Monitoring and Analysis of Water Level Changes in Mekong River from ICESat-2 Spaceborne Laser Altimetry

Abstract

The monitoring and analysis of the water level in the Mekong River is of major importance in water resources security, management, and geostrategic cooperation. This study proposed a new approach for monitoring and analysis of changes in water level of the Mekong River by using ICESat-2 spaceborne laser altimetry. River water levels were extracted from ICESat-2 inland water level data (ATL13). Then, the remote-sensed water level was quantitatively compared with the in situ water level measured by hydrological stations. Finally, the responses of water level to natural and anthropogenic factors were explored. The results showed that the ATL13 products provided river water level data with a high precision (root mean square error (RMSE) = 0.24 m, bias = −0.11 m) and a low measurement uncertainty (median of standard deviations (MSD) = 0.04). The analysis indicated that ATL13 products under different beam intensities and acquisition times can be applied to derive river water level. However, the use of nighttime measurements achieved slightly higher accuracies. The seasonal characteristics of river water level (flooding season from May to October and dry season from November to April of the next year) were because of natural factors, such as upstream flow and rainfall. A comparison of water level changes among different periods showed that hydropower development generally decreased the range of water level in the flooding season and increased water level in the dry season, thereby mitigating the current uneven spatial and temporal distribution characteristics of water resources in Mekong basin.

ICESat‐2 Based River Surface Slope and Its Impact on Water Level Time Series From Satellite Altimetry

“…The median standard deviation of ICESat‐2 observations over inland waters is reported to be 0.017 m, with a mean error of 0.14 m (Cooley et al., 2021; Ryan et al., 2020). A regional study validating ATL13 data at the Mekong River reports similar results with an RMSE of 0.24 m and a median standard deviation of 0.04 m (Lao et al., 2022).…”

“…The median standard deviation of ICESat-2 observations over inland waters is reported to be 0.017 m, with a mean error of 0.14 m (Cooley et al, 2021;Ryan et al, 2020). A regional study validating ATL13 data at the Mekong River reports similar results with an RMSE of 0.24 m and a median standard deviation of 0.04 m (Lao et al, 2022). The ATL13 product does not contain photon-level observations but representative values over short segments of 75-100 consecutive received photons above inland water bodies.…”

River Water Level and Water Surface Slope Measurement From Spaceborne Radar and LiDAR Altimetry: Evaluation and Implications for Hydrological Studies in the Ganga River

“…However, the validation of ICESat-2 over the Ganga River was considerably limited due to the recent release of data, resulting in just 19 sample points. A relatively weaker agreement was observed between ICESat-2 and in-situ water levels in comparison to assessments in the Mississippi River (RMSE 0.06m) and the Mekong River (RMSE 0.24 m) [28], [67]. The likely reasons for such variations include the influence of changing water surface slope and water waves, a small sample size, and the interpolation of in-situ water levels at virtual stations.…”

Inland Water Level Monitoring from Satellite Observations: A Scoping Review of Current Advances and Future Opportunities

“…When available, ICESat-2 data show a strong potential for the monitoring of inland water bodies [77]. Furthermore, in [98,99] it is highlighted that the use of night-time observations by the ICESat-2 mission achieved slightly higher accuracies than day-time measurements. On the other hand, the temporal resolution of the ICESat-2 satellite (91-day repeat cycle) is low and significantly lower than the radar altimeter satellites.…”

“…Publications incorporating multiple types or continents in their applications are included in the relevant categories on the heatmap. The most used study area is the Qinghai-Tibetan Plateau in China [58,62,[64][65][66][67]73,97,98,102,[104][105][106]111].…”