Low-elevation coastal areas and their populations are at risk during and after the appearance of a storm surge event. Coastal flooding as a result of storm surge events is investigated in this paper for a number of areas around the north-eastern (NE) Mediterranean coastal zone (Adriatic, Aegean and north Levantine seas). The sea level rise (SLR) due to storm surge events is examined for the period 2000-2004. Wind data, atmospheric pressure and wave data for this period as well as in situ sea elevation measurements (from stations around the Mediterranean coasts) were used. Potential inundation zones were then identified using a 90-m horizontal resolution digital elevation model (DEM). At these zones, the sea surface elevations were calculated for the study period, using the collected data and a 2D storm surge simulation model (1/10 o ×1/10 o ) output, examining the sea level alteration in specific coastal areas, where in situ measurements are absent and are characterised as "risky" in inundation areas, due to their topography. In order to determine the level of storm track implication on major SLR incidents, the trajectories of the respective storm events were computed. The aim of this paper is to investigate the major storm surge events that appeared during the study period, identify the major "risky" costal regions along the north-eastern Mediterranean coast and determine their hazard level due to inundation caused by storm surge phenomena. The combination of the risk level determination of an area and the calculation of sea level alteration is an important tool in terms of predicting and protecting the coastal area from extreme meteorological incidents.

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Floods are lethal and destructive natural hazards. The Mediterranean, including Greece, has recently experienced many flood events (e.g., Medicanes Zorbas and Ianos), while climate change results in more frequent and intense flood events. Accurate flood mapping in river areas is crucial for flood risk assessment, planning mitigation measures, protecting existing infrastructure, and sustainable planning. The accuracy of results is affected by all simplifying assumptions concerning the conceptual and numerical model implemented and the quality of geospatial data used (Digital Terrain Models—DTMs). The current research investigates flood modelling sensitivity against geospatial data accuracy using the following DTM resolutions in a mountainous river sub-basin of Thessaly’s Water District (Greece): (a) open 5 m and (b) 2 m data from Hellenic Cadastre (HC) and (c) 0.05 m data from an Unmanned Aerial Vehicle (UAV) topographical mission. RAS-Mapper and HEC-RAS are used for 1D (steady state) hydraulic simulation regarding a 1000-year return period. Results include flood maps and cross section-specific flow characteristics. They are analysed in a graphical flood map-based empirical fashion, whereas a statistical analysis based on the correlation matrix and a more sophisticated Machine Learning analysis based on the interpretation of nonlinear relationships between input–output variables support and particularise the conclusions in a quantifiable manner.