Evapotranspiration and Surface Energy Fluxes Estimation Using the Landsat-7 Enhanced Thematic Mapper Plus Image over a Semiarid Agrosystem in the North-West of Algeria

• Main Authors: Nehal Laounia, Hamimed Abderrahmane, Khaldi Abdelkader, Souidi Zahira, Zaagane Mansour
• Format: Article
• Language: English
• Published: Sociedade Brasileira de Meteorologia
• Series: Revista Brasileira de Meteorologia
• Subjects: evapotranspiration; remote sensing; METRIC; energy balance; Landsat
• Online Access: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862017000400691&lng=en&tlng=en

Abstract Monitoring evapotranspiration and surface energy fluxes over a range of spatial and temporal scales is crucial for many agroenvironmental applications. Different remote sensing based energy balance models have been developed, to estimate evapotranspiration at both field and regional scales. In this contribution, METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration), has been applied for the estimation of actual evapotranspiration in the Ghriss plain in Mascara (western Algeria), a semiarid region with heterogeneous surface conditions. Four images acquired during 2001 and 2002 by the Landsat-7 satellite were used. The METRIC model followed an energy balance approach, where evapotranspiration is estimated as the residual term when net radiation, sensible and soil heat fluxes are known. Different moisture indicators derived from the evapotranspiration were then calculated: reference evapotranspiration fraction, Priestley-Taylor parameter and surface resistance to evaporation. The evaluation of evapotranspiration and surface energy fluxes are accurate enough for the spatial variations of evapotranspiration rather satisfactory than sophisticated models without having to introduce an important number of parameters in input with difficult accessibility in routine. In conclusion, the results suggest that METRIC can be considered as an operational approach to predict actual evapotranspiration from agricultural areas having limited amount of ground information.