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Probabilistic Water Demand Forecasting Using Projected Climatic Data for Blue Mountains Water Supply System in Australia

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  • Md Haque
  • Ataur Rahman
  • Dharma Hagare
  • Golam Kibria

Abstract

Long term water demand forecasting is needed for the efficient planning and management of water supply systems. A Monte Carlo simulation approach is adopted in this paper to quantify the uncertainties in long term water demand prediction due to the stochastic nature of predictor variables and their correlation structures. Three future climatic scenarios (A1B, A2 and B1) and four different levels of water restrictions are considered in the demand forecasting for single and multiple dwelling residential sectors in the Blue Mountains region, Australia. It is found that future water demand in 2040 would rise by 2 to 33 % (median rise by 11 %) and 72 to 94 % (median rise by 84 %) for the single and multiple dwelling residential sectors, respectively under different climatic and water restriction scenarios in comparison to water demand in 2010 (base year). The uncertainty band for single dwelling residential sector is found to be 0.3 to 0.4 GL/year, which represent 11 to 13 % variation around the median forecasted demand. It is found that the increase in future water demand is not notably affected by the projected climatic conditions but by the increase in the dwelling numbers in future i.e. the increase in total population. The modelling approach presented in this paper can provide realistic scenarios of forecasted water demands which would assist water authorities in devising appropriate management strategies to enhance the resilience of the water supply systems. The developed method can be adapted to other water supply systems in Australia and other countries. Copyright Springer Science+Business Media Dordrecht 2014

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  • Md Haque & Ataur Rahman & Dharma Hagare & Golam Kibria, 2014. "Probabilistic Water Demand Forecasting Using Projected Climatic Data for Blue Mountains Water Supply System in Australia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1959-1971, May.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:7:p:1959-1971
    DOI: 10.1007/s11269-014-0587-1
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    1. Animesh Gain & Yoshihide Wada, 2014. "Assessment of Future Water Scarcity at Different Spatial and Temporal Scales of the Brahmaputra River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 999-1012, March.
    2. Liangxin Fan & Guobin Liu & Fei Wang & Coen Ritsema & Violette Geissen, 2014. "Domestic Water Consumption under Intermittent and Continuous Modes of Water Supply," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 853-865, February.
    3. 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.
    4. M. Froukh, 2001. "Decision-Support System for Domestic Water Demand Forecasting and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 15(6), pages 363-382, December.
    5. Schleich, Joachim & Hillenbrand, Thomas, 2009. "Determinants of residential water demand in Germany," Ecological Economics, Elsevier, vol. 68(6), pages 1756-1769, April.
    6. Amin Zargar & Rehan Sadiq & Faisal Khan, 2014. "Uncertainty-Driven Characterization of Climate Change Effects on Drought Frequency Using Enhanced SPI," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 15-40, January.
    7. Griffin, Ronald C. & Chang, Chan, 1991. "Seasonality In Community Water Demand," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 16(2), pages 1-11, December.
    8. 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.
    9. Lenka Slavíková & Vítězslav Malý & Michael Rost & Lubomír Petružela & Ondřej Vojáček, 2013. "Impacts of Climate Variables on Residential Water Consumption in the Czech Republic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(2), pages 365-379, January.
    10. Silvia Padula & Julien Harou & Lazaros Papageorgiou & Yiming Ji & Mohammad Ahmad & Nigel Hepworth, 2013. "Least Economic Cost Regional Water Supply Planning – Optimising Infrastructure Investments and Demand Management for South East England’s 17.6 Million People," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5017-5044, December.
    11. Ashu Jain & Ashish Kumar Varshney & Umesh Chandra Joshi, 2001. "Short-Term Water Demand Forecast Modelling at IIT Kanpur Using Artificial Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 15(5), pages 299-321, October.
    12. Cecilia Tortajada & Yugal Joshi, 2013. "Water Demand Management in Singapore: Involving the Public," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2729-2746, June.
    13. Barry Abrams & Santharajah Kumaradevan & Vasilis Sarafidis & Frank Spaninks, 2012. "An Econometric Assessment of Pricing Sydney’s Residential Water Use," The Economic Record, The Economic Society of Australia, vol. 88(280), pages 89-105, March.
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