Coastal ecosystems and anthropic activities are prone to be affected by the negative impact of marine-related processes induced by climate change, such as erosion, flooding and permanent inundation. Studies aiming at defining potential risk scenarios represent a valuable tool for the identification of the most suitable coastal adaptation measures. After outlining sea level rise implications at the Mediterranean scale, this paper deals with inundation risk scenarios for the years 2050 and 2100 for the north-eastern sector of the Island of Gozo (Malta), central Mediterranean Sea. The analysis, carried out by applying an index-based procedure, firstly required the evaluation of the susceptibility to inundation of the investigated coastal stretch under different sea level projections. Then, the spatial combination of inundation susceptibility with the exposure and vulnerability of the area allowed identification of the most critical sectors in terms of coastal risk. The results of the analysis showed that, under the worst-case climate scenarios, 5.5% and 8.1% of the investigated coastal sector are prone to very high inundation risk (Class R4) in 2050 and 2100, respectively. In particular, the bays of Ramla and Marsalforn, which are characterized by significant economic and touristic activities, were found to be the sites where the expected impacts of future sea level rise will be higher if no management strategy and adaptation action are taken in the near future.

The coastal landscape of the Maltese Islands is the result of long-term evolution, influenced by tectonics, geomorphological processes, and sea level oscillations. Due to their geological setting, the islands are particularly prone to marine-related and gravity-induced processes, exacerbated by climate change. This study aligns different concepts into a relatively concise and expedient methodology for overall coastal vulnerability assessment, taking the NE sector of Gozo Island as a test case. Geomorphological investigation, integrated with analysis of marine geophysical data, enabled characterization of coastal dynamics, identifying this stretch of coast as being potentially hazardous. The study area features a high economic value derived from tourist and mining activities and natural protected areas, that altogether not only make coastal vulnerability a major concern but also the task of assessing it complex. Before introducing the methodology proposed for overall vulnerability assessment, an in-depth revision of the vulnerability concept is provided. The evaluation was carried out by using a set of key indicators related to local land use, anthropic and natural assets, economic activities, and social issues. Results show that the most critical areas are located east of Marsalforn including Ramla Bay, an important tourist attraction hosting the largest sandy beach in Gozo. The method combines physical exposure and social vulnerability into an overall index. It proves to be cost effective in data management and processing and is suitable for the identification and assessment of overall vulnerability of coastal areas to consequences of climate- and marine-related processes, such as coastal erosion, landslides and sea level rise.

Within an E.U.-funded project, BESS (Pocket Beach Management and Remote Surveillance System), the notion of a geographic information system is an indispensable tool for managing the dynamics of georeferenced data and information for any form of territorial planning. This notion was further explored with the creation of a WebGIS portal that will allow local and regional stakeholders/authorities obtain an easy remote access tool to monitor the status of pocket beaches (PB) in the Maltese Archipelago and Sicily. In this paper, we provide a methodological approach for the implementation of a WebGIS necessary for very detailed dynamic mapping and visualization of geospatial coastal data; the description of the dataset necessary for the monitoring of coastal areas, especially the PBs; and a demonstration of a case study for the PBs of Sicily and Malta by using the methodology and the dataset used during the BESS project. Detailed steps involved in the creation of the WebGIS are presented. These include data preparation, data storage, and data publication and transformation into geo-services. With the help of different Open Geospatial Consortium protocols, the WebGIS displays different layers of information for 134 PBs including orthophotos, sedimentological/geomorphological beach characteristics, shoreline evolution, geometric and morphological parameters, shallow water bathymetry, and photographs of pocket beaches. The WebGIS allows not only for identifying, evaluating, and directing potential solutions to present and arising issues, but also enables public access and involvement. It reflects a platform for future local and regional coastal zone monitoring and management, by promoting public/private involvement in addressing coastal issues and providing local public administrations with an improved technology to monitor coastal changes and help better plan suitable interventions.

According to the most recent scenarios, the global mean sea level is expected to keep rising during the next decades as a consequence of ongoing global warming. In this context, coastal areas are considered highly vulnerable to marine- and climate-related processes, such as coastal erosion and flooding. Such processes are expected to cause shoreline retreat and local morphological variations with consequent permanent inundation of low-lying coastal sectors. Understanding the evolution of coastal morphological features under changing climate conditions is therefore crucial to protect coastal natural ecosystems, infrastructure, and human activities against the influence of future sea-level rise. This work aimed at mapping expected medium- and long-term variations in the coastline position along the north-eastern sector of the Island of Gozo (Malta, central Mediterranean Sea) by considering sea-level projections for the years 2050 and 2100 under different climate scenarios. The study was based on high-resolution topographic data elaborated in GIS environment and derived from LiDAR data collected in 2013 by the Malta Environment and Planning Authority (ERDF, 2013). Sea level projections were downloaded from the NASA Sea Level Projection Tool, which provides the most updated global and local sea-level projections from 2020 to 2150 relative to the baseline period of 1995-2014 (IPCC, 2021). In addition, indicators available from the  Climate Data Store (CDS) Copernicus platform were also used to take in consideration the combined effect of permanent and temporary sea-level rise. Then, future coastline positions were defined by considering the areas with a topographic elevation lower than the future sea levels as prone to be permanently inundated by rising sea.The analysis has allowed us to identify the bays of Ramla and Marsalforn as the most vulnerable areas since coastline changes expected in these zones will affect the economic, natural, and tourist activities present. In particular, in the case of Marsalforn, which is the main urban center in the study area, a wide range of utilities (roads, promenade, housing) will undergo increased coastal erosion/inundation threat, while coastline retreat due to sea-level rise is likely to have an impact on the dune system of Ramla Bay, which represents the best-preserved dune system in the Maltese Islands, and cause therefore loss in terms of natural ecosystems and related services. In order to provide stakeholders and planning authorities with a useful tool to support adaptation actions of the coastal communities threatened by sea-level rise induced by climate change, the results of the analysis are shown as easy-to-read maps in which areas at risk of permanent sea inundation are reported. Finally, this study lays the foundations for further research that will be aimed at providing a complete assessment of the marine- and climate-related processes (erosion, landslides, heavy rain, and fluvial flooding) impacting the coastal sectors of the Maltese Islands in a multi-risk perspective.