Accurate estimation of soil hydraulic parameters under drip irrigation is essential for improving water flow simulations and optimizing irrigation management; however, field measurements in aeolian sandy soils are often expensive and time-consuming. This study focused on typical aeolian sandy soils in the Kubuqi Desert. Field drip irrigation experiments were conducted to obtain temporal variations in soil water content and wetting front advancement, which were used to inversely estimate and calibrate hydraulic parameters for different soil layers. Soil pore space characteristics were quantified using nitrogen adsorption, and their relationships with hydraulic parameters were analyzed through correlation and redundancy analyses. On this basis, the combined effects of particle-size distribution and pore space structure on parameter prediction were evaluated, and soil water movement under drip irrigation was simulated and validated using HYDRUS-2D/3D. The results indicated pronounced spatial variability in soil hydraulic parameters. Residual water content, saturated hydraulic conductivity, and pore-size distribution index were significantly correlated with specific surface area, total pore volume, mean pore diameter, micropore volume fraction, and pore fractal dimension. Compared with approaches based solely on particle-size distribution, incorporating pore space structure effectively reduced the prediction errors of both hydraulic parameters and wetting front migration, thereby improving simulation accuracy. These findings demonstrate that integrating particle-size distribution and pore space characteristics provides a feasible approach for the rapid estimation of hydraulic parameters and the analysis of water movement in aeolian sandy soils under drip irrigation.
Qin et al. (Wed,) studied this question.