Human-induced and natural changes to the transport of sediment and sediment-associated constituents can degrade aquatic ecosystems and limit human uses of streams and rivers. The lack of a dedicated, easily accessible, quality-controlled database of sediment and ancillary data has made it difficult to identify sediment-related water-quality impairments and has limited understanding of how human actions affect suspended-sediment concentrations and transport. The purpose of this report is to describe the creation of a quality-controlled U.S. Geological Survey suspended-sediment database, provide guidance for its use, and summarize characteristics of suspended-sediment data through 2010. The database is provided as an online application at http://cida.usgs.gov/sediment to allow users to view, filter, and retrieve available suspended-sediment and ancillary data.
A data recovery, filtration, and quality-control process was performed to expand the availability, representativeness, and utility of existing suspended-sediment data collected by the U.S. Geological Survey in the United States before January 1, 2011. Information on streamflow condition, sediment grain size, and upstream landscape condition were matched to sediment data and sediment-sampling sites to place data in context with factors that may influence sediment transport. Suspended-sediment and selected ancillary data are presented from across the United States with respect to time, streamflow, and landscape condition. Examples of potential uses of this database for identifying sediment-related impairments, assessing trends, and designing new data collection activities are provided. This report and database can support local and national-level decision making, project planning, and data mining activities related to the transport of suspended-sediment and sediment-associated constituents.
|Citation Search Results Text: ||Compilation, quality control, analysis, and summary of discrete suspended-sediment and ancillary data in the United States, 1901-2010; 2013; DS; 776; Data Series; Lee, Casey J.; Glysson, G. Douglas