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\begin{document}

\title{How much inundation occurs in the Amazon River basin?}



\author[1]{Ayan Fleischmann}%
\author[2]{Fabrice Papa}%
\author[3]{Alice Fassoni-Andrade}%
\author[4]{John M Melack}%
\author[5]{Sly Wongchuig}%
\author[1]{Rodrigo Cauduro Dias De Paiva}%
\author[6]{Stephen K Hamilton}%
\author[7]{Etienne Fluet-Chouinard}%
\author[1]{Rafael Barbedo}%
\author[8]{Filipe Aires}%
\author[9]{Ahmad Al Bitar}%
\author[10]{Marie-Paule Bonnet}%
\author[11]{Michael Coe}%
\author[12]{Jefferson Ferreira-Ferreira}%
\author[4]{Laura Hess}%
\author[13]{Katherine Jensen}%
\author[13]{Kyle Mcdonald}%
\author[14]{Alex Ovando}%
\author[15]{Edward Park}%
\author[16]{Marie Parrens}%
\author[17]{Sébastien Pinel}%
\author[18]{Catherine Prigent}%
\author[19]{Angélica F Resende}%
\author[20]{Menaka Revel}%
\author[21]{Ake Rosenqvist}%
\author[21]{Jessica Rosenqvist}%
\author[14]{Conrado Rudorff}%
\author[22]{Thiago S F Silva}%
\author[20]{Dai Yamazaki}%
\author[1]{Walter Collischonn}%
\affil[1]{Institute of Hydraulic Research, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil}%
\affil[2]{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}%
\affil[3]{Laboratoire d’Etudes en Géophysique et Océanographie Spatiales (LEGOS)}%
\affil[4]{University of California}%
\affil[5]{Univ. Grenoble Alpes}%
\affil[6]{Kellogg Biological Station}%
\affil[7]{Stanford University}%
\affil[8]{Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères, Observatoire de Paris, UMR 8112, Paris, France.}%
\affil[9]{Centre d’Etudes Spatiales de la Biosphère (CESBIO), Toulouse University (CNES, CNRS, INRAe, IRD, UPS), Toulouse, France}%
\affil[10]{Espace-DEV, Univ Montpellier, Institute of Research for Development, Univ Guyane, Univ Reunion, Montpellier, France}%
\affil[11]{Woodwell Climate Research Center, Falmouth, MA}%
\affil[12]{Instituto de Desenvolvimento Sustentável Mamirauá}%
\affil[13]{City College of New York}%
\affil[14]{Centro Nacional de Monitoramento de Desastres Naturais (CEMADEN), São José dos Campos, São Paulo, Brazil}%
\affil[15]{National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment,  Nanyang Technological University, Singapore}%
\affil[16]{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}%
\affil[17]{CEFREM, University of Perpignan Via Domitia, Perpignan, France}%
\affil[18]{CNRS, Sorbonne Université, Observatoire de Paris, Université PSL, Lerma, Paris, France}%
\affil[19]{Universidade de São Paulo, Departamento de Ciências Florestais (ESALQ), Piracicaba, SP, Brazil}%
\affil[20]{Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.}%
\affil[21]{solo Earth Observation (soloEO), Tokyo 104-0054, Japan}%
\affil[22]{Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, UK Fk9 4LA.}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\selectlanguage{english}
\begin{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
\textless{} 500 m) is estimated at 599,700 \selectlanguage{ngerman}± 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 \textasciitilde{}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 \textgreater{} 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.%
\end{abstract}\selectlanguage{ngerman}%



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