Accurate estimation of transpiration (Tr) is important in the development of precise irrigation scheduling and to enhance water-use efficiency in agricultural production. In this study, the air temperature (Ta) and relative humidity (RH) were measured at three different heights (0.5, 1.0, and 1.8 m above the ground near the plant canopy) parameterize aerodynamic resistance (ra) based on the heat transfer coefficient method and to estimate Tr using the Stanghellini model (SM) during two growing seasons of cucumber in a greenhouse. The canopy resistance (rc) was parameterized by an exponential relationship of stomata resistance and solar radiation, and the estimated Tr was compared to the values measured with lysimeters. After parameterization of ra and rc, the efficiency (EF) and the Root Mean Square Error (RMSE) of the estimated Tr by the SM based on micrometeorological data at a height of 0.5 m were 95% and 18 W m−2, respectively, while the corresponding values were 86% and 29 W m−2 at a height of 1.8 m for the autumn planting season. For the spring planting season, the EF and RMSE were 92% and 34 W m−2 at a height of 0.5 m, while the corresponding values were 81% and 56 W m−2 at a height of 1.8 m, respectively. This work demonstrated that when micrometeorological data within the canopy was applied alongside the data measured above the canopy, the SM led to better agreement with the lysimeter measurements.@en

Models for predicting hourly canopy resistance (rc) 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 rc was using an aerodynamic resistance (ra) and climatic resistance (r*), while another one was based on a relationship with solar radiation (SR). Nonlinear relationships between rc and r*, and between rc and SR were found for different growing stages of the rice crop. The constructed rc 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 rc 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 rc estimated using r* and SR, respectively. The rc integrated PM equation provided better performance than the bulk transfer equation. The results also revealed that neglecting the effect of ra on rc did not yield a significant difference in predicting LET.@en

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.

@en

Accurate estimation of evapotranspiration is important in efficient water management for improving water use efficiency. In order to obtain evapotranspiration and evaporation beneath the canopy using the Food and Agriculture Organization (FAO) method, pan evaporation was used instead of reference evapotranspiration calculated by the Penman-Monteith equation with detailed meteorological data. The total crop coefficient and soil evaporation coefficient were determined using actual measured daytime evapotranspiration and evaporation by the Bowen ratio energy balance and lysimeter, respectively, in a rice paddy field in Japan. The average evapotranspiration was 5.3 mm/d, 4.4 mm/d, 7.4 mm/d and 6.3 mm/d and crop coefficient was 0.79, 1.18, 1.01 and 0.86 for the initial stage, development stage, middle-season stage and late-season stage, respectively. The evaporation was low and almost constant with an average value around 0.77 mm/d when the leaf area index (LAI) reached 3. The proposed average crop coefficients for different growing stages were applied to estimate daytime evapotranspiration and found suitable. A simple soil water evaporation coefficient model was developed using leaf area index for practical use and it was found that it could accurately estimate evaporation.@en

Determination of canopy resistance (rc ) 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 rc 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 rc 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 rc model. RMSE and d values for rc 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 rc sub-model based on data from different seasons was more reliable for estimating LET of tea field when integrated to the PM model.@en