Coupled Simulation of Greenhouse Crop Growth and Soil CO₂ Emissions Under Variable Irrigation Levels

How to achieve the goal of water–carbon synergistic optimization in greenhouse crop production under water-saving irrigation strategies constitutes a key pathway for the development of protected agriculture. Our study takes muskmelon and tomato with drip irrigation in greenhouses as an example and establishes different irrigation levels based on cumulative surface evaporation (E_p) from a 20 cm pan. Here, four irrigation amounts (0.6 E_p, 0.8 E_p, 1.0 E_p, and 1.2 E_p) were set for muskmelon, and three irrigation amounts (0.5 E_p, 0.7 E_p, and 0.9 E_p) were set for tomato, and then a two-year fixed-site field experiment was conducted. The growth rates of both crops were significantly higher under full-water-supply treatments (M1.0 and M1.2 for muskmelon, T0.9 for tomato) than under water-deficient treatments (M0.8 and M0.6 for muskmelon, T0.5 for tomato) (p < 0.05) at the flowering stage, while the opposite was true at the harvesting stage. More than 85% of root systems were distributed in the soil layer, ranging from 0 to 40 cm, and the average RLD under M1.0 and T0.9 was significantly higher than that under other treatments by 14.3%~27.6% (p < 0.05). Muskmelon yields at 1.0 E_p were 22.9%~45.7% higher than those at 0.6 E_p and 0.8 E_p, while tomato yields peaked at 0.9 E_p and were 17.0%~19.4% higher than those under the other two treatments. Daily average soil CO₂ emission fluxes of muskmelon under M1.2 were 9.2%~32.2% higher than those of other treatments respectively, and that of tomato under T0.9 was more than 20% higher than under T0.7 and T0.5 treatments, respectively. The WHCNS-Veg model demonstrated excellent performance in simulating SWC, LAI, and soil CO₂ emission fluxes. The RMSE for SWC simulation ranged from 0.013 to 0.022 cm³·cm⁻³, for LAI simulation, it varied from 0.103 to 0.210 cm²·cm⁻², and for soil CO₂ emission flux simulation, it changed from 1.057 to 2.188 kg·hm⁻². It should be noted that the performance was higher under high irrigation levels than under water deficit levels. These results can provide a scientific basis for optimizing greenhouse irrigation schedules and regulating water–carbon synergy under different water resource conditions.