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Soil moisture flash droughts often pose significant challenges to humans and ecosystems, with wide‐ranging socioeconomic consequences. However, the underlying mechanisms of flash droughts and their changes remain unquantified. Taking China as a case study, we present a novel framework that combines machine learning with interpretable and cluster techniques to investigate flash drought mechanisms from 1980 to 2018. We first quantified the temporal contribution of drivers and further identified different mechanisms during drought onsets. We subsequently investigated the temporal changes in different mechanisms and classified drought event types. We identified four driving mechanism types triggering drought: Concurrent precipitation, Antecedent‐concurrent precipitation, Antecedent temperature‐concurrent precipitation, and Antecedent transpiration‐concurrent precipitation. The total effects from vegetation transpiration contributed to around 50% of the impacts for mechanisms involving antecedent transpiration and concurrent precipitation, highlighting the non‐neglectable role of vegetation water consumption in drought occurrences. Remarkably, about 60% of flash drought onsets exhibited close association with the antecedent anomalies, which contribute approximately 50% of overall effects, emphasizing the importance of the cumulative effects of drivers. Moreover, driving mechanisms associated with temperature and transpiration increased significantly over time, implying an elevated influence of these factors on droughts. Our classification of drought events reveals that nearly 70% of events were driven by at least two mechanisms, underscoring a complex time‐varying pattern of driving factors during drought events. The proposed holistic framework not only sheds insight into the multifaceted mechanisms driving flash droughts within China but also extends its potential applicability to broader geographical contexts. Key Points: A novel framework combining interpretable machine learning and cluster techniques was proposed to investigate flash drought mechanismFour distinct types of driving mechanisms of flash drought onset in eastern China were discoveredNearly 70% of flash drought events involve multiple mechanisms, emphasizing the time‐varying feature of drought drivers [ABSTRACT FROM AUTHOR]

ABSTRACT Owing to their essential influence on human society and natural environment exerted by inducing disasters, such as floods and droughts, further studies on precipitation extremes in China are needed. This study presents the regional frequency and spatial-temporal patterns of precipitation extremes in China based on a high-resolution (0.5° × 0.5°) daily precipitation dataset from 1961 to 2013. With fuzzy c-means, L-moments methods and other scientific statistical tests, a regional frequency analysis ( RFA) is conducted, aiming to further understand the regional and spatial distribution of precipitation extremes across China. The results show that: (1) the whole Mainland China can be divided into 50 homogeneous regions on the basis of the characteristics of mean annual precipitation and location indices. (2) For most of the regions, Generalized Extreme Value ( GEV), Generalized Normal ( GNO) and Pearson type III ( PE3) distributions of precipitation extremes fit well, according to the results of goodness-of-fit ( GOF) test. (3) For RX1DAY, GEV has the best-fit distribution in the east, northeast and southwest of China, whereas GNO distribution mostly fits the northern and parts of southwest and southeast; in addition, regions which fit PE3 and Generalized Logistic ( GLO) distribute dispersedly across the country. (4) For RX5DAY, GEV mainly fits in the middle, southwestern and southern; GNO and PE3 apply best to the northeastern and northern, respectively. (5) Return periods of 20, 50 and 100 years for their best-fit distributions decrease gradually from southeastern China to northwestern China. Compared with the results of GEV distribution fitted to each grid, RFA may provide more accurate estimates of rainfall quantiles. Definitely, the study results will not only benefit further understanding of the unique and complex features of extreme precipitation in the whole Mainland China but also contribute to the nation-scale flood prevention, control and management in the backdrop of the changing climate. [ABSTRACT FROM AUTHOR]