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      Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm

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          Abstract

          ABSTRACT SAFER (Simple Algorithm for Evapotranspiration Retrieving) is a relatively new algorithm applied successfully to estimate actual crop evapotranspiration (ET) at different spatial scales of different crops in Brazil. However, its use for monitoring irrigated crops is scarce and needs further investigation. This study assessed the performance of SAFER to estimate ET of irrigated corn in a Brazilian semiarid region. The study was conducted in São Desidério, Bahia State, Brazil, in corn-cropped areas in no-tillage systems and irrigated by central pivots. SAFER algorithm with original regression coefficients (a = 1.8 and b = –0.008) was initially tested during the growing seasons of 2014, 2015, and 2016. SAFER performed very poorly for estimating corn ET, with RMSD values greater than 1.18 mm d –1 for 12 fields analyzed and NSE values < 0 in most fields. To improve estimates, SAFER regression coefficients were calibrated (using 2014 and 2015 data) and validated with 2016 data, with the resulting coefficients a and b equal to 0.32 and –0.0013, respectively. SAFER performed well for ET estimation after calibration, with r 2 and NSE values equal to 0.91 and RMSD = 0.469 mm d –1 . SAFER also showed good performance (r 2 = 0.86) after validation, with the lowest RMSD (0.58 mm d –1 ) values for the set of 14 center pivots in this growing season. The results support the use of calibrated SAFER algorithm as a tool for estimating water consumption in irrigated corn fields in semiarid conditions.

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          Climate change, phenology, and phenological control of vegetation feedbacks to the climate system

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            A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation

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              Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model

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                Author and article information

                Journal
                sa
                Scientia Agricola
                Sci. agric. (Piracicaba, Braz.)
                São Paulo - Escola Superior de Agricultura "Luiz de Queiroz" (Piracicaba, SP, Brazil )
                1678-992X
                2021
                : 78
                : 4
                : e20190261
                Affiliations
                [3] Lincoln orgnameUniversity of Nebraska orgdiv1Daugherty Water for Food Global Institute United States
                [1] Viçosa Minas Gerais orgnameUniversidade Federal de Viçosa orgdiv1Depto. de Engenharia Agrícola Brazil
                [2] Viçosa Minas Gerais orgnameUniversidade Federal de Viçosa orgdiv1Depto. de Engenharia Florestal Brazil
                Article
                S0103-90162021000400102 S0103-9016(21)07800400102
                10.1590/1678-992x-2019-0261
                9292e22f-9cfc-4b5e-83d1-6d0cbc360416

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 13 November 2019
                : 20 February 2020
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 52, Pages: 0
                Product

                SciELO Brazil

                Self URI: Full text available only in PDF format (EN)
                Categories
                Agricultural Engineering

                Agricultural engineering
                remote sensing,Landsat,maize,water consumption
                Agricultural engineering
                remote sensing, Landsat, maize, water consumption

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