Estimating the latent heat flux accurately is important to improve greenhouse crops irrigation schedules. Aerodynamic and canopy resistances, as two key parameters in the Bulk transfer equations, are already difficult to measure in the open field and even more in greenhouses. In this study, an experiment was conducted in a Venlo-type cucumber greenhouse where meteorological data and the latent heat flux were measured with lysimeters. Two methods: (1) Inversing Bulk Transfer equation (IBTE-method) and (2) Appling a convective heat transfer coefficient (CHTC-method), were used to evaluate the aerodynamic resistance. A fixed aerodynamic resistance (= 35 s m⁻¹) was decided by analyzing the sensitivity of heat fluxes to its changes. The reproduced sensible and latent heat flux were compared to the measured values and the good agreements between measured and estimated values were obtained. The variation of daily canopy resistance which was calculated by IBTE-method was simulated by days after transplanting of cucumber plants and net radiation inside the greenhouse. Quadratic polynomial equations between canopy resistance and days after transplant were obtained, and were integrated into the Bulk transfer equation to predict the latent heat flux. The comparing of the measured and estimated latent heat flux showed that the Bulk transfer equation integrating the fixed aerodynamic resistance and canopy resistance sub-model could be used to predict the latent heat flux of greenhouse cucumber with the index of agreement higher than 0.8.

Models for predicting hourly canopy resistance (r_c) and latent heat flux (LET) based on the Penman–Monteith (PM) and bulk transfer methods are presented. The micrometeorological data and LET were observed during paddy rice-growing seasons in 2010 in Japan. One approach to model r_c was using an aerodynamic resistance (r_a) and climatic resistance (r^*), while another one was based on a relationship with solar radiation (SR). Nonlinear relationships between r_c and r^*, and between r_c and SR were found for different growing stages of the rice crop. The constructed r_c models were integrated to the PM and bulk transfer methods and compared with measured LET using a Bowen ratio–energy balance method. The root mean square errors (RMSEs) were 155.2 and 170.5 W m⁻² for the bulk transfer method with r_c estimated using r^* and with a function of SR, respectively, while the RMSEs were 87.4 and 85.7 W m⁻² for the PM method with r_c estimated using r^* and SR, respectively. The r_c integrated PM equation provided better performance than the bulk transfer equation. The results also revealed that neglecting the effect of r_a on r_c did not yield a significant difference in predicting LET.

Determination of canopy resistance (r_c ) is necessary for accurate estimating hourly latent heat flux (LET), using the Penman–Monteith (PM) model for tea crop. In this study, a non-linear relationship between r_c and climatic resistance (r*) was obtained for tea plants based on micro-meteorological data and LET from the end of 2014 to the beginning of 2016 in southern China. The proposed r_c model was integrated to the PM method and compared with measured LET using a Bowen ratio energy balance method. The root mean square error (RMSE) and the index of agreement (d) were calculated for assessing the accuracy of the proposed r_c model. RMSE and d values for r_c and LET were 167.4 s m⁻¹ and 29.7 W m⁻² and 0.93 and 0.99, respectively. As compared to data from a single season, the r_c sub-model based on data from different seasons was more reliable for estimating LET of tea field when integrated to the PM model.