Climate Change and Hazard Mitigation
Streambank erosion and sediment loading in rivers within the context of climate changeCollaborators: Mandar Dewoolkar, Donna Rizzo, Arne Bomblies (Civil and Environmental Engineering), Jeff Frolik (Electrical Engineering), Beverley Wemple (Geography), Paul Bierman (Geology), Jarlath P. M. O’Neil-Dunne (Rubenstein School of Environment and Natural Resources)
Students Involved: Jaron Borg, Kristen Underwood, Scott Hamshaw, and Jody Stryker
Description: Streambank erosion is recognized as one of the most important nonpoint sources of sediment and phosphorus entering streams, rivers, and lakes, and thus one of the largest contributors to the impairment of surface water quality and aquatic habitat. We combine many concepts of soil mechanics, geology, hydrology, and sensor technology to gain fundamental understanding of the mechanics of riverbank instability and the source of sediments in streams contributing to increasing phosphorus levels in Lake Champlain. Using in-situ and laboratory testing of streambank soils, determining soil erodibility, continuous remote monitoring of embedded instrumentation, and transient flow and slope stability modeling, we are learning what makes some banks stable and other banks fail over both time and changing river/groundwater conditions. Additionally, a sediment fingerprinting study is underway. Recent additions to this research have included quantification of streambank erosion and deposition using terrestrial LiDAR and unmanned aerial systems (UAS). This research is currently funded through VT EPSCoR's Research on Adaptation to Climate Change grantand Vermont Water Resources & Lake Studies Center
Borg, J., Dewoolkar, M. M., and Bierman, P. (2014), “Assessment of streambank stability – a case study”, Geo-Congress 2014 Technical Papers: pp. 1007-1016, doi: 10.1061/9780784413272.098
Hamshaw, S. D., Rizzo, D. M., Underwood, K. L., Wemple, B. C., & Dewoolkar, M. (2014, March 26). Suspended Sediment Prediction Using Artificial Neural Networks and Local Hydrometeorological Data. Poster presented at the 2014 NEAEB Conference, Burlington, VT.
Hamshaw, S. D., Rizzo, D. M., Underwood, K. L., Wemple, B. C., & Dewoolkar, M. (2014b, March 28). High Frequency Turbidity Monitoring to Quantify Sediment Loading in the Mad River. Presented at the 2014 NEAEB Conference, Burlington, VT.
Rizzo, D.M., S.D. Hamshaw, H. Anderson, K.L. Underwood and M.M. Dewoolkar (2013), “Estimates of Sediment Loading from Streambank Erosion Using Terrestrial LIDAR sediment in rivers using artificial neural networks: Implications for development of sediment budgets”, EOS Transactions, American Geophysical Union, Abstract H13D-1353, Fall Meeting, San Francisco, CA, December.
Last modified April 24 2015 02:22 PM