Maria Teresa Reis

Wave runup and overtopping at seawalls built on land and in very shallow water

AbstractThe current study proposes prediction formulas both for random wave runup and mean overtopping discharge at seawalls constructed on land or in very shallow water. Although several existing formulas for runup and overtopping use the incident wave characteristics at the toes of seawalls, this study adopts the equivalent deepwater wave characteristics and an imaginary seawall slope for easy application of the formulas, especially in relation to seawalls constructed on land. The prediction formulas for overtopping use the predicted runup values. For the wave runup prediction formulas two sets of experimental data are used; i.e., a new set of data and the data obtained in a previous study. For the wave overtopping prediction formulas, the experimental data measured in a previous study are used. Comparisons with measurements show good performances of both new prediction methods.

A Comparison of Empirical, Semiempirical, and Numerical Wave Overtopping Models

Abstract Output is compared from four methods used to estimate the overtopping rate at seawalls subject to random wave action: two empirical models, a semiempirical model, and a numerical model. The empirical models were developed by fitting dimensionless groups to data derived from physical model tests. The semiempirical model was derived from consideration of the unsteady flow of water over a weir. However, like the empirical models, it was calibrated with the results of physical model tests. In contrast, the numerical model AMAZON is a high-resolution two-dimensional finite volume model based on the nonlinear shallow-water equations. In this study, we calculated the mean overtopping discharge for a range of seawalls with front slopes from 1 : 1 to 1 : 20 and for incident wave steepnesses from 0.01 to 0.03. The results are considered alongside four sets of data from physical model tests. They show general agreement between the output from the numerical and semiempirical models and the data. Agreement with the empirical models depends principally on the value of the surf similarity parameter. The empirical models substantially overpredict discharges for some conditions.

Risk assessment in submarine outfall projects: The case of Portugal

Submarine outfalls need to be evaluated as part of an integrated environmental protection system for coastal areas. Although outfalls are tight with the diversity of economic activities along a densely populated coastline being effluent treatment and effluent reuse a sign of economic prosperity, precautions must be taken in the construction of these structures. They must be designed so as to have the least possible impact on the environment and at the same time be economically viable. This paper outlines the initial phases of a risk assessment procedure for submarine outfall projects. This approach includes a cost-benefit analysis in which risks are systematically minimized or eliminated. The methods used in this study also allow for randomness and uncertainty. The input for the analysis is a wide range of information and data concerning the failure probability of outfalls and the consequences of an operational stoppage or failure. As part of this risk assessment, target design levels of reliability, functionality, and operationality were defined for the outfalls. These levels were based on an inventory of risks associated with such construction projects, and thus afforded the possibility of identifying possible failure modes. This assessment procedure was then applied to four case studies in Portugal. The results obtained were the values concerning the useful life of the outfalls at the four sites and their joint probability of failure against the principal failure modes assigned to ultimate and serviceability limit states. Also defined were the minimum operationality of these outfalls, the average number of admissible technical breakdowns, and the maximum allowed duration of a stoppage mode. It was found that these values were in consonance with the nature of the effluent (tourist-related, industrial, or mixed) as well as its importance for the local economy. Even more important, this risk assessment procedure was able to measure the impact of the outfalls on human health and the environment.

'Effects of Zero-Overtopping Data in Artificial Neural Network Predictions'

This study examined the applicability of artificial neural networks (ANNs) to the estimation of wave overtopping over sloping seawalls, especially with regard to the best structure for an ANN. Correlation coefficients between measurements and predictions were best when 6 input units and 12 hidden layer units were employed. Bayesian Regularization, recommended in this study, does not require a validation data set. It was found that the ANNs could not recognize when wave overtopping failed to occur if data on zero overtopping were omitted.

INVESTIGATING THE LENGTHS OF SCALE MODEL TESTS TO DETERMINE MEAN WAVE OVERTOPPING DISCHARGES

This paper analyses the influence on the measured mean overtopping discharge of the duration of physical model tests of wave overtopping, bearing in mind the practical purpose of the studies, and the required accuracy of the measurements. The case study of the South Breakwater of Póvoa de Varzim Harbor, Portugal, is used to investigate this subject. During the two-dimensional physical model tests, three main target test conditions were used. For each one, different wave trains were utilized, all conforming to the same target JONSWAP spectrum, and three different test durations were employed. The number of random waves ranged from about 300 to 2400. Then, one of the three main test conditions was again used, but for twelve different test durations. In this case, the number of waves ranged from about 150 to 1900. The results suggest that the convergence of the mean overtopping discharge to a constant value with increasing test duration is not obvious. Regardless of the test duration, the information obtained with a single test gives limited information about the expected mean discharge, as the mean overtopping discharge varies even for the same wave and structure characteristics. Consequently, more information is obtained on the mean discharge if several tests of the same short duration (but with different time series) are undertaken rather than if one test of long duration is carried out.

NUMERICAL MODELLING OF BREAKWATER OVERTOPPING USING A NLSW EQUATION MODEL WITH A POROUS LAYER

This paper illustrates the application of a non-linear shallow water numerical model, AMAZON, to study the mean wave overtopping discharge at a breakwater protecting the Portuguese harbour of Povoa de Varzim. The results are compared with two-dimensional physical model data collected at the National Civil Engineering Laboratory, Portugal. The implications are considered of using two different governing equations for flow within the porous layer of the breakwater: firstly, the Darcy equation for stationary laminar flow; secondly, the Forchheimer equation for stationary turbulent flow. The results suggest that the type of flow is of secondary importance in determining the mean overtopping discharge. The parameter which most affects the results is the specified maximum velocity of the flow during the exchange of water between the surface and porous layers. Choosing suitable values of the porous flow parameters leads to a good agreement between the AMAZON results and the data.

Preliminary phases of the HIDRALERTA system: Assessment of the flood levels at S. João da Caparica beach, Portugal

ABSTRACT Raposeiro, P.D., Fortes, C.J.E.M., Capitão, R., Reis, M.T., Ferreira, J.C., Pereira, M.T.S., Guerreiro, J., 2013. Preliminary phases of the HIDRALERTA system: Assessment of the flood levels at S. João da Caparica beach, Portugal. The length of the Portuguese coast, the severity of the sea conditions and the concentration of population and economic activities on its coastal zone justify the importance of studying wave-induced risks and, in particular, flooding due to wave action. Indeed, emergency situations caused by adverse sea conditions are frequent and put in danger the safety of people and goods, with negative impacts for society, economy and natural heritage. So, assessing the risk of flooding of coastal and port areas is essential for the proper planning and management of these areas. In this framework, a methodology for the flood risk assessment in coastal and port areas is under development. The methodology is embedded into the HIDRALERTA system, a novel integrated system for port and coastal management, designed to prevent emergency situations, to support their management and to forecast incidental long-term interventions. The present paper describes the methodology, the HIDRALERTA system and a case study, the São João da Caparica beach, on the Lisbons area, where the referred methodology was recently applied. Sea wave characterization and flood level calculations are presented for the study.

Risk assessment of coastal flood in a site of special scientific interest

The Canary Islands have a long coastline with varying levels of exposure to severe sea conditions. Frequent states of alert and emergency in some parts of their coastline are commonly related to the occurrence of extreme wave conditions. Among the phenomena directly driven by the waves when reaching the shore are the wave run-up and overtopping. Both the study of the flood level, including its variability, and the associated risks are key tools in the planning and management of coastal zones. The aim of this research is to examine the probability of occurrence of run-up events capable of exceeding different topographical levels, for estimating the risk level associated with flooding of the different areas in which the Boca Barranco Beach can be divided, in terms of their nature and use. This beach is located on the island of Gran Canaria, Spain, and is part of the site of scientific interest of Jinámar. A large wave dataset is used as input to a high-resolution numerical model for propagating offshore wave conditions to shallow waters in the study area. Furthermore, the morphology of the study area is reproduced by combining different bathymetric databases. Finally, the probability of occurrence of different levels of run-up and the corresponding levels of consequences are assigned, to assess the flood risk in the different areas of the beach, which are presented in a risk map of flooding in the study area.

Port of Ponta Delgada, S. Miguel, Azores: assessment of the consequences of overtopping using AHP methodology

This work describes the application of a methodology for assessment of overtopping consequences at the port of Ponta Delgada, S. Miguel, Azores, by using a multi-criteria analysis (Analytic Hierarchy Process, AHP) on the impact of extreme overtopping exceeding the admissible values. Such approach allows obtaining results based on spatial analysis of the indicators that characterize the studied port area with respect to their relative importance.

Performance of a Fuzzy ARTMAP Artificial Neural Network in Characterizing the Wave Regime at the Port of Sines (Portugal)

ABSTRACT Santos, F.L.; Reis, M.T.; Fortes, C.J.E.M.; Lotufo, A.D.; Neves, D.R.C.B.; Poseiro, P., and Maciel, G.F., 2016. Performance of a fuzzy ARTMAP artificial neural network in characterizing the wave regime at the Port of Sines (Portugal). Techniques based on artificial neural networks (ANNs) have been increasingly applied to predict emergency situations, such as extreme wave conditions, wave overtopping or flooding, and damage to maritime structures, in coastal and port areas. In this work, a fuzzy adaptive resonance theory with mapping (FAM) ANN was trained to predict the wave regime both inside and at the entrance to the Port of Sines, one of the major trade and economic gateways of the Iberian Peninsula, located on the Portuguese west coast. In situ measurements using pressure sensors, wave buoy data, and results from two numerical wave propagation models—simulating waves nearshore (SWAN) and diffraction refraction elliptic approximation mild slope (DREAMS)—were used to train and validate the ANN. The wave regime was calculated for different points outside and inside the port. In general, the FAM predictions outside the port showed a satisfactory fit to the wave parameters (significant wave height, peak wave period, and mean wave direction) from the numerical model SWAN. Inside the port, differences from the DREAMS model were greater, because the optimized FAM parameters were obtained only for outside the port and the FAM network showed some difficulties in accounting for the complex phenomena of wave refraction, diffraction, and reflection within the port. Consequently, it is of paramount importance to obtain the FAM results based on fully optimized parameters to use the FAM output in place of the numerical models of wave propagation. Nevertheless, this methodology proved capable of providing a fast and satisfactory response that is especially useful in the scope of risk management, particularly in wave forecasting and warning systems.