Abstract

Evapotranspiration is considered as one of the most crucial surface fluxes describing the water movement from the land to the atmosphere in the form of evaporation from the soil and transpiration from plants. Several evapotranspiration models exist, but their accuracy is subject to change because of the differences between the underlying assumptions used in their formulation and the conditions of the application at hand. The appropriate selection of an evapotranspiration model is necessary to ensure the accurate estimation of crop water requirements. This work compares between 20 different evapotranspiration models for the estimation of transpiration of cucumber crops grown in a cooling-based greenhouse with CO2 enrichment located in a high solar radiation region. The models are classified into temperature-based, radiation-based, mass transfer-based, and combination models. These models are assessed against direct gas exchange measurements in a greenhouse with cucumber crops. The performance of the models is evaluated using nine statistical indicators to determine the most suitable models for the application under study. Results demonstrate that among the temperature-based models, Schendel and Blaney and Criddle models resulted in the best transpiration prediction, contrary to Hargreaves and Samani which presented the worst performance. Transpiration estimates from Rohwer were the closest and that of Trabert were the furthest to the measured data amongst the other mass-transfer based models. The Abtew model was the best transpiration predicting model, while Priestley and Taylor exhibited the worst performance in the radiation-based model category. The combination-based FAO56 Penman Monteith entailed the best performance among all models and can be considered the best suitable method to estimate transpiration for cucumber crops grown in CO2 enriched and HVAC based greenhouses located in high solar radiation regions. Nonetheless, the parametrization of this model is still crucial and should be considered to achieve better estimates and accurately evaluate the effect of high solar radiation, CO2 enrichment and HVAC cooling for this agricultural greenhouse application.

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