Articles | Volume 26, issue 12
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


Total article views: 4,620 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,385 1,142 93 4,620 45 67
  • HTML: 3,385
  • PDF: 1,142
  • XML: 93
  • Total: 4,620
  • BibTeX: 45
  • EndNote: 67
Views and downloads (calculated since 03 Nov 2021)
Cumulative views and downloads (calculated since 03 Nov 2021)

Viewed (geographical distribution)

Total article views: 4,620 (including HTML, PDF, and XML) Thereof 4,388 with geography defined and 232 with unknown origin.
Country # Views %
  • 1


Latest update: 19 Jun 2024
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.