Actual evapotranspiration by machine learning and remote sensing without the thermal spectrum.

The objectives of this study were to use machine learning algorithms to establish a model for estimating the evapotranspiration fraction (ETf) using two data input scenarios from the spectral information of the Sentinel-2 constellation, and to analyze the temporal and spatial applicability of the models to estimate the actual evapotranspiration (ETr) in agricultural crops irrigated by center pivots. The spectral bands of Sentinel 2A and 2B satellite and vegetation indices formed the first scenario. The second scenario was formed by performing the normalized ratio procedure between bands (NRPB) and joining the variables applied in the first scenario.

Impact of drought associated with high temperatures on Coffea canephora plantations: a case study in Espírito Santo State, Brazil.

Droughts are major natural disasters that affect many parts of the world all years and recently affected one of the major conilon coffee-producing regions of the world in state of Espírito Santo, which caused a huge crisis in the sector. Therefore, the objective of this study was to conduct an analysis with technical-scientific basis of the real impact of drought associated with high temperatures and irradiances on the conilon coffee (Coffea canephora Pierre ex Froehner) plantations located in the north, northwest, and northeast regions of the state of Espírito Santo, Brazil. Data from 2010 to 2016 of rainfall, air temperature, production, yield, planted area and surface remote sensing were obtained from different sources, statistically analyzed, and correlated.

Mapping within‑field variability of soybean evapotranspiration and crop coefficient using the Earth Engine Evaporation Flux (EEFlux) application.

Accurate information about the spatiotemporal variability of actual crop evapotranspiration (ETa), crop coefficient (Kc) and water productivity (WP) is crucial for water efficient management in the agriculture. The Earth Engine Evapotranspiration Flux (EEFlux) application has become a popular approach for providing spatiotemporal information on ETa and Kc worldwide. The aim of this study was to quantify the variability of water consumption (ETa) and the Kc for an irrigated commercial planting of soybeans based on the EEFlux application in the western region of the state of Bahia, Brazil.