Drought and rapid population growth strain urban water supplies throughout the urbanizing Intermountain West (IMW). Irrigated urban landscapes are the largest use of municipal water resources and can consume ≈60% of potable municipal water in the region (Kjelgren et al., 2000; Utah Division of Water Resources, 2003). Because it is a limited resource in the IMW, efficient water use in irrigated urban landscapes is a fundamental long-term conservation policy for managing increasing demand and limited and uncertain supplies (St. Hilaire et al., 2008).
Xeriscaping, low water use landscaping, and water efficient landscaping are key water conservation approaches promoted in periodically water-deficit regions of the United States (Smith and St. Hilaire, 1999). In practice, these techniques are generally synonymous and refer to landscaping specifically designed to reduce water use relative to uniform turfgrass landscapes (St. Hilaire et al., 2008). For simplicity, this study will use the term water-efficient landscaping to include mindful design, efficient irrigation systems, appropriate turf areas, appropriate plant material (turf and non-turf) choices, improved soil, mulching, and strategic maintenance.
Water-efficient landscaping can reduce water consumption without compromising landscape functionality or aesthetics (St. Hilaire et al., 2008). However, little research has quantified water needs of water-efficient landscapes compared with traditional landscapes, particularly regarding plant material. One 5-year study in Las Vegas, NV, showed single-family homes with water-efficient landscapes used 76% less water than turfgrass landscapes (Sovocool et al., 2006). However, those results were taken from a survey of voluntary participants such that traditional and water-efficient landscapes differed in many ways, including planting design, irrigation systems, and plant material. Because most water-efficient landscaping principles apart from plant material can be applied to any landscape, impact of plant selection alone is of research interest.
Many of these assumptions do not translate well to urban landscapes. Sufficient urban fetch and solar exposure for calculating ETo for a uniform plant surface complicate and limit weather station site selection (Eching and Snyder, 2005). Ideal urban weather station sites with a uniform plant surface are then at odds with the non-uniformity, small size, and ventilated roughness characteristics of urban landscapes. Moreover, plants in urban landscapes are diverse architectural types—trees, shrubs, perennials, turfgrass—manifesting a wide range of water use characteristics. Furthermore, urban landscape plants succeed when meeting appearance expectations rather than yielding a quantitative product. Biophysical diversity and appearance expectations suggest minimum water needs in a water-efficient landscape are a subjective threshold rather than an objective target (Shaw and Pittenger, 2004). This threshold is potentially much lower than what plants would use with unlimited water supply and may be achieved even when plants are water-limited or stressed. Consequently, a plant factor, Kp (Eching and Snyder 2005; EPA WaterSense, 2009), rather than a coefficient Kc, more candidly represents the attenuated relationship between heterogenous urban landscape biophysical water use and homogenous urban ETo. A Kp can characterize minimum water needs of general landscape plant types—woody and herbaceous—but can be species-specific for the few commonly used turfgrass species, because turf Kp may be equal to Kc when grasses are well-watered and obtain optimum growth and development.
Species complexity in distinguishing minimum plant needs from maximum, well-watered use constrains development of landscape Kp values useful to water-efficient landscape stakeholders. Well-watered Kp values for warm- and cool-season turfgrass species have been reasonably well characterized (Aronson et al., 1987; Carrow, 1995; Fry and Butler, 1989; Kopec et al., 1988), but minimum turfgrass water requirements have not. Plant factors have been reported for a number of landscape (tree, shrubs, herbaceous) species under well-watered (Beeson, 2005; Montague et al., 2004; Pannkuk et al., 2010) and minimum, water-limited conditions (Pittenger and Henry, 2005; Reid and Oki, 2008; Shaw and Pittenger, 2004). These reports cover a small percentage of the total number of possible landscape plants and how Kp values developed in one climate translate to a different climate is problematic (Kjelgren et al., 2005).
Further complicating water-efficient landscape water needs estimation, scaling an assemblage of Kp values up to part of or the entire urban landscape is an increasingly necessary but conceptually muddled process. Increasing use of ETo-based smart controllers demands input of a Kp for turf and typically mixed species landscape plants for setting irrigation schedules at the individual irrigation zone level. Policy needs for allocating a fixed amount of water to end users demands a Kp over an entire landscape (often referenced as Kl; see Costello et al., 2000) for setting water allocation at the policy level. Theoretical approaches to zone level or landscape level have suggested assigning K values grouped by plant types (tree, shrub, perennial, turf; EPA WaterSense, 2009; Water Use Efficiency Branch, 2009) or water use categorization (high–medium–low; Costello et al., 2000), each with various factors to correct for climate, plant density, and sometimes water stress (Bos et al., 2008; Eching and Snyder, 2005). However, there are little empirical data validating grouping of minimum water needs by plant type, water use categorization, or various correction factors (see Devitt and Morris, 2008; Pannkuk et al., 2010; Sachs et al., 1975).
Consequently, empirical data are needed to distinguish plant water use of different plant types and water use categorizations. This research was conducted under well-watered conditions in designed landscapes comprised of plant types such as turf, perennials, and woody plants. Once established, minimum water-efficient landscape water needs under water-limiting conditions may then be more clearly defined. Objectives of this study were to develop water balances for water-efficient landscapes with no soil water limits consisting of three putative water use characterizations—mesic, mixed and xeric—and plant material of three different types—woody, herbaceous perennial, and turf—to develop Kp values integrated at the irrigation zone and entire landscape level.
Allen, R.G., Walter, R., Elliot, R. & Howell, T. 2005a The ASCE standardized reference evapotranspiration equation. Amer. Soc. Civil Eng., Reston, VA.
Allen, R.G., Pereira, L.S., Smith, M., Raes, D. & Wright, J.L. 2005b FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions J. Irr. and Drainage Eng.-Asce 131 2 13
Ambrose, A.R., Sillett, S.C., Koch, G.W., van Pelt, R., Antoine, M.E., Dawson, T.E. & Meinzer, F. 2010 Effects of height on treetop transpiration and stomatal conductance in coast redwood (Sequoia sempervirens) Tree Physiol. 30 1260 1272
Aronson, L.J., Gold, A.J., Hull, R.J. & Cisar, J.L. 1987 Evapotranspiration of cool-season turfgrasses in the humid Northeast Agron. J. 79 901 905
Blonquist, J.M., Jones, S.B. & Robinson, D.A. 2006 Precise irrigation scheduling for turfgrass using a subsurface electromagnetic soil moisture sensor Agr. Water Mgt. 84 153 165
Bos, M.G., Kselik, R.A.L., Allen, R.G. & Molden, D. 2008 Water Requirements for Irrigation and the environment. 1st Ed. Springer, New York, NY.
Brown, P. & Kopec, D. 2000 Converting reference evapotranspiration into turf water use. Turf Irrigation Management Series II, The University of Arizona. 7 Mar. 2011. <http://ag.arizona.edu/pubs/water/az1195.pdf>.
Brown, P.W., Mancino, C.F., Young, M.H., Thompson, T.L., Wierenga, P.J. & Kopec, D.M. 2001 Penman Monteith crop coefficients for use with desert turf systems Crop Sci. 41 1197 1206
Carrow, R.N. 1995 Drought resistance aspects of turfgrasses in the Southeast—Evapotranspiration and crop coefficients Crop Sci. 35 1685 1690
Choudhury, B. & Monteith, J. 1986 Implications of stomatal response to saturation deficit for the heat balance of vegetation Agr. Meteorol. 36 215 225
Costello, L.R., Matheny, N.P. & Clark, J.R. 2000 The landscape coefficient method. In: A guide to estimating irrigation water needs of landscape planting in California. University of California Cooperative Extension, California Department of Water Resources, Sacramento, CA. <http://www.water.ca.gov/wateruseefficiency/docs/wucols00.pdf>.
Cuenca, R.H. 1989 Irrigation system design. Prentice Hall, Englewood, NJ.
Devitt, D.A. & Morris, R.L. 2008 Urban landscape water conservation and the species effect, p. 171–192. In: Beard, J.B. and M.P. Kenna. Water quality and quantity issues for turfgrasses in urban landscapes. The Council for Agricultural Science and Technology, Ames, IA.
Devitt, D.A., Morris, R.L. & Bowman, D.C. 1992 Evapotransportation, crop coefficients, and leaching fractions of irrigated desert turfgrass systems Agron. J. 84 717 723
Eching, S. & Snyder, R.L. 2005 Estimating urban landscape evapotranspiration. In: Walton, R. (ed.). Impacts of global climate change: World Water and Environmental Resources Congress, Anchorage, AK. 15–19 May. <http://cedb.asce.org/cgi/WWWdisplay.cgi?147023>.
EPA WaterSense 2009 WaterSense water budget approach. Environmental Protection Agency. 11 Mar. 2011. <http://www.epa.gov/WaterSense/docs/ws_water_budget_approach508.pdf>.
Ervin, E.H. & Koski, A.J. 1998 Drought avoidance aspects and crop coefficients of kentucky bluegrass and tall fescue turfs in the semiarid west Crop Sci. 38 788 795
Gao, Q., Yu, M., Zhang, X., Xu, H. & Huang, Y. 2005 Modelling seasonal and diurnal dynamics of stomatal conductance of plants in a semiarid environment Funct. Plant Biol. 32 583 598
Jia, X.H., Dukes, M.D. & Jacobs, J.M. 2009 Bahiagrass crop coefficients from eddy correlation measurements in central Florida Irrig. Sci. 28 5 15
Kjelgren, R., Montague, T. & Beeson, R. 2005 Water use and stomatal behavior of sweetgum (Liquidambar styraciflua L.) relative to reference evaporation in three contrasting regions Acta Hort. 664 353 360
Medeiros, J.S. & Pockman, W.T. 2010 Carbon gain and hydraulic limits on water use differ between size classes of Larrea tridentata J. Arid Environ. 74 1121 1129
Moller, A.L. & Gillies, R.R. 2008 Utah climate. 2nd Rd. USU Press, Logan, UT.
Montague, T., Kjelgren, R., Allen, R. & Wester, D. 2004 Water loss estimates for five recently transplanted landscape tree species in a semi-arid climate J. Environ. Hort. 22 189 196
Pannkuk, T.R., White, R.H., Steinke, K., Aitkenhead-Peterson, J.A., Chalmers, D.R. & Thomas, J.C. 2010 Landscape coefficients for single-and mixed-species landscapes HortScience 45 1529 1533
Pereira, A.R., Green, S.R. & Nova, N.A.V. 2007 Sap flow, leaf area, net radiation and the Priestley-Taylor formula for irrigated orchards and isolated trees Agr. Water Mgt. 92 48 52
Pittenger, D. & Henry, J.M. 2005 Refinement of urban landscape water requirements. University of California Cooperative Extension, Central Coast & South Region. 10 Mar. 2011. <http://groups.ucanr.org/CLUH/files/25773.pdf>.
Salo, C., Unnasch, R. & Wisnewski, C. 2008 Measuring vegetation with line-point intercept and line intercept methods. Sound Science White paper Series #3. 10 Mar. 2011. <http://www.sound-science.org/S2WhitePaper03LPI.pdf>.
Schleppi, P., Thimonier, A. & Walthert, L. 2011 Estimating leaf area index of mature temperate forests using regressions on site and vegetation data For. Ecol. Mgt. 261 601 610
Seraphin, A. & Guyenne, P. 2008 A flume experiment on the adjustment of the mean and turbulent statistics to a transition from short to tall sparse canopies Boundary-Layer Meteorol. 129 47 64
Shaw, D.A. & Pittenger, D.R. 2004 Performance of landscape ornamentals given irrigation treatments based on reference evapotranspiration Acta Hort. 664 607 614
Smith, C.S. & St. Hilaire, R. 1999 Xeriscaping in the urban environment, p. 241–250. In: Herrera, E.H. and J.G. Mexal (eds.). Ensuring sustainable development of arid lands. New Mexico J. Sci. 38. New Mexico Acad. Sci., Albuquerque, NM.
Sovocool, K.A., Morgan, M. & Bennett, D. 2006 An in-depth investigation of Xeriscape as a water conservation measure J. Amer. Water Works Assn. 98 82 93
St. Hilaire, R., Arnold, M.A., Wilkerson, D.C., Devitt, D.A., Hurd, B.H., Lesikar, B.J., Lohr, V.I., Martin, C.A., McDonald, G.V., Morris, R.L., Pittenger, D.R., Shaw, D.A. & Zoldoske, D.F. 2008 Efficient water use in residential urban landscapes HortScience 43 2081 2092
Stewart, J.R., Kjelgren, R., Johnson, P.G. & Kuhns, M.R. 2004 Soil-water-use characteristics of precision-irrigated buffalograss and Kentucky bluegrass. Online. Applied Turfgrass Sci. DOI:10.1094/ATS-2004-1118-01-RS.
Turner, N., Schulze, E. & Gollan, T. 1984 The responses of stomata and leaf gas exchange to vapour pressure deficits and soil water content Oecologia 63 338 342
United States Department of Agriculture 1968 Soil survey: Davis-Weber area, Utah. US Printing Office, Washington, DC.
Utah Division of Water Resources 2003 Utah's M&I water conservation plan: Investing in the future. 21 Feburary 2011. <http://www.water.utah.gov/M&I/plan7-14-03.pdf>.
van Genuchten, M.T. 1980 A closed-form equation for prediction the hydraulic conductivity of unsaturated soils Soil Sci. Soc. Amer. J. 44 892 898
Water Use Efficiency Branch 2009 Model water efficient landscape ordinance: Senate Bill SBx7-7. California Dept. Water Resources. 21 Jan. 2011. <http://www.water.ca.gov/wateruseefficiency/sb7/>.
West, A.G., Hultine, K.R., Jackson, T.L. & Ehlerninger, J.R. 2007 Differential summer water use by Pinus edulis and Juniperus osteosperma reflects contrasting hydraulic characteristics Tree Physiol. 27 1711 1720
White, R., Havlak, R., Nations, J., Pannkuk, T.R., Thomas, J.C., Chalmers, D.R. & Dewey, D. 2004 How much water is 'enough'? Using PET to develop water budgets for residential landscapes. TX Water Resources Institute TR-271, College Station, TX.