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Article summary:

1. Gravel beaches are becoming more common for coastal protection and beach nourishment due to the shortage of sand.

2. The equilibrium profile of gravel beaches is influenced by variables such as wave steepness, probability of occurrence, profile starting slope, energy reduction coefficient due to marine vegetation, and meadow width.

3. Numerical models were developed using these variables to accurately predict the gravel beach profile, leading to a saving in material used and greater certainty in the effectiveness of beach nourishment.

Article analysis:

The article "Gravel beaches nourishment: Modelling the equilibrium beach profile" presents a study on the variables that influence the equilibrium profile of gravel beaches and proposes a methodology to accurately predict this profile. The authors highlight the importance of knowing the equilibrium profile for successful beach nourishment with coarse-grained material or a mixture of sand and gravel, which is becoming more common due to the shortage of sand to mitigate beach erosion.

The study area includes 51 gravel beaches located in the provinces of Alicante and Murcia (Spain), where sedimentological data, maritime climate data, and characteristics of Posidonia oceanica meadows were collected. The authors analysed 31 variables related to sedimentology, waves, morphology, and marine vegetation present on the beaches to determine which are most influential in the profile.

From their analysis, they found that variables such as wave steepness and probability of occurrence perpendicular to the coast, starting slope between MWL and -2m, energy reduction coefficient due to Posidonia oceanica, and width of the meadow are most influential in determining parameters A and B for the power function of gravel beach equilibrium profile. Using these variables, they generated different numerical models that accurately predict the gravel beach profile.

Overall, this article provides valuable insights into predicting accurate profiles for gravel beaches. However, there are some potential biases and limitations in this study that need consideration. Firstly, all data used in this study were obtained from one region only (Alicante and Murcia), which may not be representative of other regions with different geological features or environmental conditions. Secondly, while 31 variables were analysed in this study, there may be other factors that could influence parameters A and B but were not considered. Thirdly, while numerical models were generated using selected variables to predict accurate profiles for gravel beaches, it is unclear how well these models perform when applied to other regions or under different environmental conditions.

In conclusion, while this article provides useful information on predicting accurate profiles for gravel beaches based on selected variables through numerical modelling techniques; it is important to consider potential biases and limitations when applying these findings outside of Alicante and Murcia or under different environmental conditions. Further research is needed to validate these models across different regions before they can be widely adopted as standard practice for designing effective beach nourishment strategies.