Modeling suspended sediment distribution patterns of the Amazon River using MODIS data

Patterns of surface sediment concentration distribution in rivers are significant for understanding fluvial morphodynamics and environmental characteristics of the rivers and their floodplains. 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. In this paper, patterns of surface sediment distribution are modeled based on Moderate Resolution Imaging Spectroradiometer (MODIS) data over the Amazon River by estimating surface sediment concentrations. Specifically, we aim to 1) detect the regional and seasonal variability of surface sediment in the main channel, 2) observe the influence of tributaries into the main system, 3) identify channel-floodplain interactions, and 4) investigate the internal variability of surface sediment along the main channel system. Field surface sediment concentration data from three gauging stations representing the upstream, midstream, and downstream sections of the Amazon River between 2000 and 2010 were used to calibrate 1328 MODIS daily surface reflectance images. Robust empirical models were derived between field surface sediment concentration and surface reflectance data from each station (0.79 < R2 < 0.92, slopes significant at 99% confidence level) from 752 selected data after quality control. We applied empirical models to 2112 8-day composite surface reflectance images to generate surface sediment distribution maps since 2000. Overall, this study successfully demonstrated the capability of our MODIS-based model to capture the spatial and temporal variability of surface sediments in the Amazon River Basin, the largest river system on Earth.