The bed roughness is specified for the hydrodynamic calculations with either a Manning's roughness coefficient (), Nikuradse roughness height (), or bed friction coefficient ( ). It is important to note that the bed roughness is assumed constant in time and not changed according to bed composition and bedforms. This is a common engineering approach which can be justified by the lack of data to initialize the bed composition and the large error in estimating the bed composition evolution and bedforms. In addition using a constant bottom roughness simplifies the model calibration. In future versions of CMS, the option to automatically estimate the bed roughness from the bed composition and bedforms will be added. In addition, the bed roughness used for hydrodynamics may not be the same as that which is used for the sediment transport calculations because each sediment transport formula was developed and calibrated using specific methods for estimating bed shear stresses or velocities, and these cannot be easily changed.
The bed friction coefficient () is related to the Manning’s roughness coefficient ( ) by (Soulsby 1997)
Commonly, the bed friction coefficient is calculated by assuming a logarithmic velocity profile as (Graf and Altinakar 1998)
where = 0.4 is Von Karman constant, and is the bed roughness length which is related to the Nikuradse roughness () by (hydraulically rough flow).
Current-Related Shear Stress
The current bed shear stress is given by
- = water density (~1025 kg/m3)
- = bed friction coefficient [-]
- = current velocity magnitude [m/s]
The magnitude of the current-related bed shear stress is simply
Wave-Related Shear Stress
The wave-related bed shear stress amplitude is given by (Jonsson 1966)
where = wave friction factor, and is an equivalent or representative bottom wave orbital velocity amplitude. The wave friction factor () is estimated using one of the following:
- r = relative roughness = [-]
- = Nikuradse roughness [m]
- semi-orbital excursion = [m]
- T = wave period[s]
Mean Bed Shear Stress Due to Waves and Currents
Under combined waves and currents, the mean (wave-averaged) bed shear stress is enhanced compared to the case of currents only. This enhancement of the bed shear stress is due to the nonlinear interaction between waves and currents in the bottom boundary layer. In CMS, the mean (short-wave averaged) bed shear stress () is calculated as
- = nonlinear bottom friction enhancement factor [-]
- = current-related bed shear stress [Pa].
The nonlinear bottom friction enhancement factor () is calculated using one of the following formulations (name abbreviations are given in parenthesis):
- Wu et al. (2010) quadratic formula (QUAD)
- Soulsby (1995) empirical two coefficient data fit (DATA2)
- Soulsby (1995) empirical thirteen-coefficient data fit (DATA13)
- Fredsoe (1984) analytical wave-current boundary layer model(F84)
- Huynh-Thanh and Temperville (1991) numerical wave-current boundary layer model ((HT91)
- Davies et al. (1988) numerical wave-current boundary layer model (DSK88)
- Grant and Madsen (1979) analytical wave-current boundary layer model (GM79)
In the case of the QUAD formula, is given by
where is an empirical coefficient, and is the wave bottom orbital velocity amplitude based on linear wave theory. For random waves, where is the bottom wave orbital velocity amplitude calculated based on the significant wave height and peak wave period (Equation 15). Wu et al. (2010) originally proposed setting . Here, the coefficient has been calibrated equal to 1.33 for regular waves and 0.65 for random waves to agree better with DATA2 formula.
A formula similar to Equation (10) was independently proposed by Wright and Thompson (1983) and calibrated using field measurements by Feddersen et al. (2000). The main difference in the two formulations is that Wu et al. (2010) uses the bottom wave orbital velocity based on the significant wave height, while the Wright and Thompson (1983) formulation uses the standard deviation of the bottom orbital velocity.
The DATA2, DATA13, F84, HT91, DSK88, and GM79 formulations are calculated using the general parameterization of Soulsby (1993):
where and b, P, and q are coefficients given by (Soulsby et al. 1993)
where are coefficients which have been fitted to each model (Table 1).
Table 1. Fitting coefficients for combined wave-current mean bottom friction.
The GM79, DATA2, and DATA13 models use the logarithmic relationship for the bed friction coefficient given by Equation (2). In the case of the F84, HT91, and DSK88 models, the bed friction coefficient is linearly interpolated in log-space using the tabulated values presented in Soulsby (1997).
In the case of the F84, HT91, DSK88, and GM79 models, the wave friction factors are linearly interpolated in log-space using the tabulated values found in Soulsby (1997). In the case of the DATA2 and DATA13 formulas, the wave friction factor is estimated using Equation (6).
Bottom Wave Orbital Velocity
The bottom wave orbital velocity amplitude for regular waves is calculated based on linear wave theory as
- H = wave height [m]
- T = wave period [s]
- k = wave number [rad/m]
Unless specified otherwise, for random waves, is set to an equivalent or representative bottom orbital velocity amplitude equal to where the root-mean-squared bottom wave orbital velocity amplitude is defined here following Soulsby (1987; 1997):
- var() = variance function,
- = instantaneous bottom orbital velocity [m/s]
- = wave orbital velocity spectrum density [s m2/s2]
- f = wave frequency [1/s] .
It is noted that the definition of is slightly different from others such as Madsen (1994), Myrhaug et al. (2001), and Wiberg and Sherwood (2008) which include factor of 2 in their definition. A simple approximation for from linear wave theory and the root-mean-squared wave height (for a Rayleigh distribution) is given by
Wiberg and Sherwood (2008) reported that estimates using and agree reasonably well with field measurements (except for and produces better estimates than other combinations with , and the zero-crossing wave period . The zero-crossing wave period is calculated as the average period (time lapse) between consecutive upward or downward intersections of the water level time series with the zero water line. A better approach is to assume a spectral shape such as the Joint North Sea Wave Project (JONSWAP) (Hasselman et al. 1973) and obtain an explicit curve for by summing the contributions from each frequency (Soulsby 1987; Wiberg and Sherwood 2008). A simple explicit expression is provided below based on the JONSWAP ( = 3.3) spectrum following the work of Soulsby (1987):
where . The above expression agrees closely with the curves presented by Soulsby (1987; 1997).
In some cases the bottom wave orbital velocity amplitude is calculated based on the significant wave height and peak wave period as
Bed slope Friction Coefficient
It is noted that in the presence of a sloping bed, the bottom friction acts on a larger surface area for the same horizontal area. This increase in bottom friction is included through the coefficient (Mei 1989; Wu 2007)
where is the bed elevation, and For bottom slopes of 1/5 and 1/3, the above expression leads to an increase in bottom friction of 2.0 percent and 5.4 percent, respectively. In most morphodynamic models, the bottom slope is assumed to be small, and the above term is neglected. However, it is included here for completeness.
- Davies, A. G., R. L. Soulsby, and H. L. King. 1988. A numerical model of the combined wave and current bottom boundary layer. Journal of Geophysical Research 93(C1):491–508.
- Fredsoe, J. (1984). “Turbulent boundary layer in wave-current motion,” Journal of Hydraulic Engineering, ASCE, 110, 1103-1120.
- Graf, W. H., and M. Altinakar. 1998. Fluvial hydraulics. Hoboken, NJ: Wiley & Sons, Ltd.
- Grant, W. D., and O. S. Madsen. 1979. Combined wave and current interaction with a rough bottom. Journal of Geophysical Research 86(C4):1797–1808.
- Hasselmann, K., T. P. Barnett, E. Bouws, H. Carlson, D. E. Cartwright, K. Enke, J. A. Ewing, H. Gienapp, D. E. Hasselmann, P. Kruseman, A. Meerbrug, P. Muller, D. J. Olbers, K. Richter, W. Sell, and H. Walden. 1973. Measurements of windwave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). Deutsche Hydrographische Zeitschrift A80(12):95.
- Huynh-Thanh, S., and Temperville, A. (1991). “A numerical model of the rough turbulent boundary layer in combined wave and current interaction,” in Sand Transport in Rivers, Estuaries and the Sea, eds. R.L. Soulsby and R. Bettess, pp.93-100. Balkema, Rotterdam.
- Jonsson, I. G. 1966. Wave boundary layers and friction factors. In Proceedings of the 10th Coastal Engineering Conference, ASCE, 127–148.
- Madsen, O. S. 1994. Spectral wave–current bottom boundary layer flows. In Proceedings of the 24th Conference on Coastal Engineering, ASCE, 384–398. Kobe, Japan.
- Myrhaug, D., L. E. Holmedal, R. R. Simons, and R .D. MacIver. 2001. Bottom friction in random waves plus current flow. Coastal Engineering (43):75–92.
- Nielsen, P. 1992. Coastal bottom boundary layers and sediment transport. Singapore: World Scientific.
- Soulsby, R.L. (1995). “Bed shear-stresses due to combined waves and currents,” in Advanced in Coastal Morphodynamics, ed M.J.F Stive, H.J. de Vriend, J. Fredsoe, L. Hamm, R.L. Soulsby, C. Teisson, and J.C. Winterwerp, Delft Hydraulics, Netherlands. 4-20 to 4-23 pp.
- Soulsby, R. L. 1997. Dynamics of marine sands. London, England: Thomas Telford Publications.
- Swart, D. H. 1974. Offshore sediment transport and equilibrium. Beach profiles. Delft, The Netherlands: Delft Hydraulics Laboratory Publications.
- Wiberg, P. L., and C. R. Sherwood. 2008. Calculating wave-generated bottom orbital velocities from surface-wave parameters. Computers and Geosciences 34(10):1243–1262.
- Wu, W., A. Sánchez, and M. Zhang. 2010. An implicit 2-D depth-averaged finite-volume model of flow and sediment transport in coastal waters. In Proceedings of the International Conference on Coastal Engineering, No. 32. Paper Number: Sediment 23. Shanghai, China.
- Wright, D. G., and K. R. Thompson. 1983. Time-averaged forms of the nonlinear stress law. Journal of Physical Oceanography (13):341–346.