The coastal vulnerability index (CVI) is a popular index in literature to assess the coastal vulnerability of climate change. The present paper proposes a CVI formulation to make it suitable for the Mediterranean coasts; the formulation considers ten variables divided into three typological groups: geological; physical process and vegetation. In particular, the geological variables are: geomorphology; shoreline erosion/accretion rates; coastal slope; emerged beach width and dune width. The physical process variables are relative sea-level change; mean significant wave height and mean tide range. The vegetation variables are width of vegetation behind the beach and posidonia oceanica. The first application of the proposed index was carried out for a stretch of the Apulia region coast, in the south of Italy; this application allowed to (i) identify the transects most vulnerable to sea level rise, storm surges and waves action and (ii) consider the usefulness of the index as a tool for orientation in planning strategies. For the case study presented in this work, the most influential variables in determining CVI are dune width and geomorphology. The transects that present a very high vulnerability are characterized by sandy and narrow beaches (without dunes and vegetation) and by the absence of Posidonia oceanica.

Abstract:Proper water resources management involves the analysis and resolution of various optimization problems according to climate change effects on the availability and distribution of the resources themselves. Specifically, these conditions require the identification of new resource allocation optimization solutions capable of taking into account the water resource losses due to climate change scenarios. As is well known, Southern Italy is a region that is potentially very sensitive to climate change. In this paper, a 1717 km 2 area, corresponding to the province of Crotone, was analyzed as a study case. This area is characterized by a sufficient availability of resources as a whole as compared to the needs of the users, but has an unbalanced distribution of water through its various systems. After identifying water resource allocations in detail for this area, an optimization solution accounting for the expected reduced availability of water resources in the context of climate change was created and was compared with the optimization solution for current water availability.

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