A Multi-temporal MODIS Based Platform to Analyze Suspended Sediment Distribution Patterns in the Amazon River

Abstract:

Patterns of surface sediment concentration distribution in rivers are significant for understanding the broad ranges of fluvial environmental systems. In the case of the Amazon Basin, complexity in sediment pattern distribution is affected by the anabranching channel pattern of the Amazon River, inputs from tributaries (some of which are among the largest rivers on earth) and the existence of huge and complex floodplains. This study presents a remote sensing based platform that aims to improve the understanding of the patterns of sediment distributions over the Amazon River by estimating surface sediment concentration. Field acquired surface sediment concentration data were supplied from three gauging stations representing the upstream, midstream and downstream sections of the Amazon River from 2000 to 2010 and calibrated with over 1,300 MODIS daily surface reflectance images. Robust empirical models were derived (0.63<R2<0.92, N=207, 232, 313 respectively from each station) between field surface sediment concentration and surface reflectance data from each station; however, sensitivity of reflectance around each station was proved to be significantly affected by the local hydrological behaviors. Empirical models were applied to 8-day composite surface reflectance images to generate surface reflectance distribution maps. Overall, the capability of the MODIS-based platform introduced in this study is successfully demonstrated by capturing the spatial and temporal variability of surface sediments in the Amazon River Basin, the largest and the most complex river system on earth.