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    Irrigation scheduling decision support

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    azu_td_9817330_sip1_m.pdf
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    Author
    Fox, Fred Andrew
    Issue Date
    1997
    Keywords
    Engineering, Agricultural.
    Engineering, System Science.
    Operations Research.
    Advisor
    Slack, Donald C.
    
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    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Irrigation scheduling using the soil water balance approach has been recommended to irrigators for many years. Reasonably good results are normally obtained by researchers using carefully quantified inputs. Irrigators in production agriculture may estimate inputs and then question the validity of the method when the irrigation recommendations conflict with present irrigation schedules. By associating each input with an interval representing possible bias based on the way the input was estimated, and solving the irrigation scheduling model using the intervals as inputs, the output was associated with an interval representing possible bias. This method was also used to evaluate possible bias associated with growing degree day based crop coefficient curves developed from Arizona crop consumptive use measurements. For comparison purposes, roughly estimated inputs based on irrigation system type, soil type, area weather data and available crop coefficient curves were used as default intervals. Improved input intervals consisted of observed irrigation system performance, soil property measurements, local weather data and theoretical improvements in crop coefficient curves. For surface irrigation, field observation of plant stress and soil water content showed the greatest potential to improve irrigation date predictions. For buried drip under a row crop, accuracy of the predicted daily irrigation rate was most improved by a better estimate of irrigation efficacy.
    Type
    text
    Dissertation-Reproduction (electronic)
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Agricultural & Biosystems Engineering
    Degree Grantor
    University of Arizona
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