Improving water distribution network performance: A comparative analysis

Transcription

1 PENCIL Publication of Physical Sciences and Engineering Vol. 1(2):21-33 ISSN: (c)2015 PENCIL Academic Press CIVIL ENGINEERING Research Improving water distribution network performance: A comparative analysis Terry Henshaw and Ify L. Nwaogazie* Authors' Affiliation Department of Civil and Environmental Engineering, University of Port Harcourt, Nigeria. *Corresponding author. [email protected], [email protected]. Accepted: 20 th March, Published: 1 st April, ABSTRACT Three computer software for simulating water distribution network systems are demonstrated using the failed water distribution network of Choba Park, University of Port Harcourt (Uniport). Two networks are modeled as network 1 and network 2. Network 1 is a theoretical problem solved using WASDIM software based on the Hardy Cross method; WASDIMPRO software based on the Hardy Cross method and EPANET- 2 based on the gradient method. Network 2 is a model of Choba Park (Uniport) which demonstrates two options and five cases. Results from network 1 are compared on the basis of statistical method of test of significance and the law of conservation of energy. For network 1, a comparison of WASDIM and WASDIMPRO based on a 5% level of significance showed an estimated t-value of , which is greater than the critical t-value of 2.78, indicating that there is no significant difference between them. When WASDIM and EPANET 2 were compared based on a 5% level of significance, an estimated t-value of which is greater than the critical t-value of 2.78 shows a significant difference between them. Results from network 1 shows that the gradient method is more efficient than the Hardy Cross method. EPANET-2 achieves 0% error in 5 iterations, while WASDIM shows a very slow convergence achieving 11% error after 7 iterations and 0.05% error after 1000 iterations. The Model of the existing Choba network (option 2, case 2) shows that 15 m OHT will be sufficient to improve the water distribution network and it will take 11 h for the tank to get empty. Including water demand pattern in the design (option2, case3) improves the time for water to empty from 11 to 15 h. The OHT when positioned at the highest point in Choba and modeled as option 1, case 1 shows that 10 m OHT was sufficient and would take 11 h for water to empty. By including water demand pattern, option 1, case 2 took 15 h for the OHT to get empty. The Result for network 2 shows that the reason for the failed Choba network is as a result of the insufficient over head tank (OHT) height. It also gives the reason for the failure of the water distribution network models (WASDIM, WASDIMPRO) based on the Hardy Cross principles and further shows the gradient method as a more efficient method to be used for design of water distribution network. Key words: Computer software, WASDIM, WASDIMPRO, EPANET-2, water distribution network Analysis, test of significance, Choba - Uniport.

2 22. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) INTRODUCTION Increasing complexities associated with water distribution systems necessitated precise estimation of flows and pressures in various parts of the system. Solution of single pipe flow problem was no longer adequate. uest for methods that analyze (solve for flows and pressures) for entire water distribution network gave birth to the topic water distribution network analysis or pipe network analysis. The analysis of pipe networks has long been one of the most computationally complex problems which hydraulic engineers have to contend with. The basic hydraulic equations describing the phenomena are nonlinear algebraic equations which cannot be solved directly. Therefore all current numerical methods of solution are iterative, that is, they start with an assumed, approximate solution that is improved. These equations are usually written in terms of the unknown flow rates in the pipes, often referred to as LOOP equations. Alternatively, they are expressed in terms of unknown heads at unctions throughout the pipe system (node equations). The most commonly used solution methods are: Hardy Cross, Newton-Ralphson and Linear theory. These algorithms and techniques which are currently in use are employed in proprietary and commercial software. A considerable amount of published materials dealing with pipe network analyses are available in literature, all of which cannot be cited herein. However, some principal contributions of historical interest will be cited. Hardy Cross (1936) authored the original and classic work titled Analysis of Flow in Networks of Conduits or Conductors. In this study, only Closed Loop Networks are considered with no pumps, and a method for solving the loop equations based on adusting flow rates to individually balance each of the energy equations is described. Hardy Cross also described a second method for solving the node equations by adusting the head at each node so that the continuity equation is balanced. A number of subsequent works have appeared which further describe these methods or computer programs utilizing these methods (Fietz, 1972; Chenoweth and Crawford, 1974; Jeppson, 1977). Because the head adustments are computed independent of each other, 'Convergence' problems often arises in using the Hardy Cross method. Subsequent efforts are needed following Hardy Cross concentrated on developing methods to improve convergence. McPherson and Prasad (1965) presented the method of equalizing storage. An empirical formula based upon assumptions such as proportional loading is used in the analysis. The validity of this formula has also been questioned by Adam (1961). Watanatada (1973) presents a computer-based automatic design method which, given a network configuration, will simultaneously compute the pipe sizes and pumping capacities that minimize the total cost, while satisfying the demand requirements. Also, Martins and Peters (1972) introduced the Newton-Raphson iteration method to solve water distribution system problems. This method had much improved Convergence characteristics and forms the basis for more general applications (Jeppson, 1977). Works of Williams (1973) also discussed in details on the enhancement of convergence of pipe network analysis. In recent times, lots of works have been done in the use of EPANET- 2 to improve water distribution networks, but a comparison to quantify the actual improvement EPANET-2 offers in the improvement over the existing design is lacking in literature. The study of Fabunmi (2010) demonstrates the use of EPANET-2 to provide effective and reliable water distribution pipeline network for University of Agriculture, Abeokuta (UNAAB) campus. Also, a study by Ademiran and Oyelowo (2013) demonstrate the use of EPANET-2 to improve existing water distribution networks in the University of Lagos (UNILAG). However, the water distribution network in Choba Park is inefficient and needs to be improved with better options, so this gives the opportunity to compare and evaluate the best method of water distribution analysis. A selection of references considered relevant to this work as it concerns hydraulics of water distribution networks are Heafley and Lawson (1975), Lam and Wolia (1972), Mays (1996;2001), Vance (1979), Shamie (1974) and Wood (1981). NETWORK SIMULATION Conservation laws The distribution of flows through a network under a certain loading pattern must satisfy the conservations of mass and energy. For incompressible fluids, the conservation of mass is given as: in Where and in out respectively, and at the node. ext (1) out are the pipe flows in and out of the node, ext is the external demand or supply

3 23. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) For each primary loop, the conservation energy is the sum of energy or head losses, h L, minus the energy gains due to pumps, H pumps around the loop must be equal to zero: h Li Ip H kjp pump, k 0 (2) Where: h Li = Headloss in the pipe connecting nodes i and ; I p = Set of pipes in loop, p; k = Number of pumps in loop, p; Jp = Set of pumps in loop, p; and H pump, k = Energy added by pump k contained in the loop. Study area The study area is the Choba Park premises of the University of Port Harcourt (Uniport for short, see Figure 1a). The University has three campuses within the radius of 1.2 km namely Choba park, Abua park and Delta park. Each campus has an isolated water distribution network. However, Choba park has a perimeter of 2,500 m, a land area of 121 acres and houses four large blocks of hostels, facilities of Engineering, Education, Agricultural science and business centres that include banks, canteens and photocopying outlets. The perimeter of Choba is bounded by five coordinates which makes it a polygon of five sides. Any of the five coordinates such as N, E is sufficient to google the map of the study area. The existing water distribution network of Choba park is shown in Figure 1b with indications of the existing Over Head Tank (OHT) position. Proect requirement and study plan The maor requirement of this study is to analyze and report reasons for the failure of Choba water distribution network, design working options and recommend the best option which would replace or improve the existing network. Achieving this work involved field activities of testing pressure drops at different points of the existing network and carrying out a detailed survey to pinpoint the lowest and highest points. Field works were complimented with design simulators/methods which gave the opportunity to select the best simulator for designing a water distribution network. MATERIALS AND METHODS Hardy-Cross method The energy equation for each loop in a water distribution system must be written to take into account the direction of flow according to Cross (1936) as in Equation (3): n n1 p, nk p, i, K 0 (3) Where: K p i,, = coefficient for pipe connecting nodes i and ; n = 2 for Darcy-Weisbach Equation; and n i, = direction of flow. The assumed flows, however, may not satisfy the energy requirement given in Equation (3). Therefore, the correction, is made to all pipes in a particular i, loop, p. To compute, Equation (4) is thus, presented: p K nk p, p, n n1...(4) Note that pipes with flows in the clockwise direction n have positive headloss term while it is of K p, negative value for flows in a counter clockwise direction. The Hardy-Cross basically determines the for each loop separately. Then the flow for each pipe is corrected using Equation (5): new old P (5) Gradient method pmp The method is used to solve the flow continuity and headloss equations that characterize the hydraulic state of the pipe network at a given point in time and can be termed a hybrid node-loop approach. Todini and Pilati (1987) and Salgado et al. (1988) chose to call it the "Gradient Method". Similar approaches have been described by Hamam and Brameller (1971) (the "Hybrid Method) 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 p

4 24. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) a b Figure 1a. Choba Park Uniport, the study area; (b) Existing water distribution network. Source a new trial solution for nodal heads have been found. Because Todini's approach is simpler, it was chosen for use in the EPANET software. The Gradient solution method begins with an initial estimate of flow in each pipe that may not necessarily satisfy flow continuity. At each iteration of the method, new nodal heads are found by solving the matrix Equation (6) (Luwis, 2000): AH = F (6) Where A = an (NxN) Jacobian matrix, H = an (Nxl) vector of unknown nodal heads, and F = an (Nxl) vector of right hand side terms. The diagonal elements of the Jacobian matrix are: A i P i (7) Where P i is the inverse derivative of the head loss in the link between nodes, i and with respect to flow. For pipes: 1 Pi (8) n 1 nr 2m i i After new heads are computed by solving Equation (6), new flows are found from Equation (9) (Luwis, 2000): i( NEW ) i( OLD) yi pi Hi H (9) If the sum of absolute flow changes relative to the total flow larger than a tolerance (e.g., 0.001), then Equations (6) and (8) are solved once again. The flow update formula (Equation 9) always results in flow continuity around each node after the first iteration. Computer Simulator With the stress involved in manual computations; computer simulators are developed to make work easier, faster and more efficient. Works of Chan (1972), Dillingham (1967), Donachie (1974), Robinson (1975), Nwaogazie and Okoye (1994), and Lewis (2000) have demonstrated different computer approaches to water distribution network analysis. WASDIM, WASDIMPRO and EPANET simulators are discussed in subsequent sections WASDIM Simulator The WASDIM program is a computer software written in FORTRAN IV, for water distribution network analysis (Nwaogazie and Okoye, 1994). This program is based on the conventional approaches of Darcy-Weisbach s headloss computation and Von Karman s friction factor

5 25. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) for the turbulent flows. The model is a relaxation form of the Hardy-Cross type permitting accurate computation of the head losses and design flows in pipes of various diameters. It has the advantage of solving both closed and open loop networks. Works of Anicho (2008) and Chattel (1995) have used the WASDIM simulator in analyzing water distribution networks. WASDIMPRO Simulator The WASDIMPRO program is a computer software written in visual basic.net, for water distribution network analysis for the purpose of this study. The only difference between the WASDIM and WASDIMPRO software is that of the programming language. Visual Basic.net is a modern programming language which is also an obect-oriented program (OOP) and event driven program. More recent releases of Visual Basic continue to move it closer to a true obect oriented program. In event driven model, programs are no longer procedural; they do not follow a sequential logic. The design programmer does not determine the sequence of execution. Instead the user can press keys and events occur, which triggers the basic procedures that have been written. EPANET- 2 Simulator EPANET is a computer program that performs extended period simulation of hydraulic and water quality behavior within pressurized pipe networks. A network consists of pipes, nodes (pipe unctions), pumps, valves and storage tanks or reservoirs. EPANET tracks the flow of water in each pipe, the pressure at each node, the height of water in each tank, and the concentration of a chemical species throughout the network during a simulation period, comprised of multiple time steps. In addition to chemical species, water age and source tracing can also be simulated. EPANET is designed to be a research tool for improving our understanding of the movement and fate of drinking water constituents within distribution systems. It can be used for many different kinds of applications in distribution systems analysis. Sampling program design, hydraulic model calibration, chlorine residual analysis, and consumer exposure assessment are some- examples. EPANET can help assess alternative management strategies for improving water quality throughout a system. Test of significant (t test) Test of significance is a statistical tool used to give decisions to an argument. The procedure involves selecting a % of significance which is used to test the argument. The final decision of any argument is tied to the % of significance used. For example, if a 5% level of significance is chosen in designing a test of significance, then there are about 5 chances in 100 that you will reect the hypothesis when it should be accepted, that is, we are about 95% confident that we have made the right decision (Nwaogazie, 2011). The t-statistic was adopted for this work because of the number of data points, N=5. Using statistical t-test for comparison of significant difference with a null (H 0) and alternative (H 1) hypotheses as stated: H o : all d = 0; there is no significant difference between the two methods of solving water distribution network; and H 1 : all d 0; there is a significant difference between the two methods of solving water Distribution network. This is a case of two tailed test by reason of the alternative hypothesis. For the null hypothesis to be accepted and alternative hypothesis reected, the estimated t-value from the data set (simulated results) has to be less than the critical t value read off from the percentile values of t p for distribution with a given degree of freedom (ν). It is the reverse if the null hypothesis is reected and the alternative hypothesis is accepted. Description of networks The first network (Network 1) consist of a single loop which is a theoretical example problem from Simon (1981) to establish significant difference between the new and existing method of solving water distribution networks. The second network which is that of Choba Park (Network 2) consists of 4 maor loops enclosing Choba park, which shows a failed water network. Network 1 Network 1 is solved with WASDIM, WASDIMPRO and EPANET-2 for the purpose of comparison. The network diagram for network 1 is shown in Figure 2 and input data in Table 1.

6 26. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) Figure 2. Pipe distribution for Network 1. Table 1. Input data for Network 1. S/N Pipe- ID Length(ft) Diameter(in) Roughness Figure 3. Flow diagram of EPARNET-2 Print out of Network 2 (OHT positioned at highest point).

7 27. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) Table 2. Input data for Network 2. S/N Pipe ID Length( m) Diameter (m) Roughness Network 2 Network 2 was solved with EPANET- 2 using Hazen William s formula. It solved the network as options 1 and 2. Option 1 solved the network with the over head tank (OHT) situated at the lowest point of the area (see Map in Figure 1b) and option 2 solved the network with the OHT situated at the highest point of the area (Figure 3). The input data for this network were the pipe lengths, diameters, elevations and water demand. The pipe types were selected in accordance with the standards and this resulted in using upvc pipes except in areas on high vibrations. The demand of water was estimated based on the World Health Organization demand (World Bank e- Library, WBL, 2015) estimates and proected for a design period of 20 years. Overtime, it has been observed that with a geometric increase in population of 3% yearly, a 20 year design period, population will increase by 55%, and in the same way the estimated water demand will increase. It was on this note that the estimated water demand for Choba was proected. The demand pattern for the different nodes were programmed and uploaded to the program. Offices will not open till 8 am and as such, EPANET-2 is programmed to start delivering water based on demand to such nodes. Table 2 gives the summary of input data. RESULTS AND DISCUSSION Results from network 1 Based on the analysis, the detailed results are presented in Table 3, and they comprise of the head or pressure at each nodal unction. Statistical comparison of results The first significant test is between WASDIM and WASDIMPRO after 7 iterations. From the simulated results (Table 4) the standard error, S d and the t-value are obtained respectively and thus, the test of significance is actualized. The details of the calculations are as presented: From the Table 2, d= Col.3 Col.4; F= dmean of d i; N = No di of samples = 5; Mean of d (dmean) = = 5.333; N and s 2 d = (d i dmean ) 2 = ; s d = ; t = dmean s d N N 1 = = The number of degree of freedom (df), ν = N-1 = 4. By reason of the alternative hypothesis, H 1 we adopt a two tail test. The critical value of t or t % sigf, df, for 5%

8 28. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) Table 3. Results showing Pressure head for the three simulators. Node number WASDIMPRO WASDIM EPANET Table 4. T-test analysis between pressure heads for WASDIM and WASDIMPRO. S/N (1) Node No. (2) WASDIMPRO (3) WASDIM (4) di(5) F^2(6) Table 5. t-test analysis between WASDIM and EPANET-2. N/S Node No. (2) EPANET 2 (3) WASDIM (4) di(5) F^2(6) significance is t 97.5, 4= Given that t <t 97.5, 4, the null hypothesis is accepted. Next is the second significant test between the WASDIM and EPANET- 2 after 7 iterations (Table 5) and the following calculations for standard error, S p, and t- value to facilitate t-test analysis: From the Table 3; d i= Col.3 Col.4; F= d i-mean of d (dmean); N = number of sample = 5; and Mean of d di (dmean) = = ; s N d 2 = (d 1 dmean ) 2 = N ; s d = ; t = dmean s d N = = The number of degree of freedom (df), ν = N-1 = = 4 A two-tail test is adopted by reason of the alternative hypothesis, H 1. From standard textbook on statistics (Nwaogazie, 2011) the value of t % sigf, df at 5% significance is read off as t 97.5,4 = Given that t > t 97.5,4 the null hypothesis is reected. To further appreciate the computational efficiency of WASDIM and EPANET-2, we apply the principle of energy conservation which states that the sum of all incoming flows must be equal to the sum of all out going flows at a given node after a number of iterations. Considering node 2 we performed the following calculations: i). For WASDIM after 7 iterations incoming flow = ft 3 /s outgoing flow = ( ) = ft 3 /s incoming flow outgoing flow % Error = 11% ii). For the EPANET -2 after 5 iterations incoming flow = 19.0 ft 3 /s outgoing flow = ( ) = 19 ft 3 /s incoming flow = outgoing flow % Error = 0% From the results of the foregoing energy balance computations at Node 2, it is evident that after 7 iterations, WASDIM records an error of 11%, thus, iteration continues, while at 5 th iteration, EPANET

9 % error 29. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) Number of iteration versus % error for WASDIM simulator No. of iterations No. of iterations iteration versus error for for WASDIM simulator Figure 4. Number of Iteration versus %Error for WASDIM Simulator. records an error of 0% and iteration is terminated. This is basically so because of the methods the softwares are based on. WASDIM is based on Hardy Cross method which requires assumption of correct head values and this turns out to lower its accuracy, while EPANET- 2 is based on the gradient method which solves each node as an equation using Matrix techniques. Discussion of results for network 1 The test of significance between WASDIM and WASDIMPro for which a 5% level of significance shows that 95% confidence was selected, indicated an acceptance of the null hypothesis because the calculated t- value of was less than the critical t-value of This result shows there is no significant difference between the WASDIM and WASDIMPro softwares which agrees with the fact that the WASDIMPro like the WASDIM software uses Hardy Cross method of analysis. The test of significance between the WASDIM and EPANET for which a 5% level of significance was also used indicated a reection of the null hypothesis because the calculated t-value of is greater than the critical t-value of This reection shows a significant difference between the two software but does not disclose the best of them. The estimated error after each iteration process gives the final udgment of which software is better. EPANET software presents itself to be more efficient as the estimated error after 5 iterations is 0%, while WASDIM shows 11% error after 11 iterations and continues to reduce until the accepted minimum of 0.05% after 1000 iterations (Figure 4). The WASDIM software shows a very slow convergence which is one of the maor issues with the Hardy Cross method as discussed earlier. Results for network 2 Based on the analysis, the detailed results are as presented in Figures 5 and 6 and Tables 6 and 7, and they comprise of the head or pressure at each nodal unction with time. The time is varied for 12 h to observe the behavior of the network if put to run. A summary of the results gotten for the two options and 5 cases each are shown in Table 7. Discussion of results for network 2 Network 2 is the Choba Park and is represented in Figures 1b and 3. Figure 1b shows the failed Choba water distribution network and Figure 3 shows the network of Choba with Over Head Tank (OHT) positioned at the highest point. EPANET-2 was used to model the existing Choba distribution network without a water demand use pattern and results were summarized as Option 2, case1. The results show a negative pressure in the distribution system which means the 10 m height existing OHT was insufficient to supply water effectively to the distribution of pipes. This was the existing problem as water was unable to get to distances beyond 15 m from the OHT position. EPANET-2 was used to remodel the system with the OHT height increased to 15 m, but maintaining the existing position without a water

10 Pressure (m) Pressure (m) Pressure (m) PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) Time (h) Figure 5. EPANET-2 output printout of pressure distribution at Note 3 for Network Time (h) Figure 6. EPANET-2 output printout of pressure distribution at Note 15 for Network 2. demand use pattern and this was presented as option 2, case 2. The results showed that 15 m OHT height would be sufficient to effectively distribute water to all parts of the network with an 11 h duration before the tank is empty. Option 2, case 2 was remodeled by including a water demand use pattern and the result presented as Option 2, case 3. Results show an improvement in the duration for tank to empty; it improves from 11 to 15 h. The survey plan of Choba park shows the existing position of the OHT as the lowest point. Epanet-2 remodels the system using the new position of the OHT as the highest point in Choba Park. Option 1, case 1 presents the results of modeling Choba distribution network with OHT at the highest point with no water demand use pattern included. Results show that a 10 m OHT is sufficient with 11 h duration for the Tank to empty. EPANET-2 is used to remodel the distribution network with the OHT at the highest point with a water demand use pattern included and results are presented as option 1, case 2. The results show a 10 m OHT height with 15 h duration for tank to be empty. Most studies in literature have used EPANET-2 to model only correction of failed water distribution

11 31. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) Table 6. EPANET-2 output print out for Network 2. Node ID Demand LPS Head M Pressure M Junc Junc 8 O Junc Junc Junc Junc Junc Junc Junc Junc Junc Junc Resvr Tank Table 7. Summary of results from Network 2. S/N Item Description OHT (m) Filling time (h) Time to empty (h) Size of OHT (m) Pump characteristics Head (m) Flow (m 3 /s) 1 Option 1, case 1 Overhead tank is placed at a high point without a demand pattern D=6m H=3m Option 1, case 2 Overhead tank is placed at a high point with a demand pattern D=6m H=3m Option 2, case 1 Overhead tank is placed at a low point without a demand pattern 10 NEGATIVE PRESSURE IN SYSTEM 4 Option 2, case 2 Overhead tank is placed at a low point without a demand pattern D=6m H=3m Option 2, case 3 Overhead tank is placed at a low point with a demand pattern D=6m H=3m networks and this has failed to demonstrate its capabilities in tracing the exact faults in network failures. In this study, EPANET-2 has been used to model the failed water distribution network system of Choba and the reason for its failure is attributed to insufficient OHT height and positioning of OHT on the lowest point. It is always important to search the highest spot for OHT in designing a water distribution network as this is one of the factors which always results in the least cost design (Watanatada, 1973). In most cases, Engineers try to give excuses for locating OHT at low point, one of the popular excuses is that of savings on drilling cost when ground water serves as a source of water supply, but Garg (1994) in his research has put it to us that the water table is a reflection of the earth surface, which indirectly means that, the level at which a driller meets water on the hill top with reference to the earth surface is relatively the same level the driller will meet water on

12 32. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) the low land with reference to the earth surface and this he says is a case of 70 in 100. EPANET-2 print-out of pressure distributions at Nodes 3 and 15 (See Figure 3 on Network diagram) are plotted as shown in Figures 5 and 6, respectively. The abscissa indicates the time frame to fill the OHT and equally empties it at the point of interest. The best network for Choba park is Option 1, case 2 (OHT height of 10m at the highest point) and this would save up to 5 m of the OHT height when compared with option 2, case 3 which is the perfect working network if the OHT is place on the lowest point of Choba park (OHT height of 15 m at lowest point). CONCLUSION The results presented in this study show the following conclusions: 1. WASDIM and WASDIMPro are not significantly different because they are operated with the same principle (Hardy-Cross method) 2. WASDIM and EPANET-2 can be used to model simple networks with relatively flat terrains but WASDIM has a very slow rate of convergence compared to EPANET. 3. The water distribution Network of Choba is a failure because of the insufficient OHT height of 10 m provided and positioned on the lowest point in Choba park. 4. EPANET-2 can handle time dependent analysis of water distribution network showing important features like time for water to fill and empty the over head tank (OHT}. 5. The best water distribution network design for Choba would be to position the OHT on the highest point in Choba park and provide a 10 m height for the OHT. REFERENCES Adam, R. W. (1961). Distribution Analysis by Electronic Computer, Institution of Engineers, London, pp Adenrian, A. E., and Oyelowo, M. A. (2013). An EPANET analysis of water distribution network of the University of Lagos, Nigeria. J. Eng. Res., 18(2). Simon, L. A. (1981). Practical Hydraulics, New York: John Wiley & Sons, Inc., pp Anicho, C. 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13 33. PENCIL Pub. Phys. Sci. Eng. Henshaw and Nwaogazie (2015) Network Solutions, ASCE, 99(HY7): Wood, D. J., and Rayes, A. M. (1981). Reliability of Algorithms for Pipe Network Analysis, ASCE, 107(HY10): World Bank e-library, WBL (2015). Water demand from World health organization, (WHO). Accessed on the