Parameterization of a two-layer model for estimating vineyard evapotranspiration using meteorological measurements

• Published in: Agricultural and forest meteorology 2010-02, Vol.150 (2), p.276-286
• Main Authors: Ortega-Farias, S., Poblete-Echeverría, C., Brisson, N.
• Format: Article
• Language: English
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agricultural and forest meteorology; Agricultural sciences; Agronomy. Soil science and plant productions; Biological and medical sciences; Canopy resistance; eddy covariance method; Energy balance; Errors; Estimates; Estimating; estimation; Evapotranspiration; fruit crops; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; grapes; heat transfer; latent heat; Life Sciences; Mathematical models; meteorological parameters; microirrigation; model validation; Parametrization; Shuttleworth and Wallace model; Silviculture, forestry; soil temperature; soil water content; solar radiation; Valleys; Vine; Vineyards; Vitaceae; Vitis vinifera; Water balance and requirements. Evapotranspiration
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/j.agrformet.2009.11.012

The Shuttleworth and Wallace (SW) model with variable canopy resistance was evaluated to estimate evapotranspiration (ETv) from a drip-irrigated Merlot ( Vitis vinifera L.) vineyard trained on a vertical shoot-positioned (VSP) system. This vineyard is located in the Talca Valley, Region del Maule, Chile (35°25′ LS; 71°32′ LW; 125 m a.s.l). The performance of the SW model was evaluated using the eddy-covariance method on a 30 min time interval. Also, sub-models to estimate net radiation (Rn) and soil heat flux ( G) were used in the SW model. A good agreement between observed and estimated values of Rn was found with a root mean square error (RMSE) of 33 W m −2 and a mean absolute error (MAE) of 24 W m −2. Also, the SW model was able to estimate latent heat flux with RMSE and MAE of 34 and 21 W m −2, respectively. On a daily basis, results indicate that the SW model was able to predict the ETv with RMSE and MAE values of 0.51 and 0.41 mm d −1, respectively. These results suggest that it is possible to directly estimate ETv over unstressed grapevines using meteorological data and soil moisture measurements.