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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]

Droughts resulting from global warming severely hamper the healthy development of terrestrial vegetation ecosystems. This paper defines a terrestrial vegetation ecological drought index, i.e., the Standardized Water Supply–Demand Index (SSDI), based on the water balance method using the same calculation model as the SPEI. The theory of run is used to analyze the spatial and temporal distribution of the drought characteristics in the Yangtze River Basin (YRB). The results show that (1) the drought events monitored by the SSDI were in good agreement with historical drought events, and the correlation coefficient between SSDI and NDVI (0.94) was significantly higher than that between SPEI and NDVI (0.88). (2) About 55.4% of the regions in the YRB experienced more than 13 droughts, and about 41.4% of the regions had an average drought duration of more than 3.1 months. In the northern part of the YRB, droughts tend to develop in a short-term high frequency, while in the southern part of the YRB, there is a long-term low-frequency development trend. Nearly 24.5% of the regions have an average drought intensity of more than 1.4, and most of them are located in the lower reaches of the Yangtze River. (3) Over the last 18 years, about 79.5% of the regions in the YRB showed an increasing trend in SSDI, of which 36.8% showed an increasing trend of more than 0.04/yr. In addition, 40.4% of the regions showed a significant upward trend. Precisely analyzing the spatiotemporal variation of drought characteristics in the YRB is critical for drought risk assessment and sustainable development of water resources and could provide a theoretical basis for effective water resource allocation and drought relief. • A new drought monitoring index, i.e., the Standardized Water Supply–Demand Index (SSDI) was defined. • SSDI can effectively monitor drought events. • SSDI is more suitable for monitoring ecological drought. • Drought of vegetation ecosystem in the Yangtze River Basin was assessed and analyzed with the SSDI. • It provides a theoretical basis for drought management and water allocation in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]

For the day-by-day evaporation observation data in the Yangtze River Basin from 1951 to 2019, the effects of the gradual shift of observation instruments from 20 cm diameter evaporation pan (D20) to E601 evaporation pan after 1980 are discussed, including inconsistent data series, and missing and anomalous data. This study proposes a governance and improvement method for dual-source evaporation data (GIME). The method can accomplish the homogenization of data from different observation series and solve the problem of inconsistent and missing data, and we applied it in practice on data of the Yangtze River Basin. Firstly, the primary and secondary periods of the data were obtained by wavelet periodicity analysis; secondly, we considered the first cycle of observations to be representative of the sample and calculated the conversion relationship between the primary and secondary periods; thirdly, the conversion coefficient between the dual-source observations was calculated, and the results were corrected for stations outside the main cycle; finally, the daily evaporation dataset of E601 pan was established through data fusion and interpolation technology. The study found that the annual average conversion coefficients of the D20 and E601 pans in the Yangtze River Basin are basically between 0.55 and 0.80, and there are obvious differences in different regions. The conversion coefficient is positively correlated with relative humidity, wind speed, minimum temperature and altitude; and negatively correlated with sunshine duration, average temperature and maximum temperature. Evaporation is high in the upper reaches of the basin and low in the middle and lower reaches; in particular, evaporation is highest in the southwest, which is associated with the drought hazards. In addition, the article presents the spatial distribution of the conversion coefficients of D20 and E601 pans in the Yangtze River Basin. The results can realize the rapid correction of the evaporation data of the local meteorological department, and can be extended to the processing of other types of data in similar areas. [ABSTRACT FROM AUTHOR]