Estimating Tomato Transpiration Cultivated in a Sunken Solar Greenhouse with the Penman-Monteith, Shuttleworth-Wallace and Priestley-Taylor Models in the North China Plain

Abstract

Tomato crops are increasingly cultivated in winter in solar greenhouses to achieve high economic benefit in the North China Plain (NCP). Accurate predictions of crop transpiration (Tr) are of great significance for formulating a scientific irrigation system and increasing water productivity in this water shortage region. In this study, tomato transpiration at daily and hourly scales were estimated using Penman-Monteith (PM), Shuttleworth-Wallace (SW), and Priestley-Taylor (PT) models, and results were compared to the measured sap flow data (SF) in three tomato growth seasons in winter from 1 November 2018 to 9 December 2020. Results showed that both PM and SW models could perfectly estimate daily tomato Tr, with a determination coefficient R2 of 0.96 and 0.94 and slopes of 0.99 and 0.98, respectively, when all three seasons’ data were pooled together. The estimated daily Tr by the original PT model with a coefficient (α) of 1.26 was also linearly related to the SF with R2 of 0.92; however, the Tr was underestimated by 33%. Then α was calibrated using the data in the 2018 winter season. When the calibrated α was used in the 2019 and 2020 seasons, the estimated daily Tr showed comparable results with the PM and SW models. At hourly scales, the PM model performed best with an error of 3.0%, followed by the PT model (7.8%); the SW model underestimated Tr by 18.2%. In conclusion, all three models could be used to estimate daily Tr, and the PM and calculated PT models can be used to estimate hourly Tr.

Simulation of irrigation in southern Ukraine incorporating soil moisture state in evapotranspiration assessments

“…When using the Priestley-Taylor model, the opposite trend was observed. The reasons for the latter could be the error accumulation in the performed long-range simulations that, in turn, could be caused by lower accuracy of the Priestley-Taylor model in water stress condition as reported in Shao et al (2022). In the case of the data collected in 2018, there was an overestimation of water intake according to the data of the two upper sensors located at depths of 0.1 m and 0.25 m (Figure 1).…”

“…Thus, to quantify the intensity of evapotranspiration for more accurate modeling of moisture transport in the "soil-plantatmosphere" system, integrated models that consider soil and atmospheric physics along with plant physiology are needed (Overgaard et al, 2006). A widely used evapotranspiration model based on the Penman-Monteith equation (Monteith, 1965) successfully estimates it in the case of closed vegetation for various weather and soil conditions (see, e.g., Shao et al, 2022). In it, the processes of transpiration and evaporation from the bare soil, which are different intrinsically, are not considered separately.…”

Performance of the Improved Priestley-Taylor Model for Simulating Evapotranspiration of Greenhouse Tomato at Different Growth Stages

“…At present, there were few studies on the PT coefficient and its improved form in greenhouses. Shao et al (2022) [ 19 ] used the PT model to calculate the daily transpiration of tomatoes in a sunken heliostat in northern China and pointed out that the PT model had large errors when plants were subjected to high temperatures and water stress. Gong et al (2021) [ 20 ] also believed that the PT coefficient should be modified in combination with environmental changes due to the semi-closed characteristic of a greenhouse, whilst the ET of tomatoes in greenhouses was seriously underestimated by using the unimproved PT model.…”

“…However, some studies found that α was not only affected by the surrounding conditions, but also by other factors, such as plastic film coverage, canopy cover [ 18 ], soil available moisture [ 12 ] and leaf senescence [ 14 ]. Shao et al (2022) [ 19 ] used the PT model to calculate the daily transpiration of tomatoes in a sunken heliostat in northern China, and Gong et al (2021) [ 20 ] simulated the tomato ET in the solar greenhouse, indicating that establishing the α equation according to the environmental conditions was important. However, few studies have focused on this aspect in the greenhouse condition.…”

Estimation of Greenhouse Tomato Transpiration through Mathematical and Deep Neural Network Models Learned from Lysimeter Data

“…Measuring transpiration on a time scale using weighing lysimeters or sap flow measurement takes more time and costs, so crop transpiration models are commonly adopted (Katsoulas and Stanghellini, 2019). The common models for predicting evapotranspiration and transpiration are Penman-Monteith (PM) (Allen et al, 1998), Shuttleworth-Wallace (SW) (Shuttleworth and Wallace, 1985), and Priestly-Taylor (PT) (Priestly and Taylor, 1972) models (Shao et al, 2022). PM is the most recommended worldwide standard method because it integrates energy, aerodynamic, and atmospheric parameters (Chia et al, 2022).…”