Coastal communities are increasingly vulnerable to storm impacts, highlighting the urgent need for predictive tools and enhanced preparedness. In this work, a comprehensive, high-resolution hydrodynamic operational service using the XBeach model is presented and tested for three urban beaches in Barcelona, NW Mediterranean Sea. The operational system is designed to provide early warnings of coastal flooding at a 3 d horizon. The operational architecture is based on Python scripts combined with task automation tools, ensuring a user-friendly system implemented on a standard desktop computer. Hydrodynamic validation of the model is carried out using data gathered during a field campaign in 2022, when a high-intensity storm occurred, resulting in a root mean square error of around 0.4 m and a skill score assessment index of 0.82. Flooding predictions were validated using videometry systems, yielding satisfactory Euclidean distances of less than 5 m for storms close to the topobathymetry collection. For storms occurring years earlier, the distances ranged between 7–15 m, underscoring the need for regular topobathymetry updates to maintain forecasting accuracy. The service provides a warning system with a specific categorisation of the event, enabling the end-users to prepare for a possible flooding. The strategy is currently running in operational mode, issuing alert warnings at the correct severity level. The outcome assists in decision-making relating to such events by utilising the operational system. The presented methodology is easily adaptable and replicable to meet user requirements or to be applied in other areas of interest.

The paper tackles some of the major challenges associated with coastal risk reduction, based on restored river-delta-coast continuums. The presented approach builds on the Ebro River-Delta system, located in the Spanish Mediterranean coast, where available data and results from hands-on restoration actions provide quantitative evidence on the synergies and trade-offs when implementing restoration. The work addresses the evolution of climatic- and human-induced risks driven by recent deltaic evolution, starting in the 1960s, when socioeconomic development increased and river regulation by large dams in the lower river course started. Such development has driven up freshwater demand, consequently diminishing both liquid and solid discharges in the river system, which has affected the natural deltaic evolution, compounded by sea-level-rise and changes in storminess due to global warming. Evolving erosion and flooding risks (problem symptoms) consider the decrease in sediment input to the delta and the increase in mean sea level (problem origin). To address the origin of the problem, we address sediment availability and transport in the lower river coast and reservoirs, followed by an assessment of sediment transport and deficit at the coastal fringe. The proposed solutions consider reservoir by-pass techniques, sediment mobilisation and downstream transport, as well as downstream transport capacity under present and future climates. Regarding the problem symptoms, we analyse the alternatives to enhance coastal resilience by means of restored coastal roughness resulting from embryonic dunes, lagoons and ridge and runnel topography. The analysis also considers coastal sediment recycling, based on a combination of wind and wave induced transports that provide a natural conveyor belt in dynamic equilibrium. Finally, the paper systematises the main synergies and trade-offs that must be considered in any coastal restoration plan, targeting a low carbon reduction of coastal risks while maintaining the important socio-economic assets in the river-delta-coast system. The conclusion section briefly explores the extrapolation of the proposed approach to other vulnerable coastal regions in Europe.

Coastal ecosystems are becoming less resilient under climate (e.g., sea-level rise, warming, acidification) and human (e.g., urbanization, coastal hardening, and river regulation) pressures, forcing local communities to face increasing risk levels. This lack of resilience is linked to an adaptation deficit that can be recovered through restoration. Yet, restoration faces barriers related to governance, funding, technical practice, and social context. To overcome such barriers, the REST-COAST project has developed a framework that reckons with coastal restoration platforms and restoration agreements, supported by “enablers” that support the upscaling and implementation of restoration projects. The proposed agreements and platforms can effectively overcome barriers by embedding governance, technical, financial, and social enablers into the agreements among stakeholders. Tailored, place-based approaches foster collaboration, long-term adaptive management, and the scaling of restoration to address accelerating climate-driven risks. The proposed agreements build on hands-on restoration lessons, offering transferable insights for global coastal resilience.

A comprehensive, high-resolution hydrodynamic operational service using XBeach model is presented and tested for three urban beaches in Barcelona, NW Mediterranean Sea. The operational architecture is based on Python scripts combined with task automation tools, ensuring a user-friendly system implemented on a standard desktop computer. Hydrodynamic validation of the model is carried out using data gathered during a field campaign in 2022, when a high-intensity storm occurred, resulting in a root mean square error of around 0.4 m and a skill score assessment index of 0.82. Flooding predictions were validated using videometry systems, yielding satisfactory Euclidean distances less than 5 m for storms close to the topobathymetry collection. For storms occurring years earlier, the distances ranged between 7–15 m, underscoring the need for regular topobathymetry updates to maintain forecasting accuracy. The operational system is designed to provide early-warning coastal flooding at three-days horizon. The service provides a warning system with a specific categorisation of the event, enabling the end-users to prepare for a possible flooding. The outcome assists in decision-making of such events by utilizing the operational system. The presented methodology is easily adaptable and replicable to meet user requirements or to be applied in other areas of interest.

Coastal erosion, caused by extreme weather events such as storms, poses a major risk to the sustainability of estuarine and coastal shorelines. Storm surges, driven by intense winds and low atmospheric pressure, can rapidly raise sea levels, leading to severe inundation and increased erosion along vulnerable coastlines. Addressing these challenges requires innovative and sustainable approaches that go beyond traditional engineered defenses.Nature-Based Solutions (NBS) for coastal protection are strategies that utilize natural ecosystems to protect coastal environments from erosion, flooding, and other environmental challenges. These solutions act as natural barriers, reduce wave energy and stabilize shorelines. In contrast to traditional engineered coastal defense systems, NBS provide sustainable, cost-effective, and resilient alternatives. Furthermore, they provide additional benefits such as new habitat creation for coastal organisms, carbon sequestration, and improved water quality. Seagrass meadows, in particular, act as natural wave dampers, interfering with coastal wave processes and significantly lowering wave heights, which reduces the impact of wave-induced stress on shorelines.This study employs an integrated modeling framework to conduct "What-If" Scenarios (WiS) for evaluating the effectiveness of seagrass meadows as a coastal protection measure. The framework combines a regional hydrodynamic model with the morphodynamic model XBeach to simulate storm impacts and nearshore morphological changes. This framework further integrates artificial intelligence (AI) with hydro-morphodynamic numerical simulations to enhance the efficiency on predicting bed level changes as indicators of erosion and deposition dynamics. Using different coastal areas (e.g. within the German Bight or Black Sea), the scenarios explore different configurations of seagrass meadows to determine optimal strategies for erosion reduction.The analysis highlights the importance of selecting appropriate planting depths, meadow density, and stem height to maximize the protective benefits of seagrass. Results indicate that the placement of meadows, rather than simply maximizing their size, plays a critical role in mitigating erosion. Strategic adjustments in planting design, based on storm characteristics and local bathymetry, can significantly enhance the efficiency of sediment stabilization, reducing erosion risks across varying conditions. This work demonstrates the value of Digital Twin-based What-If Scenarios for guiding the design and implementation of NBS. By simulating different configurations and environmental conditions, the approach fosters data-driven decision-making and collaborative planning among stakeholders. The findings provide actionable insights for coastal managers and policymakers, supporting the broader adoption of NBS as a viable strategy for enhancing coastal resilience and adapting to the growing impacts of climate change.