Evolution model of shoreline position on sandy, wave-dominated beaches

Lim, Changbin; Kim, Tae-Kon; Lee, Jung-Lyul

doi:10.1016/j.geomorph.2022.108409

Cited by 7 publications

(9 citation statements)

References 19 publications

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“…Thus, this study derives a mathematical equation for the horizontal behavior of suspended sediments, in a manner similar to the methods already applied to the vertical behavior (Partheniades, 1965;Hanson, 1990;Cook, 1997, 2004). First, assuming that suspended sediment is transported horizontally, the temporal change in the shoreline position where water and land meet at a constant sea level Lim and Lee 10.3389/fmars.2023.1179598 Frontiers in Marine Science frontiersin.org can be expressed as follows (Kim et al, 2021;Lim et al, 2022b):…”

Section: Shoreline Change By Normal Incident Wavementioning

confidence: 99%

“…This model has the advantage of being able to simulate episodic shoreline retreat and recovery under storm wave conditions. Although sea level changes (e.g., wave setup, tides, and sea level rise) are not considered separately in this paper, shoreline changes considering sea level changes can be easily simulated by adding corresponding terms (Lim et al, 2022b). Sea level changes should be taken into account if the shoreline sensitively responds to them due to large tidal differences or mild beach slopes.…”

Section: Shoreline Change By Normal Incident Wavementioning

confidence: 99%

“…The entrainment rate q c E is expressed as a function of the wave energy exerted at the starting point of wave breaking (Kim et al, 2021;Lim et al, 2022b), as follows:…”

Section: Shoreline Change By Normal Incident Wavementioning

confidence: 99%

“…Nevertheless, the CERC (1984) formula cannot explain the complex characteristics of shoreline retreat and recovery by episodic high energy/storm waves (Wright et al, 1985;Miller and Dean, 2004;Yates et al, 2009). Recently, Kim et al (2021) and Lim et al (2022b) drew attention to the repetitive process by which shorelines are rapidly eroded and restored in response to storm events, leading to the concept that suspended sediments behave horizontally, rather than vertically according to wave action. By applying this concept, a shoreline change model was established for a beach dominated by transverse drift, and the model performance for the repetitive incidence of short-term storms was verified through comparison with field observation data.…”

Section: Introductionmentioning

confidence: 99%

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Derivation of governing equation for short-term shoreline response due to episodic storm wave incidence: comparative verification in terms of longshore sediment transport

Lim

Lee

2023

Front. Mar. Sci.

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The shoreline temporarily recedes significantly as incoming storm waves reach the beach and cause wave breaking and energy dissipation. However, since the existing shoreline change model simulates shoreline change based on the longshore sediment transport rate (LSTR) empirical formulae, which are derived using the correlation between energy flux and littoral drift, it is difficult to simulate this phenomenon, which is drafted with transverse drift. Therefore, in this study, by applying the concept of the horizontal behavior of suspended sediments, a set of governing equations were derived that can simulate short-term shoreline changes in which the shoreline temporarily recedes, and then recovers. Among the three variables of the governing equation, the two main physical variables related to transverse drift—the beach response factor and the beach recovery factor—can be obtained from the median grain size. However, in the present study, the third variable, the actual transport speed of littoral drift, was estimated by comparison with the CERC formula and discussed from the point of view of alongshore energy flux and wave duration. This was established by introducing the delay factor of longshore sediment transport (DFLST), which indicates how slowly suspended sediments move relative to the longshore current speed. It was found that the littoral sediment speed is inversely proportional to the square root of the beach scale factor. The LSTR formula derived in this study was compared with the observed LSTR values collected from 25 beaches in the United States and with the results of four existing empirical formulae. The proposed governing equation is expected to be widely used as a means of predicting short-term shoreline changes, unlike existing shoreline change models, because it can consider the temporal shoreline retreat and recovery due to storm wave incidence.

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Section: Shoreline Change By Normal Incident Wavementioning

confidence: 99%

Section: Shoreline Change By Normal Incident Wavementioning

confidence: 99%

“…The entrainment rate q c E is expressed as a function of the wave energy exerted at the starting point of wave breaking (Kim et al, 2021;Lim et al, 2022b), as follows:…”

Section: Shoreline Change By Normal Incident Wavementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Derivation of governing equation for short-term shoreline response due to episodic storm wave incidence: comparative verification in terms of longshore sediment transport

Lim

Lee

2023

Front. Mar. Sci.

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“…Based on the orthogonality hypothesis of the processes that take place on beaches, the EBSEM can be separated according to the predominance of sediment transport direction, cross-shore or longshore, responding only to beach profile movements or beach planform variability. In the literature, there are several EBSEM proposals that only consider cross-shore sediment transport for shoreline displacement (e.g., Castelle et al, 2014;Davidson, Lewis, and Turner, 2010;Davidson, Splinter, and Turner, 2013;Davidson and Turner, 2009;Doria et al, 2016;Jara, González, and Medina, 2015;Jara et al, 2018;Jaramillo et al, 2020;Kriebel and Dean, 1993;Lim, Kim, and Lee, 2022;Long and Plant, 2012;Miller and Dean, 2004;Splinter et al, 2014;Yates, Guza, and O'Reilly, 2009), while there are few proposals for this kind of models related to longshore sediment transport (e.g., Blossier et al, 2017;Jaramillo et al, 2021a;Turki et al, 2013). The EBSEM can also be combined in a simplified way to undertake both cross-shore and longshore processes (e.g., Jaramillo et al, 2021b).…”

Section: Introductionmentioning

confidence: 99%

Equilibrium-Based Shoreline Evolution Models to Predict Coastal Response

Jaramillo,

de Freitas,

González

et al. 2024

Journal of Coastal Research

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A Study on the Influence of Sand Median Grain Size on the Short-Term Recovery Process of Shorelines

Lim

Kim

Kim³

et al. 2022

Front. Mar. Sci.

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Recently, the impacts of short-term erosion caused by storm waves on coastal damages are increasingly recognized as social issues, compared to those of long-term erosion from climate change or coastal development. The erosion caused by the storm wave has an episodic characteristic that the shoreline recovers gradually after retreating for a short-term. Furthermore, if shoreline changes caused by longshore sediment transport are not taken into consideration, the shoreline position is determined by following two physical parameters based on the bulk response model. The beach response factor determines converging ultimate erosion on the assumption that incident waves constantly affects a beach, which can be estimated according to the concept of Dean’s profile. On the contrary, the beach recovery factor affects the velocity of the shoreline retreat and recovery. Therefore, the parameter plays an important role to predict the peak erosion due to the storms. However, there are still insufficient researches to utilize it as an engineering design for erosion reduction. In this study, the two methodologies (i.e., approximation formula and statistical analysis) that estimates peak erosion width caused by the storms are compared to extract the beach recovery factor. During the process, it is confirmed that peak wave height has little impact on the beach recovery factor. Instead, it is mainly determined by the median grain size. Also, the beach recovery factor is estimated as a function of median grain size based on the shoreline and sand survey data conducted over ten years. Among the 41 surveyed sites along the east coast, 11 sites of straight-type shorelines that directly react to the incident waves were applied to consider only the short-term recovery process. To prove validity, the estimated applied into the real sea and then the results were compared to the shoreline data extracted from CCTV images. Using these results, the peak erosion width for a target wave event can be predicted with only median grain size. These study results are expected to be used as a concrete and practical means to manage the coast, in preparation for the current and future shoreline erosion threats.

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Evolution model of shoreline position on sandy, wave-dominated beaches

Cited by 7 publications

References 19 publications

Derivation of governing equation for short-term shoreline response due to episodic storm wave incidence: comparative verification in terms of longshore sediment transport

Derivation of governing equation for short-term shoreline response due to episodic storm wave incidence: comparative verification in terms of longshore sediment transport

Equilibrium-Based Shoreline Evolution Models to Predict Coastal Response

A Study on the Influence of Sand Median Grain Size on the Short-Term Recovery Process of Shorelines

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