首页 > , Vol. , Issue () : -
Seasonal water bodies are an important component of global surface water, and play an indispensable role in regional flood mitigation and biodiversity maintenance. Acquiring high-precision bathymetric information is the key to effectively support the estimation of water storage and carbon flux in seasonal water bodies, which is of great significance for comprehensive understanding of regional hydrological processes and material-energy balance. In view of the complexity of the subsurface conditions of seasonal water bodies and the limitations of traditional bathymetric techniques, this paper proposes a quantitative estimation method of underwater topography for seasonal water bodies based on GEE cloud platform, combined with active LiDAR and passive optical sensor data, and then systematically evaluates the estimation accuracy and applicability of the method with Poyang Lake as the research object, which is a typical seasonal lake composed of a number of dished lakes. The results show that the quantitative estimation method is feasible based on the photon elevation of ICESat-2/ATLAS profiles and the inundation frequency information obtained from Sentinel-2 to achieve the “point-to-surface” topography of seasonal water bodies. The R2 values between the predicted and measured yield are greater than 0.7 and the root mean square errors (RMSEs) are controlled within 1 meter. Additionally, the simulation accuracy of dished lakes in different areas and subsurface conditions is also different due to the combined effects of various factors such as lake area, inundation frequency range and photon track distribution. The method proposed in this paper can realize the quantitative estimation of underwater topography for seasonal water bodies in a large scale, low cost and long time series, which is expected to provide ideas and directions for the development of bathymetric retrieving models for seasonal water bodies at the global scale.