Drought and heat stresses are severe threats to crop production and food security in arid and semi-arid regions of the globe, especially during the summer. This study investigates the effects of micro-spray on micro-climatic and physiological characteristics of cucumber and tomato plants for four growing seasons (two growing seasons each (cucumber: 2017 and 2018 and tomato: 2021 and 2022)). The experiment was conducted in a Venlo-type greenhouse where plants were irrigated with a combined micro-spray and drip irrigation (MSDI) system (1 min for tomato (seven times a day) and 2 mins (four times a day) for cucumber) and drip irrigation (DI). Both plants’ growth and physiological parameters were recorded at the end of the experiment. Moreover, the experimental results showed that plant height and stem diameter increased under MSDI in all seasons. In addition, a micro-spray duration of 2 min decreased the average daily air temperature (T_a) and leaf temperature (T₁) by 0.8 °C and 4.9 °C, respectively, and increased the average daily relative humidity (RH) by 4.3%. However, a micro-spray duration of 1 min reduced the average daily T_a and T₁ by 0.76 °C and 4.6 °C, respectively, but the increase in RH (2.7%) was much lower than that in the single micro-spray duration of 2 min. In addition, the net leaf photosynthetic rate (P_n), the effective quantum yield of PSII (Φ_PSII), and the stomatal conductance (G_s) of both plants increased under MSDI compared with DI. A K-means analysis showed that MSDI could eliminate the adverse effects of sunlight stress on cucumbers and tomatoes. MSDI increased the yield of cucumber and tomato plants by 18.9% and 40.4%, respectively. The fruit weight of cucumber (2017) and tomato (2021) under MSDI did not increase significantly compared to DI, which indicates that MSDI mitigated heat stress, prevented flowers from being burned, and increased the number of fruits. The results also suggested that the total soluble solids in the cucumbers and tomatoes showed no significant differences (p > 0.05) between the two treatments in four seasons. In conclusion, the MSDI system can be an appropriate strategy for the irrigation needs and climate control of plants grown in greenhouses during the hot season.

Determination of evaporation (E) and transpiration (T) in tea fields separately is important in developing precise irrigation scheduling and enhancing water use efficiency. In this study, the Shuttleworth–Wallace (S-W) model was applied to simulate the variations of E and T based on the data from 2015 to 2018 in a tea field in southeast China. The dual crop coefficient (D-K) method recommended by FAO-56 was also applied to calculate E and T, using the same data set to compare with the S-W model. The measured crop coefficient (K_c) ranged from 0.43 to 1.44 with the average value was 0.90 during 1–150 DOY (days of year), and the measured K_c tended to be stable with the average value of 0.83 during 151–365 DOY in 2015. The S-W model estimated ET_c with root mean square error (RMSE) and R² of 0.45 mm d⁻¹ and 0.97, while for the D-K method the values were 0.61 mm d⁻¹ and 0.95. Therefore, both approaches could estimate the E and T separately in tea fields in southeast China, however, the D-K method had a slightly poorer accuracy compared to the S-W model in the estimation of ET_c.

This paper looks at regional water security in eastern China in the context of global climate change. The response of runoff to climate change in the Qinhuai River Basin, a typical river in eastern China, was quantitatively investigated by using the Soil and Water Assessment Tool (SWAT) model and the ensemble projection of multiple general circulation models (GCMs) under three different shared socioeconomic pathways (SSPs) emission scenarios. The results show that the calibrated SWAT model is applicable to the Qinhuai River Basin and can accurately characterize the runoff process at daily and monthly scales with the Nash–Sutcliffe efficiency coefficients (NSE), correlation coefficients (R), and the Kling–Gupta efficiency (KGE) in calibration and validation periods being above 0.75 and relative errors (RE) are ±3.5%. In comparison to the baseline of 1980–2015, the mean annual precipitation in the future period (2025–2060) under the three emission scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5 will probably increase by 5.64%, 2.60%, and 6.68% respectively. Correspondingly, the multiple-year average of daily maximum and minimum air temperatures are projected to rise by 1.6–2.1 °C and 1.4–2.0 °C, respectively, in 2025–2060. As a result of climate change, the average annual runoff will increase by 16.24%, 8.84%, and 17.96%, respectively, in the period of 2025–2060 under the three SSPs scenarios. The increase in runoff in the future will provide sufficient water supply to support socioeconomic development. However, increases in both rainfall and runoff also imply an increased risk of flooding due to climate change. Therefore, the impact of climate change on flooding in the Qinhuai River Basin should be fully considered in the planning of flood control and the basin’s development.

It is of great importance to study the changes in reference evapotranspiration (ET₀) and the factors that influence it to ensure sustainable and efficient water resource utilization. Daily ET₀ data calculated using the Penman–Monteith method from 37 meteorological stations located within Guangdong Province in the humid zone of southern China from 1960 to 2020 were analyzed. The trend analysis and Mann–Kendall test were used to analyze the time series changes in ET₀ and major climatic factors (air temperature (T), relative humidity (RH), sunshine duration (SD), and wind speed (u₂)) for over 61 years. Sensitivity and contribution analyses were used to evaluate the driving factors of ET₀. The main findings of the study are as follows: (1) the trend in average annual ET₀ time series in Guangdong slightly increased at a trend rate of 1.61 mm/10a over the past 61 years, with most stations experiencing an increase in ET₀. During the same period, air temperature significantly increased, while RH and SD decreased; u₂ also decreased. (2) Sensitivity analysis showed that ET₀ was more sensitive to RH and T than SD and u₂, with ET₀ being most sensitive to RH in spring and winter and T in summer and autumn. (3) The contribution analysis showed that T was the dominant factor for ET₀ variation in Guangdong, followed by SD. SD was found to be the dominant factor in ET₀ changes in areas where the “evaporation paradox” occurred, as well as in spring and summer. The study concludes that the climate in Guangdong became warmer and drier over the past 61 years, and if the current global warming trend continues, it will lead to higher evapotranspiration and drought occurrence in the future.

Elucidation of different vegetation energy partitioning and environmental control factors at the agro-ecosystem levels is critical for better understanding and scientific management of farmland. Pineapple (Ananas comosus (L.) Merril) is a tropical plant widely cultivated in the southern subtropical region of China; however, the energy partitioning of crassulacean acid metabolism (CAM) plants like pineapple and their interactions with the environment remain not well understood. In this study, we investigated the energy partitioning patterns of pineapple fields and latent heat flux (LET) response to environmental factors using the Bowen ratio energy balance system and meteorological observation field data. The results showed that the CAM plant pineapple energy partitioning was significantly different from the common C₃ and C₄ crops during the study period, which was mainly attributed to the complex interactions between CAM plant transpiration and the environment. Specifically, sensible heat flux was the main component of net radiation (R_n), followed by the LET, accounting for 65.0% and 30.8% of the R_n, respectively. Soil heat flux accounts for a very small fraction (4.2%). The mean values of the Bowen ratio were 2.09 and 1.41 for sunny and cloudy days during the daytime and 0.74 and 0.46 at night, respectively. LET is a key factor in responding to crop growth status and agricultural water management, and the path analysis indicates that its variation is mainly influenced directly by R_n with a direct path coefficient of 0.94 on sunny days, followed by vapor pressure deficit, air temperature and relative humidity, which indirectly affect LET through the R_n pathway, whereas soil moisture and wind speed have a low effect on LET. On cloudy days, the effect of R_n on LET was overwhelmingly dominant, with a direct path coefficient of 0.91. The direct path coefficients of the remaining factors on LET were very small and negative. Overall, this study is an important reference for enhancing the impact of pineapple as well as CAM plants on the surface energy balance and regional climate.