Future Response of the Wadden Sea Tidal Basins to Relative Sea-Level rise—An Aggregated Modelling Approach

Lodder, Quirijn; Wang, Zheng Bing; Elias, Edwin; Spek, A.J.F. van der; Looff, Harry de; Townend, Ian

doi:10.3390/w11102198

“…The shift of tidal asymmetry depends on these two competing effects (Friedrichs et al, 1990). The comparable magnitude of these two effects can result in the relative insensitivity of tidal asymmetry to SLR in the Ria de Aveiro lagoon (Lopes and Dias, 2015) and to deepening in the Western Scheldt . The SLR-induced shift to ebb dominance in the Oosterschelde implies a stronger reduction in a/ h than V s /V c .…”

Section: Discussionmentioning

confidence: 99%

“…However, projecting the geomorphic adaptation under SLR is challenging given the uncertainties in the future meteorological forcing, marine and fluvial sediment sources, and grain size distribution (Ganju and Schoellhamer, 2010;Elmilady et al, 2019). The SLR rate, as well as its pace relative to the basin morphodynamic response, is also critical to the morphological development (Zhou et al, 2013;Lodder et al, 2019). In addition to the natural development of bed morphology, future anthropogenic activities such as dredging may change the regional bathymetry in estuaries and bays (Ralston et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Effects of sea-level rise on tides and sediment dynamics in a Dutch tidal bay

Jiang

¹

,

Gerkema

²

,

Idier

³

et al. 2020

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Sea-level rise (SLR) not only increases the threat of coastal flooding, but may also change tidal regimes in estuaries and coastal bays. To investigate such nearshore tidal responses to SLR, a hydrodynamic model of the European Shelf is downscaled to a model of a Dutch coastal bay (the Oosterschelde, i.e., Eastern Scheldt) and forced by SLR scenarios ranging from 0 to 2 m. This way, the effect of SLR on tidal dynamics in the adjacent North Sea is taken into account as well. The model setup does not include meteorological forcing, gravitational circulation, and changes in bottom topography. Our results indicate that SLR up to 2 m induces larger increases in tidal amplitude and stronger nonlinear tidal distortion in the bay compared to the adjacent shelf sea. Under SLR up to 2 m, the bay shifts from a mixed floodand ebb-dominant state to complete ebb dominance. We also find that tidal asymmetry affects an important component of sediment transport. Considering sand bed-load transport only, the changed tidal asymmetry may lead to enhanced export, with potential implications for shoreline management. In this case study, we find that local impacts of SLR can be highly spatially varying and nonlinear. The model coupling approach applied here is suggested as a useful tool for establishing local SLR projections in estuaries and coastal bays elsewhere. Future studies should include how SLR changes the bed morphology as well as the feedback effect on tides.

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“…Known sources and sinks of sediment (e.g., sea cliffs or submarine canyons) or criteria like depth, sediment transport patterns, or morphological characteristics can be used to define these cells (e.g., Jeuken & Wang, 2010; Lodder et al., 2019; Stive et al., 1998; Stive & Wang, 2003). Geomorphic cells can also be defined without any reference to their function or position.…”

Section: Methodsmentioning

confidence: 99%

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

Pearson

¹

,

Prooijen

²

,

Elias

³

et al. 2020

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Connectivity provides a framework for analyzing coastal sediment transport pathways, building on conceptual advances in graph theory from other scientific disciplines. Connectivity schematizes sediment pathways as a directed graph (i.e., a set of nodes and links). This study presents a novel application of graph theory and connectivity metrics like modularity and centrality to coastal sediment dynamics, exemplified here using Ameland Inlet in the Netherlands. We divide the study site into geomorphic cells (i.e., nodes) and then quantify sediment transport between these cells (i.e., links) using a numerical model. The system of cells and fluxes between them is then schematized in a network described by an adjacency matrix. Network metrics like link density, asymmetry, and modularity quantify system-wide connectivity. The degree, strength, and centrality of individual nodes identify key locations and pathways throughout the system. For instance, these metrics indicate that under strictly tidal forcing, sand originating near shore predominantly bypasses Ameland Inlet via the inlet channels, whereas sand on the deeper foreshore mainly bypasses the inlet via the outer delta shoals. Connectivity analysis can also inform practical management decisions about where to place sand nourishments, the fate of nourishment sand, or how to monitor locations vulnerable to perturbations. There are still open challenges associated with quantifying connectivity at varying space and time scales and the development of connectivity metrics specific to coastal systems. Nonetheless, connectivity provides a promising technique for predicting the response of our coasts to climate change and the human adaptations it provokes. Plain Language Summary The pathways that sand takes as it moves along coasts and estuaries are determined by a complex combination of waves, tides, geology, and other environmental or human factors. These pathways can be challenging to analyze and predict using existing approaches, so we turn to the concept of connectivity. Connectivity represents the pathways that sediment takes as a series of nodes and links, much like in a subway or metro map. This approach is well used in other scientific fields, but in this study we apply these techniques to a new research field: coastal sediment dynamics. To demonstrate the sediment connectivity approach, we use it to map sediment pathways at a coastal site in the Netherlands. The statistics computed using connectivity let us quantify and visualize these sediment pathways, revealing new insights into the coastal system. We can also use this approach to address practical engineering questions, such as where to place sand nourishments for coastal protection. Sediment connectivity thus provides a promising technique for predicting the response of our coasts to climate change and the human adaptations it provokes.

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“…Known sources and sinks of sediment (e.g., sea cliffs or submarine canyons) or criteria like depth, sediment transport patterns, or morphological characteristics can be used to define these cells (e.g., Jeuken & Wang, 2010;Lodder et al, 2019;Stive et al, 1998;Stive & Wang, 2003). Geomorphic cells can also be defined without any reference to their function or position.…”

Section: Methodsmentioning

confidence: 99%

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

Pearson

¹

,

Prooijen

²

,

Elias

³

et al. 2020

Preprint

View full text Add to dashboard Cite

Connectivity provides a framework for analyzing coastal sediment transport pathways, building on conceptual advances in graph theory from other scientific disciplines. Connectivity schematizes sediment pathways as a directed graph (i.e., a set of nodes and links). This study presents a novel application of graph theory and connectivity metrics like modularity and centrality to coastal sediment dynamics, exemplified here using Ameland Inlet in the Netherlands. We divide the study site into geomorphic cells (i.e., nodes) and then quantify sediment transport between these cells (i.e., links) using a numerical model. The system of cells and fluxes between them is then schematized in a network described by an adjacency matrix. Network metrics like link density, asymmetry, and modularity quantify system-wide connectivity. The degree, strength, and centrality of individual nodes identify key locations and pathways throughout the system. For instance, these metrics indicate that under strictly tidal forcing, sand originating near shore predominantly bypasses Ameland Inlet via the inlet channels, whereas sand on the deeper foreshore mainly bypasses the inlet via the outer delta shoals. Connectivity analysis can also inform practical management decisions about where to place sand nourishments, the fate of nourishment sand, or how to monitor locations vulnerable to perturbations. There are still open challenges associated with quantifying connectivity at varying space and time scales and the development of connectivity metrics specific to coastal systems. Nonetheless, connectivity provides a promising technique for predicting the response of our coasts to climate change and the human adaptations it provokes. Plain Language Summary The pathways that sand takes as it moves along coasts and estuaries are determined by a complex combination of waves, tides, geology, and other environmental or human factors. These pathways can be challenging to analyze and predict using existing approaches, so we turn to the concept of connectivity. Connectivity represents the pathways that sediment takes as a series of nodes and links, much like in a subway or metro map. This approach is well used in other scientific fields, but in this study we apply these techniques to a new research field: coastal sediment dynamics. To demonstrate the sediment connectivity approach, we use it to map sediment pathways at a coastal site in the Netherlands. The statistics computed using connectivity let us quantify and visualize these sediment pathways, revealing new insights into the coastal system. We can also use this approach to address practical engineering questions, such as where to place sand nourishments for coastal protection. Sediment connectivity thus provides a promising technique for predicting the response of our coasts to climate change and the human adaptations it provokes.

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Future Response of the Wadden Sea Tidal Basins to Relative Sea-Level rise—An Aggregated Modelling Approach

Cited by 30 publications

References 64 publications

Effects of sea-level rise on tides and sediment dynamics in a Dutch tidal bay

Effects of sea-level rise on tides and sediment dynamics in a Dutch tidal bay

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

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