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A multivariate econometric approach for domestic water demand modeling: An application to Kathmandu, Nepal

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  • M. Babel
  • A. Gupta
  • P. Pradhan

Abstract

Domestic water use/demand is a complex function of socio-economic characteristics, climatic factors and public water policies and strategies. This study therefore develops a model based on the multivariate econometric approach which considers these parameters to forecast and manage the domestic water use/demand. The model applies statistical tools to select suitable demand function and most relevant explanatory variables that have strong relationship with water use/demand. The model applicability is demonstrated with an example of domestic water use in Kathmandu Valley, Nepal. The results indicate that the number of connections, water pricing, public education level, and average annual rainfall are significant variables of domestic water use/demand. The paper further analyzes the effect of length of data series on accuracy of model results. The developed model is used to forecast the water use/demand in the future in the study area. Copyright Springer Science + Business Media, Inc. 2007

Suggested Citation

  • M. Babel & A. Gupta & P. Pradhan, 2007. "A multivariate econometric approach for domestic water demand modeling: An application to Kathmandu, Nepal," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(3), pages 573-589, March.
    • Handle: RePEc:spr:waterr:v:21:y:2007:i:3:p:573-589
    DOI: 10.1007/s11269-006-9030-6
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    References listed on IDEAS

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    1. Graeme Dandy & Tin Nguyen & Carolyn Davies, 1997. "Estimating Residential Water Demand in the Presence of Free Allowances," Land Economics, University of Wisconsin Press, vol. 73(1), pages 125-139.
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    2. Dinusha Dharmaratna & Edwyna Harris, 2012. "Estimating Residential Water Demand Using the Stone-Geary Functional Form: The Case of Sri Lanka," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2283-2299, June.
    3. Liangfeng Zou & Yuanyuan Zha & Yuqing Diao & Chi Tang & Wenquan Gu & Dongguo Shao, 2023. "Coupling the Causal Inference and Informer Networks for Short-term Forecasting in Irrigation Water Usage," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 427-449, January.
    4. Wang Xiao-jun & Zhang Jian-yun & Shahid Shamsuddin & He Rui-min & Xia Xing-hui & Mou Xin-li, 2015. "Potential impact of climate change on future water demand in Yulin city, Northwest China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 20(1), pages 1-19, January.
    5. Muhammad Al-Zahrani & Amin Abo-Monasar, 2015. "Urban Residential Water Demand Prediction Based on Artificial Neural Networks and Time Series Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3651-3662, August.
    6. Subhash Andey & Prakash Kelkar, 2009. "Influence of Intermittent and Continuous Modes of Water Supply on Domestic Water Consumption," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(12), pages 2555-2566, September.
    7. Xiao-Chen Yuan & Yi-Ming Wei & Su-Yan Pan & Ju-Liang Jin, 2014. "Urban Household Water Demand in Beijing by 2020: An Agent-Based Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2967-2980, August.
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    13. Henrique Monteiro, 2010. "Residential Water Demand in Portugal: checking for efficiency-based justifications for increasing block tariffs," Working Papers Series 1 ercwp0110, ISCTE-IUL, Business Research Unit (BRU-IUL).
    14. Mohamed Mohamed & Aysha Al-Mualla, 2010. "Water Demand Forecasting in Umm Al-Quwain (UAE) Using the IWR-MAIN Specify Forecasting Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 4093-4120, November.
    15. Mahmut Firat & Mehmet Yurdusev & Mustafa Turan, 2009. "Evaluation of Artificial Neural Network Techniques for Municipal Water Consumption Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 617-632, March.
    16. Mukand Babel & Victor Shinde, 2011. "Identifying Prominent Explanatory Variables for Water Demand Prediction Using Artificial Neural Networks: A Case Study of Bangkok," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1653-1676, April.
    17. Aminou Arouna & Stephan Dabbert, 2010. "Determinants of Domestic Water Use by Rural Households Without Access to Private Improved Water Sources in Benin: A Seemingly Unrelated Tobit Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(7), pages 1381-1398, May.
    18. Negin Ashoori & David A. Dzombak & Mitchell J. Small, 2016. "Modeling the Effects of Conservation, Demographics, Price, and Climate on Urban Water Demand in Los Angeles, California," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5247-5262, November.
    19. Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & En-hong Guan & Yong-xiang Wu & Juan Gao & Rui-min He, 2016. "Adaptation to climate change impacts on water demand," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(1), pages 81-99, January.
    20. Sholpan Saimova & Gulsim Makenova & Aizhan Skakova & Aitolkyn Moldagaliyeva & Ardak Beisembinova & Zhamilya Berdiyarova & Bagdagul Imanbekova, 2020. "Towards a Low-carbon Economic Sustainable Development: Scenarios and Policies for Kazakhstan," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 638-646.
    21. Xiao-Jun Wang & Jian-Yun Zhang & Shamsuddin Shahid & Wei Xie & Chao-Yang Du & Xiao-Chuan Shang & Xu Zhang, 2018. "Modeling domestic water demand in Huaihe River Basin of China under climate change and population dynamics," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(2), pages 911-924, April.
    22. Saeed Ghavidelfar & Asaad Y. Shamseldin & Bruce W. Melville, 2017. "A Multi-Scale Analysis of Single-Unit Housing Water Demand Through Integration of Water Consumption, Land Use and Demographic Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(7), pages 2173-2186, May.
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