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Proceedings Paper

Comparison between energy balance and mass balance models for actual evapotranspiration assessment
Author(s): A. Gentile; L. Pierce; G. Ciraolo; G. Zhang; G. La Loggia; R. Nemani
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Paper Abstract

The assessment of the water needs for a specific crop has a fundamental importance in the management of water resources. The application of empirical models able to retrieve estimates of the actual evapotranspiration (ETa) to assess the need for water could give a valid tool for the planning of water supply, avoiding unnecessary water losses. In this context, two independent models for estimating actual evapotranspiration were compared. The first model is based on an energy balance and uses remotely sensed data and ancillary data from weather stations to assess the ETa. The second model also uses remotely sensed data and climatic data on a daily basis from a weather network. Field measurements are needed to calibrate both models. The study was conducted in a commercial vineyard located in Napa Valley (California). The observed range of ETdaily is included within the values measured by other authors. The results retrieved from both models show actual ETdaily values with a different trend over time; after mid-summer (early July) VSIM estimates of ETdaily trend downwards, while SEBAL estimates remain fairly constant. This disagreement illustrate the difficulty in estimating the actual evapotranspiration at the end of season, when soil moisture gets low and vine water stress increases due to reducing stomatal conductance.

Paper Details

Date Published: 18 September 2009
PDF: 12 pages
Proc. SPIE 7472, Remote Sensing for Agriculture, Ecosystems, and Hydrology XI, 747212 (18 September 2009); doi: 10.1117/12.830229
Show Author Affiliations
A. Gentile, Univ. of Palermo (Italy)
L. Pierce, California State Univ., Monterey Bay (United States)
G. Ciraolo, Univ. of Palermo (Italy)
G. Zhang, Utah State Univ. (United States)
G. La Loggia, Univ. of Palermo (Italy)
R. Nemani, NASA Ames Research Ctr. (United States)

Published in SPIE Proceedings Vol. 7472:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XI
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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