Articles | Volume 27, issue 2
https://doi.org/10.5194/hess-27-559-2023
https://doi.org/10.5194/hess-27-559-2023
Research article
 | 
27 Jan 2023
Research article |  | 27 Jan 2023

Estimating propagation probability from meteorological to ecological droughts using a hybrid machine learning copula method

Tianliang Jiang, Xiaoling Su, Gengxi Zhang, Te Zhang, and Haijiang Wu

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Manuscript not accepted for further review
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Cited articles

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Altunkaynak, A. and Jalilzadnezamabad, A.: Extended lead time accurate forecasting of palmer drought severity index using hybrid wavelet-fuzzy and machine learning techniques, J. Hydrol., 601, 126619, https://doi.org/10.1016/j.jhydrol.2021.126619, 2021. 
Andreadis, K. M., Clark, E. A., Wood, A. W., Hamlet, A. F., and Lettenmaier, D. P.: Twentieth-Century Drought in the Conterminous United States, J. Hydrometeorol., 6, 985–1001, https://doi.org/10.1175/jhm450.1, 2005. 
Apurv, T., Sivapalan, M., and Cai, X.: Understanding the role of climate characteristics in drought propagation, Water Resour. Res., 53, 9304–9329, https://doi.org/10.1002/2017WR021445, 2017. 
Ayantobo, O. O. and Wei, J.: Appraising regional multi-category and multi-scalar drought monitoring using standardized moisture anomaly index (SZI): A water-energy balance approach, J. Hydrol., 579, 124139, https://doi.org/10.1016/j.jhydrol.2019.124139, 2019. 
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Short summary
A hybrid method is developed for calculating the propagation probability of meteorological to ecological drought at different levels. Drought events are identified from a three-dimensional perspective. A spatial and temporal overlap rule is developed for extracting propagated drought events.