Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Abstract > 0.8 Kling–Gupta efficiency in 161 out of the 179 catchments. By the late 21st century, bivariate drought risk is projected to double over 60 % of the catchments mainly located in southwestern China under SSP5-85, which shows the increase in drought duration and severity. Our hybrid model also projected substantial GDP and population exposure by increasing bivariate drought risks, suggesting an urgent need to design climate mitigation strategies for a sustainable development pathway.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China ; volume:28 ; number:14 ; year:2024 ; pages:3305-3326 ; extent:22
Hydrology and earth system sciences ; 28, Heft 14 (2024), 3305-3326 (gesamt 22)
- Creator
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Liu, Rutong
Yin, Jiabo
Slater, Louise
Kang, Shengyu
Yang, Yuanhang
Liu, Pan
Guo, Jiali
Gu, Xihui
Zhang, Xiang
Volchak, Aliaksandr
- DOI
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10.5194/hess-28-3305-2024
- URN
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urn:nbn:de:101:1-2408061449402.840749146917
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:57 AM CEST
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Associated
- Liu, Rutong
- Yin, Jiabo
- Slater, Louise
- Kang, Shengyu
- Yang, Yuanhang
- Liu, Pan
- Guo, Jiali
- Gu, Xihui
- Zhang, Xiang
- Volchak, Aliaksandr
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