Sandy beaches can survive sea-level rise

Cooper, J. Andrew G.; Masselink, Gerd; Coco, Giovanni; Short, Andrew D.; Castelle, Bruno; Rogers, Kerrylee; Anthony, Edward J.; Green, A. N.; Kelley, Joseph T.; Pilkey, Orrin H.; Jackson, Derek W.T.

doi:10.1038/s41558-020-00934-2

Cited by 149 publications

(94 citation statements)

References 13 publications

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“…1995; Lampe et al, 2007;Zhang et al, 2010;Tõnisson et al, 2013a;Furmanczyk and Musielak, 2015;Deng et al, 2019). Barrier coasts are generally resilient to changing climate and can maintain their morphology provided that there is a neutral or positive sediment budget (Zhang et al, 2014) and beach migration is unimpeded (Cooper et al, 2020). The foredunes form a natural barrier for coastal protection along a major part of the southern Baltic coast.…”

Section: )mentioning

confidence: 99%

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Sea Level Dynamics and Coastal Erosion in the Baltic Sea Region

Weisse¹,

Dailidienė²,

Hünicke³

et al. 2021

Preprint

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Abstract. There are a large number of geophysical processes affecting sea level dynamics and coastal erosion in the Baltic Sea region. These processes operate on a large range of spatial and temporal scales and are observed in many other coastal regions worldwide. Together with the outstanding number of long data records, this makes the Baltic Sea a unique laboratory for advancing our knowledge on interactions between processes steering sea level and erosion in a climate change context. Processes contributing to sea level dynamics and coastal erosion in the Baltic Sea include the still ongoing visco-elastic response of the Earth to the last deglaciation, contributions from global and North Atlantic mean sea level changes, or from wind waves affecting erosion and sediment transport along the subsiding southern Baltic Sea coast. Other examples are storm surges, seiches, or meteotsunamis contributing primarily to sea level extremes. All such processes have undergone considerable variations and changes in the past. For example, over the past about 50 years, the Baltic absolute (geocentric) mean sea level rose at a rate slightly larger than the global average. In the northern parts, due to vertical land movements, relative sea level decreased. Sea level extremes are strongly linked to variability and changes in the large-scale atmospheric circulation. Patterns and mechanisms contributing to erosion and accretion strongly depend on hydrodynamic conditions and their variability. For large parts of the sedimentary shores of the Baltic Sea, the wave climate and the angle at which the waves approach the nearshore are the dominant factors, and coastline changes are highly sensitive to even small variations in these driving forces. Consequently, processes contributing to Baltic sea level dynamics and coastline change are expected to vary and to change in the future leaving their imprint on future Baltic sea level and coastline change and variability. Because of the large number of contributing processes, their relevance for understanding global figures, and the outstanding data availability, we argue that global sea level research and research on coastline changes may greatly benefit from research undertaken in the Baltic Sea.

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Section: )mentioning

confidence: 99%

“…Simple approximations such as Bruun's rule are continuously applied (e.g. Vousdoukas et al, 2020) despite being widely criticized (Cooper and Pilkey, 2004;Le Cozannet et al, 2016;Cooper et al, 2020).…”

Section: Coastline Changes and Erosionmentioning

confidence: 99%

Sea Level Dynamics and Coastal Erosion in the Baltic Sea Region

Weisse¹,

Dailidienė²,

Hünicke³

et al. 2021

Preprint

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“…This situation is projected to worsen with climate change (Ranasinghe, 2016;Vousdoukas et al, 2020). Yet, future coastal retreat projections are highly uncertain, reflecting the deep uncertainties of future sea level rise projections and of coastal impact models (Le Cozannet et al, 2019a;Athanasiou et al, 2020;Ranasinghe, 2020;Cooper et al, 2020;Vershuur et al, 2020). An improved understanding and a better quantification of these sources of uncertainty are required to improve coastal risk management and inform adaptation decisions (Stephens et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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

Thiéblemont¹,

Cozannet

Rohmer

et al. 2021

Nat. Hazards Earth Syst. Sci.

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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.

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“…Reliable long-term 3D data would help improve geomorphic predictions such as shoreline variation models [4,5], and would Remote Sens. 2021, 13, 95 2 of 22 help establish trends for dune erosion or changes of beach configuration [6,7], particularly under rising sea level rise scenarios [8]. Coastal change models are normally based on simplified hydrodynamic assumptions that attempt to present broad-scale global shoreline movement patterns [9] or are tested using synthetic scenarios that are specifically designed to emulate the large range of natural sandy shoreline behaviour [10].…”

Section: Introductionmentioning

confidence: 99%

“…As argued by [12], one of the main reasons why geomorphological models struggle to reproduce real-world behaviour in coastal settings is the predominance of short-term observations, which fail to understand the full character of longer-term morphological evolution, and therefore cannot fully quantify the main driving phenomena and constraints on coastal change [13]. Models accounting for more accurate long-term predictions of coastal change would, therefore, be useful, especially for site-specific cases where long-term 3D data are usually scarce [8].…”

Section: Introductionmentioning

confidence: 99%

Structure-from-Motion-Derived Digital Surface Models from Historical Aerial Photographs: A New 3D Application for Coastal Dune Monitoring

et al. 2020

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Recent advances in structure-from-motion (SfM) techniques have proliferated the use of unmanned aerial vehicles (UAVs) in the monitoring of coastal landform changes, particularly when applied in the reconstruction of 3D surface models from historical aerial photographs. Here, we explore a number of depth map filtering and point cloud cleaning methods using the commercial software Agisoft Metashape Pro to determine the optimal methodology to build reliable digital surface models (DSMs). Twelve different aerial photography-derived DSMs are validated and compared against light detection and ranging (LiDAR)- and UAV-derived DSMs of a vegetated coastal dune system that has undergone several decades of coastline retreat. The different studied methods showed an average vertical error (root mean square error, RMSE) of approximately 1 m, with the best method resulting in an error value of 0.93 m. In our case, the best method resulted from the removal of confidence values in the range of 0–3 from the dense point cloud (DPC), with no filter applied to the depth maps. Differences among the methods examined were associated with the reconstruction of the dune slipface. The application of the modern SfM methodology to the analysis of historical aerial (vertical) photography is a novel (and reliable) new approach that can be used to better quantify coastal dune volume changes. DSMs derived from suitable historical aerial photographs, therefore, represent dependable sources of 3D data that can be used to better analyse long-term geomorphic changes in coastal dune areas that have undergone retreat.

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Sandy beaches can survive sea-level rise

Cited by 149 publications

References 13 publications

Sea Level Dynamics and Coastal Erosion in the Baltic Sea Region

Sea Level Dynamics and Coastal Erosion in the Baltic Sea Region

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

Structure-from-Motion-Derived Digital Surface Models from Historical Aerial Photographs: A New 3D Application for Coastal Dune Monitoring

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