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A Method to Estimate Residential Irrigation from Potable Meter Data
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Applied Engineering in Agriculture. 32(2): 245-250. (doi: 10.13031/aea.32.11194) @2016
Authors: Consuelo C. Romero, Michael D Dukes
Keywords: Estimated irrigation, Florida, Indoor water use, Landscape irrigation requirements, Minimum month method, Observed irrigation, Per capita method.
Abstract. A methodology to estimate residential irrigation using monthly metered total water use and metered irrigation data is presented here in a case study in central Florida. The objective of this article was to determine the most accurate method of indoor/outdoor water use separation for single-family homes. In this study, 1781 homes located in Orlando, Florida, were analyzed. The analysis was based on monthly billing records for the January 2006-June 2009 period where total metered water use and separately metered irrigation data were available. Residential irrigation was estimated based on minimum month and per capita methods to derive indoor use, and by assuming three different irrigable areas for each home. Average total water use was 70.4 m3 month-1 and average observed irrigation was 45.8 m3 month-1. This method was calibrated and validated using metered irrigation data. Metered irrigation data indicated that irrigation accounted for 64% of the total water use. Observed indoor water use was fairly constant across the year with an average of 24.6 ± 1.3 m3 month-1, and values were compared to those estimated by the minimum month method and the per capita method. The minimum month method over-estimated indoor water use as 61.3 m3 month-1 whereas the per capita method estimated the value as 16.9 m3 month-1. Observed annual cumulative irrigation was 60% higher than the gross irrigation requirement and this excess irrigation varied from 10% to more than 300% depending on month with most excess in the winter months. The calibration and validation demonstrated that around 60% to 99% of the variability of the observed data can be reproduced by this proposed method. However, this approach maintains a limited area of potential application just for central Florida.
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