Environmental Controls on Littoral Sand Transport

Komar, Paul D.

doi:10.1061/9780872626874.093

Cited by 10 publications

(18 citation statements)

References 13 publications

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“…Figure 3 shows data relating the CERC K term to sediment grain size. It includes the field studies listed in Komar (1988), plus the gravel and shingle transport studies of Nicholls and Webber (1987), Chadwick (1989), and Nicholls and Wright (1991) from England, and Leidersdorf et al (1988) from Alaska. Though there is a clear trend of decreasing transport with increasing grain size, there is also extensive scatter in the data, with more scatter for the larger grain sizes.…”

Section: Variation Of Cerc K With Grain Sizementioning

confidence: 99%

“…Komar (1988) examined most of the available field data, and questioned the validity of some. He concluded that existing data, most of which were for sand-size beaches, showed little relationship between K and grain size.…”

Section: Variation Of Cerc K With Grain Sizementioning

confidence: 99%

“…The equation was based on data presented by Komar (1988) and data obtained from their research along the Adra River Delta, Spain. The relationship is:…”

Section: Variation Of Cerc K With Grain Sizementioning

confidence: 99%

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Influence of Grain Size on Sediment Transport Rates With Emphasis on the Total Longshore Rate

King¹

2005

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PURPOSE:The calculation of longshore sediment transport (LST) rates is a key component of most coastal engineering studies. While the LST process is conceptually simple, in practice the development of reliable rates is made difficult by problems associated with collecting accurate field data, by limitations to model predictions, and by substantial variations of the rates in time and space. This Coastal and Hydraulic Engineering Technical Note (CHETN) summarizes the state of understanding of the influence of grain size on surf zone sediment transport and is a companion to Smith et al. (2004). This CHETN discusses details of bed-load and suspended load transport, and the classical bed-load regime is shown to encompass two distinct modes of transport. Four LST models with varying levels of complexity are discussed to show how they incorporate the physics of grain size variation and its effect on the transport rate. In addition, a relationship between the K coefficient in the CERC formula (Coastal Engineering Manual (2002), Section III-2-3-a) and grain size is presented. Finally, some inconsistencies between theory and data are discussed in the context of the interrelationship between grain size and beach slope.The final conclusion is repeated here. In general, an increase in the median grain size will decrease LST rates in the surf zone. If a simple exponential relationship between transport rate and grain size (D) is needed (Equation 7: LST rate ∝ D n ), the most appropriate value for the exponent n should be of the order of -1, as seen from Equation 23. However, this tech note argues that this is clearly a simplistic view of surf zone sediment dynamics. A more realistic (though still highly simplified) approach would be that, for fine grain sediments (D 50 on the order of 0.15 to 0.30 mm), suspended load transport should dominate and n should be somewhere within the range of -0.5 to -3.0. For coarse sands (D 50 around 1.0 mm), sheetflow bed-load transport should dominate (Figure 6), and the transport rate should be nearly independent of grain size (n = 0). For large gravel and shingle (D 50 > 20 mm), the dominant transport should be in the IM (Initial Motion) bed-load regime, with n within the range of -0.5 to -2.0. To state this another way, the exponent n in Equation 7 is itself a function of grain size. BACKGROUND:Though most researchers recognize the median grain size as a parameter of first order importance in its effects on the magnitude of sediment transport, its variation is not as easily studied as the variation of many of the other primary parameters. In the field, it is easy to obtain data for a range of values for wave heights and periods, for instance, as these vary constantly in time. However, the grain size on a beach typically shows no (or insignificant) variations in time. Similar problems can occur in the laboratory. Changing the wave height or period in a laboratory study is usually as simple as reprogramming a wave paddle. However, usually, changing the grain size in a large model is infrequen...

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Section: Variation Of Cerc K With Grain Sizementioning

confidence: 99%

Section: Variation Of Cerc K With Grain Sizementioning

confidence: 99%

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Influence of Grain Size on Sediment Transport Rates With Emphasis on the Total Longshore Rate

King¹

2005

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“…Therefore, the CERCformula is only valid for a narrow range of conditions as represented by the calibration data. According to Komar (1988), Dean (1988, 2002), Del Valle et al (1993 and King (2005), the K-coefficient is a function of particle size (based on data with d 50 -values in the range of 0.15 mm to 1.5 mm). Based on their results, the K-coefficient can be represented by: K=1.5exp(-2.5d 50 ) with d 50 in mm.…”

Section: Cerc Formulamentioning

confidence: 99%

The Effects of Grain Size and Bottom Slope on Sand Transport in the Coastal Zone

Rijn¹,

Boer²

2007

Coastal Engineering 2006

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This paper presents the effects of grain size and bottom slope on the longshore sand transport in the coastal zone (surf zone). Field data sets of sand transport in rivers, estuaries and coastal seas have been analysed to determine the effect of grain size. Three bulk-type formulae of longshore transport have been used to compute the longshore transport for a range of offshore wave conditions. Finally, a detailed cross-shore profile model (UNIBEST-TC of Delft Hydraulics) has been used to determine these effects for a new land reclamation site near the Port of Rotterdam, The Netherlands.

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“…The model calculates K as a function of breaker angle and the ratio of velocity magnitude to sediment fall speed. The Bailard model was calibrated with field and laboratory data (wave heights ranging from 0.5 m to 2.0 m) and is similar to a relationship developed based on limited laboratory data by Walton (1979) and Walton and Chiu (1979 Komar (1988) and data obtained from the Adra River Delta, Spain. The equation, applied to rms breaking wave heights is given as:…”

Section: Introductionmentioning

confidence: 99%

Dependence of Total Longshore Sediment Transport Rates on Incident Wave Parameters and Breaker Type

Smith¹,

Ebersole²,

Wang³

2004

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PURPOSE:Total longshore sediment transport (LST) rate and its cross-shore distribution in the surf zone are essential to many coastal engineering and science studies. Practical engineering applications such as predicting beach response in the vicinity of coastal structures, beach-fill evolution and renourishment requirements, and sedimentation rates in navigation channels all require accurate predictions of LST rates. Present predictive tools have been developed based primarily on field studies; however, obtaining high-quality data in the field is difficult (Wang and Kraus 1999). Arguably the most widely used model for estimating total longshore sediment transport rate is the "CERC" formula (Coastal Engineering Manual 2002, Shore Protection Manual 1984, which is based on field measurements and is often applied to calculate the total LST rate. Accuracy of the CERC formula is believed to be ± 30-50 percent at best; and several parameters that logically might influence LST are excluded in the formula, such as breaker type and grain size.This CHETN summarizes results of experiments conducted in the Large-scale Sediment Transport Facility (LSTF) Fowler et al. 1995) to investigate the importance of wave height, period, and breaker type (spilling and plunging breakers) on total LST and the cross-shore distribution of LST. The LSTF is capable of simulating wave conditions that are almost directly comparable to annual averages along many low-wave-energy coasts, for example a majority of estuarine beaches (Nordstrom 1992) and many beaches along the Gulf of Mexico and the Great Lakes in the United States. BACKGROUND:A common tool for predicting the total rate of longshore transport is the CERC formula. The model, based on the assumption that the total longshore sediment transport rate is proportional to longshore energy flux, is given as:

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Environmental Controls on Littoral Sand Transport

Cited by 10 publications

References 13 publications

Influence of Grain Size on Sediment Transport Rates With Emphasis on the Total Longshore Rate

Influence of Grain Size on Sediment Transport Rates With Emphasis on the Total Longshore Rate

The Effects of Grain Size and Bottom Slope on Sand Transport in the Coastal Zone

Dependence of Total Longshore Sediment Transport Rates on Incident Wave Parameters and Breaker Type

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