Spatiotemporal distribution of drought and nonlinear propagation probability in Sichuan-Chongqing region

The escalating frequency of extreme drought events poses grave threats to water security and agricultural stability in the ecologically vulnerable Sichuan-Chongqing region of Southwest China. To clarify the nonlinear propagation probability from meteorological to agricultural drought, this study conducted a systematic comparative analysis of the 2006 progressive drought and 2022 compound heat-drought events. The spatiotemporal evolution of these two typical drought archetypes was characterized using the Standardized Precipitation Index (SPI), Temperature Condition Index (TCI) and Soil Moisture Condition Index (SMCI). The joint propagation probabilities across three typical sub-basins (Fujiang, Jialing, and Qujiang) were quantified based on bivariate Copula functions, while dissecting the driving roles of precipitation and evapotranspiration anomalies. Results showed that precipitation deficits acted as the primary driver for both events, but the 2022 compound heat-drought was drastically exacerbated by extreme thermal forcing. Enhanced evapotranspiration was associated with intensified drought development and higher sensitivity of vegetation to moisture deficits in 2022. Drought propagation exhibited distinct scale dependence and regional heterogeneity: SPI-1 was identified as the optimal scale for driving TCI, and SPI-3 showed the strongest association with SMCI variability. Bivariate Copula analysis revealed that the Frank Copula provided the best fit for the SPI1-TCI dependence structure, while the optimal Copula selection for SPI3-SMCI varied across sub-basins. This study highlights that integrating multi-scale climatic drivers with local environmental resilience is essential for improving drought risk assessment and adaptive water resource management in complex terrain regions.