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