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How much inundation occurs in the Amazon River basin?
  • +27
  • Ayan Fleischmann,
  • Fabrice Papa,
  • Alice Fassoni-Andrade,
  • John M Melack,
  • Sly Wongchuig,
  • Rodrigo Cauduro Dias De Paiva,
  • Stephen K Hamilton,
  • Etienne Fluet-Chouinard,
  • Rafael Barbedo,
  • Filipe Aires,
  • Ahmad Al Bitar,
  • Marie-Paule Bonnet,
  • Michael Coe,
  • Jefferson Ferreira-Ferreira,
  • Laura Hess,
  • Katherine Jensen,
  • Kyle Mcdonald,
  • Alex Ovando,
  • Edward Park,
  • Marie Parrens,
  • Sébastien Pinel,
  • Catherine Prigent,
  • Angélica F Resende,
  • Menaka Revel,
  • Ake Rosenqvist,
  • Jessica Rosenqvist,
  • Conrado Rudorff,
  • Thiago S F Silva,
  • Dai Yamazaki,
  • Walter Collischonn
Ayan Fleischmann
Institute of Hydraulic Research, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil

Corresponding Author:[email protected]

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Fabrice Papa
Laboratoire d’Etudes en Géophysique et Océanographie Spatiales (LEGOS), Université Toulouse, IRD, CNRS, CNES, USP, Toulouse, France ; Institut de Recherche pour le Développement (IRD), Universidade de Brasília (UnB), Institute of Geosciences, Campus Universitário Darcy Ribeiro, 70910-900, Brasilia, Brazil
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Alice Fassoni-Andrade
Laboratoire d’Etudes en Géophysique et Océanographie Spatiales (LEGOS)
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John M Melack
University of California
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Sly Wongchuig
Univ. Grenoble Alpes
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Rodrigo Cauduro Dias De Paiva
Institute of Hydraulic Research, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
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Stephen K Hamilton
Kellogg Biological Station
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Etienne Fluet-Chouinard
Stanford University
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Rafael Barbedo
Institute of Hydraulic Research, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
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Filipe Aires
Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères, Observatoire de Paris, UMR 8112, Paris, France.
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Ahmad Al Bitar
Centre d’Etudes Spatiales de la Biosphère (CESBIO), Toulouse University (CNES, CNRS, INRAe, IRD, UPS), Toulouse, France
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Marie-Paule Bonnet
Espace-DEV, Univ Montpellier, Institute of Research for Development, Univ Guyane, Univ Reunion, Montpellier, France
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Michael Coe
Woodwell Climate Research Center, Falmouth, MA
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Jefferson Ferreira-Ferreira
Instituto de Desenvolvimento Sustentável Mamirauá
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Laura Hess
University of California
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Katherine Jensen
City College of New York
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Kyle Mcdonald
City College of New York
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Alex Ovando
Centro Nacional de Monitoramento de Desastres Naturais (CEMADEN), São José dos Campos, São Paulo, Brazil
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Edward Park
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University, Singapore
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Marie Parrens
Centre d’Etudes Spatiales de la Bioshpère (CESBIO), CNES, Université de Toulouse (UPS), France ; Dynafor, Université de Toulouse, INRAE, INPT, INP-PURPAN, Castanet-Tolosan, France
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Sébastien Pinel
CEFREM, University of Perpignan Via Domitia, Perpignan, France
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Catherine Prigent
CNRS, Sorbonne Université, Observatoire de Paris, Université PSL, Lerma, Paris, France
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Angélica F Resende
Universidade de São Paulo, Departamento de Ciências Florestais (ESALQ), Piracicaba, SP, Brazil
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Menaka Revel
Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.
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Ake Rosenqvist
solo Earth Observation (soloEO), Tokyo 104-0054, Japan
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Jessica Rosenqvist
solo Earth Observation (soloEO), Tokyo 104-0054, Japan
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Conrado Rudorff
Centro Nacional de Monitoramento de Desastres Naturais (CEMADEN), São José dos Campos, São Paulo, Brazil
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Thiago S F Silva
Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, UK Fk9 4LA.
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Dai Yamazaki
Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.
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Walter Collischonn
Institute of Hydraulic Research, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
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Abstract

The Amazon River basin harbors some of the world’s largest wetland complexes, which are of major importance for biodiversity, the water cycle and climate, and human activities. Accurate estimates of inundation extent and its variations across spatial and temporal scales are therefore fundamental to understand and manage the basin’s resources. More than fifty inundation estimates have been generated for this region, yet major differences exist among the datasets, and a comprehensive assessment of them is lacking. Here we present an intercomparison of 29 inundation datasets for the Amazon basin derived from remote sensing-based products, hydrological models and multi-source products. Spatial resolutions range from 12.5 m to 25 km, and temporal resolution from static to monthly intervals, covering up to a few decades. Overall, 26% of the lowland Amazon basin is estimated as subject to inundation by at least one product. The long-term maximum inundated area across the entire basin (lowland areas with elevation < 500 m) is estimated at 599,700 ± 81,800 km² if considering only higher quality SAR-based products and 490,300 ± 204,800 km² if considering 18 basin-scale datasets. However, even the highest resolution SAR-based product underestimates the local maximum values, as estimated by subregional products, suggesting a basin-wide underestimation of ~10%. The minimum inundation extent shows greater disagreements among products than the maximum extent: 139,300 ± 127,800 km² for SAR-based products and 112,392 ± 79,300 km² for the overall average. Discrepancies arise from differences among sensors, time periods, dates of acquisition, spatial resolution, and data processing algorithms. The median total area subject to inundation in medium to large river floodplains (drainage area > 1,000 km²) is 323,700 km². The highest spatial agreement is observed for floodplains dominated by open water such as along the lower mainstem rivers, whereas intermediate agreement is found along major vegetated floodplains fringing larger rivers (e.g., Amazon mainstem floodplain). Especially large disagreements exist among estimates for interfluvial wetlands (Llanos de Moxos, Pacaya-Samiria, Negro, Roraima), where inundation tends to be shallower and more variable in time. Our data inter-comparison helps identify the current major knowledge gaps regarding inundation mapping in the Amazon and their implications for multiple applications. In the context of forthcoming hydrology-oriented satellite missions, we make recommendations for future developments of inundation estimates in the Amazon and present a WebGIS application (https://amazon-inundation.herokuapp.com/) we developed to provide user-friendly visualization and data acquisition of current Amazon inundation datasets.