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

Related authors

Technical Note: Smartphone-based evapotranspiration monitoring
Adriaan J. Teuling and Jasper F. D. Lammers
EGUsphere, https://doi.org/10.5194/egusphere-2023-3096,https://doi.org/10.5194/egusphere-2023-3096, 2024
Short summary
Guiding community discussions on human-water-related challenges by serious gaming in the upper Ewaso Ng’iro river basin, Kenya
Charles Nduhiu Wamucii, Pieter R. van Oel, Adriaan J. Teuling, Arend Ligtenberg, John Mwangi Gathenya, Gert Jan Hofstede, Meine van Noordwijk, and Erika N. Speelman
EGUsphere, https://doi.org/10.5194/egusphere-2023-2459,https://doi.org/10.5194/egusphere-2023-2459, 2023
Short summary
Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)
Awad M. Ali, Lieke A. Melsen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 27, 4057–4086, https://doi.org/10.5194/hess-27-4057-2023,https://doi.org/10.5194/hess-27-4057-2023, 2023
Short summary
Linking reported drought impacts with drought indices, water scarcity and aridity: the case of Kenya
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936, https://doi.org/10.5194/nhess-23-2915-2023,https://doi.org/10.5194/nhess-23-2915-2023, 2023
Short summary
Intensified future heat extremes linked with increasing ecosystem water limitation
Jasper M.C. Denissen, Adriaan J. Teuling, Sujan Koirala, Markus Reichstein, Gianpaolo Balsamo, Martha M. Vogel, Xin Yu, and Rene Orth
EGUsphere, https://doi.org/10.5194/egusphere-2023-1925,https://doi.org/10.5194/egusphere-2023-1925, 2023
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Mathematical applications
Using statistical models to depict the response of multi-timescale drought to forest cover change across climate zones
Yan Li, Bo Huang, and Henning W. Rust
Hydrol. Earth Syst. Sci., 28, 321–339, https://doi.org/10.5194/hess-28-321-2024,https://doi.org/10.5194/hess-28-321-2024, 2024
Short summary
Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations
Magdalena Uber, Michael Haller, Christoph Brendel, Gudrun Hillebrand, and Thomas Hoffmann
Hydrol. Earth Syst. Sci., 28, 87–102, https://doi.org/10.5194/hess-28-87-2024,https://doi.org/10.5194/hess-28-87-2024, 2024
Short summary
The most extreme rainfall erosivity event ever recorded in China up to 2022: the 7.20 storm in Henan Province
Yuanyuan Xiao, Shuiqing Yin, Bofu Yu, Conghui Fan, Wenting Wang, and Yun Xie
Hydrol. Earth Syst. Sci., 27, 4563–4577, https://doi.org/10.5194/hess-27-4563-2023,https://doi.org/10.5194/hess-27-4563-2023, 2023
Short summary
The role of atmospheric rivers in the distribution of heavy precipitation events over North America
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023,https://doi.org/10.5194/hess-27-2645-2023, 2023
Short summary
Study on a mother wavelet optimization framework based on change-point detection of hydrological time series
Jiqing Li, Jing Huang, Lei Zheng, and Wei Zheng
Hydrol. Earth Syst. Sci., 27, 2325–2339, https://doi.org/10.5194/hess-27-2325-2023,https://doi.org/10.5194/hess-27-2325-2023, 2023
Short summary

Cited articles

Allen, C. D., Macalady, A. K., Chenchouni, H., Bachelet, D., Mcdowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D. D., and Hogg, E. H.: A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests, Forest Ecol. Manag., 259, 660–684, https://doi.org/10.1016/j.foreco.2009.09.001, 2010. 
Almendra-Martín, L., Martínez-Fernández, J., Piles, M., and González-Zamora, Á.: Comparison of gap-filling techniques applied to the CCI soil moisture database in Southern Europe, Remote Sens. Environ., 258, 112377, https://doi.org/10.1016/j.rse.2021.112377, 2021. 
Aghakouchak, A., Farahmand, A., Melton, F. S., Teixeira, J., Anderson, M. C., Wardlow, B. D., and Hain, C. R.: Remote sensing of drought: Progress, challenges and opportunities, Rev. Geophys., 53, 452–480, https://doi.org/10.1002/2014RG000456, 2015. 
Anderson, M. C., Hain, C., Otkin, J., Zhan, X., Mo, K., Svoboda, M., Wardlow, B., and Pimstein, A.: An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with US Drought Monitor classifications, J. Hydrometeorol., 14, 1035–1056, https://doi.org/10.1175/JHM-D-12-0140.1, 2013. 
Bennett, A. and Nijssen, B.: Deep learned process parameterizations provide better representations of turbulent heat fluxes in hydrologic models, Water Resour. Res., 57, e2020WR029328, https://doi.org/10.1029/2020WR029328, 2021. 
Download
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.