improvement of dar-es-salaam water system management through isolated localised distribution...

8/14/2019 IMPROVEMENT OF DAR-ES-SALAAM WATER SYSTEM MANAGEMENT THROUGH ISOLATED LOCALISED DISTRIBUTION NETWORKS

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IMPROVEMENT OF DAR-ES-SALAAM WATER SYSTEM MANAGEMENTTHROUGH ISOLATED LOCALISED DISTRIBUTION NETWORKS


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DISCLAIMER

The information contained in this document is the outcome of a six monthcourse on Integrated Water Resources Management which was tailored toenable participants from southern Sub Sahara countries in Africa toacquire knowledge necessary to foster the sustainable development ofwater resources in a holistic manner. The training was fully funded by the

Italian Government through its Ministry Foreign Affairs and conducted byWater Resources, Research and Documentation Centre at Villa deColombella, University for Foreigners, Perugia.

The analysis output documented here is by far the outcome of varioussubjects undertaken during the programme period and basic hydraulicprinciples. The approach considered in this study and all the commentsshould be regarded as my personal suggestions based on technical facts

as explained in the report. In order to apply what has been proposed toimprove the management of Dar-es-salaam water supply system, it isimportant to update and verify all the data used and scenarios attemptedwithout turning aside the aspect of creating the localised distributionzones.


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ACKNOWLEDGEMENT

Many people have contributed a lot to enable me attend the course sincewhen I was in Tanzania and during the course period. It is unfortunate that itwould not be possible to mention all of them and the roles they played. Tomention few of them I would like to start by expressing my sincere gratitudeto Italian Governmentwhich has financial supported me fully to pursue the

course.

I wish also to thank the WARREDOC management team; the directorProfessorBruno Brunone for his efforts by making the course successivelyapart from several constraints which were associated with refurbishment ofthe centre with appropriate working tools and participants basic needs;

Professor Kodwo Andah the Centres Scientific Coordinator for his physicaland moral support he gave me in course of data acquisition and treatment;Professor Roberto Maria Rossi for organising special courses andsignificant technical study tours and workshops.

Last but not least, I would like also to express my deep appreciation to myManaging Director Mr. Edgar H. Berege who for being dedicated to his dutiesenabled me to acquire all necessary information and documents in order to

attend the course


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TABLE OF CONTENT

DISCLAIMER .................................................................................................................................iACKNOWLEDGEMENT ..............................................................................................................iiTABLE OF CONTENT .................................................................................................................iii

LIST OF FIGURES .......................................................................................................................iv

LIST OF TABLES .........................................................................................................................viABSTRACT ................................................................................................................................ viii

CHAPTER ONE .............................................................................................................................1

1 INTRODUCTION ........................................................................................................................1

1.1 STUDY AREA ...................................................................................................................... 11.1.1 Location ..........................................................................................................................1

1.1.2 Population ....................................................................................................................... 2

CHAPTER TWO ............................................................................................................................ 42 CURRENT STATE OF WATER SERVICES IN DAR ES SALAAM REGION .......................4

2.1 DEFINITION OF THE PROBLEM ......................................................................................5

2.2 EXISTING WATER SOURCES STATUS ...........................................................................72.2.1 Lower Ruvu Water Treatment Plant ............................................................................... 8

2.2.2 Upper Ruvu Water Treatment Plant ............................................................................... 82.2.3 Mtoni Water Treatment Plant ......................................................................................... 9

2.3 UNACCOUNTED WATER ...............................................................................................11CHAPTER THREE ...................................................................................................................... 13

3 METHODOLOGICAL TO STREAMLINE WATER SUPPLY TO DSM AND OUTLYING

AREAS .......................................................................................................................................... 133.1 DATA ACQUISITION AND TREATMENT .....................................................................14

3.1.1 Data Acquisition ........................................................................................................... 15


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LIST OF FIGURES

Figure 1: Location map of Dar-es-salaam region the project area...................................................1Figure 2: Dar-es-salaam region urban population growth trend map..............................................2

Figure 3: Map of the existing water transmission mains from Upper and Lower Ruvu treatment

plants to Kimara and University reservoirs respectively...............................................................10Figure 4: Illustration of interpolation process from segment maps...............................................17

Figure 5:: Proposed water distribution zones map.........................................................................19

Figure 6: Map of the first simulated water transmission mains for supplying water to localized

water distribution zone created by using EPANET software........................................................30Figure 7: Map of the final simulated water transmission mains for supplying water to localized

water distribution zone created by using EPANET software........................................................37

Figure 8: LONGITUDINAL SECTION OF PROPOSED ADDITIONAL TRANSMISSIONMAIN FROM LOWER RUVU TREATMENT PLANT TO MANYEMA.............................XVII

Figure 9: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM LUGERA

JUNCTION NODE TO MTAKUJA DISTRIBUTION ZONE...............................................XVIIIFigure 10: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM MSANGANI

JUNCTION NODE TO KIDEGE DISTRIBUTION ZONE......................................................XIX

Figure 11: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM MSANGANI

JUNCTION NODE TO Up12 JUNCTION NODE.....................................................................XXFigure 12: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM KIDIMU

JUNCTION NODE TO PANGANI DISTRIBUTION ZONE...................................................XXI

Figure 13: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM KIVUKONI

JUNCTION NODE TO MAGOE DISTRIBUTION ZONE XXII


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Figure 22: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM Lw3 JUNCTION

NODE TO CHAMAGWE DISTRIBUTION ZONE..........................................................XXXVII

Figure 23: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM Lw6 JUNCTIONNODE TO NYAKAHAMBA DISTRIBUTION ZONE....................................................XXXVIII

Figure 24: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM Lw9 JUNCTION

NODE TO MBOPO DISTRIBUTION ZONE.....................................................................XXXIX


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LIST OF TABLES

Table 1: Rationalization of water produced by Upper and Lower Ruvu treatment plant to reflect

what would be water demand in localized distribution zones.......................................................22Table 2:Pipe Head loss Formulas for Full Flow (for head loss in feet and flow rate in cfs).........26

Table 3:Rougness Coefficient for New Pipe.................................................................................26

Table 4: Results at the nodes after the first simulation of the model for supplying water to

localized water distribution zone created by using EPANET software.........................................31Table 5: Results at the links after the first simulation of the model for supplying water to created

localized water distribution zone created by using EPANET software.........................................33Table 6:Results at the nodes after the first simulation of the model for supplying water to

localized water distribution zone created by using EPANET software.........................................38

Table 7: Results at the links after the second simulation of the model for supplying water to

created localized water distribution zone created by using EPANET software............................40Table 8: Surface Areas of Each Zone and Designed Water Discharge Rates...............................43

Table 9: DESCRIPTIONS OF PROPOSED ADDITIONAL TRANSMISSION MAIN FROM

LOWER RUVU TREATMENT PLANT TO MANYEMA......................................................XVITable 10: DESCRIPTIONS OF PROPOSED BRANCH FROM LUGERA JUNCTION NODE

TO MTAKUJA DISTRIBUTION ZONE................................................................................XVIII

Table 11: DESCRIPTIONS OF PROPOSED BRANCH FROM MSANGANI JUNCTIONNODE TO KIDEGE DISTRIBUTION ZONE.........................................................................XIX

Table 12: DESCRIPTIONS OF PROPOSED BRANCH FROM MSANGANI JUNCTION

NODE TO U 12 JUNCTION NODE XX


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Table 23: DESCRIPTIONS OF PROPOSED BRANCH FROM Lw3 JUNCTION NODE TO

CHAMAGWE DISTRIBUTION ZONE.............................................................................XXXVII

Table 24: DESCRIPTIONS OF PROPOSED BRANCH FROM Lw6 JUNCTION NODE TONYAKAHAMBA DISTRIBUTION ZONE......................................................................XXXVIII

Table 25: DESCRIPTIONS OF PROPOSED BRANCH FROM Lw9 JUNCTION NODE TO

MBOPO DISTRIBUTION ZONE........................................................................................XXXIX


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ABSTRACT

The scale of the urban population growth in DSM City is at alarming state ascompared to the availability of utility services. The gap between access tosafe and clean water for domestic use experienced by DSM populations is onincrease due to the irregular expansion of the city while the existing watersupply infrastructures neither cover nor satisfy the need of already

developed areas.

So as to be able to reorganise the functions of existing water systems toserve the current and future demand this analysis dedicated on preparinglocalized water distribution zones for areas which are fully or partially servedby the existing system. The proposed system could control water leakage toan acceptable practicable level, streamline the application of effective water

quality control practice, ensure relatively unbiased distribution of waterservices between various users at reasonable discharge rates and pressurehead, enable the identification and setting of appropriate water service tariff,moderate the revenue collection exercise.


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CHAPTER ONE

1 INTRODUCTION

1.1 STUDY AREA

1.1.1Location

Dar es Salaam is the capital city of Tanzania with a total coverage of about

1350 km square. The city is situated on the eastern cost of Africa at alatitude of 6 45 South and a longitude of 39 18 East. From the coast areainland lays the coastal plains, bordering the Pugu hills, which rise up to analtitude of 200 meters. The temperature in the city is usually high, ranging

between 17C and 32C with humidity between 50% and 90%. The mainwinds are monsoons blowing to and from Indian Ocean. The heavy rainnormally falls on March and May, but continued showers throughout the yearare common. The total rainfall per year is between 1,000 and 1,400 mm.


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Dar es Salaam, once called "Mzizima" (which means the healthy town), is anold city dating as early as 1857. Though the history of Mzizima went beyond

1,000 years when the Barawa people (who then mingled with Zaramo to beamong them) started to settle and cultivate the area around Mbwa Maji,Magogoni (now Kivukoni) Mjimwema, Gezaulole and Kibonde Maji Mbagala.

The city has faced major changes dating from the influences of theSultanates to the Germans and the British. The name Dar es Salaam meansheaven of peace, a name chosen by Sultan Seyyid Majid of Zanzibar. Thecity started as a fishing village in the mid 19th Century before being turned

to a port and a trading centre. The major changes experienced in the cityare industrialisation, civilisation, expansion of the city, increase inpopulation etc; all these changes associated with increase in demand ofwater services as core for all development.

1.1.2Population

Dar-es-salaam is the largest city in Tanzania, and is politically, economicallyand culturally the national centre with a population of approximately2,800,000 as per preliminary results of 2002 census.


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In consideration to the project coverage area it is obvious that the populationserved by DSM water system is big than the mentioned one; this is due to

the fact that the area served by existing DSM water system extending to twodistrict in the Coast region. Usually, assessment on water demand fordomestic uses based on population and other uses such as recreation,emergency and industrial uses. It is unfortunate that the increase inpopulation and development over the project area is out of control; so if thissituation prevails any measures of providing any basic utility services topublic would be out dated before or after a very short time after itscompletion. Thus the trend of increase in population over the project area

needs to be careful analysed with respect to an anticipated project life span.

Traditionally, in DSM water supply services have been delivered by means ofa centralized system. The government has been implementing water supplyprogrammes with an intension to support the citizens with adequate, cleanand safe drinking water as a free or subsidised commodity. Its positive healthand environment externalities seemed to justify the view of bothgovernment and communities that free or subsidised water is afundamental right of the people. However, inadequate resourcesconstrained the Governments ability to fulfil this goal; as a result thatcoverage and quality of services have suffered so apart from many years ofattention being paid by the Government to the water supply problems, therestill remains a lot to be done. Water supply services have not been a successin DSM both in urban and rural areas. Currently, the government hasrecognized that the burden to provide clean and safe water is heavy, and is

ki t t i l i t i t d bli t


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CHAPTER TWO

2 CURRENT STATE OF WATER SERVICES IN DAR ES SALAAM REGION

The growing of population, as well as unplanned expansion of the city beingexperienced in DSM region over recent decades has led to mountingpressures on the need of water for domestic and industrial activities. Thereare several problems associated with lack of effective water supply system inDSM region and the neighbouring districts. Among various problems, thefollowing are worth mentioning: insufficient water coverage, ineffectiveoperation of several parts of the water system, unequal quantitative andspatial distribution of the available water, water losses, inappropriate pricingof water services resulting in periodic outbreak of water borne diseases.

DSM is divided into 3 administrative districts which are Kinondoni, Ilala andTemeke. Each of these districts is further sub-divided into wards. Watersupply in DSM is largely handled by the National Urban Water Authority(DAWASA), with the DSM Rural Water Supply Department (RWSD) handlingoutlying rural areas within the greater DSM region. DAWASA has classifiedDSM into 5 sub-branches. The Kinondoni administrative district is divided intoKawe, Kinondoni and Magomeni sub-branches, while Ilala and Temeke sub-

b h f t th i k d i i t ti di t i t


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according to existing and future demands. This fact can be vividly depictedfrom the following: -

Capacities of three treatment plants, in relation to present and futuredemand of water when they were constructed or upgraded.

Capacities, locations and altitudes of University and Kimara waterreservoirs in relation to areas where the water from the reservoir can reachunder the influence of gravity force.

Areas with existing distribution networks which can serve the purpose to anacceptable practical level and their age.

Deterioration in amount of water received in University and Kimara waterreservoirs due to excessive extraction of water from the primary mainbetween the treatment plants and reservoirs.

2.1 DEFINITION OF THE PROBLEM

Dar Es Salaam water supply system is mainly fed by two water treatmentplants located 20km apart along Ruvu River in Coast region and areapproximately 65 km from DSM city centre. These plants were designed andconstructed to render services to the old urban centres of DSM city. At

t l b t h b d l i l th t


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distribution of the water volumes and the hydraulic characteristics of thenetworks.


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2.2 EXISTING WATER SOURCES STATUS

The chief source of water in DSM region is the Ruvu River flowing northwardsof the west of the city through the Coast Region towards the Indian Ocean.The supply is supplemented to small degree by tapping water from KizingaRiver at Mtoni and several wells drilled within the region.

Along river Ruvu water is drawn at two different intakes namely the UpperRuvu and the Lower Ruvu. These intakes are located about 20 km apart.The Upper Ruvu water treatment plant is approximately 65km from the city

centre along Morogoro Road, constructed in 1969 and is producing a totalamount of 82,000m3/day of treated water. The second treatment plant ofLower Ruvu intake is located downstream of the Upper Ruvu intake nearBagamoyo Town, 18 km upstream from the mouth of the river. The LowerRuvu treatment plant started operation in 1976 and is currently producing182,000m3/day of treated water.


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2.2.1 Lower Ruvu Water Treatment Plant

Each of the three pumps installed have capacity to pump clear watertowards the University reservoir at a discharge rate of 1.05m3/s (20mgd)against a total dynamic head of 108 m. At present, out of the three pumpsonly two of them are operational at a time to convey the treated water from

the pumping stations at a rate of 2.1m3/s (40mgd) through a 54 pre-stressed concrete pipeline over a total distance of 55,225 km to theUniversity reservoir which is at 70.4 m above the mean sea level. Themaximum design capacity of clear water pumping main is 3.16m 3/s (60mgd)at an operating head of 186 m, but this design capacity is not currently inoperation due to the poor condition of the primary main and the treatmentplant. As per design of the scheme about 47 to 51 m of the total dynamichead of the pump is used in static lift in order to overcome friction lossesthrough the water transmission main from the treatment plant to Universityreservoir.

The total capacity of the university reservoirs is 45,400 m3 which is the totalamount of two equal rectangular reinforced reservoirs with capacities 22,700m3 each. These reservoirs currently receive an average of 176,000 m3, butwater does not accumulate to reach the maximum capacity of the reservoirsdue to the fact that the amount of water being pumped is two third of theexpected volume, moreover a large amount of water is being consumed orleak before reaching the reservoirs and at the same time the demand of

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2.2.3Mtoni Water Treatment Plant

The third water source is Mtoni treatment plant located at the south of thecity approximately 7km from the town centre, which if compared to the othertwo plants is very small and the oldest. This plant was constructed in 1933and has a capacity to produce 6,800m3/day of treated water. The totalinstalled capacity of the three water plants is 270,800m3/day.


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Figure 3: Map of the existing water transmission mains from Upper and Lower Ruvu treatment plants to Kimara and University reservoirs respectively

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2.3 UNACCOUNTED WATER

Accordingly to JICA (Japanese International Cooperation Agency) findings ona study for the rehabilitation of DSM Water System 1991, the amount ofwater delivered by the Upper Ruvu system which is between 10% and 20%consumed or lost through leakage along the transmission mains beforereaching the reservoir in the city. The report elaborated further that waterlosses also exist in the distribution system; house service pipes, valveseating and public stand posts that have been estimated to be 35%, so thetotal amount of water unaccounted for according to the report was about

55%.

The JICA study, also explained that DAWASA has a list of domesticconnections in DSM, arranged in wards. The list was updated in 1989 and1990 but during that time many of connections were still unregistered toDAWASA. The study done by Price Waterhouse and Associates in 1989indicated that the ratio of accounted to unaccounted connections was almost1:1. However, in the case of commercial consumers, it was revealed thatthere were a considerable number of unregistered consumers. According to asurvey conducted by the Ardhi Institute, the ratio of the total number ofcommercial consumers to the total number of registered commercialconsumers (i.e. with account numbers) was of the order of 1:1.8. Therefore,at that period the total number of commercial consumers accordingly wasestimated as 1.8 times the total number of commercial accounts.

W f DSM l l h h h i l l k i


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serve one family which has the financial resources to venture onimplementing the project. In the long run this trend results into laying

several dozens of pipe lines in almost the same trench from the sametapping point conveying water to the same area.

Essentially, the efficient water system should furnish the whole area ofinterest with sufficient water at reasonable pressure. The following are someof the challenges which hamper the performance of the existing system todeliver optimal service over an area of interest as per design: -

The on-going exercise of providing water to individuals, direct from theprimary mains between the sources and the reservoir without constructingany appropriate water distribution networks.

The impending task of providing water to the outlying areas which arecurrently being surveyed to create plots conforming to Town Planningregulations so as to be developed on residential basis.


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CHAPTER THREE

3 METHODOLOGICAL TO STREAMLINE WATER SUPPLY TO DSM ANDOUTLYING AREAS

In order to minimize or eliminate the problems associated with insufficientsafe water there is the need to analyse all important aspects in designingwater systems by considering the current and precisely predeterminedfuture demand in the whole area of interest; rather than simply consideringsome parts within the area at different occasions so as to arrest the existingproblems at that particular time. It is obvious that water demand over anyparticular area within the project area is unevenly distributed and its patternis among the key factors governing the design of any water supply system.The available water sources, variation in topography and distances betweenwater sources and various distribution points should also be equally

considered in the course of setting up effective water systems. It is also beevident that from socio-economic point of view, within a particularcommunity there are variation within groups as people in regards theirability as well willingness to pay for operation and maintenance costs ofwater services, and the scope of deviation between these different groupsalso varies considerably.

From this explanation it can be observed that this analysis requires multi

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Current water production of main water sources currently servicing the city.

Estimated population of major parts of the project area.

Information from the topographical maps could be conventionally obtainedby manually scale out from the maps for establishing a working frameworkfor designing of water supply system. But it is a tedious task if this process ofobtaining and aggregating information to single plane representation entailsmultiple sheets of topographical maps so as to attain the required accuracy.Due to advent of computers, several software are already developed whichcan assist in transforming data from one form to another in order to facilitate

the analysis such as the use of attributed spatial data (Vectors and Rastamaps). Thus apart from Microsoft window package software; this study willutilize the GIS package software called ILWIS (Integrated Land and WaterInformation System) and EPANET software which performs extended periodsimulation of hydraulic and water quality behaviour within pressurized pipenetworks. The afore said and other software has limitations on performingtheir specific tasks, thus in order to use them successively, users are

required to know the basis of their developments such as mathematicalmodels used and limitation; however on top of that each software needsprogressive reasoning and evaluation of its outputs.

3.1 DATA ACQUISITION AND TREATMENT

h d i i i i hi d f d f f i


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Creation of water distribution zones using the created DEM.

Delineating highest point of each zone from the DEM.

Creation of junction nodes point map to represent the existing watersystems primary mains, treatment plant and reservoirs; this was carriedout by using DEM and a raster map for the existing water system.

Creation of EPANET softwares partial input-file for the existing primarywater transmission main network.

Simulation of primary transmission main model for supplying water to theidentified zones by using EPANET software.

Checking/analysing the output of a simulated model. Creation of second input file for EPANET software to refine the suggested

improvement obtained through simulation of the first input file.

Simulation of the model by exporting the second input file to EPANET so asto obtain the refined model.

3.1.1Data Acquisition

The main objective of the selected data acquisition techniques in this studyis to be able to use available computer supported tools to design the watersupply distribution network for different isolated zones over an area ofinterest, this means the entry of all required information to the computer isnecessary. Alphanumerical information can easily be entered in the modelcompared to information contained in a form of hardcopy images by just

i k b d d i i i i h i


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Model of entire project area, which was carried out by first digitising allcontours indicated in the topographical maps. The contours were digitised by

using on screen digitisation technique, under this technique eachtopographic map sheet was scanned using an A4 paper size scanner, eachsheet was scanned six to eight times so as to be able to scan the whole mapwith some degree of overlap.

The scanned images in bitmap format were exported to ILWIS software andgeo-referenced with reference to the coordinate system of the topographicalmaps so as to facilitate the digitisation process as well as the digitized map

gluing exercise. All portions of the digitized map as per intended theme wereglued together to form one thematic map, then the digitised six maps of thesame theme were also joined together to represent the whole study areaunder that particular subject. The major themes of the digitized map are: -

Contour segment map.

Road segment map.

Lower Ruvu and Upper Ruvu primary mains segment map.

Township point map.

Existing major reservoirs and treatment plant point map.

3.1.1.2 Creation of Digital Elevation Model

The digital elevation model was created from an aggregated contour map


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Figure 4: Illustration of interpolation process from segment maps

The pixel values in this example are calculated as follows:

1.The value for output pixel no. 1 is determined by the contour lines withvalue 0m and value 10m. The distance to these contour lines isrespectively 1 and 3 and therefore the pixel value will be ((3*10)+(1*0))/4= 7.5m. This interpolation relatively matches reality.


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When conducting contour interpolation exercise on a segment mapcontaining height (contour) information, the resulting raster map is a DigitalElevation Model (DEM). Basically the values calculated for pixels are the onesthat fall in between any two successive segments. For each undefined pixel,the distance is calculated towards the two nearest contour lines. Thedistances are calculated forwards and backwards, until no more changesoccur. Then a linear interpolation is performed using the two distance values;this returns the value for the undefined pixel.

In order to obtain the best DEM from the contour, it is important to select thepixel size which does not allow more than one contour line to fall in onepixel. So in this exercise the first DEM was created using pixel size of 10 andthen re-sampled to a DEM of 100m pixel size.

3.1.2 Data Treatment

3.1.2.1 Creation of Water Distribution Zones

Each of the digital vector maps created was used to facilitate variousanalysis through spatial data analysis by using ILWIS software, which in turnwas used to schematise a localized distribution zone with respect to the


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Figure 5:: Proposed water distribution zones map


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: Three dimension view of an area of interest as derive from the digital elevation model


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3.1.2.2 Computation of Water Demand

Basically, as described earlier, water demand for each zone should becomputed by analysing current and future demand, needs to be carried outby analysing every function to be supplied with water within each zone. Fromthe information presently in hand it is not easier to determine precisely thedemand of water for each zone and the maximum effective yield of theexisting source of water under consideration. So in order to be able to create

a prototype of water transmission network to the created zones from the twosources (Upper and Lower Ruvu); some information on preliminary results of2002 National Census was adopted and used as the basis for determinationof water demand for each zone.

However, it is unfortunate that the information on the detailed results of2002 National Census is still not yet released due to the fact that theinformation collected during the census exercise is still being processed sothat can clearly portray all intended statistical information. Meanwhile inorder to determine the water demand in each zone, the study would opt toredistribute the preliminary lumped result of DSM population to the createdzones relatively to previous population information in JICA report on studyresults for the rehabilitation of DSM Water System. The approach on theexercise of redistributing the population to respective zones apart from notbeing accurate, the information to be used could not enable the excellent


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Table 1: Rationalization of water produced by Upper and Lower Ruvu treatment plant to reflect what would

be water demand in localized distribution zones

No.

AreaZone Total

Aream2

PreviousEstimatedPopulatio

n

CurrentEstimatedPopulation

Distribution Zone

LPS

1. Kinyerezi

76,301,240

4540 5448 Kimara 9.46

2. Kipawa 49873 59848 Kimara 103.90

3. Kigogo 23496 55905 Kimara 97.06

4. Mabibo 50887 109513 Kimara 190.13

5. Magomeni 22895 33511 Kimara 58.18

6. Makuburi 52203 Kimara 90.63

7. Makurumla 59775 79221 Kimara 137.54

8. Manzese 60338 99796 Kimara 173.26

9. Mburahati 32353 Kimara 56.171

0. Mzimuni 26555 37602 Kimara 65.28

11. Ndugumbi 36243 55520 Kimara 96.391

2. Tandale 64671 66624 Kimara 115.671

3. Ubungo 63480 66381 Kimara 115.241

4. Unforeseen uses Kimara 500.00A Subtotal


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No.

AreaZone Total

Area

m2


n

CurrentEstimated

Population

Distribution Zone

LPS

2

2. Gerezani 9164 10997 University 19.09

3. Ilala 38803 46564 University 80.84

4. Jangwani 16961 20354 University 35.34

5. Kariakoo 13916 16700 University 28.99

6. Kisutu 9253 11104 University 19.28

7. Kivukoni 7259 8711 University 15.12

8. Mchafukoge 9463 11356 University 19.72

9. Mchikichini 16651 19982 University 34.6910. Tabata 24950 29940 University 51.981

1. Upanga East 12003 14404 University 25.011

2. Upanga West 13488 16186 University 28.101

3. Vingunguti 50185 60222 University 104.55

14. Hananasifu 47716 University 82.841

5. Kijitonyama 70929 University 123.141

6. Kinondoni 46928 32251 University 55.991

7. Makumbusho 82503 University 143.231


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No.

AreaZone Total

Area

m2


n

CurrentEstimated

Population

Distribution Zone

LPS

G. Kidege 90,594,532 Kidege 240.15H. Magoe

137,355,136 Magoe 91.08

I. Mbopo108,182,40

3 Mbopo 131.35

J. Mtakuja126,463,88

1 Mtakuja 335.23

K. Nyakahamba

134,675,482

Nyakahamba 357.00

L.Pangani

119,174,846 Pangani 315.91

M. Tondoroni

138,612,919 Tondoroni 367.44

N. Vikuge

228,711,068 Vikuge 606.27

O

. Viziwaziwa

185,623,20

7 Viziwaziwa 492.06

Grand Total8,070.8

0


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3.1.2.3 Creation of EPANET Software Input File

The input of schematized zones to EPANET could be in a form of image asbackdrop or NOTE PAD input file with extension INP. The former one is somehow too involving because the entry of most of the necessary informationshould be done through the software input dialogue box. The secondmethod of using input file prepared using NOTE PAD software is easier andso flexible due to the fact that it allows the entry of partial or entire networkinformation.

After having created the zones in order to obtain EPANET softwares input filethe following stage was carried out to determine the highest point withineach zone and treat them as the points for construction of storage tanks foreach of the respective zones. However it was realised that it is veryimportant to identify some point along the primary transmission mains fromthe two treatment plants to the two storage reservoirs to allow some

flexibility in the course of simulating the model. At the same time, thelocation points of the two treatment plant and reservoirs were also indicatedon the created input point-map.

The essence of this exercise was to create a point map which is attributedwith coordinates and altitudes for every created point; however this exercisewere repeated in order to create the second point map to identity the pointsin form of names of the area and abbreviations for the points along the


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more information on how EPANET software conduct hydraulic analysisconsult APPENDIX I

The methods used to solve the flow behaviour in pressurized pipes utilizecontinuity and head loss equations that illustrate the hydraulic state in thepipe network at a particular point in a given time. The hydraulic head lossesin the system occurs as water moves from one point to another depends onvariation in altitudes from one point to another, transmission media and allfittings. Since this analysis is a preliminary one and deals with long distancesof pipes, the network is not well detailed and hence the effects of fittings and

special on hydraulic behaviour would therefore not be taken intoconsideration. However, for long pipes, the contribution of all fittings onhydraulic head losses do not have large effects in the analysis so can beneglected. The hydraulic head losses by water flowing in a pipe due tofriction with the pipe walls can be computed using Hazen-Williams formula orDarcy-Weisbach formula or Chezy-Manning formula.

Table 2:Pipe Head loss Formulas for Full Flow (for head loss in feet and flow rate in cfs)

FORMULARESISTANCECOEFFICIENT

FLOW EXPONENT

Hanzen-Williams 4.727C-1.852 d-4.871 L 1.852Darcy-Weisbach 0.0252f( ,d,q)d-5 L 2

Chezy-Manning 4.66n2 d-5.33 L 2


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Concrete orConcrete lined

120-140 1.0-10 0.012-0.017

Galvanized Iron 120 0.5 0.015-0.017Plastic 140-150 0.005 0.011-0.015Steel 140-150 0.15 0.015-0.017Vitrified Clay 110 0.013-0.015

The Hazen-Williams formula is the one selected among the three mentionedformulae to be used because it is commonly used for computing head loss inpressurised water system. It cannot be used for liquids other than water and

was originally developed for turbulent flow only.

The Darcy-Weisbach formula is the most theoretically correct; it applies overall flow regimes and to all liquids. With the Darcy-Weisbach formula, EPANETuses different methods to compute the friction factor depending on the flowregime:

The HagenPoiseuille formula is used for laminar flow (Re < 2,000).

The Swamee and Jain approximation to the Colebrook-White equation isused for fully turbulent flow (Re > 4,000).

A cubic interpolation from the Moody Diagram is used for transitional flow(2,000 < Re < 4,000).

The Chezy-Manning formula is more commonly used for open channel flow.Basically each formula uses the following equation to compute head lossbetween the start and end node of the pipe:


37/95


38/95

Simulation Process

The first input map prepared on NOTE PAD was used to simulate a prototypemodel for primary transmission mains for zoned areas using EPANET. Thepartial model which was the result of input file was improved with otherinformation which were extracted from 1991 JICA report on the assessmentof performance of DSM water supply system and other studies carried out toinvestigate water leakages. This information includes: -

Size and length of water system primary mains

Installed capacities of Upper Ruvu and Lower Ruvu intake and treatment

plants Size and location of University and Kimara reservoirs etc.

Current water production of Upper and Lower Ruvu sources.

Estimated water demand for DSM city residents who are within thecommand area of University and Kimara water reservoirs.

Using EPANET, some parameters of the model were altered several times

with consideration to different scenarios by adding and omitting pipes andother special fittings in order to make sure that water from the two watersources reaches the highest point of each zone at a reasonable flow andpressure. After obtaining the first simulated model of primary transmissionmains, the improvement of the model entailed extra information from thedigital elevation model. These information were so necessary in order toposition the new point and links which are the outcomes of the simulatedmodel on a relatively gradually varying ground plane and on the other hand


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Figure 6: Map of the first simulated water transmission mains for supplying water to localized water distribution zone created by using EPANET

software


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Table 4: Results at the nodes after the first simulation of the model for supplying water to localized water

distribution zone created by using EPANET software

ELEVATION BASE DEMAND DEMAND HEAD PRESSURENode ID m LPS LPS m m

Junc Up1 34.57 0 0 262.84 228.27

Junc Up2 69.46 0 0 258.9 189.44

Junc Up3 81.65 0 0 255.66 174.01

Junc Up4 86.21 0 0 246.97 160.76

Junc Up5 100 0 0 242.05 142.05

Junc Up6 100.89 0 0 238.18 137.29

Junc Vikuge 120.64 606.274 606.27 211.23 90.59Junc Up7 114.31 0 0 236.35 122.04

Junc Up8 120.37 0 0 235.86 115.49

Junc Up9 108.07 0 0 235.17 127.1

Junc Mtakuja 71.74 335.23 335.23 270.63 198.89

Junc Lw1 29.21 0 0 246.36 217.15

Junc Up10 121 0 0 234.35 113.35

Junc Up11 118.04 0 0 233.11 115.07

Junc Viziwaziwa 160 492.056 492.06 218.26 58.26

Junc Up12 140.6 0 0 231.1 90.5

Junc Lw2 40 0 0 230.87 190.87

Junc Up13 150.54 0 0 230.99 80.45

Junc Kidege 142.16 240.15 240.15 244.47 102.31

Junc Up14 119.59 0 0 230.89 111.3

Junc Lw3 43.16 0 0 214.78 171.62

Junc Chamagwe 83.73 553.58 553.58 214.19 130.46

Junc Up15 141.06 0 0 230.83 89.77


41/95

ELEVATION BASE DEMAND DEMAND HEAD PRESSURE

Node ID m LPS LPS m m

Junc Kimara 120 1808.9 1808.9 157.63 37.63

Junc Manyema 120 429.4 429.4 130.16 10.16

Junc Lw10 51.24 0 0 146.57 95.33

Junc Lw11 31.81 0 0 141.94 110.13

Junc University 74.56 2268.49 2268.49 134.64 60.08

Junc Lw12 42.33 0 0 137.42 95.09

Resvr UpperRv 44.64 #N/A -1213.49 44.64 0

Resvr LowerRv 20.21 #N/A -7287.72 20.21 0


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Table 5: Results at the links after the first simulation of the model for supplying water to created localized water distribution zone created by usingEPANET software

LENGTH DIAMETERROUGHNESSCONSTANT

FLOW VELOCITYUNIT HEAD

LOSSFRICTIONFACTOR

REACTIONRATE

STATUS

Link ID m MmHazen-

WilliamsLPS m/s m/km mg/L/d

Pipe 4 4609.77 1400 120 3739.82 2.43 3.36 0.016 0 Open

Pipe 5 4785.39 1400 120 3739.82 2.43 3.36 0.016 0 Open

Pipe 6 4242.64 1400 120 3186.24 2.07 2.5 0.016 0 Open

Pipe 7 4512.21 1400 120 3186.24 2.07 2.5 0.016 0 Open

Pipe 8 3401.47 1400 120 3186.24 2.07 2.5 0.016 0 Open

Pipe 9 3312.1 1400 120 2829.24 1.84 2 0.016 0 Open

Pipe 10 3640.05 1400 120 2829.24 1.84 2 0.016 0 Open

Pipe 11 5950.63 1400 120 2829.24 1.84 2 0.016 0 Open

Pipe 12 6519.2 1400 120 2697.89 1.75 1.84 0.016 0 OpenPipe 13 3478.51 1400 120 2268.49 1.47 1.33 0.017 0 Open

Pipe 14 3395.59 1400 120 2268.49 1.47 1.33 0.017 0 Open

Pipe 15 2088.06 1400 120 2268.49 1.47 1.33 0.017 0 Open

Pipe 16 1360.15 600 140 433.64 1.53 2.9 0.015 0 Open

Pipe 17 1118.03 600 140 433.64 1.53 2.9 0.015 0 Open

Pipe 18 3000 600 140 433.64 1.53 2.9 0.015 0 Open

Pipe 19 1700 600 140 433.64 1.53 2.9 0.015 0 Open

Pipe 20 1334.17 600 140 433.64 1.53 2.9 0.015 0 Open

Pipe 21 2280.35 600 140 216.99 0.77 0.8 0.016 0 Open

Pipe 22 608.28 600 140 216.99 0.77 0.8 0.016 0 Open


Pipe 25 1552.42 600 140 216.99 0.77 0.8 0.016 0 Open

Pipe 26 2500 600 140 216.99 0.77 0.8 0.016 0 Open

Pipe 27 2816.03 600 140 41.15 0.15 0.04 0.021 0 Open

Pipe 28 2692.58 600 140 41.15 0.15 0.04 0.021 0 Open

Pipe 29 1708.8 600 140 41.15 0.15 0.04 0.021 0 Open

Pipe 30 2195.45 600 140 41.15 0.15 0.04 0.021 0 Open

Pipe 31 1878.83 600 140 41.15 0.15 0.04 0.021 0 Open


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LOSSFRICTIONFACTOR

REACTIONRATE

STATUS

Link ID m MmHazen-


Pipe 32 1523.15 600 140 322.69 1.14 1.68 0.015 0 Open


Pipe 35 2500 600 140 191.39 0.68 0.64 0.016 0 Open

Pipe 36 1931.32 600 140 646.76 2.29 6.07 0.014 0 Open

Pipe 37 2529.82 600 140 646.76 2.29 6.07 0.014 0 Open

Pipe 38 1886.8 600 140 646.41 2.29 6.07 0.014 0 Open

Pipe 39 1403.57 600 140 646.41 2.29 6.07 0.014 0 Open

Pipe 40 2473.86 600 140 646.41 2.29 6.07 0.014 0 Open

Pipe 41 1360.15 750 140 779.85 1.77 2.9 0.014 0 Open

Pipe 42 1118.03 750 140 779.85 1.77 2.9 0.014 0 Open

Pipe 43 3000 750 140 779.85 1.77 2.9 0.014 0 Open

Pipe 44 1700 750 140 779.85 1.77 2.9 0.014 0 OpenPipe 45 1334.17 750 140 779.85 1.77 2.9 0.014 0 Open

Pipe 46 2280.35 750 140 390.23 0.88 0.8 0.015 0 Open

Pipe 47 608.28 750 140 390.23 0.88 0.8 0.015 0 Open

Pipe 48 854.4 750 140 390.23 0.88 0.8 0.015 0 Open

Pipe 49 1019.8 750 140 390.23 0.88 0.8 0.015 0 Open

Pipe 50 1552.42 750 140 390.23 0.88 0.8 0.015 0 Open

Pipe 51 2500 750 140 390.23 0.88 0.8 0.015 0 Open

Pipe 52 2816.03 750 140 74 0.17 0.04 0.019 0 Open

Pipe 53 2692.58 750 140 74 0.17 0.04 0.019 0 Open

Pipe 54 1708.8 750 140 74 0.17 0.04 0.019 0 Open

Pipe 55 2195.45 750 140 74 0.17 0.04 0.019 0 OpenPipe 56 1878.83 750 140 74 0.17 0.04 0.019 0 Open

Pipe 57 1523.15 750 140 580.32 1.31 1.68 0.014 0 Open

Pipe 58 3001.67 750 140 580.32 1.31 1.68 0.014 0 Open

Pipe 59 2807.13 750 140 344.19 0.78 0.64 0.015 0 Open

Pipe 60 2500 750 140 344.19 0.78 0.64 0.015 0 Open

Pipe 61 1931.32 750 140 1163.14 2.63 6.07 0.013 0 Open

Pipe 62 2529.82 750 140 1163.14 2.63 6.07 0.013 0 Open

Pipe 63 1886.8 750 140 1162.49 2.63 6.07 0.013 0 Open


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LOSSFRICTIONFACTOR

REACTIONRATE

STATUS

Link ID m MmHazen-


Pipe 64 1403.57 750 140 1162.49 2.63 6.07 0.013 0 Open

Pipe 65 2473.86 750 140 1162.49 2.63 6.07 0.013 0 OpenPipe 68 4522.17 600 140 357 1.26 2.02 0.015 0 Open

Pipe 69 6276.94 600 140 131.35 0.46 0.32 0.017 0 Open

Pipe 70 5768.88 600 140 429.4 1.52 2.85 0.015 0 Open

Pipe 74 5001 600 140 606.27 2.14 5.39 0.014 0 Open

Pipe 75 3505.71 600 140 492.06 1.74 3.66 0.014 0 Open

Pipe 76 6428.06 1000 140 367.44 0.47 0.18 0.016 0 Open

Pipe 78 5818.08 600 140 201.04 0.71 0.7 0.016 0 Open

Pipe 73 6103.28 1400 120 553.58 0.36 0.1 0.021 0 Open

Pipe 104 13720.06 1400 140 3212.68 2.09 1.91 0.012 0 Open

Pipe 105 7884.8 1400 140 2972.52 1.93 1.65 0.012 0 Open


Pipe 108 8509.41 1400 140 1777.67 1.15 0.64 0.013 0 Open

Pump 1 #N/A #N/A #N/A 3739.82 0 -226.15 0 0 Open

Pump 2 #N/A #N/A #N/A 1213.49 0 -218.2 0 0 Open

Pump 79 #N/A #N/A #N/A 3547.91 0 -250.42 0 0 Open

Pump 3 #N/A #N/A #N/A 503.35 0 -150.13 0 0 Open

Valve 66 #N/A 1400 #N/A 0 0 0 0 0 Closed


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The creation of another improved input file was carried out by adding newpoints to the previous point map. This exercise was achieved using ILWISsoftware on the basis of the created digital elevation model. The new pointswere added to the point map through following gradual changes in altitudeby investigating the trend of values of neighbouring pixel to the positionwhere the new points were located with regard to the output of thesimulation exercise. Some of the new points which were found that could bepositioned on almost the same altitude belt were shifted so as to ensure the

smooth placement of the pipes if the project has to be carried out.

Basically this exercise of creating the second input map to improve theprevious one was so important in order to ensure that the final output modeldo not deviate so much from the model likely to be implemented. Afterrepositioning the new points in the point map, a similar procedure oftransferring information from point map in ILWIS to NOTE PAD input file werefollowed as described above. The final model of primary transmission mains

was created by refining the previous model of primary transmission mainusing the second input file. The exercise was carried out by systematicallyvarying parameters of the network and each time ran the model to obtainthe result.


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Figure 7: Map of the final simulated water transmission mains for supplying water to localized water distribution zone created by using EPANET

software


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Table 6:Results at the nodes after the first simulation of the model for supplying water to localized water

distribution zone created by using EPANET software

ELEVATION BASE DEMAND DEMAND HEAD PRESSURENode ID m LPS LPS m m

Junc Up1 34.57 0 0 364.46 329.89

Junc Up2 69.46 0 0 355.59 286.13

Junc Up3 81.65 0 0 348.3 266.65

Junc Up4 86.21 0 0 328.74 242.53

Junc Up5 100 0 0 317.66 217.66

Junc Up6 100.89 0 0 308.96 208.07

Junc Vikuge 120.64 606.274 606.27 282.01 161.37Junc Up7 114.31 0 0 301.73 187.42

Junc Up8 120.37 0 0 299.8 179.43

Junc Up9 108.07 0 0 297.09 189.02

Junc Mtakuja 71.74 335.23 335.23 262.99 191.25

Junc Lw1 29.21 0 0 186.66 157.45

Junc Up10 121 0 0 293.85 172.85

Junc Up11 118.04 0 0 288.93 170.89

Junc Viziwaziwa 160 492.056 492.06 268.17 108.17

Junc Up12 140.6 0 0 281 140.4Junc Lw2 40 0 0 174.3 134.3

Junc Up13 150.54 0 0 270.36 119.82

Junc Kidege 142.16 240.15 240.15 239.96 97.8

Junc Up14 119.59 0 0 260.19 140.6

Junc Lw3 43.16 0 0 161.46 118.3

Junc Chamagwe 83.73 553.58 553.58 133.67 49.94

Junc Up15 141.06 0 0 253.73 112.67


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ELEVATION BASE DEMAND DEMAND HEAD PRESSURE

Node ID m LPS LPS m m

Junc Kimara 120 1808.9 1808.9 147.78 27.78

Junc Manyema 120 429.4 429.4 162.67 42.67

Junc Lw10 51.24 0 0 110.48 59.24

Junc Lw11 31.81 0 0 105.85 74.04

Junc University 74.56 2268.49 2268.49 98.54 23.98

Junc Lw12 42.33 0 0 101.33 59

Junc chasimba 61.78 0 0 351.51 289.73

Junc lugera 72.31 0 0 340.71 268.4

Junc kumba 94.21 0 0 329.58 235.37

Junc msangani 115.79 0 0 315.53 199.74Junc kidimu 122.04 0 0 301.95 179.91

Junc kivukoni 127.15 0 0 295.78 168.63

Junc luis 158 0 0 283.61 125.61

Junc goba 136.88 0 0 269.61 132.73

Resvr UpperRv 44.64 #N/A -1880.41 44.64 0

Resvr LowerRv 20.21 #N/A -6619.8 20.21 0


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Table 7: Results at the links after the second simulation of the model for supplying water to created localized water distribution zone created by using

EPANET software



LOSSFRICTIONFACTOR

REACTIONRATE

STATUS

Link ID M mm

Hazen-Williams LPS m/s m/km mg/L/d

Pipe 1 4609.77 1400 120 3310.42 2.15 2.68 0.016 0 Open

Pipe 2 4785.39 1400 120 3310.42 2.15 2.68 0.016 0 Open

Pipe 3 4242.64 1400 120 2756.84 1.79 1.91 0.016 0 Open

Pipe 4 4512.21 1400 120 2756.84 1.79 1.91 0.016 0 Open

Pipe 5 3401.47 1400 120 2756.84 1.79 1.91 0.016 0 Open

Pipe 6 3312.1 1400 120 2399.84 1.56 1.48 0.017 0 Open

Pipe 7 3640.05 1400 120 2399.84 1.56 1.48 0.017 0 Open

Pipe 8 5950.63 1400 120 2399.84 1.56 1.48 0.017 0 Open

Pipe 9 6519.2 1400 120 2268.49 1.47 1.33 0.017 0 Open


Pipe 12 2088.06 1400 120 2268.49 1.47 1.33 0.017 0 Open

Pipe 13 4031.13 1400 120 3309.38 2.15 2.68 0.016 0 Open

Pipe 14 5060.63 1400 120 2974.15 1.93 2.2 0.016 0 Open

Pipe 15 6389.05 1400 120 2974.15 1.93 2.2 0.016 0 Open

Pipe 16 11605.6 1400 120 2115.53 1.37 1.17 0.017 0 Open

Pipe 17 7111.26 1400 120 1799.62 1.17 0.87 0.017 0 Open

Pipe 18 3214.03 600 120 429.4 1.52 3.79 0.019 0 Open

Pipe 19 3700 600 120 429.4 1.52 3.79 0.019 0 Open

Pipe 20 3920.46 400 120 429.4 3.42 27.28 0.018 0 Open


Pipe 23 3000 600 140 671.96 2.38 6.52 0.014 0 Open

Pipe 24 1700 600 140 671.96 2.38 6.52 0.014 0 Open

Pipe 25 1334.17 600 140 671.96 2.38 6.52 0.014 0 Open

Pipe 26 2280.35 600 140 455.31 1.61 3.17 0.014 0 Open

Pipe 27 608.28 600 140 455.31 1.61 3.17 0.014 0 Open

Pipe 28 854.4 600 140 455.31 1.61 3.17 0.014 0 Open

Pipe 29 1019.8 600 140 455.31 1.61 3.17 0.014 0 Open


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LOSSFRICTIONFACTOR

REACTIONRATE

STATUS

Link ID M mmHazen-


Pipe 30 1552.42 600 140 455.31 1.61 3.17 0.014 0 Open

Pipe 31 2500 600 140 455.31 1.61 3.17 0.014 0 OpenPipe 32 2816.03 600 140 500.48 1.77 3.78 0.014 0 Open

Pipe 33 2692.58 600 140 500.48 1.77 3.78 0.014 0 Open

Pipe 34 1708.8 600 140 500.48 1.77 3.78 0.014 0 Open

Pipe 35 2195.45 600 140 500.48 1.77 3.78 0.014 0 Open

Pipe 36 1878.83 600 140 500.48 1.77 3.78 0.014 0 Open

Pipe 37 1523.15 600 140 500.48 1.77 3.78 0.014 0 Open

Pipe 38 3001.67 600 140 500.48 1.77 3.78 0.014 0 Open

Pipe 39 2807.13 600 140 369.18 1.31 2.15 0.015 0 Open

Pipe 40 2500 600 140 369.18 1.31 2.15 0.015 0 Open

Pipe 41 1931.32 600 140 646.41 2.29 6.07 0.014 0 Open


Pipe 44 1403.57 600 140 646.41 2.29 6.07 0.014 0 Open

Pipe 45 2473.86 600 140 646.41 2.29 6.07 0.014 0 Open

Pipe 46 1360.15 750 140 1208.45 2.74 6.52 0.013 0 Open

Pipe 47 1118.03 750 140 1208.45 2.74 6.52 0.013 0 Open

Pipe 48 3000 750 140 1208.45 2.74 6.52 0.013 0 Open

Pipe 49 1700 750 140 1208.45 2.74 6.52 0.013 0 Open

Pipe 50 1334.17 750 140 1208.45 2.74 6.52 0.013 0 Open

Pipe 51 2280.35 750 140 818.83 1.85 3.17 0.014 0 Open

Pipe 52 608.28 750 140 818.83 1.85 3.17 0.014 0 Open


Pipe 55 1552.42 750 140 818.83 1.85 3.17 0.014 0 Open

Pipe 56 2500 750 140 818.83 1.85 3.17 0.014 0 Open

Pipe 57 2816.03 750 140 900.07 2.04 3.78 0.013 0 Open

Pipe 58 2692.58 750 140 900.07 2.04 3.78 0.013 0 Open

Pipe 59 1708.8 750 140 900.07 2.04 3.78 0.013 0 Open

Pipe 60 2195.45 750 140 900.07 2.04 3.78 0.013 0 Open

Pipe 61 1878.83 750 140 900.07 2.04 3.78 0.013 0 Open


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LOSSFRICTIONFACTOR

REACTIONRATE

STATUS

Link ID M mmHazen-


Pipe 62 1523.15 750 140 900.07 2.04 3.78 0.013 0 Open


Pipe 65 2500 750 140 663.93 1.5 2.15 0.014 0 Open

Pipe 66 1931.32 750 140 1162.49 2.63 6.07 0.013 0 Open

Pipe 67 2529.82 750 140 1162.49 2.63 6.07 0.013 0 Open

Pipe 68 1886.8 750 140 1162.49 2.63 6.07 0.013 0 Open

Pipe 69 1403.57 750 140 1162.49 2.63 6.07 0.013 0 Open

Pipe 70 2473.86 750 140 1162.49 2.63 6.07 0.013 0 Open

Pipe 71 5001 600 140 606.27 2.14 5.39 0.014 0 Open

Pipe 72 3505.71 600 140 492.06 1.74 3.66 0.014 0 Open

Pipe 73 6428.06 600 140 367.44 1.3 2.13 0.015 0 Open


Pipe 76 4522.17 600 140 357 1.26 2.02 0.015 0 Open

Pipe 77 4527.69 600 140 91.08 0.32 0.16 0.018 0 Open

Pipe 78 2662.71 300 140 240.15 3.4 28.38 0.014 0 Open

Pipe 79 1992.49 600 140 315.91 1.12 1.61 0.015 0 Open

Pipe 80 6174.14 600 140 618.47 2.19 5.59 0.014 0 Open

Pipe 81 4001.25 600 140 1279.14 4.52 21.48 0.012 0 Open

Pipe 86 6276.94 600 140 131.35 0.46 0.32 0.017 0 Open

Pipe 88 1476.48 300 140 335.23 4.74 52.64 0.014 0 Open

Pump 82 #N/A #N/A #N/A 3310.42 0 -166.45 0 0 Open

Pump 83 #N/A #N/A #N/A 3309.38 0 -331.3 0 0 OpenPump 84 #N/A #N/A #N/A 1880.41 0 -319.82 0 0 Open

Pump 85 #N/A #N/A #N/A 503.35 0 -110.09 0 0 Open

Valve 87 #N/A 600 #N/A 0 0 0 0 0 Closed


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3.2 INNOVATIVE RECCOMMENDATION

From the simulated water system model, the introduced 15 zones would beprovided with water from the two treatment plant; Upper and Lower Ruvu. Inorder to make sure that the supply of water to the introduced zones does notimpair the delivery of water to University and Kimara reservoirs, a newtransmission main is introduced. This transmission main is expected tosupply water from Lower Ruvu treatment plant at a rate of 3309.38litres per

second and supposed to be laid along the corridor which is between the twoexisting transmission mains. The path proposed for this transmission main isadopted in order to enable the efficient delivery of water to the createdzones.

Operationally, the introduced transmission main could also be used to feedthe existing Lower Ruvu transmission main in case of any breakdown;especial when the problem along the said main occur before where the

introduced transmission main has to be connected with it. For moreclarification on the specifications of the introduced, major and minortransmission mains consult appendix III. The following table indicates areasof each zone and the discharge of water which would be delivered.

Table 8: Surface Areas of Each Zone and Designed Water Discharge Rates

No. Distribution Zone Zone Total Area (m2) LPS


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3.3 PROJECT BENEFITS

Compared to the existing DSM water system, the localized distribution zonesbeing proposed have a wide spectrum of advantages which canaccommodate technical, administrative and socio-economic aspects.

Technical Benefits

Technically the proposed archetype water distribution system can assist onachieving the following: -

Reasonable and stable pressure and discharge in each zone.

Monitor and regulate water consumption rates at every zone.

Examine the amount of water entering and leaving each junction to a

specific direction.

Planning and preparation of various construction phases of the project.

Permitting post disinfection process at zone level whenever required.

Conducting of water losses assessment along the transmission mains byanalysing the amount of water which enters and leaves the system junction


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Delineation and protection of areas for water supply system infrastructureover the project area.

Assessment on the performance of a specific zone management team

Encourage and pave a way to a swift shift from the current practice ofwater supply driven approach to meet water demands to theeffective methodology ofwater demand management approach.

Socio-Economic Benefits

In each zone there are different groups of people with diverse livingstandards. With reference to the whole project area, it would be easier toidentify individual and groups of people with low ability to pay water serviceswithin zones. This means that any special arrangements can efficiently becarried out within each zone in order to furnish the disadvantaged groupswith water services compared to the current situation.


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CHAPTER FOUR

4 CONCLUSSION AND RECOMMENDATIONS

With regard to all constraints which hinder the efficiency in delivering waterservices in DSM region and the outlaying areas; it is essential to carry out athorough study for improving the water system for the whole area of DSMcity, its peri-urban and the neighbourhood region districts which are totally

or partially being served by the existing water system; rather than keep ondeveloping water services which their analysis at particular time are mostlyconfined only to some portions of the project area. On the other hand it isalso important to make sure that the outcome of the study can be carriedout in various stages depending on the priorities without affecting previouslyimplemented project phase of the new design of water system.

With regard to the existing system the aim of this study is to improve thelevel of water services in the project area by improving the managementaspects of the scheme using the approach suggested in this study, but it isvery difficult to implement the suggested measures in a short time due tofinancial constraints. This situation should not frustrate the process ofachieving reliable water services due to the fact that the water demand is onhigh increase over the area of interest. Therefore arrangement should bedone so that the suggested project can be carried out in phases.


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REFERENCE

1. EPANET 2 USERS MANUAL: by Lewis A. Rossman -Water Supply andWater Resources Division - Cincinnati, OH 45268

2. ILWIS 2.1 USERS GUIDE - Integrated Land and Water InformationSystem: by ILWIS Department International Institute for AerospaceSurvey & Earth Science Enschede, The Netherlands.

3. P. N. Khanna 1958. Indian Practical Civil Engineering Handbook

4. Clark, Viessman & Hammer (1971). Water Supply and Pollution Control

5. Babbit and Doland (1949). Water Supply Engineering


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APPENDIX I

EPANET SOFTWARE ANALYSIS ALGORITHMS

HydraulicsThe method used in EPANET to solve the flow continuity and headloss equations that characterize the hydraulic state of the pipenetwork at a given point in time can be termed a hybrid node-loopapproach. Todini and Pilati (1987) and later Salgado et al. (1988)chose to call it the "Gradient Method". Similar approaches havebeen described by Hamam and Brameller (1971) (the "HybridMethod) and by Osiadacz (1987) (the "Newton Loop-Node Method").The only difference between these methods is the way in which link

flows are updated after a new trial solution for nodal heads has beenfound. Because Todini's approach is simpler, it was chosen for use inEPANET.

Assume we have a pipe network with N junction nodes and NF fixedgrade nodes (tanks and reservoirs). Let the flow-head loss relation ina pipe between nodes i and j be given as:


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The Gradient solution method begins with an initial estimate of flowsin each pipe that may not necessarily satisfy flow continuity. At each

iteration step of the method, new nodal heads are found by solvingthe matrix equation:

where A = an (NxN) Jacobian matrix, H = an (Nx1) vector ofunknown nodal heads, and F = an (Nx1) vector of right hand side

terms The diagonal elements of the Jacobian matrix are:

while the non-zero, off-diagonal terms are:

wherepijis the inverse derivative of the head loss in the linkbetween nodes i and j with respect to flow. For pipes,


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for pumps, where sgn(x) is 1 if x > 0 and -1 otherwise. (Qijis alwayspositive for pumps.)

After new heads are computed by solving Eq. (D.3), new flows arefound from:

If the sum of absolute flow changes relative to the total flow in all

links is larger than some tolerance (e.g., 0.001), then Eqs. (D.3) and(D.4) are solved once again. The flow update formula (D.4) alwaysresults in flow continuity around each node after the first iteration.

EPANET implements this method using the following steps:

1.The linear system of equations D.3 is solved using a sparsematrix method based on node re-ordering (George and Liu, 1981).

After reordering the nodes to minimize the amount of fill-in formatrix A, a symbolic factorization is carried out so that only the non-zeroelements of A need be stored and operated on in memory. Forextended period simulation this re-ordering and factorization is onlycarried out once at the start of the analysis.


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Cubic Interpolation from Moody Diagram for 2,000 < Re < 4,000(Dunlop, 1991):

where e = pipe roughness and d= pipe diameter.


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iteration, up until the 10th iteration. After this, status checks aremade only after convergence is achieved. Status checks on pressure

control valves (PRVs and PSVs) are made after each iteration.

8. During status checks, pumps are closed if the head gain isgreater than the shutoff head (to prevent reverse flow). Similarly,check valves are closed if the head loss through them is negative(see below). When these conditions are not present, the link is re-opened. A similar status check is made for links connected toempty/full tanks. Such links are closed if the difference in head

across the link would cause an empty tank to drain or a full tank tofill. They are reopened at the next status check if such conditions nolonger hold.

9. Simply checking ifh < 0 to determine if a check valve should beclosed or open was found to cause cycling between these two statesin some networks due to limits on numerical precision. The following

procedure was devised to provide a more robust test of the status ofa check valve (CV):


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13.The logic used to test the status of a PRV is as follows:

where Q is the current flow through the valve, Hi is its upstreamhead, Hj is its downstream head, Hset is its pressure settingconverted to head, Hml is the minor loss when the valve is open (=mQ2), and Htol and Qtol are the same values used for check valvesin item 9 above. A similar set of tests is used for PSVs, except thatwhen testing against Hset the i and j subscripts are switched as are


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pumps, CVs, FCVs, and links to tanks is made. Also, the status oflinks controlled by pressure switches (e.g., a pump controlled by the

pressure at a junction node) is checked. If any status change occurs,the iterations must continue for at least two more iterations (i.e., aconvergence check is skipped on the very next iteration). Otherwise,a final solution has been obtained.

17. For extended period simulation (EPS), the following procedure isimplemented:

a) After a solution is found for the current time period, the time stepfor the next solution is the minimum of:

the time until a new demand period begins,

the shortest time for a tank to fill or drain,

the shortest time until a tank level reaches a point that triggers achange in status for some link (e.g., opens or closes a pump) asstipulated in a simple control,

the next time until a simple timer control on a link kicks in,the next time at which a rule-based control causes a status changesomewhere in the network. In computing the times based on tanklevels, the latter are assumed to change in a linear fashion basedon the current flow solution. The activation time of rule-basedcontrols is computed as follows:


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c) A new set of iterations with Eqs. (D.3) and (D.4) are begun at thecurrent set of flows.


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APPENDIX II

FIRST INPUT FILE TO EPANET SOFTWARE

[TITLE]

FIRST INPUTFILE

[JUNCTIONS]

;--------------------------------------------

;ID Elevations Demand

; m LPS

;--------------------------------------------

UpperRv 44.64 92.4

Up1 34.57 92.4

Up2 69.46 88.2Up3 81.65 88.2

Up4 86.21 88.2

Up5 100 88.2

Up6 100.89 88.2

Vikuge120.64 170

LowerRv 20.21 1


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Lw6 46.94 57.5Up20 129.49 117.1

Lw7 32.06 117.1

Up21 175 170

Magoe 180 92.4

Kwembe 175.19 92.4

Up22 141.85 88.2

Lw8 53.71 88.2

Pugu 260.42 88.2

Up23 119.55 88.2

Mbopo101.17 88.2

Up24 140.35 170

Up25 128.16 1

Lw9 19.06 170

Kimara 120 117.1

Manyema 120 117.1Lw10 51.24 92.4

Lw11 31.81 92.4

University 74.56 170

Lw12 42.33 57.5

[COORDINATES]


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Up15 495900 9252200Up16 497800 9251100

Lw4 498500 9274500

Up17 499500 9250300

Pangani 500700 9255600

Up18 500900 9249700

Lw5 502900 9273500

Up19 503900 9249600

Tondoroni 504500 9243200

Nyakahamba 504600 9267800

Lw6 506000 9272100

Up20 506700 9249800

Lw7 508900 9270500

Up21 509100 9249100

Magoe 509500 9257600

Kwembe 509700 9246600Up22 510900 9249800

Lw8 512300 9269200

Pugu 512500 9241500

Up23 513300 9250600

Mbopo514500 9261300

Up24 514900 9249600

Up25 516300 9249700


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SECOND INPUT FILE TO EPANET SOFTWARE

[TITLE]

SECOND INPUTFILE

[JUNCTIONS]

;--------------------------------------------

;ID Elevations Demand

; m LPS

;--------------------------------------------

Up1 34.57 1

Up2 69.46 1

Up3 81.65 1

Up4 86.21 1

Up5 100 1

Up6 100.89 1Vikuge120.64 712.43

Up7 114.31 1

Up8 120.37 1

Up9 108.07 1

Mtakuja 71.74 393.93

Lw1 29.21 1

Up10 121 1


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Up22 141.85 1

Lw8 53.71 1Pugu 260.42 201.04

Up23 119.55 1

Mbopo101.17 61.90

Up24 140.35 1

Up25 128.16 1

Lw9 19.06 1

Kimara 120 1,808.90

Manyema 120 429.40

Lw10 51.24 1

Lw11 31.81 1

University 74.56 2,268.49

Lw12 42.33 1

[RESERVOIRS];------------------------------------

; Elev.

; ID m

;-----------------------------------

UpperRv 44.64

LowerRv 20.21


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Up14 494300 9252800

Lw3 494300 9275100Chamagwe 494500 9269000

Up15 495900 9252200

Up16 497800 9251100

Lw4 498500 9274500

Up17 499500 9250300

Pangani 500700 9255600

Up18 500900 9249700

Lw5 502900 9273500

Up19 503900 9249600

Tondoroni 504500 9243200

Nyakahamba 504600 9267800

Lw6 506000 9272100

Up20 506700 9249800

Lw7 508900 9270500

Up21 509100 9249100Magoe 509500 9257600

Kwembe 509700 9246600

Up22 510900 9249800

Lw8 512300 9269200

Pugu 512500 9241500

Up23 513300 9250600

Mbopo514500 9261300


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APPENDIX III

LONGITUDINAL SECTIONS AND DESCRIPTIONS OF

EXISTING AND PROPOSED ADDITIONAL TRANSMISSION

MAINS


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Table 9: DESCRIPTIONS OF PROPOSED ADDITIONAL TRANSMISSION MAIN FROM LOWER RUVU TREATMENT PLANT TO MANYEMA

Node IdLink Id Chainage

ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant

Flow VelocityUnit Head

lossFrictionFactor

(m) (m) (m) (m) (LPS) (mm)Hazen-

Williams(LPS) (m/s) (m/km)

Junc LoweRv 0 20.21 20.21 0 0

Pump 83 #N/A 0 3309.38 0 -331.3 0

Junc chasimba 4876.47 61.78 351.51 289.73 01400 120 3309.38 2.15 2.68 0.016

Junc lugera Pipe 13 8907.6 72.31 340.71 268.4 0

1400 120 2974.15 1.93 2.2 0.016

Junc kumba Pipe 14 13968.23 94.21 329.58 235.37 0

1400 120 2974.15 1.93 2.2 0.016

Junc msangani Pipe 15 20357.28 115.79 315.53 199.74 0

1400 120 2115.53 1.37 1.17 0.017

Junc kidimu Pipe 16 31962.88 122.04 301.95 179.91 0

1400 120 1799.62 1.17 0.87 0.017

Junc kivukoni Pipe 17 39074.14 127.15 295.78 168.63 0

600 120 429.4 1.52 3.79 0.019

Junc luis Pipe 18 42288.17 158 283.61 125.61 0

600 120 429.4 1.52 3.79 0.019Junc goba Pipe 19 45988.17 136.88 269.61 132.73 0

400 120 429.4 3.42 27.28 0.018

Junc Manyema Pipe 20 49908.63 120 162.67 42.67 429.4

GONSALVES RWEGASIRA RUTAKYAMIRWA

XVI


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P

Figure 8: LONGITUDINAL SECTION OF PROPOSED ADDITIONAL TRANSMISSION MAIN FROM LOWER RUVU TREATMENT PLANT TO

MANYEMA


XVII


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Table 10: DESCRIPTIONS OF PROPOSED BRANCH FROM LUGERA JUNCTION NODE TO MTAKUJA DISTRIBUTION ZONE


ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant


lossFrictionFactor



Junc lugera 0 72.31 340.71 268.4 0

Pipe 88 300 140 335.23 4.74 52.64 0.014

Junc Mtakuja 1476.48 71.74 262.99 191.25 335.23

P

400

Figure 9: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM LUGERA JUNCTION NODE TO MTAKUJA DISTRIBUTION ZONE


XVIII


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Table 11: DESCRIPTIONS OF PROPOSED BRANCH FROM MSANGANI JUNCTION NODE TO KIDEGE DISTRIBUTION ZONE


ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant


lossFrictionFactor



Junc msangani 0 115.79 315.53 199.74 0

Pipe 78 300 140 240.15 3.4 28.38 0.014

Junc Kidege 2662.71 142.16 239.96 97.8 240.15

P

350

Figure 10: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM MSANGANI JUNCTION NODE TO KIDEGE DISTRIBUTIONZONE


XIX


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Table 12: DESCRIPTIONS OF PROPOSED BRANCH FROM MSANGANI JUNCTION NODE TO Up12 JUNCTION NODE


ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant


lossFrictionFactor



Junc msangani 0 115.79 315.53 199.74 0

Pipe 80 600 140 618.47 2.19 5.59 0.014

Junc Up12 6174.14 140.6 281 140.4 0

PROPOS

350

Figure 11: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM MSANGANI JUNCTION NODE TO Up12 JUNCTION NODE


XX


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Table 13: DESCRIPTIONS OF PROPOSED BRANCH FROM KIDIMU JUNCTION NODE TO PANGANI DISTRIBUTION ZONE


ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant


lossFrictionFactor



Junc kidimu 0 122.04 301.95 179.91 0

Pipe 79 600 140 315.91 1.12 1.61 0.015

Junc Pangani 1992.49 180 298.74 118.74 315.91

P

350

Figure 12: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM KIDIMU JUNCTION NODE TO PANGANI DISTRIBUTIONZONE


XXI


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Table 14: DESCRIPTIONS OF PROPOSED BRANCH FROM KIVUKONI JUNCTION NODE TO MAGOE DISTRIBUTION ZONE


ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant


lossFrictionFactor



Junc kivukoni 0 127.15 295.78 168.63 0

Pipe 77 600 140 91.08 0.32 0.16 0.018

Junc Magoe 4527.69 180 295.05 115.05 91.08

P

350

Figure 13: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM KIVUKONI JUNCTION NODE TO MAGOE DISTRIBUTIONZONE


XXII


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Table 15: DESCRIPTIONS OF PROPOSED BRANCH FROM KIVUKONI JUNCTION NODE TO Up21 JUNCTION NODE


ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant


lossFrictionFactor



Junc kivukoni 0 127.15 295.78 168.63 0

Pipe 81 600 140 1279.14 4.52 21.48 0.012

Junc Up21 4001.25 175 209.83 34.83 0

PR

350

Figure 14: LONGITUDINAL SECTION OF PROPOSED BRANCH FROM KIVUKONI JUNCTION NODE TO Up21 JUNCTION NODE


XXIII


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Table 16: DESCRIPTIONS OF EXISTING 600mm IN DIAMETER TRANSMISSION MAIN FROM UPPER RUVU TREATMENT PLANTTO KIMARA RESERVOIR


ReducedLevel

Head PressureBase

DemandDiameter

RoughnessConstant


lossFrictionFactor



Junc UpperRv 0 44.64 44.64 0 #N/A

Pump 84 #N/A 0 1880.41 0 -319.82 0Junc Up1 1140.18 34.57 364.46 329.89 0

Pipe 21 600 140 671.96 2.38 6.52 0.014

Junc Up2 2500.33 69.46 355.59 286.13 0

Pipe 22 600 140 671.96 2.38 6.52 0.014

Junc Up3 3618.36 81.65 348.3 266.65 0

Pipe 23 600 140 671.96 2.38 6.52 0.014

Junc Up4 6618.36 86.21 328.74 242.53 0

Pipe 24 600 140 671.96 2.38 6.52 0.014

Junc Up5 8318.36 100 317.66 217.66 0

Pipe 25 600 140 671.96 2.38 6.52 0.014

Junc Up6 9652.53 100.89 308.96 208.07 0

Pipe 26 600 140 455.31 1.61 3.17 0.014

Junc Up7 11932.88 114.31 301.73 187.42 0Pipe 27 600 140 455.31 1.61 3.17 0.014

Junc Up8 12541.16 120.37 299.8 179.43 0

Pipe 28 600 140 455.31 1.61 3.17 0.014

Junc Up9 13395.56 108.07 297.09 189.02 0

Pipe 29 600 140 455.31 1.61 3.17 0.014

Junc Up10 14415.36 108.07 297.09 189.02 0

Pipe 30 600 140 455.31 1.61 3.17 0.014

Junc Up11 15967.78 118.04 288.93 170.89 0

Pipe 31 600 140 455.31 1.61 3.17 0.014

Junc Up12 18467.78 140.6 281 140.4 0

Pipe 32 0 600 140 500.48 1.77 3.78 0.014

Junc Up13 21283.81 150.54 270.36 119.82

Pipe 33 600 140 500.48 1.77 3.78 0.014Junc Up14 23976.39 119.59 260.19 140.6 0

Pipe 34 600 140 500.48 1.77 3.78 0.014

Junc Up15 25685.19 119.59 260.19 140.6 0

Pipe 35 600 140 500.48 1.77 3.78 0.014

Junc Up16 27880.64 119.59 260.19 140.6 0

Pipe 36 600 140 500.48 1.77 3.78 0.014


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8/14/2019 IMPROVEMENT OF DAR-ES-SALAAM WATER SYSTEM MANAGEMENT THROUGH ISOLATED LOCALISED DIST

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