Evapotranspiration of banana using the SEBAL algorithm in an irrigated perimeter from the Northeastern Brazil

Abstract

The study aimed to estimate the evapotranspiration of banana (Musa spp.) in an irrigated perimeter of the municipality of Barbalha, CE, Brazil, using the Surface Energy Balance Algorithm for Land (SEBAL) model and to compare these results with those estimated using the Penman-Monteith method. Landsat-8 OLI/TIRS satellite images of May 22, 2016, August 10, 2016, and October 29, 2016 and data on temperature, relative humidity, wind speed and solar irradiance, obtained from an automatic weather station, installed close to the experimental area were used. The bands were stacked, and the stacked images were cut, then mathematical operations and evapotranspiration estimation were performed, whose actual daily banana values, estimated by the SEBAL algorithm, were 4.70; 5.00 and 6.50 mm, respectively, for May 22, August 10, and October 29, 2016. Comparing the daily ETr given by SEBAL with that obtained by the Penman-Monteith method, absolute errors of 0.26, 0.44, and 0.64 mm d-1 were observed for May 22, August 10, and October 29, 2016, respectively. These errors are within the ranges accepted in the literature.

Integrated Studies of Banana on Remote Sensing, Biogeography, and Biodiversity: An Indonesian Perspective

“…However, the documentation of Landsat satellite images for banana herbs is still limited. The study conducted by [22], which elaborated on evapotranspiration, based on the surface energy balance for land (SEBAL) algorithm, may help in facilitating better explanation of conditions over banana plantations.…”

Assessing the water use efficiency of irrigated fruit crops in semi‐arid regions of Brazil using remote sensing and meteorological data

“…Improving the estimation of evapotranspiration (ET) is an initial step towards enhancing irrigation water use; however, temporal and spatial variations make such estimations difficult (Dari et al, 2020). To overcome this problem, remote‐sensing tools, meteorological data and mathematical models have been integrated (Allen et al, 1998; Freitas et al, 2008; Jamshidi et al, 2020; Silva et al, 2009; Silva et al, 2021; Teixeira et al, 2021).…”