Sediment Trend Analysis (STA<sup>®</sup>): Kinematic<i>vs</i>. Dynamic Modeling

McLaren, Patrick

doi:10.2112/jcoastres-d-13-00121.1

“…When we only consider the premise of pricing and user's demand are inversely proportional relationship, the respective demand of users' can be found out by using Equation (1). The sum of four values is the total demand of users' and users' total demand is divided respectively by demand of each port to find out their market share (McLaren, 2014). Then by knowing their equalization charging and user's demand, we can find out the equilibrium revenue by using Equation (2).…”

Section: The Results Of Simulation and Analysismentioning

confidence: 99%

Game Theory Analysis of Container Port Alliance

Xu

¹

,

Lu

²

,

Ding

³

et al. 2015

Journal of Coastal Research

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“…Sediment tracer studies (both artificial, Black et al., 2007; Bosnic et al., 2017; Elias et al., 2011, and natural, Hein et al., 2013; McGann et al., 2013; Reimann et al., 2015; Rosenbauer et al., 2013; Wong et al., 2013) offer a Lagrangian technique for identifying pathways but are challenging to execute and recover (Elias et al., 2011). Grain trend analysis (Duc et al., 2016; Gao & Collins, 1991; Le Roux & Rojas, 2007; McLaren, 2013; McLaren & Bowles, 1985; McLaren et al., 1998; Poizot et al., 2006, 2008; Velegrakis et al., 2007) and analysis of bedform asymmetry (Barnard, Erikson, et al, 2013; Bartholdy et al., 2002; Sha, 1989; Velegrakis et al., 2007) offer additional techniques for identifying sediment pathways. However, field measurements alone are generally too limited to quantify sediment connections on the timescales of typical interest for engineering and policy decisions.…”

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.

show abstract

“…Sediment tracer studies (both artificial, Black et al, 2007;Bosnic et al, 2017;Elias et al, 2011, andnatural, Hein et al, 2013;McGann et al, 2013;Reimann et al, 2015;Rosenbauer et al, 2013;Wong et al, 2013) offer a Lagrangian technique for identifying pathways but are challenging to execute and recover (Elias et al, 2011). Grain trend analysis (Duc et al, 2016;Gao & Collins, 1991;Le Roux & Rojas, 2007;McLaren, 2013;McLaren & Bowles, 1985;McLaren et al, 1998;Poizot et al, 2006Poizot et al, , 2008Velegrakis et al, 2007) and analysis of bedform asymmetry Bartholdy et al, 2002;Sha, 1989;Velegrakis et al, 2007) offer additional techniques for identifying sediment pathways. However, field measurements alone are generally too limited to quantify sediment connections on the timescales of typical interest for engineering and policy decisions.…”

Section: Developing a Networkmentioning

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.

show abstract

Sediment Trend Analysis (STA^®): Kinematicvs. Dynamic Modeling

Cited by 11 publications

References 72 publications

Game Theory Analysis of Container Port Alliance

Game Theory Analysis of Container Port Alliance

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

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Sediment Trend Analysis (STA®): Kinematicvs. Dynamic Modeling

Cited by 11 publications

References 72 publications

Game Theory Analysis of Container Port Alliance

Game Theory Analysis of Container Port Alliance

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

Sediment Connectivity: A Framework for Analyzing Coastal Sediment Transport Pathways

Contact Info

Product

Resources

About

Sediment Trend Analysis (STA^®): Kinematicvs. Dynamic Modeling