Discussions and Closures Closure to “Interactive Irrigation Tool for Simulating Smart Irrigation Technologies in Lawn Turf” by N. A. Dobbs, K. W. Migliaccio, M. D. Dukes, K. T. Morgan, and Y. C. Li DOI: 10.1061/(ASCE)IR.1943-4774.0000612 Kati W. Migliaccio, P.E. 1 ; Michael D. Dukes, P.E. 2 ; Nicole A. Dobbs 3 ; Kelly T. Morgan 4 ; and Yuncong Li 5 1 Associate Professor, Agricultural and Biological Engineering Dept., Univ. of Florida, 18905 SW 280th St., Homestead, FL 33031 (corresponding author). E-mail: klwhite@ufl.edu 2 Professor, Agricultural and Biological Engineering Dept., Univ. of Florida, P.O. Box 110570, Gainesville, FL 32611-0570. E-mail: mddukes@ ufl.edu 3 Graduate Student, Biological and Agricultural Engineering Dept., North Carolina State Univ., Campus Box 7625, Raleigh, NC 27695. E-mail: nadobbs@ncsu.edu 4 Associate Professor, Soil and Water Science Dept., Univ. of Florida, 2685 State Rd. 29 North, Immokalee, FL 34142. E-mail: conserve@ufl.edu 5 Professor, Soil and Water Science Dept., Univ. of Florida, 18905 SW 280th St., Homestead, FL 33031. E-mail: yunli@ufl.edu The original paper published in 2013 described a new interactive irrigation tool that could be used to simulate different irrigation technologies in urban turf systems, that is, time-based irrigation, time-based irrigation with rain sensor, time-based irrigation with soil water sensor, and evapotranspiration (ET) controller. The origi- nal paper introduced a water balance–based model and compared model simulated data with measured data. Recently, a discussion on the original paper was written and submitted. The writers’ response for that discussion is as follows. Inclusion of Additional Literature The discusser identifies additional literature review on smart irri- gation controllers from three references (Vasanth 2008; Grabow et al. 2009, 2013). The research from these authors does relate to the topic and provides additional literature review on soil moisture–based and ET-based smart irrigation. However, the original paper did provide over 15 references related to smart irrigation technology and the objectives of the original paper were not to provide an extensive literature review. The discusser also includes additional literature in the discus- sion on available water, readily available water, water stress, and deficit. The concepts were presented in the original paper as part of the model decision-making process. Each component was de- fined and its role in the model was explained. Those unfamiliar with the concept would benefit from the discussion. As part of the water stress concept, the discusser discusses the stress crop co- efficient (K s ) from Allen et al. (1998) as used by McCready and Dukes (2009) to include depletion of soil water in the estimation of ET. The authors did not include the water stress crop coefficient factor in their estimation as they assumed that the conditions were well watered and did not suffer significant water stress. However, this is a viable concept and could be implemented if deemed necessary and resulting in significant changes in model results. Water Balance Equation The interactive irrigation tool model is based on a typical water balance equation with a daily time step. The equation presented in the original paper as Eq. (2) is as follows: SWC iþ1 ¼ SWC i þ R i þ IRR i - ET ci - Q i - PERC i where SWC = soil water content; R = rainfall; IRR = irrigation; ET = evapotranspiration; Q = runoff; and PERC = deep percolation. The discusser noted an error in the subscript of this equation for the SWC term and proposed the following equation: SWC iþ1 ¼ SWC i þ R iþ1 þ IRR iþ1 - ET ciþ1 - Q iþ1 - PERC iþ1 ð1Þ The writers believe the discusser is correct that there was an error in the subscripts of Eq. (2) in the original paper. The writers would also like to note that this original daily time step model has been modified into an hourly time step model and submitted for publication. The hourly time step model has been renamed Your Virtual Lawn Tool (Migliaccio 2014). The interactive irrigation tool, now updated with an hourly time step (Migliaccio et al., unpublished, 2013), is meant to be an exploratory model for evaluating different irrigation technologies using real-time data. The tool is not meant to provide irrigation water requirements. References Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (1998). “Crop evapo- transpiration: Guidelines for computing crop requirements. ” Irrigation and Drainage Paper No. 56, Food and Agricultural Organization of the United Nations, Rome. Grabow, G. L., Dukes, M., and Thapa, B. (2009). “The use of soil-water sensors in turf irrigation control-how effective are they?” The World Environmental and Water Resources Congress, Great Rivers. Grabow, G. L., Ghali, I. E., Huffman, R. L., Miller, G. L., Bowman, D., and Vasanth, A. (2013). “Water application efficiency and adequacy of ET- Based and soil moisture-based irrigation controllers for turfgrass irriga- tion. ” J. Irrig. Drain. Eng., 10.1061/(ASCE)IR.1943-4774.0000528, 113–123. McCready, M., and Dukes, M. D. (2009). “Evaluation of irrigation scheduling efficiency and adequacy by various control technologies compared to theoretical irrigation requirement. ” Proc., World Environ- mental and Water Resources Congress. Migliaccio, K. W. (2014). “Your virtual lawn tool. ” Florida Automated Weather Network, 〈http://irrigationtool.appspot.com/〉 (Jun. 5, 2014). Vasanth, A. (2008). “Evaluation of evapotranspiration-based and soil- moisture-based irrigation control in turf. ” M.S. thesis, Dept. of Biological and Agricultural Engineering, North Caroline State Univ., Raleigh, NC. © ASCE 07014049-1 J. Irrig. Drain Eng. J. Irrig. 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