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Winter irrigation is an effective means of salt leaching, but the long-term effect on salinity is unclear. In 2008–2019, three different soil types of farmlands were selected as the study area by drip irrigation under film mulch combined with periodic winter irrigation in the non-growth period. The salinity of 0–150 cm as well as the survival rate and yield of cotton in the non-growth and growth periods were monitored, respectively. The mass fraction of soil salt decreased rapidly under winter irrigation, and then, the salt content in each observation layer increased with years of cultivation. After 10 years of application, the soil salt content basically stabilized at a low level. In 2008, the salinity of the 0–150 cm observation layer of loamy clay, loam, and sandy loam varied within 6–60, 10–65, and 4–22 g·kg−1, after four winter irrigations in 2019, corresponding values dropped below 5.74, 3, and 4.76 g·kg−1, respectively. The salinity returns rate of the different observation layers all exceeded 40%. The desalination rate of the different soils after four winter irrigations all exceeded 63.52%. Cotton survival rate and yield in different soils were directly proportional to each other. After the second winter irrigation, the survival rates on the different soils all exceeded 60%. The results of this study can provide technical support for the sustainable development of different types of soil, farmers’ income increase, and salinization land improvement.

In this study, the influence of the relevant parameters of a subsurface pipe layout on soil water and salt transport in a cotton field under mulched drip irrigation is explored. Based on the measured data of the changes in the groundwater level and salt in the field, the DRAINMOD numerical model has been used for simulating the water and salt dynamics of a salinized cotton field under subsurface pipe drainage. The results of the investigation show that the DRAINMOD model can accurately simulate the changes in the hydrological conditions and the salt-leaching process in the study area. The average deviation between the simulated and measured values of the groundwater depth in 2013 and 2014 was −1.72 cm and 2.43 cm, the average absolute deviation was 3.84 cm and 2.43 cm, the root mean square error was 5.14 cm and 3.63 cm, and the correlation coefficient was 0.87 and 0.94, respectively. The average deviation between the simulated and measured values of soil salinity in 2013 and 2014 was −0.68 g/kg and −1.86 g/kg, the average absolute deviation was 1.60 g/kg and 1.99 g/kg, the root mean square error was 1.95 g/kg and 2.99 g/kg, and the correlation coefficient was 0.82 and 0.86, respectively, which are all within the acceptable error range. After validation, the model was used to simulate and analyze the desalination process of a cotton field in the study area for 27 different subsurface pipe layout modes. The projection pursuit classification model has been combined with the accelerated genetic algorithm based on real-number coding. The comprehensive benefits of the subsurface pipe layout were evaluated using the construction cost, average desalination rate, and relative yield of cotton as the evaluation indices. The results show that C11 (buried depth 2.1 m, spacing 30 m) is the optimal layout of the subsurface pipe. The results of this study can provide theoretical support and scientific guidance for the popularization and application of subsurface pipe salt discharge technology and drip irrigation under film in the arid inland areas of northwest China.