Study region: The Loess Plateau of China Study focus: Meteorological drought (MD) is the main driver and precursor of hydrological drought (HD). This process is susceptible to multiple factors. Previous studies have primarily used qualitative methods to examine how influencing factors affect drought propagation, overlooking the interactions between them. A factorial Bayesian propagation ensemble (FBPE) approach is developed to quantify the primary and interaction contributions of various meteorological, underlying surface and environmental, and human-activity factors to drought transmission. This method is proposed by integrating the Bayesian model averaging (BMA) and factorial effect analysis (FEA). The maximum Pearson correlation coefficient (MPCC) and drought propagation time (DPT) are calculated to characterize the process. New hydrological insights for the region: The results showed that: (i) the propagation time from meteorological drought to hydrological drought exhibits distinct seasonal and regional characteristics, with an average DPT of 3.2 months; (ii) seven factors are selected for drought propagation modeling, among which the multi-year mean temperature contributes most significantly to DPT, accounting for 13.49 %; (iii) the interaction between multi-year mean temperature and multi-year mean soil moisture also shows a notable effect on drought propagation time, contributing 5.6 %; (iv) the contribution of multi-year mean temperature to the propagation of drought increases from humid areas to arid area. In the context of global warming, the relationship between MD and HD will be closer than it has been in previous historical periods.