Urban water-energy service demand forecasting through linear model approach for sustainability: a case study of Addis Ababa city

Bedassa Dessalegn Kitessa (), Semu Moges Ayalew, Geremew Sahilu Gebrie and Solomon Tesfamariam Teferi
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Bedassa Dessalegn Kitessa: Addis Ababa University
Semu Moges Ayalew: University of Connecticut
Geremew Sahilu Gebrie: Addis Ababa University
Solomon Tesfamariam Teferi: Addis Ababa University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 7, No 6, 16483-16501

Abstract: Abstract Urban water-energy demand is an important basic data for urban engineering planning, design and management. Making full use of multi-source data and prior knowledge to quickly and economically obtain high-precision urban water-energy demand are of great significance to the optimal allocation of sustainable urban water-energy supply. In order to accurately forecast the future urban water-energy demand, this study took Addis Ababa City as a research area to forecast the water-energy demand of the city from 2020 to 2050. Aiming at the oscillating characteristics of the urban water-energy demand sequence and the over-fitting problem of prediction models, this study proposed the linear mathematical regression algorithm model. Urbanization drivers such as population (POP), gross domestic product (GDP) and per capita income (PCI) were explored to determine the water-energy consumption, or demand. Technologies based water-energy delivery efficiency, which is one of urbanization driver, was also considered to forecast the electric energy and water demand. This study adopted a linear model using data-mining approach, which is used to associate the historical water-energy consumption with the POP, GDP and PCI growth scenarios in order to address the water-energy consumptions. Overall, the total water-energy demand is projected to increase by 65% for water supply and 120% energy in 2030 and by 365% for water supply and 700% energy in 2050 from the baseline period of 2020 because the increase in the water-energy urbanization drivers mainly the POP, GDP, and PCI. For the water-energy demand forecast, the model's performance was assessed in order to correctly pinpoint the most significant urbanization drivers. This has been done to help planners and policymakers think about sustainable water-energy supply with a better understanding and more thorough insights.

Keywords: Water; Energy; Urbanization; Consumption; Data-mining; Linear regression model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03416-5

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