Fluvial sediment fingerprinting: literature review and annotated bibliography

Open-File Report 2014-1216
By: , and 

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Abstract

The U.S. Geological Survey has evaluated and adopted various field methods for collecting real-time sediment and nutrient data. These methods have proven to be valuable representations of sediment and nutrient concentrations and loads but are not able to accurately identify specific source areas. Recently, more advanced data collection and analysis techniques have been evaluated that show promise in identifying specific source areas. Application of field methods could include studies of sources of fluvial sediment, otherwise referred to as sediment “fingerprinting.” The identification of sediment is important, in part, because knowing the primary sediment source areas in watersheds ensures that best management practices are incorporated in areas that maximize reductions in sediment loadings. This report provides a literature review and annotated bibliography of existing methodologies applied in the field of fluvial sediment fingerprinting. This literature review provides a bibliography of publications where sediment fingerprinting methods have been used; however, this report is not assumed to provide an exhaustive listing. Selected publications were categorized by methodology with some additional summary information. The information contained in the summary may help researchers select methods better suited to their particular study or study area, and identify methods in need of more testing and application.

Publication type Report
Publication Subtype USGS Numbered Series
Title Fluvial sediment fingerprinting: literature review and annotated bibliography
Series title Open-File Report
Series number 2014-1216
DOI 10.3133/ofr20141216
Year Published 2014
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) South Dakota Water Science Center, Dakota Water Science Center
Description Report: iii, 8 p.; Appendix
Online Only (Y/N) Y
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
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