A new multivariate composite drought index considering the lag time and the cumulative effects of drought
文献类型：期刊论文
| 作者 | Yuan, Mengjia3,4; Gan, Guojing2; Bu, Jingyi1; Su, Yanxin3,4; Ma, Hongyu3,4; Liu, Xianghe3,4; Zhang, Yongqiang4; Gao, Yanchun4 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2025-06-01 |
| 卷号 | 653页码:132757 |
| 关键词 | Drought monitoring Multivariate composite drought index Lag time Cumulative effects Gringorten empirical formula |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2025.132757 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Frequent and intense droughts pose significant threats to ecosystem health and human society under global change, making timely and rapid detection of such events crucial. Drought index is an essential tool for drought monitoring and risk assessment. Univariate drought indices cannot effectively characterize comprehensive drought characteristics and rarely account for the time lag between different types of droughts as well as their cumulative effects. Considering this, we developed a multivariate composite drought index (MCDI) using the Gringorten empirical formula based on four drought indices representing meteorological drought (Standardized Precipitation Actual Evapotranspiration Index, SPAEI), agricultural drought (Standardized Soil Moisture Index SSI), and hydrological drought (Standardized Runoff Index (SRI), and Water Storage Deficit Index (WSDI)). To verify the effectiveness of MCDI, we first calculated the Pearson correlation coefficients (PCC) between scPDSI (Self-calibrating Palmer Drought Severity Index) and MCDI in China. The results showed that the percentage of pixels with PCC greater than 0.5 was 70.02 % (p < 0.05). Then we analyzed the spatial/temporal drought trends in China and different hydroclimatic zones. Drought indices performed differently, and MCDI generally exhibited a dry areas become wetter, wet areas become drier pattern in China based on the trends shown by regional means. However, in terms of spatial distribution, the wet and dry trends in China are highly spatially heterogeneous. In addition, we selected two typical drought events that occurred in Arid/Semi-Arid (Inner Mongolia) and Humid/Semi-Humid (Yunnan Province) zones, respectively, to assess the ability of the MCDI to characterize drought. Compared with other drought indices and drought indicators (Soil Moisture and Solar-induced Chlorophyll Fluorescence), MCDI characterized the drought event most consistently with official records and responded faster to drought. Overall, the MCDI has good potential for drought monitoring and assessment. |
| URL标识 | 查看原文 |
| WOS关键词 | TERRESTRIAL WATER STORAGE ; WET GETS WETTER ; INDUCED CHLOROPHYLL FLUORESCENCE ; RIVER-BASIN ; GLOBAL ASSESSMENT ; INNER-MONGOLIA ; CLIMATE-CHANGE ; CHINA ; PRECIPITATION ; EVAPOTRANSPIRATION |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001424478200001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/212271]  |
| 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 | Gao, Yanchun |
| 作者单位 | 1.Univ New Hampshire, Inst Study Earth Oceans & Space, Earth Syst Res Ctr, Durham, NH 03824 USA 2.Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Watershed Geog Sci, Nanjing 210008, Peoples R China; 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Yuan, Mengjia,Gan, Guojing,Bu, Jingyi,et al. A new multivariate composite drought index considering the lag time and the cumulative effects of drought[J]. JOURNAL OF HYDROLOGY,2025,653:132757. |
| APA | Yuan, Mengjia.,Gan, Guojing.,Bu, Jingyi.,Su, Yanxin.,Ma, Hongyu.,...&Gao, Yanchun.(2025).A new multivariate composite drought index considering the lag time and the cumulative effects of drought.JOURNAL OF HYDROLOGY,653,132757. |
| MLA | Yuan, Mengjia,et al."A new multivariate composite drought index considering the lag time and the cumulative effects of drought".JOURNAL OF HYDROLOGY 653(2025):132757. |
入库方式： OAI收割
来源：地理科学与资源研究所
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