Evaluation of Three Long-Term Remotely Sensed Precipitation Estimates for Meteorological Drought Monitoring over China
文献类型：期刊论文
| 作者 | Li, Yanzhong; Zhuang, Jiacheng; Bai, Peng; Yu, Wenjun; Zhao, Lin; Huang, Manjie; Xing, Yincong |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023 |
| 卷号 | 15期号:1 |
| 关键词 | drought monitoring meteorological drought remotely sensed precipitation estimates (RSPEs) SPI drought characteristics CMA |
| DOI | 10.3390/rs15010086 |
| 文献子类 | J |
| 英文摘要 | Remotely sensed precipitation estimates (RSPEs) play an essential role in monitoring drought, especially in ungauged or sparsely gauged areas. In this study, we evaluated the ability of three popular long-term RSPEs (PERSIANN, CHIRPS, and MSWEP) in capturing the meteorological drought variations over the 10 first-level water resource basins of China, based on the standardized precipitation index (SPI). Drought events were identified by run theory, and the drought characteristics (i.e., duration, severity, and intensity) were also evaluated and compared with a gridded in situ observational precipitation dataset (CMA). The results showed that the three RSPEs could generally capture the spatial patterns and trends of the CMA and showed better performance in the wetter basins. MSWEP had the best performance for the categorical skill of POD, followed by CHIRPS and PERSIANN for the four timescales. SPI6 was the optimal timescale for identifying meteorological drought events. There were large skill divergences in the 10 first-level basins for capturing the drought characteristics. CHIRPS can efficiently reproduce the spatial distribution of drought characteristics, with similar metrics of MDS, MDI, and MDP, followed by MSWEP and PERSIANN. Overall, no single product always outperformed the other products in capturing drought characteristics, underscoring the necessity of multiproduct ensemble applications. Our study's findings may provide useful information for drought monitoring in areas with complex terrain and sparse rain-gauge networks. |
| WOS关键词 | HAIHE RIVER-BASIN ; HYDROLOGICAL DROUGHT ; SPI ; PRODUCTS ; INDEX |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:000909188500001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/188642]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 作者单位 | 1.Institute of Geographic Sciences & Natural Resources Research, CAS 2.Chinese Academy of Sciences 3.Nanjing University of Information Science & Technology |
| 推荐引用方式 GB/T 7714 | Li, Yanzhong,Zhuang, Jiacheng,Bai, Peng,et al. Evaluation of Three Long-Term Remotely Sensed Precipitation Estimates for Meteorological Drought Monitoring over China[J]. REMOTE SENSING,2023,15(1). |
| APA | Li, Yanzhong.,Zhuang, Jiacheng.,Bai, Peng.,Yu, Wenjun.,Zhao, Lin.,...&Xing, Yincong.(2023).Evaluation of Three Long-Term Remotely Sensed Precipitation Estimates for Meteorological Drought Monitoring over China.REMOTE SENSING,15(1). |
| MLA | Li, Yanzhong,et al."Evaluation of Three Long-Term Remotely Sensed Precipitation Estimates for Meteorological Drought Monitoring over China".REMOTE SENSING 15.1(2023). |
入库方式： OAI收割
来源：地理科学与资源研究所
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