Improving Stream Bank Erosion Estimates by Adjusting the Applied Shear Stress for Different Bank Characteristics

Stream bank erosion rates are commonly modeled using the excess shear stress equation ε_r = k_d(τ-τ_c)^a, where the exponent a is assumed to be unity. The coefficient of erodibility k_d, and the critical shear stress τ_c [Tau _c] are properties of the bank soil and the applied shear stress τ [Tau] is a function of the channel geometry and discharge. This equation appears to overstimate bank erosion likely due to effects of channel morphology and bank vegetation, among other factors. The objective of this study was to determine whether the excess shear stress equation could be parameterized with an α [alpha] coefficient to more accurately estimate stream bank erosion accounting for the effects of channel curvature and bank vegetation. The study included seven stream bank sites at Beaver, Bullrun, and Stock creeks located in Knox County, Tennessee with USGS gaging stations located downstream. Bank erosion pins were placed at four channel morphology/vegetation categories to measure retreat or soil deposition; they were straight and curved channels with and without woody bank vegetation. At each channel cross-section, 18-inch steel pins were installed vertically along the lower, middle, and upper portion of the banks. A mini-jet test device was used to approximate k_d and the τ_c using the Blaisdell method (BM). Flows and stage heights were modeled with HEC-RAS to determine the τ at each pin. Pin erosion averages varied by category and bank position ranging from -0.03 to -0.78 feet during the one-year study period and were used as estimates of site erosion rates ε_r [Epsilon _r]. With all the parameters being known alpha parameters in the modified excess shear stress equation were solved for each of the erosion pins for the different channel categories. The alpha values typically varied between about 0.001 and 0.73 showing that excess shear stress equation over predicts erosion. Due to the wide range of alpha values, further research is needed to better assess the factors that influence bank erosion and improve the predictability of bank retreat rates.