Studies show that meteorological and agricultural droughts are inherently correlated, and understanding the spatiotemporal propagation mechanism between these two drought types is crucial for drought early warning and mitigation. In this study, the standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSMI) are used to evaluate meteorological drought and agricultural drought in northwestern China from 1960 to 2018. A three-dimensional clustering method is then adopted to capture drought events, and analyze drought dynamics. Furthermore, meteorological-agricultural drought event pairs are matched from a higher dimension (i.e., space and time), offering profound insights into drought propagation mechanisms on both temporal and spatial scales. The results indicate that agricultural drought exhibits longer duration but smaller magnitude compared to meteorological drought based on identification results, and the dynamic migration process of individual drought event is visually and explicitly described from a three-dimensional perspective. Using a novel spatiotemporal matching procedure, 53 drought event pairs are successfully matched. Following matching, the magnitude of drought events escalates, characterized by prolonged duration, expanded area, increased severity, and lengthened migration distance. Minor meteorological drought events are less likely to cause agricultural drought events, while drought events with larger magnitudes are prone to induce agricultural drought events in various ways. The propagation of most paired drought events involved in the C1, C2 and C4 categories moves in the lateral direction with the relatively long average propagation distance, while moving in the vertical direction for the C3 category. Additionally, the season of paired drought events with the highest occurrence is spring, spring, summer, and autumn for the C1, C2, C3 and C4 categories, respectively. From a higher perspective, the propagation process from meteorological to agricultural drought is effectively and visually depicted, characterized by pooling effect, lengthening effect, lagging effect, and attenuation effect. The findings of this study contribute to a better understanding of drought development and propagation mechanisms, providing solutions to the application restrictions of traditional methods in regions with broad spatial coverage.