ChileanJAR

Net radiation (Rn) is the main energy balance component controlling evaporation and transpiration processes. In this regard, this study evaluated two models to estimate Rno above a commercial vineyard (Vitis vinifera cv. Cabernet Sauvignon) located in Pencahue Valley, Maule Region (35º22’ S; 71°47’ Wl; 75 m.a.s.l.). An automatic meteorological station (AMS) was installed in the central part of the vineyard and used to measure Rn, solar radiation (Rsi), air temperature (Ta), canopy temperature (Tf) and relative humidity (RH). On a 30 min interval, results indicated that model Rne1 (assuming Ta ≠ Tf) and model Rne2 (assuming Ta = Tf ) were able to estimate Rn with a mean absolute error (MAE) of less than 40 W m^-2 and root mean square error (RMSE) of less than 61 W m^-2. On daily intervals, the two models estimated Rno with MAE and RMSE values of less than 1.68 and 1.75 MJ m^-2 d^-1, respectively. In global terms, the models presented errors below 9 and 11% on 30 min and daily intervals, respectively. Furthermore, this study indicated that the incorporation of canopy temperature did not improve the Rno estimation substantially, in spite of having a temperature gradient (dT = Tf - Ta) between -3 and to 4 oC. These results suggest that an Rne2 model could be used to estimate Rno using Rsi, Ta and RH measurements.