In the present paper, we investigate the feasibility of wave electricity production in Italian seas by the deployment of the Seabased wave energy converter (WEC). A numerical model of the coupled buoy-generator system is presented, which simulates the behavior of the wave energy converter under regular waves of different wave heights and periods. The hydrodynamic forces, including excitation force, radiation impedance and hydrostatic force, are calculated by linear potential wave theory, and an analytical model is used for the linear generator. Two buoys of different radii are considered to explore the effect of buoy dimension on energy conversion and device efficiency. The power output is maximized by adding a submerged object to the floating buoy, in order to bring the system into resonance with the typical wave frequencies of the sites. The simulation results show a very good agreement with the published data on the Seabased WEC. The model is used to estimate energy production at eight Italian offshore locations. The results indicate that the degree of utilization of the device is higher than 20% at the two most energetic Italian sites (Alghero and Mazara del Vallo) and that it can be considerably increased if the floating body is connected to a submerged object, thanks to the resonant behavior of the WEC. In this case, the degree of utilization of the device would be higher than 40% at most of the study sites, with the highest value at Mazara del Vallo. The work enlarges the perspective, to be confirmed by experimental tests and more accurate numerical modeling, on clean electric power production from ocean waves in the Italian seas.

The North Atlantic coast of Morocco is characterised by a flat rocky outcrop in the south (Asilah Beach) and a sandy beach free of rocky outcrops in the north (Charf el-Akab). These natural beaches were monitored for a period of two years (April 2005–January 2007) and two different profiles (one for each beach) were analysed based on differences in the substrate. Topographic data were analysed using statistics and empirical orthogonal functions (EOFs) to determine beach slope and volumetric changes over time. Several morphologic phenomena were identified (accretion/erosion and seasonal tilting of beach profiles around different hinge points), attesting to their importance in explaining variability in the data. Periods of accretion were similar in both profiles, but the volumetric rate of change was faster in the sand-rich (SR) profile than in the reef flat (RF) profile. Moreover, the erosion rate for the SR profile was greater than the RF profile (135.18 m³/year vs. 55.39 m³/year). Therefore, the RF acted as a geological control on the evolution of its profile because of wave energy attenuation. Thus, special attention should be given to the RF profile, which has larger slopes, less amounts of mobilised sand, and slower erosion/accretion rates than the SR profile.

Extensive research on vegetation flow resistance at the laboratory scale has yielded numerous formulations for determining vegetation friction coefficients. However, implementing and validating these equations at the river scale is often complex due to the lack of data on vegetation features and flow characteristics during floods, resulting in a limited number of field application studies. In this research, we use the Telemac-2D hydrodynamic model in a new case study to evaluate the performance of five vegetation friction formulations applied to arboreal vegetation. Employing vegetation data acquired through field surveys and LiDAR, along with flow data collected during one of the highest peak floods recorded on the Piave River, we built a two-dimensional (2D) river model. This model considers existing arboreal vegetation and terrain conditions to compare observed water surface elevations (WSE) during the flood with those simulated using vegetation friction equations. Our findings reveal that all tested equations perform similarly in all simulations. While these equations overestimated WSE throughout most of the flood, they accurately predicted levels at the highest peak and its proximity. Additionally, we explore several vegetation scenarios, varying density and percentage of area covered by arboreal vegetation, to assess their effect on water levels and flood risk.