Water scarcity constrains the sustainable development of Chinese agriculture, and deficit irrigation as a new irrigation technology can effectively alleviate the problems of water scarcity and water use inefficiency in agriculture. In this study, the drip irrigation cotton field under film in Xinjiang was taken as the research object. Meta-analysis and machine learning were used to quantitatively analyze the effects of different farm management practices, climate, and soil conditions on cotton yield and water use efficiency under deficit irrigation, to investigate the importance of the effects of different factors on cotton yield and water use efficiency, and to formulate appropriate optimization strategies. The results showed that deficit irrigation significantly increased cotton water use efficiency (7.39%) but decreased cotton yield (−15.00%) compared with full irrigation. All three deficit irrigation levels (80~100% FI, 60~80% FI, and 40~60% FI; FI: full irrigation) showed a significant decrease in cotton yield and a significant increase in water use efficiency. Under deficit irrigation, cotton yield reduction was the smallest and cotton water use efficiency increased the most when planted with one film, two tubes, a six-row cropping pattern, an irrigation frequency ≥10 times, a nitrogen application of 300~400 kg·ha⁻¹, and a crop density ≥240,000 per hectare, and planted with the Xinluzhong series of cotton varieties; deficit irrigation in areas with average annual temperature >10 °C, annual evapotranspiration >2000 mm, annual precipitation <60 mm, and with loam, sandy soil had the least inhibition of cotton yield and the greatest increase in cotton water use efficiency. The results of the random forest showed that the irrigation amount and nitrogen application had the greatest influence on cotton yield and water use efficiency. Rational irrigation based on optimal management practices under conditions of irrigation not less than 90% FI is expected to achieve a win–win situation for both cotton yield and water use efficiency. The above results can provide the best strategy for deficit irrigation and efficient water use in drip irrigation cotton under film in arid areas.

As one global issue, soil salinization has caused soil degradation, thus affecting the sustainable development of irrigated agriculture. A two-year study was conducted in 2018 and 2019 to identify the effects of subsurface drainage spacing on soil salinity and groundwater level, the latter of which is in a high-water table in drip irrigation cotton fields in the Tarim Basin oasis in southern Xinjiang, China. Three subsurface drainage treatments, with a drain spacing of 10 m (W10), 20 m (W20), and 30 m (W30), respectively, and a drainage-absent treatment (CK), are tested. With CK, soil salinity in the 0–60 cm layer was accumulated within a year. In contrast, the subsurface drainage reduced the soil salinity at a leaching rate of 10–25%. When decreasing the drain spacing, it was found that the soil desalination rate increased significantly (p < 0.05) with good repeatability. Experimental results showed that the fitting equation of the soil salinity leaching curve could accurately describe the soil salinity leaching pattern of drip irrigation, and thus could be further used to inversely determine the theoretical drip irrigation leaching quota for those soils with different salinity degrees. As such, subsurface drainage could effectively control the groundwater table. Compared with CK, subsurface drainage deepened the groundwater table and mitigated the fluctuation of the groundwater level. These effects were strengthened by reducing the drain spacing. Correspondingly, the influence of the fluctuation of the groundwater table was reduced.

The global demand for cotton makes sustainable cotton production an important issue that can be improved by a better understanding of the influence of soil microbes on cotton growth. We collected cotton field soils at the seedling and flowering/boll-setting (FBS) stages in order to obtain soil properties and cotton growth indices. Bacterial and fungal community compositions were assessed by high-throughput sequencing of 16S rRNA and internal transcribed spacer genes, respectively, after which the differences in microbial functions and their influencing factors at different growth stages were analyzed. Both the diversity and composition of soil bacterial and fungal communities were found to be significantly different between the seedling and FBS stages. Microbes in the seedling stage had significantly higher richness and biomass than those in the FBS stage. Compared with the seedling stage, the stability of the soil bacterial communities was decreased. The cotton growth indices at both the seedling and FBS stages were associated with compositional shifts in the bacterial community and but not the fungal community. The abundance of specific soil microbial taxa (e.g., Pseudarthrobacter, Thiobacillus, Cephalotrichum, Chaetomium, and Fusarium) were correlated with cotton growth indices at the seedling stage, being mainly regulated by soil salinity and nitrate content. Our results highlight the importance of soil microbial communities in mediating cotton growth and will be useful in providing better strategies for the improvement of cotton agriculture.