Performance of SAFER evapotranspiration using missing meteorological data

Santos, Jannaylton Éverton Oliveira; Cunha, Fernando França da; Filgueiras, Roberto; Silva, Gustavo Henrique da; Teixeira, A. H. de C.; Silva, Francisco Charles dos Santos; Sediyama, Gilberto Chohaku

doi:10.1016/j.agwat.2020.106076

Cited by 19 publications

(23 citation statements)

References 31 publications

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“…In this paper a correction factor is applied to the evaporative fraction (ETf) for considering distinct atmospheric demands for actual evapotranspiration (ET) acquirements. In this way, the SAFER algorithm has been validated in several Brazilian agroecosystems (Araujo et al 2019;Leivas et al 2015;Nuñez et al 2017;Rampazo et al 2020;Santos et al 2020;Silva et al 2019;Teixeira et al 2020a, b;2021a, b;Venancio et al 2021). Besides the corrected ETf values were satisfactorily checked with literature.…”

Section: Remote Sensing Environmental Indicators Modellingmentioning

confidence: 80%

“…In the Brazilian biomes, there is a large diversify of natural species and agricultural crops (Lewinsohn and Prado 2005) which are suffering of several environmental impacts, as deforestations; burnings; air, water and soil pollutions, as well intensive agricultural crops replacing natural species (Casagrande et al 2021;Mariano et al 2018). These problems demand large-scale studies to support sustainable consumptions of the natural resources (Araujo et al 2019;Jardim et al 2022;Nuñez et al 2017;Santos et al 2020;Teixeira et al 2021a, b).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of water and vegetation conditions: applications to the Brazilian biomes

Teixeira

Leivas

Takemura

et al. 2023

Preprint

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The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in the Brazilian biomes. The MODIS MOD13Q1 reflectance product and gridded weather data were used for the year 2016. The analyzed biomes were Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant differences on precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P - ET) and water productivity (WP = ET/BIO). The highest WB and WP differences along the year were for the wettest Amazon, Atlantic Forest, and Pampa biomes, when compared with the driest Caatinga biome. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e, the ratio of ET to reference evapotranspiration (ET0), however there was a gap between ETf and WB, what can be related to the time needed for recovering the good soil moisture conditions after the rainy seasons. For some biomes, BIO was more related to the levels of absorbed photosynthetically active radiation (Amazon, Atlantic Forest, and Pampa), while for others BIO followed more the soil moisture levels, represented by ETf (Caatinga, Cerrado, and Pantanal). The large-scale modelling presented suitability for monitoring environmental indicators, opening the room to detect anomalies for specific periods along the year by using historical images and weather data, with great potential to subsidize public policies regarding the management and conservation of the natural resources and possibility for replication of the methods in other countries.

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Section: Remote Sensing Environmental Indicators Modellingmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of water and vegetation conditions: applications to the Brazilian biomes

Teixeira

Leivas

Takemura

et al. 2023

Preprint

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“…O SAFER é um modelo elaborado por Teixeira (2010) HERNANDEZ et al, 2014;COAGUILA et al, 2017;SILVA et al, 2018aSILVA et al, , 2018bSANTOS et al, 2020). Hernandez et al (2014) aplicaram o SAFER a imagens Landsat-5 no Noroeste de São Paulo e compararam seus resultados aos do modelo SEBAL, e da metodologia do coeficiente de cultura -𝐾 𝐶 (ALLEN et al, 1998) da Food Agriculture Organization (FAO), nas culturas de milho, feijão e cana-de-açúcar, irrigadas por pivôs centrais.…”

Section: Simple Algorithm For Evapotranspiration Retrieving (Safer)unclassified

Sensoriamento Remoto Orbital Para Modelagem Da Evapotranspiração: Síntese Teórica E Aplicações Em Computação Na Nuvem

2021

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O objetivo desse artigo de revisão foi compilar os aspectos teóricos e tecnológicos da modelagem de evapotranspiração (ET) baseada em sensoriamento remoto. Levantamos os conceitos termohidrológicos que dão base ao fenômeno da ET, a saber, os fluxos de energia no solo ("termo") e balanço hidrológico. Também apresentamos as principais variantes do conceito de ET. Os modelos baseados em sensoriamento remoto são voltados à ET real. Levantamos os modelos aplicados a imagens de satélite mais difundidos (a serem implementados pelo pesquisador) e apresentamos suas premissas, limitações e oportunidades. Por fim, levantamos bases de dados de ET real já prontas (disponiveis no Google Earth Engine - GEE), e para elas desenvolvemos paineis interativos para extração desses dados. Com esses paineis é possível extrair facilmente séries temporais de ET real e realizar posteriores calibrações com dados de campos.

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“…Os resultados obtidos tiveram valores médios de ET com respaldo na literatura e, assim como observado por Santos et al (2020), ficou evidente que a metodologia de estimativa de ET por meio do algoritmo SAFER tem grande potencial para ser aplicada no monitoramento espaço-temporal da demanda hídrica da agricultura irrigada.…”

Section: Metodologiaunclassified

Mapeamento espaço-temporal da evapotranspiração na bacia do rio Paracatu utilizando imagens MODIS e o algoritmo SAFER

Andrade

Lima

Teixeira

et al. 2020

BJAER

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Performance of SAFER evapotranspiration using missing meteorological data

Cited by 19 publications

References 31 publications

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of water and vegetation conditions: applications to the Brazilian biomes

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of water and vegetation conditions: applications to the Brazilian biomes

Sensoriamento Remoto Orbital Para Modelagem Da Evapotranspiração: Síntese Teórica E Aplicações Em Computação Na Nuvem

Mapeamento espaço-temporal da evapotranspiração na bacia do rio Paracatu utilizando imagens MODIS e o algoritmo SAFER

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