Relating ASCAT backscatter and dynamic vegetation parameters to vegetation water dynamics in the Amazon

The Amazon rainforest is among the most vital ecosystems on earth, holding about a quarter of the global terrestrial carbon sink. Since 2005, three 100-year return period droughts have occurred, the likes of which have the potential to turn the forest from a carbon sink to a carbon source. Monitoring the Amazon is essential to understand the functioning of the various ecoregions and how they respond to water stress. 

In this study, we investigate the ASCAT backscatter and dynamic vegetation parameters (DVP) over the Amazon region as a potential source of information about the vegetation. The dynamic vegetation parameters are slope and curvature of the second order Taylor polynomial used to represent the incidence angle dependence of backscatter. We looked for spatial and temporal patterns in the backscatter and DVP over Amazonia, and related them to climatic variables such as radiation and precipitation from the Princeton Global Meteorological Forcing Dataset, as well as variations in terrestrial water storage from GRACE. 

Results will be presented from the first ten years of ASCAT observations over the Amazon region, including the Cerrado grasslands southeast of the Amazon forest. We found that spatial patterns of the backscatter and ASCAT DVP reflect the distribution of major land cover types in the region. Seasonal variations in the parameters match the seasonality of moisture demand and availability, and show an influence of vegetation phenology. Diurnal differences in backscatter between the morning (~10:00 AM) and evening overpasses (~10:00 PM) suggest that the backscatter is sensitive to vegetation water dynamics. Significant anomalies were observed during the Amazon droughts of 2010 and 2015, indicating that ASCAT could detect water stress and drought effects in the vegetation. Therefore, the ASCAT DVP show promise for long-term monitoring of the Amazon with respect to vegetation water dynamics and droughts.