Drought propagation in china: Uncertainties originate more from dataset choice than drought index selection
文献类型：期刊论文
| 作者 | Huang, Kesheng2; Zhang, Haicheng1,2; Cui, Guotao1,2; Wang, Yijia5; Yin, Mijia3,4; Du, Jianhui1,2 |
| 刊名 | ATMOSPHERIC RESEARCH
 |
| 出版日期 | 2026 |
| 卷号 | 330页码:108555 |
| 关键词 | Mutiple datasets Mutiple drought indices Uncertainty China Drought propagation time Drought propagation propability |
| ISSN号 | 0169-8095 |
| DOI | 10.1016/j.atmosres.2025.108555 |
| 产权排序 | 4 |
| 文献子类 | Article |
| 英文摘要 | Accurate assessment of drought propagation time (PT) and probability (PB) from meteorological to soil moisture drought is crucial for mitigating natural and socio-economic losses. However, inconsistencies among datasets and drought indices (DIs) hinder reliable early warning. Here, we evaluated multiple meteorological and soil moisture datasets against in-situ observations to establish a benchmark. Four DIs-SPI, SPEI, PA, and MI-were employed to estimate PT and PB using maximum correlation coefficient and Copula function. We further quantified uncertainties arising from datasets and DIs and proposed a framework for selecting optimal DIs under varying dataset scenarios. The results show that: (i) Benchmark-based PT ranges from 3.10 months (for SPEI) to 5.37 months (for MI) and PB increases with the regional humidity. (ii) ERA5-Land exhibits the highest spatial consistency, matching benchmark PT in 48.47 % (MI) to 61.62 % (SPEI) of pixels, with no significant monthly bias. In contrast, MERRA-2 yields prolonged PT in over 80 % of pixels and shows substantial overestimations (4-10 months) in humid regions. For PB, more than 80 % of pixels from ERA5-Land, GLDAS-2, and MERRA-2 show significant overestimations. (iii) On average, 67.63 % of pixels display greater PT uncertainty from dataset differences than from DI differences, and 68.77 % show higher PB uncertainty from datasets. Compared to the other indices, SPEI can minimize the assessment uncertainties in drought PT/PB across different dataset scenarios. These findings provide a quantitative basis for selecting DIs and datasets, supporting more reliable drought propagation assessment in China. |
| URL标识 | 查看原文 |
| WOS关键词 | MOISTURE ; PRECIPITATION ; SENSITIVITY ; LEVEL |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001597672900001 |
| 出版者 | ELSEVIER SCIENCE INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217701]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Du, Jianhui |
| 作者单位 | 1.Carbon Water Res Stn Karst Reg Northern Guangdong, Guangzhou, Peoples R China; 2.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China; 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China; 5.South China Normal Univ, Sch Geog, Guangzhou, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Huang, Kesheng,Zhang, Haicheng,Cui, Guotao,et al. Drought propagation in china: Uncertainties originate more from dataset choice than drought index selection[J]. ATMOSPHERIC RESEARCH,2026,330:108555. |
| APA | Huang, Kesheng,Zhang, Haicheng,Cui, Guotao,Wang, Yijia,Yin, Mijia,&Du, Jianhui.(2026).Drought propagation in china: Uncertainties originate more from dataset choice than drought index selection.ATMOSPHERIC RESEARCH,330,108555. |
| MLA | Huang, Kesheng,et al."Drought propagation in china: Uncertainties originate more from dataset choice than drought index selection".ATMOSPHERIC RESEARCH 330(2026):108555. |
入库方式： OAI收割
来源：地理科学与资源研究所
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