IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v28y2014i7p1959-1971.html
   My bibliography  Save this article

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

Author

Listed:
  • 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

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-014-0587-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-014-0587-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Schleich, Joachim & Hillenbrand, Thomas, 2009. "Determinants of residential water demand in Germany," Ecological Economics, Elsevier, vol. 68(6), pages 1756-1769, April.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Can Bülent Karakuş, 2020. "Evaluation of water quality of Kızılırmak River (Sivas/Turkey) using geo-statistical and multivariable statistical approaches," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4735-4769, June.
    2. Darshana Rajapaksa & Robert Gifford & Benno Torgler & María A. García-Valiñas & Wasantha Athukorala & Shunsuke Managi & Clevo Wilson, 2019. "Do monetary and non-monetary incentives influence environmental attitudes and behavior? Evidence from an experimental analysis," Post-Print hal-03191523, HAL.
    3. Taís Maria Nunes Carvalho & Francisco Souza Filho, 2021. "Variational Mode Decomposition Hybridized With Gradient Boost Regression for Seasonal Forecast of Residential Water Demand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3431-3445, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Sara Fontdecaba & Pere Grima & Lluís Marco & Lourdes Rodero & José Sánchez-Espigares & Ignasi Solé & Xavier Tort-Martorell & Dominique Demessence & Victor Martínez De Pablo & Jordi Zubelzu, 2012. "A Methodology to Model Water Demand based on the Identification of Homogenous Client Segments. Application to the City of Barcelona," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(2), pages 499-516, January.
    3. Gajda, Janusz & Bartnicki, Grzegorz & Burnecki, Krzysztof, 2018. "Modeling of water usage by means of ARFIMA–GARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 644-657.
    4. 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.
    5. 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.
    6. 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.
    7. Philip Kofi Adom & Joonho Yeo & Lin Zhang, 2021. "Is water use sustainable and efficient in China? Evidence from a macro level analysis," Applied Economics, Taylor & Francis Journals, vol. 53(53), pages 6166-6183, November.
    8. Salah L. Zubaidi & Sadik K. Gharghan & Jayne Dooley & Rafid M. Alkhaddar & Mawada Abdellatif, 2018. "Short-Term Urban Water Demand Prediction Considering Weather Factors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4527-4542, November.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Mukand Babel & Nisuchcha Maporn & Victor Shinde, 2014. "Incorporating Future Climatic and Socioeconomic Variables in Water Demand Forecasting: A Case Study in Bangkok," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 2049-2062, May.
    14. 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).
    15. Abdüsselam Altunkaynak & Mehmet Özger & Mehmet Çakmakci, 2005. "Water Consumption Prediction of Istanbul City by Using Fuzzy Logic Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(5), pages 641-654, October.
    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. Milan Ščasný & Šarlota Smutná, 2021. "Estimation of price and income elasticity of residential water demand in the Czech Republic over three decades," Journal of Consumer Affairs, Wiley Blackwell, vol. 55(2), pages 580-608, June.
    18. Fullerton, Thomas M., Jr. & White, Katherine & Smith, Wm. Doyle & Walke, Adam G., 2012. "An Empirical Analysis of Halifax Municipal Water Consumption," MPRA Paper 54113, University Library of Munich, Germany, revised 14 Mar 2013.
    19. E. Pacchin & F. Gagliardi & S. Alvisi & M. Franchini, 2019. "A Comparison of Short-Term Water Demand Forecasting Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(4), pages 1481-1497, March.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:28:y:2014:i:7:p:1959-1971. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.