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HydroLOGIC: An irrigation management system for Australian cotton

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  • Richards, Q.D.
  • Bange, M.P.
  • Johnston, S.B.

Abstract

The worldwide need to improve water use efficiency within irrigated agriculture has been recognised in response to environmental concerns and conflicts in resource use. Within the Australian cotton industry, the imperative to reduce water use and optimise irrigation management through the understanding of risk, using information generated by computerised decision aids was identified and subsequently developed into the HydroLOGIC irrigation management software. This paper summarises the attributes of the HydroLOGIC irrigation management software, with particular emphasis on functionality and its application to irrigation decisions within the Australian cotton industry. The software development process is documented to provide direction for future software application initiatives, with particular emphasis on a process of user feedback, evaluation and support requirements providing direction to software development. On-farm experiments throughout the development period allowed the validation of internal software logic, irrigator decision processes, and the OZCOT cotton growth model. The software demonstrated the ability to improve yield and water use efficiency by optimising strategic and tactical irrigation decisions in the Australian furrow irrigation cotton production system. In 7 of the 11 on-farm experiments conducted, the use of HydroLOGIC helped improve overall field water use efficiency by optimising the timing of irrigation events or by indicating further irrigations would not provide yield or maturity benefits. The paper also presents useful insights into the development of software targeted for irrigation utilising in-field measurements of soil water, crop growth and a crop growth simulation model.

Suggested Citation

  • Richards, Q.D. & Bange, M.P. & Johnston, S.B., 2008. "HydroLOGIC: An irrigation management system for Australian cotton," Agricultural Systems, Elsevier, vol. 98(1), pages 40-49, July.
    • Handle: RePEc:eee:agisys:v:98:y:2008:i:1:p:40-49
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    References listed on IDEAS

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    Cited by:

    1. Mabhaudhi, Tafadzwanashe & Dirwai, Tinashe Lindel & Taguta, Cuthbert & Sikka, Alok & Lautze, Jonathan, 2023. "Mapping Decision Support Tools (DSTs) on agricultural water productivity: A global systematic scoping review," Agricultural Water Management, Elsevier, vol. 290(C).
    2. Itzel Inti Maria Donati & Davide Viaggi & Zorica Srdjevic & Bojan Srdjevic & Antonella Di Fonzo & Teresa Del Giudice & Orlando Cimino & Andrea Martelli & Anna Dalla Marta & Roberto Henke & Filiberto A, 2023. "An Analysis of Preference Weights and Setting Priorities by Irrigation Advisory Services Users Based on the Analytic Hierarchy Process," Agriculture, MDPI, vol. 13(8), pages 1-15, August.
    3. Darouich, Hanaa & Gonçalves, José M. & Muga, André & Pereira, Luis S., 2012. "Water saving vs. farm economics in cotton surface irrigation: An application of multicriteria analysis," Agricultural Water Management, Elsevier, vol. 115(C), pages 223-231.
    4. Luo, Qunying & Bange, Michael & Braunack, Michael & Johnston, David, 2016. "Effectiveness of agronomic practices in dealing with climate change impacts in the Australian cotton industry — A simulation study," Agricultural Systems, Elsevier, vol. 147(C), pages 1-9.
    5. Ara, Iffat & Turner, Lydia & Harrison, Matthew Tom & Monjardino, Marta & deVoil, Peter & Rodriguez, Daniel, 2021. "Application, adoption and opportunities for improving decision support systems in irrigated agriculture: A review," Agricultural Water Management, Elsevier, vol. 257(C).
    6. Luo, Qunying & Behrendt, Karl & Bange, Michael, 2017. "Economics and risk of adaptation options in the Australian cotton industry," Agricultural Systems, Elsevier, vol. 150(C), pages 46-53.

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