期刊
REMOTE SENSING
卷 14, 期 16, 页码 -出版社
MDPI
DOI: 10.3390/rs14164023
关键词
lake volume monitoring; satellite data; Sentinel-1; Sentinel-2; Jason-3; altimetry data; Thac Mo reservoir; Vietnam
类别
资金
- Vietnam Academy of Science and Technology (VAST) [THTEXS.03/22-24]
- French Space Agency (Centre National d'Etudes Spatiales-CNES) [SWHYM]
This study estimates the monthly variation of surface water volume in Thac Mo hydroelectric reservoir in South Vietnam using Sentinel-1 observations and Jason-3 altimetry data. The results show a high correlation between surface water extent and water level, as well as between different satellite observations and in situ measurements. The study highlights the importance of using satellite data for monitoring lakes' water storage.
This study estimates monthly variation of surface water volume of Thac Mo hydroelectric reservoir (located in South Vietnam), during the 2016-2021 period. Variation of surface water volume is estimated based on variation of surface water extent, derived from Sentinel-1 observations, and variation of surface water level, derived from Jason-3 altimetry data. Except for drought years in 2019 and 2020, surface water extent of Thac Mo reservoir varies in the range 50-100 km(2), while its water level varies in the range 202-217 m. Correlation between these two components is high (R = 0.948), as well as correlation between surface water maps derived from Sentinel-1 and free-cloud Sentinel-2 observations (R = 0.98), and correlation between surface water level derived from Jason-3 altimetry data and from in situ measurement (R = 0.99; RMSE = 0.86 m). We showed that water volume of Thac Mo reservoir varies between -0.3 and 0.4 km(3) month(-1), and it is in a very good agreement with in situ measurement (R = 0.95; RMSE = 0.0682 km(3) month(-1)). This study highlights the advantages in using different types of satellite observations and data for monitoring variation of lakes' water storage, which is very important for regional hydrological models. Similar research can be applied to monitor lakes in remote areas where in situ measurements are not available, or cannot be accessed freely.
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