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Progress in Developing Scale-Able Approaches to Field-Scale Water Accounting Based on Remote Sensing

Author

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  • Rutger Willem Vervoort

    (Data Analytics for Resources and the Environment Industry Transformation Training Centre and School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia)

  • Ignacio Fuentes

    (WaterTechnology Pty, Ltd., Notting Hill, VIC 3168, Australia)

  • Joost Brombacher

    (eLEAF B.V., 6703CT Wageningen, The Netherlands)

  • Jelle Degen

    (eLEAF B.V., 6703CT Wageningen, The Netherlands)

  • Pedro Chambel-Leitão

    (Hidromod LDA, Porto Salvo, 2740-278 Lisboa, Portugal)

  • Flávio Santos

    (Hidromod LDA, Porto Salvo, 2740-278 Lisboa, Portugal)

Abstract

To increase water productivity and assess water footprints in irrigated systems, there is a need to develop cheap and readily available estimates of components of water balance at fine spatial scales. Recent developments in satellite remote sensing platforms and modelling capacities have opened opportunities to address this need, such as those being developed in the WaterSENSE project. This paper showed how evapotranspiration, soil moisture, and farm-dam water volumes can be quantified based on the Copernicus data from the Sentinel satellite constellation. This highlights distinct differences between energy balance and crop factor approaches and estimates that can be derived from the point scale to the landscape scale. Differences in the results are related to assumptions in deriving evapotranspiration from remote sensing data. Advances in different parts of the water cycle and opportunities for crop detection and yield forecasting mean that crop water productivity can be quantified at field to landscape scales, but uncertainties are highly dependent on input data availability and reference validation data.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2732-:d:759168
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    References listed on IDEAS

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    1. Safi, Abdur Rahim & Karimi, Poolad & Mul, Marloes & Chukalla, Abebe & de Fraiture, Charlotte, 2022. "Translating open-source remote sensing data to crop water productivity improvement actions," Agricultural Water Management, Elsevier, vol. 261(C).
    2. Matthew Rodell & Isabella Velicogna & James S. Famiglietti, 2009. "Satellite-based estimates of groundwater depletion in India," Nature, Nature, vol. 460(7258), pages 999-1002, August.
    3. 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.
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    Cited by:

    1. Fuentes, Ignacio & Vervoort, R. Willem & McPhee, James & Rojas, Luis A. Reyes, 2024. "Agricultural water accounting: Complementing a governance monitoring schema with remote sensing calculations at different scales," Agricultural Water Management, Elsevier, vol. 292(C).

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