chosen for
convenience; it appears to give a reasonably detailed view of network
operation without overloading supervisors with data. Unfortunately, new
demands on network efficiency mean much more precise diagnostic tools are
The problem is that conventional averaging hides important details. Figure 1
shows an example on a real DMA. The minimum 15 minute average value is 5.34
litres/sec over the period 02:30 to 02:45. The actual flow pattern can be
seen varying above and below the average valves; it is markedly different
and, crucially, the minimum valve (an indicator of leakage) is considerable
lower. The example is taken from a mixed trade/domestic DMA and it
illustrates problems endemic to such sites. Varying trading and production
patterns will almost always defeat conventional sampling methods.
When accounting for leakage, practitioners also need to understand how
domestic customers use water at night. Traditionally, it is assumed all
domestic properties use the same average quantity of water every night
regardless of social or climatic circumstances. A common global estimate is
1.7 litres per property per hour. This is perhaps the biggest single flaw in
the system by which the industry now estimates leakage. Tests with
consumption monitors show the assumption is invalid. As an example, Figure 2
shows one week¹s data derived from such a site the night to night
variation approaches 50 per cent.
Socrates tackles these problems by exploiting the maximum resolution
available from the flow measuring system. It collects thousands of data
values per night which it processes into a smaller set of micro-values. This
set (typically 500 values) exposes the crucial details of night lines which
are masked by conventional averaging. This has enormous value in diagnosing
discrepancies in trade use. It is also possible to analyse nightly
distributions of micro-values to find estimates of domestic consumption
which reflect prevailing site conditions.
On pulse generating flow meters, Socrates uses an advanced form of Pulse
Interval Timing (PIT). On analogue meters it carries out rapid sampling.
These methods potentially enable it to probe nightlines more thoroughly than
conventional pulse counting or averaging. However, simple PIT measurements
will give artificially low values. Before presenting results, Socrates
processes the raw data to remove extraneous artefacts associated with the
measurement system, pressure surges and hydraulic oscillations.
On pulse generating flow meters, there can be substantial variation in
output pulse values unrelated to variation in the flow being measured. On
some types of meter, the variation is systematic. On others it is random.
Socrates uses proprietary filtering algorithms to remove these errors.
Sudden hydraulic disturbances, such as pump starts, can generate surges in
networks causing flows to oscillate strongly abut mean levels. The troughs
of these oscillations are difficult to distinguish from genuine short term
reductions in user demand. PIT measurements which do not discount such
troughs will always give wrong estimates of baseline flows. The errors will
be serious. To avoid errors, Socrates checks for sudden changes in pressure.
Pressure change thresholds can be set by the user and if these are exceeded,
Socrates assumes a transient has occurred and ignores flow data around this
section of the nightline.
When searching for minimum valves, Socrates also sets restrictions on the
rate at which flows are allowed to change around minimum points. This
catches spikes and and other short transients which are not evident in the
In addition to transient hydraulic artefact some systems exhibit continuous
low level hydraulic oscillation even after removing measurement artefact. If
this Œcyclic¹ hydraulic artefact is not filtered, errors will be caused by
confusing trough values in natural hydraulic cycles with periods of low user
activity. Socrates uses autocorrelation to determine the optimum averaging
time to smooth out such oscillations. This averaging time is calculated for
each and every nightline; it is the minimum time over which measurements
must be averaged to minimise errors. The averaging time is called the
micro-period and average values calculated over such periods are called
micro-values. Figure 3 shows an example of cyclic artefact.
For each nightline, Socrates searches for a minimum flow valve which
satisfies pressure and flow transient restrictions and which is free of
measurement and cyclic hydraulic artefact. Because of the measurement speed,
it is able to probe deep into nightlines to reveal the lowest baseline
Figure 4 shows results from a rural DMA. Socrates reported a 25 per cent
lower nightline than 15 minute averaging on the night shown. The selected
minimum point at approximately 04:35 shows a stable dip in the nightline
some 30 seconds long. Socrates rejects the minima around 04:26 as
In another example, a data logger on a city centre site had detected high
Œleakage¹ the logger was reporting a minimum flow of 11 litres/sec.
Socrates, however, revealed a true minimum of 6.3 litres/sec with an
additional varying flow component superimposed. This extra use explained the
high nightline and saved time consuming investigation.
On many conventional logging systems, Œfast’ may not be fast enough. High
speed measurements are required to detect surges. No conventional logger
automatically detects transients. Additionally, no conventional logger
detects and compensates for measurements system error nor for
Fast logging on pulse counting systems is subject to large quantisation
errors. For example, a 3.5 litre/sec flow logged every second from a
pulse-head generating one pulse/litre will store the sequence of flow values
as 3, 4, 3, 4, 3. There will be no intermediate values. This is not precise
Even if fast logging was suitable, the shear volume of raw data would
overload network supervisors. Socrates avoids this by processing raw
measurements before presenting a limited set of key facts describing the
state of the distribution system.
Socrates can be used in cul-de-sac type consumption monitors where flows
into statistically chosen small groups of houses are measured to calculate
per capita consumption.
Figure 5 shows a Socrates nightline plot from a 111 property ACORN F50 site.
Clearly evident is a Œcore’ flow on which intermittent Œevents’ such as
toilet flushes and washing machine fills are superimposed. Because these
sites are small, events rarely coalesce. The Œcore¹ flow will thus be very
close to, if not actually at, the leakage level of the site. Figure 6
compares the reporting of the lowest nightline flows using conventional
averaging and Socrates over one week.
Conventional averaging over-estimates
the minimum flow, and hence the leakage, on this site by, on average, 37 per
cent. This improved accuracy clearly has a positive implications for Per
Capita Consumption calculations used in integrated flow analyses of leakage.
Compared with conventional monitoring, on sites of up to approximately 500
properties, Socrates routinely records minimum flows undistorted by
intermittent night use. This opens the possibility of using larger
consumption monitor areas. Core flow levels would still be exposed, but the
larger property count would improve the statistical analysis of night use.
An average night flow value, say over one hour, from a consumption monitor
comprises two components: intermittent use and core flow. Socrates always
penetrates to the core flow. Core flow itself comprises three parts:
continuous use, plumbing losses and leakage. On a consumption monitor, core
flow is arguably all waste. An example of continuous use is a tap dripping
because it hasn¹t been turned fully off. A plumbing loss might be a tap
dripping because of a faulty washer. These two components vary randomly and
are the principal reason why consumption monitor minimum micro-values vary
about mean levels. A statistical estimate of the actual leakage boundary may
be derived from the distribution of the minimum micro-values over a series
of nights. An example is shown in Figure 7.
The concept of core flow can be extended to DMAs. Larger DMAs, up to 2,000
properties, have been simulated by adding together random sequences of real
Socrates nightlines. These studies indicate that Socrates will typically
penetrate the intermittent use on a 500 property DMA to within four per cent
of the actual core flow. On a 2,000 property DMA it penetrates to within 16
Core flow on a DMA will comprise the same components as on a consumption
monitor but with two extra random elements: continuous trade use and the
penetration error described above.
These four components vary randomly and cause minimum nightly micro-values
to vary about mean levels. A statistical estimate of the actual leakage
boundary may be derived from the distribution of these minimum values over a
series of nights. Figure 8 shows a typical analysis applied to a DMA
comprising 1,700 properties and a harbour. It is worth noting in this
example, and it is by no means unique, that conventional analysis yields
ridiculous leakage values, even before trade allowances are subtracted.
In contrast to these dubious speculations, the Socrates method makes no
assumptions. It needs neither domestic night use, or trade night use values.
The estimate is based solely on the evidence of the nightline.
New demands being made on network efficiency require much more precise tools
to monitor performance. Conventional monitoring, based on limited average
data-sets, masks important details of night flows, so making troubleshooting
difficult. In this article, we have seen practical cases where Socrates’
high resolution data has helped the leakage manager determine what is or
isn’t leakage. We have also seen how simplistic measurements based solely on
fast or PIT sampled absolute minimum flow rates will be dangerously
misleading. We have also seen how tangible benefits are gained by using
Socrates on consumption meters. The errors caused by counting in
intermittent night use are eliminated. The concept of core flow has been
introduced and with it the potential for a completely default-free analysis