Journal of Waterway, Port, Coastal, and Ocean Engineering

This paper describes a decade of research on siltation-reducing measures for harbor basins and the methodology and measuring techniques developed. A classification of harbor systems is made on the basis of siltation mechanisms, i.e. horizontal entrainment by mixing layers, tidal filling, and density currents. This classification distinguishes between harbors in various environments, i.e. stagnant water systems such as shallow lakes, where wind-induced currents prevail, riverine systems, tidal systems, either homogeneously fresh or saline, and estuarine systems with fresh/salt water induced density gradients. Case studies and detailed design studies yielded large reductions in siltation rates of many tens of percents for all harbor basins located in flowing water systems, using a variety of siltation-reducing techniques. These reductions were attained by reducing the exchange flow rates between the harbor and ambient water, and by reducing the sediment concentration of the water entering the basin. In the case of stagnant water systems with very fine, mainly organic matter, a reduction in exchange flow rate cannot be successful, and a reduction in siltation rates can only be achieved through the prevention of dead water zones in the harbor basins. The methodology developed is cost efficient and therefore applicable for large commercial ports as well as small marinas.

Sedimentation in harbor basins necessitates continuous maintenance dredging to keep the bed level of the harbor at the desired depth. Costs involved in the dredging and disposal of the material are often significant, and Port Authorities therefore search for adequate methods to mitigate the influx of sediment into harbors. In the 1990s, a current deflecting wall (CDW) was constructed in the entrance of the Köhlfleet harbor in Hamburg. Field observations on dredging volumes showed that siltation in the Köhlfleet could be reduced by about 40%. To investigate the feasibility of a CDW for other harbor basins in Hamburg, experiments for the Parkhafen were carried out in a nondistorted physical scale model. Water exchange between the Parkhafen and the river Elbe is governed by tidal effects and horizontal entrainment and possibly sediment-induced density currents. The first two effects were addressed in the hydrodynamic scale model. Various design parameters, such as curvature, length, and location of the CDW, were investigated under steady state as well as tidal conditions by means of visual observations of float tracks and dye injection to arrive at an optimum configuration. The spreading of dye was assessed with digitized video images, which were analyzed in terms of dye concentrations. This technique appeared to be very adequate, as high-resolution spatial information was obtained. From the dye experiments under steady state conditions, it was concluded that with the selected CDW design it is possible to reduce the gross inflow of river water into the harbor by 25–45%. The application of a sill, connected to the upstream side of the CDW, may contribute another 10% as near-bed water with high suspended sediment concentration is deflected into the river. The tidal filling of the harbor is then accomplished with water carrying a reduced sediment load.

Significant wave height is a very important variable used in ocean engineering studies. Spatial variation of the significant wave height is very important for wave energy abstraction studies which is highly dependent on the wave climate. Significant wave height and period are two of the most important wave features that directly affect the energy production. In nature these two variables exhibit temporal randomness and spatial changes. These variations cause heterogeneous regional dispersion of wave energy. In order to assess regional energy distribution, it is necessary to use the concept of regionalized variables through geostatistical methods. The main purpose of this paper is to evaluate the spatial characteristics of significant wave height by the point cumulative semivariogram approach leading to a standard regional dependence function (SRDF) based on concepts of the semivariogram. It is also possible to estimate the unmeasured station value from the closest stations by using SRDF and determine the optimum station intervals. The SRDFs are obtained from available spatial data decreasing with distance for a given set of sites. The wave energy resource in a region of the Pacific Ocean off the west coast of the United States has been evaluated as the application of proposed methodology. It is found that spatial modeling of the region considered can be achieved by using the SRDF function in acceptable error limits.

Numerical simulations are performed with a two-dimensional (2D) fully nonlinear potential flow (FNPF) model for tsunami generation by two idealized types of submarine mass failure (SMF): underwater slides and slumps. These simulations feature rigid or deforming SMFs with a Gaussian cross section, translating down a plane slope. In each case, the SMF center of mass motion is expressed as a function of geometric, hydrodynamic, and material parameters, following a simple wavemaker formalism, and prescribed as a boundary condition in the FNPF model. Tsunami amplitudes and runup are obtained from computed free surface elevations. Model results are experimentally validated for a rigid 2D slide. Sensitivity studies are performed to estimate the effects of SMF–shape, type, and initial submergence depth—on the generated tsunamis. A strong SMF deformation during motion is shown to significantly enhance tsunami generation, particularly in the far-field. Typical slumps are shown to generate smaller tsunamis than corresponding slides. Both tsunami amplitude and runup are shown to depend strongly on initial SMF submergence depth. For the selected SMF idealized geometry, this dependence is simply expressed by power laws. Other sensitivity analyses are presented in a companion paper, and results from numerical simulations are converted into empirical curve fits predicting characteristic tsunami amplitudes as functions of nondimensional governing parameters. It should be stressed that these empirical formulas are only valid in the vicinity of the tsunami sources and, because of the complexity of the problem, many simplifications were necessary. It is further shown in the companion paper how 2D results can be modified to account for three-dimensional tsunami generation and used for quickly estimating tsunami hazard or for performing simple case studies.

Based on numerical simulations presented in Part I, we derive predictive empirical equations describing tsunami generation by submarine mass failure (SMF) that are only valid in the vicinity of the tsunami sources. We give equations for slides and slumps, along with some cautions about their appropriate use. We further discuss results obtained here and in Part I and their practical application to case studies. We show that initial acceleration is the primary parameter describing SMF center of mass motion during tsunami generation. We explain an apparent paradox, raised in Part I, in slump center of mass motion, whereby the distance traveled is proportional to shear strength along the failure plane. We stress that the usefulness of predictive equations depends on the quality of the parameters they rely on. Parameter ranges are discussed in the paper, and we propose a method to estimate slump motion and shear strength and discuss SMF thickness to length values, for case studies. We derive the analytical tools needed to characterize SMF tsunami sources in propagation models. Specifically, we quantify three-dimensional (3D) effects on tsunami characteristic amplitude, and we propose an analytical method to specify initial 3D tsunami elevations, shortly after tsunami generation, in long wave tsunami propagation models. This corresponds to treating SMF tsunami sources like coseismic displacement tsunami sources. We conduct four case studies of SMF tsunamis and show that our predictive equations can provide rapid rough estimates of overall tsunami observations that might be useful in crisis situations, when time is too short to run propagation models. Thus, for each case, we show that the characteristic tsunami amplitude is a reasonable predictor of maximum runup in actual 3D geometry. We refer to the latter observation as the correspondence principle, which we propose to apply for rapid tsunami hazard assessment, in combination with the predictive tsunami amplitude equations.

The topographical scattering of gravity waves is investigated using a spectral energy balance equation that accounts for first-order wave-bottom Bragg scattering. This model represents the bottom topography and surface waves with spectra, and evaluates a Bragg scattering source term that is theoretically valid for small bottom and surface slopes and slowly varying spectral properties. The robustness of the model is tested for a variety of topographies uniform along one horizontal dimension including nearly sinusoidal, linear ramp, and step profiles. Results are compared with reflections computed using an accurate method that applies integral matching along vertical boundaries of a series of steps. For small bottom amplitudes, the source term representation yields accurate reflection estimates even for a localized scatterer. This result is proved for small bottom amplitudes $h$ relative to the mean water depth $H$ . Wave reflection by small amplitude bottom topography thus depends primarily on the bottom elevation variance at the Bragg resonance scales, and is insensitive to the detailed shape of the bottom profile. Relative errors in the energy reflection coefficient are found to be typically $2h∕H$ .

This note presents the application of the functional network (FN) and the sequential learning neural network (SLNN) for accurate prediction of tides during surge using short-term observation. Based on 34-day observed data, the proposed functional network model can predict the time series data of hourly tides directly, using an efficient learning process that minimizes the error. In the functional network, a simple equation in the form of a finite-difference equation is derived, using the tidal levels at two previous time steps. The sequential learning neural network uses one hidden neuron to predict the current tidal level. Hourly tidal data for the Typhoon Herb, measured at Taichung Harbor along the Taiwan coastal region, is used for testing the capacity of the functional network and sequential neural network models. Numerical results demonstrate that the proposed models can predict the tidal level during typhoon surge with a high correlation coefficient, based on 1-month hourly data.