Abstract

Information on the sources of sediment is required both for the targeting, development and implementation of best management practices (BMPs) in agricultural regions and for understanding the nature of sediment dynamics within watersheds. Investigations have shown that a number of physical and biogeochemical sediment properties can be used as fingerprints to trace sediment back to its source. Three groups of fingerprints – spectral reflectance (colour), particle morphology (size and shape), and fallout radionuclides (137Cs) – were used to fingerprint the sources of sediment in a predominantly agricultural watershed (14.5 km2) in Atlantic Canada over a 7-year period. Both spectral reflectance and fallout radionuclides were successful in discriminating between sources of sediment identified within the watershed. In contrast, fingerprints based on particle morphology were not able to discriminate between any of the sources of sediment. A composite fingerprint including both spectral reflectance and radionuclide fingerprints was used to estimate the relative contributions from agricultural topsoil (i.e. rill and inter-rill erosion), agricultural subsurface (i.e. streambank and gully erosion) and forested areas. Sediment fingerprinting indicated that topsoil derived from agricultural land was the greatest contributor (77.2%; 95% credible interval (CI95%) [35.5, 92.5]) to suspended sediment collected at the outlet of the watershed. Streambanks and gullies within agricultural areas were also identified as important sources of sediment (17.4%; CI95% [3.1, 46.9]), while forested land was a minor source of sediment in the watershed (3.2%; CI95% [0.2, 18.9]). The fingerprinting results demonstrate that BMPs that target soil erosion in agricultural fields will result in the greatest reduction in the export of sediment from the watershed. This study also established that adjusting the spatial scale at which suspended sediment samples are collected would provide more detailed information on the location of the sources of sediment (i.e. identify sources at the sub-watershed level) and lead to better targeting of BMPs.

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