Monitoring monthly variation of Tonle Sap Lake water volume using Sentinel-1 imagery and satellite altimetry data

Binh Pham-Duc; Quan Tran Anh; Son Tong Si

doi:10.15625/2615-9783/18897

Author affiliations

Authors

Binh Pham-Duc REMOSAT, University of Science and Technology of Hanoi, VAST, Hanoi, Vietnam
Quan Tran Anh Hanoi University of Mining and Geology, Hanoi, Vietnam
Son Tong Si REMOSAT, University of Science and Technology of Hanoi, VAST, Hanoi, Vietnam

DOI:

https://doi.org/10.15625/2615-9783/18897

Keywords:

Tonle Sap Lake; lake volume monitoring; Sentinel-1; altimetry data

Abstract

This work estimates the surface water volume variation of the Cambodian Tonle Sap Lake at a monthly scale from 2015-2022. To achieve this, radar Sentinel-1 imagery was processed using the Google Earth Engine platform to generate backscatter coefficient maps. The Otsu method was utilized to identify the optimal threshold to classify each backscatter coefficient map into water or non-water clusters. Additionally, altimetry data from three satellites (i.e., Sentinel-3, Jason-3, and Jason-CS/Sentinel-6) was processed to estimate Tonle Sap Lake’s water level variation using the AlTiS software. Surface water maps of the lake, derived from MODIS and clear-sky Sentinel-2 imagery, were used to validate the lake’s surface water extent time series, while in situ water level data collected at Prek Kdam station was used to validate the variation of the lake’s water height. Our results estimated that the lake’s open water area varies from 2200 to 6000 km², while its water level ranges from 3.1 to 10.9 m. Combining the two time series, we estimated that Tonle Sap Lake’s water volume varies between approximately -7.2 and 9.4 km³ month^-1, which shows high correlation with the variation of the water volume flowing through Chau Doc and Tan Chau stations (R = 0.9528 after removing the time lag). This study highlights the ability of satellite data for lake monitoring, which is very useful in remote areas where gauge stations are limited or unavailable. Future work aims to test the accuracy of the proposed methodology in other types of environments, particularly in mountainous regions of North Vietnam, where the terrain is very steep.

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