Monitoring Lake Volume Variation from Space Using Satellite Observations—A Case Study in Thac Mo Reservoir (Vietnam)

Abstract

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 km2, 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 km3 month−1, and it is in a very good agreement with in situ measurement (R = 0.95; RMSE = 0.0682 km3 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.

Distinctive Patterns of Water Level Change in Swedish Lakes Driven by Climate and Human Regulation

“…However, due to the nadir‐looking geometry of the satellite altimetry and long gaps between satellite ground tracks, small lakes with few and short along‐track passes of the satellites have a low temporal resolution of altimetry observations, that is, ≥10 days depending on the altimetry mission (Nielsen et al., 2022). Therefore, data from multiple altimetry missions can achieve higher temporal resolutions and longer time series of water levels (Boergens et al., 2017; Pham‐Duc et al., 2022; Tourian et al., 2016). Moreover, new altimeter satellites such as Sentinel‐3 and Cryosat‐2 are equipped with Synthetic Aperture Radar (SAR), which provides higher along‐track data resolution with a 300‐m footprint (Villadsen et al., 2016), and sensors with high‐frequency Ka‐band signals (ARgos and ALtiKa; SARAL) that are less affected by the ionosphere, have better horizontal and higher vertical resolutions (Bonnefond et al., 2018; Verron et al., 2021).…”

Using Optical Satellite Images and Satellite Altimetry Data to Estimate Volume Variations in Dams

“…The water volume fluctuates between -0.3 and 0.4 km³ month −1 , demonstrating strong agreement with in situ measurements (R = 0.95; RMSE = 0.0682 km³ month −1 ). The study emphasizes the efficacy of diverse satellite observations for monitoring lake water storage variations, particularly beneficial for regions lacking in situ measurements or facing accessibility constraints (Pham-Duc et al, 2022). In this study, Sentinel-3 SRAL (Synthetic Aperture Radar Altimeter) altimetry data will be employed to monitor variations in the water level in the Doroudzan dam reservoir.…”

Land–Water Transition Zone Monitoring in Support of Drinking Water Production

“…Multiple studies have attempted to combine radar and multispectral data with the aim of obtaining comprehensive information about surface water dynamics in inland water systems by leveraging the advantages of both information sources. In [15], Binh Pham-Duc et al calculated monthly variations in the surface water volume of Thac Mo hydroelectric reservoir, located in Vietnam, by extracting the surface water extent from S1 observations and the water level from Jason-3 altimetry data. In a similar context, Weidong Zhu et al [16] proposed a new method based on multisource remote sensing data to calculate the changes in water level, surface area and storage capacity of Ngoring Lake, located in Tibetan Plateau in Qinghai Province.…”