Climate change has led to increased frequency, duration, and severity of meteorological drought (MD) events worldwide, causing significant and irreversible damage to terrestrial ecosystems. Understanding the impact of MD on diverse vegetation types is essential for ecological security and restoration. This study investigated vegetation responses to MD through a drought propagation framework, focusing on the Yangtze River Basin in China, which has been stricken by drought frequently in recent decades. By analyzing propagation characteristics, we assessed the sensitivity and vulnerability of different vegetation types to drought. Using Copula modeling, the occurrence probability of vegetation loss (VL) under varying MD conditions was estimated. Key findings include: (1) The majority of the Yangtze River Basin showed a high rate of MD to VL propagation. (2) Different vegetation types exhibited varied responses: woodlands had relatively low sensitivity and vulnerability, grasslands showed medium sensitivity with high vulnerability, while croplands demonstrated high sensitivity and moderate vulnerability. (3) The risk of extreme VL increased sharply with rising MD intensity. This framework and its findings could provide valuable insights for understanding vegetation responses to drought and inform strategies for managing vegetation loss.

In 2022, a severe drought and heatwave occurred in the middle and lower reaches of the Yangtze River Basin. Previous studies have highlighted the severity of this event, yet the relevance of soil moisture (SM), as well as vapor pressure deficit (VPD) and vegetation damage, remained unclear. Here, we utilized solar-induced chlorophyll fluorescence (SIF) and various flux data to monitor the impact of drought on vegetation and analyze the influence of different environmental factors. The results indicated a severe situation of drought and heatwave in the Yangtze River Basin in 2022 that significantly affected vegetation growth and the ecosystem carbon balance. SIF and NDVI have respective advantages in reflecting damage to vegetation under drought and heatwave conditions; SIF is more capable of capturing the weakening of vegetation photosynthesis, while NDVI can more rapidly indicate vegetation damage. Additionally, the correlation of SM and SIF are comparable to that of VPD and SIF. By contrast, the differentiation in the severity of vegetation damage among different types of vegetation is evident; cropland is more vulnerable compared to forest ecosystems and is more severely affected by drought and heatwave. These findings provided important insights for assessing the impact of compound drought and heatwave events on vegetation growth.

Compound floods induced by co-occurring multiple drivers may exacerbate the flood impacts and lead to larger flood damage. Exploring future changes in compound flood risk is imperative for flood management and disaster reduction. This study attempts to investigate future changes in compound flood risk across the Yangtze River Basin during 2030 similar to 2100. Future river flow was projected using an improved hydrological model and pairwise series of extremes of rainfall and river flow were extracted from both observed and projected series. Subsequently, stochastic pairs of rainfall and river flow characterizing compound floods were proportionally sampled from their bivariate joint distributions. The damage from each compound flood was obtained from the flood damage function constructed by Random Forests (RF). Further, the expected annual damage (EAD) was calculated to investigate future changes in compound flood risk. Results show that: (1) Future annual maximums of rainfall and river flow are expected to increase by 14.51 % similar to 66.13 % and 1.72 % similar to 55.73 % in the mainstream and northern tributaries, while future annual peak discharge in the southern tributaries (except for the Dongting Lake Basin) is expected to decrease by 4.18 % similar to 12.30 %. A similar spatial distribution of future changes is also found in the bivariate joint distribution of rainfall and river flow. (2) The high coefficient of determination (R-2) of 0.84 indicates the satisfactory simulation and projection capacity of the constructed flood damage function. The positive stepped relationship between flood damage and rainfall or river flow reflects the superposition of multiple flood damage processes. (3) The Han River Basin, the Jialing River Basin, and the two-lakes (the Dongting and Poyang Lakes) area face great threat from compound floods in both historical and future periods. Future compound flood risk is expected to increase by 13.43 % similar to 46.04 % in these regions except for the Poyang Lake Basin, while future risk is expected to increase by 2.03 % similar to 46.04 % in the whole basin. The findings help improve the understanding of future flood risk variations in the Yangtze River Basin and provide essential information for damage reduction.

Terrestrial water storage (TWS) is a key variable in global and regional hydrological cycles. In this study, the TWS changes in the Yangtze River Basin (YRB) were derived using the Lagrange multiplier method (LMM) from Gravity Recovery and Climate Experiment (GRACE) data. To assess TWS changes from LMM, different GRACE solutions, different hydrological models, and in situ data were used for validation. Results show that TWS changes from LMM in YRB has the best performance with the correlation coefficients of 0.80 and root mean square error of 1.48 cm in comparison with in situ data. The trend of TWS changes over the YRB increased by 10.39 +/- 1.27 Gt yr(-1) during the 2003-2015 period. Moreover, TWS change is disintegrated into the individual contributions of hydrological components (i.e., glaciers, surface water, soil moisture, and groundwater) from satellite data, hydrologic models, and in situ data. The estimated changes in individual TWS components in the YRB show that (1) the contribution of glaciers, surface water, soil moisture, and groundwater to total TWS changes is 15%, 12%, 25% and 48%, respectively; (2) Geladandong glacier melt from CryoSat-2/ICESat data has a critical effect on TWS changes with a correlation coefficients of -0.51; (3) the Three Gorges Reservoir Impoundment has a minimal effect on surface water changes (mainly lake water storage), but it has a substantial effect on groundwater storage (GWS), (4) the Poyang and Doting Lake water storage changes are mainly caused by climate change, (5) soil moisture storage change is mainly influenced by surface water, (6) human-induced GWS changes accounted for approximately half of the total GWS. The results of this study can provide valuable information for decision-making in water resources management.

As an important factor of surface processes, soil moisture has great influence on atmospheric circulation and weather climate of local and adjacent areas. Because the observation sites of soil moisture in the Tibetan Plateau (TP) are sparse and the observation time is short, we use a set of satellite retrieval data which has validated by field observations, to study the relationship between earlier soil moisture of TP and later precipitation of eastern China and its mechanism. The results indicate that with the global warming, the general soil moisture of TP has an obvious trend to increase. After removing the linear trend, we define the Tibetan Plateau soil moisture index (TPSMI) to characterize the interannual variation of TP soil moisture. Such variations of soil moisture have great conformance in 0 similar to 10 cm, 10 similar to 40 cm and 40 similar to 100 cm, which makes soil moisture interannual signal from spring continue into summer. The correlation coefficient between spring and summer TPSMI is 0. 56. When the TPSMI is bigger, which means that the soil moisture of eastern TP is bigger, and when the soil moisture of western TP is smaller, there is a latent heat source (sensible heat source) in eastern (western) TP. The two heat sources together induce a cyclone-anticyclone-cyclone wave train from the west of TP through China mainland to northeast China, which presents a prominent quasi-barotropic structure through the middle and upper troposphere. This has great contribution to the enhancement of Northeast Cold Vortex, which leads to the outburst of cold air. At the same time, the South Asian anticyclone gets enhanced and eastward, while the Sub-tropical anticyclone gets enhanced and westward with the converge of warm moist airflow from south and cold dry airflow from north in the Yangtze River basin. In addition to the stronger rising movement, the summer precipitation of the Yangtze River basin is much more. On the contrary, when the TPSMI is smaller, the precipitation of the Yangtze River basin is much less.

In this study, the water balance-based Precipitation-Evapotranspiration-Runoff (PER) method combined with the land surface model Variable Infiltration Capacity (VIC) was used to estimate the spatiotemporal variations of terrestrial water storage (TWS) for two periods, 1982-2005 (baseline) and 2071-2100, under future climate scenarios A2 and B2 in the Yangtze River basin. The results show that the estimated TWS during the baseline period and under the two future climate scenarios have similar seasonal amplitudes of 60-70 mm. The higher values of TWS appear in June during the baseline period and under the B2 scenario, whereas the TWS under A2 shows two peaks in response to the related precipitation pattern. It also shows that the TWS is recharged from February to June during the baseline period, but it is replenished from March to June under the A2 and B2 scenarios. An analysis of the standard derivation of seasonal and interannual TWS time series under the three scenarios demonstrates that the seasonal TWS of the southeastern part of the Yangtze River basin varies remarkably and that the southeastern and central parts of the basin have higher variations in interannual TWS. With respect to the first mode of the Empirical Orthogonal Function (EOF), the inverse-phase change in seasonal TWS mainly appears across the Guizhou-Sichuan-Shaanxi belt, and the entire basin generally represents a synchronous change in interannual TWS. As a whole, the TWS under A2 presents a larger seasonal variation whereas that under B2 displays a greater interannual variation. These results imply that climate change could trigger severe disasters in the southeastern and central parts of the basin.