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Assessing actual evapotranspiration via surface energy balance aiming to optimize water and energy consumption in large scale pressurized irrigation systems
Author(s): H. Awada; G. Ciraolo; A. Maltese; M. A. Moreno Hidalgo; G. Provenzano; J. I. Còrcoles
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Paper Abstract

Satellite imagery provides a dependable basis for computational models that aimed to determine actual evapotranspiration (ET) by surface energy balance. Satellite-based models enables quantifying ET over large areas for a wide range of applications, such as monitoring water distribution, managing irrigation and assessing irrigation systems’ performance. With the aim to evaluate the energy and water consumption of a large scale on-turn pressurized irrigation system in the district of Aguas Nuevas, Albacete, Spain, the satellite-based image-processing model SEBAL was used for calculating actual ET. The model has been applied to quantify instantaneous, daily, and seasonal actual ET over high- resolution Landsat images for the peak water demand season (May to September) and for the years 2006 – 2008. The model provided a direct estimation of the distribution of main energy fluxes, at the instant when the satellite overpassed over each field of the district. The image acquisition day Evapotranspiration (ET24) was obtained from instantaneous values by assuming a constant evaporative fraction (Λ) for the entire day of acquisition; then, monthly and seasonal ET were estimated from the daily evapotranspiration (ETdaily) assuming that ET24 varies in proportion to reference ET (ETr) at the meteorological station, thus accounting for day to day variation in meteorological forcing. The comparison between the hydrants water consumption and the actual evapotranspiration, considering an irrigation efficiency of 85%, showed that a considerable amount of water and energy can be saved at district level.

Paper Details

Date Published: 2 November 2017
PDF: 9 pages
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104210G (2 November 2017); doi: 10.1117/12.2279964
Show Author Affiliations
H. Awada, Univ. degli Studi di Palermo (Italy)
G. Ciraolo, Univ. degli Studi di Palermo (Italy)
A. Maltese, Univ. degli Studi di Palermo (Italy)
M. A. Moreno Hidalgo, Univ. de Castilla-La Mancha (Spain)
G. Provenzano, Univ. degli Studi di Palermo (Italy)
J. I. Còrcoles, Univ. de Castilla-La Mancha (Spain)


Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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