Potential to use free satellite imagery to retrieve the past bathymetry of large rivers

Abstract

Information on bathymetric changes in large rivers is useful for flood planning, navigation, and predicting channel change. Recent studies have demonstrated the potential for measuring bathymetry of rivers from satellite images, but such studies have used high-resolution, expensive data applied to ideal river conditions, such as low turbidity. Many of the large rivers of the world are located in countries that cannot afford the carefully planned field surveys and commercial satellite images used in these studies. In this study we investigate whether past bathymetry of large rivers could be retrieved by using readily collated free satellite images, combined with the limited cross-sectional surveys that are typically available in less wealthy countries. We tested the method in the heavily regulated Han River of central China. The Landsat-8 and Sentinel-2 image-derived depth could quantitatively match in situ depths along cross-sections up to depths of 13.9 m, where the suspended sediment concentration was low due to dam regulation. However, in most of the river where turbidity was high, the method was less successful. The image-to-depth quantile transformation (IDQT) approach could improve passive bathymetry retrieval in cases like the Han River, where there was some spatial and temporal misalignment between in situ data and remote-sensing data. The lateral depth pattern up to the 2.5 m depth contour could also be qualitatively and visually interpreted over an extended length (15 km). These results suggest that there is potential to use free satellite imagery to derive bathymetry in many large rivers, but this potential can only be achieved in very limited (low turbidity) conditions, and with image to depth correlation analysis and band selection.