Straw return directly increases carbon inputs, enhancing soil organic carbon (SOC) stocks. However, long-term straw return leads to carbon saturation in the topsoil (0–20 cm). While most studies focus on the topsoil, the effects of long-term straw return on deep soil (100–200 cm) carbon sequestration remain poorly understood. This study investigated carbon dynamics in an arid region by analyzing 0–200 cm soil profiles under different straw return treatments: control (uncultivated) and cotton straw return for 5 (SR5), 10 (SR10), and 20 years (SR20). Straw return significantly improved soil properties by reducing electrical conductivity (EC), increasing nutrient availability, and enhancing bacterial activity. SR20 resulted in the most pronounced SOC increase (18.6–252.7%) across the entire profile and significantly enhanced soil inorganic carbon (SIC) (27.7–52.7%) in deep layers. In contrast, SOC in the topsoil (0–20 cm) increased initially but plateaued after 5–10 years. Principal component and random forest analyses showed that SOC sequestration was primarily driven by sucrase, urease, available phosphorus, dissolved organic carbon (DOC), microbial diversity indices, and available calcium (p < 0.05), while SIC dynamics were significantly influenced by sucrase, urease, DOC, CO₂ emissions, available calcium, and EC (p < 0.05). These findings underscore the importance of exploring subsoil carbon sequestration mechanisms in arid ecosystems.

Water and nitrogen (N) are the most critical limiting factors for sudangrass (Sorghum sudanense (Piper) Stapf) growth under drip irrigation in arid oases of southern Xinjiang, yet the quantitative interaction mechanism governing yield–quality–efficiency trade-offs remains unclear. This study employed a quadratic orthogonal regression design to generate 11 water–nitrogen treatment combinations (irrigation: 1800–4200 m³·ha⁻¹; nitrogen: 240–720 kg·ha⁻¹). Agronomic traits, dry matter yield, nutritional quality, and nitrogen use efficiency (NUE) were measured through field experiments in 2023–2024, and quadratic models were fitted to identify optimal water–nitrogen bundles maximizing multi-objective performance. Irrigation volume was the dominant factor controlling the plant height, SPAD index, and stem–leaf ratio, whereas stem diameter depended on the water × N interaction (p < 0.01). The “medium-water × moderate-nitrogen” regime (3000 m³·ha⁻¹ + 480 kg·ha⁻¹) maximized dry matter yield (~28 t·ha⁻¹), NUE (~44%) and forage quality (Relative Feed Value > 135, crude protein ≥ 8.8%). This climate-adaptive precision strategy reduces water use by 30% and nitrogen by 20% while increasing yield by 15% and quality by 15%, providing a sustainable production framework for arid and semi-arid regions of Xinjiang.