New report analyses and verifies the value of beaches for adaptation to future coastal flood risk

The future impacts of climate change and of mean sea-level rise (SLR) are expected to have a profound effect on the coastal zone^1,2, although the magnitude of these impacts is still uncertain^3,4. Higher water levels will lead to the permanent inundation of some low-lying coastal zones⁵ and more frequent extreme flood events^6,7,8, which will in turn modify coastal landscapes increasing the exposure of coastal communities and assets^9,10. Essential features of coastal landscapes include ecosystems such as wetlands, mangroves, coral reefs, and beach and dune systems, which provide multiple benefits that have begun to decline and will continue to do so at rapid rates without climate change mitigation, risk management and adaptation ^11,12,13,14. One of the coastal ecosystem services under threat is flood protection, which is particularly important along densely populated and developed coastlines^15,16.

The flood protection services provided by mangroves and coral reefs have been economically assessed in the literature considering climate and degradation scenarios^17,18,19. This has contributed to the benefits of conserving and restoring them being increasingly recognised by scientists, multilateral and governmental agencies, and the insurance industry^20,21. As for beaches, there are several studies that analyse their effectiveness as natural flood defences^22,23,24,25, however, additional work is needed to understand their benefits in flood risk reduction. Knowing this information can be of key importance as beaches represent one-third of the world’s coasts²⁶, they are subject to the action of storms and rising mean sea levels^27,28, and their maintenance has long been under discussion^29,30. Cost-effective decision-making on beach conservation would benefit from assessing the trade-off between the cost of an action and the benefit, including the economic benefit, that would accrue from its implementation.

Previous efforts to monetise beach services have examined the loss of human recreation due to erosion^31,32,33, the influence of erosion (and beach nourishment policies) on coastal property values^34,35,36,37, the tax rates needed to fund adaptation projects^38,39, and the willingness-to-pay for erosion prevention^40,41,42 and flood protection ^43,44,45. Here, our goal is to advance knowledge on how to quantify the flood protection value of beaches to deliver relevant information for adaptation decisions.

We propose a dynamic approach based on the avoided damage cost method, which is similar to that applied for mangroves and coral reefs (e.g., refs. ^17,18), but considers the specificities of beaches. We acknowledge that coastal flood protection is strongly dependent on the shoreline response to coastal dynamics. Therefore, our approach accounts for the dynamic interaction of shoreline evolution and flooding by coupling both processes at different time scales. This allows us to evaluate how the shoreline evolves under extreme events and due to long-term changes and how this evolution affects the total water level (TWL) and the propagation of flooding inland, which are in turn influenced by shoreface geometry and terrain heights. We also assume that robust adaptation requires not only a good understanding of physical processes but also sufficient uncertainty sampling to accommodate decisions in different contexts and time horizons and for different levels of risk and uncertainty tolerance.

We use the widely studied Narrabeen-Collaroy beach system (Australia) as an illustration to showcase our approach. The need for coupling flooding and erosion in beach protection benefits assessment is highlighted by comparing flooding results with and without including coastal erosion at the storm scale and in the long term. The flooding scenarios are built for the present-day 30-year return period storm combined with AR6 SLR⁴⁶ in 2050 and 2100. The scenarios with erosion consider the effect of storm and SLR erosion on the TWL, flooded area, and flood damage to assets. As represented in seven steps in Fig. 1, we use process-based models to downscale offshore waves, compute storm hydro- and morphodynamics and propagate flooding inland. Throughout this process, we update the present-day topo-bathymetry to first incorporate the action of SLR and then that of the storm. We quantify flood damage by combining our flood maps with data on spatially distributed land and buildings value. Further details on the approach can be found in the “Methods” section.

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