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Monitoring irrigation water use over paddock scales using climate data and landsat observations

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  • Bretreger, David
  • Yeo, In-Young
  • Quijano, Juan
  • Awad, John
  • Hancock, Greg
  • Willgoose, Garry

Abstract

Irrigated agriculture has been identified as using approximately 72% of water globally. Many regions of the world are subject to water sharing plans that cross government boarders which contain a mixture of management policies, leading to the requirement to monitor irrigation water use. The study reported here aims to develop and test an approach using Landsat observations to monitor irrigation water use over paddock scales without the need for in-situ observations, ground data or knowledge of planting dates. Using conservative assumptions about agricultural land management practice (i.e. negligible runoff, drainage and soil moisture change), the irrigation is calculated over 25 m x 25 m Landsat images. The approach uses a combination of three vegetation indices derived from Landsat images to calculate crop coefficients (Kc) based on multiple published relationships. These are combined through the FAO56 methodology using gridded rainfall and two gridded reference evapotranspiration (ETo) products to estimate actual evapotranspiration, providing six ETo - Kc combinations which are then compared to actual/recorded irrigation volumes from test sites. The method was tested over an almond farm, two vineyards and a cotton field; in addition to Goulburn-Murray Water’s (GMW) individual farm scale sites with unknown crops, all located within Australia. The developed approach provided estimated irrigation volumes that closely matched measured data for almond and cotton farms, while vineyards returned less accurate results due to localised management techniques that do not agree with land management assumptions made. The results from GMW showed some indication of the irrigation water use, although more details of the site being assessed needs to be available (i.e. crop type and extent). This study demonstrates the ability of certain remote sensing Kc relationships for sensing irrigation water use and shows the potential applications of the developed approach in monitoring irrigation over paddock scale environments.

Suggested Citation

  • Bretreger, David & Yeo, In-Young & Quijano, Juan & Awad, John & Hancock, Greg & Willgoose, Garry, 2019. "Monitoring irrigation water use over paddock scales using climate data and landsat observations," Agricultural Water Management, Elsevier, vol. 221(C), pages 175-191.
    • Handle: RePEc:eee:agiwat:v:221:y:2019:i:c:p:175-191
    DOI: 10.1016/j.agwat.2019.05.002
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    References listed on IDEAS

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    1. Jayanthi, Harikishan & Neale, Christopher M.U. & Wright, James L., 2007. "Development and validation of canopy reflectance-based crop coefficient for potato," Agricultural Water Management, Elsevier, vol. 88(1-3), pages 235-246, March.
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    1. Gonçalves, Ivo Zution & Mekonnen, Mesfin M. & Neale, Christopher M.U. & Campos, Isidro & Neale, Michael R., 2020. "Temporal and spatial variations of irrigation water use for commercial corn fields in Central Nebraska," Agricultural Water Management, Elsevier, vol. 228(C).
    2. Bretreger, David & Yeo, In-Young & Hancock, Greg, 2022. "Quantifying irrigation water use with remote sensing: Soil water deficit modelling with uncertain soil parameters," Agricultural Water Management, Elsevier, vol. 260(C).
    3. Rutger Willem Vervoort & Ignacio Fuentes & Joost Brombacher & Jelle Degen & Pedro Chambel-Leitão & Flávio Santos, 2022. "Progress in Developing Scale-Able Approaches to Field-Scale Water Accounting Based on Remote Sensing," Sustainability, MDPI, vol. 14(5), pages 1-22, February.
    4. Dimitrios Tassopoulos & Dionissios Kalivas & Rigas Giovos & Nestor Lougkos & Anastasia Priovolou, 2021. "Sentinel-2 Imagery Monitoring Vine Growth Related to Topography in a Protected Designation of Origin Region," Agriculture, MDPI, vol. 11(8), pages 1-20, August.
    5. Rigas Giovos & Dimitrios Tassopoulos & Dionissios Kalivas & Nestor Lougkos & Anastasia Priovolou, 2021. "Remote Sensing Vegetation Indices in Viticulture: A Critical Review," Agriculture, MDPI, vol. 11(5), pages 1-20, May.

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