中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang-Mekong River Basin

文献类型:期刊论文

作者Zhang, Xuejun1; Qu, Yanping1; Ma, Miaomiao1; Liu, Hui1; Su, Zhicheng1; Lv, Juan1; Peng, Jian2; Leng, Guoyong3; He, Xiaogang4; Di, Chongli5
刊名REMOTE SENSING
出版日期2020-02-01
卷号12期号:3页码:21
关键词drought monitoring satellite real-time data bias-correction VIC hydrological model
DOI10.3390/rs12030376
通讯作者Leng, Guoyong(lenggy@igsnrr.ac.cn)
英文摘要Existing gauging networks are sparse and not readily available in real-time over the transboundary Lancang-Mekong River (LMR) basin, making it difficult to accurately identify drought. In this study, we aimed to build an operational real-time Lancang-Mekong drought monitor (LMDM), through combining satellite real-time data and the Variable Infiltration Capacity (VIC) hydrological model at a 0.25 degrees spatial resolution. Toward this, three VIC runs were conducted: (1) a 60-year (1951-2010) historical simulation driven by Princeton's global meteorological forcing (PGF) for yielding 'normal' conditions (PGF-VIC), wherein the VIC was calibrated with 20-year observed streamflow at six hydrological stations; (2) a short-period (2011-2014) simulation to bridge the gap between the historical and the real-time modeling; (3) the real-time (2015-present) simulation driven by bias-corrected satellite data, wherein the real-time soil moisture (SM) estimate was expressed as percentile (relative to the 'normal') for drought monitoring. Results show that VIC can successfully reproduce the observed hydrographs, with the Nash-Sutcliffe efficiency exceeding 0.70 and the relative bias mostly within 15%. Assessment on the performance of LMDM shows that the real-time SM estimates bear good spatial similarity to the reference, with the correlation coefficient beyond 0.80 across >70% of the domain. In terms of drought monitoring, the LMDM can reasonably reproduce the two recorded droughts, implying extreme droughts covering the Lower LMR during 2004/05 and widespread severe 2009/10 drought across the upper domain. The percentage drought area implied by the LMDM and the reference is close, corresponding to 66% and 60%, 43% and 40%, and 44% and 36% for each typical drought month. Since January 2015, the LMDM was running in an operational mode, from which the 2016 unprecedented drought was successfully identified in Mekong Delta. This study highlights the LMDM's capability for reliable real-time drought monitoring, which can serve as a valuable drought early warning prototype for other data-poor regions.
WOS关键词LAND-SURFACE ; HYDROLOGICAL DROUGHTS ; SPATIAL VARIABILITY ; WATER-RESOURCES ; GLOBAL DROUGHT ; MODEL ; CLIMATE ; SOIL ; PRECIPITATION ; 21ST-CENTURY
资助项目National Key Research & Development Program of China[2017YFC1502406] ; National Key Research & Development Program of China[2018YFC1508702] ; National Key Research & Development Program of China[2016YFC0400106-2] ; National Natural Science Foundation of China[51609257] ; National Natural Science Foundation of China[51609259] ; National Natural Science Foundation of China[41701023] ; National Natural Science Foundation of China[41901016] ; IWHR Research & Development Support Program[JZ0145B582017] ; IWHR Research & Development Support Program[JZ0145B472016] ; IWHR Research & Development Support Program[JZ0145B862017]
WOS研究方向Remote Sensing
语种英语
出版者MDPI
WOS记录号WOS:000515393800035
资助机构National Key Research & Development Program of China ; National Natural Science Foundation of China ; IWHR Research & Development Support Program
源URL[http://ir.igsnrr.ac.cn/handle/311030/132966]  
专题中国科学院地理科学与资源研究所
通讯作者Leng, Guoyong
作者单位1.China Inst Water Resources & Hydropower Res, Beijing 100038, Peoples R China
2.Univ Oxford, Sch Geog & Environm, Oxford OX1 3QY, England
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
4.Stanford Univ, Woods Inst Environm, Water West, Stanford, CA 94305 USA
5.Tianjin Univ, Inst Surface Earth Syst Sci, Tianjin 300072, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Xuejun,Qu, Yanping,Ma, Miaomiao,et al. Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang-Mekong River Basin[J]. REMOTE SENSING,2020,12(3):21.
APA Zhang, Xuejun.,Qu, Yanping.,Ma, Miaomiao.,Liu, Hui.,Su, Zhicheng.,...&Di, Chongli.(2020).Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang-Mekong River Basin.REMOTE SENSING,12(3),21.
MLA Zhang, Xuejun,et al."Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang-Mekong River Basin".REMOTE SENSING 12.3(2020):21.

入库方式: OAI收割

来源:地理科学与资源研究所

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