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://amazon-inundation.herokuapp.com/) we developed to provide user-friendly visualization and data acquisition of current Amazon inundation datasets.
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Seasonal and spatial variability of CO2 in aquatic environments of the central lowland Amazon basin.
Different sources and processes contribute to pCO2 and CO2 exchange with the atmosphere in the rivers and floodplains of the Amazon basin. We measured or estimated pCO2, CO2 fluxes with the atmosphere, planktonic community respiration (PCR), and environmental and landscape variables along the Negro and Amazon-Solimões rivers during different periods of the fluvial hydrological cycle. Values of pCO2 ranged from 307 to 7,527 μatm, while CO2 fluxes ranged from -9.3 to 1,128 mmol m-2 d-1 in the Amazon-Solimões basin. In the Negro basin, pCO2 values ranged from 648 to 6,526 μatm, and CO2 fluxes from 35 to 1,025 mmol m-2 d-1. In a general linear model including data from Negro and Amazon-Solimões basins, seasonal and spatial variation in flooded vegetated habitat area, dissolved oxygen, depth and water temperature explained 85% of surface pCO2 variation. Levels of pCO2 varied with inundation extent, with higher pCO2 values occurring in periods with greater water depth and inundation area, and lower dissolved oxygen concentrations and water temperatures. In a separate analysis for the Amazon-Solimões river and floodplains, ecosystem type (lotic or lentic), hydrological period, water temperature, dissolved oxygen, depth and dissolved phosphorus explained 83% of pCO2 variation. Our results demonstrate the influence of alluvial floodplains and seasonal variations in their limnological characteristics on the pCO2 levels in river channels of the lowland Amazon.
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- Award ID(s):
- 1753856
- NSF-PAR ID:
- 10091419
- Date Published:
- Journal Name:
- Biogeochemistry
- ISSN:
- 0168-2563
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/https://doi.org/10.1007/s10533-019-00554-9(01234567.
