Journal of Hydraulic Engineering

The hydrodynamic feasibility of a proposed third inlet to East Matagorda Bay, Texas, was examined by application of a two-dimensional, depth-averaged hydrodynamic model. Wind-driven flows in this remote, shallow bay frequently dominate the weak astronomical tide. The bay presently has two connections to the Gulf of Mexico, one through a short flood-relief channel and the other through a long and circuitous navigation channel. The study had to consider whether installation of a third inlet would cause the relief channel to close or increase the already strong current velocity in the navigation channel that is a concern for boating safety. The model was calibrated with measurements of wind, water level, and current taken in this study. It is concluded that the new inlet will be ebb-dominated because of the wind-induced current, and that the relief channel will not close in the presence of the new inlet. In addition, the peak current at a critical maneuvering area in the navigation channel that presently poses a hazard to vessel traffic will be reduced by as much as 25% as a result of opening the new inlet.

3-D numerical models are being used more commonly to predict changes in coastal water quality associated with point discharges such as sewage outfalls. Because these “far field” models use grid sizes which are orders of magnitude larger than the scale of near field entrainment processes, it is of interest to compare their predictive capability with that of initial mixing models and to identify ways in which the two model types can be coupled. Comparisons between the 3-D circulation model ECOMsi and the Environmental Protection Agency's mixing model RSB suggest that the former does a reasonable job predicting plume trap height and volumetric dilution but often overpredicts plume width. Results are sensitive to source representation and parameterization of horizontal and vertical diffusion. The success results from the fact that initial dilution is governed in part by gravitational exchange flow (a large-scale phenomenon that can be resolved in a far field model) in addition to plume entrainment (which is clearly subgrid scale), as well as the self-regulating relationship between plume trap height and initial dilution. Overprediction of plume width is attributed to numerical diffusive effects. Several procedures for improving predictions by coupling near and far field models are explored, ranging from the use of the near field model to dynamically adjust far field mixing parameters, so that the far field model simulates the correct trap height, to simply using the near field model to assign source location and dimension for the far field.

Riverine water temperature extremes have typically been analyzed using event-based simulations, for example the 10-year 7-day low flows, combined with record-high air temperatures and other extreme conditions relevant to the location (e.g., maximum power generation). Using this combination of extreme conditions, one can estimate the maximum water temperature that may occur on the river. However, this method does not allow for calculation of, for example, the probability of a given temperature exceedence, or the average duration of such an excursion event. Alternatively, long-term continuous simulation using historical and physically representative reconstructed data records provides a large database of realistic events, which can be used to analyze the thermal regime of a river and its variability under current and changing conditions. This study applies such a procedure to the Missouri River between Gavins Point Dam at Yankton, S.D., and Rulo, Nebr. Along this reach, the thermal regime is influenced by six power installations, which release heated condenser cooling water to the main stem. Several scenarios were simulated numerically with the one-dimensional (1D) CHARIMA model to examine the effects of current power generation, as well as changing operational, hydrologic, and climatological conditions on the river thermal regime. Model simulations revealed that climate change and increased power demand may significantly affect the thermal regime of the Missouri River; however, the scenarios simulated in this study did not result in water temperatures that exceed the current temperature standards.

Recent developments in computing turbulent and buoyant flow in sedimentation tanks are introduced. The test case is a circular, center-feed secondary clarifier with inclined bottom and central sludge withdrawal. Axisymmetry is assumed, and the flow and settling processes are modeled in a radial section by using the k-ε turbulence model on a two-dimensional, nonorthogonal grid. The computation domain includes the sludge blanket where the viscosity is affected by the rheological behavior of the sludge. The aim of the present study is to evaluate the sensitivity of the flow and concentration fields to parameters that characterize (1) the rheological properties of highly concentrated regions; (2) the settling of sludge; and (3) the effect of stratification on the turbulent diffusion. The overall appearance of the fields proves to be similar, whereas the regions of high velocities and high gradients are strongly affected by using different parameters or approaches on rheology, settling, and diffusive transport, resulting in different sludge blanket heights.

Simulation of flow and sediment transport in mountain streams is complicated by the presence of high gradients, abrupt changes in geometry, variations in regime of flow, and large roughness elements. Most of the numerical models to predict aggradation and degradation in alluvial channels have been developed for low-gradient rivers. This paper is devoted to the development of a numerical model to calculate bed elevation and grain size distribution changes in mountain streams where the maximum bed material size is in the range of boulders. An attempt is made to validate the model by using observed field data collected upstream from a small retention dam in a Venezuelan stream. After calibration of the sediment transport equation, reasonable agreement is obtained for the variations in the grain size distribution of the bed-surface material. An additional application is presented in the Cocorotico River, a small mountain stream located in the northwest region of Venezuela, which illustrates the adaptability of the model to handle a case of coarsest-bed-material removal from the active channel and to simulate the armoring process.

In this paper, a hydraulic flood routing method for multibranch rivers is developed by means of the imaginary channel length using the double-sweeping method. This method is based on the St. Venant equations describing the channel flow movement and can solve some flood routing problems for which solutions cannot be obtained by the hydrological methods. The model presented in this paper provides an effective tool to handle the problem of flood routing for multibranch rivers and to treat the problem of weir control on flood movement.

Estimation of water loss at small leaks and openings in different areas of a pipe network is handled by means of an iterative two-step procedure. The first step is estimation of the parameters in the network simulation model. It is achieved with the maximization of a likelihood function, equal to the sum of the squares of the difference between the observed water heads and flow rates and their computed values in a given number of nodes and pipes. The estimated parameters include the loss factors and the loss exponent. They provide the water loss per unit time in each area of the network, called zone. The second step is optimization of the openings of the valves included in the network. It is constrained by the minimum pressure head allowed in the nodes. Closure of the valves enhances the different response of the network with respect to the water loss and the load in each node. The robustness of the procedure is tested with numerical experiments by relaxing most of the assumptions made in the model. The water loss estimation in a real network with fictitious measures also shows the robustness of the procedure.

Steady seepage from two-dimensional domains is investigated using a dimensionless formulation for variably saturated media that depends on three dimensionless parameters, M, n, and α. The parameter M is the product of the anisotropy ratio and the squared ratio of the vertical length scale to the horizontal length scale. The parameter n increases with the uniformity of the pore sizes, and α represents the ratio of the domain height to the height of the capillary fringe. Our modeling results show that the seepage face height in rectangular domains is always larger than the seepage face height computed from saturated flow models. The results also show that the seepage face height increases with increasing M, increasing n, and/or decreasing α. The outflows computed from the present model are always larger than the outflows computed by the Dupuit assumption. Nomographs for rectangular and trapezoidal domains simulating trenches and dams are presented.

The interpretation of in situ rheometry based on shear wave propagation techniques is examined in terms of various viscoelastic model assumptions concerning sediment behavior under water waves. It is shown that, due to viscoelastic wave dispersion, measurements of shear wave velocity by pulse techniques are unsuitable as a basis for in situ rheometry, and that resonance-based techniques are unreliable.

The goal of this note is to examine a continuum theory that describes the evolution of sediment beds when subjected to time-dependent shearing forces resulting from surface water movement. The bed was conceptualized as a medium with continuously varying properties such as shear strength and void ratio. The nonlinear equation describing finite strain consolidation, and the complicated nature of the shearing forces acting on top of the bed, preclude the possibility of analytical solutions. Ramifications of linearizing the governing flow equations were explicitly evaluated for applications in bed modeling. Numerical solutions were obtained for the linear and nonlinear models under transient boundary conditions. Model results indicated that the linear model typically predicts lower void ratios, and consequently underestimates the amounts of sediment eroded from the bed as compared to the nonlinear model.

A methodology for detecting nonlinear dynamics in bed load transport rate time series and testing the ability of distribution functions to characterize rate variations is outlined. The Kolmogorov entropy of a time series consisting of >10,000 bed load transport measurements made in a laboratory flume indicates that >80% of the variability can be explained by the sequential passage of bed forms as modeled by Hamamori's logarithmic cumulative distribution function, and the remainder may be attributable to deterministic uncertainty (chaos). Greater understanding of the mutual adjustments between the turbulent flow, sediment transport, and bed forms might reduce the level of uncertainty. Nevertheless, the Hamamori function affords an effective characterization of the distribution of at-a-point bed load transport rates in cases where the fine temporal details of the transport process can be ignored.

In the well-known de Saint Venant equations, the bed roughness-coefficient cannot be measured directly and therefore needs to be estimated. The estimation process is referred to as “parameter identification,” which is a mathematical process based on using the difference between the solution of the model equations and the measured system response. This paper introduces an approach for solving the parameter identification problem in the de Saint Venant equations. The method proposed herein is widely used in gas dynamics; however, it has not been used before for unsteady problem identification of open channel flow parameters. Although the proposed solution procedure will be applied herein to the bed roughness-coefficient, it can be used for other parameters, e.g., cross-sectional area, bed width, etc. Starting with an initial guess of the roughness coefficient, the algorithm iteratively improves the guesses in the direction of the gradient of the least square criterion. The gradient is obtained by means of a variational approach, while the conditions of the criterion minimum are identified by the general method of indefinite Lagrangian multipliers.