Evaluation of Irrigation Scheduling Efficiency and Adequacy by Various Control Technologies Compared to Theoretical Irrigation Requirement

McCready, Mary S.; Dukes, Michael D.

doi:10.1061/41036(342)430

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…The different aspects of irrigation in agricultural water management, such as irrigation efficiency [VALIPOUR, MONTAZAR 2012], soil salinity [DU PLES-SIS 1985], water-saving [MONTENEGRO et al 2010;VALIPOUR 2016a, b, c], sustainable development [VALIPOUR 2014a, b;VALIPOUR 2017;YANNOPOULOS et al 2015], soil water management [STEINER, KELLER 1992], evapotranspiration [MCCREADY, DUKES 2009;VALIPOUR 2014a, b;2015a, b, c, d, e, f, g, h, i;VALIPOUR, ESLAMIAN 2014;VALIPOUR et al 2017a, b;VALIPOUR, GHOLAMI SEFIDKOUHI 2017] and crop yield [WU et al 2013] have been investigated in previous works. TURRAL et al [2010] showed that investment is one of the most effective factors on area equipped for irrigation to 2050.…”

Section: Introductionmentioning

confidence: 99%

Global experience on irrigation management under different scenarios

Valipour

2017

Journal of Water and Land Development

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This study aims to assess global experience on agricultural water management under different scenarios. The results showed that trend of permanent crops to cultivated area, human development index (HDI), irrigation water requirement, and percent of total cultivated area drained is increasing and trend of rural population to total population, total economically active population in agriculture to total economically active population, value added to gross domestic production (GDP) by agriculture, and the difference between national rainfall index (NRI) and irrigation water requirement is decreasing. The estimating of area equipped for irrigation in 2035 and 2060 were studied acc. to the three scenarios: I -the values of the main indices would be changed by the same slope of the past half of century, II and III -the slopes would be decreased by 30% and 50% respectively. The minimum and maximum values of pressure on renewable water resources by irrigation, are related to the third and first scenarios by 2035 (6.1%) and 2060 (9.2%), respectively.

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Section: Introductionmentioning

confidence: 99%

Global experience on irrigation management under different scenarios

Valipour

2017

Journal of Water and Land Development

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“…Those unfamiliar with the concept would benefit from the discussion. As part of the water stress concept, the discusser discusses the stress crop coefficient (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.…”

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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

Migliaccio

Dukes

Dobbs

et al. 2015

J. Irrig. Drain Eng.

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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 original 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 LiteratureThe discusser identifies additional literature review on smart irrigation controllers from three references (Vasanth 2008;Grabow et al. 2009Grabow et al. , 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 discussion 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 defined 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 coefficient (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 EquationThe 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: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: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...

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Discussion of “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

Yıldırım

2015

J. Irrig. Drain Eng.

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Evaluation of Irrigation Scheduling Efficiency and Adequacy by Various Control Technologies Compared to Theoretical Irrigation Requirement

Cited by 6 publications

References 5 publications

Global experience on irrigation management under different scenarios

Global experience on irrigation management under different scenarios

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

Discussion of “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

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