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Controlling water losses through leaks in water supply systems is of great importance for the sustainable management of this scarce resource in South Africa and the world. Much work has been done in this field, both locally and internationally, and various factors influencing water losses have been identified and investigated. One of the major factors still not well understood, is the effect of the water pressure in a pipe on the leakage rate. According to the theory, the rate of leakage through a hole in a pipe is proportional to the square root of the pressure. However, using measurements in real water distribution systems, especially in the UK and South Africa, it has been found that pressure has a much greater effect on the leakage rate than the theory predicts. To illustrate this point, doubling the pressure in a pipeline will increase the theoretical rate of leakage by approximately 40 %. However, in practice the real increase in the rate of leakage is typically 100 %, and increases as high as 570 % have been reported. Various possible reasons for the discrepancies between the theory and practice exist. The purpose of this paper is to identify the main mechanisms that may be responsible for these discrepancies. The mechanisms discussed include expanding leak openings, the effect of soil conditions around the pipe and laminar flow conditions.
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11 December 2006
JE van Zyl 1 (Ph.D.) and CRI Clayton 2 (Ph.D.)
1 Associate Professor,
Department of Civil Engineering Science,
University of Johannesburg,
PO Box 524, 2006 Auckland Park, South Africa,
Ph +2711 489 2345, Fax +2711 489 2148,
2 Professor,
School of Civil Engineering and the Environment,
University of Southampton,
Southampton SO17 1BJ
Number of words: 4000
Number of tables and figures: 2
Key words: Hydraulics & Hydrodynamics, Pipes & pipelines, Water supply
Submitted to: Proceedings of the Institution of Civil Engineers, Water Management
11 December 2006
The results of pressure management field studies have shown that the leakage exponent is
often considerably higher than the theoretical orifice value of 0.5. The purpose of this paper is
to identify and analyse factors that may be responsible for the higher leakage exponents. Four
factors are considered: leak hydraulics, pipe material behaviour, soil hydraulics and water
demand. It is concluded that a significant proportion of background leakage can consist of
transitional flow, and thus have a leakage coefficient value above 0.5 (although not above 1).
An important factor is pipe material behaviour: laboratory test results are presented to show
that pipe material behaviour can explain the range of leakage exponents observed in the field.
The complexity of the interaction between a leaking pipe and its surrounding soil is discussed
and it is concluded that the relationship between pressure and leakage is unlikely to be linear.
Finally, it is noted that if water demands are present in minimum night flows, the resulting
leakage exponent is probably underestimating the true value.
A orifice or hole area
c leakage coefficient
c' stress factor
C constant
Cd discharge coefficient
d hole diameter
d0 original hole diameter
Δd change in hole diameter
11 December 2006
D pipe diameter
E elasticity modulus
F shape factor for soil flow region
g acceleration due to gravity
h pressure head
k soil coefficient of permeability
n aspect ratio of a rectangle
P wetted perimeter
q flow rate
Qdem demand flow rate
R hydraulic radius
Re Reynolds number
t pipe wall thickness
v velocity
α leakage exponent
β water demand elasticity
ε material strain
ρ fluid density
σ material stress
ψ kinematic viscosity
Note to the Editor: The accepted symbol for kinematic viscosity is not ψ as used in this
manuscript, but the Greek letter nu (ν). The change was made to avoid confusion with the
symbol v, which looks very similar to the Greek nu in the font used. We will appreciate it if
the correct symbol ν (Greek nu) can be used in the printed paper, provided that it can be
distinguished clearly from the letter v.
11 December 2006
Water distribution systems world-wide are aging and deteriorating, while the demands on
these systems, and thus on natural water resources, are ever increasing. Losses from water
distribution systems are reaching alarming levels in many towns and cities throughout the
world. Water losses are made up of various components including physical losses (leaks),
illegitimate use, unmetered use and under-registration of water meters. Leakage makes up a
large part, sometimes more than 70 % of the total water losses1.
One of the major factors influencing leakage is the pressure in the distribution system. In the
past the conventional view was that leakage from water distribution systems is relatively
insensitive to pressure, as described by the orifice equation:
... (1)
Where q the flow rate, Cd a discharge coefficient, A the orifice area, g acceleration due to
gravity and h the pressure head differential over the orifice. To apply this equation to leaks in
pipes it can be written in more general form as:
q ch
... (2)
Where c is defined as the leakage coefficient and α as the leakage exponent (α is sometimes
referred to as N1). A number of field studies have shown that α can be considerably larger
than 0.5, and typically varies between 0.5 and 2.79 with a median of 1.15 2. This means that
11 December 2006
leakage in water distribution systems is much more sensitive to pressure than conventionally
believed. The range of exponents observed reflects substantial differences in the impact of
pressure on rate of leakage. For example, halving the pressure in a pipe will result in
reductions in flow rate of 29 %, 50 % and 82 % respectively for exponents of 0.5, 1.0 and 2.5.
The reasons for the high leakage exponents are not well understood, but an important cause is
believed to be the expansion of the hole opening with increasing pressure 2.
The large influence of the leakage exponent when estimating the potential impact of pressure
management on leakage rate means that it is essential to develop an understanding of the
mechanisms responsible for the observed behaviour. The purpose of this paper is to identify
possible causative factors and, where possible, quantify the effect of these factors on the
leakage exponent. The possible causative factors are discussed under four headings: leak
hydraulics, pipe material behaviour, soil hydraulics and water demand.
The Orifice equation (equation 1) is derived for an orifice in the side of a tank and describes
the conversion of all the potential energy, in the form of pressure, to kinetic energy. The
discharge coefficient is added to incorporate energy losses and the reduction of jet diameter
downstream of the orifice. The pressure in the jet downstream of the orifice is assumed to
equal that of the surrounding fluid.
The hydraulic behaviour of orifices has been researched extensively and can be predicted with
some degree of certainty. The exponent of 0.5 is generally only true for large Reynolds
11 December 2006
numbers (Re). For smaller Reynolds numbers, equation 1 is typically modified by writing the
coefficient c as a function of the Reynolds number. This variable coefficient can also be
expressed as a fixed coefficient with an exponent that is not 0.5. For example, substituting the
expression for laminar flow through an orifice (from 3) into equation 1 results in an equation
with constant coefficient and an exponent of 1. For transitional flow, the equivalent exponent
will vary between 0.5 at the transitional-turbulent flow boundary to 1.0 at the laminar-
transitional flow boundary.
As noted above, the flow regime is determined by the Reynolds number (Re). Flow through
orifices is typically laminar at Re below 10 and turbulent at Re above 4000 to 5000 3. The
Reynolds number for a general leak opening or orifice can be written as:
... (3)
Where v velocity and ψ kinematic viscosity of the fluid, and R the hydraulic radius of the
orifice (defined as flow area A divided by the wetted perimeter P).
Since the kinematic viscosity of a fluid is a function of temperature, it follows from the
equation that the leakage flow rate for a fixed Reynolds number (e.g. for maximum laminar or
transitional flow) and fluid is only affected by two variables: the temperature of the fluid and
the wetted perimeter of the orifice. The viscosity of water approximately halves when its
temperature increases from 0 to 30 ˚C, meaning that the maximum laminar or turbulent flow
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will approximately double. Leak openings with large wetted perimeters (such as cracks) will
be able to sustain much larger laminar or transitional flow rates than circular openings with
the same areas.
It is possible to find an expression for the maximum laminar and transitional flow rates
through different types of leak openings for the typical pressure range in a water distribution
system. First, the flow rate is written as the product of the velocity and area of an opening.
For a circular opening, this is given by:
vDQ 2
Where D the diameter of the leak opening. Writing equation 3 in terms of the hole diameter
and replacing it and equation 1 into equation 4 results in the expression:
... (5)
For a rectangular leak opening with an aspect ratio of n, the expression is given by:
( )
... (6)
If a constant discharge coefficient (say Cd = 0.6) and kinematic viscosity (say ψ = 1.14 x 10-6
for water at 15 ˚C) are assumed, the equations can be used to estimate the maximum laminar
and transitional flow rates that are possible in water distribution networks. Cracks can be
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viewed as rectangular leak openings with high aspect ratios. The maximum laminar and
transitional flow rates for different types of leak openings are shown in Figure 1 for the 10 to
100 m pressure range, which covers the pressures found in most water distribution systems.
The figure shows that cracks can have much higher laminar or transitional flow rates than
round or square holes. This is due to the role of their much larger wetted perimeters. Theory
predicts that the maximum possible flow rates that are fully laminar are typically very small
(e.g. less than 3 l/day even for a crack with an aspect ratio of 10 000) and it is thus unlikely
that substantial losses from water distribution systems will occur in the fully laminar zone.
A distinction is often made between bursts and background leakage. Bursts are large
individual leaks that come to the surface or are found through active leakage control
initiatives. Background leakage comprises numerous small leaks that are very difficult or
impossible to detect without excavating the pipe. In a well-run system, much of a network’s
water loss that we seek to reduce through pressure control may thus result from background
leakage. This view is supported by water leakage figures for England and Wales (about 25
million connected properties) that has been estimated by OFWAT 4 in 2004 to be on average
of the order of 10 m3/km of main/day, or 360 l/h/km of main. Comparing this figure with the
maximum transitional flow rates above indicate that it is possible that much of the
background leakage can occur in this range, especially in systems that are likely to have pipes
that develop crack failures. Transitional flow can thus be an important cause of a leakage
exponent above 0.5 (although not above 1.0) when background leakage is a large contributor
to leakage from a system.
11 December 2006
Pipe material plays an important role in the leakage behaviour of pipes. Water pressure in a
pipe is taken up by stresses in the pipe wall, and thus may be a factor in failure and leakage
behaviour. The following effects can be linked to an increase in the internal pressure of a
Small cracks or fractures that do not leak at low pressures open up to create new leaks.
The area of existing leak openings in a pipe increase due to increased stresses in the
pipe wall.
The frequency of pipe bursts increases 2, 5 with a corresponding increase in
maintenance costs.
Greyvenstein and Van Zyl 6 used an experimental setup to measure the leakage exponents of
failed pipes taken from the field and pipes with artificially induced leaks. The study included
round holes, and longitudinal and circumferential cracks in uPVC, steel and asbestos cement
pipes. All flows were turbulent and leaks were exposed to the atmosphere. The resulting
leakage exponents varied between 0.42 and 2.4 as detailed in Table 1. The main findings of
the study were:
The results confirm that the leakage exponents found in field studies are not
The highest leakage exponents occurred in corroded steel pipes, probably due to
corrosion reducing the support material around the hole. This is contrary to the
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perception that plastic pipes will have higher leakage exponents due to their lower
modulus of elasticity.
Round holes had leakage exponents close to the theoretical value of 0.5 and no
significant difference was observed between steel and uPVC pipes.
Besides corrosion holes, the largest exponents were found in longitudinal cracks. This
is due to the fact that circumferential stresses in pipes are normally significantly
higher than longitudinal stresses.
The leakage exponents for circumferential cracks in uPVC pipes were sometimes less
than 0.5, suggesting that the leak opening might be contracting with increasing
pressure. This is explained by the fact that the experimental setup did not allow
substantial longitudinal stresses to develop in the pipe. It is thought that the
circumferential stresses caused the cracks to elongate, and at the same time reduce in
area. These results have subsequently been verified through finite element analysis 7.
Theoretical expressions for the longitudinal and circumferential stresses in a pipe under
pressure are given in many textbooks (for example, see 8). These expressions show that the
stresses in the circumferential direction are double those in the longitudinal direction. When a
discontinuity such as a hole is present, the pipe wall stresses are increased in the vicinity of
the hole. The circumferential stress in the vicinity of the hole is now written as:
gDhc 2
... (7)
Where σ the pipe wall stress, c' a stress factor, D the pipe diameter, h the pressure head and t
the pipe wall thickness. The stress factor incorporates both the variation in stress around the
11 December 2006
circumference of the hole and the stress concentration factor. Assuming linear elastic
behaviour, the wall stress can also be written in terms of the strain ε and elasticity modulus E:
... (8)
Where d0 the original hole diameter and Δd the change in diameter due to the pressure in the
pipe. Using equations 7 and 8, the hole diameter
d d d= + 
can now be expressed as:
( )
... (9)
Where C is a constant. Substituting the equation for the area of a hole (based on equation 9)
into equation 1 results in the following expression for the leakage flow rate from a circular
hole in a pipe:
1 3 5
2 2 2
0.125 2
q g C d h Ch C h
= + +
... (10)
The relationship shows that the processes involved in the expanding leak opening are more
complex than the simple power relationship normally used to describe leakage. The equation
contains the sum of three terms with leakage exponents of 0.5, 1.5 and 2.5 respectively, which
seem to tie in well with field and experimental observations. However, when calculating the
11 December 2006
leakage from typical pipes using equation 10 it is found that the terms with exponents 1.5 and
2.5 contribute little to the leak under normal pressure conditions.
Due to the material properties, pipes of different materials will fail in certain characteristic
ways. For instance, longitudinal cracks are common in asbestos cement pipes, while steel and
cast iron pipes often leak through corrosion holes. Small-diameter cast iron pipes typically fail
in bending leading to circumferential cracks which, because of the relatively high coefficient
of thermal expansion of the pipe material, may open and close as the temperature of the water
in the system changes. Understanding the failure behaviour of pipes and the associated
leakage exponents can assist with modelling the response of a given distribution system to a
change in pressure and in better managing leakage reduction programmes.
A simplistic application of geotechnical seepage theory would suggest, in contrast to equation
(1), that if head losses through the pipe orifice are neglected, the flow rate should be linearly
proportional to the head of the water in the pipe, h, since following Darcy’s Law, the flow rate
(q) in the soil for a given head on the orifice water/soil boundary will be 13
q = F . k . h ... (11)
Where F is the form factor for the soil flow region, and k is the coefficient of permeability of
the soil. However this equation is underpinned by a number of assumptions, and these are not
generally valid for seepage around a water pipe.
11 December 2006
Firstly, in soil seepage analysis it is generally safe to assume that the velocity component of
total head is very small, and can be ignored. The velocity of flow through soil under a
hydraulic gradient of unity varies from 10-2 m/s for a clean coarse sand to 10-8 m/s and
smaller for clays. Yet in contrast the hydraulics orifice equation (equation 1) predicts very
high velocities at the soil/water interface. There is clearly an incompatibility here, and an
equation for the combined system cannot be properly defined by the straightforward coupling
the orifice equation with the soil seepage equation, as has been previously done 9. Soil
outside the pipe will modify downstream jet behaviour, whilst perhaps also obscuring part of
the orifice itself. The simple Darcy soil seepage equation assumes that there is a fixed
upstream boundary geometry with constant head applied to it but, because of the high orifice
outlet velocity, both the boundary geometry and the head applied to it are likely to be
modified by scour of the soil boundary and fluidisation of the soil. A number of studies have
shown the complexity of these processes 10, 11, 12
Secondly, the downstream boundary conditions in the ground surrounding the pipe are not
generally constant regardless of flow rate. In many geotechnical seepage problems both
upstream and downstream boundaries can reasonably be assumed to have fixed geometries
and head conditions, and the position of any phreatic surface can be assumed fixed. Since
water pipes are generally laid above the ground water level the seepage flow net (and thus F
in equation 10 above) varies as a function of the rate of outflow from the pipe and the
coefficient of permeability of the soil. For any given soil permeability, increasing flow leads
to progressive build-up of pore pressure in the soil around the pipe, and eventual “mounding”
of water above it. For low flow rates relative to the permeability of the soil, seepage will not
11 December 2006
reach the ground surface, and leakage will go unnoticed. At higher rates of leakage water will
emerge at ground surface and a burst will be detected.
Thirdly there are limits to validity of Darcy’s law. A linear relationship between head and
flow in soil is, as observed by Osborne Reynolds in 1883, only valid for laminar flow. The
critical value of Re (expressed in soil mechanics as
, where v is the discharge
velocity (flow per unit cross section of soil), and D is the average soil particle diameter) at
which flow in soil changes from laminar to turbulent has been found to range between about 1
and 10 (for example, see 13) . Discharge velocity depends upon both hydraulic gradient and
permeability (which is itself a function of particle size). Under the low hydraulic gradients
(Δh/Δl << 1) typical of many soil seepage situations laminar flow can be expected in sands
and finer materials, but not in gravels. However the hydraulic gradient around a leaking pipe
will be much larger - water distribution pipes are generally buried at a depth of less than 1m,
and have supply heads of the order of 30 m. Non-laminar flow can therefore be expected in
most coarse granular soils and loose backfills.
Finally, the stress conditions in the ground contribute to the way in which flow takes place.
Calculations of Darcy flow generally assume permeability to be constant, with flow
distributed across the entire region of permeable soil. Considerations of force equilibrium
make it clear, however, that for a particulate material such as soil the maximum water
pressure in the pores between the particles, on any given plane, cannot exceed the (total
stress on that plane. Once the water pressure at any point in the ground rises above the minor
total principal stress (which may be in the horizontal or vertical direction, but is unlikely to
The total stress on a plane in a soil mass is the stress on that plane that arises as a result of external loading and
of the self weight of the soil. This is distinct from the effective stress, which governs the strength,
compressibility and to some extent permeability of soil, and is the numerical difference between total stress and
pore pressure on any given plane.
11 December 2006
exceed 20-30kPa for typical pipe burial depths) then hydraulic fracture takes place. The soil
cracks along planes of weakness, flow occurs preferentially along these cracks, flow rates rise
through orders of magnitude, and conventional seepage analysis is no longer applicable (for
an example see 14). Because of their size, and for the reasons discussed above, flow along
these cracks is unlikely to be laminar. As heads increase, the move from Darcy flow to
hydraulic fracturing can be expected to produce flow increases that contribute to leakage
exponents greater than unity.
Even if the water pressure is not sufficiently high to cause hydraulic fracture, if upward flow
takes place in unbonded granular soil and its velocity become sufficiently great then
fluidisation may occur. “Piping”, as this is known, results when the upward force on the soil
particles resulting from seepage exceeds its buoyant self-weight, and occurs at a hydraulic
gradient approximately equal to unity. Since the particles in the fluidised zone move as an
integral part of the fluid, the overall permeability of the flow region is greatly reduced.
On average, leakage figures for a well-maintained system (such as the England and Wales
estimate of about 0.1 l/s/km of main 4) probably represent a few larger-volume infrequent
bursts combined with a much greater number of continuous but undetected losses from
smaller defects in the network. For example, vertical downward flow (gravitational flow, i.e.
without any development of excess pore water pressure in the soil) from a single 0.1 litre/s
leak would occupy a plan area of only about 10cm x 10cm in gravel, and 1m x 1m in sand,
suggesting that in coarse granular soil leaks will be absorbed without trace by the ground
around the pipe.
11 December 2006
In summary, it can be concluded that the interaction between a leaking pipe and its
surrounding soil is complex, and requires further investigation. The relationship between head
loss and flow is unlikely to be linear, as a result of interaction of soil particles with the orifice,
turbulent flow in the soil, the changing geometry of the unconfined flow regime, hydraulic
fracturing and piping. Theoretical considerations suggest that small continuous leaks from
pipes will drain away without trace into underlying granular soil. This cannot be expected to
occur in lower permeability clays and silts, where hydraulic fracture is more likely, with leaks
rapidly becoming visible as wet patches and bursts at the ground surface.
While water demand is not classified as leakage, it is often impossible to separate legitimate
water consumption from leakage measurements in the field. It is thus important to understand
the behaviour of water demand as a function of pressure. The effect of pressure on demand
Qdem can be expressed as 15:
Q Ch
... (12)
With C a constant coefficient and β the elasticity of demand with respect to pressure. There is
a clear resemblance between equations for leakage (equation 2) and demand elasticity
(equation 12). The elasticity includes the effects of human behaviour, such as reacting to an
increased pressure by opening taps less to obtain the same flow rate. In a study of water
consumption patterns at a student village on the campus of the University of Johannesburg,
Bartlett 16 found the indoor demand elasticity for pressure to be approximately 0.2. Outdoor
water consumption such as garden irrigation is typically time-based rather than volume-based,
meaning that a higher exponent can be expected for outdoor use. The typical exponent for
11 December 2006
outdoor irrigation equipment is around 0.5 5, 16 although soaker hoses were found to have
values as high as 0.75 17.
In large systems it becomes likely that even minimum measured night flows will include
some legitimate consumption. Since the combined ‘leakage exponent’ for outdoor and indoor
consumption is likely to be less than 0.5, it may be concluded that measured leakage
exponents in systems with demand are likely to underestimate the true leakage exponent of
the system, provided that the level of demand in the measured night flows do not differ
The leakage exponent determined from field studies differ significantly from the theoretical
orifice exponent of 0.5. The purpose of this paper has been to identify and analyse factors that
may be responsible for the range of leakage exponents observed in the field. Leak hydraulics,
pipe material behaviour, soil hydraulics and water demand were considered as possible
causative factors. It is concluded that a significant proportion of background leakage can
consist of transitional flow, and thus have a leakage coefficient value above 0.5 (although not
above 1). Both experimental and theoretical investigations indicate that pipe material
behaviour can provide one explanation for the observed range of leakage exponents.
The interaction between a leaking pipe and its surrounding soil is complex, and flow rates are
unlikely to be a linear function of pressure, as a result of interaction of soil particles with the
11 December 2006
jet and the orifice, turbulent flow in the soil, the changing geometry of the unconfined flow
regime, hydraulic fracturing and piping. Finally, if water demands are present in minimum
night flows, the resulting leakage exponent is probably an underestimate of the true value.
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Leakage Relationship of Some Failed Water Pipes, Journal of Water Supply: Research
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under pressure, 2006, Master’s degree thesis, Department of Civil Engineering Science,
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Understanding the hydraulics of water distribution system leaks. Proc. 6th ASCE/EWRI
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Research thesis, Department of Civil Engineering, University of Queensland, Australia.
11 December 2006
Table 1. Leakage exponents found in an experimental study by Greyvenstein 6
Failure type
Leakage exponent for pipe material
Asbestos cement
Mild steel
Round hole
Longitudinal crack
1.38 1.85
0.79 1.04
Circumferential crack
0.41 0.53
Corrosion cluster
0.67 2.30
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10 20 30 40 50 60 70 80 90 100
Pressure Head (m)
Flow rate at the limit (l/h)
Round Square
Rectangular (aspect ratio 100) Rectangular (aspect ratio 10 000)
Transitional flow limits
Laminar flow limits
Fig 1. Maximum laminar and transitional flow rates for different types of leak openings
... To explain the variation in the leakage exponent found in field tests, van Zyl and Clayton (2007) proposed four factors that may explain the observed range of leakage exponents: leak hydraulics, pipe material behaviour, soil hydraulics and water demand. Pipe material behaviour, i.e. material strain resulting in varying leak areas, was the main factor responsible for the observed behaviour. ...
A pipe condition assessment device (PCAD) was developed to detect, characterise leakage and assess the condition of water distribution networks (WDN). In this study, the reliability and repeatability of the device results were established by first characterising known leak types on pipe sections using a standardised method. Then, three manufactured leak types were tested, with each leak tested ten times. These tests were then repeated using the PCAD and showed that the PCAD could produce results comparable to laboratory-acquired results within a 95% confidence interval. Field tests conducted in a real network revealed that the PCAD could detect and identify leakage characteristics in water networks.
... The abnormality of leakage exponents requires further theoretical clarification. This relationship can be affected by the leak hydraulics, pipe material behavior, soil hydraulics, and user demands (Zyl and Clayton, 2007). Among them, the effect of soil on leakage flow-pressure remains controversial. ...
The assessment and control of the real losses from water distribution systems require the accurate estimation of the flow rate from an individual leak as a function of the internal pressure. The lack of analytical models able to accurately describe the relationship between the area of the leak and the pressure head is the key problem. This paper utilized the linear-elastic fracture mechanics (LEFM) theory for thin shells to derive models for both longitudinal and circumferential cracks. The models were validated by both finite element (FE) simulations and laboratory experiments under varying crack and pipe parameters. Both fluid-structure interaction (FSI) and traditional FE simulations were performed, and the results were compared to quantify the effect of leakage hydraulics on leak area. In the laboratory experiments, an image analysis technology was utilized to measure the leak area and flow rate simultaneously, so that the effect of the discharge coefficient could be excluded. In addition, the leak area was systematically measured under the effect of different parameters. The results revealed that the values predicted by the derived models were in good agreement with the experimental and FE simulation values for both types of cracks. The LEFM theory and the phenomena observed in this study can improve our understanding of the leak behavior and enable the development of effective pressure management strategies for water distribution systems.
... where, NRW = Non-Revenue Water, SIV = System Input Volume, and BAC = Billed Authorized Consumption During the field visit, utility statistics related to average leak flow, number of reported bursts, and average leak duration were also observed. The physical loss in the mainline was analyzed based on available data, and it was accepted by taking into account the system of minimum annual physical loss, known as the unavoidable annual real loss (UARL) [27,29]. The following is how UARL would be calculated. ...
Full-text available
The existing water distribution system was insufficient for all parts of the study town due to rapid population growth, hydraulic performance issues, and water quality of Dangila town. The main objective of this study was to evaluate the hydraulic performance modeling of water distribution systems and physicochemical water quality analysis of Dangila town using WaterGEMS and on-site and off-site water quality analyses. Sampling sizes of physicochemical water quality analysis were 240 at twelve distribution network stations from different pipes, high- and low-pressure zones using systematic random sampling techniques. The results of this study indicate that the water loss of the systems is 34%, which is very high. However, the average daily per capital water consumption was 18.1 l/c/d and the level of connections per family was 41.4%. Simulation of existing water distribution systems at nodes and pipes have 19% and 28.7% of lower pressures and velocities during peak hourly consumption, respectively. Hydraulic performances of distribution systems were evaluated by calibration and validation models of pressure, tank level, and link flow. The values of R² during calibration and validation of pressure, tank level, and link flow were 0.98, 0.96, and 0.988%, respectively. The results of all physicochemical water quality parameters were within the acceptable limits of WHO and Ethiopia standards, except turbidity, total dissolved solid, and residual chlorine from some station during the dry and wet seasons. In general, the results of this study indicated that simulation of the hydraulic performance of existing distribution networks and water quality were inadequate.
... Regardless of the water scarcity, it is shocking that in developing countries, especially in sub-Saharan Africa, the rate of water loss and non-revenue water (NRW) is high [3]. High NRW is mostly caused by leakages in the water distribution network (WDN), which sometimes exceed more than 70% of the total NRW [4,5]. Leakages are frequent in the WDNs in these regions because the pipes transporting water to the user's premises are usually installed by the users themselves. ...
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Water is a basic necessity and one of the most valuable resources for human living. Sadly, large quantities of treated water get lost daily worldwide, especially in developing countries, through leaks in the water distribution network. Wireless sensor network-based water pipeline monitoring (WWPM) systems using low-cost micro-electro-mechanical systems (MEMS) accelerometers have become popular for real-time leak detection due to their low-cost and low power consumption, but they are plagued with high false alarm rates. Recently, the distributed Kalman filter (DKF) has been shown to improve the leak detection reliability of WWPM systems using low-cost MEMS accelerometers. However, the question of which DKF is optimal in terms of leak detection reliability and energy consumption is still unanswered. This study evaluates and compares the leak detection reliability of three DKF algorithms, selected from distributed data fusion strategies based on diffusion, gossip and consensus. In this study, we used a combined approach involving simulations and laboratory experiments. The performance metrics used for the comparison include sensitivity, specificity and accuracy. The laboratory results revealed that the event-triggered diffusion-based DKF is optimal, having a sensitivity value of 61%, a specificity value of 93%, and an accuracy of 90%. It also has a lower communication burden and is less affected by packet loss, making it more responsive to real-time leak detection.
... Liemberger and Wyatt (2019) estimated global water loss at 126 billion cubic metres, costing a massive US $39 billion annually. Leakages represent 70% of the water losses (Zyl and Clayton 2007); therefore, leak management in WDNs has been a research topic of interest, especially since the release of the International Water Management Institute (IWMI) report in 1988 stating that "45 countries accounting for 33% of the world's population will suffer from water scarcity by 2025" if proper measures are not taken (El-Abbasy et al. 2016). Besides water scarcity, increasing plant operating costs and diminishing water quality as a result of pipeline leakages also contributed towards the increasing research focus on water-leak management (Guo et al. 2021). ...
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Leakages in water distribution networks (WDNs) cause economic losses and environmental hazards. It is, therefore, unsurprising that water-leak management has been a focus of research over the last couple of decades, but leaks in WDNs still occur frequently. Thus, this domain is experiencing a transformation from traditional signal processing and statistical-based models to artificial intelligence (AI) based models for recognizing complex leak patterns, handling large datasets, and establishing accurate leak-management models, especially in leak detection and localization. However, a comprehensive review of the application of AI in water-leak management is largely missing from the literature. To bridge this gap, this review presents a criteria-based critical review to systematically investigate the existing literature on the application of AI in four sub-domains of leak management including leak detection, localization, prediction, and sizing. The first criterion (research attributes) established the (1) research trends, (2) links between influential countries and sources, and (3) popular keywords using scientometric analysis. The systematic analysis of the second criterion (research technicality) and the third criterion (research focus) revealed the (1) AI-techniques adopted, (2) equipment used for collecting data, (3) data features used in the models, (4) objectives of different models adopted, (5) type of experiments conducted to collect the data, and (6) types of pipes for which models were developed. The study highlighted research gaps, future research directions, and proposed a leak management framework for upcoming AI studies in this domain. This review is intended to serve early researchers by enhancing their understanding of existing research in AI-based leak management as well as seasoned researchers by providing a platform for future research.
... Leaks can cause water transmission networks to lose between 20% and 30% of the transported water (Cheong, 1991); in some undermanaged systems, this number can increase to 50%. A water loss value of 70% was also recorded under poor management and maintenance conditions (AWWA, 1987;Shabangu et al., 2020;Van Zyl and Clayton, 2007). According to the World Health Organization (WHO), the impact of leaks does not stop on the level of water networks, and it plagues buildings as well (World Health Organization, 2011). ...
Modern water networks from municipal network to building networks are plagued with the threat of leaks. Leaks create a significant amount of loss of resources. Pressurized water pipelines are more susceptible due to the high pressure at which water travels. Multiple researchers have tried to utilize a variety of static (devices that are left in the network) and dynamic (devices that are mobilized to the suspected location) leak detection techniques to ensure the early detection and pinpointing of leaks in water transportation networks. The main goal is to provide quick and efficient tools that can identify and pinpoint leaks in buildings while being cost-effective. This article proposes a small-scale experimental static real-time monitoring system that can identify leaks and their location with high accuracy by measuring vibration signals via wireless accelerometers. The experiment utilizes one-inch and two-inch Polyvinyl Chloride (PVC) and iron pipelines, which are commonly used in residential buildings. Since the proposed system is static, the wireless accelerometers are placed on the exterior walls of the pipelines. The vibration signals, derived from each accelerometer, were calculated and analyzed. A leak is identified when a spike in the signal is detected. Once a leak was identified, the model would move to determine the source of the signal, that is, the leak location. The developed models proved to be capable of accurately pinpointing leaks within an accuracy of 25 cm. The main techniques that were used in model development were regression analysis and backpropagation of artificial neural networks models.
Reasons such as rapid population growth, urbanization, unconscious water use, environmental pollution, and changes in climate conditions increase water consumption, and water is consumed before completing its cycle in nature. This situation has directed the water producers to search for new resources in the face of increasing water demand and decreasing resources, but due to the high cost of the resource search, the water producers have turned to the understanding of reducing the high amounts of lost water and using water resources in a more planned and efficient manner. Minimizing water losses in drinking water distribution networks is among these objectives. In this study, drinking water data between January 2014 and January 2020 in Erzincan was examined, and the SCADA (Supervising Control and Data Acquisition) system placed in the drinking water distribution network in March 2018 was evaluated by considering the pre and post-drinking water data in the system. First of all, the terms between January 2014 and March 2018 which means before the installation of the SCADA system were examined, the data of the amount of water produced and the data of water consumed by the subscribers was collected from the Municipal Waterworks Unit, these data were transferred to the Water Balance Table, the results was analyzed and the actual water loss rates in the system were estimated. As a result of this estimation, before the SCADA system was established, the total physical and administrative water loss rate was seen as 64%, while the physical water loss rate was 28%. After the establishment of the SCADA automation system after March 2018, the date of the amount of water produced received from the SCADA system and the amount of water consumed was transferred to the Water Balance Table and the total physical and administrative loss was seen as 37% while the physical water loss rate was 14%. According to these results, it was observed that the water loss rate approached the minimum level within a short period with the SCADA automation system.
Leakage in water distribution systems accounts for a significant portion of total supplied water, up to 30% in certain Canadian cities. This has attracted a lot of attention from professionals in this field to develop effective methods to reduce water loss via leakage. The present study proposes a method using data of pressure and flow sensors, and support vector machines (SVMs) to detect if there is a leak at each time. The main objective of the SVM is to find a hyperplane that distinctly classifies the network nodes into two groups, leaking and non-leaking. Classes are identified based on pressure measurements at pressure sensors and flow values collected by flow monitors. Historical information about when and where leakage occurred is also required to train the SVM. When pressure sensors are close to a leak, measurements are expected to become abnormal. The proposed method is being applied to the hypothetical L-Town example network. High accuracy is found for the model predictions.
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Water is a finite resource and should be given the attention it deserves to reduce its depletion through leakages in pipe systems. The authors implemented pressure management strategies linked to fixed and variable discharge (FAVAD), the burst and background estimate (BABE), and orifice principle methodologies to analyze a two-phased comparative method for applying optimal pressure management and its efficiency indexes in measuring volumetric cost performance, consumption, leakage flowrate, linear leakage reduction, infrastructural leakage and leakage cost indices. Using time-modulated smart control pressure reducing valve (PRV) simulation processes, the authors selected Alexandra Township in Johannesburg, South Africa as a case study. The results showed a reduction in head pressure, a reduction in the system input volume (SIV) from 26,272,579 m3 to 21,915,943 m3 and a reduction in minimum night flow (MNF) from 14.01% to 12.50%. The annual estimated nodal system output (NSO) was reduced from 14,774.62 m3 to 12,787.85 m3. The monthly average linear system repairs were reduced from 246 to 177, while the efficiency index percentages of leakage frequency/km/pressure were reduced from 8.31% to 5.98%. At a unit cost of $3.18/m3, the cost of leakages declined from $4,009,315.54 to $2,862,053.10 per month, while average household consumption (AMC) reduced from 36.33 m3 to 24.56 m3. Finally, the linear reduction value R2 for the percentage of the total leakage flowrate (TLFR)/SIV declined from 0.58 to 0.5, whereas the infrastructure leakage ratio (ILI) increased from 4 to 4.3. The results fully demonstrated that optimal pressure management is an alternative way to simulate, estimate, quantify and understand where and how water is lost in a distribution system. The authors propose that the implementation of proactive leakage management and domestic background leakage repair could further assist in reducing the frequency and cost of water leakages.
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This study presents the potential of integrating Hydrams in modern water distribution systems (WDSs) for managing excess pressure and reducing energy costs. Hydrams, which are also termed Hydraulic ram pumps in the literature, is a cyclic water pump powered by hydropower, generally used to pump drinking and irrigation water in mountainous and rural areas having short of power. The Hydrams is introduced as a sustainable low-cost alternative solution to the more conventional pressure reducing valves (PRVs) approach for managing pressure zones in WDSs. Unlike PRVs, where the pressure is lost and not put into good use, Hydrams mitigate excess pressure at high-pressure zones and direct it to much-needed low-pressure zones. In addition, Hydrams are cheap, simple, environmentally friendly, and require little maintenance. The proposed approach integrates a Hydram in parallel to the original centrifugal pump, where they can be operated interchangeably according to the system’s hydraulic needs. Nevertheless, it is vital to correctly size the Hydram at the feed line and accompany it with a proper storage tank at the low-pressure zone. The storage tank serves as a buffer between the intermittent water supply and consumer demand pattern. Moreover, the tank introduces flexibility into the system that allows more sustainable operating schedules. Two case study applications of increasing complexity are presented to demonstrate the potential of this Hybrid system, later referred to as Hybrid Pumping Unit (HPU). The Hydram and tank sizing is done by a simple heuristic approach, while the operation of the system is dictated by a genetic algorithm. The results demonstrate the potential of integrated Hydrams in reducing excess pressures and energy costs.
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Investigations have been conducted of in situ (unbounded) fluidisation produced by a vertical jet acting internally within saturated sands. This produces a sharply defined in situ fluidised zone, which changes with increasing jet depth from an open, axisymmetric, approximately ellipsoidal form to an asymmetric, spouted profile, and thence to a submerged fluidised cavity. Measurement and dimensional analysis of fluidised zone geometries indicate in situ fluidisation to be controlled by two mechanisms: (i) scour below the jet tip, which follows the linear velocity decrease of a submerged jet; and (ii) the ability of the flow to maintain fluidisation, which controls the zone diameter. The depth of fluidised cavity formation is shown to be a function of the ratio of the flow rate to that required for minimum (turbulent) fluidisation. The observations are justified in terms of jet diffusion, sediment transport, fluidisation and slope stability theory.
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End-use water demand modelling is used to generate water demand projections by modelling various end uses, for example showers, toilets and washing machines. End-use models can be used to estimate water demand changes due to various scenarios, such as price increases, housing densification and conservation programmes. This study reports on the potential application of end-use modelling in South Africa, based on a pilot study that was done for Rand Water. The model includes elasticities of water demand with respect to variations in water price, household income, stand size and pressure. The study highlights many of the difficulties and limitations, as well as the potential applications of end-use modelling as a water deman predictor. A special effort is made to explain the meaning and application of elasticity in end-use modelling. Various data sources were used to determine elasticities for the variables used, and to identify minimum and maximum elasticity values. The implications of the elasticities are illustrated using a sensitivity analysis and case study.
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The results of pressure management field studies have shown that the leakage exponent is often considerably higher than the theoretical orifice value of 0.5. The first part of this paper identifies and analyses factors that may be responsible for the higher leakage exponents. Four factors are considered: leak hydraulics, pipe material behaviour, soil hydraulics and water demand. The second part of the paper presents the results of an experimental study with different pipe materials. The pipes used were taken from the field in Johannesburg or consisted of new pipes with artificially induced failures. The leakage exponents found were in the following ranges: • Asbestos-cement pipe with longitudinal crack 0.78 - 1.04
Since the 1991 IWSA International Report on “Unaccounted for Water and the Economics of Leak Detection”, the topic of management of water losses in distribution systems has received increased attention. This International Report seeks to present an overview of the “state of the art” in management of Water Losses, based on the Reports prepared by National Rapporteurs, the recent recommendations of the IWA Task Forces on Water Losses and Performance Measures, and improved concepts for modelling components of leakage and pressure: leakage relationships. The IWA Task Force recommendations provide overdue clarification and guidance on several issues that have caused persistent problems in quantifying Water Losses and comparing the effectiveness of their management. It is hoped that this Report will assist in the promotion of a more standardised international approach to the definition, assessment, monitoring and management of Non-Revenue Water and Water Losses.
This technical note discusses an experimental study on the erosion of sandy beds by submerged circular impinging water jets. It concludes that there are similarities between the air-sand system and the water-sand system, but there are also significant differences regarding the depth as well as the radial extent of the scour hole. (A.B.)
A soil parameter is developed based on concepts from local scour studies of non-cohesive and cohesive soils and the results of a site-specific submerged jet testing device. Submerged jet test results on four soils with a range of physical conditions are analyzed. The submerged jet had a nozzle diameter of 13 mm, and was set at a jet height of 0.22 m prior to testing the soil. The soils were tested over a range of jet velocities at the nozzle of 166 cm/s to 731 cm/s. The results indicate that erosion, expressed as the depth of scour divided by time, in the site-specific submerged jet testing device may be related to the jet velocity, a time function, and a soil parameter (jet index, Ji). The jet index is intended to provide a common method of expressing erosion resistance, to assist those who work with different soils and soil conditions for measurement and design, and possibly to develop performance and prediction relationships for earthen spillways.
Field studies at the Dead Sea, Israel, and in Oslo have indicated that serious errors may be introduced in estimating the permeability of fine-grained clay soils using in situ tests if excessive water pressures are used, a fact already appreciated by rock and petroleum engineers. Model laboratory tests in London have confirmed that very low pressures must be employed and a mathematical analysis has been developed to indicate the factors which influence the allowable pressure. By inducing fracture the existing stresses in the ground may be estimated. Des études sur place, effectées dans la Mer Noire, en Israel, et à Oslo, ont montré que l'on peut introduire de graves erreurs dans l'estimation de la perméabilité des sols d'argile à grains fins en se servant d'essais in situ au tours desquels la pression d'eau est excessive, un fait expérimental qui a déja été démontré par les spécialistes en mécanique des roches et an génie du pérole. Des essais sur modèle au laboratoire, à Londres, ont confirmé que l'on doit employer de très basses pressions et on a développé une analyse mathématique qui permet d'étudier les facteurs qui influencent la pressionpermissible. On peut également estimer les contraintes existant dans le sol en créant des fractures.
The second, revised edition of this comprehensive handbook by one of the leading experts in the field of hydraulic engineering has been completely updated and will be a valued addition to the literature. Partial Contents: General Information and Elements of Aerodynamics and Hydraulics of Pressure Systems; Flow in Straight Tubes and Conduits; Flow at the Entrance into Tubes and Conduits; Flow through Orifices with Sudden Changes in Velocity and Flow Area; Flow with a Smooth Change in Velocity; Flow with Changes in Stream Direction; Merging of Flow Streams and Division into Flow Streams; Flow through Barriers Uniformly Distributed over the Channel Cross Section; Flow through Pipe Fittings and Labyrinth Seals; Flow Past Obstructions in a Tube; Flow at the Exit from Tubes and Channels; Flow through Various Types of Apparatus.