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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. [ABSTRACT FROM AUTHOR]

The Yangtze River Basin experienced a once-in-a-century extreme drought in 2022 due to extreme weather, which had a serious impact on the local agricultural production and ecological environment. In order to investigate the spatial distribution and occurrence of the extreme drought events, this study used multi-source remote sensing data to monitor the extreme drought events in the Yangtze River Basin in 2022. In this study, the gravity satellite data product CSR_Mascon was used to calculate the GRACE Drought Intensity Index (GRACE-DSI), which was analyzed and compared with the commonly used meteorological drought indices, relative soil humidity, and soil water content data. The results show that (1) terrestrial water storage change data can well reflect the change in water storage in the Yangtze River Basin. Throughout the year, the average change in terrestrial water storage in the Yangtze River Basin from January to June is higher than the average value of 33.47 mm, and the average from July to December is lower than the average value of 48.17 mm; (2) the GRACE-DSI responded well to the intensity and spatial distribution of drought events in the Yangtze River Basin region in 2022. From the point of view of drought area, the Yangtze River Basin showed a trend of extreme drought increasing first, and then decreasing in the area of different levels of drought, and the range of drought reached a maximum in September with a drought area of 175.87 km2, which accounted for 97.71 per cent of the total area; at the same time, the area of extreme drought was the largest, with an area of 85.69 km2; (3) the spatial and temporal variations of the GRACE-DSI and commonly used meteorological drought indices were well correlated, with correlation coefficients above 0.750, among which the correlation coefficient of the SPEI-3 was higher at 0.937; (4) the soil moisture and soil relative humidity products from the CLDAS, combined with soil moisture products from the GLDAS, reflect the starting and ending times of extreme drought events in the Yangtze River Basin in 2022 well, using the information from the actual stations. In conclusion, gravity satellite data, analyzed in synergy with data from multiple sources, help decision makers to better understand and respond to drought. [ABSTRACT FROM AUTHOR]

This paper explored the drought propagation phenomenon based on meteorological, hydrological, and agricultural aspects in the Yangtze River basin (YRB), China. To evaluate meteorological, hydrological, and agricultural droughts, this paper used three drought indices, standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI), and standardized soil moisture index (SSMI), respectively. The community land model (CLM) in the YRB to generate the monthly evapotranspiration, soil moisture, runoff data, which are required for the estimation of drought index, were applied. Different mean durations (6-and 12-month) were used for drought estimation, and propagations of meteorological to hydrological and meteorological and agricultural droughts were investigated for different durations as SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, SPEI12-SSMI12. The average drought propagation between 1950 and 2010 presented the highest autocorrelation and correlation with one-month lags in four combinations of drought indices in SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, and SPEI12-SSMI12. Additionally, this paper estimated the optimal lags of SPEI-SRI and SPEI-SSMI drought propagations using mean 6-and 12-month lag times for six representative drought periods. Therefore, the propagation phenomenon of meteorological to hydrological and to agricultural droughts were confirmed in the YRB. • SPEI, SRI, and SSMI indices have been applied to the Yangtze River basin (YRB). • Propagation analysis of SPEI-SRI and SPEI-SSMI have extended to 1951–2010. • Mean 12-month duration shows clearer drought propagation than mean 6-month duration. • SPEI-SSMI presents 1–7 months propagation time. • SPEI-SRI presents 1–2 months propagation time. [ABSTRACT FROM AUTHOR]