SPATIAL PATTERNS IN BED-SAND GRAIN SIZE FROM HIGH DENSITY STREAM BED SAMPLING OF THE COLORADO RIVER IN GRAND CANYON

Quantification of sediment bed-sand grain size in the context of depositional setting -- i.e. flow strength, location relative to sediment source, etc. -- is fundamental to understanding the drivers of sediment transport and storage within fluvial systems. As part of a larger effort to comprehensively map the bed of the Colorado River in Glen, Marble, and Grand Canyons, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center has collected over 30,000 bed-sand grain size measurements using digital underwater imaging systems. These systems employ a high definition digital video camera housed in a 45-kg wrecking ball that also includes diving lights and lasers for scaling. The system is suspended on 60-meter cable connected to a GPS and shipboard computer with custom acquisition software to capture and classify imagery in real time. Georeferenced photographs collected by these systems provide data for substrate classification, vegetation mapping, and habitat identification. In locations where the bed is sand or finer, macro images were collected for processing with open source Digital Grain Size software. Spatial patterns among the grain-size measurements yield information on sediment conditions in the river, and document bed response to events such as sediment inputs and high flows. We present an analysis of these data showing that local variations in grain size, associated with geomorphic setting, and temporal variations in grain size, associated with dam releases and tributary activity, are much larger than longitudinal variations in grain size over reaches of ~100 km or longer. Importantly, this demonstrates that conclusions about sediment conditions over long reaches can’t be robustly drawn from sparsely-spaced sampling protocols. Improved understanding of the relations among grain size, sediment supply, and streamflow regime will be used to better predict effects of management actions, such as controlled floods, and help managers configure flow regimes to meet sediment-related objectives.