Population Growth Forecasting and Clean Water Demand Analysis for Denpasar City Toward 2030

Water is poised to become the most critical natural resource of the third millennium, influencing both economic stability and human survival, particularly as developing nations face rapid population growth. This surge in population and industrial activity is driving up water demand while simultaneously depleting available resources. The resulting gap between high demand and dwindling supply poses significant challenges for water distribution. This study outlines a methodology for forecasting population growth and water demand in the Denpasar area over a ten-year period.

Three projection models—linear, quadratic, and exponential—were evaluated to identify the most accurate solution. The findings indicate that the quadratic method provides the most reliable forecast for Denpasar's future water needs. Current projections reveal that existing water infrastructure can only meet 41.63% of total demand. Consequently, it is imperative for the Denpasar municipal government to implement more robust strategies to address this substantial supply deficit

Population trends, sustainability, freshwater reserves, demand, forecasting

1. Parwita, I. G. L. M., Dharma, I. G. B. S., Yekti, M. I., Pariartha, I. P. G. S., & Tarigan, Z. J. H. (2024). Sustainable clean water supply management in the South Bali, Indonesia. Water Conservation & Management (WCM), 8(1), 10–19. doi.org [Google Scholar] [Crossref]

2. Suryatmaja, I. B., Kurniari, K., & Nada, I. M. (2021). Comparison of clean water demand and availability in Denpasar City. Jurnal Ilmiah Kurva Teknik, 10(1), 45–52. doi.org [Google Scholar] [Crossref]

3. Wandari, A., & Junaidi, A. (2021). Perspectives on population growth and clean water supply in Denpasar City. Proceedings of the International Conference on Industrial, Sustainable and Strategic Technology (ICIST 2020), 156–162. Atlantis Press. [Google Scholar] [Crossref]

4. BPS-Statistics of Denpasar City. (2023). Denpasar City in Figures 2023. BPS Denpasar. [Google Scholar] [Crossref]

5. Ministry of Public Works and Housing. (2022). Regulation No. 27/PRT/M/2016 regarding the optimization of drinking water supply systems (SPAM). Jakarta: PUPR. [Google Scholar] [Crossref]

6. Sari, A. N., & Rahmawati, D. (2021). Forecasting urban water demand: A comparative study of projection methods. Journal of Water Resources Engineering, 12(2), 88–97. [Google Scholar] [Crossref]

7. Walpole, R. E., & Myers, R. H. (1995). Ilmu peluang dan statistik untuk insinyur dan ilmuwan (R. K. Sembiring, Terj.; Ed. ke-4). ITB Press. [Google Scholar] [Crossref]

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