Abstract
Coastal bed profile change is described by bed load, pickup, and settling on a boundaryfitted moving grid. Existing bed load formula is modified by changing threshold bed shear stress to reflect local bed slope. A numerical model system adopting the above function is developed to simulate crossshore sediment transport around swash zone with steep bed slope as well as surf zone. The model system adopts a moving boundary grid which fits bed boundary slope, and other horizontal grid lines are parallel to the bed grid line. The model system is composed of flow module and sediment transport module. The flow module solves continuity equation and Reynoldsaverage NavierStokes momentum equations in intrawavephase manner. The flow module provides detailed flow information including nearbed fluid velocity which varies asymmetrically within a regular wave period near seabed and wavephase average undertow profile of main fluid body including wave boundary layer. The sediment transport module solves sediment mass conservation equation. Exchange of sediment mass between bed itself and fluid column containing suspended sediment happens through pickup and deposition. Wild bed level undulation is controlled by using a smoothing method. Model system is applied to two extreme cases of sand experiments by Kajima et al., and reasonable agreements between measurements and computations are obtained for both onshoredominant and offshoredominant cases.
1. Introduction
Sand or gravel beach functions as important protection barrier against severe natural forces, as well as pleasant place for leisure. Some coastal zones are muddy where waves are not high, which is outside of our interest in this paper. Understanding of sediment transport is the first step to preserve coastal zone.
Sediment transports in both alongshore and crossshore directions. Even if alongshore sediment transport amount is known, and shoreline movement is roughly guessed with some stable equilibrium profile concept, we are sometimes interested in shortterm crossshore seabed profile change affected by complex interaction between waves, tide, and morphology, e.g. beach profile change after artificial nourishment.
Accuracy of prediction of sediment transport and morphological change depends on quality of prediction methodology. Field sediment transport is often described by combination of alongshore transport and crossshore transport. Although field waves are shortcrested random waves, a general prediction tool should be able to reproduce morphological change for monochromatic or longcrested random wave conditions at laboratory as well.
Common field bed material is relatively poorlysorted, while laboratory experiment can use artificially chosen sediment material like wellsorted sand. When poorlysorted material is used at laboratory experiment, sediment starts sorting along beach profile; i.e. swash zone gets coarser, and underwater zone gets finer. Eventually an equilibrium state on median grain size distribution along profile will develop similarly to field environment, but obtaining final equilibrium grain sorting at laboratory may take very long time depending on initial condition, and driving force strength. Grain size sorting is not considered in this study.
Prediction of sediment transport and profile change in the swash and surf zone involves several stages, and thus a methodology for profile change prediction could be called a system. Methods are deterministic, or empirical, but most of them describe individual or combined processes. Information on fluid flow side can be obtained from either direct simulation or from parameterised methods, while information on sediment transport side is obtained from mostly empirical formulas based on statistical analysis of measurements at laboratory or field.
Sediment transport is described by two aspects: sediment movement within fluid body, and sediment exchange between fluid body and sedimentlaid seabed.
An example of the simplest end of prediction system may be lumpsum formulas for total alongshore sediment transport rate at crossshore section. Likewise, objects related to crossshore profile include equilibrium beach profile concept [1], index for typical beach shape type [2], index for existence of offshore bar [3] and beachface slope [4]. However, these approaches do not provide detailed profile change information.
The detailed end of the prediction system for crossswash zone profile change may be intrawavephase approaches. From fluid flow point of view NavierStokes equation or Reynoldsaveraged equation solver is the most detailed approach. It is not yet feasible to use fluid moleculesized grid. It is known that limitations exist in this direction, e.g. on grid size, computational time, and numerical error. The finer the grid size, the longer cpu. From sediment transport within fluid body point of view sediment particle tracking would be the utmost detailed approach. Schmeekle [5] computed fluid flow and tracked individual sediment particles on a fine threedimensional grid to investigate bed load. However, Schmeekle used uniformsized spherical sediment particles instead of real irregularly angular sediment particles, which may behave much differently from true sediment particles, and may not accurately reproduce bed form development or decay. Density of suspended sediment has often been expressed by suspended sediment concentration, and suspended sediment mass conservation is expressed by the equation including advectiondiffusionsettling terms of the suspended sediment concentration.
Most crossshore profile change prediction systems are between the two extreme ends. Some systems adopt a number of parameterisations for flow and sediment transport, while others adopt direct simulation of flow field and some empirical formulas for sediment transport. Existing prediction systems include CROSMOR [6], XBEACH [7], CSHORE [8], each of which has its own combination of process parameterisations.
Individual processes included in prediction systems have also been independently studied. Thus an existing prediction system could be upgraded by adopting a new development of specific processes. Processes involved in crossshore profile prediction can be classified into two groups, i.e. fluid flowrelated one, and sedimentrelated one.
Fluid flowrelated individual processes include wave transformation before and after breaking in shallow water [910], skewness of water level variation, or asymmetry of nearbed waveinduced orbital velocity variation, wave breaking condition, type, position, and crossshore wave height distribution after breaking, wave breakinginduced turbulence, horizontal or vertical dispersion, rupup limit and height, seabed shear stress due to wave [11], mass transport due to wave [12], undertow, effect of groundwater or tidal level, infiltration and exfiltration, and infragravity wave.
Sedimentrelated individual processes include phase lag between bed shear stress and orbital velocity [13], pickup, bed load, suspended sediment concentration at reference level, threshold bed shear stress of noncohesive sediment [14], settling velocity of sediment particle, deposition, hindered deposition, horizontal and vertical diffusion [15], bedform formation or change, and vortex entrainment over bedform [16]. The above processes have been parameterised or directly simulated depending on system.
Onoffshore bed profile at swash zone with relatively steep seabed slope is balanced by onshore sediment transport and offshore sediment transport. We can list that two major onshoretransportdriving factors are fluid velocity skewness due to nonlinear wave deformation, and nearbed onshore fluid mass transport. Wavebreakinginduced pressure impact or turbulence energy may also contribute to the onshore sediment transport. On the other hand two major offshoretransportdriving factors are seabed slope, and undertow produced by wave breaking in surf zone. The seabed slope is a sedimentrelated parameter, while the others are flowrelated parameters, see Fig. 1.
Fig. 1Major factors contributing to onshore and offshore sediment transport
There have been arguments on distinction of bed load and suspended load. Bed load is often known as sediment movement pattern of rolling, sliding and saltation. However, as seabed is mostly covered by bedforms like ripple or dune, it is more difficult to divide bed load over bedforms. Sediments on ripple crest surface are lifted, shoot over the crest into vortex grown between ripple troughs, lifted backwards with the vortex itself when flow reverses, and released from the vortex after that [16]. Here we define bed load as instant horizontal sediment response to external driving force, and pickup as vertical upward sediment movement driven by external force, which involves phaselag between the force and the sediment transport, see Fig. 2.
Fig. 2Two sediment transport modes: vertical and horizontal movements
Niroshinie et al. [17] developed a relatively detailed intrawavephase profile prediction system, which is composed of a flow module with large eddy simulation and a sediment transport module with advectiondiffusion of the suspended sediment concentration, pickup, and deposition. They did not include bed load in their prediction system. They adopted an inclined fixed grid to obtain smooth flow output along bed surface. Flow module in their system automatically produces wave skewness, waveinduced nearbed undertow above wave boundary layer. However, their inclined model grid cannot expand to offshore side with milder bed slope, and thus it is hard to provide accurate wave condition at offshore boundary. Furthemore their fixed grid cannot be used to simulate thick bathymetric change involving bottom boundary grid point removal or attachment. They didn’t take local seabed slope into account, which may influence final equilibrium profile shape of swash zone. They compared laboratory experimental results with their numerical model results at the elapsed time of 30 seconds, and showed rapid bed level oscillation during the time. Their prediction system seems a preliminary result and may need further validation for longer time of bathymetric change.
In this study a detailed intrawavephase prediction system is developed to simulate bathymetric change more naturally. A movingboundaryfitted grid is adopted to simulate thick bathymetric change in this study. Fluid flow is computed resolving wave period by solving continuity and Reynoldsaverage momentum equations in vertical domain with a mixing length closure for turbulence. Sediment transport is computed by solving the concentration advectiondiffusion equation in water body; bed load, pickup and deposition at fluidbed interface. The bed load and pickup function are modified to account the seabed slope.
2. Model system
Model system for CROSSshore profile development with Moving Grid (CROSSMG in short) proposed here is composed of three modules: flow, suspended sediment transport, and bathymetric change modules. The modules interact with each other at userspecified time steps.
2.1. Flow module
Fluid flow is basically threedimensional due to threedimensionality of turbulence. However, twodimensional simulation might be acceptable to represent a flow field, if the flow is uniform in one redundant direction like flow within a uniform sectional flume. The flow module simulates freesurface gravity wave motion of incompressible fluid in ${x}^{\text{'}}$$z$ domain.
The governing equations of the flow module are the continuity equation and two momentum equations in two directions. The continuity equation for incompressible fluid reads:
where $u$ is the fluid velocity in the $x\text{'}$ direction, $w$ is the fluid velocity in the $z$ direction, $x\text{'}$ is the longitudinal horizontal direction, and $z$ is the upward vertical direction. The Reynoldsaveraged NavierStokes equations, and the eddy viscosity are introduced as:
where $\rho $ is the fluid density; $p$ is the pressure; ${\epsilon}_{{x}^{\text{'}}}$, and ${\epsilon}_{z}$ are the turbulent eddy viscosity in the ${x}^{\text{'}}$ and $z$ directions, respectively; and $g$ is the gravitational acceleration.
The position of free water surface is computed by using the volumeoffluid (VOF) method.
The above governing equations have often been solved with a fixed, rectangular grid, see Fig. 3(a). For simulation of morphological change, fixed grid cannot follow microscale bed level change with a finitesized grid height. It is useful for computation of flow around fixed bed morphology only.
Another group tried to introduce partially full grid concept at the liquidsoil interface, see Fig. 3(b)(c). Fig. 3(b) allows partially full grid with flat or vertical border, and Fig. 3(c) allows partially full grid with a linearly sloped border [18]. These trials may produce continuous flow pattern around the partially full grid, but they have not yet been proved to produce smooth flowrelated physical properties like bed shear stress, which acts an important role for a computation of sediment transport and morphologic change, an existing bedboundaryfitted grid, sigmacoordinate fails for short period waves, especially for waves with overturning crests, which is not good for present purpose.
In order to simulate sediment transport at coastal zones a bedboundaryfitted grid is adopted here, see Fig. 3(d). A typical coastal beach profile may be expressed as Fig. 4 when this new grid is adopted.
Fig. 3Merits and demerits of grid systems for simulation of morphologic change
a) Bed level rises by a grid size
b) Partial grid with flat level
c) Partial grid with slope
d) Grid moves as accretion or erosion height
The bottom line of the new grid follows the slowlymoving bed profile, and the other higher grid points move in parallel with the bottom grid line. The vertical grid border lines are in the $z$ direction. The bottom grid line is folded with a small angle every delta $x$. It is assumed that the grid moving speed is not large, and the folding angle at every horizontal grid point remains small, either. Coastal geography is not flat, but sloped or wavy. In most cases coastal bed slope does not exceed a certain value, unless nonerodible rocks are around. The steepest slope is often observed at swash zone along crossshore profiles, and is smaller than the angle of repose for still water condition. The folding angle at every horizontal grid point interval is limited to 10° (slope = 0.18). To simulate wave transformation through curvy grid lines with no discontinuity in pressure distribution, gravity is modified: additional gravity, ${g}_{x}$, in the $x\text{'}$ direction is added in the momentum equation along grid columns, see Fig. 5.
The speed of morphological change due to deposition or erosion is not fast, and therefore the whole grid adjusts to slowly varying bed profile every time step. Then, the above governing equations become:
The turbulent eddy viscosity is modelled by a mixing length hypothesis, which has been known to be useful for flows near plane wall boundary [18]. Kim et al. [19] adopted the mixing length hypothesis with a substitution of the vertical gradient of horizontal fluid velocity ($\partial u/\partial z$) with fluid deformation ($\partial u/\partial z+\partial w/\partial x$) for flows over wavy bed form. The mixing length can be approximated by the vertical distance from the point of interest to the nearest bed surface, if bed slope is not steep. The eddy viscosity is assumed isotropic. Then:
where $l$ is the mixing length, $\kappa $ is the von Karman constant (= 0.4), ${z}^{\mathrm{*}}$ is the distance between the internal point and bed surface, and $h$ is the water depth.
Fig. 4New grid system adapted for present model system: whole grid levels change in the vertical direction depending on bed level change
a) New boundaryfitted parallelogram grid and axis $x$. Airwater interface is expressed by two kinds of grids, $F\ge $0.5 and $F<$0.5, where $F$ is volumefill ratio
b) Distorted viewing of still water level with axis $x$
Fig. 5Artificial gravitational acceleration induced in the momentum equation
Based on operator splitting theory [20], each of the above two momentum equations are split into two equations:
where superscripts *, ** express the first and second split operators, respectively. Eqs. (6) and (8) are solved by using the first order upwind scheme, and Eqs. (7) and (9) are solved by using a timeforward, spacecentered scheme.
The pressure is then computed by using the SOLA method [21] with coincident adjustment of velocity field. The present model uses a fixed coefficient $\alpha $ (= 0.8) for pressuredivergence adjustment instead of using over relaxation parameter of the SOLA:
Newton’s second law of motion is used for pressure adjustment instead of fluid compressibility for compressible fluid flows:
where $D$ is the divergence $(\partial u/\partial x+\partial w/\partial z)$, subscripts $i$, $k$ are indices for variables in grid points in a staggered grid in the $x$ and $z$ directions, respectively, see Fig. 6.
Fig. 6Staggered grid for the present flow model
2.2. Sediment transport module
Sediment transport is computed including the suspended sediment load, and the bed load. The suspended sediment transport describes sediment movement in suspended mode subject to flow conditions. On the other hand, the bed load is defined as instantaneous horizontal response to imposed shear stress on the bed surface.
The suspended sediment is often expressed as concentration, and governed by sediment mass conservation, which reads:
where $s$ is the suspended sediment concentration [kg/m^{3}]; ${w}_{f}$ is the settling velocity of sediment particles; ${\epsilon}_{s,x}$, ${\epsilon}_{s,z}$ are the diffusion coefficients of the suspended sediment concentration in the $x$, $z$ directions, respectively.
There is an interface between water column containing the suspended sediment and the deposited bed, where deposition moves sediment from the water column onto the bed, and pickup moves sediment from the bed into the water column. The deposition rate is computed from settling of suspended sediment as:
where $D$ is the deposition rate [kg/m^{2}s], and ${C}_{h}$ is the coefficient to take into account hindered settling due to high concentration near the bed (unity for low concentration), and $R$ is the probability function.
The bed load is related to both flow and bed sediment properties including bed shear stress. The bed shear stress acting on the bed surface exerted by flow can be approximated by fluid particle nearbed velocity under assumption of constant shear stress profile or equilibrium logarithmic velocity profile within thin boundary layer, that is:
where ${\tau}_{b}$ is the bed shear stress, ${C}_{f}$ is the instantaneous current friction coefficient (=${\kappa}^{2}\mathrm{l}\mathrm{n}(z/{z}_{0}{)}^{2}$), $\kappa $ is the von Karman constant (= 0.4), ${z}_{0}$ is the one thirtieth of bed roughness, and $u\left(z\right)$ is the fluid horizontal particle velocity at level z from the mean bed level.
As we look in interwavephase sediment movement, we need a prediction formula for instantaneous bed load.
Some existing empirical formulas for bed load are for wavephaseaverage bed load at wavecurrent environment, while other existing formulas are for steady current. We need not distinguish empirical bed load formula for steady current or for instantaneous current, if our approach resolves the wave phase. MeyerPeter and Muller [22], Bagnold [23], and van Rijn [24] proposed empirical formulas of bed load for current, all of which have a similar form as:
where ${q}_{b}$ is the bed load [kg/ms], ${C}_{b}$ is the scaling coefficient, ${\tau}_{b}$ is the bed shear stress, ${\tau}_{cri}$ is the critical shear stress needed for initiation of motion of a specific or representative grain size, and n is the empirical power. Nondimensional form is practically used for arbitrary bed grain size, and more universal coefficient:
where ${q}_{b}^{\mathrm{\text{'}}}$ is the nondimensional bed load; ${C}_{b,2}$ is the scaling coefficient; ${T}_{b}\text{,}$${T}_{cri}$ are nondimensional bed shear stress, and critical shear stress, respectively. Van Rijn’s [24] bed load formula is adopted here:
where ${\rho}_{s}$ is the sediment density, $\rho $ is the fluid density, ${d}_{50}$ is the median diameter [m], $g$ is the gravitational acceleration, $\nu $ is the fluid kinetic viscosity, ${\tau}_{b}$ is the bed shear stress, and ${\tau}_{cri}$ is the critical shear stress for initiation of motion.
Bed load with instantaneous response to the external force is believed to be affected by the local bed slope. Some researchers suggested modification of the critical motioninitiating bed shear stress due to the local bed slope [2527]. Dey analyzed their laboratory data, and proposed the following formula:
where ${\theta}_{x}$, ${\theta}_{y}$ are bed slopes in the $x$, $y$ directions, respectively; and $\mathrm{\u0424}$ is the angle of repose. For flows in $(xz)$ twodimensional vertical domain, the second part of Eq. (23) disappears.
For the present study we look in the problem from mechanical point of view instead of analysis of experimental data. Assume a situation that a cylinder is laid on a flat bed. Two moments balance i.e. overturning moment due to flow shear force, and resisting moment due to gravitational force, see Fig. 6. There is a pivot on a cylinder surface at the angle of repose on the vertical line from cylinder centre. Now we consider a case when flow is upward over a sloped bed. The resisting moment due to gravity is increased because of the expanded distance of action of the force to the vertical line from the cylinder centre. Thus, the critical overturning moment becomes larger. On the other hand for downward flow the resisting moment becomes smaller. This modification of resisting moment can be expressed as:
where $\theta $ is the upward bed slope. If bed slope is downward angle of repose (= $\mathrm{\u0424}$), the critical shear stress becomes zero as the above equation. Therefore, we modify Eq. (17) by replacing ${\tau}_{cri}$ with ${\tau}_{cri,\theta \mathrm{}}$ by using the relationship between the two in Eq. (24).
Fig. 7Effect of bed slope on critical bed shear stress for initiation of motion
The pickup rate has similarity to the bed load from the point that the initiation of motion is suppressed, if the bed shear stress is below the critical value, ${\tau}_{cri}$, and is more or less proportional to the bed load. Partheniades [28], Nielsen [29], and van Rijn [30] proposed formulas for instantaneous pickup rate in the following form as:
However, the pickup is vertical movement, and therefore empirical coefficient and unit are different from those of bed load. We use the following modified van Rijn’s formula for pickup rate by adding an additional coefficient, ${C}_{p,2}$ as:
where ${C}_{r}$ is the reference level concentration [volume/volume], and $a$ is the reference level above mean bed.
2.3. Bathymetric change module
Bed level change is computed from the total sediment mass conservation with sediment mass exchanges to and from water column:
where ${z}_{b}$ is the bed level [m], $t$ is time [s], $e$ is the void ratio of bed sediment, ${\rho}_{s}$ is the pure sediment density [kg/ m^{3}], $D$ is the deposition rate [kg/m^{2}s], $P$ is the pickup rate [kg/m^{2}s], and ${q}_{b}$ is the bed load [kg/ms].
Bathymetric change is computed periodically, and extrapolated with a multiplication factor for simulation of long term change. When the bed slope at a part of the bed profile exceeds the underwater angle of repose, the bed profile is modified by using a moving boundary filter. Interim profile is further treated by using the movingaverage filter multiple times as needed.
3. Model system applications and results
The flow module won preliminarily tested on a still water condition, and showed no movement of water as expected.
Majority of previous numerical works on onoffshore profile modelling have been about the erosion type profile changes so far. Initial condition of constant slope has often been used for laboratory experiments, and fast profile change was accompanied at the beginning stage because constant slope does not represent an equilibrium state.
The model system is applied to two sets of previous experiments of Kajima et al. [31] at a large wave tank for regular waves. Water depth for the two experiments was 4.5 m. The conditions of the two select sets of experiments are shown in Table 1.
Table 1Select experimental cases carried out by Kajima et al. (1982) at large wave tank
Case  Wave height, $H$ (m)  Wave period, $T$ (s)  Median grain size (m)  Bed slope ($\mathrm{t}\mathrm{a}\mathrm{n}\theta $)  Offshore water depth (m)  Duration (hr) 
13  0.95  9.0  0.000470  0.05  4.5  69.5 
34  1.62  3.1  0.000270  0.05  4.5  76.1 
Table 2Numerical parameters used for simulation of Cases 13 and 34 of Kajima et al. [31]
Case  Delta $x\left(\mathrm{\Delta}x\right)$ (m)  Delta $z$ ($\mathrm{\Delta}z$) (m)  Delta $t$ ($\mathrm{\Delta}t$) (s) 
13  0.2  0.2  9.0/256 
34  0.2  0.2  3.1/128 
The above two cases may be two opposite typical cases from the sediment transport direction point of view. Case 13 corresponds to the accretion type (Type III), and Case 34 corresponds to the erosion type (Type I) according to Sunamura and Horikawa’s [2] classification. Similar numerical parameters are used for Cases 13 and 34 of Kajima et al. [31], see Table 2.
Fig. 8Initial folded coordinate for simulation of Cases 13 and 34 laboratory experiments of Kajima et al. [31]
a) True profile
b) Distorted profile
3.1. Computation results of Case 13
Measured new bed profile of Case 13 at 69.5 hours from the start is shown in Fig. 8. Computed water level and pressure distribution, and the particle velocity vector field at a wave phase after 30 waves are shown in Figs. 910. Computed results are presented in $x$$z$ domain for convenience. Acceleration parameter of 1500 was applied to the bed level change speed.
Fig. 9Measured crossshore profile change after 69.5 hours of wave action for Case 13 of Kajima et al. [31]
Fig. 10Computed pressure after 30 waves after 30 waves
In order to reduce computational load, the bed level change speed was accelerated by using a scaling factor (multiplication factor). The laboratory experiments lasted 69.5 hours, but only 30 waves were run for numerical modelling. After every 15 waves bed profile change was allowed with the acceleration factor.
Generated waves on flat bed propagate over sloped profile, and get broken as spilling type. Fluid particle velocity near the seabed is affected by the bed friction.
Computed phaseaverage horizontal velocity component (residual current) profile at $x=$80 m after 30 waves is shown in Fig. 11. The residual current near water surface is more onshoreward, while the residual current near bed is more offshoreward.
Asymmetry of temporal nearbed particle velocity variation with respect to mean sea level has been known as one of the important factors affecting the direction of net sediment transport on crossshore profile. Previous research results described typical pattern as strong onshore current for a short term, and weak offshore current for a long term [29], in other words asymmetric speed with respect to the mean water level drives onshore sediment transport. Computed nearbed velocity variation at a point shows this asymmetry, see Fig. 12. The computed nearbed velocity asymmetry at a point within a swash zone within a wave period is considered to include the effect of enhanced turbulence due to wave breaking.
Fig. 11Computed particle velocity vector field after 30 waves
Fig. 12Computed residual horizontal velocity profile at x'= 80 m after 30 waves
Fig. 13Computed nearbed particle velocity variation within a wave period after 30 waves
a)$x=$86.4 m
b)$x=$40 m
Computed wavephaseaverage suspended sediment concentration distribution in the domain after 30 waves is shown in Fig. 13. The suspended sediment concentration is high near eroded zone, and it settles down quickly around the eroded zone.
Computed bed profile with measured one after 69.5 hours are shown in Fig. 14. The trend of accretion at onshore zone was well reproduced. The computed eroded position and the maximum erosion depth of 0.55 m were reasonably reproduced compared to measured erosion depth of about 0.77 m. The computed accretion position and the maximum accretion height of 0.89 m were also well reproduced, compared to measured accretion of about 1.02 m. It is thought that the model system satisfactorily reproduced the sediment transport and following bed profile change for this case.
Fig. 14Computed wavephaseaverage suspended sediment concentration field after 30 waves
3.2. Computation results of Case 34
Case 34 is for a setting with higher wave height, shorter wave period, and finer grain size. Measured bed profile change of Case 34 at 76.1 hours is shown in Fig. 15. Waves break earlier than Case 13, and the asymmetry of the orbital velocity is not prominent, and therefore doesn’t much enhance the onshore sediment transport in this case.
The computed water level and pressure distribution, and the particle velocity vector field at a wave phase at the beginning stage and after 30 waves are shown in Figs. 1617. Computed results are presented in $x\text{'}$$z$ domain for convenience. The acceleration parameter of 4750 was applied to the bed level change speed, respectively.
Fig. 15Computed bathymetric change after 69.5 hours waves for Case 13
Fig. 16Measured crossshore profile change after 76.1 hours of wave action for Case 34 of Kajima et al. [31]
Fig. 17Computed pressure after 30 waves
Computed phaseaverage velocity (residual current) vector profile at ${x}^{\mathrm{\text{'}}}=$80 m is shown in Fig. 18. The residual current near water surface is more onshoreward, while that near bed is more offshoreward.
Nearbed velocity variation within a wave period for Case 34 is also asymmetric with respect to the mean water level, but the asymmetry is weaker then Case 13, see Fig. 19.
Computed wavephaseaverage suspended sediment concentration distribution in the domain after 30 waves is shown in Fig. 20. The suspended sediment concentration is high near eroded zone, and it settles down around the eroded zone.
Fig. 18Computed particle velocity vector field after 30 waves
Fig. 19Computed residual horizontal velocity profile at x= 80 m after 30 waves
Fig. 20Computed nearbed particle velocity variation within a wave period after 30 waves
a)$x=$86.4 m
b)$x=$40 m
Fig. 21Computed wavephaseaverage suspended sediment concentration field after 30 waves
Computed bed profile with measured one after 76.1 hours is shown in Fig. 21. The trend of eroded onshore zone and offshore bar formation were well reproduced. The computed eroded position and the maximum erosion depth of 0.99 m were reasonably reproduced compared to measured erosion depth of about 0.81 m. The computed accretion position and the maximum accretion height of 1.82 m were also well reproduced, compared to measured accretion of about 2.04 m. It is thought that the model system satisfactorily reproduced the sediment transport and following bed profile change of Case 34, as well.
Fig. 22Computed bathymetric change after 76.1 hours for Case 34
4. Conclusions
A numerical model system was developed for specific purpose to simulate swash and surf zone profile change in this paper. The model adopts a moving boundaryfitted, parallel, nonorthogonal grid composed of parallelogram grid cells. The new governing momentum equation includes additional artificial gravity terms in the sloped $x$ axis. The new model system adopted an additional method to reflect the bed slope, which modifies the critical initiation bed shear stress.
The model system was applied to two existing laboratory experimental cases, and model results reproduced both erosiondominant, and accretiondominant laboratory at swash zone results reasonably well.
More tests of the present model system are needed to increase its reliability further. It could expand its usage to random wave cases, field situations, and threedimensional problems in the future.
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This includes research results of “MIDAS” 2016 supported by Ministry of Oceans and Fisheries (Korea).