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Spatial variability of coffee plant water consumption based on the SEBAL algorithm

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DataCite Commons2020-08-28 更新2024-07-27 收录
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https://scielo.figshare.com/articles/Spatial_variability_of_coffee_plant_water_consumption_based_on_the_SEBAL_algorithm/7453052/1
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ABSTRACT: Awareness of evapotranspiration (ET) and crop coefficient (Kc) is necessary for irrigation management in coffee crops. ET and Kc spatial variabilities are disregarded in traditional methods. Methods based on radiometric measurements have potential to obtain these spatialized variables. The Kc curve and spatial variability of actual evapotranspiration (ETa) were determined using images from Landsat 8 satellite. We used images of young and adult coffee plantations from OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors over a two-year period. Evapotranspiration was estimated using the Surface Energy Balance Algorithm for Land (SEBAL). Moreover, the reference evapotranspiration (ETo) was estimated through the Penman-Monteith method. We obtained the values for the evapotranspiration fraction (ETf), analogous to Kc, according to ET and ETo values. The study was conducted in Buritis, Minas Gerais State, Brazil, in areas cropped with Coffea arabica irrigated by central pivots. A comparative analysis was made using different statistical indices. Average ETa was 2.17 mm d−1 for young coffee plantations, , and the Kc mean value was 0.6. For adult coffee plantations, average ETa was 3.95 mm d−1, , and the K mean value was 0.85. The ET and K data obtained based on the SEBAL algorithm displayed similar values to studies that used traditional methods. This model has huge potential to estimate ET of different stages of coffee plantation for the region studied.
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SciELO journals
创建时间:
2018-12-12
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