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

Abstract

Awareness of evapotranspiration (ET) and crop coefficient (K c) is necessary for irrigation management in coffee crops. ET and K c spatial variabilities are disregarded in traditional methods. Methods based on radiometric measurements have potential to obtain these spatialized variables. The K c curve and spatial variability of actual evapotranspiration (ET a) 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 (ET o) was estimated through the Penman-Monteith method. We obtained the values for the evapotranspiration fraction (ET f), analogous to K c , according to ET and ET o 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 ET a was 2.17 mm d-1 for young coffee plantations, , and the K c mean value was 0.6. For adult coffee plantations, average ET a was 3.95 mm d-1 , , and the K c mean value was 0.85. The ET c and K c 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.

Determining the Leaf Area Index and Percentage of Area Covered by Coffee Crops Using UAV RGB Images

“…The studies carried out by [8] reached values of LAI at the upper part of the plant of 1.78 and of 6.5, on average, at the lower portion. In another study, [47] concluded that the LAI value was between 0 and 6.…”

Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm

“…The knowledge of crop evapotranspiration (ET) is critical for irrigation management (Gheysari et al, 2017). At field level, ET can be measured using conventional techniques, such as the Bowen ratio, eddy covariance, soil water balance and lysimetric procedure (Costa et al, 2018;Gharsallah et al, 2013). However, these techniques are complex, costly, and require specific equipment and are thus generally applied only in scientific research (Gharsallah et al, 2013) and limited to homogeneous surfaces (Costa et al, 2018).…”

“…At field level, ET can be measured using conventional techniques, such as the Bowen ratio, eddy covariance, soil water balance and lysimetric procedure (Costa et al, 2018;Gharsallah et al, 2013). However, these techniques are complex, costly, and require specific equipment and are thus generally applied only in scientific research (Gharsallah et al, 2013) and limited to homogeneous surfaces (Costa et al, 2018). On the other hand, over heterogeneous surfaces, water consumption can be monitored with the scintillation technique (Ezzahar et al, 2007) and especially using ET models/algorithms, based on remote sensing data.…”

Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil

“…Its application is recommended for water resources management due to its ability to provide high resolution estimates of ET [27,43]. Although most SEBAL applications were performed in arid and temperate regions [17,44,45], its use in tropical climates also yielded accurate estimations [46][47][48][49][50][51][52].…”