Roham Bakhtyar

Effects of wave forcing on a subterranean estuary

Wave and tide are important forcing factors that typically co-exist in coastal environments. A numerical study was conducted to investigate individual and combined effects of these forces on flow and mixing processes in a near-shore subterranean estuary. A hydrodynamic model based on the shallow water equations was used to simulate dynamic sea level oscillations driven by wave and tide. The oscillating sea levels determined the seaward boundary condition of the coastal aquifer, where variably-saturated, variable-density flow was modeled. The simulation results showed that waves induced an onshore upward tilt in the phase-averaged sea level (wave set-up). The resulting hydraulic gradient generated pore water circulations in the near-shore zone of the coastal aquifer, which led to formation of an upper saline plume (USP) similar to that due to tides. However, mixing of recirculating seawater in the USP with underlying fresh groundwater was less intensive under the high-frequency wave oscillations. In the case of combined forcing, wave-induced circulations coupled with the intra-tidal flows strengthened the averaged, circulating pore water flows in the near-shore zone over the tidal period. The circulating flows increased exchange between the subterranean estuary and ocean, contributing 61% of the total submarine groundwater discharge for the simulated condition in comparison with the 40% and 49% proportions caused by the same but separate tidal and wave forcing, respectively. The combined forces also created a more extensive USP with the freshwater discharge zone shifted further seaward. The freshwater flow paths in the intertidal subterranean estuary were altered with a significant increase of associated transit times. The interplay of wave and tide led to increased mixing between discharging fresh groundwater and recirculating seawater. These results demonstrated the complexity of near-shore groundwater systems and have implications for future investigations on the fate of land-sourced chemicals in the subterranean estuary prior to discharge to the ocean.

Two-phase flow modeling of the influence of wave shapes and bed slope on nearshore hydrodynamics

ABSTRACT Bakhtyar, R., Razmi, A.M., Barry, D.A., Yeganeh-bakhtiary, A. Kees, C.E., and C.T. Miller, 2013. Two-Phase Flow Modeling of the Influence of Wave Shapes and Bed Slope on Nearshore Hydrodynamics. An Eulerian two-phase flow model (air-water) was used to simulate nearshore hydrodynamic processes driven by wave motion. The flow field was computed with the Reynolds-Averaged Navier-Stokes equations in conjunction with the Volume-Of-Fluid method and the RNG turbulence-closure scheme. To study the effects of different wave shapes on surf-swash zone hydrodynamics, a set of numerical experiments was carried out. Predictions of three wave theories (Airy, 2nd-order Stokes and 5th-order Stokes) were compared, with a focus on the turbulence and flow fields. Model performance was assessed by comparing numerical results with laboratory experimental observations. Relationships between the water depth, undertow, TKE and wave characteristics are presented. The results indicate that the characteristics of turbulence and flow, for example the position of wave breaking and magnitude of TKE, are affected by different wave types. Numerical simulations showed that only high-order Stokes wave theory predicts the nonlinearity required for predicting hydrodynamic characteristics in agreement with existing understanding of nearshore processes. Numerical simulations were run for different hydrodynamic conditions, but with a focus on different bed slopes. The transformation of incoming waves as they reach shallow water occurs closer to the shoreline for steeper profiles. Consistently, the peaks in TKE and wave set-up are shifted onshore for steeper slopes. The numerical results showed that TKE and undertow velocity are smaller on dissipative beaches than on intermediate beaches.

Cross-shore sediment transport estimation using fuzzy inference system in the swash zone

The interactions between fluid and sediment in the swash zone dominate the erosion or accretion of the beach, and they act as boundary conditions for nearshore hydrodynamic and morphodynamic models. Thus, the evaluation of sediment transport is of particular importance for many coastal processes and the design of coastal structures. In this paper, unlike conventional approaches, Fuzzy Inference System (FIS) and Adaptive-Network-Based Fuzzy Inference System (ANFIS) methods are used for the prediction and simulation of cross-shore sediment transport in the swash zone. The ANFIS and FIS are established using the free stream velocity time series, Shields parameter and antecedent cross-shore sediment transport of the available swash experimental data. Statistical measures were used to evaluate the performance of the models. Numerical experiments showed that the neuro-fuzzy approach provided satisfactory predictions in sediment transport modeling without incorporating different multipliers for uprush and backwash. Furthermore, the numerical results revealed that the ANFIS-based predictions are slightly superior to the FIS-based predictions.

Discussion of "Application of a Nonstandard Explicit Integration to Solve Green and Ampt Infiltration Equation" by D. R. Mailapalli, W. W. Wallender, R. Singh, and N. S. Raghuwanshi

Mailapalli et al. (2009) presented an explicit numerical scheme for calculation of solutions to the 1D Green and Ampt (1911) infiltration equation. They compared their numerical solution to a numerical solution obtained using the Newton-Raphson method (e.g., Rao et al., 2006) and the “approximate explicit solutions” of Salvucci and Entekhabi (1994) and (iii) Barry et al. (1995d). It is shown that (i) that the Green-Ampt model can be approximated very accurately using a simple formula, (ii) that the effective hydraulic conductivity mentioned by the authors is consistent with another infiltration model and (iii) that their numerical scheme becomes more accurate if the short-time expansion of the Green and Ampt model is used to provide that starting value of the infiltration.

An Application of Evolutionary Optimization Algorithms for Determining Concentration and Velocity Profiles in Sheet Flows and Overlying Layers

The Particle Swarm Optimization (PSO) method and the Genetic Algorithm (GA) were used to derive formulas for determining the velocity and concentration profiles in sheet flows. Specifically, these evolutionary optimization algorithms were used in conjunction with experimental data to determine coefficients and identify parameters for pre-selected formulas. The objective function, defined as the sum-of-squared errors between observed and predicted values of sediment velocity and concentration, was minimized by adjusting the parameter values in the formulas. Two well-known empirical formulas were also applied to the same data. The bias, root mean square error and scatter index were used to evaluate the comparison between predictions and measurements. The results indicated that the errors based on the PSO and GA approaches to predicting sediment parameters were less than those of the existing empirical formulas. Overall, both evolutionary approaches provided formulas that were in good agreement with the experimental data, giving improved descriptions of the vertical distribution of velocity and sediment concentration in the sheet flow for practical purposes. These models also described well the behavior of the velocity and sediment concentration above the sheet flow layer, in contrast with most existing formulas that are applicable only to the sheet flow layer.

Prediction of Longshore Sediment Transport Using Soft Computing Techniques

An important task for coastal engineers is to predict the sediment transport rates in coastal regions with correct estimation of this transport rate, it is possible to predict both natural morphological or beach morphology changes and the influence of coastal structures on the coast line. A large number of empirical formulas have been proposed for predicting the longshore sediment transport rate as a function of breaking wave characteristics and beach slope. The main shortcoming of these empirical formulas is that these formulas are not able to predict the field transport rate accurately. In this paper, an Adaptive- Network-Based Fuzzy Inference System which can serve as a basis for consulting a set of fuzzy IF-THEN rules with appropriate membership functions to generate the stipulated input-output pairs, is used to predict and model longshore sediment transport. For statistical comparison of predicted and observed sediment transport, bias, Root Mean Square Error, and scatter index are used. The results suggest that the ANFIS method is superior to empirical formulas in the modeling and forecasting of sediment transport. We conclude that the constructed models, through subtractive fuzzy clustering, can efficiently deal with complex input–output patterns. They can learn and build up a neuro-fuzzy inference system for prediction, while the forecasting results provide a useful guidance or reference for predicting longshore sediment transport.