Variations of surface and subsurface water storage in the Lower Mekong Basin (Vietnam and Cambodia) from multisatellite observations

B Pham-Duc, F Papa, C Prigent, F Aires… - Water, 2019 - mdpi.com
B Pham-Duc, F Papa, C Prigent, F Aires, S Biancamaria, F Frappart
Water, 2019mdpi.com
In this study, we estimate monthly variations of surface-water storage (SWS) and subsurface
water storage (SSWS, including groundwater and soil moisture) within the Lower Mekong
Basin located in Vietnam and Cambodia during the 2003–2009 period. The approach is
based on the combination of multisatellite observations using surface-water extent from
MODIS atmospherically corrected land-surface imagery, and water-level variations from 45
virtual stations (VS) derived from ENVISAT altimetry measurements. Surface-water extent …
In this study, we estimate monthly variations of surface-water storage (SWS) and subsurface water storage (SSWS, including groundwater and soil moisture) within the Lower Mekong Basin located in Vietnam and Cambodia during the 2003–2009 period. The approach is based on the combination of multisatellite observations using surface-water extent from MODIS atmospherically corrected land-surface imagery, and water-level variations from 45 virtual stations (VS) derived from ENVISAT altimetry measurements. Surface-water extent ranges from ∼6500 to ∼40,000 km2 during low and high water stages, respectively. Across the study area, seasonal variations of water stages range from 8 m in the upstream parts to 1 m in the downstream regions. Annual variation of SWS is ∼40 km3 for the 2003–2009 period that contributes to 40–45% of total water-storage (TWS) variations derived from Gravity Recovery And Climate Experiment (GRACE) data. By removing the variations of SWS from GRACE-derived TWS, we can isolate the monthly variations of SSWS, and estimate its mean annual variations of ∼50 km3 (55–60% of the TWS). This study highlights the ability to combine multisatellite observations to monitor land-water storage and the variations of its different components at regional scale. The results of this study represent important information to improve the overall quality of regional hydrological models and to assess the impacts of human activities on the hydrological cycles.
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