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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Sea-level rise and its acceleration are projected to aggravate coastal erosion over the 21st century. Resulting shoreline projections are deeply uncertain, however, which constitutes a major challenge for coastal planning and management. Our work presents a new extra-probabilistic framework to develop future shoreline projections under deep uncertainties and show that deep uncertainties could be drastically reduced by better constraining sea-level projections and improving coastal impact models.
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https://doi.org/10.5194/nhess-2020-412
https://doi.org/10.5194/nhess-2020-412

  13 Jan 2021

13 Jan 2021

Review status: this preprint is currently under review for the journal NHESS.

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

Rémi Thiéblemont1, Gonéri Le Cozannet1, Jérémy Rohmer1, Alexandra Toimil2, Moisés Álvarez-Cuesta2, and Iñigo J. Losada2 Rémi Thiéblemont et al.
  • 1Bureau de Recherches Géologiques et Minières “BRGM”, French Geological Survey, 3 Avenue, Claude Guillemin, CEDEX, 45060 Orléans, France
  • 2IHCantabria-Instituto de Hidráulica Ambiental de la Universidad de Cantabria, Parque Científico y Tecnológico de Cantabria, Calle Isabel Torres 15, 39011 Santander, Cantabria, Spain

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 considering 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 m 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 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.

Rémi Thiéblemont et al.

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Rémi Thiéblemont et al.

Rémi Thiéblemont et al.

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Short summary
Sea-level rise and its acceleration are projected to aggravate coastal erosion over the 21st century. Resulting shoreline projections are deeply uncertain, however, which constitutes a major challenge for coastal planning and management. Our work presents a new extra-probabilistic framework to develop future shoreline projections under deep uncertainties and show that deep uncertainties could be drastically reduced by better constraining sea-level projections and improving coastal impact models.
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