WaterSense
®
Water Budget Approach
is likely to lead to a landscape that has more “curb appeal” and increases the value of the home,
benefiting both the environment and the homeowner.
WaterSense chose a well-maintained lawn composed entirely of cool season turfgrass as the
baseline, or conventional, model and a 30 percent reduction in associated water use as the
reduction that would result in water efficiency. This does not mean that WaterSense believes a
lawn should be watered with 70 percent of the water it requires, but that a plant mix should be
selected that would use 30 percent less water than a landscape composed entirely of turf. The
data used to calculate water use, discussed below, is modeled across the entire United States
by zip code, resulting in site-specific allotments. Therefore, while everyone must achieve the
same minimum percentage reduction, the actual requirement, in gallons of water, varies greatly
based on what is appropriate for each region. Additionally, the data are conservative in nature in
order to result in a landscape capable of withstanding the most challenging months of the year.
Data
The tool requires two climate-based inputs in addition to the types of vegetation planted and the
types of irrigation equipment installed. These two climate-based inputs are local reference
evapotranspiration (ET
o
) and rainfall. In order to make an easy-to-use tool, it was imperative to
have a standardized set of data that covered the entire country. While there are numerous local
sources of rainfall data, local ET
o
, data sets are scarce. However, the International Water
Management Institute (IWMI) produced a World Water and Climate Atlas
(www.iwmi.cgiar.org/WAtlas/Default.aspx
) that used 1961–1990 weather station data across the
world to model monthly summary data for a number of parameters, including standardized
Penman-Monteith reference evapotranspiration rates. The U.S. data were extracted and
summarized with an average value for each zip code using ESRI ArcGIS version 9.3.
2
In order
to be consistent, both in terms of actual data and the process used to model it, WaterSense also
extracted the 1961–1990 precipitation data to create the Water Budget Data Finder
. After the
user enters a zip code, the Water Budget Data Finder displays the peak watering month,
associated ET
o,
and associated rainfall amounts for that zip code. Builders must use the values
provided by the Water Budget Data Finder in the WaterSense Water Budget Tool.
WaterSense designated the peak watering month to be the month when ET
o
exceeds
precipitation by the greatest amount. This month was chosen because it identifies the month
during which the landscape will require the most supplemental irrigation. For locations where
precipitation always exceeds ET
o
, the peak watering month is the month with the highest ET
o
.
The tool also requires the use of a landscape coefficient for each category of vegetation
planted. Theoretically, these coefficients reduce ET
o
by a percentage, based on species type, to
portray the water needs of each plant. While extensive research has been conducted on the
water needs of various types of turfgrasses, very little data exists on the water needs of other
vegetation, including groundcovers, shrubs, and trees. Additionally, the landscape coefficient
varies depending on location, meaning that the available data cannot automatically be ascribed
to the same species in different regions. However, vegetation can be described in broad
categories as high water-using, medium water-using, or low water-using. In order to make a
functional tool, WaterSense has assigned relative factors to each category within the broad
plant types: trees, shrubs, groundcover, and turfgrass. The coefficients chosen were based on
2
More information on this process is available at:
www.epa.gov/watersense/nhspecs/wb_data_finder.html
.
Version 1.02 2 July 24, 2014