IGSNRR OpenIR
Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang-Mekong River Basin
Zhang, Xuejun1; Qu, Yanping1; Ma, Miaomiao1; Liu, Hui1; Su, Zhicheng1; Lv, Juan1; Peng, Jian2; Leng, Guoyong3; He, Xiaogang4; Di, Chongli5
2020-02-01
Source PublicationREMOTE SENSING
Volume12Issue:3Pages:21
Corresponding AuthorLeng, Guoyong(lenggy@igsnrr.ac.cn)
AbstractExisting 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.
Keyworddrought monitoring satellite real-time data bias-correction VIC hydrological model
DOI10.3390/rs12030376
WOS KeywordLAND-SURFACE ; HYDROLOGICAL DROUGHTS ; SPATIAL VARIABILITY ; WATER-RESOURCES ; GLOBAL DROUGHT ; MODEL ; CLIMATE ; SOIL ; PRECIPITATION ; 21ST-CENTURY
Indexed BySCI
Language英语
Funding ProjectNational 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]
Funding OrganizationNational Key Research & Development Program of China ; National Natural Science Foundation of China ; IWHR Research & Development Support Program
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000515393800035
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/132967
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLeng, Guoyong
Affiliation1.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
Recommended Citation
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.
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