Climate change and sea-level rise (SLR) profoundly impact coastal zones, increasing the frequency and severity of extreme flood events. Coastal ecosystems, including beaches, provide crucial flood protection services, particularly along densely populated coastlines. While the economic value of mangroves and coral reefs for flood protection has been assessed, the quantification of beach flood protection benefits requires further investigation. Beaches constitute one-third of the world's coasts and are vulnerable to storms and SLR, making their effective management critical. Cost-effective decision-making necessitates assessing the trade-off between the costs of beach conservation and the accruing economic benefits. Previous economic assessments of beach services have focused on recreational losses due to erosion, the impact on property values, and willingness-to-pay for erosion prevention and flood protection. This study aims to advance the understanding of quantifying the flood protection value of beaches to inform adaptation decisions.

Existing literature includes economic assessments of the flood protection services provided by mangroves and coral reefs under various climate and degradation scenarios. This has led to increased recognition of the benefits of their conservation and restoration among scientists, agencies, and the insurance industry. Several studies analyze the effectiveness of beaches as natural flood defenses; however, further research is needed to fully understand their contribution to flood risk reduction. Previous efforts to monetize beach services have examined the loss of human recreation due to erosion, the impact of erosion and nourishment policies on property values, tax rates for adaptation projects, and willingness-to-pay for erosion prevention and flood protection. This study builds upon this existing research by proposing a novel dynamic approach to quantify the flood protection value of beaches.

The study employs a dynamic approach based on the avoided damage cost method, adapted to the specific characteristics of beaches. This approach acknowledges the strong dependence of coastal flood protection on shoreline response to coastal dynamics. It couples shoreline evolution and flooding processes at different time scales to evaluate how shoreline changes affect total water level (TWL) and inland flood propagation. The methodology accounts for the influence of shoreface geometry and terrain heights. Uncertainty sampling is incorporated to accommodate decisions in diverse contexts, time horizons, risk levels, and uncertainty tolerances. The Narrabeen-Collaroy beach system in Australia is used as a case study due to its extensive study and data availability. Flooding scenarios are constructed for the present-day 30-year return period storm combined with AR6 SLR projections for 2050 and 2100. Process-based models downscale offshore waves, compute storm hydro- and morphodynamics, and propagate flooding inland, updating the topo-bathymetry to incorporate SLR and storm effects. Flood damage is quantified by combining flood maps with spatially distributed land and building value data. A dynamic approach, considering erosion, is compared with a traditional static approach, assuming a fixed coastline. The beach flood protected area is defined as the increase in flooded area due to erosion, and its value represents avoided flood damage. Uncertainty is considered in emissions scenarios (SSP2-4.5 and SSP5-8.5), SLR projections (medium and low confidence), and SLR trajectories (5th, 50th, and 95th percentiles). The trade-off between benefits and nourishment costs of maintaining current beach width is also assessed. The study utilizes several models: GOW for offshore wave conditions, Sydney Port Jackson tide gauge and TPXO7.2 for storm surges and astronomical tides, NSW Marine LiDAR Topo-Bathy 2018 for topo-bathymetric data, SWAN for nearshore wave downscaling, ShoreTrans for long-term topo-bathymetry updates, XBeach for surf-zone storm modeling, and RFSM-EDA for coastal flood modeling. Land and building values are obtained from the NSW Office of the Valuer General and real estate websites. Recreational value is assessed using data from the Sydney Beaches Valuation Project, employing the travel cost method. A benefit-cost analysis compares flood protection and recreational benefits with beach nourishment costs. Variance partitioning analysis disentangles the contributions of SSPs, SLR percentiles, and modeling approaches to the uncertainty in TWL, flooded area, and flood damage.

The analysis reveals the significant role of beaches in protecting coastal assets. The interaction between storm hydrodynamics and morphodynamics leads to an eroded shoreface and attenuated wave contribution to TWL. Storm erosion can reduce TWL, but this effect is less pronounced with high SLR percentiles and low-confidence scenarios. SLR raises profiles, leading to TWL changes due to profile geometry rather than foreshore slope changes. The flooded area is influenced by beach condition at the time of storm impact. For storm conditions, SLR has a greater impact than storm erosion on the flooded area. In post-storm conditions, cumulative erosion from consecutive storms becomes more significant. Flood damage is highly sensitive to the interaction of erosion and SLR. The static approach underestimates flood damage by 60–100% by 2100, reaching 7–34 million AUD in 2050 and 553–880 million AUD in 2100. Variance partitioning analysis shows that the modeling approach (considering erosion) is a major source of uncertainty for TWL, flooded area, and flood damage, particularly in post-storm conditions. The flood protection value, or avoided flood damage, is substantial. Maintaining the present-day shoreline avoids 1–7 million AUD in 2050 and 22–456 million AUD in 2100, reaching up to 785 million AUD in post-storm conditions. Recreational benefits, calculated using the avoided loss of recreation, are significant as well, ranging from 65–596 million AUD in 2050 and 355–2120 million AUD in 2100. Benefit-cost analysis shows a high benefit-cost ratio (65–160 in 2050 and 75–230 in 2100), largely driven by recreational benefits. Nourishment is cost-effective in most scenarios, with avoided flood damage potentially exceeding nourishment costs by a factor of 4.5 in 2050 and 50 in 2100. Beaches exhibit resilience, recovering from storm erosion during calm periods, unless storm clusters exceed their resilience threshold. SLR reduces beach resilience by lowering the return period of storms.

The findings demonstrate that beaches provide substantial flood protection benefits that are likely to increase in the future. The process-based analysis quantifies the economic value of beaches and identifies scenarios where erosion, due to the combined effects of SLR and storminess, causes the greatest flood impact. Understanding beach resilience, buffer zones for landward translation, and the timing of beach decline that increases flood damage is crucial for successful and cost-efficient adaptation. The study highlights the importance of dynamic approaches that model beach adjustments at different time scales, capturing potential tipping points that can amplify known impacts or create new conditions. Future research should investigate the effects of changing storm properties, asset vulnerability, and the influence of adaptation interventions like beach nourishment on land-use markets and coastal development. A comprehensive benefit-cost analysis should consider additional ecosystem services, long-term effects, ancillary costs, and various adaptation policies.

This study presents a novel approach for quantifying the economic value of beaches for flood protection. The results highlight the significant and increasing value of beaches as natural coastal defenses, emphasizing the importance of incorporating erosion dynamics in coastal flood modeling and adaptation planning. A realistic valuation of beach benefits can support informed land use and management decisions, accelerating the adoption of financial instruments for beach restoration and conservation. Future work could extend the analysis to other coastal environments and incorporate more detailed assessments of asset values, vulnerabilities, and the impacts of future climate change.

The study uses a single case study in Narrabeen-Collaroy, Australia. While the methodology is replicable, the findings may not generalize perfectly to all coastal environments. The study assumes constant asset values and vulnerability functions in the future, which may not always hold true. The benefit-cost analysis simplifies storm effects to TWL dynamics and only considers SLR erosion for nourishment cost estimation, potentially underestimating the full impact of storms. The recreational value assessment relies on existing data from the Sydney Beaches Valuation Project and may not fully capture all aspects of recreational benefits.