Preprints
https://doi.org/10.5194/essd-2021-32
https://doi.org/10.5194/essd-2021-32

  08 Feb 2021

08 Feb 2021

Review status: this preprint is currently under review for the journal ESSD.

Comprehensive bathymetry and intertidal topography of the Amazon estuary

Alice César Fassoni-Andrade1, Fabien Durand1,2, Daniel Moreira3, Alberto Azevedo4, Valdenira Ferreira dos Santos5, Claudia Funi5, and Alain Laraque6 Alice César Fassoni-Andrade et al.
  • 1Institut de Recherche pour le Développement (IRD), Universidade de Brasília (UnB), Brasília, 70910-900, Brazil
  • 2LEGOS UMR5566, CNRS/CNES/IRD/UPS, 31400 Toulouse, France
  • 3CPRM, Serviço Geológico do Brasil, Avenida Pasteur, 404, Urca, Rio de Janeiro, Brazil
  • 4Laboratório Nacional de Engenharia Civil (LNEC), Avenida do Brasil 101, Lisboa, Portugal
  • 5Instituto de Pesquisas Científicas e Tecnológicas do Estado do Amapá (IEPA), Campus IEPA Fazendinha, Macapá, Brasil
  • 6IRD, GET-UMR CNRS/IRD/UPS – UMR 5562 du CNRS, UMR 234 de l’IRD, Toulouse, France

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).

Alice César Fassoni-Andrade et al.

Status: open (until 05 Apr 2021)

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Alice César Fassoni-Andrade et al.

Alice César Fassoni-Andrade et al.

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