Soil moisture (SM) plays a crucial role in the hydrological and ecological processes of the Yellow River Basin (YRB), with its spatiotemporal distribution and variability serving as key factors for understanding ecosystem responses to environmental changes. However, previous research has often overlooked the spatiotemporal variation of SM across different soil layers and the complex bidirectional interactions between SM and vegetation, particularly as indicated by the Normalized Difference Vegetation Index (NDVI), within different vegetation zones and soil layers. Widely used in fields such as agriculture and water cycle research, the GLDAS dataset has been applied to analyze the spatiotemporal patterns of SM at four different depths (0-10 cm, 10-40 cm, 40-100 cm, and 100-200 cm) in the YRB from 1948 to 2022, revealing a continuous increase in SM over time, with more pronounced changes after identified breakpoints (1985 for the 10-40 cm layer, and 1986 for the other layers). Granger causality tests show that the bidirectional interaction between NDVI and SM dominates across all soil layers and regions, far surpassing the unidirectional effects of SM on NDVI or vice versa. Regardless of whether SM or NDVI is the primary variable, the Temperate Evergreen Broadleaf Forest (TEBF) region consistently exhibits the strongest lag effects across all layers, followed by the Qinghai-Tibet Plateau Alpine Vegetation (QTPAV) and the Temperate Desert Region (TDR). The Subtropical Warm Temperate Deciduous Forest (SWTDF) and Temperate Grassland Region (TGR) show the weakest lag effects. This research offers new insights into the mutual feedback between vegetation and hydrology in the YRB and provides a scientific basis for more effective water resource management.