Deep uncertainties in shoreline change projections: an extra-probabilistic approach applied to sandy beaches

Abstract

Abstract. Global mean sea level rise and its acceleration are projected to aggravate coastal erosion over the 21st century, which constitutes a major challenge for coastal adaptation. Projections of shoreline retreat are highly uncertain, however, namely due to deeply uncertain mean sea level projections and the absence of consensus on a coastal impact model. An improved understanding and a better quantification of these sources of deep uncertainty are hence required to improve coastal risk management and inform adaptation decisions. In this work we present and apply a new extra-probabilistic framework to develop shoreline change projections of sandy coasts that allows consideration of intrinsic (or aleatory) and knowledge-based (or epistemic) uncertainties exhaustively and transparently. This framework builds upon an empirical shoreline change model to which we ascribe possibility functions to represent deeply uncertain variables. The model is applied to two local sites in Aquitaine (France) and Castellón (Spain). First, we validate the framework against historical shoreline observations and then develop shoreline change projections that account for possible (although unlikely) low-end and high-end mean sea level scenarios. Our high-end projections show for instance that shoreline retreats of up to 200 m in Aquitaine and 130 m in Castellón are plausible by 2100, while low-end projections revealed that 58 and 37 m modest shoreline retreats, respectively, are also plausible. Such extended intervals of possible future shoreline changes reflect an ambiguity in the probabilistic description of shoreline change projections, which could be substantially reduced by better constraining sea level rise (SLR) projections and improving coastal impact models. We found for instance that if mean sea level by 2100 does not exceed 1 m, the ambiguity can be reduced by more than 50 %. This could be achieved through an ambitious climate mitigation policy and improved knowledge on ice sheets.

Effects of stochastic wave forcing on probabilistic equilibrium shoreline response across the 21st century including sea-level rise

“…Probabilistic, mostly ensemble-based, approaches have become increasingly popular to study the impact several sources of uncertainties on shoreline predictions. However, most studies focused on the impact of uncertainties in future SLR on shoreline predictions while accounting for probabilistic extrapolated trends of wave-driven shoreline change (Athanasiou et al, 2020;Le Cozannet et al, 2016;Thiéblemont et al, 2021Thiéblemont et al, , 2019Vousdoukas et al, 2020), or resolving ~hourly shoreline response to deterministic realizations of future wave climate (D'Anna et al, 2021a(D'Anna et al, , 2020, and did not include the inherent variability of wave climate.…”

Assessing coastline recession for adaptation planning: sea level rise versus storm erosion

“…0.05) exceedance probabilities (see “ Methods ” for a more detailed description of the model). The model, and its derivatives, have been applied at several locations around the world (Australia, France, Japan, Sri Lanka) 15 – 21 .…”

Future Changes in Built Environment Risk to Coastal Flooding, Permanent Inundation and Coastal Erosion Hazards

“…Erosion of cliffs is a one-way process, but unconsolidated shorelines (beaches) may accrete following periods of erosion. Models of shoreline evolution generally predict long-term shoreline recession with rising mean sea level (MSL) [10][11][12] but the response is complex with many sources of uncertainty including the rate and magnitude of RSLR [4,[12][13][14][15].…”