Monitoring stream sediment loads in response to agriculture in Prince Edward Island, Canada
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Increased agricultural land use leads to accelerated erosion and deposition of fine sediment in surface water. Monitoring of suspended sediment yields has proven challenging due to the spatial and temporal variability of sediment loading. Reliable sediment yield calculations depend on accurate monitoring of these highly episodic sediment loading events. This study aims to quantify precipitation-induced loading of suspended sediments on Prince Edward Island, Canada. Turbidity is considered to be a reasonably accurate proxy for suspended sediment data. In this study, turbidity was used to monitor suspended sediment concentration (SSC) and was measured for 2 years (December 2012–2014) in three subwatersheds with varying degrees of agricultural land use ranging from 10 to 69 %. Comparison of three turbidity meter calibration methods, two using suspended streambed sediment and one using automated sampling during rainfall events, revealed that the use of SSC samples constructed from streambed sediment was not an accurate replacement for water column sampling during rainfall events for calibration. Different particle size distributions in the three rivers produced significant impacts on the calibration methods demonstrating the need for river-specific calibration. Rainfall-induced sediment loading was significantly greater in the most agriculturally impacted site only when the load per rainfall event was corrected for runoff volume (total flow minus baseflow), flow increase intensity (the slope between the start of a runoff event and the peak of the hydrograph), and season. Monitoring turbidity, in combination with sediment modeling, may offer the best option for management purposes.
KeywordsSediment Turbidity Agriculture Particle size Streamflow
This study was funded by the Canadian Water Network through its Canadian Watershed Research Consortium program, the PEI Department of Environment and Energy, Fisheries and Oceans Canada and through a Canada Research Chair to MRV. The authors wish to thank Christina Pater, Scott Roloson, Kyle Knysh, Gillian MacDonald, Hailey Lambe, Laura Phalen, Jesse Hitchcock, Mike Coffin, Travis James, Liane Leclair, James Dwyer, and Sean Landsman for their assistance in the study.
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