Republic of Iraq

Republic of Iraq

Ministry of Higher Education

and Scientific Research

Karbala University

College of Engineering

Department of Civil Engineering

Evaluation and Analysis the Effects of Some Parameters on

the Operation Efficiency of the Main Water Pipe in Karbala

City Using WaterCAD Program

A Thesis Submitted to the

Department of Civil Engineering University of Kerbela in Partial

Fulfillment of the Requirements for the Degree of Master of

Science in Civil Engineering (Infrastructure Engineering)

By

Hussein Ali Hussein

(B.Sc. 2005)

Supervised by

Prof. Dr. Jabbar H.

Al-Baidhani

Prof. Dr. Musa H. Jassem

Al-Shammari

November; 2021

سورة يوسف - اآلية )76(

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Dedication

To the one who taught me how to stand firmly above the ground... my

respected father

To the wellspring of love, altruism and generosity... my dear mother

To the people closest to myself...my faithful wife

To my soul, the apple of my eyes, and the pulse of my heart... my children

To everyone from whom I received advice and support

I present to you the summary of my scientific efforts.

IV

ACKNOWLEDGMENTS

First of all, I thank God almighty, who granted me the power to

finish this work.

This project would not have been possible without the assistance of

many individuals. I am grateful to those people who volunteered their time

and advice, especially my supervisors, Dr. Jabbar H. Al-Baidahni and Dr.

Musa H. Jassem Al-Shammari, for their guidance, advice, invaluable

remarks, and fruitful discussions throughout the preparation of this thesis.

Without them, the work would not have appeared in this way.

I also wish to express my deep appreciation and gratitude to Dr.

Laith Shakir Rasheed, Dean of the College of Engineering, and Dr. Raid

Rahman AL-Muhana, Head of the Department of Civil Engineering,

Kerbala University, for their help and support throughout the study period.

I am also grateful to the Directorate of Karbala water, especially the

Director of the department Mr. Mohammed Al Nasrrawi, Engineers and

Cadres for their support. Special thanks are also due to Mr. Mohammed

Shmoto, the technical associate of the Karbala Directorate water, Mr.

Moayed Jalwkahn Implementation division officer, Mr. Ahmed Yassin

Head of planning, and to the engineers Mr. Usama, Mr. Safaa branch

administrators in the directorate for their generous help and guidance.

I would also like to express my deepest gratitude to my family for

their support and encouragement. Finally, many thanks to anyone who

helped me and I forgot to mention him.

V

Abstract

The present study will highlight the assessment of the efficiency of

one of the main water pipe Karbala province, it is considered one of the

most important holy province in Iraq and witnesses a large volume of

pilgrims each year. Further, this study was conducted to evaluate the

current main water pipe efficiency to improve its efficiency. A field

reading at different junctions’ locations was taken in the branching and the

main water pipe at different annual seasons, which were in summer,

autumn, winter, and different hours by using an Ultrasonic flowmeter. The

main water pipe is analyzed in two parts. The first part deals with the

analysis of the collected data with the steady flow assumption, and the

second part is simulated and analyzed in the WaterCAD software with the

variation of hourly consumption, which is the unsteady flow assumption.

Based on the results of the first part of the manual analysis, it was

found that there is a clear and a large losses of water at the beginning of

the main water pipe started from junction-1 to junction-5; and then is

accompanied by a clear and large scarcity at the end of the main water pipe.

The total of the losses and scarcity quantities in the main water pipe was

equal to 326.24 𝑚3/ℎ𝑟 and -113.25 𝑚3/ℎ𝑟, respectively. The quantities of

losses are very large compared to the quantities of scarcity, so if the

quantities of losses were controlled, the quantities supplied to the main

water pipe would be enough to fill the presence of scarcities without the

need to increase the quantities supplied based on the steady flow without

any future expansions for junctions. It is noteworthy that controlling the

quantities of losses is very difficult because of the difficulty of detecting

excesses on the network and the absence of water meters in houses to

determine the percentage of losses.

VI

In the second part of the analysis, simulated using WaterCAD

program for six scenarios to analyze and identify the problem of scarcity

according to unsteady flow, and control it to achieve the best solution.

based on simulation of results, it was found that the water needed to

overcome water scarcity was 2400m3/hr. And it cannot be ignored there is

no losses of water in high quantities, especially at the beginning of the main

water pipe, and more specifically in the first five junctions which was

losing quantities of water estimated at 326.24m3/hr. based on manual

calculations, and these losses is because of the use of drinking water for

irrigation of gardens and orchards and a large number of illegal

connections. And this addition to the new capacity of the main water pipe

will take part to increasing the number of junctions according to the needs

Karbala water directorate.

VII

Table of Contents

Dedication……………………………………………………… II

Supervisor Certificate………………………………………... III

ACKNOWLEDGMENTS……………………………………. IV

Abstract………………………………………………………… V

Table of Contents …………………………………………….. VII

List of Figures…………………………………………………... X

List of Tables…………………………………………………. XII

Abbreviations………………………………………………... XIII

Chapter One: Introduction………………………………….2

1.1. Background ........................................................................... 2

1.2. Problem Statement ................................................................ 3

1.3. Study Objectives: .................................................................. 4

1.4. Assumptions .......................................................................... 5

1.5. Outline ................................................................................... 5

Chapter Two: Literature Review ………………………….. 7

2.1. Introduction ........................................................................... 7

2.2. Evaluation and Analysis of water-distribution networks ..... 8

2.3. Summary ............................................................................. 29

2.4. Gap of Knowledge .............................................................. 29

Chapter Three: Theoretical…………………………………. 31

3.1. The Basic Laws for analysis ............................................... 31

3.1.1. Darcy-Weisbach formula ............................................. 33

3.1.2. Hazen-Williams equation ............................................. 36

3.2. Network Analysis Methods ................................................ 40

3.3. Hardy Cross Method ........................................................... 40

3.3.1. Head Balance Method .................................................. 41

3.3.2. Quantity Balance Method ............................................. 42

3.4. Newton-Raphson Method ................................................... 44

VIII

3.5. Computer Models ............................................................... 46

3.5.1. History of computer models. ........................................ 46

3.5.2. Software packages. ....................................................... 47

3.5.3. Development of a system model. ................................. 48

3.6. Water CAD ......................................................................... 48

3.6.1. Junctions ....................................................................... 50

3.6.2. Reservoirs ..................................................................... 50

3.6.3. Pipes ............................................................................. 50

Chapter Four: Field Work…………………………………. 53

4.1. Location .............................................................................. 53

4.2. Al-Sijlah and Al-Feyadh Complexes Project ..................... 55

4.3. The Main Water Pipe .......................................................... 56

4.3.1. Existing Distribution System ....................................... 57

4.3.2. Connections junctions .................................................. 57

4.4. Field Recording Data .......................................................... 58

4.4.1. Recording data in the summer, specifically the month of

August ........................................................................... 60

4.4.2. Recording data in the autumn, specifically the month of

October ......................................................................... 61

4.4.3. Recording data in the winter, specifically the month of

December ...................................................................... 62

Chapter Five: Results and Discussion…………………….. 65

5.1. Analysis of the recorded field data of Main water pipe ..... 65

5.1.1. Consumption type in a mainline pipe ........................... 66

5.2. Building of the hydraulic model using WaterCAD ............ 73

5.3. Proposal Scenarios for the hydraulic Model in WaterCAD

............................................................................................. 78

5.3.1. First scenario ................................................................ 78

5.3.2. Second scenario ............................................................ 81

5.3.3. Third scenario ............................................................... 85

IX

5.3.4. Fourth scenario ............................................................. 88

5.3.5. Fifth scenario ................................................................ 91

5.3.6. Sixth Scenario ............................................................... 94

5.3.7. The summary of scenarios ............................................ 97

Chapter Six: Conclusion and Recommendation………. 100

6.1. Conclusions ....................................................................... 100

6.2. Recommendations ............................................................. 102

6.2.1. Recommendations for operating staff of the main water

pipe ............................................................................. 102

6.2.2. Recommendations for future studies .......................... 104

Reference……………………………………………………… 106

أ ...……………………………………………………………الخالصة

X

List of Figures

Figure 3-1: Closed loop type network. ..................................................... 41

Figure 3-2: Branched-type pipe network. ................................................. 43

Figure 4-1: Geographical location of Karbala relative to Iraq. ................ 53

Figure 4-2: Geographical location of the mainline. .................................. 55

Figure 4-3: Layout plan of the Al-Sijlah and Al-Feada complex project.56

Figure 4-4: The different ultrasonic devices using during record data. ... 58

Figure 4-5: The pressure gauge using for record data. ............................. 59

Figure 4-6: during record data. ................................................................. 63

Figure 5-1: The layout of distribution network in WaterCAD. ................ 74

Figure 5-2: Flex table (pipe table) for identified the characteristics. ....... 75

Figure 5-3: Flex table (junction table) for identified the characteristics. . 76

Figure 5-4: Identify pump characteristics in pump Definitions windows.

............................................................................................... 77


............................................................................................... 77

Figure 5-6: Calculation summery for simulation at first scenario. ........... 79

Figure 5-7: Head Pressure at junction-p at pump station during 24 hr. ... 80

Figure 5-8: layout of mainline with booster station. ................................ 82

Figure 9: The pump definition for Booster Station. ................................. 83

Figure 5-10: Calculation summery for simulation at second scenario. .... 84

Figure 5-11: Head Pressure at some of junctions during 24 hr. ............... 84

Figure 5-12: The pump definition for 3rd scenario. ................................. 85

Figure 5-13: Calculation summery for simulation at third scenario......... 86

Figure 5-14: Hydraulic Grade line profile for 3rd scenario at 18:00. ..... 87

Figure 5-15: Hydraulic Grade line profile for 3rd scenario at peak time 19:00. ....... 87

Figure 5-16: Hydraulic Grade line profile for 3rd scenario at 20:00. ...... 88

Figure 5-17: Calculation summery for simulation at fourth scenario. ..... 89

file:///D:/Dropbox/بحث%20مهندس%20حسين/writing/Total.docx%23_Toc80295452

XI

Figure 5-18: Hydraulic Grade line profile for 4th scenario at 18:00. ....... 90



Figure 5-21: The pump definition for 5th scenario. ................................. 92

Figure 5-22: Calculation summery for simulation at fifth scenario. ........ 93

Figure 5-23: Hydraulic Grade line profile for 5th scenario at peak time. 94

Figure 5-24: Calculation Summary for Simulation at sixth Scenario ..... 97

Figure 5-25: Hydraulic Grade line profile for 6th scenario at peak

time(19:00)……………………………………………………….…… 97


time(18:00)……………………………………………..……….……… 98


time(19:00)……………………………………………...………………98

XII

List of Tables

Table 3-1: Values of Constant in Hazen-Williams Formula. ................... 37

Table 3-2:Values of Hazen-Williams Coefficient for Clean New Pipes of

Different Materials. .................................................................. 38

Table 3-3: Correction Factors for Hazen-Williams Coefficients. ............ 39

Table 4-1: Recording data during morning operation. ............................. 60

Table 4-2: Recording data during afternoon operation. ........................... 60

Table 4-3: Recording data during evening operation. .............................. 60


Table 4-4-5: Recording data during afternoon operation. ........................ 61



Table 4-8: Recording data during afternoon operation. ........................... 62


Table 5-1: Elevation and Demand for branch junctions. .......................... 79

Table 5-2: Elevation and Demand for branch junctions at 4th scenario. .. 88

Table 5-3: Summarizes the advantages and disadvantages of scenarios. . 98

XIII

Abbreviations

Abbreviation Description

SDP Stochastic Dynamic Program

LDRs Linear Decision Rules System

SOP Stochastic Operating Program

NLDR Non Linear Decisions Rules

TPLS Technical Performance Index System

GMC Gandhinagar Municipal Corporation

PROBPB Pipe Burst Possibility

WSR Water System Replacement

PM Pressure Management

PSI Puckorius Scading Index

RSI Ryznar Stability Index

WDS Water Distribution System

WDNs Water Distribution Network System

GA Genetic Algorithm

GIS Geographic Information System

ANN Artificial Neural Network

PDNA Pressure Deficient Network Analysis

ACO Ant Colony Optimization

AHP Analytical Hierchy Processes

DE Differential Evolution

DENET Differential Evolution Network

NRW Non-Revenue Water

AI Aggressiveness Index

HGL Hydraulic Gradient line

WDSs Water Distribution Supply System

CHW Hazen William Coefficient

VR Valve Proportion

CA Condition Assessment

SDGs Sustainable Development Goals System

f Darcy Coefficient Friction

(ASCII) American Standard Coding for Information Interchange

Chapter One

Introduction

Chapter One ……………..………………….…………… Introduction

2

Chapter One: Introduction

1.1. Background

The system of water distribution has been a hydraulic infrastructure,

which contains types of valves, pumps, supplied reservoirs, different

various of tanks, pipes, and among other things. They're all necessary for

delivering water of acceptable quantity at the right pressure. It possible are

Either looped or branched distribution systems. looped systems are favored

over branching systems since they may offer a greater degree of

dependability when coupled with appropriate valving. A pipe break may

also be repaired and isolated in a looping system with little effect on

consumers beyond the local region. Customers downstream from the

breach in a system the branch, on the other hand, will be without water till

the repairs have been finished. A looped design, on the other hand, enables

water to reach the consumer through several paths, boosting system

capacity at any time (Atiquzzaman, 2004). Because of the cost and

significance, the system of water distribution (WDS) is considered

amongst the most important of the water supply system components. Water

distribution network system (WDNs) are designed with the primary goal

of supplying the required amount of water at the essential time with

adequate pressure. Drinking water supplies in several third-world countries

are insufficient to satisfy the demands of consumers.

Along each main water pipe, there are many connections with tiny

ports or pipes, all of which enable flow from or into the main pipe (less

frequently). Main water pipe have a lot of junctions or ports, which are

typically near together but not same the flow at neighboring

junctions(Larock et al., 1999).


3

Intermittent water supply systems have been operated and designed

accordingly. Because free flow ports and pressure heads are provided in

the different nodes, discharged at junctions will be relative to the accessible

pressure head at each junction, resulting in a variation in the amount of

water delivered. In the systems of water distribution design, this aspect was

not given much weight. When there is a shortage of water, the problem of

unequal distribution becomes even more serious. Some nodes will receive

more than their fair share, while others will discharge far less than their

proportionate share. One of the design recommendations in design guides

was to guarantee that the variance in pressure head among different nodes

within a distribution zone remained within a specified range, or that the

region was split into smaller zones to fulfill this requirement (Gottipati &

Nanduri, 2014).

1.2. Problem Statement

As a consequence of increasing urbanization and the development of

hundreds of local and large-scale water supply and distribution systems in

the past few decades, many people today have access to clean water and

sufficient sanitation. However, the quality of water utility service is

frequently questioned, and the cost of new systems is frequently

prohibitive. Water supply systems are critical strategic systems that are

physically complex in their design, installation, and operation, posing

significant economic and environmental concerns. They also make a

significant contribution to public health. Despite this, professionals and

engineers frequently underestimate design and operational challenges, and

their direct or indirect impacts, while often considered separately, are

rarely investigated comprehensively (Jalal, 2008).

The present study will focus the assessment of the efficiency of one

of the main water pipes in the Karbala province specifically in the area of


4

AL-Feyadh, which belongs to the Al-Kheirat township where the water

complexes are located. The main water pipe has a diameter of 800 mm

ductile from these water complexes, passing through the villages and

countryside’s on the side of the road, and reaching the Najaf road, where it

runs along the Husseiniyat on the road to the province of Karbala.

The line was chosen to conduct the study and increase its operational

efficiency because it is considered the main feeder to Karbala international

airport, which is under construction, and it’s one of the important

infrastructure facilities through one of the junctions branching from it, as

well as the residential complex in Al-Zabilia road towards the Karbala

center. This study contributes to helping the Karbala water directorate to

increase the capability and to get better the hydraulic performance of the

main water pipe.

1.3. Study Objectives:

The main objectives of the present study are:

1. Evaluating the hydraulic performance of the existing main water pipe

that owns a dead-end system and is located in Karbala city in Iraq.

2. Finding the best methods and appropriate solutions to solve this deficit

using an analytical study of the main water pipe.

3. Using Hydraulic analysis software Bentley WaterCAD. under peak

consumption and extended period simulation of 24 hours and its

performance was assessed according to current hydraulic

circumstances.

4. The main hydraulic parameters of main water pipe are the discharge,

required pressure, and other associated factors of them are pipe

diameter, flow velocity, and all those had been studied.


5

1.4. Assumptions

1. The main water pipe existing has a dead-end system and the water

moved from the first zone towards the last zone.

2. The main water pipe system operates entirely by a pump station

which is located in a compact unit.

3. The quantity of the flow in main water pipe junctions is unique

because of the difference in level and near of pump station.

4. The quantity of flow is not constant for every junction.

5. Minor losses at the nodes (junctions) are neglected.

1.5. Outline

1. Chapter one describes the overview of main water pipe, objective for

research, the layout of dissertation, and assumptions.

2. Chapter two reviews some of the recent work done on analysis for

water networks and distribution systems.

3. Chapter three describes the theory of water networks and the method

of analysis and program used in assessment.

4. Chapter four survey of main water pipe for case-study.

5. Chapter five presents the results of the analysis and discussion.

6. Chapter six explains the main conclusions and recommendations for

future work.

Chapter Two

Literature Review

Chapter Two ……………..……………..…….…… Literature Review

7

Chapter Two: Literature Review

2.1. Introduction

This chapter aims to provide a systematic and up-to-date review of

achievements concerning of analysis and operation of the water

distribution networks field. It's also discussing problems and key issues in

the context of future research needs in the analysis and operation of water

distribution networks.

Water distribution networks are an essential component of water

delivery systems and one of society's most valuable infrastructure assets.

Simulating hydraulic activity in a looped pipe network is a difficult job that

entails solving a set of nonlinear formulas. The head loss function,

continuity, and energy formulas are all studied at the same time throughout

the solution procedure.

Several techniques for addressing steady-state networks hydraulics

were developed throughout the years. The capacity to model the hydraulic

behavior of major water distribution networks had also significantly

increased in the last two decades, thanks to the development of models and

the availability of low-cost, reliable equipment.

A large number of researchers studied water distribution networks

in various ways. Some of them studied the issue of designing water

distribution networks in general, while others tried to analyze and evaluate

water distribution networks and investigate the problems faced by the

network to find appropriate solutions.


8

2.2. Evaluation and Analysis of water-distribution networks

(Alshammari, 2000) Use Hazen-William equation in applied to

calculate the amount of water transported through the pipe at the intake

points and the number of real discharges withdrawn from these points (real

consumption) and from knowing the inhabitants served from these points

and multiplying this number by the per capita consumption rate of water to

know the hypothetical consumption at these points and from comparing the

two quantities was determining the nature of consumption in the network

by calculating of losing based on the mathematical sign, If it is positive

indicating an excess, and if it is negative it indicates the presence of water

scarcity in the network.

(Rajani & Kleiner, 2001) A water supply system's distribution

network has been the most costly component. The degradation of water

mains leads to increased maintenance costs, worse water quality, lower

service quality, water loss, and interruption of street-level activity. Always

water lines repair and renewal must be planned through rehabilitation if

sufficient water supply goals are to be met. Understanding and quantifying

pipe degradation processes is a critical component of the planning process.

In the past 20 years, historical performance data has been used to assess

the structural degradation of water mains. The physical processes that

cause pipe failures typically necessitate data that is both scarce and

expensive to acquire.

(Selvakumar et al., 2002) In the Americas, there is increasing

concern about the requirement to repair, replace, and rehabilitate potable

water distribution and wastewater collecting systems. According to a

recent study performed by the US Environmental Protection Agency,

maintaining and replacing current drinking water infrastructure would cost

$138 billion during the next 20 years. The cost of rehabilitating and


9

repairing pipes is expected to reach $77 billion. Epoxy coating, cleaning

and repacking techniques were used for the lining materials.

The CANDA-GA Model was created by (Keedwell & Khu, 2005)

and utilizes a local representative cellular automata, a heuristic-based

method to generate a suitable starting inhabitant for genetic algorithm

starts. Three networks were solved using the CANDA-GA algorithm. The

findings indicate that the suggested technique regularly outperforms the

non-heuristics-based GA method in terms of designing more cost-effective

water distributions networks.

(Al-Zahrani & Syed, 2005) used the minimal cut-set technique to

assess the dependability of a municipal water distribution system. On an

actual water distribution network, a technique for assessing water

distribution system dependability was devised and proven. The technique

consists of two stages: (1) nodal pressures were estimated utilizing the

hydraulic simulation software (EPANET), and (2) nodal and system

reliabilities of the AI-Khobar water distribution system are determined

using the minimal cut-set method. The hydraulic dependability of the core

section of the AI-Khobar water distribution network was found to be 69.73

percent.

(Christodoulou et al., 2006) proposed a framework for managing

urban water distribution systems that combined numerical and analytical

simulation methods with geographical information systems (GIS) for better

dissemination and visualization of important information to management

teams. The state of components in the water distribution system has been

evaluated using numerical simulations and artificial intelligence methods,

forms in the underpinning historical data have been investigated using

artificial neural network (ANN), knowledge is gathered and assessed using

database managing systems and fuzzy logic, and the findings have been


10

eventually mapped on GIS for improved visualization. The methodology

and methods created and described in this study have been depending on

data gathered in New York City and then used in Freeport (Long Island,

NY), Limassol, and Larnaca, Cyprus (Cyprus).

(Geem, 2006) utilized a harmony searches optimization method to

identify the best water distribution system design whilst keeping all design

limitations in mind. To discover better design solutions, the harmony

search algorithms replicates a jazz improvising process, in this instance

pipe sizes in a water distribution system. To assess the hydraulic

limitations, the model connects to EPANET, a prominent hydraulic

simulator. The degree of violation is included in the cost function as a

penalty if the design solution vector breaches the hydraulic restrictions.

Under comparable or less favorable circumstances, they applied a model

to five systems of water distribution and produced designs that have been

similar or slightly cost 0.28–10.26percent lower compaed with those

competing for meta-heuristic algorithms like the tabu search, simulated

annealing, and genetic algorithm. The findings indicate, which the

harmony search-based approach is appropriate for designing water

networks.

The pressure-deficient network method (Ang & Jowitt, 2006)

proposed a new technique for solving a water distribution system under

pressure-deficient circumstances (PDNA). The model gradually inserted a

fake reservoir into the network to start nodal flows, with full demanding

loads eventually replacing such reservoirs after it was apparent that the

nodal flow could be met. The PDNA was provided in a format that could

be used to program a computer. The PDNA has been utilized to solve flows

in a basic network, but it should be utilized in conjunction with a


11

hydraulically networks solver to solve flows in a looping network; since

the manual calculation is too time-intensive.

(Jamieson et al., 2007) created a model to assess the feasibility and

effectiveness of implementing real-time, near-optimal management for

water-distribution networks. With that in mind, the book's contents cover

the present state of the art as well as some of the challenges that must be

overcome if the aim of near-optimal control is to be realized. Since it would

be difficult to utilize a near-optimal controlling, traditional hydraulic

model simulation for real-time that is theoretically much more efficient,

they used artificial neural networks to replicate the model. The preceding

model was then integrated into a dynamic genetics algorithm that were

developed especially for real-time usage. This method may be used to

generate near-optimal control parameters to satisfy present needs while

minimizing total pump-up prices to the operational horizon.

The Ant Colony Optimization (ACO) methodology was used by

(López-Ibáñez et al., 2008) to find the best pump schedule. They broke

down a pumping timetable into a sequence of numbers, each indicating the

number of hours a pump is active or idle. In comparison to the binary

representation, this decreases the number of possible timetables (search

space). They aimed for the lowest possible electrical cost while still

meeting system limitations. Then used an ant colony Optimization

methodology to solve the optimum pump scheduling instead of utilizing a

penalty function method for constraint violations, and they prioritized the

solutions depending on the significance of the violations. On such a limited

test network and a big real-world network, they have been put to the test.

(Al-Barqawi & Zayed, 2008) developed a robust model to evaluate

the status of water mains and forecast their performance. To create the


12

model, the researchers used data gathered from three distinct Canadian

towns. Artificial neural network (ANN) and analytical hierarchy processes

(AHP) have been used to create an integrated model and framework.

Furthermore, a web-based infrastructure management application (CR-

Predictor) based on the combined AHP/ANN model was created to

evaluate water main status. The created tool and models have been verified,

and the findings are reliable (98.51 percent) and that is the median validity

percent. Practitioners and Academics (contractors, consultants, and

municipal engineers) were anticipated to profit from them by prioritizing

rehabilitation and inspection plans for existing water systems.

The following are some of the main advantages of supplying water

for firefighting:

1. Preservation of the economy from the effects of fire

2. Insurance costs for homeowners and businesses in the

neighborhood have been reduced.

3. Human life preservation.

4. Human suffering is reduced. As a result, there seem to be

additional reasons for supplying sufficient fire flows to a

town, in addition to public safety.

Because an appropriate water supply system is a critical component

of a fire protections/suppression system, effectively managing/fighting a

fire emergency requires a thorough study and knowledge of the water

supply system's firefighting capability. Hydrant flow tests may be used to

assess the ability of an existing water distribution system to determine the

available fire flow in a given region. Field assessment of hydrants wherever

they existed, on the other hand, has been deemed excessively expensive,

time-consuming, disruptive, and only approximate. It's also difficult to

physically test each hydrant in the system, therefore computer modeling is


13

used to offer a reliable and precise way of forecasting fire flow in a water

supply system.

(Izinyon & Anyata, 2009a) utilized the WaterCAD program to create

a hydraulic system model of the current water distribution network in

Ikpoba Hill, Benin City, Nigeria, which was calibrated for investigations

of steady-state simulation utilizing the system's calibration, operational,

and physical data. The model has been used to analyze an available fire

flow and develop system improvements. The results of the computerized

fire flow analysis for the current network indicate that no node in the

system meets the study's fire flow restrictions. That is, the total available

fire flow for all nodes in the system is 0 l/s, suggesting that the system is

unable to provide the required flow for fire suppression. Nevertheless, the

planned upgraded network, which includes expanded diameters of current

pipes as well as future expansion projections, has available fire rate of

between 40l/s and 29.6l/s at the network's nodes. Hydrant tagging,

numbering, and color-coding may be changed based on the available fire

flow that will improve the fire department's firefighting/suppression

capabilities.

(Tabesh et al., 2009) developed a novel technique for assessing non-

revenue water (NRW) and losses in a systems of water distribution using

the "year water balance" and "minimum night flow" assessments. The

major NRW components, including leakages from reported and

background leakage and un-reported bursts, were assessed using actual or

estimated data, allowing the evaluation of leakage performance indicators.

They have developed a new method that uses a hydraulic simulation

models to assess nodal and pipe leaks. Because leakage is pressure-

dependent, the entire usage is split into two portions, one pressure

dependent and the other independent of local pressures, and the hydraulic


14

behavior of the network is investigated. Depending on the suggested

approach, they created a computer coding for evaluating all elements of

water losses. They converted the outcomes to a GIS model for a more

accurate depiction of the findings and system administration. Utilizing the

GIS model's capabilities, they connected the attribute data and map

network and discovered variables influencing network leakage. They also

looked at the consequences of lowering the pressure. A real-life case study

was used to evaluate the concept. The findings revealed that the suggested

model overcomes the limitations of previous methods by more accurately

estimating leaks and other NRW elements in water distribution systems.

The use of algorithms' Differential Evolution (DE) for optimum

rehabilitation and design of existing water distribution systems was the

topic of (Suribabu, 2010). To accomplish a goal of optimization of the

given objective function, the algorithms of Differential Evolution (DE)

uses a notion similar to that of the genetic algorithm. The optimum network

design seems to be a mathematically difficult issue that falls under the NP-

hard category. They used four well-known benchmark networks to

evaluate the effectiveness algorithms of the Differential Evolution (DE).

Within a reasonable number of function evaluations, the DE method

proved to be highly successful in identifying near-optimal or optimum

solutions. In comparison to other algorithms, the algorithms of Differential

Evolution (DE) performed very well.

(Kanakoudis & Tsitsifli, 2010) demonstrates that when the water

tariffs utilized by the water company involve set minimum additional fees

associated with water volumes being charged but not utilized (based on the

most recent meters' measurements), the levels of the Real Shortfalls,

determined thru the established IWA WB, is underestimated by every other

variation, which, while generating revenues (falsely reducing the NRW


15

levels), remains unaffected. Because a large part of Real Losses (up to 43

percent in certain cases) generates income, the need to design and execute

any water loss mitigation strategy is reduced. To prevent these erroneous

findings, a change to the IWA WB was suggested that included the entire

economic component. Two Greek cities used the planned modified IWA

WB in their water distribution systems. The findings showed that in

situations in which there are large demand peaks (seasonal), it is preferable

to assess the network across shorter periods. The findings also showed that

throughout periods of high water demand, whenever operational pressure

levels drop, actual losses are lower than during periods of low demand.

(Vasan & Simonovic, 2010) discusses the creation of a DENET

simulation environment for optimum water distribution system design,

which included the use of a differential evolution evolutionary

optimization method connected to the EPANET hydraulic simulation

solver. They developed a model to reduce costs, and they used it to solve

two standard water distribution network optimization issues: The New

York water supplying system and the Hanoi water distribution network.

When compared to previous experiments in the literature, the findings were

encouraging, prompting the researchers to restructure the model with a new

goal of increasing network resilience. The findings of the study showed

that DENET may be used as an alternate tool for designing and managing

water distribution networks that are both cost-effective and dependable.

(Yazdani & Jeffrey, 2011) suggested that water supply systems

could be represented as multi-nodes networks (including hydraulic

connections, storage tanks, and tanks) linked by physical connections

(including pipes), with the network's communication patterns affecting its

durability, efficiency, and reliability in the event of a failure. To establish

relationships between structural features and performance of water


16

distribution systems, the researcher used correlation node representations

of water infrastructures and a wide range of advanced and emerging

network theory metrics and metrics to study the building blocks of systems

and identify characteristics such as redundancy and fault tolerance. The

researcher looked at a third-world country's water distribution system and

looked at network expansion methods targeted at ensuring and improving

structural resilience while keeping design and budget limitations in mind.

Water losses will always happen in water distribution systems,

according to (Gomes et al., 2011). Given that the majority of actual losses

happen in distribution pipes and service connections, the researcher's

approach is based on several leakage assessment methodologies from the

literature as well as simulating the water distribution system. This enables

an evaluation of the advantages of pressure control in water distribution

networks, especially in terms of decreasing water output. Furthermore, this

method may be helpful for cost- benefit analysis to assist identify the point

at which decreasing water loss is no longer economically beneficial (the

economic leakage's levels). The implementation of pressure-lowering

valves at the entrance points of the rating regions was assumed in the

hypothetical research articles.

(Ostfeld et al., 2013) The hydraulic simulation of the dynamic pipe

network, according to the investigator, is a study of the municipal water

distribution system to develop an efficient technique of timetabling and

scientific operations. The key to developing an accurate model is to gather

basic data, acquire it, and integrate it into a pipeline modeling process. For

instance, GIS data in an urban piping system generates a computer

simulation of the water delivery system.


17

(Mutikanga et al., 2013) Water shortages and financial losses are

plaguing the water sector throughout the globe. Over time, techniques and

procedures have been developed to minimize these losses and improving

the effectiveness of water distribution systems. Current techniques and

methods for assessing, monitoring, and controlling losses in water

distribution systems are discussed in this article. According to the findings

of the study, many water loss control techniques and procedures have been

created and applied. They range from basic management tools like

performance indicators to complex optimization techniques like

evolutionary algorithms. Its applicability to real-world water distribution

systems, on the other hand, is restricted. To bridge the gap between theory

and practice, future research possibilities exist via strong cooperation

between researches institutions and water service providers.

(Bolouri-Yazdeli et al., 2014) Tank operating rules were

mathematical or logical formulae that compute water discharge from a tank

based on flow magnitudes and storage capacity, taking into consideration

system factors. Throughout reality, in each operating period, past system

experiences are utilized to balance tank system parameters. The reservoir

operating rules were created utilizing different optimization methods and

were classified as linear decision rules (LDRs) and constant variables. The

study looked at how real-time operating rules might be applied to a

reservoir system that seeks to meet the entire ultimate demand. With

various magnitudes of flow and reservoir storage, these rules include

Nonlinear Decision Rules (NLDR), LDR, Stochastics Dynamics

Programming (SDP), and Standards Operating Policies (SOP). To organize

the aforementioned principles, the technique of selecting, eliminating, and

multi-attribute decision to represent reality (ELECTER -I ) is employed,


18

along with a range of measures, objective functions, and tank performance

objectives (vulnerability, adaptability, and reliability).

(Tricarico et al., 2014) The network topology is used as a continuous

reference for input in most water distribution system redesign methods,

with optimization allowing only duplication/replacements of existing

components. This article presents a novel approach that reports the effect

of current network architecture and performance in terms of its

contribution to the discovery of optimum alternatives that may lead to a

decreased chance of failure to deliver the necessary water, as well as a

lower cost of redesign. The looping frequency and network strength

architecture are studied in particular using a genetic algorithm-based

optimization method that takes into consideration the unpredictable water

requirements at every node. The proposed approach was used in two case

studies that looked at the impact of the structure on total system

dependability and risk.

(Muranho et al., 2014) The Technical Performance Indexes (TPIs)

use to evaluate the operating performance of Water Distribution Systems

(WDNs) is explored in this article, as well as its potential for quickly

identifying issue areas. The article also discusses some of the issues with

existing TPIs and offers new analytic methods to address these issues.

These new analytical techniques (including constraint violation as state

variable slack) have been combined with the pressure-driven simulation

study for demonstration purposes, including assessing operational

performance throughout pipe bursts or firefighting scenarios, and

identifying and accounting for the "supply not satisfied" as a result of those

events.


19

(Medeiros et al., 2015) One of the most significant problems that

public managers and system operators confront today is reducing water

loss in water delivery systems. Water loss at high levels has a direct effect

on the system's income and, as a result, on investments and finance.

Moreover, they are liable for causing environmental damage by exploring

and extracting a larger amount of water than is required. To reverse this

condition, various options for water networks partition have been

examined using scenario simulations created with the WaterCAD V8i

water distribution modeling program. The reorganization of the water

distribution system may result in a significant decrease in water loss.

Moreover, the water network's digital model is an essential tool for system

managers to better manage water resources, resulting in both

environmental and economic benefits.

(Dave et al., 2015) The purpose of this research, titled "Analysis of

Continuous Water Distribution System in Gandhinagar City Utilizing

EPANET Software: A Case Study of Sector-8," was to achieve effective

design, development, and analysis of the water distribution system using

EPANET software. The current water distribution system data was

obtained from Town Planning Departments, and Buildings Departments,

Gandhinagar Municipal Corporation (GMC), Road and Gujarat

Government, Gandhinagar, for this study. Three techniques were used to

predict the population of Gandhinagar City over the next thirty years:

Arithmetic Increase Technique, Geometric Increase Technique, and

Incremental Increase Technique. The projected citizenry's water

consumption for the following three decades had also been calculated. The

height of nodes and pipe length was recorded for 285 nodes and an


20

equivalent number of pipes using a Google Earth image of Gandhinagar

city. EPANET Software was utilized to analyze pressure, head loss, and

elevation using these data. Pressure and height at different nodes, as well

as pressure losses at different pipes, were the results of this study. The

findings of data analysis in EPANET Software revealed that there is

reduced head loss in Sector-8, Gandhinagar that is critical for maintaining

the constant pressure needed for the continuous water delivery system.

(Choi & Koo, 2015) The pipe burst possibility (ProbPB), the effect

of a burst pipe (ImpPB), and the (WSR) determined as the product of these

two magnitudes were developed for a water distribution system and applied

in a target location for deciding the pipe burst possibility (ProbPB), the

effect of pipe burst (ImpPB), and the WSR determined as the product of

these two magnitudes. When the water supply is cut-off or decreased,

ImpPB was computed separately for the leaking duration period and the

repair work time. To validate this (WSR), pipe replacements have been

carried out using ProbPB, a water provider management indication,

ImpPB, a water consumption management indicator, and the WSR, which

incorporates both of these, by evaluating the WSR reduction impact of

each. As a result, pipe replacements depending on WSR had the greatest

decrease efficiency. The findings showed that the suggested WSR

evaluation model may take into account the perspectives of both the water

supplier and the water user at the same time. Furthermore, the model's cost-

effectiveness has been confirmed.

(Archetti, 2015) In this article, resilience is defined as a networked

infrastructure's capacity to provide service even if certain components fail;

it is dependent on both net-wide measurements of connection and the

function of a single component. The goal of this study was to demonstrate


21

how well a set of general methods can be produced using network theory

methods, specifically how the spectral analysis of adjacency and Laplacian

matrices can be used to create a mathematically sound and practical

definition of global connectedness. Second, using a clustering technique in

the subspace covered by the Laplacian matrix's l lowest eigenvectors

allows us to find the network's edges whose failure causes the network to

collapse (vulnerabilities). Even while the majority of the study may be

applied to any networked infrastructure, particular references to Water

Distribution Networks (WDN)will be made. The suggested technique's

operational utility is shown using a standard and three real-world

examples. Nevertheless, depending on an abstract graph context, this work

is only the first step in the creation of tools to assist the investigation of

resilience at global and national levels. The present stage of the study is to

develop graph-based metrics connected with network-wide resilience as

well as techniques to identify vulnerabilities in terms of physical

infrastructure connection. The most important graph theory-based metrics

to assess the overall resilience of a WDN about physical separation since

disruptive occurrences on pipes were found as spectral gap and algebraic

connectivity.

(Vicente et al., 2016) In water distribution systems, pressure

management (PM) is a frequent practice (WDSs). The development of new

scientific and technological techniques for its application has been a

strategic goal in the area for the past decade. However, improvement was

not always reflected in actual activities owing to a lack of systematic

examination of the findings gained in practical situations. This article has

given a thorough examination of the most novel problems connected to PM

to solve this challenge. The suggested approach is depending on a case-


22

study comparison of qualitative conceptions that includes 140 published

sources. The findings included a qualitative study of four aspects: (1) the

goals achieved by PM; (2) forms of regulation, including sophisticated

control systems thru electronic controllers; (3) innovative district design

techniques; and (4) the creation of PM-related optimization models.

Because of its technical and practical character, the job of (PM) continues

to develop. The introduction of new technologies, methods, and tactics

necessitates a continuous upgrading of knowledge to keep the scientific

community up to date.

(Mirzabeygi et al., 2016) The propensity of water to corrode and

scale seems to be an etiology of health and economic problems in water

delivery systems. The purpose of this research was to look at the water

stability of the Torbat Heydariye potable water system. This cross-

sectional research used cluster sampling methods, with 90 samples

obtained from 15 clusters using simple random sampling. During the year

2014, all samples were collected from the water distribution network. The

Aggressiveness index (AI), Larson-Skold index (LS), Puckorius scaling

index (PSI), Ryznar Stability index (RSI), and Langelier saturation index

(LSI) were also used to evaluate the water stability (AI). Utilizing a

Geographic Information System, the degree of corrosion in various areas

of Torbat Heydariye was shown. Even though these estimated parameters

were below acceptable limits, the findings showed that high TDS levels

associated with chloride and sulfate anions play a major role in enhancing

water's corrosive propensity.

(Balacco et al., 2017) The use of conventional peak factor formulae

in the water distribution system design might lead to over-dimensioning of


23

network pipes, particularly in small towns. This disparity is most likely

attributable to changes in human behavior as a result of improved living

circumstances. Based on these considerations and the access to a large

randomized data sample, a study of water demand for numerous towns in

Puglia was conducted, leading to the establishment of a stochastic

connection between the previous section peak parameter and the number

of people. The use of weekly and monthly peak parameters in the design

of a water distribution system is not required, according to this research,

since contemporary water needs do not seem to be very sensitive to these

fluctuations.

(Seyoum & Tanyimboh, 2017) Water distribution system numerical

simulations have been utilized for a variety of reasons. Planning, design,

monitoring, and control are some instances. Nevertheless, in low-pressure

situations, traditional models that use demand-driven analysis may provide

deceptive findings. Almost all models that use pressure-driven analysis, on

the other hand, do not conduct smooth dynamic and/or water quality

simulations. Tanks, control devices, and pumps for example, are often left

out. The EPANET-PDX simulation model seems to be a pressure-driven

expansion of the EPANET 2 computer simulation that keeps all of

EPANET 2's features, including water quality modeling. It cannot,

however, mimic several chemical compounds at the same time. Water

quality modeling based on a single species is inefficient and rather

inaccurate. The reason for this is because in water distribution networks,

various chemical compounds might coexist. This paper presents EPANET-

PMX (pressure-dependent multi-species extension), a fully integrated

network analysis model that solves these flaws. Both dynamic and steady-


24

state simulations are conducted by the model. It may be used in any

network that has a variety of chemical processes and reaction kinetics.

(Shuang et al., 2017) WDNs, or water distribution systems, are a

kind of critical infrastructure network. Components breakdowns in a

(WDN) will cause system failures, resulting in larger-scale responses,

when a catastrophe happens. The purpose of this study is to assess the

development of system reliability and breakdown transmission time for a

WDN suffering cascading failures, as well as to identify key pipes that may

significantly decrease system dependability. The technique takes into

account several variables, including network architecture, water supply and

request balance, demanding multiplier, and pipe breakage isolation. The

study simulates a pipe-based assault with various failure scenarios. To

demonstrate the technique, a WDN case is utilized. The findings indicate

that when a WDN is in limited supply, the lowest capacity becomes the

dominating element in determining the development of system

dependability and failure transmission time. There is a flattened S curve

connection between valve proportion (VR) and system dependability, and

VR has two turning points. It is possible to identify the essential pipelines.

A WDN may enhance system dependability and successfully withstand

cascade failures by using fixed 5percentage valves. The results provide

light on the system's dependability and the time it takes for a cascading

failure to propagate across a WDN. It is helpful in future research focusing

on water utility management and operation.

(Abdelbaki et al., 2017) Mapinfo GIS (8.0) software has been

combined with a hydraulic model (EPANET 2.0) and used in a case study

area, Chetouane, in the north-west of Algeria, for more efficient

management of a water distribution network in a dry region. Water


25

shortages, as well as inadequate water management techniques, are

prevalent in the region. The findings revealed that combining GIS and

modeling allows network operators to better evaluate faults, resulting in a

faster reaction time and a better knowledge of the work done on the

network. Managers can diagnose a network, analyze issue solutions, and

forecast future scenarios by combining GIS and modeling as an operational

tool. The latter may help them make educated choices to maintain an

acceptable level of performance for optimum network functioning.

(Agunwamba et al., 2018) In most metropolitan areas, population

growth puts tremendous strain on existing water delivery infrastructure. As

a consequence, total water demand is often not met. Utilizing WaterCAD

and EPANET, this research assessed the performance of the Wadata sub-

zone water distribution network in terms of pressure, velocity, hydraulic

head loss, and nodal demands. Even though there has been no statistically

significant difference between EPANET and WaterCAD findings,

EPANET provided somewhat higher pressure and velocity magnitudes in

approximately 60% of the instances studied. Around 19% (18.52 percent)

of the total nodes number examined had negative pressures, whereas 69

percent (69%) of the nodes having pressures lower than the study' adopted

magnitude. These negative pressures suggest that the distribution network's

head is insufficient to provide water to all areas. Approximately 87.7% of

the flow velocities in the pipes were within the chosen velocity, whereas

around 13% (12.3 percent) of the velocities exceeding the adopted velocity.

These high velocities are partially to blame for the leaks and pipe breaks

that have been recorded in certain parts of the system. The findings of this

research showed that the Wadata sub-water zone's distribution

infrastructure is inefficient under present demand.


26

(Mazumder et al., 2018) Water supply systems (WDS) have been

one of the most important types of civil infrastructure. For society's

development and long-term well-being, a dependable and safe water

supply is necessary. As a result, proper maintenance, repair, and

replacement of WDS' enormous physical assets are essential, particularly

in areas where key water infrastructure assets are deteriorating rapidly.

However, owing to a lack of resources, water systems struggle to keep up

with the aging of components in their asset management plans. Utilities

have recently made attempts to modify the conventional condition-based

approach to pipelines asset management that focuses on preserving the

current asset situation, into a service-based approach that explicitly

considers system performance. This article examines the current literature

on different elements of WDS asset management, with an emphasis on

underground pipelines. There includes a review of existing condition

assessment (CA) methods, failure forecasting models, time-dependent

vulnerability modeling techniques, planned maintenance strategies, and

renewal procedures. Various modeling methods for WDS performance

were always discussed, as well as their interaction with other infrastructure

systems. As a result, the paper provides a comprehensive overview of the

different elements that make up a WDS service-based asset management

approach. Various approaches and methods to the different elements are

also compared to assist in the selection of a suitable instrument. An outline

of future investment interdependence and management research

requirements is given.

(Rai & Lingayat, 2019) emphasized the use of the EPANET tool, as

well as the Hardy Cross and Newton-Raphson methods, to effectively


27

analyze and distribute a network of pipes. EPANET is computer software

that simulates hydraulic behavior over a long period in a pressurized pipe

network. Hydraulic variables including flow rate and pressure were

subjected to simulation. All connections and flows with their velocities

throughout all pipes have been confirmed to be capable of providing

sufficient water to the research area's network. The residual head at each

node was calculated using the elevation as an input, and the associated flow

characteristics such as nodal request, velocity, and residual head have been

calculated as a result. The results may aid in a better understanding of the

research area's pipeline infrastructure. The researchers found that the

EPANET program saves time and has no limits on the number of nodes,

pipelines, or pumps that may be simulated and evaluated in it, allowing

complicated networks to be solved quickly. The amount of head loss

approaches zero as the number of iterations increases, and balancing flows

at every point are done to validate the acquired results.

(Robert, 2019) The pressure exerted on a water distribution system

due to population increase and aging of the system amounts to the routine

assessment of its functionality. waterCAD and waterGEMS software were

used comparatively in evaluating the serviceability of the water

distribution system of the Federal University of Agriculture Makurdi.

Steady-state analysis was also carried out to determine hydraulic

parameters such as pressure, velocity, head loss, and flow rate. The result

of the statistical analysis revealed that both simulators can be used

interchangeably since there were no statistical differences. The pressure

result indicated low head within the system which resulted in 100 percent

(100%) of the nodes operating below the adopted system pressure of 10

meters. Also, 85 percent (85%) of the system velocity was within the range


28

of 0.2 – 3 m/s adopted while 15% of the velocity exceeded the adopted

velocity. The resultant effect of very high velocities in the system

accounted for the pipe burst and leakages detected within the system.

Hence, the system is inefficient and requires strengthening for optimum

performance.

(Yunarni Widiarti et al., 2020) One of the government's initiatives

to help reach the Sustainable Development Goals' goal is to meet people's

drinking water requirements (SDGs). A good distribution system is one of

the most essential factors in meeting drinking water requirements. The goal

of this study is to develop a plan for analyzing the hydraulic model of

potable water distribution. The EPANET 2.0 software was used in the

model. Land elevation, pipe distribution base map, inhabitants, and

discharge were among the data sets used. The findings revealed that the

current design did not meet the requirements for availability, hydraulics

analysis, or calibration. As a result, a redesign is required that meets all

criteria. For the new water distribution system, the findings of the new

design need a two-stage development procedure. According to hydraulic

analysis, more discharge is required to increase pressure and velocity. The

model has been calibrated by comparing simulation results to field data;

the pressure calibration result seemed to be 0.928, and the discharge

calibration result was 0.894. These two findings suggested that the

simulation's outcomes are strongly linked with field circumstances.


29

2.3. Summary

Many studies that dealt with designing, analyzing, and evaluating a

water distribution networks using multiple methods and programs such as

EPANET, WaterCAD, and WaterGems. The present study will analyze

and evaluate the characteristics of water distribution network for case-

study in the Holy Karbala province by using a WaterCAD program;

because this program has high efficiency in hydraulic analysis and

simulation. Because it can deal with the GIS program that gives details and

locations of the water distribution system, in addition to the AutoCAD

program from which we can import the network distribution map, in

addition to that the values resulting from the analysis are of high accuracy.

It was noted that in the study (Robert, 2019) the same program was used to

improve the pressures required for the system, but with a different method

for collecting data on flow quantities.

2.4. Gap of Knowledge

First: The field measurements of the water networks were not carried

out in different months of the year for the purpose of knowing the behavior

of the distribution system, its working mechanism, and the amount of real

consumption during one day. Secondly, a portable flowmeter was not used

to measure the real flows in pipes and junctions, but most of the data was

obtained from water meters in houses. Finally, the water quota of

individuals using the distribution system was not addressed and compared

to the actual consumption through withdrawal points.

Chapter Three

Theoretical

Chapter Three …………..……………..…….…………….. Theoretical

31

Chapter Three: Theoretical

3. Background

The network of the main water pipe, distributing pipelines and pure

water stations is an integrated water system. The network can be defined

as the set of pipes for transporting and distributing water according to the

demand areas. These pipes intersect with each other forming knots and thus

form closed or open loops. The water enters the network through some of

these junctions are called the supply junctions, which are often pumping

stations or high tanks, and the water comes out of the network for various

purposes of consumption from several other points known as withdrawal

points. There are several methods of analyzing networks in a routine

manner, such as finding the discharge magnitude in each pipe or the

pressure magnitude in the nodes. Among the main popular techniques of

network analysis were:

1. Hardy Cross Technique.

2. Sections Methods.

3. Newton Raphson Method.

4. Electrical Analog Method.

The Hardy Cross technique is considered one of the most common

techniques in the analysis field due to its ease of application and acceptable

results.

3.1. The Basic Laws for analysis

The basic laws can be summarized in the analysis for water networks

distribution, regardless of the method of analysis used (Swamee & Sharma,

2008), as follows:


32

1. Conservation of Mass: According to the rule of mass conservation,

mass cannot be created or destroyed. In a system, the change, outflows,

and inflows in mass storage all should be balanced. For a certain period,

the mass flow into and out of a controlling volume (via a virtual or

physical barrier) may be represented as:

𝑑𝑀 = 𝜌𝑖 𝑣𝑖 𝐴𝑖 𝑑𝑡 − 𝜌𝑜 𝑣𝑜 𝐴𝑜 𝑑𝑡 ……….…………… 3-1

where

dM = changing the mass of storage in the system (kg),

ρ = densities (kg/m3),

v = speeds (m/s),

A = areas (m2),

dt = time expanded (s).

2. Conservation of Energy: Energy is neither produced nor absent in any

isolated system, according to the Law of Conservation of Energy,

although it may be transformed from one form to another. That is, in

any closed loop, the algebraic total of energy and charges losses is zero.

3. The amount of discharge (Q) depends on the amount of head loss at

the beginning and end of the pipe (head difference), as following

formula:

ℎ𝑓 ∝ 𝑄𝑛, then ℎ𝑓 = 𝑘𝑄𝑛 ……………………………3-2

where

hf = head loss (m),

Q = the discharge (m/s3).

k = variable coefficient depends on different parameters, including

(pipe’s diameter, length, …. etc.)

Several of researchers in the field of network analysis have presented

several methods to determine a magnitude, and among the most commonly

used of these equations were:

1. Darcy-weisbach formula.

2. Hazen-Williams formula.


33

3.1.1. Darcy-Weisbach formula

The Darcy–Weisbach formula is an empirical formula that links the

head losses, or pressure loss, caused by friction over a specified pipe's

length to the average fluid flow velocity for an incompressible fluid. Henry

Darcy and Julius Weisbach are the names of the formula. There is currently

no more precise or generally applicable formula comparison with the

Darcy-Weisbach formula with the Colebrook formula and Moody diagram

(Bhave, 1991).

Figure 3-1:Moody diagram (Bhave, 1991).

Through which the value of the coefficient of friction can be found

through the intersection of the values, where its vertical axis consists of

Relative Pipe Roughness (E/D) and its horizontal axis is Reynolds Number

(Re), which determines the type of flow in pipes.

The Darcy-Weisbach equation has a lengthy history of development,

dating back to the 18th century and continuing until this day. Even though

it is named for two famous nineteenth-century engineers, many others have

contributed to the project. Darcy-Weisbach is a well-known equation that


34

provides linear friction losses in the situation of liquid flow under pressure

in a closed conduit:

ℎ𝑓 = 𝑓𝐿

𝐷

𝑉2

2𝑔 ……………………………. 3-3

Where

𝑓 =4 𝜏𝑜/𝛾

𝑣2/2𝑔 Darcy’s coefficient friction, also can obtaining from

Moody diagram,

g = acceleration due to gravity = 9.81 m/s2,

𝛾 = density of fluid (N/m3)

hf = head loss (m),

L =length of pipe (m),

D =pipe internal diameter (m), and

V=velocity (m/s).

Since basic force equilibrium and dimensional analysis enjoin that

ℎ𝑓 𝛼 𝐿 𝐷−1 𝑉2 𝑔−1, the Darcy-Weisbach equation is considered a logical

formula. However, a complex function of the pipe roughness, pipe

diameter, fluid kinematic viscosity, and flow velocity is the friction factor,

f. The uncertainty in f, which arises from the mechanics of the boundary

layer, hid the correct relationship and led to the development of many

empirical formulas that are irrational, dimensionally inhomogeneous.

A. Laminar Flow

At the beginning of the 1830's the difference between low and high-

velocity flows was clear and at the same time almost independent. The

scientist Jean Poiseuille (1799-1869) and Gotthilf Hagen (1797-1884)

determined low-velocity flow in small pipes. The two scientists did not use

a clear variable for the viscosity, but instead from this they developed

algebric operations with the first and second forces of temperature. One of

the most important results of Poiseuille's and Hagen's research is to obtain


35

accurate results. where the restriction was achieved on small pipes and low

velocity, and the equations they obtained were the first modern and high

accuracy fluid friction equations if they were compared to each other.

Hagen's work was more theoretically sophisticated, while Poiseuille has

more accurate measurements and observations of liquids other than water.

Until 1860, Newton's law of viscosity was not accomplished, and an

analytical derivation of laminar flow was mentioned by the scientist

Osborne Reynolds (1842-1912) the movement from laminar to turbulent

flow and it was found that can be distinguished by the modulus.

𝑅𝑒 =𝑉𝐷

𝜐 ……………………………. 3-4

Since Re in this time referred to as the Reynolds number and have

the scope for laminar flow in pipes is Re less than 2000, while turbulent

flow generally occurs for Re greater than 4000. The ill-defined, ill-behaved

region between those two values is called the critical zone. After the

mechanics and scope on laminar flow was well determined, it was a simple

matter to provide an expression for the Darcy f in the laminar range,

𝑓 =64

𝑅𝑒 ……………………………. 3-5

B. Turbulent Flow

In 1857 the scientist Henry Darcy (1803-1858) presented a new copy

of the Prony equation that relied on experiments with different types of

pipes over a wide velocity range from 0.012 to 0.50 m diameter. J.T.

Fanning (1837-1911) was seemingly the first to effectively join Weisbach's

equation with Darcy's better assessment of the friction factor. Instead of

finding attempting a new mathematical formula for f, he simply published

tables of f magnitudes taken from French, American, English and German

publications, with Darcy being the biggest source. where the designer


36

could search for the value of f from special tables after knowing the

roughness of the pipe material, diameter, and velocity.

For very low values of the relative roughness, Nikuradse’s implicit

equation:

1

√𝑓= 2 × 𝑙𝑜𝑔 (

𝑅𝑒.√𝑓

2.51) ……………………………. 3-6

and Colebrook’s explicit equation:

1

√𝑓= 1.8 × 𝑙𝑜𝑔 (

𝑅𝑒

6.9) ……………………………. 3-7

In the opposite case, the Von Karman relation holds large relative

roughness values.

1

√𝑓= 2 × 𝑙𝑜𝑔 (

3.7𝑒

𝐷⁄)……………………………. 3-8

Colebrook equation, also known as the Colebrook–White equation

is used worldwide covering the whole range of Reynolds numbers and

relative roughness:

1

√𝑓= −2 × 𝑙𝑜𝑔 (

𝑒𝐷⁄

3.7+

2.51

𝑅𝑒.√𝑓) ……………………………. 3-9

3.1.2. Hazen-Williams equation

An empirical formula widely used in water supply engineering for

the flow of water through pipes is due to G.S. Williams and A. Hazen. This

relationship, known as the Hazen-Williams formula (Bhave, 1991), is

𝑉 = 0.849 𝐶𝐻𝑊 𝑅0.63 𝑆0.54 ……………………………. 3-10

where

V = average velocity of flow in m/s,

CHW = Hazen-Williams (HW) coefficient,

R = hydraulic radius in m, and

S = hf/L slope of the energy line.


37

For circular pipes 𝑉 = 4𝑄/𝜋𝐷2, and 𝑅 = 𝐷/4. Substituting these

values and taking 𝑆 = ℎ𝑓/𝐿, equation (3-11) on simplification becomes

ℎ𝑓 =10.68 𝐿 𝑄1.852

𝐶𝐻𝑊1.852 𝐷4.87

……………………………. 3-12

in which L and D are in meters and Q in cubic meters per second. In

practice, the pipe diameter D may also be given in millimeters or

centimeters and the discharge Q in liters per minute, million liters per day

and several other units. Instead of converting the pipe diameter to meters

and pipe discharge to cubic meters per second for the entire network, it

may be advisable to replace 10.68 in equation (3-12) with an appropriate

value. Such values are given in table (3-2).

Table 3-1: Values of Constant in Hazen-Williams Formula (Bhave, 1991). Pipe

diameter,

D, in

Discharge, in

m3/s m3/min m3/h m3/d L/s L/min ML/d

m 10.68 5.438 x 10-3 2.769 x 10-6 7.694 x 10-9 2.969 x10-5 1.512 x 10-8 2.768 x 10-3

cm 5.869 x 1010 2.988 x 107 1.522 x 104 42.28 1.631 x105 83.07 1.521 x 107

mm 4.351 x 1015 2.215 x 1012 1.128 x 109 3.134 x 106 1.209 x1010 6.158 x 106 1.128 x 1012

The Hazen-Williams formula is derived for 𝑅 = 0.3 m and 𝑆 =

1/1000. Therefore, the Hazen-Williams coefficient CHW is dependent on

the R and S magnitudes and also the flow conditions. The Hazen-Williams

coefficient magnitudes for common pipe materials as recommended by

Lamont (1981) after examining 372 records are given in table (3-3). These

magnitudes are for a velocity of flow of about 0.9 m/s. These magnitudes

should be corrected as shown in table (3-4) when the velocities are

considerably above or below 0.9 m/s. Lamont emphasizes that the Hazen-

Williams formula is not suitable when the CHW magnitudes are appreciably

below 100.

The Hazen-Williams formula is more suitable for smooth pipes and

therefore for medium to large diameter new pipes. Although it is not quite


38

suitable for old pipes, the formula is used in practice by reducing the CHW

magnitudes.

Table 3-2:Values of Hazen-Williams Coefficient for Clean New Pipes of

Different Materials (Bhave, 1991).

Pipe Material CHW value for pipe diameter in millimeters

75 150 300 600 1200

Uncoated cast iron 121 125 130 132 134

Coated cast iron 129 133 138 140 141

Uncoated steel 142 145 147 150 150

Coated steel 137 142 145 148 148

Wrought iron 137 142 — — —

Galvanized iron 129 133 — — —

Coated spun iron 137 142 145 148 148

Uncoated asbestos

cement 142 145 147 150 —

Coated asbestos

cement 147 149 150 152 —

PVC wavy 142 145 147 150 150

Concrete 69-129 79-133 84-138 90-140 95-141

Pre-stressed

concrete — — 147 150 150

Spun cement-

lined; spun

bitumen-lined,

PVC, brass, lead,

copper

147 149 150 152 153

Newly scraped

mains 109 116 121 125 127

Newly brushed

mains 97 104 108 112 115

Scobey assembled results of more than 1000 determinations made

by himself and others on 147 pipelines ranging in diameters from 25 mm

to 5470 mm and suggested a relationship similar to the Hazen-Williams

formula but with the exponent of S as 0.53. White on the other hand, from

several tests on the glazed and unglazed pipelines, found an average

magnitude of 0.54 for the exponent of S, thereby confirming the exponent

of S in the Hazen-Williams formula.


39

Table 3-3: Correction Factors for Hazen-Williams Coefficients (Bhave, 1991).

CHW Value at

Velocity Below Velocity Above,

0.9 m/s for Each Halving,

Rehalving of Velocity Relative

to 0.9 m/s

Velocity Below Velocity Above,

0.9 m/s for Each Doubling,

Redoubling of Velocity Relative to

0.9 m/s

CHW below 100 add, 5% to CHW value subtract, 5% from CHW value

CHW from 100 to 130 add, 3% to CHW value subtract, 3% from CHW value

CHW from 130 to 140 add, 1% to CHW value subtract, 1% from CHW value

CHW above 140 subtract, 1% from CHW

value

add, 1% to CHW value

The ease of applying this formula has made its use more common

than others, especially in designing water distribution networks and

sprinkler and drip irrigation networks. The ease of applying this formula

because the roughness coefficient magnitude (CHW) takes a fixed

magnitude for all discharges (Q) unlike the coefficient of friction (f) in the

Darcy-Weisbach formula. Conversely, the results of the friction losses

calculations will be less than accurate when using a Darcy-Colebrook-

White formula.

When using the Hazen-Williams formula find that friction losses are

inversely proportional to the magnitude of (CHW), If it takes into account

the change in the roughness characteristics of the tube with time during

use, it is better to choose a low magnitude for this factor during the design

as a safety factor for the future of the network.

The idea of analyzing water distribution networks using any of the

previously mentioned common formulas lies in obtaining the magnitudes

of discharges (Q) and energy losses (of which friction losses (hf) constitute

the largest proportion of them) and this is done for all parts of the network

by fulfilling the basic conditions or laws for energy and mass conservation.

In other words, the analysis of any network is a solution to the non-linear

set of simultaneous formulas, since the relationship of discharge with

energy loss is a non-linear relationship.


40

3.2. Network Analysis Methods

The main methods used in the calculations for analyzing water

networks can be divided as follows:

1. Manual Method: The method of calculations for designing and

analyzing water networks manually is the first method that was

previously available with the aim of achieving the basic laws, whether

by trial and error or by applying the Hardy Cross equation. Due to the

enormous calculations required to be performed in network analysis,

this method was lengthy and tedious, making the designer or analyst

content with approximate results.

2. Computerize Method: These methods have spread after the

development and spread of computers, which sensibly facilitated

manual calculations, and it became possible to analyze entire networks

with less effort than the manual method requires. These computers,

with their large memory and high speed, were helped by using other

analysis methods than the Hardy Cross method, such as the Sections

method and the Newton Raphson method.

3. Electrical Analog Method: This method is based on the similarities

between the flow of electric current in electrical circuits and the flow

of water in networks and pipes, as the current represents the discharge,

the voltage represents the charge (pressure), and the resistance

represents the friction. The technical configuration process to make the

model is complex and very expensive. In addition, the model prepared

for one network cannot be used for another network, and this

determines the use of this method.

3.3. Hardy Cross Method

Professor Hardy-Cross developed the first systematic technique of

network analysis, described as the head equilibrium or 'loop' technique that


41

applies to systems with closed systems of pipes. Presumed pipe flow rates

that satisfy the continuity criterion formula (3-1) are modified loop by loop

till formula (3-2) is met within a modest tolerance in each loop. Presumed

junction head heights are progressively changed until formula (3-1) is

convinced at every junction within a modest tolerance, according to a later

technique developed by Cornish; it may be used in both open-loop and

close- loop networks. This method is considered the easiest available in the

field of water network analysis (Swamee & Sharma, 2008), and it can be

classified into two methods:

3.3.1. Head Balance Method

Closed-loop pipe systems may benefit from his approach. It is likely

more frequently used in comparison with the quantity balancing technique

in this kind of network. Professor Hardy-Cross invented the head balance

technique, which is typically called the Hardy-Cross technique. The major

nines in a system of water distribution are shown in figure (3-2).

The system's outflows have often been believed to happen at nodes

(junctions); these assumptions resulted in regular flows in the pipelines,

simplifying the study.

Figure 3-2: Closed loop type network (Steel, 1979).

The head balancing technique seems to be an iterative process

depending on previously predicted flows in the pipes for a particular pipe


42

system with specified junction outflows. These flows must meet the

continuity requirement at each intersection.

The head balancing criteria states that the mathematical total of the

head losses through any closed - ring system is zero, with the sign

convention of positive clockwise flows (and corresponding head losses).

A single pipe has a head loss as follows:

ℎ𝑓 = 𝑘 𝑄2 ………………………………………….……. 3-13

Once the flow has been assessed with an error ∆𝑄

ℎ𝑓 = 𝑘(𝑄 + ∆𝑄)2 = 𝑘 [𝑄2 + 2 𝑄 ∆𝑄 + (∆𝑄)2] …………… 3-14

Neglecting ∆𝑄2 , assuming ∆𝑄 to be small:

ℎ𝑓 = 𝑘 (𝑄2 + 2 𝑄 ∆𝑄) …………………………..…………. 3-15

Make a closed-loop now. To ensure continuity, ∑ℎ𝑓 = 0 and ∆𝑄

are similar to every pipe.

∑ℎ𝑓 = ∑𝑘𝑄2 + 2∆𝑄 ∑𝑘𝑄 = 0 ………………………..……. 3-16

i.e. ∆𝑄 = −∑𝑘𝑄2

2∑𝑘𝑄= −

∑𝑘𝑄2

2∑𝑘𝑄2

𝑄

………………………………. 3-17

which may be written ∆𝑄 = −∑ℎ

2∑ℎ/𝑄

whereas:

Depending on the expected flow, h = is the head loss in a pipe. Q..

3.3.2. Quantity Balance Method

Figure (3-3) shows a branching pipe system that transports water

from repossessing reservoir A to service reservoirs D, C, and B. F has been

a well straight egress from J.


43

Figure 3-3: Branched-type pipe network (Steel, 1979).

If ZJ is the true elevation of the pressure head at J the head loss along

each pipe can be expressed in terms of the difference between ZJ, and the

pressure head elevation at the other end.

For example: ℎ𝑓𝐴𝐽 = 𝑍𝐴 − 𝑍𝐽.

Expressing the head loss in the form: ℎ𝑓 = 𝑘𝑄2, N such equations

can be written where N is the number of pipes.

i.e.

[ [𝑍𝐴 − 𝑍𝐽]

[𝑍𝐵 − 𝑍𝐽]

⋮ ⋮[𝑍𝐼 − 𝑍𝐽]]

=

[ (𝑆𝐼𝐺𝑁)𝑘𝐴𝐽(|𝑄𝐴𝐽|)

2

(𝑆𝐼𝐺𝑁)𝑘𝐵𝐽(|𝑄𝐵𝐽|)2

⋮

(𝑆𝐼𝐺𝑁)𝑘𝐼𝐽(|𝑄𝐼𝐽|)2]

……..… 3-18

(SIGN) is + or – according to the sign of (ZI - ZJ). Therefore, positive

flows toward the junctions and negative flows opposite to the junction

exist.

KIJ is composed of friction loss and minor loss coefficients.

The continuity equation for flow rates at J is:

∑𝑄𝐼𝐽 − 𝐹 = (𝑄𝐴𝐽 + 𝑄𝐵𝐽 + 𝑄𝐶𝐽 + 𝑄𝐷𝐽) − 𝐹 = 0 ……..… 3-19

Examining formulas (3-18) and (3-19), it is clear that the right

magnitude of ZJ will provide magnitudes of 𝑄𝐼𝐽 derived from formula (3-

and in

general


44

18) that will fulfill formula (3-19). We may get the formula (3-18) by

rearranging the equations.

[𝑄𝐼𝐽] = [(𝑆𝐼𝐺𝑁) (|𝑍𝐼−𝑍𝐽|

𝑘𝐼𝐽)1/2

] …….………………………… 3-20

By establishing an initial estimation of ZJ, computing the pipeline

discharges from formula (3-20), and verifying the continuity requirement

in formula (3-20), the magnitude of ZJ may be determined utilizing an

iterative formula (3-19).

If (∑𝑄𝐼𝐽 − 𝐹) ≠ 0 (with acceptable bounds) a correction, ∆𝑍𝐽 is

made to 𝑍𝐽 and the procedure repeated until equation (3-19) is reasonably

satisfied. A systematic correction for ∆𝑍𝐽 can be developed: expressing the

head loss along a pipe as ℎ𝑓 = 𝑘 𝑄2, for a small error in the estimate 𝑍𝐽,

the correction ∆𝑍𝐽 may be obtained as:

∆𝑍𝐽 =2(∑𝑄𝐼𝐽−𝐹𝐽)

∑𝑄𝐼𝐽

ℎ𝑓𝐼𝐽

………………………………………..…… 3-21

3.4. Newton-Raphson Method

The Newton–Raphson technique, unlike the Hardy Cross technique,

analyzes the whole piping system. For systems of nonlinear formulas, the

Newton–Raphson technique is a strong numerical approach. Assume three

nonlinear formulas exist (Steel, 1979):

𝐹1(𝑄1, 𝑄2, 𝑄3) = 0

𝐹2(𝑄1, 𝑄2, 𝑄3) = 0

𝐹3(𝑄1, 𝑄2, 𝑄3) = 0

] …………………………….……… 3-22

Q1, Q2, and Q3 must all be answered. Decide on a beginning point

(Q1, Q2, Q3). Consider that the solutions of the mathematical formula is

(Q1+∆ Q1, Q2+∆ Q2, Q3+∆ Q3). That is,


45

𝐹1(𝑄1 + ∆𝑄1, 𝑄2 + ∆𝑄2, 𝑄3 + ∆𝑄3) = 0

𝐹2(𝑄1 + ∆𝑄1, 𝑄2 + ∆𝑄2, 𝑄3 + ∆𝑄3) = 0

𝐹3(𝑄1 + ∆𝑄1, 𝑄2 + ∆𝑄2, 𝑄3 + ∆𝑄3) = 0

] ………..…… 3-23

Using Taylor's series to expand the above formulas,

𝐹1 + (𝜕𝐹1

𝜕𝑄1) ∆𝑄1 + 𝐹1 + (

𝜕𝐹1

𝜕𝑄2)∆𝑄2 + 𝐹1 + (

𝜕𝐹1

𝜕𝑄3) ∆𝑄3 = 0

𝐹2 + (𝜕𝐹2

𝜕𝑄1)∆𝑄1 + 𝐹2 + (

𝜕𝐹2

𝜕𝑄2) ∆𝑄2 + 𝐹2 + (

𝜕𝐹2

𝜕𝑄3) ∆𝑄3 = 0

𝐹3 + (𝜕𝐹3

𝜕𝑄1)∆𝑄1 + 𝐹3 + (

𝜕𝐹3

𝜕𝑄2) ∆𝑄2 + 𝐹3 + (

𝜕𝐹3

𝜕𝑄3) ∆𝑄3 = 0]

… 3-24

Arranging the above set of equations in matrix form,

[

𝜕𝐹1/𝜕𝑄1 𝜕𝐹1/𝜕𝑄2 𝜕𝐹1/𝜕𝑄3

𝜕𝐹2/𝜕𝑄1 𝜕𝐹2/𝜕𝑄2 𝜕𝐹2/𝜕𝑄3

𝜕𝐹3/𝜕𝑄1 𝜕𝐹3/𝜕𝑄2 𝜕𝐹3/𝜕𝑄3

] [

∆𝑄1

∆𝑄2

∆𝑄3

] = − [𝐹1

𝐹2

𝐹3

] ……………..… 3-25

Solving Eq. (3-25)

[

∆𝑄1

∆𝑄2

∆𝑄3

] = − [

𝜕𝐹1/𝜕𝑄1 𝜕𝐹1/𝜕𝑄2 𝜕𝐹1/𝜕𝑄3

𝜕𝐹2/𝜕𝑄1 𝜕𝐹2/𝜕𝑄2 𝜕𝐹2/𝜕𝑄3

𝜕𝐹3/𝜕𝑄1 𝜕𝐹3/𝜕𝑄2 𝜕𝐹3/𝜕𝑄3

]

−1

[𝐹1

𝐹2

𝐹3

]……...… 3-26

The discharges seem to be better as a result of knowing the

modifications

[

𝑄1

𝑄2

𝑄3

] = [

𝑄1

𝑄2

𝑄3

] + [

∆𝑄1

∆𝑄2

∆𝑄3

] ………………………….….… 3-27

It could be observed that inverting the matrix repeatedly for a

massive network is time-intensive. As a result, the inverting matrix was

kept and utilized at a minimum of three times to get the adjustments.

In summary, there is no technique for solving such sets of equations

directly, and all pipeline network analysis approaches are iterative. Pipes

network analysis is indeed most suited to digital computer applications like

(EPANET, WaterGEMS, WaterCAD, etc.), although basic networks may


46

be evaluated using a pocket calculator. Also, convergence is considerably

faster with these techniques; nevertheless, because several simultaneous

formulas must be solved, depending on the size of the network, the Hardy-

Cross and Newton-Raphson techniques are only practical for computer

assessment.

3.5. Computer Models

3.5.1. History of computer models.

Before automation, solving network for distributions of flow and

pressure needed laborious and time-consuming manual computations. The

Hardy-Cross numerical technique of analysis for deterministic networks

was used to do these computations. Due to the obvious time and effort

needed to find a solution, only basic pipeline systems with a few loops are

simulated and under restricted circumstances. Electric counterparts were

the first computers used in network modeling, following by huge

mainframe digital computers and smaller microcomputers. A laptop

computer's processing capability now is much better than the first

computing machines, which would take up many floors in an office

building and cost a fraction of the price.

Several early computer models lacked interactive on-screen visuals,

which limited engineers' opportunity to produce and understand model

runs. The user interface seemed basic at best, and it was often an

afterthought. Punch cards or prepared American Standard Coding for

Information Interchange (ASCII) files produced using a text editor were

used to input data. Errors were frequent, and getting a data file to run might

take days, if not weeks, based on the scale and complexity of the system to

be analyzed. A large tabular summary of important network findings was

typically the model output. The findings were time-consuming to interpret,

and usually required hand-drawing pressure contour on system maps.


47

Network modeling had already gained renewed dimensions as a

result of the widespread usage of microcomputers during the last two

decades. Today's engineers use computer models to address a wide range

of hydraulic issues. In the water business, interactive on-screen graphics

are becoming standard for entering and editing network data, as well as

color coding and displaying network maps, characteristics, and analysis

findings. This makes it simpler for the engineer to build, calibrate, and

modify the model, as well as see what's going on in the network in different

scenarios, including noncompliance with system performance

requirements. The engineer may now spend more time thinking about and

assessing system changes rather than scrolling thru pages of computer

printouts, resulting in better operation and design suggestions. The

daunting job of gathering and arranging network data and understanding

huge findings has been considerably eased by the current generation of

computer modeling (Bhadbhade, 2004).

3.5.2. Software packages.

Several of the software packages obtainable offer further capabilities

beyond standard hydraulic modeling, such as water quality assessment

(both reactive species and conservative), network optimization, real-time

simulation, automated network calibration, system head curve generation,

surge (transient) analysis, fire flow modeling, pressure and leakage

management, power cost and energy calculation, travel time determination,

and multi-quality source blending. Some sophisticated models could even

accommodate the full library of hydraulic network components including

reservoirs and multiple inlet/outlet tanks, variable head reservoirs,

cylindrical and variable cross-sectional area tanks, turbines, fixed-and

variable speed pumps, throttle control valves, float valves, flow control

valves, pressure breaker valves, and pressure-regulating valves, pressure-


48

sustaining valves. Computer network models offer a useful tool for

generating educated choices to support various organizational initiatives

and policies because of their predictive capabilities. Modeling was critical

for obtaining a thorough knowledge of system dynamic behavior, as well

as for training operators, maximizing the usage of existing facilities,

lowering operating costs, predicting future facility needs, and resolving

water quality distribution problems (Bhadbhade, 2004).

3.5.3. Development of a system model.

As previously stated, today's computerized instruments for

engineers seem to be impressive and powerful. After choosing the right

software, data must be entered into it to create a computer program of the

water system during the investigation. Physical properties of the system,

including reservoir, topography, lengths and pipe sizes and pump

properties, and also anticipated nodal requests, are all input data.

The mean day flow is distributed across the system is proportional

to land usage, which is how nodal needs are often developed. This is

usually done by determining a demand area for each node, measuring the

area of each various land use within the required zone, expanding the zones

of every various land use in the required zone by its respective standard

day water duty (transformed to L/sec or gal/min), summing the water duties

to every land use within the required zone, and applying the total amount

at the node. The worldwide peaking parameters are then applied to the

water system computer program (Bhadbhade, 2004).

3.6. Water CAD

Water CAD is a useful tool for designing, analyzing, and improving

existing water distribution systems in cities. Water CAD was chosen for

this study because it has a high-quality manual, integration with other


49

external software such as Auto CAD, GIS background support, and

Microsoft Excel, requires less effort and time to build a model than others,

rule-based controls, and ground elevation extraction from shape files and

CAD drawings, and it requires less effort and time to build a model than

others. The Water CAD software also can examine the hydraulics for

various demands at a single node with changing time patterns. Determine

fire flow capabilities for hydrants, model tanks, including those that are not

circular, and model various valve operations using the Hazen-William,

Darcy-Weisbach, or Chezy-Manning equations to account for differing

frictional head losses (Bhadbhade, 2004). The available data and plan of

the distribution network of the water supply system were analyzed to

analyze the distribution network system. Input data collecting, model

creation in Bentley Water Cad, data entry (Elevations, XY coordinates,

base demand, pump data, tank data, and pipe data), model testing, and

hydraulic modeling, as well as problem analysis, are all part of the

modeling process.

The following data was used as input for the distribution system

analysis:

Pipes: Pipe diameters, lengths, material type

Nodes: Elevations and base requirement.

Tanks: the tank's base, minimum and maximum elevations, and

diameter.

Pumps: The pump curve is the most significant characteristic in

pump functioning. Another factor to consider is the pump's

elevation.

The reservoir is a term used to describe a body of water. – elevation.

After all of the parameters are set, the simulation model's outputs are

displayed.


50

Flows through the system at all times.

Flow rates in the pipes.

The tanks' levels.

The curve of the pump.

Water quality and age.

Node pressure head.

Head losses.

3.6.1. Junctions

Junctions are sites in the network where links come together and

water enters or exits (Rossman, 2000). Elevation above some reference

(typically mean sea level), position (X-coordinate, Y-coordinate), and

water demand are the most fundamental input variables for junctions (rate

of withdrawal from the network).

3.6.2. Reservoirs

Reservoirs are nodes in the network that represent an infinite

external water source or sink. The hydraulic head of a reservoir is the most

important input attribute. Because a reservoir is a network's boundary

point, what happens within the network does not effect on its head. As a

result, it doesn't have any computed output attributes.

3.6.3. Pipes

Pipes connect two points in a network to transport water. The flow

is from the end of the higher hydraulic head to the end of the lower

hydraulic head. The start and end nodes, diameter, length, roughness

coefficient, and status were the main hydraulic input parameters for pipes

during the analysis (open or closed). Pipe head loss, velocity, and flow

were among the computed results. The Hazen-Williams equation was used

to calculate friction head losses, with the assumption that viscosity was


51

constant. The following was the Hazen William equation for calculating

friction head losses:

ℎ𝑓 =10.68 𝐿 𝑄1.852

𝐶1.852 𝐷4.87 ………………………..…………… 3-28

Where,

hf = friction of head;

L = the pipe length (m);

Q = discharge (m3/s);

D = diameter (mm) and

C = roughness coefficient, which varies depending on pipe material

and age.

Chapter Four

Field Work

Chapter Four…………..……………..…….…..………….. Field Work

53

Chapter Four: Field Work

This chapter presents the location, layout, characteristics, and

recorded data for the case study that has been studied which was one of the

water main lines in the Karbala province.

4.1. Location

The case study is located in Karbala city, Iraq. Karbala is an Iraqi

city and the center of Karbala province is located in the Middle Euphrates

region. It’s located 105 kilometers south of Baghdad, on the edge of the

desert in the Western Euphrates and the left side of the Al-Hussainiya

district. For more accuracy, the city is located between longitudes of 43˚

15ʹ 0ʺ E - 44˚ 15ʹ 0ʺ E, and latitudes of 32˚ 7ʹ 30ʺ N - 32˚46ʹ 5ʺN the location

of the water pumping project is shown in figure 4-1.

Figure 4-1: Geographical location of Karbala relative to Iraq (Mohammed, 2017).

One of the main objectives of this study is to assessment of the

efficiency and improve the operability of one of the main water pipes in

Karbala city, and Karbala province is an important financial source for the

Iraqi state and for the people who profit through their work from religious

tourism imports, where the main water pipe is linked to three branches


54

belonging to the Karbala Water Directorate, which are the city center and

the two branches of Al-Kheirat and Al-Jadwel Algarby, which are

witnessing a remarkable development infrastructure services.

Many obstacles that faced the field work. Firstly, the difficulty of

excavation extracts the junctions branching from the main line of the water

distribution system, as it requires high coordination with the Karbala Water

Directorate to get formal approvals from its affiliated branches, to be the

main line is administratively followed to three offices, which are the Al-

Kheirat and Al-Jadwel Algarby, sector network water center. Secondly,

they cannot use the equipment outside the water sectors above, and this

needs to be the good stuff of these sectors because they are government

property under the responsibility of these offices. In addition to the

excavation problem, there is another issue that required high accuracy, with

a few available workers and equipment, and because the workers have a

large number of works assigned to them as well as to the issue of the curfew

that accompanied the corona pandemic, therefore delay has happened in

excavation works. Finally, some citizens are working above the connection

sites, and keep them away requires an additional effort. Field works were

performed to obtain data on the junction’s sites branching from the main

line to insert these data into the computer program used in the analysis. The

surveying work was conducted at different times of summer, autumn and

winter and different hours of the day utilizing an Ultrasonic flowmeter to

measure the actual water consumption of the inhabitants, as well as to

measure the operating pressure for those locations and the same periods.


55

4.2. Al-Sijlah and Al-Feyadh Complexes Project

The main water pipe that feeds from the Al-Sijlah and Al-Feyadh

complex project as located in the Al-Kheirat township, where is the

location of the pumping station. The main water pipe is supplied with water

through a pumping station that withdraws water directly from the

Euphrates river. The pumping station is located at the longitude of 44° 17’

13’’ E and latitude of 32° 24’ 33” N as shown in figure 4-2.

Figure 4-2: Geographical location of the main water pipe (Karbala

Water Directorate).

The Sijlah complex project contains an intake to draw water directly

from the Euphrates river. This water is transported to coagulation,

flocculation, and sedimentation processes to remove much of the colloidal


56

materials that cause turbidity, then collected the water in a press-steel tanks

and pumped to the main water pipeline as shown in the layout of the project

plan which is shown in figure 4-3. The project can produce water for

domestic use of approximately 1200 m3/hr.

Figure 4-3: Layout plan of the Al-Sijlah and Al-Feyadh complex project

(Karbala Water Directorate).

The collected water is pumped via two working pumps with design

capacity of each of 600 m3/hr. and two pumps in a break working

alternately, meaning that the amount of water pumped into the main water

pipe from the operational side is 1200 m3/hr.

4.3. The Main Water Pipe

The water is pumped by pumps to the main water pipe. The main

water pipe which has a diameter of 800 mm and of ductile iron-type which

receives water from these water projects, passing through the villages and

countryside on the side of the road, and reaching the Najaf road, where it

runs along the Husseiniyat on the road to the holy city of Karbala. The

water compacts that pump water are located in the area of Al-Kheirat,

specifically in the Al-Sijlha area, as mentioned that previously, and this


57

water conveyance line was established in 2017 and is considered one of the

main conveyance lines in the governorate as the most important linkages

for supplying water to Karbala International Airport site, and it is one of

the important infrastructure projects that contribute to the movement

Visitors, if it is completed, and the ( plans to increase the design capacity

of the main water pipe to include all areas to be fed with water from it.

4.3.1. Existing Distribution System

The main water pipe's working system is known as the "dead ends"

system or "tree branches," because it consists of a main pipe that transports

water and secondary pipes that branching off of it at nodes.

4.3.2. Connections junctions

The junctions are the points where pipes meet. Supplied reservoirs

and storage tanks, for example, are considered junctions because their

(HGL) is defined at the start. There are other types of junction for which

the (HGL) has not yet been determined and for which the pipe network

analysis must be performed. The elevation of all junctions should be

specified above sea level. System maps or drawings can sometimes be used

to determine a junction's elevation (Sileshi, 2011).

The main water pipe has eight branching points in the form of seven

connections, seven of which are 225 mm in diameter of a PVC plastic pipe,

and the last link is 160 mm in diameter according to the data of the Karbala

water directorate as follows:

1. The first link is away from 2000 meters from the pumping station.

2. The second link is away from 7952 meters from the pumping

station.

3. The third link is away from 9402 meters from the pumping station.


58

4. The fourth link is away from 12002 meters from the pumping

station.

5. The fifth link is away from 19252 meters from the pumping station.

6. The sixth link is away from 21452 meters from pumping the

station.

7. The seventh link is away from 27352 meters from the pumping

station.

8. The eighth link at is away from 29652 meters from the pumping

station.

4.4. Field Recording Data

When analyzing any water system, it is critical to understand the

sources supplying water to the system. Without an adequate source, even

the best-designed water systems will fail to deliver the required flow to

water users (Datwyler, 2012).

Figure 4-4: The different ultrasonic devices using during record data.


59

The data were collected by taking readings of the discharges in the

main water pipe and pressures at each connection by using an Ultrasonic

flowmeter works through sensors placed on the back of the pipe from both

sides and enters its data that includes the type of pipe material with the

diameter and thickness of the walls in turn the device accurately measures

the amount of flow passing through the pipe it represents the real

consumption and a pressure gauge, which is placed on the locations of the

branches after perforating the pipe wall, in to measure the pressure head by

gradations installed in it, respectively. Field data were recorded during

three different seasons: the summer, autumn and winter seasons with

different times of the day. The numbers of consumers were obtained from

the branches to which the water main pipe belongs.

Figure 4-5: The pressure gauge using for record data.


60

4.4.1. Recording data in the summer, specifically the month of August

Table 4-1: Recording data during morning operation.

location Elevation

(m)

Discharge

(m3/hr)

Pressure

(bar) Inhabitants

At pump station 30.8 942 1

Junction 1 25 212 0.5 5000

Junction 2 28.5 178 0.2 6000

Junction 3 27.5 122 0.1 1000

Junction 4 24.27 153 0.1 6000

Junction 5 25.67 127 0.05 5000

Junction 6 26.94 83 0.05 5000

Junction 7 24.37 36 0.05 3000

Junction 8 25 31 0.05 5000

Table 4-2: Recording data during afternoon operation.

location Elevation

(m)

Discharge

(m3/hr)

Pressure

(bar) Inhabitants


Junction 1 25 197 0.5 5000

Junction 2 28.5 179 0.2 6000

Junction 3 27.5 108 0.1 1000

Junction 4 24.27 147 0.1 6000

Junction 5 25.67 122 0.05 5000

Junction 6 26.94 79 0.05 5000

Junction 7 24.37 58 0.05 3000

Junction 8 25 41 0.05 5000

Table 4-3: Recording data during evening operation.

location Elevation

(m)

Discharge

(m3/hr)

Pressure

(bar) Inhabitants


Junction 1 25 202 0.5 5000

Junction 2 28.5 178 0.2 6000

Junction 3 27.5 113 0.1 1000

Junction 4 24.27 152 0.1 6000

Junction 5 25.67 127 0.05 5000

Junction 6 26.94 79 0.05 5000

Junction 7 24.37 53 0.05 3000

Junction 8 25 36 0.05 5000


61

4.4.2. Recording data in the autumn, specifically the month of October


location Elevation

(m)

Discharge

(m3/hr.)

Pressure

(bar) Inhabitants


Junction 1 25 197 0.5 5000

Junction 2 28.5 181 0.2 6000

Junction 3 27.5 127 0.1 1000

Junction 4 24.27 146 0.1 6000

Junction 5 25.67 122 0.05 5000

Junction 6 26.94 82 0.05 5000

Junction 7 24.37 56 0.05 3000

Junction 8 25 24 0.05 5000

Table 4-4-5: Recording data during afternoon operation.

location Elevation

(m)

Discharge

(m3/hr.)

Pressure

(bar) Inhabitants


Junction 1 25 195 0.5 5000

Junction 2 28.5 183 0.2 6000

Junction 3 27.5 113 0.1 1000

Junction 4 24.27 142 0.05 6000

Junction 5 25.67 118 0.05 5000

Junction 6 26.94 79 0.05 5000

Junction 7 24.37 78 0.05 3000

Junction 8 25 39 0.05 5000


location Elevation

(m)

Discharge

(m3/hr.)

Pressure

(bar) Inhabitants


Junction 1 25 193 0.5 5000

Junction 2 28.5 178 0.2 6000

Junction 3 27.5 114 0.1 1000

Junction 4 24.27 143 0.05 6000

Junction 5 25.67 119 0.05 5000

Junction 6 26.94 88 0.05 5000

Junction 7 24.37 69 0.05 3000

Junction 8 25 29 0.05 5000


62

4.4.3. Recording data in the winter, specifically the month of December


location Elevation

(m)

Discharge

(m3/hr.)

Pressure

(bar) Inhabitants


Junction 1 25 191 0.5 5000

Junction 2 28.5 181 0.1 6000

Junction 3 27.5 127 0.1 1000

Junction 4 24.27 141 0.1 6000

Junction 5 25.67 139 0.05 5000

Junction 6 26.94 84 0.05 5000

Junction 7 24.37 58 0.05 3000

Junction 8 25 21 0.05 5000

Table 4-8: Recording data during afternoon operation.

location Elevation

(m)

Discharge

(m3/hr.)

Pressure

(bar) Inhabitants


Junction 1 25 181 0.5 5000

Junction 2 28.5 178 0.1 6000

Junction 3 27.5 117 0.1 1000

Junction 4 24.27 137 0.1 6000

Junction 5 25.67 135 0.05 5000

Junction 6 26.94 84 0.05 5000

Junction 7 24.37 72 0.05 3000

Junction 8 25 31 0.05 5000


location Elevation

(m)

Discharge

(m3/hr.)

Pressure

(bar) Inhabitants


Junction 1 25 184 0.5 5000

Junction 2 28.5 178 0.1 6000

Junction 3 27.5 123 0.1 1000

Junction 4 24.27 139 0.1 6000

Junction 5 25.67 139 0.05 5000

wiping Junction 6 26.94 82 0.05 5000

Junction 7 24.37 59 0.05 3000

Junction 8 25 38 0.05 5000


63

Given the aforementioned data that the areas at the end of the line

do not fully receive a sufficient quantity of water. The field study was

conducted on the operation process and the amount of discharges coming

out of the junctions at the node sites was measured by an ultrasonic

flowmeter and at different times during the summer, autumn and winter

seasons with different times of the day. The data collection will be used for

the hydraulic analysis of the main water pipe using the WaterCAD

program. In the next chapter.

Figure 4-6: during record data.

Chapter Five

Results and

Discussion

Chapter Five …………..…………..…..…….… Results and Discussion

65

Chapter Five: Results and Discussion

This chapter describes the analysis and discussion of the recorded

field data and data generated by the WaterCAD simulation application for

the mainline pipe, then a comparison was made between the simulated

results and the recorded data. The analysis and discussion will be in two

stages: the first stage; is an analysis of the recorded field data alone while,

the second stage: is the analysis of data generated by the WaterCAD

simulation application with field recorded data.

The supply might come from pumps, storage tanks, or reservoirs, or

it could be defined as inflows or outflows at certain points in the network,

and the pressures or head losses thru the system are calculated using the

known flow rates (Izinyon & Anyata, 2009b). The operation performance

was observed under peak consumption and with an extended period

simulation of 24-hours. The performance was evaluated based on existing

hydraulic conditions.

5.1. Analysis of the recorded field data of Main water pipe

The path of the mainline pipe was determined, also branch pipes at

each junction to feed the neighboring areas, and the number of residents in

those areas was estimated based on the site surveys of the water branches

there belong to Karbala water directorate, as indicated in chapter four. In

this part of the analysis, it will be considered that the flow is steady.

The discharge quantities passing through each pipe that branched

from the mainline were measured by the ultrasonic flowmeter. It was

consumed in the areas that passed through the main pipeline branches.

These quantities are compared to the hypothetical consumption quantities

computed from the per capita consumption rate multiplied by the

population of those areas.


66

5.1.1. Consumption type in a mainline pipe

The consumption data for every customer has been gathered to

assess the water loss in the distribution network. The amount of water used

may be estimated based on the rate of consumption of individuals.

According to the rules of the Ministry of Municipalities and Public Works'

General Directorate of Water, the estimated consumption rate of persons

for water fit for human use per capita is as follows:

1. A person living in the city is 450 liters per day.

2. A person living in the township is 360 liters per day.

3. A person living in villages and rural areas is 250 liters per day.

4. The percentage of lost in networks ranges 20%-45%

The study area in the present study is the township area, so the

consumption rate was determined based on a magnitude 360 liters per

capita per day, the percentage of losses was assumed as 35% of the

consumed quantity, so the total consumption rate with losses was 486 liters

per capita per day. The number of consumers who use each junction was

shown in Table 4-1 in Chapter four to calculate the estimated or

hypothetical discharge for each junction, as following:

𝑨𝒗𝒆𝒓𝒂𝒈𝒆 𝒅𝒐𝒎𝒆𝒔𝒕𝒊𝒄 𝒅𝒆𝒎𝒂𝒏𝒅 = 𝒄𝒐𝒏𝒔𝒖𝒎𝒑𝒕𝒊𝒐𝒏 𝒓𝒂𝒕𝒆 × 𝑷𝒐𝒑𝒖𝒍𝒂𝒕𝒊𝒐𝒏

After finding the amount of the approximate consumption at each

junction, the actual discharge measured by the ultrasonic flow meter is

compared with the estimated approximate discharge, using the same

equation in the study(Alshammari, 2000), and the percentage of scarcity

and loss in each junction is determined as follows:

𝐏𝐞𝐫𝐜𝐞𝐧𝐭 𝐨𝐟 𝒔𝒄𝒂𝒓𝒄𝒊𝒕𝒚 𝐨𝐫 𝐥𝐨𝐬𝐬𝐞𝐬 % =𝐐𝐀−𝐐𝐄

𝐐𝐄× 𝟏𝟎𝟎 % Equation 5-1

where:


67

QA: Actual consumption discharge measured by the ultrasonic

flowmeter.

QE: Estimation consumption discharge.

The resulting magnitude from the previous equation is a percentage

of scarcity or losses, and the sign of percent magnitude indicates that this

percentage is scarcity or losses in the supplied quantities, as follows:

(+ve) The positive sign indicates that the resulting percentage is a loss in

the supplied quantities.

(-ve) The negative sign indicates that the resulting percentage is a scarcity

in the supplied quantities.

1. Junction-1

From Table 4-1, the number of servants in this Junction is 5000

persons and by multiplying this number by the daily consumption rate,

it can be obtained the estimated approximate consumption in this

junction using the following equation:


𝑨𝒗𝒆𝒓𝒂𝒈𝒆 𝒅𝒆𝒎𝒂𝒏𝒅 =𝟒𝟖𝟔𝑳

𝑪.𝒅× 𝟓𝟎𝟎𝟎𝑪 ×

𝟏𝒎𝟑

𝟏𝟎𝟎𝟎𝑳×

𝒅

𝟐𝟒𝒉𝒓= 𝟏𝟎𝟏. 𝟐𝟓 𝒎𝟑/𝒉𝒓

On this basis, the approximate consumption rate in this junction

is 101.25 𝑚3/ℎ𝑟. Using the ultrasonic flowmeter, the discharge

(realistic consumption) passing through this junction measured is 212

𝑚3/ℎ𝑟, so this junction contains a percentage of losses equal to:

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒍𝒐𝒔𝒔𝒆𝒔 % =𝑸𝑨 − 𝑸𝑬

𝑸𝑬× 𝟏𝟎𝟎 %

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒍𝒐𝒔𝒔𝒆𝒔 % =𝟐𝟏𝟐 − 𝟏𝟎𝟏. 𝟐𝟓

𝟏𝟎𝟏. 𝟐𝟓× 𝟏𝟎𝟎 % = 𝟏𝟎𝟗. 𝟒%

It is a very large percent since the daily consumption that is

supposed to contain 35% allowed losses. Meaning that the losses in the


68

quantity of water in this junction are 110.74 𝑚3/ℎ𝑟 at the one hour,

which is very large number.

2. Junction-2



the estimated approximate consumption in this junction could be

determined by utilizing the next formula:


𝑨𝒗𝒆𝒓𝒂𝒈𝒆 𝒅𝒆𝒎𝒂𝒏𝒅 = 𝟒𝟖𝟔 × 𝟔𝟎𝟎𝟎 ×𝟏

𝟐𝟒×𝟏𝟎𝟎𝟎= 𝟏𝟐𝟏. 𝟓 𝒎𝟑/𝒉𝒓

Based on this magnitude, the approximate consumption rate in

this junction is 121.5 𝑚3/ℎ𝑟. Using the ultrasonic flowmeter, the

discharge (realistic consumption) passing through this junction

measured is 178 𝑚3/ℎ𝑟, so this junction has a percentage of losses

equal to:


𝑸𝑬× 𝟏𝟎𝟎 %

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒍𝒐𝒔𝒔𝒆𝒔 % =𝟏𝟕𝟖 − 𝟏𝟐𝟏. 𝟓

𝟏𝟐𝟏. 𝟓× 𝟏𝟎𝟎 % = 𝟒𝟔. 𝟓%

It is a large percent since the daily consumption that is supposed

to contain 35% for allowed waste or losses. Meaning that the losses in

the quantity of water in this junction are 56.5 𝑚3/ℎ𝑟 at one hour, which

is considered high number.

3. Junction-3



the obtained estimated consumption in this junction could be

determined by utilizing the next formula:


69


𝑨𝒗𝒆𝒓𝒂𝒈𝒆 𝒅𝒆𝒎𝒂𝒏𝒅 = 𝟒𝟖𝟔 × 𝟏𝟎𝟎𝟎 ×𝟏

𝟐𝟒×𝟏𝟎𝟎𝟎= 𝟐𝟎. 𝟐𝟓 𝒎𝟑/𝒉𝒓






𝑸𝑬× 𝟏𝟎𝟎 %

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒍𝒐𝒔𝒔𝒆𝒔 % =𝟏𝟐𝟐 − 𝟐𝟎. 𝟐𝟓

𝟐𝟎. 𝟐𝟓× 𝟏𝟎𝟎 % = 𝟓𝟎𝟐. 𝟒𝟔%

It is a very large percent since the daily consumption assumes

on allowable 35% of allowed waste or losses. Meaning that the losses

in the quantity of water in this junction are 101.75 𝑚3/ℎ𝑟 at the one

hour, which is very large number.

4. Junction-4



it can get the estimated approximate consumption in this junction by

using the following equation:


𝑨𝒗𝒆𝒓𝒂𝒈𝒆 𝒅𝒆𝒎𝒂𝒏𝒅 = 𝟒𝟖𝟔 × 𝟔𝟎𝟎𝟎 ×𝟏

𝟐𝟒×𝟏𝟎𝟎𝟎= 𝟏𝟐𝟏. 𝟓 𝒎𝟑/𝒉𝒓






𝑸𝑬× 𝟏𝟎𝟎 %


70

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒍𝒐𝒔𝒔𝒆𝒔 % =𝟏𝟓𝟑 − 𝟏𝟐𝟏. 𝟓

𝟏𝟐𝟏. 𝟓× 𝟏𝟎𝟎 % = 𝟐𝟓. 𝟗%

It is a very large percent since the daily consumption that is

supposed to contain 35% allowed losses. Meaning that the losses in the

quantity of water in this junction are 31.5 𝑚3/ℎ𝑟 at the one hour,

which is acceptable because it is less than 35%.

5. Junction-5



the estimated approximated consumption in this junction is calculated

as follows:


𝑨𝒗𝒆𝒓𝒂𝒈𝒆 𝒅𝒆𝒎𝒂𝒏𝒅 = 𝟒𝟖𝟔 × 𝟓𝟎𝟎𝟎 ×𝟏

𝟐𝟒×𝟏𝟎𝟎𝟎= 𝟏𝟎𝟏. 𝟐𝟓 𝒎𝟑/𝒉𝒓

Based on analysis of such value, the approximate consumption

rate in this junction is 101.25 𝑚3/ℎ𝑟. Using the ultrasonic flowmeter,

the discharge (realistic consumption) passing through this junction

measured is 127 𝑚3/ℎ𝑟, so this junction contains a percentage of

losses equal to:


𝑸𝑬× 𝟏𝟎𝟎 %

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒍𝒐𝒔𝒔𝒆𝒔 % =𝟏𝟐𝟕 − 𝟏𝟎𝟏. 𝟐𝟓

𝟏𝟎𝟏. 𝟐𝟓× 𝟏𝟎𝟎 % = 𝟐𝟓. 𝟒𝟑%

It is considered a high value because it is more than 30% the

daily consumption that is supposed to contain 35% allowed losses.

Meaning that the losses in the quantity of water in this junction are

25.75 𝑚3/ℎ𝑟 at the one hour ,which is large number.


71

Most of the water losses that go at the first five junctions are to

water the orchards and what is related to agricultural lands, and the

lack of monitoring of users.

6. Junction-6



it can get the estimated approximate consumption in this junction by

applying the following equation:



𝟐𝟒 × 𝟏𝟎𝟎𝟎= 𝟏𝟎𝟏. 𝟐𝟓 𝒎𝟑/𝒉𝒓


is 101.25 𝑚3/ℎ𝑟. Using the ultrasonic device, the discharge (realistic

consumption) passing through this junction measured is 83 𝑚3/ℎ𝑟, so

this junction contains a percentage of scarcity equal to:

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒔𝒄𝒂𝒓𝒄𝒊𝒕𝒚 % =𝑸𝑨 − 𝑸𝑬

𝑸𝑬× 𝟏𝟎𝟎 %

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒔𝒄𝒂𝒓𝒄𝒊𝒕𝒚 % =𝟖𝟑 − 𝟏𝟎𝟏. 𝟐𝟓

𝟏𝟎𝟏. 𝟐𝟓× 𝟏𝟎𝟎 % = −𝟏𝟖%

It is a reasonable percentage, as it is assumed that the daily

consumption contains 35% of the permissible losses, and this

percentage indicates that the percentage of loss in this junction is less

than 35%, and thus Meaning that the scarcity in the quantity of water

in this junction is -18 𝑚3/ℎ𝑟 at the one hour.

7. Junction-7




72

it is possible to get the estimated approximate consumption in this

junction using the following equation:


𝑨𝒗𝒆𝒓𝒂𝒈𝒆 𝒅𝒆𝒎𝒂𝒏𝒅 = 𝟒𝟖𝟔 × 𝟑𝟎𝟎𝟎 ×𝟏

𝟐𝟒 × 𝟏𝟎𝟎𝟎= 𝟔𝟎. 𝟕𝟓 𝒎𝟑/𝒉𝒓

This magnitude of demand indicates that, the approximate

consumption rate in this junction is 60.75 𝑚3/ℎ𝑟. Using the ultrasonic

flowmeter, the discharge (realistic consumption) passing through this

junction measured is 36 𝑚3/ℎ𝑟, so this junction suffers from a clear

and very large scarcity, the percentage of which reaches:


𝑸𝑬× 𝟏𝟎𝟎 %

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒔𝒄𝒂𝒓𝒄𝒊𝒕𝒚 % =𝟑𝟔 − 𝟔𝟎. 𝟕𝟓

𝟔𝟎. 𝟕𝟓× 𝟏𝟎𝟎 % = −𝟒𝟎. 𝟕𝟒%

It is a large percentage, as this junction suffers from a scarcity

in the quantities of water supplied compared to the required demand,

and thus meaning that the scarcity in the quantity of water in this

junction are -24.75 𝑚3/ℎ𝑟 at the one hour, which is considered large.

8. Junction-8



the approximated consumption in this junction using the following

equation:



𝟐𝟒 × 𝟏𝟎𝟎𝟎= 𝟏𝟎𝟏. 𝟐𝟓 𝒎𝟑/𝒉𝒓





73

𝑚3/ℎ𝑟. Therefore, this junction suffers from a clear and large scarcity,

the percentage the scarcity of this junction can be calculated as follows:


𝑸𝑬× 𝟏𝟎𝟎 %

𝑷𝒆𝒓𝒄𝒆𝒏𝒕 𝒐𝒇 𝒔𝒄𝒂𝒓𝒄𝒊𝒕𝒚 % =𝟑𝟏 − 𝟏𝟎𝟏. 𝟐𝟓

𝟏𝟎𝟏. 𝟐𝟓× 𝟏𝟎𝟎 % = −𝟔𝟗. 𝟒%

It is a large percentage, as this junction suffers from a scarcity

in the quantities of water supplied compared to the actual required

demand, and this indicated that the scarcity in the quantity of water in

this junction is -70.25 𝑚3/ℎ𝑟 at the one hour, which is considered large

magnitude.

According to the analysis of aforementioned calculations, it was

found that there is a clear and a large loss of water at the beginning of the

main water pipe started from junction-1 to junction-5 and then is

accompanied by a clear and large scarcity at the end of the main water pipe.

The total of the loss and scarcity quantities in the mainline was equal to

326.24 𝑚3/ℎ𝑟 and -113.25 𝑚3/ℎ𝑟, at the one hour respectively.

The quantities of loss are very large compared to the quantities of

scarcity, so if the quantities of losses were controlled, the quantities

supplied to the mainline would be enough to fill the presence of scarcities

without the need to increase the quantities supplied. It is noteworthy that

controlling the quantities of loss is very difficult because of the difficulty

of detecting excesses on the network and the absence of water meters in

houses to determine the percentage of losses.

5.2. Building of the hydraulic model using WaterCAD

Firstly, it was created a hydraulic model for the distribution network

using the WaterCAD simulation program. It was created by drawing a

network layout, then identifying all the hydraulic properties of the network

parts such as junction elevation, demand, pipes length, pipes diameter,


74

pipes type, pump characteristics, and hourly rate consumption pattern as

shown in the following figures.

Figure 5-1 shows the interface of the WaterCAD program, in

addition to the main line diagram showing the locations of the junctions

and the resulting offshoots of the main water pipe. After completing the

network diagram, the data for each pipe in the network is entered, including

diameters, lengths and the type of material it is made of to determine

Hazen-William’s modulus existing already in the program according to the

type of pipe through the interface of the (flex-table) window for pipes, as

shown in Figure 5-2

Figure 5-1: The layout of distribution network in WaterCAD.


75

Figure 5-2: Flex table (pipe table) for identified the characteristics.

Figure 5-3 shows the interface of the (Flex-Table) window it’s in the

program for entering the special information, which includes the elevation

and demand for each junction. In which Figure 5-4 shows the interface for

entering the design characteristics of the pump in terms of discharge, head

pressure, and efficiency where the red line indicates the value of discharge,

while the blue line indicates the value of the pressure head, Program it

automatically draws the pump diagram according to the characteristics

mentioned previously.


76

Figure 5-3: Flex table (junction table) for identified the characteristics.

Figure 5-5 shows the interface of the special window for drawing

the variance diagram of daily consumption within 24 hours (peak hourly

factor) and determining the peak periods according to the entered values,

where the horizontal axis is the time and the vertical axis is the factor that

multiplies the rate of consumption per hour. It shows that the peak is

concentrated during the morning period at 8 am and at 7 pm.


77


Figure 5-5: Identify daily consumption within 24 hours (peak hourly

factor).


78

Secondly, it was applied a hydraulic model exists to analyze the

fieldwork recorded data compared with simulation results obtained.

Through the fieldwork recording data and the results of the analysis, it was

found that the flowrate quantities of water pumped from the pumping

station are not proportional to the diameter of the main water pipe, and do

not meet the minimum flow velocity in the pipes which is minimum of

0.6m/s as shown in figure 5-2. In addition to the difficulty of reaching water

the end of the line to feed the required areas. Moreover, water cannot reach

the ends in adequate. As the diameter is large and the quantities of water

pumped into it are few, in addition to the losing operations that were at the

beginning, where the design capacity of the line was 1200 𝑚3/ℎ.

5.3. Proposal Scenarios for the hydraulic Model in WaterCAD

The main water pipe will be simulated using WaterCAD for more

than one scenario. It has been proposed to analyze and identify the problem

of scarcity according to unsteady flow, and control it to achieve the best

solution, as follows:

5.3.1. First scenario

In this scenario, the main water pipe is taken as it exists without any

modification of the characteristics of the line in terms of pipe diameters,

elevations, and quantities of water pumped into the mainline, taking into

consideration that the amount of demand for each junction is equal to the

approximate consumption rate as shown in Table 5-1.


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Table 5-1: Elevation and Demand for branch junctions.

Junction Label Elevation

(m)

Demand

(m³/h)

Real

demand(m3/hr.)

Percentage

of losses or

scarcity

Junction 1 J-11 25.00 101.25 212 109.4

Junction 2 J-22 28.50 121.50 178 46.5

Junction 3 J-33 27.50 20.25 122 504.46

Junction 4 J-44 24.27 121.5 153 25.9

Junction 5 J-55 25.67 101.25 127 25.43

Junction 6 J-66 26.94 101.25 83 -18

Junction 7 J-77 24.37 60.75 36 -40.74

Junction 8 J-88 25.00 101.25 31 -69.4

Figure 5-6: Calculation summary for simulation at first scenario.

When simulation of the hydraulic model is based on the demand rate

for each junction that is the same as the approximate consumption rate, it


80

was found that there is a scarcity in the quantities of water supplied during

the morning period for two hours from 8 am to 10 am, and during the

evening period for a four hours from 5 pm to 9 pm, as shown in Figure 5-

6. This scenario simulates the current main water pipe if the losing

quantities are controlled in the first five junctions of the mainline to fill the

scarcity in the last three junctions. As mentioned previously, it is difficult

to control the quantities of loss for the same reasons that were mentioned

previously. This scenario is considered ineffective in solving the problem

of scarcity that exists.

Figure 5-7: Head Pressure at junction-p at pump station during 24 hr.

After the scarcity periods are mentioned in the supplied quantities

and their duration, the head pressures at each junction must be checked

during the 24-hour operating period, because one of the important

requirements in networks is the pressure at each junction. By checking the


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profile energy chart during 24 operating hours, it was found that there was

a decrease in pressure during the morning period for two hours from 8 am

to 10 am, besides a decrease in pressure during the evening period for 6

hours from 3 pm to 9 pm, as shown in the figure 5-7 which shows the

energy diagram at the pumping station and for all the junctions from the

main water pipe and based on the demand inputs that were entered into the

program. This indicates a decrease in quantities for 6 hours/day and a

decrease in pressure for 8 hours/day, it is concluding that the drop of

pressure in the program is due to insufficient quantities of provided from

the source. This indicates that this scenario, even if the amount of loss is

controlled, remains ineffective.

5.3.2. Second scenario

In this scenario, the mainline is taken as it exists without any

modification of the characteristics of the line in terms of pipe diameters,

elevations, and quantities of water pumped into the mainline, but adds a

booster station after junction 5 as shown in and figure 5-8, taking into

consideration that the amount of demand for each junction is equal to the

approximate consumption rate as shown in Table 5-1.


82

Figure 5-8: layout of main water pipe with booster station.

A simulation has been made for the proposed scenario, which is to

add an intermediate pumping station to the same quantity produced at

present, which is, of course, as mentioned, less than the design capacity

under which the pipeline is established. It was found that there was a

problem with operating the mainline with an intermediate lifting station,

which caused an increase in the number of shortage hours during one day

because the quantity received from the pumping station was small and

insufficient, which caused an increase in the hours of scarcity. The scarcity

in the network is in the quantities supplied from Al-Sajelah and Al-Fayada

stations. The work of the booster station is based only on raising the

vertical pressure of each junction after the pump.


83

Figure 5-9: The pump definition for Booster Station.

Figure 5-10 shows a summary of the simulation calculations for the

proposed scenario, and the hours marked in yellow mean that there is a

problem with the quantities supplied or the pressures during this period.

Figure 5-11 shows the amount of head pressure with time during 24 hours

at some points, such as a point inside the Al-Sijlah and Al-Feyadh station

symbolized by J-P, a point at the fourth junction before the proposed

booster station symbolized by J-4, and a point at the sixth junction after the

proposed booster station symbolized by J-6. This figure shows that from 7

am to 9 pm, the problems begin with pressure and are negative because of

the intermediate pumping station begins by withdrawing additional

quantities of water to treat the junctions after pumping station, and this is

at the expense of the previous ones and leads to a decrease in its quantities,

especially if it is not treated from the source, and this need cannot be filled

with the current supplied quantities, which causes a decrease in pressure

and a scarcity of quantities. Into the quantities supplied must be increased

to solve this problem.


84

Figure 5-10: Calculation summary for simulation at second scenario.

Figure 5-11: Head Pressure at some junctions during 24 hr.


85

5.3.3. Third scenario

In this scenario, the main water pipe is taken as it is without any

modification to the characteristics of the line in terms of pipe diameters

and heights, and the production capacity of Al-Sijlah Al-Feyadh station is

added to increase the quantity of supplied water pumped into the main

water pipe to 1800 m3/hr. Taking into consideration that the quantity of

demand for each junction is equal to the approximate rate of consumption

based on the assumption that the field-measured discharge using the

Ultrasonic flowmeter is the Peak hour demand, as shown in Table 5-1.

Figure 5-12: The pump definition for 3rd scenario.

From the summary of the simulation calculations for this scenario

shown in Figure 5-13, it is shown that the supplied quantities are sufficient

to meet the demand needs at each junction, and that the highest discharge

of the required consumption is 1312 m3/hr. at a peak time of 19:00. The

sufficient quantity of water supplied to the mainline does not mean that the

line does not face problems in its operation, so it is necessary to check the

pressures at each junction. Figure 5-15 shows the hydraulic line of the

mainline in the peak period at 19:00, that the pressures for all junctions are


86

good and that the minimum pressure value at the junction j-6 is equal to

1.9 meters of water height. The figure 5-14 shows that the lowest pressure

is equal to 3 meters of water height at 18:00, and the figure 5-16 shows that

the lowest pressure is equal to 7.5 meters of water height at 20:00.

Figure 5-13: Calculation summary for simulation at third scenario.


87

Figure 5-14: Hydraulic Grade line profile for 3rd scenario at 18:00.

Figure 5-15: Hydraulic Grade line profile for 3rd scenario at peak time

19:00.


88

Figure 5-16: Hydraulic Grade line profile for 3rd scenario at 20:00.

5.3.4. Fourth scenario

In the previous scenarios, it was assumed that the field-measured

discharges by the ultrasonic flowmeter were represented the peak hourly

consumption discharges, and the critical case of the main water line must

be taken into consideration. Therefore, in this scenario the demand will be

adjusted for the first five junctions equal to field-measured discharge it’s

represent reality consumption, And the last three junctions to equal to the

approximate consumption rate as shown in Table 5-2, and this is

representing the worst case for the main water pipe.

Table 5-2: Elevation and Demand for branch junctions at 4th scenario.

Junction Label Elevation (m) Demand (m³/h)

Junction 1 J-11 25.00 212

Junction 2 J-22 28.50 178

Junction 3 J-33 27.50 122

Junction 4 J-44 24.27 153

Junction 5 J-55 25.67 127

Junction 6 J-66 26.94 101.25

Junction 7 J-77 24.37 60.75

Junction 8 J-88 25.00 101.25


89

Figure 5-17: Calculation summary for simulation at fourth scenario.




The same figure 5-17 shows that there is a problem with the quantities

supplied to the main water pipe at the peak time at 19:00, and the shortage

in the supplied quantities is approximately 99 m3/hr. This indicates a

shortage for one hour through the analysis based on the supplied quantities

only. In addition to the above, it is necessary to know the amount of

pressure during the peak period to ensure the actual performance of the


90

main water pipe during operation. Through the hydraulic line of the peak

period shown from Figure 5-18 to Figure 5-20, it is found that 2 hours are

scarce from 6 p.m. to 8 p.m.

Figure 5-18: Hydraulic Grade line profile for 4th scenario at 18:00.



91


After the analysis, it was proven that there was a shortage for 2 hours

during the day, which is 2 hours from 6 p.m. to 8 p.m. This analysis is

based on that, the first five contract expenses equal the expenses measured

in the ceremony and the last three junctions. The summary of this scenario

is not good, and the increase in the rate of consumption is not sufficient to

meet the needs of the main line.

5.3.5. Fifth scenario

In the intention of the Holy Karbala Water Directorate to improve

the operating efficiency necessary for the main-line and add a design

capacity of not less than 1200 m3/hr. with all its equipment and accessories,

and for the improvement process to be according to scientific accounts and

engineering programs, this scenario was proposed. Also, since it is difficult

to control the amounts of loss in the first five of the junctions because of

the main water pipe extends over long distances, the lack of water meters

in houses of subscription, and the difficulty of monitoring the main water


92

pipe 24 hours a day to prevent illegal connections. Therefore, in this

scenario, it will be considered that the quantity of demand in the first five

junctions is equal to the actual consumption rate of the loss that was

measured on-site using the Ultrasonic flowmeter, and the last three

junctions are equal to the approximate consumption rate as shown in table

5-2. This scenario represents the worst case for the main water pipe in

terms of consumption, to solve the problem of shortages on the mainline,

in addition to increasing the production capacity of Al-Sejlah and Al-

Feyadh station to 2,400 m3/hr. with the excess product is pumped into the

center of the holy province of Karbala to benefit from it.

Figure 5-21: The pump definition for the 5th scenario.

From the summary of the simulation calculations for this scenario

shown in figure 5-22, it is shown that the supplied quantities are sufficient

to meet the demand needs at each junction and that the highest discharge

of the required consumption is 1899 m3/hr. at a peak time of 19:00. The

sufficient quantity of water supplied to the main water pipe does not mean

that the line does not face problems in its operation, so it is necessary to

check the pressures at each junction. Figure 5-23 shows the hydraulic line

of the main water pipe in the peak period at 19:00, that the pressures for all


93

junctions are good and that the minimum pressure value at the junction j-6

is equal to 6 meters of water height. Thus, the parameters of the main water

pipe were evaluated, which are from the requirements to improve its

operational efficiency, namely discharge, pressure and velocity, and the

results were good because of the increase in the production capacity of the

pumping station, which in turn affected the improvement of the work of

the main water pipe.

Figure 5-22: Calculation summary for simulation at fifth scenario.


94

Figure 5-23: Hydraulic Grade line profile for 5th scenario at peak time.

5.3.6. Sixth Scenario

In this scenario, a temporary situation is imposed, which is the

rotation of stopping the water supply during a certain period between the

junctions, for example, for the first and second junctions, which have the

highest consumption, but it is not possible, especially in the summer,

because the nature of the area is rural and needs water continuously as

mentioned previously, but under the current conditions Until the expansion

of the design capacity, as mentioned in the fifth scenario, And in which the

reading of the ultrasonic flowmeter in the connections represents the actual

consumption of users, it will be taken for the junctions from the third to the

fifth, And with respect to sixth to eighth junction the approximate

consumption will be based on the imposed share of the water circuits and

according to Table 5-2.


95

Figure 5-24: Calculation Summary for Simulation at sixth Scenario




there is a problem with the quantities supplied to the main water pipe at the

peak time at 17:00,18:00,19:00 and the shortage in the supplied quantities

is approximately 122,222 and 89 m3/hr. This indicates a shortage for three

hours through the analysis based on the supplied quantities only. In

addition to the above, it is necessary to know the amount of pressure during

the peak period to ensure the actual performance of the main water pipe

during operation. Through the hydraulic line of the peak period shown

from Figure 5-25 to Figure 5-27, it is found that the pressure in the fourth


96

and seventh junction at 17:00 is low, and at 18:00 it will be significantly

lower in the junctions from five to eight, and at 19:00 it is also low in

fourth, fifth, and seventh junctions, and even the rest, there was a clear

decrease in pressure, stay the fifth scenario remains the best solution to

improve the efficiency of the main water pipe.


time(17:00).


97


time(18:00).


time(19:00).

5.3.7. The summary of scenarios

Finally, after completing the simulation for all the proposed

scenarios, table 5-3 summarizes the advantages and disadvantages of each

scenario.


98

Table 5-3: summarizes the advantages and disadvantages of scenarios.

Scenario

no. Advantages Disadvantages

1 Do not need an increase in

supply quantities.

Assume ideal customers.

Having a scarcity of 6 hours at peak

times.

2 Increased head pressure in

the last 3 junctions.

Decrease head pressures at the

junctions before the pump.

The continuation of the scarcity

from 7 am to 9 pm.

3 Good performance.

Do not find a scarcity.

Assume ideal customers.

Need an increase in supply

quantities of about 600 m3/hr.

4 Considering the critical

situation of demand for

junctions.

Having a scarcity of 2 hours at peak

times.


quantities of about 600 m3/hr.

Cannot consider any developments

on the main water pipe.

5

Good performance.

Considering the critical

situation of demand for

junctions.

Considering the development

in mainline.


quantities of about 1200 m3/hr. to

improve the efficiency of the main

water pipe.

6 Do not need an increase in

supply quantities.

The difficulty of applying it due to

the nature of the agriculture area

and its continuously need water.

Chapter Six

Conclusion and

Recommendation

Chapter Six …………..………..….. Conclusion and Recommendation

100

Chapter Six: Conclusion and Recommendation

6.1. Conclusions

According to the results of manual analysis on the basis of steady

flow and simulation for the six scenarios for a period of twenty-four hours

on the basis unsteady flow according to the peak hour of the distribution

system of the main water pipe, which operates in the system of branching

tree, the following conclusions were obtained:

1. It was found that the field measurements of the amount of flow coming

out of the pumping station indicated that the amount of discharge is less

than the amount of originally designed discharge of the main water pipe.

The pumped discharge was not exceeded 950 𝑚3/ℎ𝑟 in all seasons and

situations. While the design capacity is 1200 𝑚3/ℎ𝑟 and this is because

of the low performance of the pumps.

2. In the first part of analysis, it was found that there was a clear and large

loss of water at the beginning of the main water pipe, starting from

junction-1 to junction-5, and then there was a clear and large scarcity at

the end of the main water pipe. The total of the loss and scarcity

quantities in the was equal to 326.24 𝑚3/ℎ𝑟 and -113.25 𝑚3/ℎ𝑟,

respectively.

3. The quantities of losses are very large compared to the quantities of

scarcity, so if the quantities of loss were controlled, the quantities

supplied to the main water pipe would be enough to fill the present

scarcities without the need to increase the quantities supplied.

4. In the second part of analysis, based on the simulation of results, it was

found that the water needed to overcome water scarcity was 2400m3/hr.

There is a loss of water in high quantities, especially at the beginning

of the main water pipe, and more specifically in the first five junctions,


101

and this loss is because of the use of drinking water for irrigation of

gardens and orchards and a large number of illegal connections.

5. Controlling loss rates is almost impossible to achieved because the main

water pipe extends for long distances of agricultural areas that are

difficult to monitor and identify abuses, and because there are no water

meters installed in every house.

6. The presence of a high scarcity in quantities and pressures of the last

three junctions at the end of the main water pipe is because of the high

rates of loss at the beginning of the main water pipe and the insufficient

quantities supplied to the line and the inefficiency of the pumps used.

7. The pressure inside the pumping station did not exceed 1 bar in all

cases, and this is because of the low efficiency of the pumps operating

on the main water pipe. In addition, damage to some parts of the pump

and the effect on the efficiency as well as the field reading pressure at

the junctions are weak, as indicated by the field readings.

8. It was noticed the pumping station level is higher than all the pipe levels

and the junctions branching from it. This is useful when increasing the

capacity of the main water pipe reduces the efforts exerted by the pumps

and raises the value of pressures.

9. It was found that there is no diesel generator to operate pumps when

the national electricity is shut down, Although the project is fed by

emergency lines.

10. The results of the first four scenarios and sixth from some main water

pipe junctions receiving water at low pressure during peak hour

consumption, and in some cases, there is a risk of receiving no water

because the main water pipe pressure is below the acceptable minimum

requirement.

11. The fifth scenario provides sufficient water with proper quantity

pressure of all junctions during peak hour consumption, also there are


102

quantities of excess water, especially outside peak consumption times.

Excess water can be stored.

6.2. Recommendations

To improve the status of the main water pipe and reduce its deficit

rates to the lowest possible period and percentage, the following

recommendations were developed based on the results of the previous

research and analysis:

6.2.1. Recommendations for operating staff of the main water pipe

1. Controlling losses and replacing pumps in the project, whether they are

working continuously or in standby mode, because they are old and

worn out and do not meet the required flow, as the mainline was

designed based on giving 1200 m3/hour in each case, as mentioned

previously.

2. The change in setting valves in the branch pipes of junctions to provide

the needed amounts of water to the consumers affects the values of

pressure in the mainline, and the closing valves increase the pressure in

the main water pipe.

3. Manage and reduce the water sharing for inhabitants of some junctions,

as shown in the previous simulation, by reducing the consumption rate

to an estimation rate or putting a valve to properly control the amount

of water withdrawal and using a pressure valve to raise pressure more

than the calculated value at junctions that need it. This is especially

important in the summer, with the peak of high consumption of water

withdrawals.

4. It is possible to use the pressure reducer valve and adjust it acceptably

and place it in the junctions close to the pump station, as they are rural

areas and do not need a high increase in pressure. This reduction will


103

contribute to raising the pressure in the areas that are far from the pump

station to achieve the required flow.

5. Water level monitoring entering the storage tank, affects the water level

in the steel pressure tank through which the water is drawn by pumps

to be pumped into the main water pipe. In addition to the difference in

the efficiency of the pumps being used.

6. The necessity to provide a generator for electric current in anticipation

of emergency situation and power cuts to the pumping station for long

periods, especially in the summer season, leads to the complete

emptying of the main water pipe and the difficulty of filling it again,

since the distance is long and consumption is high in these weather

conditions.

7. Working on the maintenance and cleaning of the intake structure at the

bottom of the river, as they are directly responsible for the quantities

required, and to avoid direct extinguishing of the main water pipe and

its discharge, especially in peak seasons.


104

6.2.2. Recommendations for future studies

1. Through the analysis scenarios and considering the current and near-

future needs and the importance of the main water pipe to the city of

Karbala, it requires the addition of design capacity to improve the

efficiency of the conveyancer line’s operation, as shown by the results

of the evaluation for the first fiver scenarios with the addition of all the

required accessories, steel tanks, filters, and all that the work requires.

2. During the sixth scenario which is the best, there are quantities of water

above of the needs of the current 8 junctions on the main water pipe.

Also, it can connect to new junctions to feed some nearby areas. In

addition, it is possible to establish a project to collect and pump the

surplus quantities into the center of the holy city of Karbala to fill in

part of the scarcity in the city center.

105

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106

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1315/437/1/012043

الخالصة

أ

الخالصة

ئيسية في ستسلط الدراسة الحالية الضوء على تقييم كفاءة أحد أنابيب المياه الر

دًا فهي تعتبر من أهم المحافظات المقدسة في العراق وتشهد أعدا كربالء،محافظة

نابيب أأجريت هذه الدراسة لتقييم كفاءة ذلك،كبيرة من الحجاج كل عام. عالوة على

لتقاطعات االمياه الرئيسية الحالية لتحسين كفاءتها. تم أخذ قراءة ميدانية في مواقع

التي كانت و المختلفة،سي في المواسم السنوية أنبوب الماء الرئي المتفرعة منو المختلفة

ي. في الصيف والخريف والشتاء وساعات مختلفة باستخدام مقياس التدفق فوق الصوت

بيانات التي يتم تحليل أنبوب الماء الرئيسي في جزأين. يتعامل الجزء األول مع تحليل ال

رنامج بوتحليله في ويتم محاكاة الجزء الثاني الثابت،تم جمعها مع افتراض التدفق

WaterCAD وهو افتراض التدفق غير المستقر. ساعة،مع تباين االستهالك لكل

بيرة كوجد أن هناك خسائر اليدوي،بناًء على نتائج الجزء األول من التحليل

5لتقاطع اإلى 1وواضحة للمياه في بداية أنبوب المياه الرئيسي الذي بدأ من التقاطع

يات اضحة وكبيرة في نهاية أنبوب المياه الرئيسي. مجموع الكميصاحبها ندرة و ثم

- / ساعة و 3م 326.24المفقودة والندرة في أنبوب المياه الرئيسي كان يساوي

الندرة،ات كبيرة جدًا مقارنة بكمي مفقودةكميات الال/ ساعة على التوالي. 3م 113.25

ياه الرئيسي فإن الكميات الموردة ألنبوب الم ،ةدمفقوالكميات اللذلك إذا تم التحكم في

لتدفق استكون كافية لسد الندرة دون الحاجة إلى زيادة الكميات الموردة بناًء على

مر المستمر دون أي توسعات مستقبلية للوصالت. يشار إلى أن ضبط كميات الفاقد أ

المياه صعب للغاية بسبب صعوبة كشف التجاوزات على الشبكة وعدم وجود عدادات

في المنازل لتحديد نسبة الفاقد.

WaterCADتمت المحاكاة باستخدام برنامج التحليل،في الجزء الثاني من

والتحكم فيها المستقر،لستة سيناريوهات لتحليل وتحديد مشكلة الندرة وفق التدفق غير

للوصول إلى الحل األفضل. بناًء على محاكاة النتائج وجد أن كمية المياه الالزمة للتغلب

/ ساعة. وال يمكن تجاهل عدم وجود خسائر في 3م 2400على ندرة المياه كانت

الخالصة

ب

وبشكل أكثر تحديدًا في الرئيسي،خاصة في بداية أنبوب المياه كبيرة،المياه بكميات

ـ التقاطعات متر مكعب 326.24الخمسة األولى التي كانت تفقد كميات من المياه تقدر ب

وهذه الخسائر ناتجة عن استخدام مياه الشرب اليدوية،ساعة. بناء على الحسابات /

لري الحدائق والبساتين وعدد كبير من التوصيالت غير القانونية. وهذا باإلضافة إلى

التقاطعات حسب احتياجات اهم في زيادة عدد تسيسي سالسعة الجديدة ألنبوب المياه الرئ

كربالء. اءمديرية م

وزارة التعليم العالي والبحث العلمي

جامعة كربالء

كلية الهندسة

قسم الهندسة المدنية

تأثريات بعض العوامل على كفاءة تشغيل وحتليل تقييمباستخدام برنامج كربالء دينةمانبوب املياه الرئيسي يف

WaterCAD

الى مقدمة رسالة

كربالء جامعة /الهندسة كلية في المدنية الهندسة قسم

الهندسة علوم في الماجستير شهادة نيل متطلبات من كجزء

التحتية البنى هندسة – المدنية

قبل من

حسين علي حسين عبد علي

(2005هندسة مدنية )بكالوريوس

اشراف

أ.د جبار حمود البيضاني

موسى حبيب الشمري أ.د

ـه 1443 م 2021

Republic of Iraq

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Transcript of Republic of Iraq