Articles | Volume 26, issue 12
https://doi.org/10.5194/hess-26-3241-2022
https://doi.org/10.5194/hess-26-3241-2022
Research article
 | 
24 Jun 2022
Research article |  | 24 Jun 2022

Analysis of flash droughts in China using machine learning

Linqi Zhang, Yi Liu, Liliang Ren, Adriaan J. Teuling, Ye Zhu, Linyong Wei, Linyan Zhang, Shanhu Jiang, Xiaoli Yang, Xiuqin Fang, and Hang Yin

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Latest update: 19 Jun 2024
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Short summary
In this study, three machine learning methods displayed a good detection capacity of flash droughts. The RF model was recommended to estimate the depletion rate of soil moisture and simulate flash drought by considering the multiple meteorological variable anomalies in the adjacent time to drought onset. The anomalies of precipitation and potential evapotranspiration exhibited a stronger synergistic but asymmetrical effect on flash droughts compared to slowly developing droughts.