1. Methods for Determining Streambank Critical Shear Stress: Implications for Erosion Rate Predictions The excess shear stress equation predicts the erosion of soils by fluvial entrainment (Hanson, 1990). where  = erosion rate a = exponent (assumed 1)  a = applied shear stress k d = soil erodibility  c = critical shear stress  = k d (  a -  c ) a L. Clark and T. Wynn One key to maintaining or restoring channel stability is to prevent channel bed incision and streambank erosion. Damages associated with sediment cost $16 billion annually (Osterkamp et al., 1998). Introduction 1.To compare empirical estimates of  c and k d to actual field measurements 2.To determine the effects of differences in the parameter value, k d, on streambank erosion predictions Goals and Objectives The goal of this study was to compare different methods of estimating the parameters used in the excess shear stress equation for predicting the erosion rate of fine grain soils. Methods Sediment from streambanks can account for as much as 85% of watershed sediment yields (Trimble, 1997; Prosser et al., 2000). While  a can be estimated by flow hydraulics, the soil parameters  c and k d are difficult to estimate or measure for fine grained soils; there is little guidance on methods for the measurement or estimation of  c and k d. Subaerial processes weaken the soil Soil entrained during high flows Mass failure from slope instability Twenty-five field sites near the Town of Blacksburg in southwestern Virginia were tested. In situ jet tests were conducted on both the upper and lower bank at each site using a multiangle submerged jet test device. Soil samples were taken adjacent to the jet test tank for each test. The soil samples were analyzed for particle size distribution, specific gravity, and Atterberg limits. Estimating Soil Erodibility, k d Estimating Critical Shear Stress,  c  c = 0.1+0.1779(SC)+0.0028(SC) 2 -2.35E-5(SC) 3  c = 0.0034(I w ) 0.84  c = 0.074 X 10 -28.1D 50  c = 0.0103 x 10 0.0182P c Acknowledgements The authors would like to thank Jeff Keaton and Alan Simpson formerly with the Water Resources Division of the U.S. Geological survey for providing the survey data for the Tinker Creek gage. The authors also would like to thank Dr. Greg Hanson with the USDA ARS Hydraulics Lab for use of the jet test device. Conclusions  Measured k d and  c values were much higher than those predicted by the empirical equations, with the exception of the silt-clay model, indicating empirical models applied outside the specific study area should be used with caution.  Stream  a had a large impact on streambank erosion calculations, suggesting shear stress partitioning accounting for riparian vegetation may be necessary.  For streams with low  c values, erosion rates are largely controlled by k d.  These findings suggest  c and k d are site-specific and currently should be measured in situ.  Field validation of these methods over a wide range of soil types is recommended to further develop methods of estimating  c and k d for fine grained streambank soils. Streambank  c was measured in situ with the jet test device (JT; Blaisdell et al., 1981) and estimated based on Shield’s diagram (SD; Hann et al., 1994) and empirical equations based on percent silt/clay content (SC; Julian and Torres, 2006), plasticity index (I w ), median particle size (D 50 ), and percent clay content (P c ; Smerdon and Beasley, 1961): k d = 0.2  c -0.5 (HS, 2001) k d = (1/  )223 X 10 -4 e -0.13  c (OT, 1988) where  = specific weight of water Erosion was calculated for an existing USGS gaging station using the excess shear stress equation. The analysis assumed a rectangular cross-section. Bank  c and k d were predicted and measured parameters;  a was calculated based on water depth (H) and slope (S):  a =  HS Erosion was estimated for three sections and summed for total erosion per storm event. Schematic of three sections used for analysis References Blaisdell, F. W., L. A. Clayton, and G. G. Hebaus. 1981. Ultimate dimension of local scour. J. Hydraulic Div. ASCE 107(HY3): 327-337. Hann, C. T., B. J. Barfield, and J. C. Hayes. 1994. Design Hydrology and Sedimentology for Small Catchments. San Diego, CA: Academic Press. Hanson, G. J. 1990. Surface erodibility of earthen channels at high stresses part I-Open channel testing. Trans. ASAE. 33(1): 127-131. Hanson, G. J., and A. Simon. 2001. Erodibility of cohesive streambeds in the loess area of the Midwestern USA. Hydrological Processes. 15: 23-38. Julian, J. P., and R. Torres. 2006. Hydraulic erosion of cohesive riverbanks. G eomorphology 76(1-2):196-206. Osman, A. M., and C. R. Thorne. 1988. Riverbank stability analysis I: Theory. J. Hydraulic Eng. ASAE 114(2):134-150. Osterkamp, W. R., P. Heilman, L. J. Lane. 1998. Economic consideration of a continental sediment-monitoring program. Intl. J. Sediment Res. 13(4): 12-24. Prosser, I. P., A. O. Hughes, and I. D. Rutherford. 2000. Bank erosion of an incised upland channel by subaerial processes: Tasmania, Australia. Earth Surface Processes and Landforms 25(10): 1085-1101. Smerdon, E. T., and R. P. Beasley. 1961. Critical tractive forces in cohesive soils. Agric. Eng. 26-29. Trimble, S. W. 1997. Contribution of stream channel erosion to sediment yield from an urbanizing watershed. Science 278: 1442-1444. Comparison of  c Estimates For individual soils, jet test and silt-clay methods resulted in  c values as much as four orders of magnitude greater than the empirical methods. The high silt-clay  c values were likely a result of the study soils having a higher silt-clay content (16-88%) than Julian and Torres (2.4-17.5%; 2006). Median  c values for the jet test and silt-clay methods were statistically higher than the empirical methods (p<0.001).  c (Pa) JT SD P c D 50 I w SC Results Streambank k d was estimated by empirical equations developed by Hanson and Simon (2001) and Osman and Thorne (1988). Comparison of k d Estimates k d ( cm 3 /Ns) JT OT HS The median k d produced by the jet test measurements was significantly greater than the two statistically similar empirical methods (HS, OT; p<0.001). For individual soils, the jet test measurements resulted in estimates two orders of magnitude greater than the empirical methods. Erosion Estimates Erosion predictions showed similar trends as the k d data; parameters measured by the jet test resulted in significantly higher erosion predictions (p<0.001). Erosion predictions were unrealistically high. A 50% reduction to  a (shear stress partitioning for vegetation) reduced median erosion values by 62 to 65%. Biological Systems Engineering Department, Virginia Tech, Blacksburg, VA Jet Test Device Pump Point Gage Head Tank Predicting Erosion by the Excess Shear Stress Equation