SummaryCoastal floods are regarded as among the most dangerous and harmful of all natural disasters affecting urban areas adjacent to the shorelines. Rapid urbanization combined with climate change and poor governance often results in significant increase of flood risk, especially for coastal communities. Wave overtopping and wave run-up are the key mechanisms for monitoring the results of coastal flooding and as such, significant efforts are currently focusing on their predicting. In this paper, an integrated methodology is proposed, accounting for wave overtopping and wave run-up under extreme wave scenarios caused by storm surges. By taking advantage of past and future climatic projections of wind data, a downscaling approach is proposed, utilizing a number of appropriate numerical models than can simulate the wave propagation from offshore up to the swash zone. The coastal zone of Rethymno in Greece is selected as a case study area and simulations of wave characteristics with the model SWAN for the period 1960–2100 in the offshore region are presented. These data are given as boundary conditions to further numerical models (MIKE21 PMS and HD) in order to investigate the spatial evolution of the wave and the hydrodynamic field in intermediate and shallow waters. Finally, the calculated wave height serves as input to empirical formulas and time dependent wave propagation models (MIKE21 BW) to estimate the wave run-up and wave overtopping (EurOtop). It is suggested that the proposed procedure is generic enough to be applicable to any similar region

An integrated methodological approach to the development of a coastal flood early-warning system is presented in this paper to improve societal preparedness for coastal flood events. The approach consists of two frameworks, namely the Hindcast Framework and the Forecast Framework. The aim of the former is to implement a suite of high-credibility numerical models and validate them according to past flooding events, while the latter takes advantage of these validated models and runs a plethora of scenarios representing distinct sea-state events to train an Artificial Neural Network (ANN) that is capable of predicting the impending coastal flood risks. The proposed approach was applied in the flood-prone coastal area of Rethymno in the Island of Crete in Greece. The performance of the developed ANN is good, given the complexity of the problem, accurately predicting the targeted coastal flood risks. It is capable of predicting such risks without requiring time-consuming numerical simulations; the ANN only requires the offshore wave characteristics (height, period and direction) and sea-water-level elevation, which can be obtained from open databases. The generic nature of the proposed methodological approach allows its application in numerous coastal regions.

This paper presents a recently developed Operational Forecast Platform (OFP) for prevailing sea conditions at very important ports worldwide (Accu-Waves). The OFP produces reliable high-resolution predictions of wave characteristics in and around ocean ports. Its goal is to support safer navigation, predict possible port downtime, assist vessel approaching, enhance management of towing services, and bolster secure ship maneuvering in busy ports around the globe. Accu-Waves OFP is based on integrated, high-resolution wave modelling over the continental shelf and in coastal areas that incorporates data from global- and regional-scale, open-sea wave and ocean circulation forecasts as boundary conditions. The coupling, nesting, calibration, and implementation of the models are reported and discussed in this paper, concerning 50 selected areas near and inside significant port basins. The detailed setup of the Accu-Waves OFP and its sub-system services is also provided regarding three-day forecasts at three-hourly intervals. The validation of the wave forecast system against in situ observations from wave buoys in coastal areas of the USA, Belgium, and Spain, as well as other model predictions by established OFPs, seems very promising, with performance skill scores ranging from adequate to very good. An exceptional case of stormy seas under severe marine weather conditions with very high wave maxima (>10 m) in the port of Algeciras is further discussed, confirming the good performance of the Accu-Waves OFP.

Coastal areas are dynamic multidimensional systems challenged by the complex interactions between natural, environmental, and human-induced pressures, as well as the ever-changing climate. A comprehensive evaluation of their spatial and temporal features enables the development of effective practices required to apply integrated coastal zone management (ICZM) policies. ICZM seeks to address the vulnerability of coastal areas in an attempt to mitigate their weaknesses and increase their resilience. Hence, coastal vulnerability assessment is a prerequisite to proceed with optimal adaptation or upgrading actions. Currently, assessments are performed by considering different approaches related to dividing coastal areas into segments to observe the spatial variations of vulnerability. The present research seeks to investigate the impact of the spatial segmentation of coastal areas on the assessment of their vulnerability. To achieve this, a case study of the coastal zone of the Municipality of Thebes, located in the Northeastern Corinthian Gulf, Greece, is examined. Five segmentation approaches are applied in terms of a physical-based vulnerability assessment for two different time horizons, (a) the present and (b) the future, by incorporating the climate change impacts. This study allows for optimizing practices to estimate vulnerability parameters and obtain reliable results for practical applications while reducing time-consuming analyses.