Efficacy of Nature-based Solutions for coastal protection under a changing climate: A modelling approach

Abstract

Nature-based Solutions (NbS) are emerging as sustainable alternatives to conventional coastal defences against flooding and erosion. However, modelling applications to assess their efficacy often employ deterministic approaches based on historical storms, seldom incorporating effects of climate change. We argue that assessing coastal NbS performance for current and future scenarios is essential to ensure their long-term efficacy, adaptability, and potential synergies with climate adaptation and mitigation strategies. To this aim, we propose a modelling framework to investigate effectiveness of Nature-based coastal defences to mitigate climate change-driven, storm-induced flooding and erosion. An hydro-morphodynamic modelling chain (SWAN and XBeach) is setup to evaluate the effectiveness of two interventions — a dune revegetation and a seagrass meadow reconstruction — in reducing coastal inundation and shoreline retreat. The study investigates present and future what-if scenarios, by simulating storm conditions based on present, 4.5, and 8.5 W/m² radiative forcing scenarios. Dissipative effects of vegetation are modelled by providing their characteristics and spatial distribution through habitat maps. Simple flooding and erosion reduction efficacy indicators are computed to support the assessment. The approach is applied to a case study along the Sicily coast (Italy). Results reveal that the vulnerability of the area to flooding is predominantly driven by sea level rise rather than by increase in significant wave height. In this regard, both considered interventions effectively reduce flooded areas across all investigated scenarios up to 66%, while the reconstruction of the seagrass meadow also significantly reduces storm-driven eroded volumes. Its efficacy however is less significant under 2100-time horizon scenarios, underscoring the need for NbS strategies that may be flexible and responsive to changing climate conditions.