Evaluating Greenhouse Tomato Responses to High Temperature Using AquaCrop-OSPy with Sequential Sensitivity Analysis and GLUE Calibration

How to precisely depict the effects of high temperature on greenhouse crop growth and yield formation and derive optimal irrigation schedules remains an emerging challenge for current crop models. To address this issue, our study focused on drip-irrigated tomato plants grown in a greenhouse and adopted a two-factor experimental design with high temperature (TH: daily maximum temperature 35~40 °C) and two water levels (full irrigation, WH: 1.0Epan; deficit irrigation, WD: 0.6Epan), where Epan denotes the cumulative evaporation of a 20 cm standard evaporation pan. Forty-three parameters of the AquaCrop-OSPy model were screened using the Morris global sensitivity analysis method, and the selected highly sensitive parameters were processed via GLUE-based calibration and uncertainty characterization subjected to global optimization through a GLUE method to derive the model-based preferred strategy under high-temperature conditions in the greenhouse. On this basis, four indicators (yield, biomass (Bio), water consumption (ET) and water use efficiency (WUE)) were adopted to evaluate 20 combined scenarios of five temperature gradients and four irrigation strategies, which were then ranked using the TOPSIS–Entropy Weight (TEW) method. The results showed that the highly sensitive parameters of the AquaCrop-OSPy model under high-temperature greenhouse conditions included initial harvest index, water productivity, basal crop coefficient, maximum canopy cover, canopy growth coefficient, and days to maturity. After optimization using the GLUE method, the values of the above parameters were 70.9%, 15.2 g/m3, 1.36, 86.2%, 12.6%/d, and 108 d, respectively. The calibrated AquaCrop-OSPy model performed satisfactorily for canopy cover (CC), Bio, and yield under the evaluated experimental conditions, although ET and WUE simulations remained less accurate under combined high-temperature and deficit-irrigation conditions. The root mean square error of simulated CC was less than 7.2%, and the percentage errors of yield and Bio were less than 3.5% and 6.9%, respectively. Evaluation of the 20 temperature–irrigation coupled scenarios revealed that, among the scenarios evaluated, the 32~34 °C range combined with 1.1 or 0.9 Epan was associated with comparatively high simulated yield and WUE. Among the simulated scenarios evaluated using the TEW procedure, 34 °C + 1.1 Epan produced the highest comprehensive index (0.9283). The framework provides a model-based basis for identifying candidate irrigation strategies for greenhouse tomato under high-temperature conditions, which should be further tested experimentally.