How much inundation occurs in the Amazon River basin?

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, based on remote sensing only, hydrological modeling, or multi-source datasets, with 18 covering the lowland Amazon basin (elevation < 500 m, which includes most Amazon wetlands), and 11 covering individual wetland complexes (subregional datasets). Spatial resolutions range from 12.5 m to 25 km, and temporal resolution from static to monthly, spanning up to a few decades. Overall, 31% of the lowland basin is estimated as subject to inundation by at least one dataset. The long-term maximum inundated area across the lowland basin is estimated at 599,700 ± 81,800 km² if considering the three higher quality SAR-based datasets, and 490,300 ± 204,800 km² if considering all 18 datasets. However, even the highest resolution SAR-based dataset underestimates the maximum values for individual wetland complexes, suggesting a basin-scale underestimation of ~10%. The minimum inundation extent shows greater disagreements among datasets than the maximum extent: 139,300 ± 127,800 km² for SAR-based ones and 112,392 ± 79,300 km² for all datasets. 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 Amazon River, 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 intercomparison 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://amazoninundation.herokuapp.com/) we developed to provide user-friendly visualization and data acquisition of current Amazon inundation datasets.

A global topography- and hydrography-based floodability index for the downscaling, analysis, and data-fusion of surface water

“…Meanwhile, the threshold of 1 is inadequate to conclude the water presence because any dataset can have commission error. If we have 20 datasets instead of three as now, we will have more choices of thresholding, and what would be obtained finally can be even more reliable (Fleischmann et al, 2021).…”

Expressive riverine fluxes over Amazon floodplain units revealed by high resolution 2D modelling

“…Several remote sensing-derived Amazon flood extent databases have been developed in recent years to characterize flooding in Amazon (Fassoni-Andrade et al, 2021). This is not a trivial mapping and the different approaches have led to disagreements, as shown by the comparison documented in Fleischmann et al (2022). We used two basin-scale databases that consider periods of maximum and minimum inundation Rosenqvist et al, 2020).…”

“…However, it is noteworthy that the various remote sensing-derived water extent databases also have large inconsistencies among them. For example, Fleischmann et al (2022) showed that HESS and ALOS mapping tend to underestimate the maximum inundation compared to subregional remote sensing-derived products, and there are large differences in minimum inundation among the different products.…”

“…Their seasonal flood pulse induces a large annual variation in water surface elevation in the floodplain and flooded area. The water level amplitude can reach up to 13 m (Birkett et al, 2002) and the water surface extent of the basin varies between 284'200 km 2 and 633'500 km 2 during the high (April-May) and low water (October-November) periods, respectively (Fleischmann et al, 2022;. Moreover, the bidirectional flows and water residence time in the floodplain are dynamic in space and time, and the patterns of water surface elevation variation are complex (Alsdorf et al, 2007;Cao et al, 2018).…”

Variation in Food and Nutritional Stability Among Amazonian Populations Living in a Context of Dramatic Seasonal Flooding

“…One of the places most dramatically affected by seasonality is Central Amazonia. This incredibly biodiverse and food rich environment for humans experiences a marked seasonal hydrological cycle (Fleischmann et al 2021). Characterized by a smooth and predictable ood curve with one pronounced peak per year, it is one of the largest seasonal uctuations in water level on earth.…”