Classifying households for water demand forecasting using physical property characteristics

被引:69
作者
Fox, C. [1 ]
McIntosh, B. S. [1 ]
Jeffrey, P. [1 ]
机构
[1] Cranfield Univ, Ctr Water Sci, Cranfield MK43 0AL, Beds, England
关键词
Household water demand; Water supply; Demand forecasting; Housing development; Planning; CONSUMPTION; PROVINCE; AREA; CITY;
D O I
10.1016/j.landusepol.2008.08.004
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Changes in population distribution across Europe are driving the construction of substantial numbers of new houses, creating a need to forecast water demand for new housing developments. The most certain information available on new households during planning are the physical characteristics of the properties themselves. This paper sets out to establish how to classify properties in terms of their physical characteristics for the purpose of forecasting water demand. Analysis of household water demand under a univariate classification of property type showed significant differences for properties of different size (number of bedrooms), architectural type (e.g. flats vs. terraced) and garden presence but not for age or for garden aspect. Analysis of household water demand under a multivariate classification of property type showed fewer significant differences between property types. The results of the study were compared to studies and found to fit qualitatively. However, quantitative differences were noted indicating geographical and sampling variation which requires further investigation. In addition, further research is required to determine the relative certainty of forecasts derived from physical vs. socio-economic or demographic characteristics. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:558 / 568
页数:11
相关论文
共 51 条
[41]   Multi-criteria spatial decision analysis for forecasting urban water requirements: a case study of Dehradun city, India [J].
Rao, KHVD .
LANDSCAPE AND URBAN PLANNING, 2005, 71 (2-4) :163-174
[42]  
Russac D.A., 1991, Water and Environment Journal, V5, P242
[43]  
Samuels P., 2006, SUSTAINABLE WATER MA
[44]   Predicting and understanding home garden water use [J].
Syme, GJ ;
Shao, QX ;
Po, M ;
Campbell, E .
LANDSCAPE AND URBAN PLANNING, 2004, 68 (01) :121-128
[45]   WATER DEMAND FORECASTING BY MEMORY-BASED LEARNING [J].
TAMADA, T ;
MARUYAMA, M ;
NAKAMURA, Y ;
ABE, S ;
MAEDA, K .
WATER SCIENCE AND TECHNOLOGY, 1993, 28 (11-12) :133-140
[46]  
Troy P., 2004, J ENVIRON PLANN MAN, V47, P97, DOI DOI 10.1080/0964056042000189826
[47]  
*VEOL WAT, 2008, DRAFT WAT RES MAN PL
[48]  
*WAT UK, 2003, SUST MOV AH SUST IND
[49]  
WEBER JA, 1989, J AM WATER WORKS ASS, V81, P57
[50]   RESIDENTIAL WATER DEMAND FORECASTING [J].
WHITFORD, PW .
WATER RESOURCES RESEARCH, 1972, 8 (04) :829-&