Mobile drip irrigation (MDI) systems integrate the technological advantages of center-pivot irrigation (CPI) systems and drip irrigation systems, boasting a high water-saving potential. To further enhance water use efficiency in alfalfa production in northern China, this preliminary study verified the accuracy of the HYDRUS-2D soil water movement numerical model through field experiments. Using the numerical model, four drip-line installation distances (60, 75, 90, and 105 cm), three deficit irrigation thresholds (45–50% FC, 55–60% FC, and 65–70% FC), and four irrigation depths (70% W, 85% W, 100% W, and 115% W) were set to simulate root water uptake, soil surface evaporation, total irrigation amount, and deep percolation during the entire growth cycle of alfalfa, respectively. Objective functions were constructed according to the simulation results, and the NSGA-II algorithm was used for multi-objective optimization of the deficit irrigation schedule. The preliminary results indicated that HYDRUS-2D can accurately simulate soil water movement under MDI systems, as the RMSE values of soil water content at all measured depths were less than 0.021 cm³/cm³, with the NRMSE values being below 23.3%, and the MAE values below 0.014 cm³/cm³. Increasing the deficit irrigation threshold from F1 to F3 enhanced root water uptake by 12.24–15.34% but simultaneously increased the total irrigation amount, soil surface evaporation (by up to 29.58%), and the risk of deep percolation; similar trends were observed with increasing irrigation depth. The drip-line installation distance had no significant impact on irrigation performance. The NSGA-II multi-objective optimization algorithm was used to obtain Pareto-optimal solutions that balance conflicting objectives. For this case study, a drip-line installation distance of 105 cm, a deficit irrigation threshold of 50–55% FC, and an irrigation depth of 112% W were recommended to achieve balance among the various optimization objectives. This study provides a preliminary framework for optimizing MDI systems and irrigation strategies. However, since a deeper root distribution (>80 cm) was not investigated in this study, future research incorporating deeper root zones is required for developing more comprehensive irrigation scheduling suitable for typical alfalfa cultivation scenarios.

Water scarcity and soil salinization constrain sustainable alfalfa (Medicago sativa L.) production in arid Xinjiang, China. Although drip irrigation and microbial inoculants improve soil quality and crop productivity, their synergistic effects on rhizosphere ecosystems remain unclear. This study investigated the effects of drip irrigation combined with composite microbial inoculants on rhizosphere soil properties, fungal communities, and alfalfa yield. A two-factor randomized block experiment was conducted with four irrigation levels (6450, 7050, 7650, and 8250 m³/ha) and three inoculant rates (0, 0.5, and 1.0 m³/ha), with conventional irrigation (9750 m³/ha) as the control. We analyzed soil properties, fungal communities, and ecological relationships using high-throughput sequencing and partial least squares path modeling. Combined irrigation and inoculation improved soil nutrient availability, reduced rhizosphere salinity, and enhanced fungal network stability. Moderate irrigation combined with inoculation increased soil alkali-hydrolyzable nitrogen, available phosphorus, and available potassium, while W4J2 achieved the highest yield. Irrigation explained more fungal community variation (33.2%) than inoculation (18.6%), with salinity and nutrients as key drivers. Path analysis revealed that irrigation directly promoted yield, whereas inoculation indirectly enhanced productivity through soil improvement and fungal regulation. Integrating drip irrigation with microbial inoculants provides an effective strategy for sustainable forage production in saline arid regions.