**1. Introduction**

The potentially massive impact of climate change on the world's coastal zones is globally recognized. The projections given by the Intergovernmental Panel on Climate Change (IPCC) indicate a globally averaged sea level rise (SLR) [1–3]; future storms are expected to become more intense with larger peak wind speeds; average wave conditions (wave height and direction) are also expected to be modified by climate change with frequent flooding events induced by severe overtopping and overwash. These climate change-driven variations in environmental forcing are likely to result in significant physical impact along the coasts [4]. The assessment of the vulnerability of coastal areas to climate change is therefore a topic of growing interest worldwide. There is an increasing need for a detailed knowledge of the wave conditions in order to design the coastal interventions [5–8]. In literature, there are different approaches and methodologies for the assessment of vulnerability and risk due to different types of hazard such as those related to climate change. A review of a multi-risk assessment for climate change impacts is discussed by [9] while in [10] are described the most commonly used methods to assess coastal vulnerability. According to [10] the methods to assess

coastal vulnerability can be grouped into four main categories: index-based methods, indicator-based approach, GIS-based decision support systems, methods based on dynamic computer models.

Among the index-based methods, the coastal vulnerability index (CVI), originally presented by [11,12] is the first synthetic index to assess coastal vulnerability to climate change, in particular to SLR. The method uses a number of variables that affect coastal vulnerability and allows assessment of the relative coastal vulnerability of the different stretches of an investigated coastal area.

The CVI formulation proposed by [13], that modified the initial index proposed by [11,12], has been widely used for other applications and studies at different territorial scales [14–18]. In literature there are various applications of the CVI with modifications and integrations of physical parameters to adapt the index to the particular coastal area [19–26].

In this context, the present paper proposes a methodology and presents a case study for assessment of the physical vulnerability to coastal hazards; in particular, the paper proposes a CVI suitable for Mediterranean areas which considers 10 variables. Six variables replicate those proposed by [13], while the others 4 variables have been chosen to better characterize the Mediterranean coasts, especially the low-lying coastal areas.

Regarding the Mediterranean Sea, in literature there are several studies in relation to climate change. A review of climate change projections over the Mediterranean region based on global and regional climate change simulations is described in [27]. Storm surges and wind-waves constitute a further element of vulnerability and hazard for coastal areas in relation to erosion and dune breaching. Various studies have been carried out on this topic [28–32]. Projections of extreme storm surge levels along Europe have been investigated by [33]; the results obtained for the Mediterranean Sea predict changes mostly in the ±5% band, either positive or negative. As described by [33] these results are in line with the historical trends and there is consensus among different studies (e.g., [28,30,31]) for no changes, or even a decrease in the frequency and intensity of extreme events. Furthermore, as reported by [31] the increase of mean sea level and land subsidence, might significantly increase the hazard posed by coastal floods. Due to the concentration of economic activities in coastal areas, the European Environmental Agency [34] also consider the Mediterranean Sea region as one of the main climate change hotspots (i.e., one of the areas most responsive to climate change).

Regarding the application of CVI in the Mediterranean area, Doukakis [35] carried out a study to map the relative vulnerability of the western Pelleponese in Greece for a coastal length of about 50 km, while a recent application of the CVI index utilizing GIS technology is due to [36]. Another study carried out in Greece is that described by [37]; in this study, the classification of the southern coast of the Gulf of Corinth according to the sensitivity to the future sea level rise is attempted by applying the Coastal Sensitivity Index (CSI), with variable ranges specifically modified for the coastal environment of Greece, utilizing GIS technology. The results of the CVI application with an adaptation to the coast of Andalusia, Spain, are described in [38], a modified version of the CVI approach with an application to peninsular coastline of Spain is described in [4], while the Egyptian Mediterranean coast was examined for vulnerability to sea-level rise using the CVI by [39].

The study described in this paper, as mentioned above, presents an application of the CVI with the integration of four physical variables. The choice of these variables is due to the consideration that for low-lying coastal areas of the Mediterranean, which represent 46% of the Mediterranean coastline [40], coastal flooding generated by storm surge and wave-breaking represents one of the main destructive natural disasters in the Mediterranean [41].

In this direction, the four integrated variables, emerged beach width, dune width, width of vegetation behind the beach and Posidonia oceanica, are representative of the Mediterranean areas, and allow an evaluation of the ability of "natural systems" to dissipate the wave energy.

According to the CVI formulation proposed by [13], a relative vulnerability score is assigned to each variable based on the potential magnitude of its contribution to physical changes on the coast. Variables are ranked on a linear scale from 1–5 in order of increasing vulnerability and CVI values are classified in four different groups using percentiles as limits.
