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We use an idealized numerical model to investigate the dynamics and fate of a small river discharging into the surf zone. Our study reveals that the plume reaches a steady state, at which point the combined advective and diffusive freshwater fluxes from the surf zone to the inner shelf balance the river discharge. At a steady state, the surf zone is well-mixed vertically due to wave-enhanced vertical turbulent diffusion and has a strong cross-shore salinity gradient. The horizontal gradient drives a cross-shore buoyancy-driven circulation, directed offshore at the surface and onshore near the bottom, which opposes the wave-driven circulation. Using a scaling analysis based on momentum and freshwater budgets, we determine that the steady-state alongshore plume extent (Lp) and the fraction of river water trapped in the surf zone depend on the ratio of the near-field plume length to the surf zone width (Lnf/Lsz) across a wide range of discharge and wave conditions, and a limited set of tidal conditions. This scaling also allows us to predict the residence time and freshwater fraction (or dilution ratio) in the steady-state plume within the surf zone, which range from approximately 0.1 to 10 days and 0.1 to 0.3, respectively. Our findings establish the basic dynamics and scales of an idealized plume in the surf zone, as well as estimates of residence times and dilution rates that may provide guidance to coastal managers. # Data from: Dynamics and scaling of a small river discharging into the surf zone [https://doi.org/10.5061/dryad.2280gb608](https://doi.org/10.5061/dryad.2280gb608) The present dataset includes the [COAWST model](https://www.usgs.gov/centers/whcmsc/science/coawst-a-coupled-ocean-atmosphere-wave-sediment-transport-modeling-system) outputs used to describe the dynamics and scaling of a small river discharging into the surf zone. ## File structure The data are structured as follows: 1. plume_scale.mat - Data of plume scales of all the cases, where * Hs: significant wave height [m] * Q: river discharge [m^3 s^-1] * L_nf: near-field plume length [m] * L_p: alongshore plume extent [m] * h_sz: water depth at the surf zone edge [m] * x_sz: surf zone width [m] * S_in: inflow salinity [PSU] * g_p: reduced gravity at the river mouth [m s^-2] * g_p*_*0: reduced gravity at the river mouth calculated using the density difference between river inflow and ambient ocean water [m s^-2] * Eta_0: water surface elevation anomaly at the river mouth [m] * V_sz: total volume of freshwater trapped in the surf zone [m^3] * T: the time required for the plume to reach a steady state [day] * L_t: plume turning distance [m] * S_bar: averaged salinity in the plume [PSU] 2. DepthAveraged.mat - Depth-averaged flow fields. DepthAveraged_BaseCase.mat, DepthAveraged_Case1.mat, DepthAveraged_Case3.mat, DepthAveraged_Case4.mat, DepthAveraged_Case6.mat, DepthAveraged_Case7.mat, DepthAveraged_Case8.mat, DepthAveraged_Case9.mat, DepthAveraged_Case16.mat, DepthAveraged_Case17.mat, DepthAveraged_Case18.mat, DepthAveraged_Case19.mat includes the results of the base case, cases 1, 3, 4, 6-9, and 16-19, respectively. In these files: * Wetdry_mask: wet/dry mask on RHO-points [binary] * Wetdry_mask_u: wet/dry mask on U-points [binary] * Wetdry_mask_v: wet/dry mask on V-points [binary] * Z: free-surface [m] * S: surface salinity [PSU] * Hs: significant wave height [m] * U: vertically integrated u-momentum component [m s^-1] * U_st: vertically-integrated u-Stokes drift velocity [m s^-1] * V: vertically integrated v-momentum component [m s^-1] * V_st: vertically-integrated v-Stokes drift velocity [m s^-1] 3. FullField_BaseCase.mat - 3D flow fields for the base case, where * Z: free-surface [m] * S: salinity [PSU] * Hs: significant wave height [m] * Lw: mean wavelength [m] * U: u-momentum component [m s^-1] * U_st: u-Stokes drift velocity [m s^-1] * V: v-momentum component [m s^-1] * V_st: v-Stokes drift velocity [m s^-1] * W: w-momentum component [m s^-1] * W_st: w-Stokes drift velocity [m s^-1] * Aks: salinity vertical diffusion coefficient [m^2 s^-1] * Akv: vertical viscosity coefficient [m^2 s^-1] * Cs_r: S-coordinate stretching curves at RHO-points [-] * Cs_w: S-coordinate stretching curves at W-points [-] 4. FreshwaterTrace_BaseCase.mat - Time series of freshwater volume and fluxes for the base case, where * i_sz: XI-index of the location of the surf zone edge [-] * i_shore: XI-index of the location of the shoreline [-] * Vsz: volume of freshwater in the plume in the surf zone [m^3] * Vis: volume of freshwater in the plume in the inner shelf [m^3] * Vsz_total: total volume of freshwater in the surf zone [m^3] * Vis_total: total volume of freshwater in the inner shelf [m^3] * R2SZ_flux: freshwater flux discharging into the surf zone [m^3 s^-1] * Vchannel: volume of freshwater in the plume in the river channel [m^3] * Vchannel_total: volume of freshwater in the river channel [m^3] * SBoundary_flux_SZ: the freshwater fluxes through the southern domain boundaries of the surf zone [m^3 s^-1] * SBoundary_flux_IS: the freshwater fluxes through the southern domain boundaries of the inner shelf [m^3 s^-1] * NBoundary_flux_SZ: the freshwater fluxes through the northern domain boundaries of the surf zone [m^3 s^-1] * NBoundary_flux_IS: the freshwater fluxes through the northern domain boundaries of the inner shelf [m^3 s^-1] * WBoundary_flux: the freshwater fluxes through the westhern domain boundary [m^3 s^-1] 5. DepthAveraged_XDiagnostic.mat - Depth-averaged diagnostic output of cross-shore momentum terms. DepthAveraged_XDiagnostic_BaseCase.mat includes the results of the base case at the steady state, and DepthAveraged_XDiagnostic_0day_1mWave.mat includes those at the start of river flow. In these files: * ubar_xadv: time-averaged 2D u-momentum, horizontal XI-advection term [m s^-2] * ubar_yadv: time-averaged 2D u-momentum, horizontal ETA-advection term [m s^-2] * ubar_xvisc: time-averaged 2D u-momentum, horizontal XI-viscosity term [m s^-2] * ubar_yvisc: time-averaged 2D u-momentum, horizontal ETA-viscosity term [m s^-2] * ubar_prsgrd: time-averaged 2D u-momentum, pressure gradient term [m s^-2] * ubar_zqsp: time-averaged 2D u-momentum, quasi-static pressure [m s^-2] * ubar_zbeh: time-averaged 2D u-momentum, Bernoulli head [m s^-2] * ubar_bstr: time-averaged 2D u-momentum, bottom stress term [m s^-2] * ubar_wbrk: time-averaged 2D u-momentum, wave breaking term [m s^-2] 6. DepthAveraged_YDiagnostic_BaseCase.mat - Depth-averaged diagnostic output of alongshore momentum terms, where * vbar_xadv: time-averaged 2D v-momentum, horizontal XI-advection term [m s^-2] * vbar_yadv: time-averaged 2D v-momentum, horizontal ETA-advection term [m s^-2] * vbar_xvisc: time-averaged 2D v-momentum, horizontal XI-viscosity term [m s^-2] * vbar_yvisc: time-averaged 2D v-momentum, horizontal ETA-viscosity term [m s^-2] * vbar_prsgrd: time-averaged 2D v-momentum, pressure gradient term [m s^-2] * vbar_zqsp: time-averaged 2D v-momentum, quasi-static pressure [m s^-2] * vbar_zbeh: time-averaged 2D v-momentum, Bernoulli head [m s^-2] * vbar_bstr: time-averaged 2D v-momentum, bottom stress term [m s^-2] * vbar_wbrk: time-averaged 2D v-momentum, wave breaking term [m s^-2] 7. grid.zip - Model grid file. * This grid file is designed for use with [ROMS](https://www.myroms.org/index.php), the hydrodynamic module of the COAWST modeling system. A diagram illustrating how the variables are placed on the grid and where the boundaries lie relative to the grid is available on [WikiROMS](https://www.myroms.org/wiki/Grid_Generation). * This grid file is in NetCDF format, which can be opened and used by a wide range of application software such as MATLAB, Python, and Panoply. For more detailed information, please refer to its [official website](https://www.unidata.ucar.edu/software/netcdf/). ## Code/Software All the post-processing scripts and data are prepared by MATLAB. 

Abstract We use an idealized numerical model to investigate the dynamics and fate of a small river discharging into the surf zone. Our study reveals that the plume reaches a steady state, at which point the combined advective and diffusive freshwater fluxes from the surf zone to the inner shelf balance the river discharge. At a steady state, the surf zone is well mixed vertically due to wave-enhanced vertical turbulent diffusion and has a strong cross-shore salinity gradient. The horizontal gradient drives a cross-shore buoyancy-driven circulation, directed offshore at the surface and onshore near the bottom, which opposes the wave-driven circulation. Using a scaling analysis based on momentum and freshwater budgets, we determine that the steady-state alongshore plume extent (L_p) and the fraction of river water trapped in the surf zone depend on the ratio of the near-field plume length to the surf-zone width (L_nf/L_sz) across a wide range of discharge and wave conditions and a limited set of tidal conditions. This scaling also allows us to predict the residence time and freshwater fraction (or dilution ratio) in the steady-state plume within the surf zone, which ranges from approximately 0.1 to 10 days and from 0.1 to 0.3, respectively. Our findings establish the basic dynamics and scales of an idealized plume in the surf zone, as well as estimates of residence times and dilution rates that may provide guidance to coastal managers. Significance StatementSmall rivers and estuaries often carry pollutants, sediments, and larvae into the coastal ocean, where wave action in the surf zone can trap them near the shore. This process can play an important role in the flux of material into and out of the nearshore ecosystem and presents a potential risk to swimmers when materials are harmful. The present study uses a numerical model to investigate the fate of freshwater discharged from small rivers into the surf zone and the processes through which trapped riverine freshwater escapes from the surf zone. These results establish a basis for predicting the fate of river-borne materials from coastal rivers and understanding the exchange between the surf zone and the inner shelf. Additionally, this work provides a theoretical framework for predicting the residence time and concentration of river-borne material trapped in the surf zone. 

This dataset is an accompaniment to the paper titled Statistics of bubble plumes generated by breaking surface waves, by Derakhti et al, in the Journal of Geophysical Research: Oceans. It includes extensive observations from arrays of freely drifting SWIFT buoys and shipboard systems, enabling concurrent high-resolution measurements of wind, waves, and bubble plumes. This dataset allowed us to examine the dependence of the penetration depth and fractional surface area (e.g., whitecap coverage) of bubble plumes generated by breaking surface waves on various wind and wave parameters over a wide range of sea state conditions in the North Pacific Ocean, including storms with sustained winds up to 22 m s-1 and significant wave heights up to 10 m.  Notably, this study provides the first field evidence of a direct relation between bubble plume penetration depth and whitecap coverage, suggesting that the volume of bubble plumes could be estimated by remote sensing techniques. 

Abstract We examine the dependence of the penetration depth and fractional surface area (e.g., whitecap coverage) of bubble plumes generated by breaking surface waves on various wind and wave parameters over a wide range of sea state conditions in the North Pacific Ocean, including storms with sustained winds up to 22 m s⁻¹and significant wave heights up to 10 m. Our observations include arrays of freely drifting SWIFT buoys together with shipboard systems, which enabled concurrent high‐resolution measurements of wind, waves, bubble plumes, and turbulence. We estimate bubble plume penetration depth from echograms extending to depths of more than 30 m in a surface‐following reference frame collected by downward‐looking echosounders integrated onboard the buoys. Our observations indicate that mean and maximum bubble plume penetration depths exceed 10 and 30 m beneath the surface during high winds, respectively, with plume residence times of many wave periods. They also establish strong correlations between bubble plume depths and wind speeds, spectral wave steepness, and whitecap coverage. Interestingly, we observe a robust linear correlation between plume depths, when scaled by the total significant wave height, and the inverse of wave age. However, scaled plume depths exhibit non‐monotonic variations with increasing wind speeds. Additionally, we explore the dependencies of the combined observations on various non‐dimensional predictors used for whitecap coverage estimation. This study provides the first field evidence of a direct relation between bubble plume penetration depth and whitecap coverage, suggesting that the volume of bubble plumes could be estimated by remote sensing. 

We revisit the classical but as yet unresolved problem of predicting the strength of breaking 2-D and 3-D gravity water waves, as quantified by the amount of wave energy dissipated per breaking event. Following Duncan ( J. Fluid Mech. , vol. 126, 1983, pp. 507–520), the wave energy dissipation rate per unit length of breaking crest may be related to the fifth moment of the wave speed and the non-dimensional breaking strength parameter  $$b$$ . We use a finite-volume Navier–Stokes solver with large-eddy simulation resolution and volume-of-fluid surface reconstruction (Derakhti & Kirby, J. Fluid Mech. , vol. 761, 2014 a , pp. 464–506; J. Fluid Mech. , vol. 790, 2016, pp. 553–581) to simulate nonlinear wave evolution, with a strong focus on breaking onset and postbreaking behaviour for representative cases of wave packets with breaking due to dispersive focusing and modulational instability. The present study uses these results to investigate the relationship between the breaking strength parameter $$b$$ and the breaking onset parameter $$B$$ proposed recently by Barthelemy et al. ( J. Fluid Mech. , vol. 841, 2018, pp. 463–488). The latter, formed from the local energy flux normalized by the local energy density and the local crest speed, simplifies, on the wave surface, to the ratio of fluid speed to crest speed. Following a wave crest, when $$B$$ exceeds a generic threshold value at the wave crest (Barthelemy et al. 2018), breaking is imminent. We find a robust relationship between the breaking strength parameter $$b$$ and the rate of change of breaking onset parameter $$\text{d}B/\text{d}t$$ at the wave crest, as it transitions through the generic breaking onset threshold ( $$B\sim 0.85$$ ), scaled by the local period of the breaking wave. This result significantly refines previous efforts to express $$b$$ in terms of a wave packet steepness parameter, which is difficult to define robustly and which does not provide a generically accurate forecast of the energy dissipated by breaking. 

We examine how Eulerian statistics of wave breaking and associated turbulence dissipation rates in a field of intermittent events compare with those obtained from sparse Lagrangian sampling by surface following drifters. We use a polydisperse two-fluid model with large-eddy simulation (LES) resolution and volume-of-fluid surface reconstruction (VOF) to simulate the generation and evolution of turbulence and bubbles beneath short-crested wave breaking events in deep water. Bubble contributions to dissipation and momentum transfer between the water and air phases are considered. Eulerian statistics are obtained from the numerical results, which are available on a fixed grid. Next, we sample the LES/VOF model results with a large number of virtual surface-following drifters that are initially distributed in the numerical domain, regularly or irregularly, before each breaking event. Time-averaged Lagrangian statistics are obtained using the time series sampled by the virtual drifters. We show that convergence of statistics occurs for signals that have minimum length of approximately 1000–3000 wave periods with randomly spaced observations in time and space relative to three-dimensional breaking events. We further show important effects of (i) extent of measurements over depth and (ii) obscuration of velocity measurements due to entrained bubbles, which are the two typical challenges in most of the available in situ observations of upper ocean wave breaking turbulence. An empirical correction factor is developed and applied to the previous observations of Thomson et al. Applying the new correction factor to the observations noticeably improves the inferred energy balance of wind input rates and turbulence dissipation rates. Finally, both our simulation results and the corrected observations suggested that the total wave breaking dissipation rates have a nearly linear relation with active whitecap coverage. 

Abstract We investigate the validity and robustness of the Barthelemy et al. (2018,https://doi.org/10.1017/jfm.2018.93) wave‐breaking onset prediction framework for surface gravity water waves in arbitrary water depth, including shallow water breaking over varying bathymetry. We show that the Barthelemy et al. (2018) breaking onset criterion, which they validated for deep and intermediate water depths, also segregates breaking crests from nonbreaking crests in shallow water, with subsequent breaking always following the exceedance of their proposed generic breaking threshold. We consider a number of representative wave types, including regular, irregular, solitary, and focused waves, shoaling over idealized bed topographies including an idealized bar geometry and a mildly to steeply sloping planar beach. Our results show that the new breaking onset criterion is capable of detecting single and multiple breaking events in time and space in arbitrary water depth. Further, we show that the new generic criterion provides improved skill for signaling imminent breaking onset, relative to the available kinematic or geometric breaking onset criteria in the literature. In particular, the new criterion is suitable for use in wave‐resolving models that cannot intrinsically detect the onset of wave breaking.