Assessing uncertainties in estimating surface energy fluxes from remote sensing over natural grasslands in Brazil

Abstract

Evapotranspiration (ET) is one of the main fluxes in the global water cycle. As the Pampa biome carries a rich biodiversity, accurate information on the ET dynamics is essential to support its proper monitoring and establish conservation strategies. In this context, we assessed an operational methodology based on the S-SEBI model to estimate energy fluxes over the natural grasslands of the Brazilian Pampa between 2014-2019. The S-SEBI is a remote sensing-based ET model that requires a minimum of meteorological inputs, being fully applicable for regions lacking in situ observations. Therefore, we investigated the model performance considering radiation data from both ERA5 reanalysis and Eddy Covariance measurements. Furthermore, comparisons from satellite-based estimates with in situ data were performed with and without energy balance closure (EBC).Results showed that the RMSE is impacted in 0.32 mm/day when reanalysis data are used, indicating that the meteorological inputs have low sensitivity on daily ET estimates from the S-SEBI model. In contrast, the instantaneous energy balance components are more affected. The strong climate seasonality of the Brazilian Pampa impacts the evaporative fraction, which is more evident in late summer and autumn and may compromise the performance of the model. The effects in the daily ET are lower when in situ data without EBC are considered as ground truth. However, they are less correlated with the remote sensing-based estimates. These insights are useful to monitor water and energy fluxes from local to regional scale and provide the opportunity to capture ET trends over the biome.

Evapotranspiration Assessment by Remote Sensing in Brazil with Focus on Amazon Biome: Scientometric Analysis and Perspectives for Applications in Agro-Environmental Studies

“…Brazilian biome-specific studies (covering the entire national extent) yielded 13 articles. These were further categorized as follows: four on the Cerrado [58][59][60][61], four on the Pampa [62][63][64][65], three on the Amazon [7,27,66], and two on the Pantanal [67,68]. Additionally, one study analyzed ET across several states (Maranhão, Piauí, Bahia, Mato Grosso, Mato Grosso do Sul, Goiás, Paraná, and Rio Grande do Sul) [23].…”