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Spatial variability quantification of maize water consumption based on Google EEflux tool

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  • de Oliveira Costa, Jéfferson
  • José, Jefferson Vieira
  • Wolff, Wagner
  • de Oliveira, Niclene Ponce Rodrigues
  • Oliveira, Rafaella Conceição
  • Ribeiro, Nathália Lopes
  • Coelho, Rubens Duarte
  • da Silva, Tonny José Araújo
  • Bonfim-Silva, Edna Maria
  • Schlichting, Alessana Franciele

Abstract

The evapotranspiration (ET) and crop coefficient (Kc) spatial variabilities are disregarded in traditional methods of evapotranspiration estimation based on lysimeters. With the development of remote sensing techniques, the estimative of ET on agricultural areas, in a specialized way, has become possible through the use of algorithms based on the surface energy balance such as the METRIC and its automated version, featured on the Google Earth Engine Evapotranspiration Flux (EEFlux) platform. This study was carried out at a center pivot irrigated area located in the city of Primavera do Leste, MT, Brazil. One growing season (2016) of the specie Zea mays (maize) was analyzed. Using processed images from the Landsat 8 satellite, within the EEFlux platform, the spatial variability of the actual evapotranspiration (ETa) and the Kc curve of this crop was determined. The water use efficiency (WUE) was also determined. A comparative analysis was performed using different statistical indices: root mean square error (RMSE), the mean bios error (MBE) and the index of agreement (d). The ETa for maize ranged from 1.3–4.1 mm d−1 and the Kc obtained ranged from 0.3 to 1.2. The average WUE of maize was 1.13 kg m-3. The method of estimation of ETa and Kc spatialized using the Google EEFlux platform made possible the understanding the spatial variability of these two variables and, therefore, this application has high potential to estimate the ETa and Kc on different stages of maize crop growth cycle.

Suggested Citation

  • de Oliveira Costa, Jéfferson & José, Jefferson Vieira & Wolff, Wagner & de Oliveira, Niclene Ponce Rodrigues & Oliveira, Rafaella Conceição & Ribeiro, Nathália Lopes & Coelho, Rubens Duarte & da Silva, 2020. "Spatial variability quantification of maize water consumption based on Google EEflux tool," Agricultural Water Management, Elsevier, vol. 232(C).
    • Handle: RePEc:eee:agiwat:v:232:y:2020:i:c:s0378377419312089
    DOI: 10.1016/j.agwat.2020.106037
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    References listed on IDEAS

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    1. Geerts, Sam & Raes, Dirk, 2009. "Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas," Agricultural Water Management, Elsevier, vol. 96(9), pages 1275-1284, September.
    2. Kang, Shaozhong & Gu, Binjie & Du, Taisheng & Zhang, Jianhua, 2003. "Crop coefficient and ratio of transpiration to evapotranspiration of winter wheat and maize in a semi-humid region," Agricultural Water Management, Elsevier, vol. 59(3), pages 239-254, April.
    3. Kamali, Mohammad Ismaeil & Nazari, Rouzbeh, 2018. "Determination of maize water requirement using remote sensing data and SEBAL algorithm," Agricultural Water Management, Elsevier, vol. 209(C), pages 197-205.
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    1. Parsinejad, Masoud & Raja, Omid & Chehrenegar, Behdad, 2022. "Practical analysis of remote sensing estimations of water use for major crops throughout the Urmia Lake basin," Agricultural Water Management, Elsevier, vol. 260(C).
    2. Usha Poudel & Haroon Stephen & Sajjad Ahmad, 2021. "Evaluating Irrigation Performance and Water Productivity Using EEFlux ET and NDVI," Sustainability, MDPI, vol. 13(14), pages 1-26, July.

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