The Effects of Different Planting Patterns in Bare Strips on Soil Water and Salt Accumulation under Film-Mulched Drip Irrigation

Salt accumulation in bare strips under film-mulched drip irrigation is a global concern as it adversely affects soil quality and hinders sustainable agricultural development in arid and semi-arid regions. This study aims to investigate the spatial distribution of soil moisture and salt under various planting patterns and assess the lateral salt accumulation effect in bare strips. Seven treatments were implemented based on the local cotton planting pattern, including the local classical planting pattern (LTP), mulch width of 220 cm (WFM-220), spacing of 90 cm (SFM-90), mulch width of 40 cm (WFM-40), spacing of 10 cm (SFM-10), ridge tillage (TFM-RT), and ditching (TFM-D), varying in mulch width, spacing, and tillage method in bare strips. Additionally, the performance of the HYDRUS-2D model was evaluated by comparing simulated and observed values using field data. The results revealed that (I) the WFM-220 cm treatment exhibited the best water content retention under mulched film, with lower salt accumulation in the surface bare strip (0–20 cm soil layer); (II) all treatments with narrow rows showed desalination effects in the 0–40 cm soil layer, with salt content reductions ranging from approximately 13% to 38% compared to the initial values; (III) under the LTP treatment, the lateral salt discharge effect in the bare strip of the 0–40 cm soil layer was the best, regardless of mulch width and spacing, with a salt accumulation rate up to three times higher than the initial value, and even up to four times higher in the 0–10 cm layer; (IV) the TFM-RT treatment exhibited the best salt accumulation ability on the surface bare strip; and (V) the HYDRUS-2D model proved to be an effective tool for studying the dynamic regulation mechanism of water and salt with root mean square error values ranging from 0.079 to 0.106 cm³·cm⁻³ for soil water content and from 0.044 to 0.079 dS·m⁻¹ for electrical conductivity, indicating good agreement between simulations and observations.