Long-Term Water Demand Forecasting
Jean-Daniel Rinaudo ()
Additional contact information
Jean-Daniel Rinaudo: BRGM - Bureau de Recherches Géologiques et Minières
Post-Print from HAL
Abstract:
This chapter reviews existing long term water demand forecasting methodologies. Based on an extensive literature review, it shows that the domain has benefited from contributions by economists, engineers and system modelers, producing a wide range of tools, many of which have been tested and adopted by practitioners. It illustrates, via three detailed case studies in the USA, the UK and Australia, how different tools can be used depending on the regulatory context, the water scarcity level, the geographic scale at which they are deployed and the technical background of water utilities and their consultants. The chapter reviews how practitioners address three main challenges, namely the integration of land use planning with demand forecasting; accounting for climate change; and dealing with forecast uncertainty. It concludes with a discussion of research perspectives in that domain.
Keywords: water demand forecasting; economic modeling; end-use modeling; statistical modeling; France; Australia; UK; USA (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-agr, nep-for and nep-ger
Note: View the original document on HAL open archive server: https://brgm.hal.science/hal-01183853
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Published in Understanding and Managing Urban Water in Transition, p 239-268, 2015, ⟨10.1007/978-94-017-9801-3_11⟩
Downloads: (external link)
https://brgm.hal.science/hal-01183853/document (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01183853
DOI: 10.1007/978-94-017-9801-3_11
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().