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Combination of Sentinel-2 Satellite Images and Meteorological Data for Crop Water Requirements Estimation in Intensive Agriculture

Author

Listed:
  • Jaouad El Hachimi

    (Team of Remote Sensing and GIS Applied to the Geosciences and the Environment, Faculty of Sciences and Techniques, Beni Mellal 23000, Morocco)

  • Abderrazak El Harti

    (Team of Remote Sensing and GIS Applied to the Geosciences and the Environment, Faculty of Sciences and Techniques, Beni Mellal 23000, Morocco)

  • Rachid Lhissou

    (INRS—Centre Eau Terre Environnement, 490, de la Couronne, Québec City, QC G1K 9A9, Canada)

  • Jamal-Eddine Ouzemou

    (Team of Remote Sensing and GIS Applied to the Geosciences and the Environment, Faculty of Sciences and Techniques, Beni Mellal 23000, Morocco)

  • Mohcine Chakouri

    (Team of Remote Sensing and GIS Applied to the Geosciences and the Environment, Faculty of Sciences and Techniques, Beni Mellal 23000, Morocco)

  • Amine Jellouli

    (Team of Remote Sensing and GIS Applied to the Geosciences and the Environment, Faculty of Sciences and Techniques, Beni Mellal 23000, Morocco)

Abstract

In arid and semi-arid regions, agriculture is an important element of the national economy, but this sector is a large consumer of water. In a context of high pressure on water resources, appropriate management is required. In semi-arid, intensive agricultural systems, such as the Tadla irrigated perimeter in central Morocco, a large amount of water is lost by evapotranspiration (ET), and farmers need an effective decision support system for good irrigation management. The main objective of this study was to combine a high spatial resolution Sentinel-2 satellite and meteorological data for estimating crop water requirements in the irrigated perimeter of Tadla and qualifying its irrigation strategy. The dual approach of the FAO-56 (Food and Agriculture Organization) model, based on the modulation of evaporative demand, was used for the estimation of crop water requirements. Sentinel-2A temporal images were used for crop type mapping and deriving the basal crop coefficient (Kcb) based on NDVI data. Meteorological data were also used in crop water requirement simulation, using SAMIR (satellite monitoring of irrigation) software. The results allowed for the spatialization of crop water requirements on a large area of irrigated crops during the 2016–2017 agricultural season. In general, the crops’ requirement for water is at its maximum during the months of March and April, and the critical period starts from February for most crops. Maps of water requirements were developed. They showed the variability over time of crop development and their estimated water requirements. The results obtained constitute an important indicator of how water should be distributed over the area in order to improve the efficiency of the irrigation scheduling strategy.

Suggested Citation

  • Jaouad El Hachimi & Abderrazak El Harti & Rachid Lhissou & Jamal-Eddine Ouzemou & Mohcine Chakouri & Amine Jellouli, 2022. "Combination of Sentinel-2 Satellite Images and Meteorological Data for Crop Water Requirements Estimation in Intensive Agriculture," Agriculture, MDPI, vol. 12(8), pages 1-17, August.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:8:p:1168-:d:881306
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    References listed on IDEAS

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