Improving canopy transpiration model performance by considering concurrent hot and dry conditions

CONTEXT: The Jarvis-Stewart model has commonly been used to estimate transpiration. However, its assumption regarding independent effects from different influencing factors has seldom been explored. OBJECTIVE: The aim is to test whether the Jarvis-Stewart model can well estimate transpiration under concurrent hot and dry conditions with strong environmental interactions. A secondary objective was to test was to propose a new coupling method without the environmental-independence assumption for transpiration estimation. METHODS: This study tested and compared 24 Jarvis-Stewart models composed of various constraint functions to determine the optimal model structure for an orange orchard under concurrent hot and dry conditions. Meanwhile, a new coupling equation that considers interactive environmental effects on transpiration was proposed, and a total of 48 configurations were examined to determine the most effective configuration. A comprehensive comparison was made between the best Jarvis-Stewart model and the best coupling model based on a Bayesian framework. RESULTS AND CONCLUSIONS: Results showed that with fewer parameters, the best new coupling model significantly improved model performance compared with the best Jarvis-Stewart model. Specifically, estimation accuracy was slightly improved, with the average mean relative error decreased from 11.79% to 11.06%, and the average coefficient of determination increased from 0.67 to 0.72. More importantly, estimation uncertainty was significantly decreased, with the average uncertainty band width reduction of 42%. Moreover, the new model generated some water use information that was much more consistent with measured data and did not suffer from over-fitting problems as the Jarvis-Stewart model suffered from. Furthermore, the new model did not require additional data or computational cost. SIGNIFICANCE: The results of our study emphasize the necessity for studying environmental interaction effects on plant water consumption, particularly under the possibility of concurrent hot and dry conditions that are likely to occur under future climate conditions.