Modes and emergent time scales of embayed beach dynamics

Ratliff, Katherine; Murray, A. Brad

doi:10.1002/2014gl061680

Cited by 30 publications

(51 citation statements)

References 25 publications

(33 reference statements)

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“…In addition,

M_{2}^{*}

accounts for an overall retreat or progradation of the shoreline and barline system. Moreover, temporal vector

c_{2}^{*}

exhibits interannual fluctuations with time periods of 3 to 4 years, which would agree with the characteristic time scales found by Ratliff and Murray [] for low‐angle wave climate (Figure b). Such climate is found at Tairua, where only 8% of the 7 year simulated waves exceed an angle of incidence of 45°, which could explain the emergence of the similar mode (Figures c and d).…”

Section: Discussionsupporting

confidence: 90%

“…

M_{2}^{*}

also includes curvature variation of the barline (

R_{U}^{2}

, Table ). Ratliff and Murray [] studied the long‐term behavior of embayed beach shorelines by modeling longshore sediment transport between headlands using the model of Ashton et al [] and Ashton and Murray []. They named a new dynamic mode breathing that relates to fluctuations in the curvature of the shoreline , which is not observed here.…”

Section: Discussionmentioning

confidence: 99%

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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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“…In addition,

M_{2}^{*}

accounts for an overall retreat or progradation of the shoreline and barline system. Moreover, temporal vector

c_{2}^{*}

Section: Discussionsupporting

confidence: 90%

“…

M_{2}^{*}

also includes curvature variation of the barline (

R_{U}^{2}

Section: Discussionmentioning

confidence: 99%

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

2017

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“…“Full model” transects are selected for long, sandy beaches, and all model components are included. Small (<1 km), sandy pocket beaches (with limited longshore transport and localized hydrodynamic effects [e.g., Daly et al ., ; Gallop et al ., ; Castelle and Coco , ; van de Lageweg et al ., ; Ratliff and Murray , ; Harley et al ., ]) are designated as “cross‐shore only” by setting K = 0. Cobble beaches and heterogeneous sandy/rocky beaches invalidate the process‐based models used here and, therefore, are designated as “rate only” transects by neglecting longshore and cross‐shore transport due to waves, i.e., setting K = 0 and C = 0.…”

Section: Applicationmentioning

confidence: 99%

A model integrating longshore and cross‐shore processes for predicting long‐term shoreline response to climate change

et al. 2017

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We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS‐COAST (Coastal One‐line Assimilated Simulation Tool), is a transect‐based, one‐line model that predicts short‐term and long‐term shoreline response to climate change in the 21st century. The proposed model represents a novel, modular synthesis of process‐based models of coastline evolution due to longshore and cross‐shore transport by waves and sea level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long‐term predictions. We apply CoSMoS‐COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995–2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model's predictive capability when applied to the forecast period (2010–2100) driven by GCM‐projected wave and sea level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea level rise scenarios of 0.93 to 2.0 m.

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“…Moreover, although the response of sandy beaches to external drivers presents multiple stable states and the effect of storms is amplified or mitigated depending on environmental conditions (29,30), the response of salt marshes is constant across different geographic regions and for different climatic conditions. Our analysis is only valid for salt marshes and might not be applicable to brackish or freshwater intertidal vegetation, which sometimes fail during hurricanes given their weaker root system (20).…”

Section: Significancementioning

confidence: 99%

A linear relationship between wave power and erosion determines salt-marsh resilience to violent storms and hurricanes

Leonardi

Ganju

Fagherazzi

2015

Proc. Natl. Acad. Sci. U.S.A.

231

179

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Salt marsh losses have been documented worldwide because of land use change, wave erosion, and sea-level rise. It is still unclear how resistant salt marshes are to extreme storms and whether they can survive multiple events without collapsing. Based on a large dataset of salt marsh lateral erosion rates collected around the world, here, we determine the general response of salt marsh boundaries to wave action under normal and extreme weather conditions. As wave energy increases, salt marsh response to wind waves remains linear, and there is not a critical threshold in wave energy above which salt marsh erosion drastically accelerates. We apply our general formulation for salt marsh erosion to historical wave climates at eight salt marsh locations affected by hurricanes in the United States. Based on the analysis of two decades of data, we find that violent storms and hurricanes contribute less than 1% to long-term salt marsh erosion rates. In contrast, moderate storms with a return period of 2.5 mo are those causing the most salt marsh deterioration. Therefore, salt marshes seem more susceptible to variations in mean wave energy rather than changes in the extremes. The intrinsic resistance of salt marshes to violent storms and their predictable erosion rates during moderate events should be taken into account by coastal managers in restoration projects and risk management plans.salt marsh | resilience | hurricanes | wind waves | erosion T he potential of salt marshes to serve as natural buffers against violent storms seems even more important in view of significant threats imposed by climate change, such as increased storminess and higher hurricane activity registered in the past decades (1-12). Recent research results show that salt marshes reduce wave energy during storms and possibly, mitigate storm surges (13-15). These results triggered a flurry of planned coastal restorations centered on the concept of "living shorelines" (14), which use vegetated surfaces to reduce the impact of hurricanes (13-16). However, little is known about the endurance of salt marshes against wave action and whether such ecosystems can survive extreme events.Most marsh erosion occurs at its seaward boundary, where the effect of waves is concentrated (2, 3). Wave erosion constitutes one of the main contributions to salt marsh deterioration, and even very small waves can cause failure of large salt marsh blocks (2,7,17). Despite the complexity of the problem, some studies have identified a correlation between wave energy and lateral rates of marsh erosion (18,19). Erosion of marsh edges by wave action is caused by many different mechanisms, such as the indentation of V-shaped notches into linear stretches of shoreline or cliff undercutting when lower sediment layers are eroded more rapidly than the overhanging root mats (2,17,19). Varying resistance to wave erosion can be caused by biotic and abiotic factors, such as geotechnical characteristics of the sediments (7, 20), vegetation characteristics (21), height of the marsh scarp, an...

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Modes and emergent time scales of embayed beach dynamics

Cited by 30 publications

References 25 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

A model integrating longshore and cross‐shore processes for predicting long‐term shoreline response to climate change

A linear relationship between wave power and erosion determines salt-marsh resilience to violent storms and hurricanes

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