This paper explores the feasibility of the use of two energy balance models for the estimation of evapotranspiration from satellite data in a large irrigated area. The Rio Guarico irrigation system is located in the State of Guarico in Venezuela. A large water reservoir stores the water coming from the Guarico River and provides water for irrigation to an area of near 60,000 hectares. Rice is the main crop grown in the area.
One of the models used in this study was SEBAL (Surface Energy Balance Algorithm for Land), which is an image‐processing model for calculating evapotranspiration (ET) as a residual of the surface energy balance. SEBAL was developed in the Netherlands by Bastiaanssen and has been applied in many developing countries. SEBAL uses satellite data collected by the LANDSAT Thematic Mapper (TM) or other satellite sensors collecting visible, near‐infrared and thermal infrared radiation. The main advantage of SEBAL is the need of a minimum amount of ground data. The second model applied was METRIC (Mapping Evapotranspiration at high Resolution and with Internalized Calibration) developed by the University of Idaho in the United States. METRIC has its foundation on SEBAL. A unique feature of METRIC is that an internal calibration is performed within every satellite image using the alfalfa reference evapotranspiration as an indicator of evaporative behavior of suspected well‐irrigated full cover agricultural pixels.
The results suggest that both models can be considered as operational and feasible methods to predict actual ET and improve water management on irrigated lands in Venezuela. However, limited and poorly‐distributed weather information might represent a major constraint for the use of the METRIC model in Venezuela, and a source of error for the SEBAL model when data needs to be extrapolated in time.
