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A series of linear regression models were developed and calibrated for the Minnesota and Mississippi Rivers. The linear regression models were calibrated using acoustic and suspended-sediment concentration data collected from March through November 2016 and 2017. The estimates of suspended-sediment concentrations from the linear regression were used to calculate loads. The calibrated models were used to improve understanding of sediment transport processes and increase accuracy of estimating sediment concentrations and loads for the Lower Minnesota River, the Mississippi River, and Lake Pepin, as part of the associated report, U.S. Geological Survey Scientific Investigations Report 2018–5165 (https://doi.org/10.3133/sir20185165).
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Description of Work The first major goal of this project is to characterize and evaluate the extent to which contaminants of emerging concern (CECs) threaten fish and other wildlife in the Great Lakes. This includes identifying and characterizing CECs in the Great Lakes Basin, identifying risk-based screening concentrations for priority CECs, evaluating population-relevant effects of complex mixtures on biota, and identifying the Great Lakes waterways at greatest risk. The second major goal of this project is to pilot and develop a short-term and an ongoing long-term state-of-the-art bioeffects surveillance program for the Great Lakes basin. This includes developing strategies which will account for variable conditions...
Categories: Project;
Tags: Biology,
Contaminants,
GLRI,
Great Lakes,
Great Lakes Restoration Initiative, All tags...
Habitat & Wildlife,
Lake:All,
Template 673,
Template 726,
Toxic Substances,
Watershed, Fewer tags
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