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Open AccessArticle

Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang–Mekong River Basin

China Institute of Water Resources and Hydropower Research, Beijing 100038, China
School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Water in the West, Woods Institute for the Environment, Stanford University, Stanford, CA 94305, USA
Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(3), 376;
Received: 17 December 2019 / Revised: 20 January 2020 / Accepted: 21 January 2020 / Published: 24 January 2020
(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)
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° 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. View Full-Text
Keywords: drought monitoring; satellite real-time data; bias-correction; VIC hydrological model drought monitoring; satellite real-time data; bias-correction; VIC hydrological model
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MDPI and ACS Style

Zhang, X.; Qu, Y.; Ma, M.; Liu, H.; Su, Z.; Lv, J.; Peng, J.; Leng, G.; He, X.; Di, C. Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang–Mekong River Basin. Remote Sens. 2020, 12, 376.

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