Chenmengyuan Zhu

The ridge–furrow plastic mulching technique has been widely applied due to its benefits of increasing temperature, conserving moisture, reducing evaporation, and boosting yields. Hydrus-2D is a computer model designed to simulate the two-dimensional movement of water in soil characterized by a low cost and high flexibility compared to field experiments. This study, based on field experiment data from Jianping County, Liaoning Province, China, during 2017–2018, developed Hydrus-2D models for two distinct field management practices: non-mulched flat cultivation (NM-FC) and mulched ridge tillage (M-RT). Furthermore, it simulated the dynamic changes in farmland water variations during the summer maize growth period (2021–2100) under climate change scenarios, specifically medium and high emission pathways (SSP2-4.5 and SSP5-8.5), based on the FGOALS-g3 model, which exhibits the highest similarity to the climate pattern of Jianping County in the Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models and the Shared Socioeconomic Pathways (SSPs). The results showed that in the future FGOALS-g3 model, net radiation exhibited a significant upward trend under the SSP2-4.5 scenario (Z = 2.38), while the average air temperature showed a highly significant increase under both SSP2-4.5 and SSP5-8.5 scenarios, with Z-values of 6.48 and 8.90, respectively. The Hydrus-2D model demonstrated high simulation accuracy in both NM-FC and M-RT treatments (R² ranging from 0.86 to 0.96, with RMSE not exceeding 0.011), accurately simulating the dynamic changes in soil water content (SWC) under future climate change. Compared to NM-FC, M-RT reduced evaporation, increased transpiration, and effectively decreased the leakage caused by increased future precipitation, resulting in a 0.04 and 0.01 cm³/cm³ increase in surface and deep soil SWC, respectively, during the summer maize growing season, significantly improving water use efficiency. Moreover, M-RT treatment reduced the impact coefficients of climate change on various water balance parameters, stabilizing changes in these parameters and SWC under future climate conditions. This study demonstrates the significant advantages of M-RT in coping with climate change, providing key scientific evidence for future agricultural water resource management. These findings offer valuable insights for policymakers and farmers, particularly in developing adaptive land management and irrigation strategies, helping to improve water use efficiency and promote sustainable agricultural practices.

Aerated irrigation (AI) is a method to mitigate rhizosphere hypoxia caused by the wetting front from subsurface drip irrigation (SDI). This study evaluated the impacts of AI on soil aeration, plant growth performance, fruit yield (tomato), irrigation water use efficiency (IWUE), fruit nutrition (lycopene and Vitamin C (VC)) and taste (soluble sugar, organic acid and sugar–acid ratio) quality. A three-factorial experiment including AI and SDI at three irrigation levels (W_0.6, W_0.8 and W_1.0, corresponding with crop-pan coefficients of 0.6, 0.8 and 1.0) and two dripper depths (D₁₅ and D₂₅, burial at 15 and 25 cm, respectively), totaling 12 treatments overall, was conducted in a greenhouse during the tomato-growing season (April–July) in 2016. The AI improved soil aeration conditions, with significantly increased soil oxygen concentration and air-filled porosity relative to SDI. Moreover, the AI improved crop growth performance, with increased root morphology (diameter, length density, surface area and volume density), delayed flowering time, prolonged flowering duration and increased shoot (leaf, stem and fruit) dry weight, and harvest index. Fruit yield per plant, fruit weight, IWUE, the contents of lycopene, VC and soluble sugar, and sugar–acid ratio significantly increased under AI treatments (P < 0.05). As the irrigation level increased, fruit yield, number, and weight increased (P < 0.05), but IWUE and fruit lycopene, soluble sugar, and organic acid content decreased (P < 0.05). The dripper depth had no significant impact on fruit yield, nutrition and taste quality. Principal component analysis revealed that the optimal three treatments in terms of fruit yield, IWUE, and nutrition and taste quality were the treatments W_0.6D₂₅AI, W_1.0D₂₅AI and W_1.0D₁₅AI. These results suggest that AI can improve tomato growth performance and increase fruit yield, nutrition and taste quality, and IWUE through enhancing soil aeration conditions.