Published May 30, 2022 | Version CC BY-NC-ND 4.0
Journal article Open

Simulation of Maralal Water Flow Distribution Network using EPANET Model in Samburu County, Kenya

Creators

  • 1. Managing Director, Maralal Water and Sanitation Co. Ltd., Maralal, Kenya.
  • 2. Deputy Vice-Chancellor (Planning, Partnerships, Research and Innovation), Kibabii University, Kenya.
  • 3. Senior Lecturer, Department of Civil & Environmental Engineering, Egerton University, Njoro, Kenya.

Contributors

Contact person:

  • 1. Managing Director, Maralal Water and Sanitation Co. Ltd., Maralal, Kenya.

Description

Abstract: Majority of people in developing countries do not have access to clean and potable water due to inadequate supply and distribution system challenges. While the rationale of water distribution systems is to deliver to each consumer safe drinking water that is adequate in quality and quantity at an acceptable delivery pressure, this has been a major drawback for many distribution networks. In addition, the design spans of many urban and peri-urban water distribution networks managed by the Water Service Providers (WSPs) are being exceeded without augmentation. Maralal water distribution network is one of such distribution systems with poor system performance that has been the main contributor of high Non-Revenue Water (NRW). This coupled with significant mismatch between water supply and water demand makes Maralal Water and Sanitation Company to resort to hedging/intermittent flow leading to water rationing. One of the ways of predicting the flow dynamics within the distribution system is the use of hydraulic simulation models. This study therefore applied the Environmental Protection Agency Network (EPANET) simulation model to predict the dynamic state of the hydraulics and water quality behaviour for Maralal water distribution system operating over an extended period of time. The general objective was to simulate water flow for Maralal water distribution system using the EPANET model for efficient planning, operation and maintenance protocol for the system. The study focused on the steady state (static), extended period (dynamic), and water quality analyses. The model calibration results from four statistical criteria; Nash-Sutcliffe model efficiency coefficient (E), Sum of Squares Error (SSE), Percentage Bias (PB) and Root Mean Square Error (RMSS) of 0.99, 0.01, 0.05 and 0.03 respectively show that the model performed within acceptable range of the selected statistical criteria. The findings of this study were: The roughness coefficients for a water distribution network that contribute to erratic pressure-dependent flows can be determined at any time using the regression analysis of the measured head loss and flow rate, EPANET model can predict the steady and dynamic hydraulic parameters for the current and future water distribution systems and Chlorine decay with respect to pipe diameter impacts on hydraulic performance and quality of water in a distribution network. The results from this study would assist water service providers and managers to make informed decisions in relation to water distribution system planning, operation and maintenance to achieve the desired current and future water demands.

Notes

Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved.

Files

F25330510622.pdf

Files (1.0 MB)

Name Size Download all
md5:5c8f8cae6db39330809d5604dd1b4c63
1.0 MB Preview Download

Additional details

Related works

Is cited by
Journal article: 2319-6378 (ISSN)

References

  • Ababu T., Tiruneh, Tesfamariam, Y., Debessai, Gabriel, C., Bwembya, and Stanley, J. N. (2019). A Mathematical Model for Variable Chlorine Decay Rates in Water Distribution Systems. Modelling and Simulation in Engineering, 1-11.
  • Abubakar, A. S. and Sagar, N. L. (2013). Design of NDA Water Distribution Network Using EPANET. International Journal of Emerging Science and Engineering, (IJESE) ISSN: 1 (9), 2319–6378.
  • Adeleke, A. E. and Olawale, S. O. A. (2013). Computer Analysis of Flow in the Pipe Network. Transnational Journal of Science and Technology, 3(2),
  • Adeniran, A. E. and Oyelowo, M. A (2013). An EPANET analysis of water distribution network of the University of Lagos, Nigeria. Journal of Engineering Research. 18(2).
  • Adeniran, A. E. and Bamiro, O. A. (2010). A system dynamics strategic planning model for a municipal water supply scheme, Proc. 28th International Conference of the System Dynamics Society, Seoul, Korea, 2529 July, 2010.
  • Alemtsehay, G.S. and Tiku, T.T. (2017). Integration of Hydraulic and Water Quality Modelling in Distribution Networks: EPANET-PMX. Water Resources Management, 31, 4485-4503.
  • Alkali, A.N., Yadima, S.G., Usman, B., Ibrahim, U.A. and Lawan, A.G. (2017). Design of a water supply distribution network using EPANET 2.0: A case study of Maiduguri zone 3, Nigeria. Arid zone journal of Engineering, Technology and Environment, 13(3): 347-355.
  • Anisha, G., Kumar and A., Ashok, J.K.P.S. (2016). Analysis and design of water distribution network using EPANET for Chirala Municipality. International Journal of Engineering and Applied Sciences, 3(4), 2394-366.
  • Araceli, M.C., David, S., Ana, I. and Luis, G. (2020). Optimization of the Design of Water Distribution Systems for Variable Pumping Flow Rates, Water, 12(359), 1-20.
  • Fabunmi, A. O. (2010). Design of Improved Water Distribution Network for UNAAB Campus, Unpublished B.Sc. Dissertation, Federal University of Agriculture, Abeokuta, Nigeria.
  • Feinauer, L., Russell, K. and Broadwater, R. (2008). Graph trace analysis and generic algorithms for interdependent reconfigurable system design and control. Naval Engineers Journal, 120.
  • Guidolin, M., Burovskiy, P., Kapelan, Z. and Savid, D. (2010). CWSNET: An ObjectOriented Toolkit for Water Distribution Analysis: Proceedings of American Society of Civil Engineers Water Distribution System Simulation, 2010.
  • Henseler, J., Ringle, C. and Sinkovics, R. (2009). The use of Partial Least Squares path Modeling in international Marketing. Advance in International Marketing, 20, 277-319.
  • Ivar, A. and Anatoli, V. (2015). Different approaches for calibration of an operational water distribution system containing old pipe pipes. Procedia engineering, 119(2015), 526-534.
  • Jagrat, J. and Hari, K. (2019). Design and analysis of a smart water distribution network in Jaipur, Rajasthan. International Journal of Research and Technology, 8, 2278-0181.
  • James, R. N. (2009). Comparison and simulation of a water distribution network in EPANET and a New generic graph trace analysis based model. A Thesis submitted to the Virginia Polytechnic Institute and State University in partial fulfilment for the requirements for the degree in Master of Science in Environmental Engineering.
  • KNBS. (2019). Kenya Population and Housing Census. Vol II. Distribution of Population by administrative units.
  • Manoj, N., Ramesh, B. and Santhosh, A.P. (2018). Water distribution network design using EPANET. A case study of Saveetha University. International Journal of pure and Applied Mathematics, 119 (17) 1165-1172.
  • Mays, L.W. (2004). Water Supply Systems Security. McGraw-Hill, New York, NY.
  • Muranho, J., Ferreira, A., Sousa, J. and Marques, A. S. (2014). Pressure-dependent Demand and Leakage Modelling with an EPANET Extension – WaterNetGen, Procedia Engineering, 89,632–639.
  • Naser, M. and Mohammad, R.J. (2014). Hydraulic Analysis of Water Supply Networks Using a Modified Hardy Cross Method. International Journal of Engineering, 27(9), 1331-1338. Water Supply and Distribution, Leicester Polytechnic, UK, September 8-10.
  • Nejjari, F., Puig, V., Perez, R., Quevedo, J., Cuguen, M.A., Sanz, G. and Mirats, J.M. (2014). Chlorine decay model calibration and comparison: Application to a real water network. Conference paper in Procedia Engineering, 70(2014), 1221-1230.
  • Roya, P.M., Mojtaba, A.M., Ali, A.E. and Mehdi, M. (2019). Calibration of water quality model for distribution networks using genetic algorithm, particle swarm optimization, and hybrid methods. www.elsevier.com/locate/mex.
  • Santhi, C., Arnold J. G., Williams, J. R., Dugas, W. A., Srinivasan, R. and Hauck, L. M. (2001). Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of American Water Resources Association, 37,1169-1188.
  • Sashikumar, N., Mohankumar, M.S. and Sridharan, K. (2003). Modelling an Intermittent Water Supply. In: Bizier, P and DeBarry, P. (Eds.) World Water Congress 2003, June 3–26, 2003, Philadelphia, Pennsylvania, USA. American Society of Civil Engineers, Washington, D.C.
  • Vasan, A. and Simonovic, S. P. (2010). Optimization of Water Distribution Network Design using Differential Evolution. Journal of Water Resources Planning and Management, 279287.
  • Viessman, W. and Hammer, M.J. (1998). Water supply and pollution control. Menlo Park, CA: Addisson Wesley.
  • Walski, T. (2017). Procedure for hydraulic model calibration. AWWA Journal, 109,6.
  • Walski, T. M., Chase, D.V., Savic, D.A., Grayman, W., Beckwith, S. and Koelle, E. (2003). Advanced Water Distribution Simulation and Management. Haestad Methods, Waterbury, CT.
  • Water Services Regulatory Board. (2009). Unaccounted for water. WASREB Impact report.
  • Zanfei, A., Menapace, A., Santopietro S. and Righetti, M. (2020). Calibration procedure for water distribution systems: Comparison among hydraulic models. Water 2020, 12, 1421.

Subjects

ISSN: 2319-6378 (Online)
https://portal.issn.org/resource/ISSN/2319-6378#
Retrieval Number: 100.1/ijese.F25330510622
https://www.ijese.org/portfolio-item/f25330510622/
Journal Website: www.ijese.org
https://www.ijese.org
Publisher: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
https://www.blueeyesintelligence.org