Blokker, M., Agudelo-vera, C., Moerman, A. et al. (2 more authors) (2017) Review of applications of SIMDEUM, a stochastic drinking water demand model with small temporal and spatial scale. Drinking Water Engineering and Science Discussions. pp. 1-15. ISSN 1996-9473
Abstract
Many researchers have developed drinking water demand models with various temporal and spatial scales. A limited number of models are available at a temporal scale of one second and a spatial scale of a single home. Reasons for building these models were described in the papers in which the models were introduced, along with a discussion on potential applications. However, the predicted applications are seldom re-examined. As SIMDEUM, a stochastic end-use model for drinking water demand, has often been applied in research and practice since it was developed, we are reexamining its applications in this paper. SIMDEUM’s original purpose was to calculate maximum demands in order to be able to design self-cleaning networks. Yet, the model has been useful in many more applications. This paper gives an overview of the many fields of application of SIMDEUM and shows where this type of demand model is indispensable and where it has limited practical value. This overview also leads to an understanding of requirements on demand models in various applications.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Author(s) 2017. CC-BY 3.0 License. |
Keywords: | Distribution networks; drinking water demand; modelling; applications |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Feb 2017 16:11 |
Last Modified: | 16 Feb 2017 16:11 |
Published Version: | http://doi.org/10.5194/dwes-2017-4 |
Status: | Published |
Publisher: | Copernicus Publications |
Refereed: | Yes |
Identification Number: | 10.5194/dwes-2017-4 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:112352 |