Evapotranspiration seasonality across the Amazon Basin
- 1Fisheries and Environmental Management Group, Department of Environmental Sciences, University of Helsinki, P.O. Box 68, 00014, Helsinki, Finland
- 2Climate Change Cluster (C3), University of Technology Sydney, 15 Broadway, Ultimo, New South Wales, 2007, Australia
- 3National Institute for Space Research (INPE), Avenida dos Astronautas 1758, São Jose dos Campos-SP, Brazil
- 4Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
- 5School of Life Sciences, University of Technology Sydney, 15 Broadway, Ultimo, New South Wales, 2007, Australia
Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon Basin. We used in situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (∼ 1497 mm year−1) and the lowest values in the Solimões River basin (∼ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.