Abstract
Rapid population growth in the face of an uncertain climate future challenges the desert city of Phoenix, Arizona to consume water more prudently. To better understand the demand side of this important issue, we identified the determinants of water consumption for detached single-family residential units using ordinary least squares regression (OLS). We compared the results from the OLS model to those of a geographically weighted regression (GWR) model to determine whether there are spatial effects above and beyond the effects of the OLS variables. Determinants of residential water demand reflect both indoor and outdoor use and include household size, the presence of swimming pools, lot size, and the prevalence of landscaping that requires a moist environment. Results confirm the statistical significance of household size, the presence of a pool, landscaping practices, and lot size. Improvement of the GWR over the OLS model suggests that there are spatial effects above and beyond the effects for household size and pools – two of the four determinants of water demand. This means that census tracts exhibit water consumption behavior similar to neighboring tracts for these two variables. Model parameters can be used to investigate the effects of policies designed to regulate lot size, pool construction, and landscaping practices on water consumption and to forecast water demand in areas of new construction.
Similar content being viewed by others
References
Aitken C, Duncan H, McMahon TA (1991) A cross-sectional regression-analysis of residential water demand in Melbourne, Australia. Appl Geogr 11(2):157–165
Arizona Department of Economic Security (2005) http://www.de.state.az.us/ASP/default.asp
Balling RC Jr, Gober P (2006) Climate Variability and Residential Water Use in Phoenix, Arizona. Journal of Applied Meteorology and Climatology (in press)
Billings RB, Agthe DE (1998) State-space versus multiple regression for forecasting urban water demand. J Water Resour Plan Manage 124:113–117
City of Phoenix (2005) http://www.ci.phoenix.az.us/
Dube E, van der Zaag P (2003) Analysing water use patterns for demand management: the case of the city of Masvingo, Zimbabwe. Phys Chem Earth 28(20–27):805–815
Fotheringham AS, Brunsdon C, Charlton M (2002) Geographically weighted regression: the analysis of spatially varying relationships. Wiley, New York
Gammage G (1999) Phoenix in perspective: reflections on developing the desert. Herberger Center for Design Excellence, College of Architecture and Urban Design, Arizona State University, Tempe, AZ
Gober P (2006) Metropolitan Phoenix: place making and community building in the desert. University of Pennsylvania Press, Philadelphia, PA
Guhathakurta S, Gaver S, Gober P (2005) The impact of urban heat islands on water use: the case of Phoenix metropolitan area. Paper presented at the North American Meetings of the Regional Science Association International in Las Vegas, November 11, 2005
Gutzler DS, Nims JS (2006) Interannual variability of water demand and summer climate in Albuquerque, New Mexico. J Appl Meteorol 44:1777–1787
Hope ACA (1968) A simplified Monte Carlo significance test procedure. J R Stat Soc B 30(3):582–598
Larson EK, Grimm NB, Gober P, Redman CL (2006) The paradoxical ecology and management of water in the Phoenix, USA metropolitan area. Journal of Ecohydrology and Hydrobiology 5(4) (in press)
Maidment DR, Parzen E (1984) Time patterns of water use in six Texas cities. J Water Resour Plan Manage 110:90–106
Malczewski J, Poetz A (2005) Residential burglaries and neighborhood socioeconomic context in London, Ontario: global and local regression analysis. Prof Geogr 57(4):516–529
Martin CA (2001) Landscape water use in Phoenix, Arizona. Desert Plants 17:26–31
Mayer PW, DeOreo WB, Opitz E, Kiefer J, Dziegielewski B, Davis W, Nelson JO (1999) Residential end uses of water. American Water Works Association Research Foundation, Denver, CO
Mennis JL, Jordan L (2005) The distribution of environmental equity: exploring spatial nonstationarity in multivariate models of air toxic releases. Ann Assoc Am Geogr 95(2):249–268
Nakaya T, Fotheringham AS, Brunsdon C, Charlton M (2005) Geographically weighted Poisson regression for disease association mapping. Stat Med 24(17):2695–2717
Rhoades SD, Walski TM (1991) Using regression analysis to project pumpage. J Am Water Works Assoc 83:45–50
Stefanov WL, Ramsey MS, Christensen PR (2001) Monitoring urban land cover change: an expert system approach to land cover classification of semiarid to arid urban centers. Remote Sens Environ 77(2):173–185
Troy P, Holloway D (2004) The use of residential water consumption as an urban planning tool: a pilot study in Adelaide. J Environ Plan Manag 47(1):97–114
U.S. Bureau of the Census (2005) http://www.census.gov/
Wang Q, Ni J, Tenhunen J (2005) Application of a geographically-weighted regression analysis to estimate net primary production of Chinese forest ecosystems. Glob Ecol Biogeogr 14(4):379–393
Western Regional Climate Center (2005) Retrieved on August 17, 2005 from http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?azphoe
Wilson L (1989) Addition of a climate variable to the Howe and Linaweaver western sprinkling equation. Water Resour Res 25:1067–1069
Zhao F, Park N (2004) Using geographically weighted regression models to estimate annual average daily traffic. Transp Res Rec (1879):99–107
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wentz, E.A., Gober, P. Determinants of Small-Area Water Consumption for the City of Phoenix, Arizona. Water Resour Manage 21, 1849–1863 (2007). https://doi.org/10.1007/s11269-006-9133-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-006-9133-0