SIMULATION OF PRESSURE VARIATIONS WITHIN KIMILILI WATER SUPPLY SYSTEM USING EPANET

International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308 (Print),
ISSN 0976 – 6316(Online), Volume 6, Issue 4, April (2015), pp. 28-38 © IAEME
28
SIMULATION OF PRESSURE VARIATIONS WITHIN
KIMILILI WATER SUPPLY SYSTEM USING EPANET
CHRISTOPHER BWIRE1,
RICHARD ONCHIRI2
, NJENGA MBURU3
1
Post Graduate Student, Masinde Muliro University of Science and Technology, Department of Civil
and Structural Engineering, P.O.Box 190-50100 Kakamega
2
Lecturer, Masinde Muliro University of Science and Technology, Department of Civil and
Structural Engineering, P.O.Box 190-50100 Kakamega, Kenya
3
Lecturer, Dedan Kimathi University of Technology, Department of Civil and Structural
Engineering, P.O.Box 657-10100 Nyeri, Kenya
ABSTRACT
Water Supply system is a system of engineered hydrologic and hydraulic components which
provide water supply for domestic use, industrial purposes, fire fighting and so on. The system
comprises of intake structures, treatment units, storage tanks and distribution systems. A well
designed water supply system is meant to operate optimally such that consumers have access to
portable water of sufficient pressure and quality at all times. However during operations of water
supply systems, cases of pressure drops, Leakages and contamination occur and the main challenge
is the lack of a simple tool to accurately predict zones of low pressures and areas where quality is
compromised. This study will investigate the operations of Kimilili Water Supply system in
Bungoma County in terms of pressure Variations from the Treatment Works to the consumer points.
The main objective of the study is to simulate pressure variations in the distribution system using
EPANET software and Compare with measured data in the field. The EPANET programme analyses
the pressure at each node, track the flow of water in each pipe and height of the Water in each tank
during simulation period. After simulation of the whole Water Supply system, results were presented
in various forms and compared with the field measured data using pressure loggers. Simulated water
pressure did not vary significantly with the actual values indicating that the pipes still had their
hydraulic capacities even though some sections of the network need augmentation.
Keywords: Hydraulic Simulation, Water Pressure, Pressure Variation, Nodes, Pressure Logger
INTERNATIONAL JOURNAL OF CIVIL ENGINEERING AND
TECHNOLOGY (IJCIET)
ISSN 0976 – 6308 (Print)
ISSN 0976 – 6316(Online)
Volume 6, Issue 4, April (2015), pp. 28-38
© IAEME: www.iaeme.com/Ijciet.asp
Journal Impact Factor (2015): 9.1215 (Calculated by GISI)
www.jifactor.com
IJCIET
©IAEME

29
1. INTRODUCTION
A water supply system consists of source, treatment, distribution and storage facilities whose
main function is for domestic water supply, industrial as well as fire fighting purposes. A water
distribution network is composed of a number of links connected together to form loops or branches.
The links are composed of pumps, fittings and valves. Links have constant flow with no branches.
Water supply systems have also nodes which are basically end points of the pipe where two or more
links are joined. Water distribution network analysis follows the continuity equation where the
algebraic sum of flow rates in the pipes meeting at a node together with any external flows is zero.
The water supplied by a municipal water supply system meets the three levels of usage as follows
a) The average daily demand which reflects the amount of water used per day and does not
consider occupancy differences such as commerce and industry
b) The maximum daily consumption which reflects the day within a year long period on which
the consumption was highest. This figure is approximately 150% of the average daily demand.
c) The instantaneous flow demand which represents peak flows i.e when consumption is highest
between 7 a.m -9a.m and between 5p.m and 7p.m. During the peak period the flows can reach
as high as 225% of the average daily demand [8].
It is therefore imperative that municipal water supplies are able to deliver these flows thus the
need to have a more predictive tool to depict the same. During design of water distribution systems,
it is vital to consider the projected lifespan of the system (design life), per capita water demand, the
relationship between average and peak demands and the allowable system pressure and flow
velocities. These parameters are crucial for the efficient operations of the systems. Due to their
design nature, water distribution systems include areas of vulnerability where contamination can
occur. Dead ends in the system result into low pressures and high water age thus they should be
always eliminated in distribution systems [1, 8, 12]. Water traversing the distribution system gets
into contact with a host of materials, some of which can significantly change the quality of water.
Corrosion, valves and fixtures degradation can cause contamination thus degradation of water quality
[2, 15, 17].
Pipes within a distribution system are commonly designed on the basis of average rather than
maximum hourly demands which results in considerable lower investments costs and a reasonable
compromise on reliability. Storage facilities enable water distribution systems meet demand when
treatment facility is idle or unable to produce the demand. It is more advantageous to provide several
smaller storage units at different parts of the system than to provide an equivalent large capacity at a
central point within the system. The best economical arrangement is to have storage at full capacity
at night when demand is less and increase when it falls to 50% during the day [3]. Storage equalizes
demand on supplies, transmission and distribution mains, resulting in smaller facilities than would be
required if there were no storage. It also balances system pressures as well as provides reserve for
emergencies.
1.1 Causes of Pressure Variations in Water Distribution systems
Water pressure in a distribution system can be described by static water pressure, dynamic
water pressure and water flow rate. Water pressure in a system can be lost due to the following
factors:
i) Number of plumbing fixtures being run at once: With a municipal water supply as well as
private well water supply systems, the building water pressure seen at any individual plumbing
fixture will vary depending on how many fixtures are being run. We tend to see this effect
more on private well water systems where the total water supply system flow rate may be more
limited.

30
ii) Variation in municipal water delivery pressure: the municipal water system pressure may vary
in the street as well as a function of level of water use in the whole community or when work is
being done on the system.
iii) Water pipe diameter, length, elbows and bends: Water flow rate in a building also depends on
the diameter, length, and number of bends or valves in the piping system. And if water pipes
become clogged with mineral deposits or debris, the water flow rate will diminish in the
building, even if the static water pressure remains high.
iv) Clogged water pipes reduce water flow rate, not water pressure.
v) Variations in building occupancy levels: Where building demand for water flow varies widely,
a single pressure reducing valve may not be able to handle the maximum water demand flow
rate. This condition occurs at buildings where there is a large water supply main to an
apartment or office building whose water demand can vary.
vi) Water filter clogging: Rapid sand filtration units may become clogged if they are not
backwashed regularly. This reduces the flow within the delivery pipes.
1.2 Instruments for examining Pressure variations
Pressure variations in a water distribution system can be examined using pressure data
loggers. One example is the Extech SD750 Three Channel Pressure Data Logger.
1.3 Overview of previous studies
Simulation of hydraulic parameters for Water Supply networks has been undertaken using
EPANET by various studies. This is because EPANET is public domain software which is stand
alone and can be accessed by public. The other software are expensive and have limited license
period. Most studies on hydraulic modeling using EPANET have concerned themselves with
pressure losses at nodal points and at valves and fittings. Others have also attempted to model water
quality as well as pressure driven demand within the network [4, 9, 10]. These studies indicated that
EPANET can be a useful tool in the efficient management of water supply systems but they were
concerned majorly with pressure at nodes based on demands.
Kristin Brown undertook modeling of leakage in water distribution network in 2007 at
Florida State University. In the study, WATERCAD was used to model water quality under steady
state analysis. The study recommended future research using other transient softwares that can show
the relationship between water quality and pressure variations.
In another study by Saheb Mansouri for his thesis in civil engineering at the University of
British Columbia in March 2013 titled” contaminant intrusion in water distribution systems” , it was
concluded that contaminant intrusion results due to leakages. The studies recommended future
research using a model that can show an interaction between low pressures and contaminant
ingress.This study therefore builds on such studies but brings in the concept of pressure transients i.e
variations in pressure in all the zones of a distribution system. It is a more detailed extrapolation of
nodal simulation. Other models have also simulated water quality in distribution systems using
EPANET where water quality parameters have been followed throughout the system [6]. This study
focused on how water quality parameters vary within the distribution system. It did not study if there
was any relationship between pressure variations and water quality.
In 2007, Mosab Elbashir undertook a study on Hydraulic Transient in a pipeline at Lund
University. Using FORTRAN programme to simulate transients as a result of changes in operations
of pumps, it was concluded that transients in a pipeline result in water hammer thus affecting water
quality and pressure.Also in March 2011,at De Montfort University in Leicester, Hossam Saleh
carried out a study on Pressure, Leakage and energy management in water distribution systems. The
study investigated interaction between demand and different times and pressure within the network

31
This study therefore seeks to improve on the previous studies and evaluate if water quality is
compromised in a distribution system as a result of pressure variations.
1.4 Hydraulic Modeling
Design of surface water supply system concerns the locations and capacities of diversion
works and storage, as well as operation of these to meet multiple purposes and objectives. Therefore
it is imperative that water supply schemes are designed and operate in a more useful way to meet
system requirements [5,11]. The network system must be modeled, analysed and its performance
evaluated under various physical and hydraulic conditions. This is called simulation and can be done
using computer programmes.
Several computer programmes are available for modeling including KYPIPE, WATERCAD,
EPANET and HYDROFLOW. They are all similar in operation as they depend on input variables
such as demand, pipe flows, sizes, pressure heads etc. Other models have also simulated water
quality in distribution systems using EPANET where water quality parameters have been followed
throughout the system [6,14]. This study focused on how water quality parameters vary within the
distribution system. It did not study if there was any relationship between pressure variations and
water quality. This study therefore seeks to improve on the previous studies and evaluate if water
quality is compromised in a distribution system as a result of pressure variations.
EPANET models a water distribution system as a collection of links connected to nodes.
Junctions are points where links join together or where water enters or leaves the network. The
model requires elevation, usually the mean above sea level, water demand, velocity and initial water
quality and it outputs hydraulic head, pressure, flow and water quality for each node. Junctions can
have varying demand, multiple categories of demand assigned; have negative demand where water is
entering the networks [7].
Reservoirs are nodes that represent an external source of water to the network. They model
lakes, rivers and ground water aquifers. The input parameters are hydraulic head and water quality.
Tanks are nodes that have storage capacity where the volume stored can vary with time during
simulation. The input parameters are the bottom elevation where the water level is zero, the
diameter, the maximum and minimum water levels.
Pipes are links that convey water from point to the other within the network. EPANET
assumes that pipes flow full all the time. Water flow from higher hydraulic head end to the lower
hydraulic head end. The hydraulic input parameters for pipes are start and end nodes, diameter,
length, roughness coefficient and status. The model computes and generates the flow rate, velocity,
head loss and the Darcy Weisbach friction factor [7,13].
Pumps are links that impart energy to a fluid, thereby raising its hydraulic head. The input
parameters are the start and end nodes and the pump curve which represents the combination of
heads and flows that the pump can produce. Valves are links that limit the pressure or flow at a
specific point in the network. The input variable parameters are start and end nodes, diameters,
setting and status. EPANET outputs flow rate and head loss.
Other non physical components of EPANET are curves, patterns and controls that describe
the behavior and operations of a distribution system. Curves contain data describing a relationship
between two variables. For example pump curves represent the relationship between head and flow
rate that a pump can deliver. Time patterns represent a set of multipliers that can be applied to a
quantity to allow it to vary with time. They can be used to model demands at nodes, reservoir head
etc. the control inputs to the software may be simple or rule based. Simple controls change the status
of a link based on water level in the tank, time of day, time into a simulation or pressure at a junction
and there is no limit to the number of simple controls. Rule based controls allow for link status and
settings based on a combination of conditions that might exist in the network after an initial

32
hydraulic state of the system is computed. For example a set of rules that shut down a pump and
opens a bypass valve when the level in the tank exceeds a certain level.
EPANET’s hydraulic simulation model computes junction heads and link flows for a fixed
set of reservoir levels, tanks levels and water demand over a suction of points in time. These
parameters are updated from one time step to another according to prescribed time patterns, while
tank levels are updated using the current flow solution.
The solution for head and flows at a particular point in time involves solving the conservation
of flow at each junction and the head loss relationship across each link in the network through a
process called hydraulic balancing. The process uses an iterative technique to solve the non linear
equations involved. The hydraulic time step for the extended time simulation is set by the user with
one hour being the default.
2. MATERIALS AND METHODS
Kimilili Water Supply network is divided into 5 zones for purposes of smooth operation and
maintenance. Pressure and flow measurements were carried out at each of the 33 nodes representing
the 5 different zones. The measurements were done during peak periods (5am-8am), (12.00-200) pm
and (5-9pm) which corresponded to the simulation period. This period was used as it represented
critical water consumption hours when consumers are either preparing for work in the morning,
preparing for lunch or are back in the evening and preparing for dinner. Measurements were done
using Ultrasonic Flow meter (Portaflow C) type FSC-1/FLD1.
The following was the general procedure used for pressure and flow measurement process at all the
selected points within the 5 zones of the distribution system.
• Power the Portaflow device on
• Input pipe specifications i.e. outer diameter, pipe materials and wall thickness
• Input fluid properties i.e. type of fluid and viscosity
• Enter the name of the site where measurement is being performed
• Outer diameter of the pipe ranges from 13mm to 6000mm, wall thickness ranges from 0.1mm
to 100mm
• Enter lining material for the pipe i.e. tar epoxy, mortar, Rubber, Teflow, Pyrex glass, Pvc etc
• Select sensor monitoring method V or Z method. V method is generally selected (for
diameters upto 300mm) while Z Method is used where ample space is not provided, high
turbidity occurs, there is weak receiving waveform and thick scale is deposited on the pipe
internal surface.
• Select the kind of sensor i.e. FLD12/FSD12
• Select the location for mounting the detector which should meet the following conditions:
• There is a straight pipe portion of 10D or more on the upstream side and that of 5D or more on
the downstream side
• There are no factors to disturb the flow (such as pump and valve) within about 30D of the
upstream side. (JEMIS-032)
• Pipe is always filled with fluid. Neither air bubbles nor foreign materials are contained in the
fluid.
• There is an ample maintenance space around the pipe to which the detector is to be mounted
• Avoid mounting the detector near a deformation, flange or welded part of the pipe.
• For a horizontal pipe, mount the detector within ±45° of the horizontal plane. For a vertical
pipe, it can be mounted at any position on the outer circumference

33
• Mount sensor: wipe off contaminates from the transmitting surface of the sensor and sensor
mounting surface of the pipe. Apply the silicone grease on the transmitting surface of the
sensor while spreading it evenly. Film thickness of silicone grease should be about 3mm.
• Start measuring: when wiring, piping settings and mountings of the sensor are completed, start
the measurement. The contents displayed on the measurement screen are; instantaneous flow,
instantaneous flow velocity, integrated flow rate, analog output and analog input.
Sample Display on the Portaflow-C device
Hydraulic Modeling
EPANET’s hydraulic simulation model computes junction heads and link flows for a fixed
set of reservoir levels, tank levels, and water demands over a succession of points in time. From one
time step to the next reservoir levels and junction demands are updated according to their prescribed
time patterns while tank levels are updated using the current flow solution.
The solution for heads and flows at a particular point in time involves solving simultaneously
the conservation of flow equation for each junction and the head loss relationship across each link in
the network. This process, known as “hydraulically balancing” the network, requires using an
iterative technique to solve the nonlinear equations involved. EPANET employs the “Gradient
Algorithm” for this purpose.
The general procedure for running a hydraulic simulation model involves the following:
• Creating Project defaults such as Identification labels for junctions, reservoirs, Tanks, Pipes,
Pumps, Valves, Patterns, Curves and ID increments
• Drawing the network i.e. pipes, nodes, junctions
• Setting object properties such as x, y coordinates, elevations, base demands etc, hydraulic
properties
• Running a single period analysis to indicate hydraulic properties at a given time

34
• Running an extended period analysis –to make a network more realistic we create a time
pattern that makes demands at nodes vary in periodic way over the course of a day for example
3 hours pattern step makes demand change at eight different times of the day.
• Create a pattern editor with multipliers to simulate demand variations at different times of the
day
3. RESULTS AND DISCUSSION
Simulation Results in terms of Pressure for 10 nodes selected from the 5 zones were analyzed
and compared with the actual measured data. Below is a brief of the findings:
Fig 1: Simulated Network depicting pressures at each of the 33 nodes
Results from the EPANET simulation indicate the Pressure variation from the Storage Tank
at Kamtiong Treatment Works to the various nodes within the reticulation network.
3.1 JN2-Kamtiong-ICFEM-Kaptola Junction (Zone 4)
This is the first junction from the Treatment Plant with a 50mm Upvc line meant to serve
Kaptola Primary and Secondary Schools as well as the ICFEM Mission Hospital and the surrounding
Population. Results from EPANET indicate a pressure of 8.11m while the actual measured pressure
using the Pressure logger was 7.84m. There is a 3% deviation from the simulated result. Both the
Simulated and measured pressure result is less that the recommended residual head of 10m.
Therefore, the consumers in the area cannot get water of adequate pressure if 90% of the taps are
open. An alternative to serve consumers around this area with adequate pressure will require direct
connection from the 12m high elevated Backwash Tank instead of the direct connection from the
Treated Water Main as is currently the case.

35
Fig 2: Pressure Distribution within the network
Fig 3: EPANET Simulated Pressure Compared to Actual Measured Pressure
3.2 JN8-Kamusinga Girls School-(Zone 4)
Results as simulated from EPANET indicate that there is a pressure of 17.02 m and the actual
field pressure as measured was 15.5m. Thus there is a deviation of about 8.9%. The pressure here is
adequate as it is above the required minimal residual head of 10m. The significant deviation can be
attributed to the aged status of the pipeline which has resulted in scaling and increased friction factor.
3.3 JN10-Friends School Kamusinga-(Zone 2)
The line that serves Friends School Kamusinga was identified as JN10 and pressure
measurements were done within the School Compound. Pressure measured was 13m while the
EPANET results indicate an ideal situation of 15m pressure. The variation was attributed to an
online abstraction by the Western Kenya Police Training College located adjacent to the School.
Nevertheless the pressure is enough for the school.
3.4 JN17-Sirende Junction-(Zone 2)
This node is located on the South Eastern end of the Supply area. It one of the nodes further
away from the Treatment Works and also on the lower elevations compared to the Treatment Plant.
The Pressure as measured at this node was 18.56m while the EPANET results indicate that the
pressure should be 20.03m. The Pressures in this part of the network are excessive and consumers

36
complained of water hammer in their taps. This has led to leakages along the line which lead to high
levels of Non Revenue Water as corroborated by the Water Utility Technical staff. It is
recommended that a break Pressure Tank of 10m3
be placed at about 2km to Sirende Junction to try
and contain the excessive pressures witnessed in the pipeline.
3.5 JN20-Water Offices-(Zone 1)
Pressure measurement at the Water Utility offices indicated as pressure of 26m at the Tap
while EPANET simulation indicated a pressure of 23.05m. This node had measured pressures
exceeding simulated results. This was attributed to the reduction in size of the pipeline from 75mm at
the off take to 38mm at the Water offices. This has lead to leakages through the tap it was
recommended that a new pipeline of 75mm be laid to replace the 38mm which would reduce the
pressure to manageable levels. It was also recommended that Pressure Reducing valve be installed
on the line.
3.6 JN12-Nabwana Estate Line-(Zone 1)
This Zone is at the Central Business District of Kimilili Town and consumers are mostly
commercial units as well as residential homes. Measured pressure was 15.43m while the simulated
EPANET Result was 17.76m indicating that the actual pressure in the field was lower than the ideal
one. Generally pressure in this zone is fine and consumers are happy since water of significant
pressure is received even on 3 story buildings within the town. There is however rapid growth and
connections onto the network. It is further recommended that a section valve be placed just after JN
11 to regulate flows based on the demands.
3.7 JN23-Matili R.C Church line-(Zone 3)
Pressure measured at this node was 30m while EPANET indicated a result of 34.7m. This
line is 50mm Upvc and has very few connections. Thus very few consumers use the line which
results in pressure build up. A connection to Matili Technical Training Institute needs to be effected
to reduce the excessive pressure within the line.
3.8 JN26-Bahayi line-(Zone 3)
This node recorded actual pressure of 34.5m while EPANET indicated a pressure of 39.48m.
These are excessive pressures and a pressure reducing valve is proposed on each of the pipeline
junction to avert bursts and leakages that tare frequent in this zone.
3.9 JN27-Misikhu Junction-(Zone 5)
Actual Measured pressure at this junction was 23.5m while EPANET Indicated a Pressure of
23.05m. This is the main junction from where a line goes to Namarambi Weigh Bridge and the other
line proceeds towards Lugulu through Tete. It eventually feeds Mikuva and Lugulu market.
3.10 JN33-Mikuva line-(Zone 5)
This node is on the pipeline branching from the Main line at Lugulu Market. It had an actual
pressure of 20.4m while the simulated pressure through EPANET was 24.03m indicating a deviation
of about 4m. The area has quite enough pressure bearing in mind that is among the zones with lower
elevations within the network. The Main improvement recommended on this line is to extend the
pipeline from Mikuva to some 3km towards Siloi area to help even out pressure build up.

37
4. CONCLUSION AND RECOMMENDATIONS
The Study was aimed at simulating the Variation of Pressure within the 5 zones of Kimilili
Water Reticulation network to find out how it is distributed within the zones. Field measurements
were also carried out and compared with the simulated data. In can therefore be concluded as
follows:
• Less than 12% of the nodes in the entire Kimilili Water reticulation have residual pressures
less than the recommended minimum of 10m. These areas are mainly around the Treatment
Plant owing to their elevation orientation. Therefore to serve these consumers with adequate
pressure , it is recommended that a dedicated line be laid from the Backwash Tank located at
the Treatment Works
• Pressure varies within the network and generally increases as one move further away from the
Treatment Works as a result of the buildup.
• More than 80% of the network receives pressures above 16m which requires Break pressure
tanks and Pressure reducing Valves to prevent excessive water hammer in the taps.
• Simulated Pressure results from EPANET are generally higher than actual field results due to
the aging nature of the network.
• EPANET Software is a useful tool for extended period simulation which should be embraced
by Water Utilities especially in the Developing Countries to simulate and predict Hydraulic
Parameters thereby manage efficiently the Water distribution networks.
• The Study utilized EPANET simulation to visualize pressure variations in the Water
reticulation network. Further research can be done using the same software but to establish if
there is any relation between pressure variation and levels of Contaminants ingress in the
network and also relate it to water age.
ACKNOWLEDGEMENTS
The Authors are grateful to Masinde Muliro University of Science and Technology,
Kakamega, Kenya for their cooperation and encouragement to carry out the Study. We are also
grateful to the technical staff of Nzoia Water and Sanitation Company (Nzowasco) for their
dedicated technical support.
REFERENCES
1. Oklahoma Department of Environment and Quality Manual, (2008).
2. Environmental Protection Agency Manual (2008)
3. Hickey, H (FEMA) ,(2008):Water Supply Systems and Evaluation Methods Vol.I.: Water
Supply Systems concept
4. Cheung, P. B., Van Zyl, J.E. & Reis, L.F.R. (2005): Extension of Epanet for Pressure Driven
Demand Modelling in Water Distribution System CCWI2005 Water Management for the
21st Century, Exeter, UK.
5. Kapelan, Z., Savic,D.A,.and Walters,G.A (2000): Inverse Transient analysis in pipe networks
for leakage detection and roughness calibration, proceedings of water network modeling for
optimal design and management, Exeter, UK.
6. Senyondo,(2000).: Master’s Thesis on “Optimization of Water Distribution Network using
EPANET”
7. Rossman A. L. (2000) EPANET Users’ Manual. National Risk Management Laboratory.
United States Environmental Protection Agency, Ohio.

38
8. Ang, W. K. & Jowitt P.W. (2006): Solution for water distribution systems under pressure-
deficient conditions. Journal of Water Resources Planning and Management, Volume 132,
issue (3): pp175-182.
9. Chandapillai, J. (1991): Realistic Simulation of Water Distribution Systems. Journal of
Transportation Engineering, Volume 117, Issue (2):pp 258-263.
10. Clement J.,Cheung et al, (2004).: Predictive Models for Water Distribution Systems,
Distribution Network Design using Differential Evolution”. Journal of distribution systems:
A UK case study”, Copernicus Publications, Drink, UK
11. Hayuti M. H., Burrows R. & Naga D. (2007): Modelling water distribution systems with
deficient pressure. Water Management, 160: 215-224.
12. Hickey, H (FEMA) ,(2008):Water Supply Systems and Evaluation Methods Vol.I.: Water
Supply Systems concept
13. Machell,J., Mounce, S. R. and Boxall, J. B(2004):“Online modelling of water Mays, L.W.
(2004) Water supply systems security. McGraw-Hill. Modelling “Intermittent Water Supply
Systems with Epanet”. 8th annual conference
14. Nyende-Byakika, S. (2011) Modelling of Pressurised Water Supply Networks that may
exhibit Transient Low Pressure-Open Channel Flow Conditions. PhD Thesis. Vaal University
of Technology. Vanderbijlpark. South Africa.
15. Nyende-Byakika, S., Ngirane-Katashaya G. & Ndambuki, J.M. (2010) Behaviour of stretched
water supply networks. Nile Water Science and Engineering Journal, 3(1).
16. Ozger S. (2003) A semi-pressure driven approach to reliability assessment of water
distribution networks. PhD Thesis. Arizona State University.
17. Sarbu, I and Valea, S.E (2011): “Nodal analysis of looped water Issue 3, Volume 5, Pp 452-
460, 2011.

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