Phys Chem Earth 23(4):443–448Ĭardenas-Lailhacar B, Dukes MD (2012) Soil moisture sensor landscape irrigation controllers: a review of multi-study results and future implications. Flora 196:405–430īusch J, Lösch R (1998) Stomatal behaviour and gas exchange of Sedges (Carex spp.) under different soil moisture regimes. doi: 10.1016/j.envexpbot.2007.02.007īusch J (2001) Characteristic values of key ecophysiologic parameters in the genus Carex. doi: 10.1111/j.īurkart S, Manderscheid R, Weigel H-J (2007) Design and performance of a portable gas exchange chamber system for CO 2- and H 2O-flux measurements in crop canopies. J Irrig Drain Eng 133(5):427–434īijoor NS, Czimczik CI, Pataki DE, Billings SA (2008) Effects of temperature and fertilization on nitrogen cycling and community composition of an urban lawn. doi: 10.1061/(asce)ir.1943-4774.0000391īaum-Haley M, Dukes MD, Miller GL (2007) Residential irrigation water use in Central Florida. Dissertation, University of Floridaīaum-Haley M, Dukes MD (2012) Validation of landscape irrigation reduction with soil moisture sensor irrigation controllers. Masters Abstracts International 45 (3)īaum-Haley M (2011) Irrigation conservation technology effectiveness and behavior of the domestic irrigator. doi: 10.1007/s1109-9īarnes JR (1977) Analysis of residential lawn water use. doi: 10.1016/j.agwat.2010.12.015īalogh J, Nagy Z, Foti S, Pinter K, Czobel S, Peli ER, Acosta M, Marek MV, Csintalan Z, Tuba Z (2007) Comparison of CO 2 and H 2O fluxes over grassland vegetations measured by the eddy-covariance technique and by open system chamber. FAO, RomeĪllen RG, Pereira LS, Howell TA, Jensen ME (2011) Evapotranspiration information reporting: I factors governing measurement accuracy. Food and Agricultural Organization’s version that is described in Irrigation and Drainage Paper No 56. Landsc Urban Plan 69(2–3):219–234Īllen RK, Pereira LS, Raes D, Smith M (1998) Crop Evapotranspiration: Guide lines for computing crop water requirements. The utilization of smart sensors was more important than the choice of turfgrass species for irrigation efficiency.Īlig RJ, Kline JD, Lichtenstein M (2004) Urbanization on the US landscape: looking ahead in the 21st century. Smart irrigation systems provided substantial water savings relative to a timer-based system, and prevented significant drainage losses. Differences in irrigation efficiency between landscapes were due mainly to irrigation application, which varied more than species water use. Runoff was less than 2 % in each landscape, and excess irrigation primarily drained below the root zone. Irrigation efficiencies (ET/applied irrigation) were 57 - 58 %, 86 – 97 %, and 78 - 80 % for the Typical, Alternative1, and Alternative2 landscapes, respectively. The stomatal conductance of sedge was lower than the other two species, but its ET was not lower due to higher leaf area. Soil moisture was similar in the Typical and Alternative2, while Alternative1 was drier in spring. The water applied to the Alternative1 was 54 % less than the water applied to the Typical landscape, and the water applied to the Alternative2 was 24 % less. ET was measured with a portable closed chamber and modeled using a Penman-Monteith approach, and the two methods agreed well. The “Alternative2” landscape had a cool-season native sedge and a “smart” weather station-based drip irrigation system. The “Alternative1” landscape had a warm-season paspalum and a “smart” soil moisture sensor-based irrigation system. The “Typical” landscape had a cool-season fescue and was irrigated by an automatic timer. We compared irrigation rates, soil moisture, evapotranspiration (ET), stomatal conductance, and water budgets of landscape ecosystems managed with different turfgrass species and irrigation technologies. The fate of irrigation in urban ecosystems is highly uncertain, due to uncertainties in urban ecohydrology.
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