Working to simplify mechanistic models on the basis of reliability for estimating crop evapotranspiration (ET) in a greenhouse is still worthwhile for horticulturists. In this study, four ET models (Penman–Monteith, Priestley–Taylor, and Shuttleworth–Wallace models, and the Crop coefficient method) were parameterized after taking the restriction effect of resistance parameters in these models on ET into account, named as PA-PM, PA-PT, PA-CC, and PA-SW, respectively. The performance of these four parameterized models was compared at different growth stages, as well as the entire growing season. Tomatoes that were ET-grown in a solar greenhouse without a heating device were measured using weighting lysimeters during 2016–2017 and 2019–2021, in which data from 2016 were used to adjust the model parameters, and data from the other four study years were used to examine the model performance. The results indicated that the PA-PT and PA-CC models have a better performance in estimating tomato ET at four growth stages, while the PA-PM and PA-SW performed well only at the development and middle stages. Compared to the ET that was measured with the weighting lysimeters, the ET that was predicted using the PA-PM model was 27.0% lower at the initial stage, and 8.7% higher at the late stage; the ET that was computed using the PA-SW model was 19.5% and 13.6% higher at the initial and late stages, respectively. The PA-PT model yielded the lowest root mean square error and the highest index of agreement against the other models over the entire growing season, indicating that the PA-PT model is the best recommended model for estimating tomato ET in a solar greenhouse.

Climate change is continuously intensifying extreme climatic events and their compound effects. Assessments based on changes in single climate variables are increasingly insufficient for identifying future integrated climate pressure. Based on 23 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), this study projected future changes in precipitation and temperature under different emission scenarios in the Yellow River Diversion Receiving Area of Henan Province. An integrated climate pressure index was further developed to identify the spatial pattern of climate pressure and changes in its dominant drivers. The results show that: (1) The study area will experience continuous warming with wetting, with precipitation increases mainly reflected in enhanced intensity and extremes. In the far future, the median increases in Rx1day, Rx5day, and R95pTOT reach 43.22 mm, 87.33 mm, and 310.54 mm, respectively. (2) High-value zones of key climate indicators show clear spatial aggregation. High ΔR95pTOT values remain concentrated in the southeast, high ΔT_max values shift toward the south and southeast, and ΔT_min shows weaker spatial differentiation but broader high-value coverage. (3) Future integrated climate pressure is generally higher in the eastern and southeastern areas and lower in the western and northwestern areas, with a stable high-pressure core around Zhoukou–Shangqiu–Kaifeng. (4) The dominant drivers shift from the dominance of ΔT_max under low-emission scenarios to the combined dominance of ΔT_max and ΔRx1day under high-emission scenarios, indicating a gradual transition in the source of future integrated climate pressure from a single warming signal to the combined effects of warming and extreme precipitation.