Investigating the propagation and influencing mechanism that transitions a meteorological drought to a hydrological drought in a changing environment is crucial for understanding the formation process and mechanism of hydrological drought. Furthermore, it is essential to establish an effective hydrological drought warning system based on meteorological drought. To assess the dynamic changes in the spread of meteorological drought to hydrological drought during various seasons, this study employs the Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Normalized Vegetation Index (NDVI) to represent meteorological, hydrological, and vegetation droughts, respectively, in the Ganjiang River Basin (GRB) from 2002 to 2020. Considering that meteorological drought can be caused not only by insufficient precipitation but also by excessive evaporation, an additional index, namely the Evaporative Demand Drought Index (EDDI), is constructed to quantify meteorological drought resulting from evaporation factors. The article analyzes the characteristics of the spatiotemporal evolution of meteorological, hydrological, and vegetation drought. The Spearman rank correlation coefficient is employed to calculate the propagation time of different seasons from meteorological drought to hydrological/vegetation drought and from hydrological drought to vegetation drought. Furthermore, we examine the propagation relationship among meteorological, hydrological, and vegetation drought in the time-frequency domain through cross-wavelet analysis and explore the key factors and physical mechanisms that influence the propagation of drought in various seasons. The result shows: The propagation time from meteorological to hydrological drought (SPI-SRI) is shortest in spring, extended during summer and autumn, and longest in winter. The meteorological drought arising from excessive evapotranspiration in autumn has the most substantial impact on hydrological drought. Vegetation drought and meteorological/hydrological drought exhibit significant intermittent resonance periods in 0~6 months and significant stable resonance periods in 7~15 months.

The impact of drought on ecosystems has become increasingly prominent. This study used the MODIS remote-sensing vegetation index and standardized precipitation index to quantify vegetation coverage status and meteorological drought level. Using the copula method, the joint distribution of the drought index and related vegetation cover variables was simulated for the first time. The conditional distribution of vegetation biomass was deduced, and the multidimensional response between vegetation biomass and drought was explored to understand the possible vegetation loss under different drought severity conditions. The Three-River Headwaters (TRH) region is the source place of the Yangtze River, Yellow River, and Lancang River, where the ecosystem is characterized by innate vulnerability. Using this region as a case study, the results show that the spatiotemporal evolution of drought and vegetation in the TRH region has apparent regional heterogeneity. The vegetation cover in the eastern region is significantly better than that in the northwestern region, while the vegetation growth trend in the northwestern region is stronger than that in the southeastern region. It is feasible to build a vegetation-drought multidimensional response model based on the copula method. In 92.5% of the TRH region, vegetation cover was significantly affected by the severity of the drought. The impact on the growth of vegetation caused by persistent drought events was higher than that of short-term but high-intensity drought. The vegetation in the TRH area has a certain degree of drought resistance. This study provides outstanding theoretical support and reference for the protection of the TRH basin ecosystem.

In a changing environment, changes in terrestrial water storage (TWS) in basins have a significant impact on potential floods and affect flood risk assessment. Therefore, we aimed to study the impact of TWS on potential floods. In this study, we reconstructed the TWS based on precipitation and temperature, evaluated the reconstructed TWS data based on Gravity Recovery and Climate Experiment (GRACE)-TWS data, and analyzed and calculated the flood potential index (FPI) in the Yangtze River Basin (YRB). The related influencing factors were analyzed based on the Global Land Data Assimilation System (GLDAS) data and Granger’s causality test. The main conclusions are as follows: (1) although the GRACE-TWS anomaly (GRACE-TWSA) in the YRB showed an increasing trend for the averaged TWSA over all grids in the whole basin (i.e., 0.31 cm/a, p < 0.05), the variable infiltration capacity-soil moisture anomalies (VIC-SMA) showed a decreasing trend (i.e., −0.048 cm/a, p > 0.05) during April 2002–December 2019; (2) a larger relative contribution of detrended precipitation to FPI was found in the Jialingjiang River Basin (JRB), Wujiang River Basin (WRB), Dongting Lake Rivers Basin (DLRB), YinBin-Yichang reaches (YB-YC), and Yichang-Hukou reaches (YC-HK), while the contribution of detrended TWS to FPI in the Poyang Lake Rivers Basin (PLRB) was larger than that in other basins; and (3) the original and detrended soil moisture (SM) and TWS in the YRB showed a significant positive correlation (p < 0.05), while the significant effect of SM on TWS caused a change in FPI in the YRB and its sub-basins. This study is of great significance for the correct understanding of the FPI and the accurate assessment of flood risk.