Comment on essd-2021-32

Abstract

The characterization of estuarine hydrodynamics primarily depends on the knowledge of bathymetry and topography. Here we present the first comprehensive, high-resolution dataset of the topography and bathymetry of the Amazon River estuary, the world's largest estuary. Our product is based on an innovative approach combining space-borne remote sensing data, an extensive and processed river depth dataset, and auxiliary data. Our goal with this characterization is to promote the database usage in studies that require this information, such as hydrodynamic modeling or geomorphological assessments. Our twofold approach considered 500'000 sounding points digitized from 19 nautical charts for bathymetry estimation, in conjunction with a state-of-the-art topography dataset based on remote sensing, encompassing intertidal flats, riverbanks, and adjacent floodplains. Finally, our estimate can be accessed in a unified 30 m resolution regular grid referenced to EGM08, complemented both landward and seaward with land (MERIT DEM) and ocean (GEBCO2020) topography data. Extensive validation against independent and spatially-distributed data, from an airborne LIDAR survey, from ICESat-2 altimetric satellite data, and from various in situ surveys, shows a typical accuracy of 8.4 m (river bed) and 1.2 m (non-vegetated inter-tidal floodplains). The dataset is available at http://dx.doi.org/10.17632/3g6b5ynrdb.1 (Fassoni-Andrade et al., 2021). IntroductionThe Amazon River exports the largest discharge of freshwater (205'000 m 3 s -1 ; Callède et al., 2010) and the largest sedimentary supply (5-13 10 8 tons per year; Filizola et al., 2011) to the global ocean. However, there does not exist, up to now, any consistent, comprehensive, publicly available topographic dataset in the estuary that can support hydrodynamic, sedimentary, or ecological studies. The largest estuary in the world is home to energetic exchanges of momentum between the upstream river and the ocean, with a marked variability of the water level over a broad range of timescales, from the