Abstract

Author(s): Williams, Alison, A; Chen, Yuting; Dunham, Camilla; Fuchs, Heidi; Price, Sarah; Stratton, Hannah | Abstract: Green lawns and landscaping are archetypical of the populated American landscape, and typically require irrigation, which corresponds to a significant fraction of residential, commercial, and institutional water use. In North American cities, the estimated portion of residential water used for outdoor purposes ranges from 22-38% in cooler climates up to 59-67% in dry and hot environments, while turfgrass coverage within the United States spans 11.1-20.2 million hectares (Milesi et al. 2009). One national estimate uses satellite and aerial photography data to develop a relationship between impervious surface and lawn surface area, yielding a conservative estimate of 16.4 (± 3.6) million hectares of lawn surface area in the United States—an area three times larger than that devoted to any irrigated crop (Milesi et al. 2005). One approach that holds promise for cutting unnecessary outdoor water use is the increased deployment of “smart” irrigation controllers to increase the water efficiency of irrigation systems. This report describes the methodology and inputs employed in a mathematical model that quantifies the effects of the U.S. Environmental Protection Agency’s WaterSense labeling program for one such type of controller, weather-based irrigation controllers (WBIC). This model builds off that described in “Methodology for National Water Savings Model and Spreadsheet Tool–Outdoor Water Use” and uses a two-tiered approach to quantify outdoor water savings attributable to the WaterSense program for WBIC, as well as net present value (NPV) of that savings. While the first iteration of the model assessed national impacts using averaged national values, this version begins by evaluating impacts in three key large states that make up a sizable portion of the irrigation market: California, Florida, and Texas. These states are considered to be the principal market of “smart” irrigation controllers that may result in the bulk of national savings. Modeled water savings and net present value for these three states should be more accurate and representative than the averaged national values given state-specific inputs such as lot size, water price, and housing stock. To complete the picture of national impacts, the remaining WBIC shipments not assigned to these three states are assessed using the original methodology based on the averaged national values.

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