This study aims to construct a coastal vulnerability assessment conceptual framework to improve the outcomes of Coastal Vulnerability Index (CVI) for local scale areas. Consequently, a new CVI was created adapted to the specific conditions of the area using seven variables. The new index was named Geotechnical Coastal Vulnerability Index (GCVI) due to the incorporation of two new geotechnical variables: (1) Coastal geotechnical properties and (2) Median grain size distribution. Furthermore, Fuzzy Analytic Hierarchy Process (FAHP) and Principal Component Analysis (PCA) were applied in the methodology to assign weight factors to each variable. For the verification of the GCVI predictions, a validation approach is applied using two different variables (rate of Historical shoreline movement and rate of Bed level change). GCVI results for both FAHP and PCA indicates that the greatest part of the study's area shoreline is under the regime of high and very high vulnerability. Comparison between the GCVI and GCVI results indicates higher rates in the high and very high vulnerability classes for the GCVI, while the GCVI shows lower rates in the same classes. Both analytical methods were used for the validation of the GCVI results and the comparison between them showed that the PCA was more efficient than the FAHP since it was coincided better with the rates of historical shoreline movement and bed level change.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11718066PMC
http://dx.doi.org/10.1038/s41598-025-85594-yDOI Listing

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