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The variability of coastal storms over the years and direction is considered in a unified, innovative approach, providing crucial information for a wide variety of coastal engineering studies and wave energy applications under the impact of climatic change. Specifically, an alternative easy-to-apply technique is presented and applied to consider the storms’ direction as a covariate. This technique enables the probabilistic representation of coastal storms in every direction over the directional domain and is efficiently incorporated into a non-stationary directional extreme value analysis. The developed methodology is applied to six locations in the Greek Seas. Based on the derived results, the most likely and most extreme significant wave height estimates present, in general, a bimodal behavior with pronounced maxima. In particular, the first peak is observed before the twenty-first century, while the second peak is likely to occur around the middle of the twenty-first century. Furthermore, coastal storms coming from directions of large fetches are the most severe storms, presenting though a drop in their intensity at the end of the twenty-first century. On the contrary, coastal storms of fetch-limited directions may present minor variations in their probability distributions over the years.

In the present paper a thorough probabilistic methodology is presented, aiming at estimating the reliability of coastal structures, such as rubble mound breakwaters during their lifetime, based on the probabilistic representation of load environmental and resistance parameters. One of the innovative points and main objectives of this study is the estimation of the failure probability of a coastal structure based on the long-term wave climate at the structure's location, usually met in intermediate waters, using wave observations or measurements in deeper waters. This task is accomplished by applying a wave propagation statistical model in order that the joint probability density function of all random load parameters be estimated at the structure's location. Moreover, a relation between an event-based extreme value analysis and an analysis on sea-state conditions within storm events is derived in order that both of these two approaches could be compared estimating the same kind of failure probability; an unconditional one. The latter is properly defined here as the percentage of the structure's Lifetime that the structure will be in a failure situation. This unconditional failure probability provides direct information on the time period that the structure will be in a situation of failure (since it considers the total range of loadings and total lifetime), and thus can be incorporated more efficiently in an integrated risk analysis with consideration of social and economic costs. Besides, another specific issue of scientific originality could be considered the investigation on the proper time step denoting the sea state in the sea state analysis applied. In this manner, the actual history and shape of each storm event is taken into consideration. Furthermore, it is shown that these two approaches could be incorporated in the design of a coastal structure. Moreover, two different fully probabilistic methods, Direct Integration Method and Monte Carlo Method, were applied (and compared) by using a combination of variables with zero and non-zero hazard rate, referred here as a combined time-invariant and time-variant analysis. Finally, the effect of considering additional and different types of parameters as random variables on the assessed failure probability of the structure has been investigated. The aforementioned methodology has been applied to a sample of wave and sea level data at the structure's location generated for this purpose. The original wave data were derived from measurements in deeper waters than the structure's location, covering a period of 8 years, obtained from an oceanographic buoy, located in the western Mediterranean off Malaga, Spain. Sea level data were also obtained from a tide gauge, located in Malaga's harbor. Finally, it is shown that the methodology derived from this study could be incorporated into a coastal structure's design process to meet specific safety requirements.

The main objective of the present paper is to achieve the simulation of the long-term (e.g., annual) morphological evolution (bathymetry and shoreline) of a coastal area (Mastichari beach, Greece) due to wind-generated waves in an accurate and cost-effective way. For this purpose, wave climate schematization techniques are adopted in order to reduce the computational effort without losing or distorting the crucial information. Referring to the current practice, the wave chronology is not considered in detail in these acceleration techniques, and therefore, sea bottom and shoreline evolution are not estimated as a function of time. To fill this gap, a novel and easy-to-use chronology-based wave input reduction method is developed to produce representative wave time series of different intensities and durations. The performance of all the applied techniques in the present study is evaluated, and a comparative analysis is conducted. It is shown that the new chronology-based wave input reduction method can achieve a model run-time reduction of about 70%, while at the same time, it provides satisfactorily accurate results. In general, this research could be useful for coastal engineering studies and coastal zone monitoring, and thus, it would be a valuable tool for coastal engineers and marine scientists.

The foreseeable acceleration of global sea level rise could potentially pose a major threat to the natural charm and functional integrity of the world-renowned tourist coastal attractions of Rhodes Island, as a result of the anticipated increasing frequency of flooding and erosion events. Hence, this study aims to determine the most vulnerable segments (in terms of physical impact) of the Rhodes coastline through the widely accepted coastal vulnerability index (CVI), applying a combination of well-known, broadly used approaches and methods. The frequency distribution of the current CVI along the island’s coastline suggests a rather worrying high to very high vulnerability of 40%. In addition, a CVI projection to the end of the 21st century (based on the Intergovernmental Panel on Climate Change predictive scenarios) indicates an enhancement of the total vulnerability by 48%, mainly focused on the majority of the western coastline. Hence, a considerable number of popular coastal destinations in the island shall remain under unignorable threat and, therefore, coastal managers and decision-makers need to hatch an integrated plan to minimize economic and natural losses, private property damage and tourism infrastructure deterioration from flooding and erosion episodes, which will most likely be intensified in the future.

Wave-induced morphodynamic processes that cause formation, preservation, and destruction of the Prasonisi tombolo in Rhodes Island are investigated, based on satellite image analysis and numerical modeling. A new method is developed for extracting wave events that consist of successive wave data of similar characteristics. The wave events refer either to wind seas or swell seas. This process combined with the satellite image analysis is then utilized for the derivation of the most representative wave scenarios that affect tombolo and salient formation. In particular, the main factors that play a significant role in tombolo and salient evolution are the offshore wave conditions, the location and width of the surf zone, the maximum value of the wave breaking index in the study area, and the initial bottom bathymetry before the study area is exposed to a new sea state. In general, the proposed method provides a realistic insight into tombolo morphodynamics and can be used to provide a cost-effective approach and a wave data-reduction technique for coastal engineering studies.

The main objective of the present study is the combination of short- with long-term wave statistics in deep waters in order to achieve a more accurate description of the long-term wave climate in shallower waters. Such a description would provide vital information for many engineering applications in deep and intermediate waters, including design of coastal structures. This task can be accomplished by accumulating the statistics for all short-term sea conditions, considering the frequency of occurrence of each sea state during a certain period of years. A modification of an existing relationship has been developed aiming at achieving this purpose. More specifically, by using the relative frequencies of occurrence of the significant wave height (Hs) and mean zero-crossing wave period (Tm), measured at a specific location, as well as the short-term joint distributions of wave height (H) and period (T) associated with each sea state, the long-term joint distribution of H and T can be produced at that location in deep waters. Then, the long-term joint probability density function of Hs and Tm and the long-term joint probability function of H and T can be estimated at any intermediate water depth by considering wave directionality in deep waters and wave transformation of each individual wave, as waves propagate from the open sea towards shallower waters. Wave measurements obtained at three different locations in the Aegean (Greece) have been examined and compared. The results showed that, as waves propagate from deep to shallower waters, wave statistics differ from those in deeper waters, especially when waves become significantly depth limited. It is noted that this individual wave analysis refers to short-crested waves, thus wave directionality and refraction have been considered. However, in this approach, the nonlinear wave – wave interactions have not been taken into account.

A simple, small array of a few elevation probes is proposed for the estimation of wave directional spreading and the mean wave direction. This technique offers the possibility of such estimations through two comparable methods, that is, the Maximum Likelihood Method and the Maximum Entropy Method. It is noted that the latter method was combined with an approximate technique, based on a simple alternative calculation of sea surface’s orthogonal slopes. The small array was proved to work well in both methods’ applications to laboratory and modeled data. In summary, this paper proposes a simple array of probes and an approximate technique for the estimation of wave directional spreading, which can be used in association with laboratory, numerical, and field measurements, and can give sufficiently accurate results.