Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth in mulched drip-irrigated cotton fields under different irrigation gradients. The SWAP crop growth model effectively simulates crop growth. However, the original SWAP model lacks a dedicated module to consider the impact of mulching on cotton field evapotranspiration and cotton dry matter mass. Therefore, in this study, the source codes of the soil moisture, evapotranspiration, and crop growth modules of the SWAP model were improved. The evapotranspiration and cotton growth data of the mulched drip-irrigated cotton fields under three irrigation treatments (W1 = 3360 m³·hm⁻², W2 = 4200 m³·hm⁻², and W3 = 5040 m³·hm⁻²) in 2023 and 2024 at the Xinjiang Modern Water-saving Irrigation Key Experimental Station of the Corps were used to verify the simulation accuracy of the improved SWAP model. Research shows the following: (1) The average relative errors of the simulated evapotranspiration, leaf area index, and dry matter weight of cotton in the improved SWAP crop growth model are all <20% compared with the measured values. The root means square errors of the three treatments (W1, W2, and W3) ranged from 0.85 to 1.38 mm, from 0.03 to 0.18 kg·hm⁻², and 55.01 to 69 kg·hm⁻², respectively. The accuracy of the improved model in simulating evapotranspiration and cotton growth in the mulched cotton field increased by 37.49% and 68.25%, respectively. (2) The evapotranspiration rate of cotton fields is positively correlated with the irrigation water volume and is most influenced by meteorological factors such as temperature and solar radiation. During the flowering stage, evapotranspiration accounted for 62.83%, 62.09%, 61.21%, 26.46%, 40.01%, and 38.8% of the total evapotranspiration. Therefore, the improved SWAP model can effectively simulate the evaporation and transpiration of the mulched drip-irrigated cotton fields in the Manas River Basin. This study provides a scientific basis for the digital simulation of mulched farmland in the arid regions of Northwest China.

Water scarcity and soil salinization constrain cotton production in arid regions, yet the joint effects of irrigation and plastic-film mulching on soil hydrothermal–salinity dynamics, dry matter partitioning, yield, and water productivity remain unclear. A two-year field experiment combined three irrigation amounts (3360, 4200, and 5040 m³ ha⁻¹; W1–W3) with plastic-film mulching (M1) and non-mulched (M0) treatments. Mulching increased soil water content by 7.23–32.76% during flowering and boll setting and shifted dry matter allocation toward reproductive organs, increasing the proportion allocated to reproductive organs by 6.43–11.16%. Irrigation markedly altered soil salinity distribution, with W2 promoting relative salt accumulation at 80–100 cm, whereas W3 maintained lower ECe across the 0–100 cm profile. W3M1 consistently produced the highest seed cotton yield, while W2M1 achieved the highest water productivity and maintained 89.4% of the two-year mean yield of W3M1 with 16.7% less irrigation. Path analysis further showed that yield variation was associated primarily with reproductive-organ dry matter rather than vegetative biomass or the integrated soil hydrothermal–salinity condition (path coefficient = 0.870, p < 0.001). These findings support irrigation strategies tailored to water availability and production goals while balancing yield, water use, and salinity risk in arid cotton systems.