Simple Pocket Beach Rotation Model Derived From Linear Analysis

Blossier, Brice; Bryan, Karin R

doi:10.1142/9789814689977_0032

Cited by 6 publications

(6 citation statements)

References 17 publications

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“…Under steady wave conditions (incident wave energy E 0 and wave angle θ 0 ), equilibrium orientations α eq, s and α eq, b can be inferred from equations and for the shoreline and barline, respectively:

α_{eq, s} = θ_{0},

α_{eq, b} = α_{eq} + \frac{1}{δ_{b} a_{b}} \frac{\partial E_{0}}{∂x},

These two quantities are represented in Figure a with their corresponding incident wave energy. While α eq, s relates directly to the wave angle of incidence, in agreement with Turki et al [, ] and Blossier et al [], α eq, b relates to the alongshore wave energy gradient, in agreement with Bryan et al [] and Blossier et al [].…”

Section: Discussionsupporting

confidence: 82%

“…The second model describes the rotation of the shoreline, and its formulation is based on the results of a statistical linear analysis [Blossier et al, 2015] showing a clear relationship between the shoreline rotation rate and the amount of wave energy available for alongshore sediment transport [Komar and Inman, 1970]. These observations are in agreement with the model of Turki et al [2013b], and therefore, the present shoreline rotation model is a simplified formulation of their model assuming an equilibrium orientation of the beach shoreline perpendicular to the incoming wave direction .…”

Section: C1 Formulationssupporting

confidence: 71%

“…These two quantities are represented in Figure 9a with their corresponding incident wave energy. While eq,s relates directly to the wave angle of incidence, in agreement with Turki et al [2013aTurki et al [ , 2013b and Blossier et al [2015], eq,b relates to the alongshore wave energy gradient, in agreement with Bryan et al [2013] and Blossier et al [2016].…”

Section: Rotationmentioning

confidence: 74%

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Shore and bar cross‐shore migration, rotation, and breathing processes at an embayed beach

2017

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A principal component analysis (PCA) is used to decompose data on the coupled morphodynamics of the shoreline and nearshore sandbar of a typical single‐barred embayed beach (Tairua Beach, New Zealand). Dynamic patterns are classified into simultaneous modes, where the bar and shoreline move at the same time, and nonsimultaneous modes, where the shore moves independently from the bar, and vice versa. Two simultaneous modes accounting for 65% of the variance of the shoreline and barline dominate the system. One mode describes inverse shoreline and sandbar cross‐shore migrations (alongshore averaged), occurring with simultaneous rotations in the same direction. The other mode accounts for migration in the same direction accompanied by variations of the barline curvature (similar to “breathing modes” previously described in embayed beach shoreline modeling studies). Two nonsimultaneous modes of lesser importance account separately for independent shoreline and barline rotations (10 to 15% of the variance explained). A PCA applied to the shore and sandbar behaviors modeled by four standard equilibrium models simulating shore and sandbar cross‐shore migrations and rotations show that these are interrelated because of a correlation between wave energy and direction. Shore and bar rotations are coupled partially because the shape of the bay induces a correlation of their respective drivers, the wave angle of incidence and the alongshore gradient of wave energy. However, this correlation depends on the wave energy. This, in combination with different shore and sandbar response times (quantified using the models), also explains the independent rotations reflected by the nonsimultaneous modes.

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α_{eq, s} = θ_{0},

α_{eq, b} = α_{eq} + \frac{1}{δ_{b} a_{b}} \frac{\partial E_{0}}{∂x},

Section: Discussionsupporting

confidence: 82%

Section: C1 Formulationssupporting

confidence: 71%

Section: Rotationmentioning

confidence: 74%

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Shore and bar cross‐shore migration, rotation, and breathing processes at an embayed beach

2017

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“…Questions arise about the appropriateness of linear models, considering that shorelines do not recede or accrete uniformly (Douglas and Crowell, 2000;Thieler and Danforth, 1994a, b). As an example, coastal embayments featured by a parabolic curve, which are representative of more than 50 % of the world's coastlines, are very dynamic environments where the shoreline position can fluctuate significantly due to processes such as beach rotation (Armenio et al, 2017b;Short and Trembanis, 2004;Blossier et al, 2015). This can be defined as the landward or seaward movement at one end of the beach accompanied by the reverse pattern at the other end (Bryan et al, 2013) and is often a consequence of maritime constructions (i.e., dikes, breakwaters) and variations in river sediment supply on flanking beaches.…”

Section: Introductionmentioning

confidence: 99%

Coastline evolution based on statistical analysis and modeling

Armenio

Serio

Mossa

et al. 2019

Nat. Hazards Earth Syst. Sci.

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Abstract. Wind, waves, tides, sediment supply, changes in relative sea level and human activities strongly affect shorelines, which constantly move in response to these processes, over a variety of timescales. Thus, the implementation of sound coastal zone management strategies needs reliable information on erosion and/or deposition processes. To suggest a feasible way to provide this information is the main reason for this work. A chain approach is proposed here, tested on a vulnerable coastal site located along southern Italy, and based on the joint analysis of field data, statistical tools and numerical modeling. Firstly, the coastline morphology has been examined through interannual field data, such as aerial photographs, plane-bathymetric surveys and seabed characterization. After this, rates of shoreline changes have been quantified with a specific GIS tool. The correlations among the historical positions of the shoreline have been detected by statistical analysis and have been satisfactorily confirmed by numerical modeling, in terms of recurrent erosion–accretion area and beach rotation trends. Finally, based on field topographic, sediment, wave and wind data, the response of the beach through numerical simulation has been investigated in a forecasting perspective. The purpose of this study is to provide a feasible, general and replicable chain approach, which could help to thoroughly understand the dynamics of a coastal system, identify typical and recurrent erosion–accretion processes, and predict possible future trends, useful for planning of coastal activities.

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“…Questions raise about the appropriateness of linear models, considering that shorelines do not recede or accrete in a uniform manner (Douglas et al, 2000, Thieler et al, 1994a, 1994b. As an example, coastal embayments featured by a parabolic curve, which are representative of more than 50% of the world's coastlines, are very dynamic environments where the shoreline position can fluctuate significantly due to processes such as beach rotation (Short et al, 2004;Blossier et al, 2015). This can be defined as the landward or seaward movement at one end of the beach accompanied by the reverse pattern at the other end (Bryan et al, 2013) and is often a consequence of maritime constructions (i.e.…”

mentioning

confidence: 99%

Coastline evolution based on statistical analysis and modelling

Armenio¹,

Serio²,

Mossa³

et al. 2018

Preprint

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Abstract. Wind, waves, tides, sediment supply, changes in relative sea level and human activities strongly affect shorelines, which constantly move in response to these processes, over a variety of time scales. Thus, the implementation of sound coastal zone management strategies needs reliable information on erosion and/or deposition processes. Suggesting a feasible way to provide such information is the main motivation of the present work. A chain approach is here proposed, tested on a vulnerable coastal site located along the southern Italy, and based on the joint analysis of field data, statistical tools and numerical modelling. Firstly, the coastline morphology has been examined through interannual field data, such as aerial photographs, plane-bathymetric surveys, seabed characterization. After this, rates of shoreline changes have been quantified with a specific GIS tool. Correlations among the historical shoreline positions have been detected by statistical analysis and have been satisfactorily confirmed by numerical modelling, in terms of recurrent erosion/accretion area and beach rotation trends. Finally, based on field topographic, sediment, wave and wind data, the response of the beach by the numerical simulation has been investigated in a forecasting perspective. The scope of this study is providing a feasible, general and replicable chain approach, which could help to thoroughly understand the dynamics of a coastal system, identifying typical and recurrent erosion/accretion processes, and predict possible future trends, useful for planning coastal activities.

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Simple Pocket Beach Rotation Model Derived From Linear Analysis

Cited by 6 publications

References 17 publications

Shore and bar cross‐shore migration, rotation, and breathing processes at an embayed beach

Shore and bar cross‐shore migration, rotation, and breathing processes at an embayed beach

Coastline evolution based on statistical analysis and modeling

Coastline evolution based on statistical analysis and modelling

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