Integration of impacts of sea-level rise to coastal zone management practices are performed through coastal vulnerability assessments. Out of the types of vulnerability assessments, a proposed model demonstrated that relative vulnerability of different coastal environments to sealevel rise may be quantified using basic information that includes coastal geomorphology, rate of sea-level rise, and past shoreline evolution for the National Assessment of Coastal Vulnerability to Sea-Level Rise for U.S. Coasts. The proposed methodology focuses on identifying those regions where the various effects of sea-level rise may be the greatest. However, the vulnerability cannot be directly equated with particular physical effects. Thus, using this concept as a starting point, a coastal vulnerability matrix and a coastal vulnerability index that use indicators of impacts of sea-level rise are developed. The developed model compares and ranks different regions according to their vulnerabilities while prioritizing particular impacts of sea-level rise of the region. In addition, the developed model determines most vulnerable parameters for adaptation measures within the integrated coastal zone management concept. Using available regional data, each parameter is assigned a vulnerability rank of very low to very high (1–5) within the developed coastal vulnerability matrix to calculate impact sub-indices and the overall vulnerability index. The developed methodology and Thieler and Hammar-Klose the proposed methodology were applied to the Göksu Delta, Turkey. It is seen that the Göksu Delta shows moderate to high vulnerability to sea-level rise. The outputs of the two models indicate that although both models assign similar levels of vulnerability for the overall region, which is in agreement with common the literature, the results differ significantly when in various parts of the region is concerned. Overall, the proposed Thieler and Hammar-Klose method assigns higher vulnerability ranges than does the developed coastal vulnerability index sea-level rise (CVI-SLR) model. A histogram of physical parameters and human influence parameters enables enable decision makers to determine the controllable values using the developed model.

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