Using Distributed Continuous Turbidity Monitoring to Inform Sediment and Sediment-bound Nutrient Budgets

Monday, 15 December 2014
Scott Douglas Hamshaw, Kristen L Underwood, Donna Rizzo, Beverley Coghill Wemple and Mandar Dewoolkar, University of Vermont, Burlington, VT, United States
The State of Vermont is experiencing changing hydrological regimes due to increased precipitation resulting from climate change. Understanding the impacts this change may cause to river corridors and the water quality of receiving waters is a critical need. Estimating the loading of sediment and sediment-bound nutrients such as phosphorous from various sources is a key aspect. In particular, the proportion attributable to main stem bank erosion is of concern as it is suspected to be a significant source in river basins in the Northeast. Sediment and nutrient budgets have been utilized for many years to provide a conceptual framework for proportioning loading to different sources. In this study, a continuous turbidity monitoring station network informs the creation of a watershed sediment budget in a small watershed.

Monitoring stations placed on select upstream tributaries as well as the downstream watershed outlet are used to characterize overall watershed yield as well as loading to the main stem from tributaries. Analysis of differential unit area loading from tributary and downstream monitoring sites estimate the proportion of the overall watershed sediment yield that could be attributed to main stem bank erosion. Regression models of suspended sediment and total phosphorous enable the quantification of sediment-bound phosphorous loadings from stream banks. To characterize loadings and overall watershed sediment and nutrient yields, a probabilistic framework is created using a Bayesian approach that enables updating of continuously-collected data and provides estimates of uncertainty resulting in credible ranges of sediment and phosphorous loading. These sediment and nutrient budget estimates along with their associated uncertainties help inform water resource managers of loading sources and enable prioritization of mitigation efforts.