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Proceedings Paper

Discrepancies between eddy covariance and lysimeter measurements in the assessment of energy balance modeling in vineyards
Author(s): Juan M. Sánchez; Ramón López-Urrea; Carolina Doña; Amelia Montoro; Vicente Caselles; Joan M. Galve
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Paper Abstract

Remote sensing-based models are a potential technique when evapotranspiration (ET) estimates are needed on a regional scale. These remote sensing methods are typically validated and calibrated using in situ measurements. Eddy covariance (EC) and lysimetry are two of the most prevalent techniques for measuring ET. Some discrepancies arise between these two techniques consequence of the measurement footprint or the spatial variability in atmospheric and surface conditions. An experiment was carried out in the growing season of 2015 in a ~4 ha row-crop vineyard in a semi-arid advective location in Central Spain, encouraged by the necessity to assess the feasibility of EC measurements in this area and under these conditions. A 9-m2 monolithic weighting lysimeter was available. An EC system was deployed together with a net radiometer and a set of soil heat flux plates. Data of the different terms of the energy balance equation were stored every 15 min, and then averaged at an hourly and daily scales. In this work we focus on the comparison between ET measurements from the two methods, EC and lysimetry. The imbalance in the surface energy budget was first analyzed. A lack of closure around 20% was observed. After forcing the closure, discrepancies between EC and lysimeter measurements still remained. Average estimation errors of ±0.09 mm h-1 and ±0.5 mm d-1 were obtained at hourly and daily scales, respectively, whereas a deviation of only 2% was observed in the accumulated ET for the entire experiment. These results support the use of adjusted EC technique to monitor accurate ET in vineyards.

Paper Details

Date Published: 25 October 2016
PDF: 9 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980R (25 October 2016); doi: 10.1117/12.2241436
Show Author Affiliations
Juan M. Sánchez, Univ. de Castilla-La Mancha (Spain)
Ramón López-Urrea, Instituto Técnico Agronómico Provincial (Spain)
FUNDESCAM (Spain)
Carolina Doña, Univ. de Valencia (Spain)
Amelia Montoro, Instituto Técnico Agronómico Provincial (Spain)
FUNDESCAM (Spain)
Vicente Caselles, Univ. de Valencia (Spain)
Joan M. Galve, Univ. de Valencia (Spain)


Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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