Use of acoustic backscatter to estimate continuous suspended sediment and phosphorus concentrations in the Barton River, northern Vermont, 2010-2013
The U.S. Geological Survey, in cooperation with the Vermont Department of Environmental Conservation, investigated the use of acoustic backscatter to estimate concentrations of suspended sediment and total phosphorus at the Barton River near Coventry, Vermont. The hypothesis was that acoustic backscatter—the reflection of sound waves off objects back to the source from which they came—measured by an acoustic Doppler profiler (ADP) and recorded as ancillary data for the calculation of discharge, also could be used to generate a continuous concentration record of suspended sediment and phosphorus at the streamgage, thereby deriving added value from the instrument. Suspended-sediment and phosphorus concentrations are of particular interest in Vermont, where impairment of surface waters by suspended sediments and phosphorus is a major concern.
Regression models for estimating suspended-sediment concentrations (SSCs) and total phosphorus concentrations evaluated several independent variables: measured backscatter (MB), water-corrected backscatter (WCB), sediment-corrected backscatter (SCB), discharge, fluid-absorption coefficient, sediment-driven acoustic attenuation coefficient, and discharge hysteresis. The best regression equations for estimating SSC used backscatter as the predictor, reflecting the direct relation between acoustic backscatter and SSC. Backscatter was a better predictor of SSC than discharge in part because hysteresis between SSC and backscatter was less than for SSC and discharge. All three backscatter variables—MB, WCB, and SCB—performed equally as predictors of SSC and phosphorus concentrations at the Barton River site. The similar abilities to predict SSC among backscatter terms may partially be attributed to the low values and narrow range of the sediment-driven acoustic attenuation in the Barton River. The regression based on SCB was selected for estimating SSC because it removes potential bias caused by attenuation and temperature fluctuations. The best regression model for estimating phosphorus concentrations included terms for discharge and discharge hysteresis. The finding that discharge hysteresis was a significant predictor of phosphorus concentrations might be related to preferential sorption of phosphorus to fine-grained sediments, which have been found to be particularly sensitive to hysteresis. Regression models designed to estimate phosphorus concentrations had less predictive power than the models for SSCs.
Data from the Barton River did not fully support one of the study’s hypotheses—that backscatter is mostly caused by sands, and attenuation is mostly caused by fines. Sands, fines, and total SSCs in the Barton River all related better to backscatter than to sediment-driven acoustic attenuation. The weak relation between SSC and sediment-driven acoustic attenuation may be related to the low values and narrow range of SSCs and sediment attenuations observed at Barton River. A weak relation between SSC and sediment-driven acoustic attenuation also suggests that the diameters of the fine-sized suspended sediments in the Barton River may be predominantly greater than 20 micrometers (μm). Long-term changes in the particle-size distribution (PSD) were not observed in Barton River; however, some degree of within-storm changes in sediment source and possibly PSD were inferred from the hysteresis between SSC and SCB.
|Publication Subtype||USGS Numbered Series|
|Title||Use of acoustic backscatter to estimate continuous suspended sediment and phosphorus concentrations in the Barton River, northern Vermont, 2010-2013|
|Series title||Open-File Report|
|Publisher||U.S. Geological Survey|
|Publisher location||Reston, VA|
|Contributing office(s)||New England Water Science Center|
|Description||Report: vii, 29 p.; Readme; 4 Appendixes|
|Time Range Start||2010-01-01|
|Time Range End||2013-12-31|
|Other Geospatial||Barton River|
|Online Only (Y/N)||Y|
|Google Analytic Metrics||Metrics page|