Awareness of coastal landscapes vulnerability to both natural and man-made hazards induce to monitor their evolution, adaptation, resilience and to develop appropriate defence strategies. The necessity to transform the monitoring results into useful information is the motivation of the present paper. Usually, to this scope, a coastal vulnerability index is deduced, by assigning ranking values to the different parameters governing the coastal processes. The principal limitation of this procedure is the individual discretion used in ranking. Moreover, physical parameters are generally considered, omitting socio-economic factors. The aim of the present study is to complement a geographical information system (GIS) with an analytical hierarchical process (AHP), thus allowing an objective prioritization of the key parameters. Furthermore, in the present case, socio-economic parameters have been added to physical ones. Employing them jointly, an integrated coastal vulnerability index (ICVI) has been estimated and its effectiveness has been investigated. To show how it works, the proposed method has been applied to a portion of the Adriatic coastline, along the Apulian region in southern Italy. It has permitted to identify and prioritize the most vulnerable areas, revealing its efficacy as a potential tool to support coastal planning and management.

Wind, waves, tides, sediment supply, changes in relative sea level and human activities strongly affect shorelines, which constantly move in response to these processes, over a variety of timescales. Thus, the implementation of sound coastal zone management strategies needs reliable information on erosion and/or deposition processes. To suggest a feasible way to provide this information is the main reason for this work. A chain approach is proposed here, tested on a vulnerable coastal site located along southern Italy, and based on the joint analysis of field data, statistical tools and numerical modeling. Firstly, the coastline morphology has been examined through interannual field data, such as aerial photographs, plane-bathymetric surveys and seabed characterization. After this, rates of shoreline changes have been quantified with a specific GIS tool. The correlations among the historical positions of the shoreline have been detected by statistical analysis and have been satisfactorily confirmed by numerical modeling, in terms of recurrent erosion–accretion area and beach rotation trends. Finally, based on field topographic, sediment, wave and wind data, the response of the beach through numerical simulation has been investigated in a forecasting perspective. The purpose of this study is to provide a feasible, general and replicable chain approach, which could help to thoroughly understand the dynamics of a coastal system, identify typical and recurrent erosion–accretion processes, and predict possible future trends, useful for planning of coastal activities.

The present work aims at illustrating how the joint use of monitoring data and numerical models can be beneficial in understanding coastal processes. In the first part, we show and discuss an annual dataset provided by a monitoring system installed in a vulnerable coastal basin located in Southern Italy, subjected to human and industrial pressures. The collected data have been processed and analysed to detect the temporal evolution of the most representative parameters of the inspected site and have been compared with recordings from previous years to investigate recursive trends. In the second part, to demonstrate to what extent such type of monitoring actions is necessary and useful, the same data have been used to calibrate and run a 3D hydrodynamic model. After this, a reliable circulation pattern in the basin has been reproduced. Successively, an oil pollution transport model has been added to the hydrodynamic model, with the aim to present the response of the basin to some hypothetical cases of oil spills, caused by a ship failure. It is evident that the profitable prediction of the hydrodynamic processes and the transport and dispersion of contaminants strictly depends on the quality and reliability of the input data as well as on the calibration made.

Many coastal monitoring programmes have been carried out to investigate in situ hydrodynamic patterns and correlated physical processes, such as sediment transport or spreading of pollutants. The key point is the necessity to transform this growing amount of data provided by marine sensors into information for users. The present paper aims to outline that it is possible to recognize the recurring and typical hydrodynamic processes of a coastal basin, by conveniently processing some selected marine field data. The illustrated framework is made up of two steps. Firstly, a sequence of analysis with classic methods characterized by low computational cost was executed in both time and frequency domains on detailed field measurements of waves, tides, and currents. After this, some indicators of the hydrodynamic state of the basin were identified and evaluated. Namely, the assessment of the net flow through a connecting channel, the time delay of current peaks between upper and bottom layers, the ratio of peak ebb and peak flood currents and the tidal asymmetry factor exemplify results on the vertical structure of the flow, on the correlation between currents and tide and flood/ebb dominance. To demonstrate how this simple and generic framework could be applied, a case study is presented, referring to Mar Piccolo, a shallow water basin located in the inner part of the Ionian Sea (southern Italy).

The recent COVID-19 pandemic has constrained world governments to impose measures of restraint and social distancing which also involves coastal areas. One of the most affected activities is tourism due to travel restrictions imposed by precautionary measures. This is also reflected in the recreative use of the coastal strip. Consequently, beaches and coastal stretches of small municipalities can potentially become contagious outbreaks of COVID-19 if adequate control and management measures are not promptly implemented.

The present paper aims to show and discuss the long term and continuous recordings of both meteorological and hydrodynamic data collected in a semi enclosed sea. The site in question is composed by the Mar Grande and Mar Piccolo basins (Southern Italy), which are mutually connected. In turn, the Mar Grande is joined to the Ionian Sea by means of two openings. Therefore, the system shows features typical of a lagunar environment, which is also affected by coastal heavy industry and anthropic pressure, thus being highly vulnerable. A monitoring of its hydrodynamics could be useful, allowing both to check the real-time status of the basin and promptly intervene when accidents occur and to create a dataset necessary to calibrate and validate modelling systems providing forecasts. To this, in the framework of the Italian flagship Project RITMARE, a meteo-oceanographic station, a wave-current meter and a tide gauge have been installed in the area, since December 2013. In detail, measurements of wind, waves, tides and current profiles, are acquired on site with different sampling frequencies and are transmitted on a web cloud by a router 3G, where they are stored, thus being available for download by remote users. The data acquisition and processing is managed by the research group of the Department of Civil, Environmental, Building, Engineering and Chemistry (Technical University of Bari). All the acquired data are archived in monthly time-series, examined and discussed. The analysis of currents is made in two different measuring stations for the whole year 2015, as well as the analysis of wave data. On the contrary, tide data have been assessing only recently, since August 2015. Comparisons with available recordings of the year 2014 are examined. Also spatial and temporal correlations of both waves and currents are discussed. Finally, tidal trends are shown, consistent with current inversions.