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Human activities like dam construction in rivers and urban development in coastal areas, combined with climate change, are degrading coastal systems. As a result, many European countries have implemented laws and strategies to protect their shorelines. This research focuses on Guardamar del Segura in Spain, where human actions in the Segura River basin and changes in wave patterns have significantly damaged the beach-dune system, with erosion rates reaching −0.71 m/year. If these rates and extreme climate events continue to rise, the shoreline will keep retreating, leading to the destruction of beachfront houses and parts of the dune surface by 2050. This will cause changes in land ownership and irreversible ecological damage to the natural ecosystem. The Spanish Public Administration's inaction on coastal protection is due to a lack of coordination between government levels, insufficient technical tools to combat erosion, and inadequate legal mechanisms to fund protective measures. In contrast, countries like Germany, the Netherlands, and the United Kingdom have effective models in place. Potential solutions for Guardamar del Segura include beach and dune restoration or adding sand through revetments. Another option is a managed retreat of the most vulnerable buildings to avoid continuous repair and maintenance costs. Coastal erosion is a growing issue, and preserving our coastal ecosystems requires proactive measures, so doing nothing is no solution. [Display omitted] • Disruption of the sediment supply and intensification of storms drive coastal erosion. • Spain does not have legislation that limits the retreat of the beach berm. • Failure to act in time will cause irreversible damage in urban and natural environments. • The solutions to be taken must be sustainable and preferably based on nature (NbS). [ABSTRACT FROM AUTHOR]

This paper presents a model of the cross-shore beach profile taking into account the presence of the seagrass Posidonia oceanica whose ultimate objective is to reduce the volume of sand used in beach nourishment. The methodology describes the training, validation, testing and application of models of artificial neural networks (ANN) for computing the cross-shore beach profile of sandy beaches in the province of Murcia (Spain). Eighty ANN models were generated by modifying both the input variables and the number of neurons in the hidden layer. The input variables consist of wave and sediment data and data concerning the Posidonia oceanica . To select and evaluate the performance of the optimal model, the following parameters were used: R 2 , absolute error, mean absolute percentage error and percentage relative error. The results show a mean absolute error of 0.22 m (0.21 m in training and 0.28 m in test), representing an improvement of 85.1% compared to models that do not use the Posidonia oceanica and 69.8% against those that consider it. Although the ANN was developed for beaches with P.oceanica , it could be used in areas with other seagrass able to reduce wave energy and consolidate the sand such as Syringodium filiforme, Thaalassia testudinum, Laminaria hyperborea, Halodule wrightii and Zostera marina. [ABSTRACT FROM AUTHOR]

This article focuses on the optimal architecture of the neural network for determining the three characteristic points of the bars (starting, crest and final point). For the definition of the network, precision profiles, sedimentological and wave data were used. A total of 209 profiles taken for 22 years was used. The inputs were analysed and selected considering the variables that influenced the formation of the bars and their movement. For the selection of the optimal model different architectures were studied, generating 50 models for each of them and selecting with better results and with the smaller number of neurons in the hidden layer. To evaluate the performance of the model, various statistical errors were used (absolute error, mean magnitude of relative error and percentage relative error), with an average absolute error of 17.3 m in the distances to the coast and 0.26 m in the depths. The results were compared with equations currently employed (Table 1), which show that the errors generated by the ANN (Artificial Neural Network) are much lower (per example the MAPE committed by the proposed equation for distance to shore of the crest is 47%, while the ANN is made of 29%). [ABSTRACT FROM AUTHOR]

• Longer duration and intensity of groups of storms result in greater erosion of the dune. • The slope and height of the dune have a strong correlation with changes in its volume. • In Zone 1 of the dune system, slopes can reach up to 53° and height can reach 10 m. • Average wave flow barely deviates 3° between the three study areas (97.53° vs 94.12°) Dune systems have recently become fundamental natural solutions for the protection of the coast. The study of its morphodynamic features in storm situations is well documented in the literature. However, the morphological behaviour of these ecosystems when they are artificially modified by humans is still not adequately known. In this study, the morphological parameters of the restored dunes of Viveros Beach in Guardamar del Segura, Spain, are analysed. For this, a profile study was carried out using digital elevation models (DEM). In addition, the waves and incident storms are studied and, finally, a statistical analysis of the different variables that define the three dune zones is conducted. Results show that during periods of increased wave intensity and duration (2016–2017 and 2017–2020), there is correspondingly greater erosion in the dune. Additionally, the slope and the height of the dune present a strong correlation with changes in its volume. Greater volumetric losses occur the greater the slope of the foredune and the dune height. This situation occurs especially in the northernmost area, located next to the breakwater at the mouth of Segura River (Zone 1), where they reach up to 53° and 10.24 m, respectively. A better understanding of these factors provides coastal managers with effective tools for designing new dune landforms or conserving existing ones. [ABSTRACT FROM AUTHOR]