Shoreline change is driven by various complex processes interacting at a large range of temporal and spatial scales, making shoreline reconstructions and predictions challenging and uncertain. Despite recent progress in addressing uncertainties related to the physics of sea‐level rise, very little effort is made towards understanding and reducing the uncertainties related to wave‐driven shoreline response. To fill this gap, the uncertainties associated with the long‐term modelling of shoreline change are analysed at a high‐energy cross‐shore transport dominated site. Using the state‐of‐the‐art LX‐Shore shoreline change model, we produce a probabilistic shoreline reconstruction, based on 3000 simulations over the past 20 years at Truc Vert beach, southwest France, whereby sea‐level rise rate, depth of closure and three model free parameters are considered uncertain variables. We further address the relative impact of each source of uncertainty on the model results performing a Global Sensitivity Analysis. This analysis shows that the shoreline changes are mainly sensitive to the three parameters of the wave‐driven model, but also that the sensitivity to each of these parameters is strongly modulated seasonally and interannually, in relation with wave energy variability, and depends on the time scale of interest. These results have strong implications on the model skill sensitivity to the calibration period as well as for the predictive skill of the model in a context of future climate change affecting wave climate and extremes. © 2020 John Wiley & Sons, Ltd.

Ongoing climate change is one of the largest concerns of our time, and its largest impacts on the world's environment are yet to come. Global mean sea-level rise is accelerating since 1870, and is expected to continue rising over the 21st century, although acceleration may be avoided if the Paris Agreement "below 2°C climate warming" target is met (Church et al., 2013;Oppenheimer et al., 2019). In addition, global wave power is adapting to the sea surface temperature since the late 1940s (Reguero et al., 2019), and is expected to change along with storminess by 2100 (Morim et al., 2020).Sandy beaches provide precious natural, structural and social-economical resources to coastal communities (Ghermandi & Nunes, 2013;Poumadère et al., 2015), and constitute about one third of the ice-free coasts worldwide (Luijendijk et al., 2018). Open sandy beaches constantly evolve in response to multiple environmental drivers occurring on different time scales, making sandy shoreline dynamics strongly sensitive to sea-level rise and wave climate change (Ranasinghe, 2016(Ranasinghe, , 2020. Meanwhile, the expected growth of population density in low-lying coastal areas during the twenty-first century (Merkens et al., 2016;Neuman et al., 2015) increases the need for efficient adaptation plans of coastal communities (Oppenheimer et al., 2019).The spatial heterogeneity of sea-level rise (SLR), wave-climate change, time scales of adaptation, and vulnerability of coastal communities raises the need for shoreline projections with their related uncertainties that provide full support to risk-informed decision making process (