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Meteorological drought predictability dynamics and possible driving mechanisms in a changing environment in the Loess Plateau, China

文献类型：期刊论文

作者Wang, Yiting5; Huang, Shengzhi5,6; Singh, Vijay P.7,8,9; Shi, Haiyun1,10; Leng, Guoyong2; Huang, Qiang5; Luo, Jing5; Zheng, Xudong5; Peng, Jian3,4
刊名ATMOSPHERIC RESEARCH
出版日期2025-04-01
卷号315页码:16
关键词Meteorological drought Predictability Random forest The Loess Plateau Structural Equation Model
ISSN号0169-8095
DOI10.1016/j.atmosres.2024.107842
产权排序8
英文摘要Drought forecasting is important for water resources management and effective response to drought, and the predictability of drought may change under a changing environment. Most of the studies have focused on developing drought forecasting techniques, but limited attention has been made to the theory of drought predictability, such as dynamics of meteorological drought predictability and possible driving mechanism. Here, we characterized the predictability of meteorological drought, based on the Kling-Gupta efficiency (KGE") coefficient of support vector machine regression model. Then we measured the spatial distribution, agglomeration, and dynamic changes of drought predictability, and quantitatively analyzed the main driving forces and relationships of the spatial and temporal dynamics. The Loess Plateau (LP), which is a drought-prone region with frail ecological environment in China, was chosen as a case study. Results indicated that: (1) drought predictability in the western region was higher than that in the eastern region of the LP, with the hot spots concentrated in the western sandy land and agricultural irrigation; (2) meteorological drought predictability in the LP showed a downward trend from 1962 to 2019 under the changing environment, which the autumn drought predictability declined significantly; (3) meteorological, terrestrial factors and air-sea coupling elements dominated the spatialtemporal pattern of meteorological drought predictability via strongly affecting the coefficient of variation of drought index series, and related causal paths were explored. This study sheds new light on drought predictability dynamics under a changing environment, and has significance for improving the ability of drought forecasting, warning, and mitigation.
WOS关键词MODEL ; EFFICIENCY ; BASIN ; WATER
资助项目National Natural Science Foundation of China[52279026] ; National Key Research and Development Program of China[2021YFC3000203] ; Natural Science Basic Research Program of Shaanxi Province[2022JC-LHJJ-05] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA28060100] ; Natural Science Foundation of Inner Mongolia Autonomous Region[2021ZD12]
WOS研究方向Meteorology & Atmospheric Sciences
语种英语
WOS记录号WOS:001379430300001
出版者ELSEVIER SCIENCE INC
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China ; Natural Science Basic Research Program of Shaanxi Province ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Natural Science Foundation of Inner Mongolia Autonomous Region
源URL[http://ir.igsnrr.ac.cn/handle/311030/212065]  
专题陆地水循环及地表过程院重点实验室_外文论文
通讯作者Huang, Shengzhi
作者单位1.Southern Univ Sci & Technol, Sch Environm Sci & Engn, Guangdong Prov Key Lab Soil & Groundwater Pollut C, Shenzhen, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
3.Univ Leipzig, Remote Sensing Ctr Earth Syst Res, D-04103 Leipzig, Germany
4.UFZ Helmholtz Ctr Environm Res, Dept Remote Sensing, Permoserstr 15, D-04318 Leipzig, Germany
5.Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg China, Xian 710048, Peoples R China
6.North China Univ Water Resources & Elect Power, Sch Water Conservancy, Zhengzhou 450046, Peoples R China
7.Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77843 USA
8.Texas A&M Univ, Zachry Dept Civil & Environm Engn, College Stn, TX 77843 USA
9.UAE Univ, Natl Water & Energy Ctr, Al Ain, U Arab Emirates
10.Southern Univ Sci & Technol, Sch Environm Sci & Engn, State Environm Protect Key Lab Integrated Surface, Shenzhen, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Yiting,Huang, Shengzhi,Singh, Vijay P.,et al. Meteorological drought predictability dynamics and possible driving mechanisms in a changing environment in the Loess Plateau, China[J]. ATMOSPHERIC RESEARCH,2025,315:16.
APA Wang, Yiting.,Huang, Shengzhi.,Singh, Vijay P..,Shi, Haiyun.,Leng, Guoyong.,...&Peng, Jian.(2025).Meteorological drought predictability dynamics and possible driving mechanisms in a changing environment in the Loess Plateau, China.ATMOSPHERIC RESEARCH,315,16.
MLA Wang, Yiting,et al."Meteorological drought predictability dynamics and possible driving mechanisms in a changing environment in the Loess Plateau, China".ATMOSPHERIC RESEARCH 315(2025):16.

入库方式： OAI收割

来源：地理科学与资源研究所

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