Statistical characterisation and estimation of non-domestic water demand
| Autor: | HJ van Zyl, A. A. Ilemobade, Y. Le Gat, J. E. van Zyl |
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| Přispěvatelé: | University of the Witwatersrand [Johannesburg] (WITS), University of Cape Town, Environnement, territoires et infrastructures (UR ETBX), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), UNIVERSITY OF WITWATERSRAND JOHANNESBURG ZAF, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), UNIVERSITY OF CAPE TOWN ZAF |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0208 environmental biotechnology
Geography Planning and Development Distribution (economics) Water demand 02 engineering and technology Water consumption Distribution system design demand Statistics Economics non-domestik AFRIQUE DU SUD Water Science and Technology Hydrology Estimation [STAT.AP]Statistics [stat]/Applications [stat.AP] Land use business.industry Demande en eau 020801 environmental engineering [STAT]Statistics [stat] Agriculture [SDE]Environmental Sciences Consommation en eau business Non domestic |
| Zdroj: | Urban Water Journal Urban Water Journal, Taylor & Francis, 2017, 14 (7), pp.720-726. ⟨10.1080/1573062X.2016.1253753⟩ |
| ISSN: | 1573-062X 1744-9006 |
| DOI: | 10.1080/1573062X.2016.1253753⟩ |
| Popis: | Estimation of annual average water demand figures is critical for the design and evaluation of water distribution systems. This study evaluated the metered water consumption of more than 67,000 non-domestic consumers in six categories from cities and towns in South Africa. It was found that lognormal distributions provide good descriptions of the annual average daily demand (AADD) distribution in each category. The land use categories Business Commercial, Industrial, Agricultural holdings and Sports & Parks displayed similar median AADDs of between 1.5 and 1.7 kl/property/day. Educational properties used substantially more water (4.7 kl/property/day), while Government & Institutional properties used substantially less water (0.7 kl/property/day). A step-wise regression analyses showed that property size has the greatest impact on water demand for most categories. Finally, a novel statistically based method is proposed for estimating the average AADD of a given number of properties based on an acceptable risk of non-exceedance. |
| Databáze: | OpenAIRE |
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