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Assessment of evapotranspiration estimates based on surface and satellite data and its relationship with El Niño–Southern Oscillation in the Rio de Janeiro State.
- Source :
- Environmental Monitoring & Assessment; Jul2020, Vol. 192 Issue 7, p1-15, 15p
- Publication Year :
- 2020
-
Abstract
- The need to validate the quality of evapotranspiration estimates is essential for this parameter which has extended its use. For this, it is necessary to evaluate both new remote sensing products that expand the areas of estimated evapotranspiration and empirical equations that provide estimates with different data requirements. In order to examine this problem, the present study compared the estimates of evapotranspiration obtained by remote sensing of the MOD16A2 product and seven empirical equations with the estimates obtained through the FAO-56 reference method, with data obtained from six meteorological stations in the State of Rio de Janeiro, Brazil. Data cover the period from 2007 to 2013, which contains different phases of the El Niño–Southern Oscillation phenomenon. The methods proposed by Valiantzas were those that obtained the best performances when compared with FAO-56 with R<superscript>2</superscript> over 90%. The non-parametric analysis of Mann-Kendall for the six seasons was mostly not significant; only the station of Resende showed a tendency of significant growth during the El Niño episode (Z = 0.283 and p value = 0.050). The mangrove and forest classes were the ones that obtained the highest averages (3.75 mm d<superscript>−1</superscript> and 3.62 mm d<superscript>−1</superscript>), where the gradient of evapotranspiration can be observed in the South-Northeast portions. The MOD16A2 orbital product was inferior to the methods that used surface meteorological station data. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01676369
- Volume :
- 192
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Environmental Monitoring & Assessment
- Publication Type :
- Academic Journal
- Accession number :
- 144657466
- Full Text :
- https://doi.org/10.1007/s10661-020-08421-z