Abstract

This paper aims to quantify the subbasin’s potable water supply demand forecast from 2023 to 2050 under various scenarios of climate change and socioeconomic development. The variability of the climate and the resulting problems with urbanization threaten the availability of water resources, especially in less developed countries like Ethiopia. Thus, the main objective of this study is showing the necessary to determine the amount of water needed in advance, in order to comply with the availability of water resources within a specified future period under different scenarios. Our indicator-based approach used a multicriteria decision-making technique. Accordingly, several important variables were considered, including climatological, anthropological, demographic, socioeconomic, and economic variables, in addition to water engineering-related factors (e.g. Water losses). The method also considered a number of factors, such as unexpected and extreme temperature changes, and forecasting factors studied by the Ethiopian Ministry of Water and Energy. The projected population in the subbasin is estimated at 2.52 million, so the total projected water supply demand i.e., for domestic, non-domestic, industrial, commercial, public, and institutional is approximately 126.53 MCM/yr by 2050. Our results revealed how changes in both climatic and socioeconomic factors strongly influence future water resource system performance, and this will help the water services provider better prioritize the refurbishment of existing infrastructure and investment in new infrastructure, and more importantly, manage the subbasin effectively by introducing resilient adaptation options.

Keywords

Population, Forecast, Water demand, Domestic, Non-domestic, Ghba subbasin, Northern Ethiopia,

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References

  1. W.J. Cosgrove, D.P. Loucks, Water management: Current and future challenges and research directions. Water Resources Research, 51(6), (2015) 4823-4839. https://doi.org/10.1002/2014WR016869
  2. E.A. Donkor, T.A. Mazzuchi, R. Soyer, J. Alan Roberson, Urban water demand forecasting: review of methods and models. Journal of Water Resources Planning and Management, 140(2), (2014) 146-159. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000314
  3. M.G. Hiben, A.G. Awoke, A.A. Ashenafi, Assessment of Future Water Demand for Resilient Water Allocation under Socioeconomic and Climate Change Scenarios, a Case of Ghba Subbasin, Northern Ethiopia. Preprints. (2023). https://doi.org/10.20944/preprints202311.1247.v1
  4. X. Ma, X. Xue, A. González-Mejía, J. GarlandJ. Cashdollar, Sustainable water systems for the city of tomorrow-A conceptual framework. Sustainability, 7(9), (2015) 12071-12105. https://doi.org/10.3390/su70912071
  5. V.V. Goncharuk, Water as the Earth’s buffer and immune system. Journal of Chemistry. (2013) 472323. https://doi.org/10.1155/2013/472323
  6. A.C. Twort, D.D. Ratnayaka, M.J. Brandt, (2000). Water Supply. 5th Edition, Butterworth-Heinemann, Oxford, United Kingdom
  7. G. Quezada, A. Walton, A. Sharma, Risks and tensions in water industry innovation: Understanding adoption of decentralised water systems from a socio-technical transitions perspective. Journal of Cleaner Production, 113, (2016) 263-273. https://doi.org/10.1016/j.jclepro.2015.11.018
  8. U.S Panu, T.C. Sharma, Challenges in drought research: some perspectives and future directions. Hydrological Sciences Journal, 47(1), (2002) S19-S30. https://doi.org/10.1080/02626660209493019
  9. P.H. Gleick, Basic water requirements for human activities: meeting basic needs. Water International, 21(2), (1996) 83-92. https://doi.org/10.1080/02508069608686494
  10. X. Mo, S. Liu, Z. Lin, R. Guo, Regional crop yield, water consumption and water use efficiency and their responses to climate change in the North China Plain. Agriculture, Ecosystems & Environment, 134 (1-2) (2009) 67-78. https://doi.org/10.1016/j.agee.2009.05.017
  11. A.D. Mauro, A. Cominola, A. Castelletti, A.D. Nardo, Urban water consumption at multiple spatial and temporal scales. A review of existing datasets. Water, 13(1), (2021) 36. https://doi.org/10.3390/w13010036
  12. S. Shabani, A. Candelieri, F. Archetti, G. Naser, Gene expression programming coupled with unsupervised learning: a two-stage learning process in multi-scale, short-term water demand forecasts. Water, 10(2), (2018) 142. https://doi.org/10.3390/w10020142
  13. C. Pahl-Wostl, Transitions towards adaptive management of water facing climate and global change. Water Resources Management, 21, (2007) 49-62. https://doi.org/10.1007/s11269-006-9040-4
  14. A. Blanke, S. Rozelle, B. Lohmar, J. Wang, J. Huang, Water saving technology and saving water in China. Agricultural Water Management, 87(2), (2007) 139-150. https://doi.org/10.1016/j.agwat.2006.06.025
  15. I.G. Tejero, V.H.D. Zuazo, J.A.J. Bocanegra, J.L.M. Fernández, Improved water-use efficiency by deficit-irrigation programmes: Implications for saving water in citrus orchards. Scientia Horticulturae, 128(3), (2011) 274-282. https://doi.org/10.1016/j.scienta.2011.01.035
  16. M.G. Hiben, A.G. Awoke, A.A. Ashenafi, Estimation of Current Water Use over the Complex Topography of the Nile Basin Headwaters: The Case of Ghba Subbasin, Ethiopia. Advances in Civil Engineering, (2022) 7852100. https://doi.org/10.1155/2022/7852100
  17. R. Tabassum, M.H. Arsalan, N. Imam, Estimation of water demand for commercial units in Karachi City. FAST-NU Research Journal (FRJ), 2(1), (2016) 21-26.
  18. M. Arfanuzzaman, A.A. Rahman, Conservation. Sustainable water demand management in the face of rapid urbanization and ground water depletion for social–ecological resilience building. Global Ecology and Conservation, 10, (2017) 9-22. https://doi.org/10.1016/j.gecco.2017.01.005
  19. D.B. Brooks, An operational definition of water demand management. International Journal of Water Resources Development, 22(4), (2006) 521-528. https://doi.org/10.1080/07900620600779699
  20. S.K. Sharma, K. Vairavamoorthy, Urban water demand management: prospects and challenges for the developing countries. Water and Environment Journal Promoting Sustainable Solutions, 23(3), (2009) 210-218. https://doi.org/10.1111/j.1747-6593.2008.00134.x
  21. P.H. Gleick, Water in crisis: paths to sustainable water use. Ecological Applications, 8 (1998) 571-579. https://doi.org/10.1890/1051-0761(1998)008[0571:WICPTS]2.0.CO;2
  22. R. Connor, (2015) The United Nations world water development report 2015: water for a sustainable world. United Nations Educational, Scientific and Cultural Organization.
  23. L.A. House‐Peters H. Chang, Urban water demand modeling: Review of concepts, methods, and organizing principles. Water Resources Research, 47(5), (2011). https://doi.org/10.1029/2010WR009624
  24. J. Stańczyk, J. Kajewska-Szkudlarek, P. Lipiński, P. Rychlikowski, Improving short-term water demand forecasting using evolutionary algorithms. Scientific Reports, 12 (2022) 13522. https://doi.org/10.1038/s41598-022-17177-0
  25. M.G. Hiben, A.G. Awoke, A.A. Ashenafi, Estimation of rainfall and streamflow missing data under uncertainty for Nile basin headwaters: the case of Ghba catchments. Journal of Applied Water Engineering and Research, (2023) 1-15. https://doi.org/10.1080/23249676.2023.2230892
  26. M.G. Hiben, A.G. Awoke, A.A. Ashenafi, (2023). Assessment of Hydrological and Water management Models for Ghba Subbasin, Ethiopia. African Journal of Geography and Regional Planning, 10(1), 001-007.
  27. M.G. Hiben, A.G. Awoke, A.A. Ashenafi, Homogeneity and change point detection of hydroclimatic variables: A case study of the Ghba River Subbasin, Ethiopia. Journal of Geography and Cartography, 6(1), (2023) 1-19. https://doi.org/10.24294/jgc.v6i1.2010
  28. S. Rayner, D. Lach, H. Ingram, Weather forecasts are for wimps: why water resource managers do not use climate forecasts. Climatic Change, 69 (2005) 197-227. https://doi.org/10.1007/s10584-005-3148-z
  29. R.B. Billings, C.V. Jones, (2011) Forecasting urban water demand: American Water Works Association.
  30. K. Nova, AI-enabled water management systems: an analysis of system components and interdependencies for water conservation. Eigenpub Review of Science and Technology, 7(1), (2023) 105-124.
  31. S.L Zubaidi, S. Ortega-Martorell, H. Al-Bugharbee, I. Olier, K.S. Hashim, S.K. Gharghan, P. Kot, R. Al-Khaddar, Urban water demand prediction for a city that suffers from climate change and population growth: Gauteng province case study. Water, 12(7), (2020) 1885. https://doi.org/10.3390/w12071885
  32. A. Raihan, J.J. Pereira, R.A. Begum, R. Rasiah, The economic impact of water supply disruption from the Selangor River, Malaysia. Blue-Green Systems, 5(2), (2023) 102-120. https://doi.org/10.2166/bgs.2023.031
  33. D.E. Gorelick, D.F. Gold, T. Asefa, S. Svrdlin, H. Wang, N. Wanakule, P.M. Reed, G.W. Characklis, Water Supply Infrastructure Investments Require Adaptive Financial Assessment: Evaluation of Coupled Financial and Water Supply Dynamics. Journal of Water Resources Planning and Management, 149(3), (2023) 04022084. https://doi.org/10.1061/JWRMD5.WRENG-5863
  34. M. Oberascher, L. Schartner, R. Sitzenfrei, Optimisation of Small Hydropower Units in Water Distribution Systems by Demand Forecasting. Water, 15(22), (2023) 3998. https://doi.org/10.3390/w15223998
  35. X. Xia, B. Liu, R. Tian, Z. He, S. Han, K. Pan, J. Yang, Y. Zhang, An interval water demand prediction method to reduce uncertainty: A case study of Sichuan Province, China. Environmental Research, 238, (2023) 117143. https://doi.org/10.1016/j.envres.2023.117143
  36. R. Mäntysalo, K. Granqvist, O. Duman, M.N. Mladenović, From forecasts to scenarios in strategic city-regional land-use and transportation planning. Regional Studies, 57 (2023) 629-641. https://doi.org/10.1080/00343404.2022.2058699
  37. V. Sadovnichy, A. Akaev, I. Ilyin, S. Malkov, L. Grinin, Y. Sayamov, A. Korotayev, (2023) Introduction: Hoping for the Future. In Reconsidering the Limits to Growth: A Report to the Russian Association of the Club of Rome. Cham: Springer International Publishing, 1-14. https://doi.org/10.1007/978-3-031-34999-7_1
  38. D. Fister, J. Pérez-Aracil, C. Peláez-Rodríguez, J. Del Ser, S. Salcedo-Sanz Accurate long-term air temperature prediction with Machine Learning models and data reduction techniques. Applied Soft Computing, 136, (2023) 110118. https://doi.org/10.1016/j.asoc.2023.110118
  39. CSA. Central Statistical Agency, Projected Population Size of Ethiopia by Sex, Area and Density by Region, Zone and Wereda, Central Statistical Agency, Addis Ababa, Ethiopia. In: Agency CS, editor.: CSA; 2021.
  40. G. MoWIE, (2020) Domestic and Industrial water uses and Demand Forecast. Addis Ababa, Ethiopia.
  41. K. Rathnayaka, H. Malano, M. Arora, Assessment of Sustainability of Urban Water Supply and Demand Management Options: A Comprehensive Approach. Water, 8(12), (2016) 595. https://doi.org/10.3390/w8120595
  42. B. Wang, M. Zhang, J. Wei, S. Wang, S. Li, Q. Ma, X. Li, S. Pan, Changes in extreme events of temperature and precipitation over Xinjiang, northwest China, during 1960–2009. Quaternary International, 298, (2013) 141-151. https://doi.org/10.1016/j.quaint.2012.09.010
  43. A.E. Raftery, H. Sevcíková, Probabilistic population forecasting: Short to very long-term. International Journal of Forecasting, 39(1), (2023) 73-97. https://doi.org/10.1016/j.ijforecast.2021.09.001
  44. M. Thomas, A. Syse, A. Rogne, R. Gleditsch, Assessing the accuracy of national population projections: A case study of Norway. Finnish Yearbook of Population Research, 56, (2022) 31–64. https://doi.org/10.23979/fypr.109057
  45. M.G. Hiben, A.G. Awoke, A.A. Ashenafi, Hydroclimatic Variability, Characterization, and Long Term Spacio-Temporal Trend Analysis of the Ghba River Subbasin, Ethiopia. Advances in Meteorology, (2022) 3594641. https://doi.org/10.1155/2022/3594641
  46. T.G. Gebremicael, (2019) Understanding the impact of human interventions on the hydrology of Nile Basin headwaters, the case of Upper Tekeze catchments. CRC Press, London https://doi.org/10.1201/9780367853167
  47. T.G. Gebremicael, Y.A. Mohamed, P.V. Zaag, E.Y. Hagos, Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē–Atbara river basin, Ethiopia. Hydrology and Earth System Sciences, 21(4), (2017) 2127–2142. https://doi.org/10.5194/hess-21-2127-2017
  48. T.G. Gebremicael, Y. Mohamed, P. Van der Zaag Attributing the hydrological impact of different land use types and their long-term dynamics through combining parsimonious hydrological modelling, alteration analysis and PLSR analysis. Science of The Total Environment, 660, (2019) 1155-1167. https://doi.org/10.1016/j.scitotenv.2019.01.085
  49. A. Alhamshry, A.A. Fenta, H. Yasuda, R. Kimura, K. Shimizu, Seasonal rainfall variability in Ethiopia and its long-term link to global sea surface temperatures. Water, 12(1), (2020) 55. https://doi.org/10.3390/w12010055
  50. E. Negash, T. Getachew, E. Birhane, H. Gebrewahed, Ecosystem Service value distribution along the agroecological gradient in north-central Ethiopia. Earth Systems and Environment, 4, (2020) 107-116. https://doi.org/10.1007/s41748-020-00149-7
  51. S. Tesfaye, G. Taye, E. Birhane, S.E. van der Zee, Observed and model simulated twenty-first century hydro-climatic change of Northern Ethiopia. Journal of Hydrology: Regional Studies, 22, (2019) 100595. https://doi.org/10.1016/j.ejrh.2019.100595
  52. P.A. Arias, R. Garreaud, G. Poveda, J.C. Espinoza, J. Molina-Carpio, M. Masiokas, M. Viale, L, Scaff, P.J. van Oevelen, Hydroclimate of the Andes Part II: Hydroclimate variability and sub-continental patterns. Frontiers in Earth Science, 8, (2021) 666. https://doi.org/10.3389/feart.2020.505467
  53. P. Saranya, A. Krishnakumar, N. Sinha, S. Kumar, K.A. Krishnan, Isotopic signatures of moisture recycling and evaporation processes along the Western Ghats orography. Atmospheric Research, 264, (2021) 105863. https://doi.org/10.1016/j.atmosres.2021.105863
  54. D.H. Mann, P. Groves, R.E. Reanier, M.L. Kunz, Floodplains, permafrost, cottonwood trees, and peat: What happened the last time climate warmed suddenly in arctic Alaska?. Quaternary Science Reviews, 29(27-28), (2010) 3812-3830. https://doi.org/10.1016/j.quascirev.2010.09.002
  55. K.D. Kahsay, S.M. Pingale, S.D. Hatiye, Impact of climate change on groundwater recharge and base flow in the sub-catchment of Tekeze basin, Ethiopia. Groundwater for Sustainable Development, 6, (2018) 121-133. https://doi.org/10.1016/j.gsd.2017.12.002
  56. D.T. Reda, A.N. Engida, D.H. Asfaw, R. Hamdi, Analysis of precipitation based on ensembles of regional climate model simulations and observational databases over Ethiopia for the period 1989–2008. International Journal of Climatology, 35(6), (2015) 948-971. https://doi.org/10.1002/joc.4029
  57. T. Gebrehiwot, A. van der Veen, Assessing the evidence of climate variability in the northern part of Ethiopia. Journal of Development and Agricultural Economics, 5(3), (2013) 104-119. https://doi.org/10.5897/JDAE12.056
  58. Y. Mohammed, F. Yimer, M. Tadesse, K. Tesfaye, Variability and trends of rainfall extreme events in north east highlands of Ethiopia. International Journal of Hydrology, 2(5), (2018) 594-605. https://doi.org/10.15406/ijh.2018.02.00131
  59. J. Nyssen, H. Vandenreyken, J. Poesen, J. Moeyersons, J. Deckers, M. Haile, C. Salles, G. Govers, Rainfall erosivity and variability in the Northern Ethiopian Highlands. Journal of Hydrology, 311(1-4), (2005) 172-187. https://doi.org/10.1016/j.jhydrol.2004.12.016
  60. M.A. Degefu, T. Alamirew, G. Zeleke, W. Bewket, Detection of trends in hydrological extremes for Ethiopian watersheds, Regional Environmental Change, 19, (2019) 1923–1933. https://doi.org/10.1007/s10113-019-01510-x
  61. L. Samaniego, S. Thober, N. Wanders, M. Pan, O. Rakovec, J. Sheffield, E.F. Wood, C. Prudhomme, G. Rees, H. Houghton-Carr, M. Fry, K. Smith, G. Watts, H. Hisdal, T. Estrela, C. Buontempo, A. Marx, R. Kumar, Hydrological forecasts and projections for improved decision-making in the water sector in Europe. Bulletin of the American Meteorological Society, 100(12), (2019) 2451-2472. https://doi.org/10.1175/BAMS-D-17-0274.1
  62. N.R. Sanders, K.B. Manrodt, The efficacy of using judgmental versus quantitative forecasting methods in practice. Omega, 31(6), (2003) 511-522. https://doi.org/10.1016/j.omega.2003.08.007
  63. S. Makridakis, E. Spiliotis, V. Assimakopoulos, Statistical and Machine Learning forecasting methods: Concerns and ways forward. Plos One, 13, (2018) e0194889. https://doi.org/10.1371/journal.pone.0194889
  64. S. Namany, T. Al-Ansari, R. Govindan, Sustainable energy, water and food nexus systems: A focused review of decision-making tools for efficient resource management and governance. Journal of Cleaner Production, 225, (2019) 610-626. https://doi.org/10.1016/j.jclepro.2019.03.304
  65. T. Ahmad, H. Chen, Potential of three variant machine-learning models for forecasting district level medium-term and long-term energy demand in smart grid environment. Energy, 160, (2018) 1008-1020. https://doi.org/10.1016/j.energy.2018.07.084
  66. T. Ahmad, H. Zhang, Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts. Energy, 209 (15), (2020) 118477. https://doi.org/10.1016/j.energy.2020.118477
  67. E. Pacchin, S. Alvisi, M. Franchini, A short-term water demand forecasting model using a moving window on previously observed data. Water, 9(3), (2017) 172. https://doi.org/10.3390/w9030172
  68. G. MoWR, (2006) Urban Water Supply Design Criteria Addis Ababa, Ethiopia.
  69. A.Y. Hoekstra, A.K. Chapagain, Water footprints of nations: water use by people as a function of their consumption pattern. Water Resour Manage, 21, (2007) 35-48. https://doi.org/10.1007/978-1-4020-5591-1_3
  70. A. Ruijs, A. Zimmermann, M. van den Berg, Demand and distributional effects of water pricing policies. Ecological Economics, 66(2-3), (2008) 506-516. https://doi.org/10.1016/j.ecolecon.2007.10.015
  71. P.W. Mote, E.A. Parson, A.F. Hamlet, W.S. Keeton, D. Lettenmaier, N. Mantua, E.L. Miles, D.W. Peterson, D.L. Peterson, R. Slaughter A.K. Snover, Preparing for climatic change: the water, salmon, and forests of the Pacific Northwest. Climatic Change, 61, (2003) 45-88. https://doi.org/10.1023/A:1026302914358
  72. Y. Zou, W. Xie, S. Lou, L. Zhang, Y. Huang, D. Xia, X. Yang, C. Feng, Y. Li, How weather impacts the citizens' activity patterns in southern China? Enlightenment from large-scale mobile phone signaling data of Guangzhou. Urban Climate, 52, (2023) 101700. https://doi.org/10.1016/j.uclim.2023.101700