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Hydropower dams and reservoirs have been identified as the main factorsredefining natural hydrological cycles. Therefore, monitoring water status inreservoirs plays a crucial role in planning and managing water resources, aswell as forecasting drought and flood. This task has been traditionally done byinstalling sensor stations on the ground nearby water bodies, which hasmultiple disadvantages in maintenance cost, accessibility, and global coverage.And to cope with these problems, Remote Sensing, which is known as the scienceof obtaining information about objects or areas without making contact withthem, has been actively studied for many applications. In this paper, wepropose a novel water level extracting approach, which employs Sentinel-1Synthetic Aperture Radar imagery and Digital Elevation Model data sets.Experiments show that the algorithm achieved a low average error of 0.93 metersover three reservoirs globally, proving its potential to be widely applied andfurthermore studied.

Water Level Estimation Using Sentinel-1 Synthetic Aperture Radar Imagery And Digital Elevation Models