卫星遥感技术对地表水的快速获取和高精度监测是理解水文干旱发生机理和演变规律的重要途径，不断增多的全球动态地表水体覆盖产品为研究地表水体动态变化与干旱的响应关系提供了宝贵的契机。本研究以长江中游区域及其4683个流域单元作为研究对象，基于全球动态地表水体产品数据集GLAD-GSWD，采用动态水体指数DWI（Dynamic Surface Water Index）量化流域1999-2020年水体面积的季节性异常变动信号，探讨了基于卫星观测的动态水体面积表征的水文干旱与气象干旱的响应关系，并对其进行了不确定性分析。结果表明：（1）DWI能够有效刻画出长江中游区域及其流域单元的干湿状态变化。在长江中游区域，DWI时间序列与四个时间尺度（1，3，6和12个月）的标准化降水指数SPI（Standardized Precipitation Index）时间序列波动基本一致，且均呈显著正相关关系，其中与SPI6的相关系数最高（r=0.484，p<0.01）。88.2%的子流域DWI与SPI呈显著正相关，响应时间以6至12个月为主；（2）DWI和SPI相关关系的不确定性主要来自两个方面。一是数据质量，包括流域单元内季节性水体面积过小和有效观测数据过少等；二是流域尺度，统计分析的流域尺度越大，流域水体受气象要素异动的影响越直接，相关关系越强。以子流域为监测对象，以动态水体为监测数据的水文干旱监测指标构建方法，能够实现在连续的空间上进行水文干旱监测，对遥感动态水体产品服务于区域乃至全球水文干旱监测与评估具有重要参考价值。

Under the influence of global climate change and human activities, the frequency and intensity of drought have increased, posing challenges to food, ecology, and water security. Using satellite remote sensing technology for rapid acquisition, comprehensive coverage, and high-precision monitoring of surface water is crucial for understanding the mechanisms and evolution of hydrological drought. With the continuous expansion of global dynamic surface water coverage products, there"s a valuable opportunity to explore the response relationship between surface water dynamics and drought. This study focused on the middle reaches of the Yangtze River and its 4683 sub-basin units, utilizing the Global Surface Water Dynamic (GLAD-GSWD) dataset to quantify abnormal changes in seasonal surface water areas from 1999 to 2020 through the Dynamic Surface Water Index (DWI). It aimed to investigate the response relationship between hydrological drought and meteorological drought from the perspective of dynamic surface water area, conducting an analysis of its uncertainties. The results showed that: (1) DWI effectively depicted changes in the wet/dry status of the middle reaches of the Yangtze River and its sub-basin units. From 1999 to 2020, the fluctuations of DWI time series and SPI time series in the middle reaches of the Yangtze River are basically the same, which can capture the impacts of most of the extreme hydrological and climatic events on the dynamic ranges of surface water in the region. The fluctuations of the DWI time series show significant positive correlations with the SPI time series at the four time scales (1, 3, 6, and 12 months), with the highest correlations with the SPI6 (r=0.484, p<0.01). Approximately 88.2% of the 4683 sub-basin units showed a significant positive correlation between DWI and SPI, with response times predominantly between 6 and 12 months; (2) The study also uncovered uncertainties in the correlations between DWI and SPI, primarily stemming from two key factors. The quality of raw data posed a challenge, marked by insufficient seasonal surface water area coverage and limited observed data, potentially leading to the degradation of correlations. The HANTS algorithm combines smoothing and filtering techniques to effectively identify, remove, and fill in outliers in time series data. The data reconstructed based on HANTS effectively improved the monitoring effect of DWI, but it couldn"t completely eliminate the impact of data quality. Secondly, the complex interplay of meteorological droughts at both local and upstream basins significantly influenced surface water in the sub-basins. Consequently, as the statistical analysis expanded to larger basin scales, the direct impact of meteorological factors on basin water bodies strengthened, resulting in a more pronounced correlation. The methodology employed in constructing hydrological drought monitoring indicators, with sub-basins as monitoring units and dynamic water bodies as monitoring data, not only offers invaluable insights for regional and global hydrological drought monitoring and assessment but also underscores the pivotal role of remote sensing dynamic water products in advancing these endeavors. Additionally, efforts to enhance the quality and resolution of satellite remote sensing data promise in refining the accuracy and reliability of hydrological drought monitoring, thereby bolstering resilience against water-related crises on both regional and global scales.