The Influence of Land Cover, Vertical Structure, and Socioeconomic Factors on Outdoor Water Use in a Western US City

Edward Gage () and David Cooper

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2015, vol. 29, issue 10, 3877-3890

Abstract: To help inform urban water conservation and planning, we evaluated spatial patterns and correlative relationships among physical land cover properties, socioeconomic and demographic characteristics, and single-family outdoor residential water use in Aurora, Colorado, a rapidly-growing suburb in the semi-arid Colorado Front Range. Using high resolution land cover maps and lidar-derived vertical structural data, we quantified land cover composition and vertical structural characteristics for detached, single-family residential parcels. These data were combined with socioeconomic and demographic datasets from the 2010 US Census and local government agencies and used in Random Forest analyses of outdoor water use estimated from residential water meter records, with separate analyses conducted using parcels and census block groups as sampling units. Conditional variable importance measures from Random Forest analyses and comparisons of the predictive accuracy of models developed using subsets of explanatory variables were used to assess the relative importance of physical and socioeconomic variables in predicting outdoor water use. Models developed using the subset of land cover variables had the highest predictive accuracy, followed by vertical structural variables, and lastly, socioeconomic/demographic variables. At both the parcel and census block group scale, there was significant spatial clustering in outdoor water use as indicated by various spatial statistical analyses. Our approach demonstrates the value of high resolution land cover and structure data for understanding urban water use patterns and can be used for targeting water conservation efforts. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Urban water; Irrigation; Lidar; Remote sensing; GIS; Colorado (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11269-015-1034-7

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