METHOD FOR ASSESSING COASTAL VULNERABILITY TO EROSION

This research project provided 1) a method to evaluate the Longshore sediment transport (LST), a crucial process that shapes the coastal environments, and 2) an index designed to assess the vulnerability of coastal areas to erosion at the beach scale. In the first study, I evaluated the predictive capacity of three widely used empirical formulas (CERC, 1984; Kamphuis, 1991; Van Rijn, 2014) and the XBeach 2DH numerical model for estimating the LST rate by comparing the results obtained from both methods with field LST data. I have chosen three coastal areas in Malta Island (Għadira Bay) and northern Sicily (Cefalù and Campofelice di Roccella sites) based on different characteristics in terms of sediments, coastal type (open or embayed) and morpho-bathymetry. For each site, I analysed wave parameters, grain size of the beach and seabed sediments, coastal morphology, and marine vegetation distribution. Furthermore, I used field measurements to calibrate the numerical model's sediment transport and morphological parameters. The research findings showed that the calibrated numerical model provides greater accuracy in LST rate estimation than the empirical formulas. The latter overestimated the LST rates by factors ranging from 435 to 7885. In contrast, the numerical model overestimated the LST rate by factors of 1.8 and 1.9 at the Cefalù site and Għadira Bay, respectively, and underestimated by a factor of 0.5 at the Campofelice di Roccella site. The good performance of the numerical model is due to its consideration of site-specific factors that influence the LST rate. The parameter values for the model calibration can be used successfully in embayed systems characterized by fine/coarse sandy beaches. Moreover, the numerical model, tested so far only for sandy beaches, also works well on gravelly beaches. In the second study, I focused on developing a Coastal Vulnerability Index (CVI) to erosion at the beach scale. The proposed CVI integrates natural and physical factors represented as four sub-indexes (Morphological Characteristics, Shoreline Displacement, Longshore Sediment Transport and Wave Height) that control coastal erosion. I analysed the sub-indexes through a comprehensive dataset, including aerial surveys, digital elevation models, and wave climate data, supported by numerical modelling through the XBeach 2DH model. I tested the method at the Għadira Bay, a pocket beach located in northeastern Malta. Results revealed that the coastline is affected by low vulnerability to erosion in the north and central sectors and moderate in the southern. The CVI developed in this study significantly improves previous methodologies by offering a more precise representation of beach vulnerability to erosion through 1) the consideration of the headland's length and the marine vegetation as parameters affecting the balance between sediment loss and input; 2) a quantitative evaluation of the LST sub-index. The proposed CVI offers a comprehensive and reliable approach to quantify coastal erosion risk, providing an essential tool for local governments to improve coastal management strategies and mitigate risks associated with coastal erosion.