Impacts of Dredging on Shoreline Change

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1 Impacts of Dredging on Shoreline Change Hüseyin Demir 1 ; Emre N. Otay 2 ; Paul A. Work 3 ; and Osman S. Börekçi 4 Downloaded from ascelibrary.org by UNIVERSITY OF FLORIDA on 10/13/14. Copyright ASCE. For personal use only; all rights reserved. Abstract: Nearshore dredging for construction aggregate or beach nourishment can result in a perturbation of natural littoral processes, changes in wave transformation patterns, and a net loss of sand from the littoral system. A method is described for estimating both direct and indirect effects of dredging on shoreline change. The direct effect results from infilling of the dredged pit via cross-shore sediment transport and is addressed statistically, assuming that the beach profile is in some arbitrary equilibrium shape. The indirect effect arises from project-induced wave transformation, which alters longshore sediment transport patterns, and is described using both spectral and monochromatic, numerical wave transformation models to provide input to a one-line model for shoreline change. Infilling of the pit is neglected when estimating the indirect effect, providing a worst-case estimate of the indirect effect. The methodology is applied to a site on the Turkish Black Sea coast, using hindcast wave data. The influences of pit location and geometry are investigated systematically, and recommendations regarding optimum pit dimensions and locations are made. DOI: / ASCE X :4 170 CE Database subject headings: Dredging; Shoreline changes; Sediment transport; Wave refraction; Black Sea; Turkey. Introduction In many parts of the world, terrestrial sources of sand are sufficient to meet local demand. In an increasing number of locations, however, marine deposits are being mined, typically to meet construction needs, with beach nourishment being a special but important case. Japan and the United Kingdom provide two examples of nations where marine deposits serve as the primary source of sand. Annual removal in Europe has been estimated at 50 million m 3 Simons and Hollingham In the United States, most of the marine dredging is in support of navigation and beach nourishment. On the western Black Sea coast of Turkey, marine sand is routinely mined to meet demand for construction in and near Istanbul, where most new construction is with reinforced concrete. A regulatory agency typically defines allowable locations and magnitudes of dredging activities, typically by specifying a minimum depth or distance from shore for the dredging operations, and a permitted volume Marine Habitat Committee In some cases, deviations from these requirements are permitted if it can be demonstrated that the project will not result in significant negative impacts or changes in physical or biological processes. 1 Graduate Research Assistant, School of Civil and Environmental Engineering, Georgia Tech-Savannah, 210 Technology Circle, Savannah, GA huseyin.demir@ce.gatech.edu 2 Assistant Professor, Civil Engineering Dept., Boğaziçi Univ., Bebek, Istanbul, Turkey. otay@boun.edu.tr 3 Associate Professor, School of Civil and Environmental Engineering, Georgia Tech-Savannah, 210 Technology Circle, Savannah, GA paul.work@gtrep.gatech.edu 4 Associate Professor, Civil Engineering Dept., Boğaziçi Univ., Bebek, Istanbul, Turkey. borekci@boun.edu.tr Note. Discussion open until December 1, Separate discussions must be submitted for individual papers. To extend the closing date by one month, a written request must be filed with the ASCE Managing Editor. The manuscript for this paper was submitted for review and possible publication on May 5, 2003; approved on December 17, This paper is part of the Journal of Waterway, Port, Coastal, and Ocean Engineering, Vol. 130, No. 4, July 1, ASCE, ISSN X/ 2004/ /$ There is no universally accepted methodology for making such an assessment, however, even if the problem is restricted to address only physical impacts. This paper presents a methodology for quantifying impacts of dredging on shoreline change. A combination of both analytical and numerical modeling techniques is employed, and the method could be applied to any site for which appropriate input data are available. Direct and indirect impacts of the dredged pit on sediment transport are considered. The direct impact leads to a loss of sediment from the dry beach via infilling of the dredged pit. The secondary impact results from modification of the nearshore wave conditions via the modified bathymetry. The presence of the dredged pit may lead to changes in the location of wave breaking and to modification of the wave field through refraction and, to a lesser degree, diffraction. These changes lead to modified longshore sediment transport patterns that alter the shoreline planform. Note also that while dredging for beach nourishment generally does not result in a net loss of sand from the littoral system, dredging for construction aggregate does, and therefore is a more severe concern. The impact assessment methodology is applied to a site on the Turkish Black Sea coast near Istanbul, where marine aggregate is used to meet construction demand, and where regulations regarding marine dredging are not well established. Recommendations are made regarding optimum borrow site configuration, dredging depth and the methodology by which these values should be established. Literature Review The potential negative impacts of dredging in marine areas have been recognized for many years. These include physical, chemical, and ecological impacts. Only the physical impacts will be addressed here, however, and the focus will be limited to largescale 1 10 km, long-term years effects on adjacent shorelines. Of primary concern are the changes in nearshore wave characteristics and sediment transport patterns resulting from the modified bathymetry. 170 / JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING ASCE / JUL/AUG 2004

2 Fig. 1. Schematic of beach profile before dredging, and after infilling of dredged pit Prototype scale experiments, laboratory scale models, and numerical models all represent viable techniques for studying the impacts of dredging. Because of the expense and the difficulty of separating project-induced changes from changes due to other factors, prototype studies are few. Kojima et al monitored dredged holes between 1981 and 1984 in the Genkai Sea in Japan. Dredged holes at depths less than 30 m were observed to fill with sediment in less than 1 year. Erosion along the shoreline was also observed, but the portion attributable to the presence of the dredged pits could not be isolated. Combe and Soileau 1987 see also Gravens and Rosati 1994 observed shoreline changes in the lee of dredged pits that appeared to be consistent with a wave field modified by the pit. Scale effects make laboratory models of dredging impacts problematic, as is true for most sediment transport problems. Horikawa et al conducted experiments in a wave flume that included a nonerodible dredged pit and a sand beach. Along the shoreline, accretion was observed in the lee of the pit, with erosion on either side. Results from a numerical modeling approach that combined wave ray tracing with a one-line model for shoreline change yielded similar results. Bender 2001 also performed laboratory experiments to investigate the impacts of dredged pits on shoreline change. Wave conditions and dredged hole geometries were varied. Both erosion and accretion were found behind the dredged pit for different cases. Bender also modeled the problem numerically by combining wave transformation and shoreline change models, and found that changes in the wave conditions or dredged pit specifications could alter shoreline change patterns, but numerical model results did not always match laboratory simulations. The majority of studies regarding impacts of dredging on shoreline change have employed a numerical modeling approach. Motyka and Willis 1974 used a wave refraction model and a one-line shoreline evolution model to investigate shoreline change in the lee of a dredged pit. Response was the reverse of that observed by Horikawa et al. 1977, with erosion in the lee of the hole and accumulation on either side. Maa and Hobbs 1998 used a monochromatic wave transformation model regional coastal processes wave propagation model RCPWAVE, Ebersole et al to model wave transformation with proposed dredging at Sandbridge Shoal in Virginia. Sediment transport rates with and without the dredged hole were modeled and differences were concluded to be insignificant. Maa et al suggested the use of breaking wave heights only and not wave directions to assess impacts, arguing that wave model accuracy regarding wave directions was inadequate. Basco and Lonza 1997 used spectral wave models to investigate wave transformation over dredged pits. Their approach omitted diffraction, but they argued that diffraction would not be significant for holes with large surface areas and small depths of disturbance. Other numerical model studies have focused only on wave transformation induced by pits, without addressing sediment transport. Lee and Ayer 1981 modeled the propagation of waves over an infinitely long trench. Kirby and Dalrymple 1983a considered the case of monochromatic waves obliquely incident on a trench. Williams 1990 considered the two-dimensional problem, and later extended the solution to three dimensions Williams and Vazquez McDougal et al extended the solution to consider the effects of multiple pits. Van Dolah et al investigated the infill rates of six borrow pits in South Carolina, and found that they typically recovered within 5 12 years, with this time being proportional to distance from shore. The time scale for infilling will depend strongly on local environmental and sediment parameters, however. The study described here differs from many previous efforts in that it includes directional, spectral waves and consideration of both longshore and cross-shore sediment transport. Cross-shore and longshore effects are considered separately, with one yielding what will be referred to as a direct effect, and the other leading to an indirect effect on shoreline change. Methodology The methodology employed in this study involves uncoupled descriptions of the direct and indirect effects of a dredged pit on the shoreline in its lee. The direct effect results from cross-shore sediment transport into the pit, which appears as a net loss of sand from the dry beach Fig. 1. The indirect effect arises from project-induced wave transformation that alters breaking wave heights and directions, and thus changes longshore sediment JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING ASCE / JUL/AUG 2004 / 171

3 Fig. 2. Plan view schematic illustrating indirect effect of dredged pit: wave transformation induced by bathymetric disturbance results in shoreline change. Actual shoreline change pattern will vary depending on wave conditions, pit location, and geometry transport rates, longshore gradients of longshore sediment transport, and therefore shoreline position Fig. 2. In the figure the accretion in the lee of the pit is due to wave sheltering created by the pit. However, either erosion or accretion may occur behind the pit depending on the pit and wave configurations. The direct effect will be addressed first. The depth of closure for cross-shore sediment transport is a widely used parameter to describe the depth to which seasonal variations in beach profile shape are evident e.g., Dean Its value will depend on wave conditions, sediment characteristics, and the time period under consideration. Hallermeier 1980 used the Shields parameter to define a cut depth, h c, as a function of the near-bed orbital velocity for motion of sediment under waves U b (1) s 1 gh c where U b amplitude of the wave orbital velocity at the bed; s sediment specific gravity; and g acceleration of gravity. The cut depth is defined such that beach profile changes at greater depths are insignificant although sediment will still be mobilized at times. This will be assumed equivalent to the depth of closure. The orbital velocity at the bed, per linear wave theory, is U b H (2) 2 sinh kh where wave angular frequency; h water depth; H wave height; and k wave number. Thus for any depth, wave height, wave period, and sediment size, it is possible to determine a critical orbital velocity required for sediment movement. Alternatively, given sediment size, wave height, and wave period, the critical depth beyond which the beach profile does not change may be determined. Every site will have a unique joint probability distribution describing the likelihood of any particular combination of wave height and period. Fig. 3 dashed lines shows the joint probability density function JPDF for wave height and period for a site near Kilyos on the Turkish Black Sea coast just north of Istanbul the data are derived from a wave hindcast; Cavaleri et al. Fig. 3. Joint probability density function for wave height and period dashed lines at Kilyos on Turkish Black Sea coast from Eurowaves hindcast data, site located at 41N 30, 29E 00. Solid lines indicate closure depth in meters, as function of significant wave height and period 1999a,b. Superimposed on the JPDF are contours indicating the corresponding closure depth, per Eqs. 1 and 2 solid lines. Since wave height and period are statistical quantities, with a known joint probability distribution, and it is known how closure depth varies with these parameters, it is possible to determine the percentage exceedence associated with any closure depth at any site. This is shown in Fig. 4 dots for the Kilyos site. To relate percentages to return periods more information is required. Nicholls et al proposed an approximation for the solution of Eqs. 1 and 2 : h c t 2.28H e t 68.5 H e 2 gt 2 (3) e t where t given time span of interest; h c closure depth; and H e (t) and T e (t) wave height and wave period, respectively, ex- Fig. 4. Closure depth as function of percentage exceedence and return period for Kilyos site calculated using: a joint probability density function JPDF of wave height and period and Eqs. 1 and 2 dots, b separate probability density function of wave height and period and Eq. 3 solid line, and c lognormal fits for individual probability density functions of H and T and Eq. 3 dashed line 172 / JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING ASCE / JUL/AUG 2004

4 ceeded 12 h in time t. Critical depth is given as a function of time by relating percentages with time. Equation 3 is plotted in Fig. 4 as a solid line using the individual probability distributions defining H and T for the site considered here. The dashed line in Fig. 4 also represents Eq. 3, calculated using lognormal fits to the probability distributions for wave height and period instead of the observed percentages themselves. The three lines, which coincide for large percentages, begin to deviate at low probabilities. This is due both to the inability of the lognormal fit to represent the real data and the scarcity of data for lower probabilities. If it is assumed that the cross-shore profile of the beach has some arbitrary equilibrium shape, a dredged hole placed at a depth shallower than the closure depth will be filled, yielding shoreline erosion Fig. 1. The amount of shoreline erosion y may be calculated from simple geometric considerations as y V (4) h c B where V cross sectional area of the filled region volume per unit length and B berm height. However, since it is known that closure depth is a function of time it may be replaced with h d, water depth above the dredged hole giving y max V (5) h d B where y max maximum potential net shoreline erosion due to cross-shore sediment transport. As the dredging depth increases, the time span required for the closure depth to reach the dredging depth increases logarithmically. The presence of a dredged pit creates various mechanisms that alter the wave field. Some of the incoming wave energy reflects from the hole, leading to partial standing waves on the offshore side. Reflection leads to reduced wave heights in the lee of the hole, creating gradients of wave energy in the longshore direction. Diffractional bands of increased and decreased wave height form in the lee of the pit, particularly for the case of vertical sidewalls e.g., Williams McDougal et al showed that diffraction effects decay with decreasing pit depth to water depth ratio. The dredged pits considered here assume side walls with mild slopes less than 1:10, with pit depth to water depth ratios on the order of 0.1, compared to ratios on the order of one in the papers discussed above. Thus reflectional and diffractional effects are reduced. Refraction causes waves to bend away from the sides of the dredged hole, creating an area of decreased wave height in its lee, and areas of increased wave height on either side. Diffraction plays a role here too, but to a much lesser extent, smoothing out the gradients in the wave height. Two numerical wave transformation models were used to investigate the indirect effects of dredged holes on long-term shoreline change. The REF/DIF 1 model developed by Kirby and Dalrymple 1983b is a monochromatic wave transformation model that employs a parabolic approximation to the mild slope equation and thus accounts for shoaling, refraction, and diffraction. The simulating waves nearshore SWAN model describes transformation of directional wave energy spectra by solving the conservation of wave action density equation Booij et al It simulates generation by wind, wave wave interactions, and most wave transformation processes except diffraction. Although SWAN does not simulate diffraction, the angular spreading of the waves, arising from frequency-dependent refraction, mimics its effect to some extent. Fig. 5. Transformation of wave angles for conditions given in Table 1 using shore normal waves angles are exaggerated ten times and plot shows subset of model output computed with REF/DIF1 top and SWAN bottom. Rectangular box shows pit length:1,000 m, width:500 m, depth:3 m Initial model runs were made with a simplified bathymetry, uniform in the longshore direction except for the presence of a dredged pit. The pit was assumed rectangular in planform, either trapezoidal or parabolic in cross section, and constant in time. Computational grid space steps of 50 m by 50 m were used for wave modeling. Model runs were made on this bathymetric grid with and without the dredged pit to reveal the modification of the wave field and shoreline change due to the presence of the pit. Breaking wave parameters obtained from two wave models were used to compute shoreline evolution using a one-line model for shoreline change e.g., Hanson and Kraus Breaking wave heights were evaluated at the point at which depth induced breaking began. This choice is conservative since by choosing the breaking angle at the seaward boundary of the breaking zone, the estimated longshore sediment transport rate is larger. Figs. 5, 6, and 7 compare the monochromatic and spectral wave model results for the case of normal wave incidence on the simulated dredged pit. The monochromatic model shows a much more drastic response to the presence of the pit, despite the inclusion of diffraction. Both model outputs indicate very little change in wave height in the lee of the pit along its center line Fig. 6. The ends of the dredged hole are the sources of wave field modification. Bands of increased wave height propagate outwards from the ends and bands of decreased wave height propagate to the lee of the pit. The sediment transport equation employed in the generalized model for simulating shoreline change GENESIS model Hanson and Kraus 1989 is used here Q K 5/2 1H b g/ 8 s 1 1 p sin b cos b K 5/2 2H b g/ 8 s 1 1 p cos b tan dh b dx (6) where Q longshore sediment transport rate; b angle between the breaking wave crests and the shoreline; H b breaking wave height; s ( 2.62) specific gravity of sediment; p ( 0.35) sediment bed porosity; g acceleration of gravity, (H/h) b ( 0.78) spilling breaker constant used to relate the breaking wave height to water depth; and tan( ) slope of the beach. K 1 and K 2 sediment transport coefficients, which are both taken as 0.39 since significant wave heights are used in Eq. 6. JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING ASCE / JUL/AUG 2004 / 173

5 Fig. 6. Wave height/incident wave height contours for conditions given in Table 1 using shore normal waves computed with REF/DIF 1 top and SWAN bottom The first term in Eq. 6 is proportional to a power of the breaking wave height, while the second term Bakker 1971 is proportional to longshore gradients in breaking wave height. For dredged holes, these terms have opposing effects on shoreline change Bender The first term leads to erosion in the lee of the pit, while the second causes accretion. The net effect is controlled by the ratio of K 1 to K 2, pit geometry, and wave conditions Demir The ratio of K 1 to K 2 was arbitrarily taken as one since there are not enough data on the value of K 2 and there was not enough field data for regression analysis for the area of interest. Fig. 7. Longshore distribution of breaking wave heights, wave angles, and shoreline change after 5 days computed both with REF/ DIF 1 and SWAN for conditions given in Table 1 using oblique waves ( 0 15 ) Case Study A site on the Turkish Black Sea coast was selected as a case study. Offshore dredging along the Black Sea coast near Istanbul is an important source of concrete aggregate for construction in and near Turkey s largest city. Currently, the only licensed area for sand mining around Istanbul is the Podima site, which is 65 km west of the Strait of Istanbul and 2 4 km offshore. However, this area is deprived of sand and mining is routinely done outside this area including locations much closer to shore Istanbul Sand Miners Association, personal communication According to the current regulations, the new mining areas should be at least 3 nautical miles offshore. However Eryılmaz and Yücesoy-Eryılmaz 1997 state that there are sand deposits only up to 2 mi offshore near Istanbul. It is thus common for dredging to take place at unauthorized sites, without consideration of potential negative impacts on the shoreline. Available Data There are no long-term wave measurements available within the Black Sea Cavaleri et al. 1999a. Wave generation model hindcast results based on meteorological wind statistics, maps, satellite images and short-term wave measurements for verification and parameter optimization have recently become available through the EuroWaves Cavaleri et al. 1999b, and NATO TU- Waves Özhan and Abdalla 1999 projects. The EuroWaves project provided statistical wave data for European and surrounding coasts, including the Black Sea Cavaleri et al. 1999b. The hindcast results were obtained using measured wind data and the WAM wave model Komen et al with a spatial resolution of 0.25 in latitude and longitude and a temporal resolution of 15 min to produce wave conditions. Buoy measurements and satellite altimeter data were used for calibration and verification of hindcast model results. Continuous data are available for the 7-year period between November 1991 and October Statistical wave parameters are available at every 0.5 in latitude and longitude. Available statistical parameters include the significant wave height (H s ), mean wave period (T m ), peak wave period (T p ), and mean wave direction ( m ). The NATO TU-Waves project also yielded statistical wave parameters for the Black Sea and Turkish coasts Özhan and Abdalla The approach employed is similar to the EuroWaves project. The same 7-year wind data set was used. Additionally, synoptic maps from weather stations for the period were digitized to allow a larger period for extreme value predictions. A different wave model, METU3, was used, along with the WAM model. Directional and nondirectional wave data measurements were used for verification and calibration purposes, rather than satellite data. Wave roses, showing the relationship between wave direction and wave height, were provided in a recently published wave atlas. The EuroWaves and NATO TU-Waves projects use the same wind input sources and numerical wave generation models to develop wave statistics, so the results are similar, as expected. The yearly average significant wave height is 1.0 m and the mean period is 5.2 s for the Kilyos region. Nautical charts were the only source of available bathymetric data for the region of interest. The Istanbul Strait North Approach 1811-INT 3758 nautical map with a scale of 1:50,000 was digitized to supply bathymetric data for the study area. 174 / JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING ASCE / JUL/AUG 2004

6 Table 1. Wave and dredged pit parameters for baseline tests Incident waves Height Period Angle 3m 7s 0 15 Dredged pit Length Width Depth 1,000 m 500 m 3 m Water depth Sediment size Side slope 15 m 0.30 mm 6% Results Wave heights and directions obtained from the REF/DIF 1 and SWAN wave transformation models were used to compute shoreline change using a one-line model Demir Fig. 7 shows the longshore distributions of breaking wave height and angle, as well as the resulting shoreline change after five days of constant waves. For both wave model runs, the simplified Kilyos bathymetry was used, with input parameters given in Table 1 for oblique waves. Both model results in Fig. 7 indicate perturbations in the longshore direction for all three parameters: wave height, wave angle and shoreline position. However, the spectral capability of the SWAN model reduces gradients in wave heights and angles, whereas the inclusion of diffraction in the REF/DIF 1 model creates oscillations in wave height and angle that diminish with distance from the pit. The asymmetries in wave height, wave angle and shoreline change arise due to the oblique wave incidence. Although SWAN lacks diffraction, it yielded shoreline evolution patterns similar to the REF/DIF 1 results. This suggests that except for some extreme wave and pit conditions, the diffraction effect is small compared to refraction. SWAN is a spectral model and the field conditions may be modeled more realistically with it compared to a monochromatic model, so it was selected for the remainder of the tests discussed here. The main question regarding the physical sediment transport impacts of marine sand withdrawal is how to increase production while minimizing dredging-induced shoreline change. Several wave and pit parameters were systematically altered to investigate Fig. 9. Dimensions of idealized dredged pit: a plan view and b cross-sectional view the sensitivity of shoreline change to changes in these parameters. The methodology used takes into account only the indirect effects. Therefore, Figs do not include direct effects and are applicable outside the closure depth. Inside the closure depth, they are still valid, but direct effects are also superposed on top of those. As seen in Eq. 5, direct effects are directly proportional to the dredged volume and cannot be changed by changing the pit geometry. Starting with the wave and dredging conditions as described in Table 1, each dredged pit geometrical parameter was changed to increase the dredged volume. The total displaced volume along the shoreline is used to quantify the indirect impact of dredging. Although simply moving sand alongshore from one portion of the beach to another does not represent a net loss of beach, it is problematic if the magnitude of the change becomes large. The original water depth at which the pit was located was varied from 10 to 40 m and nondimensionalized by depth of closure Fig. 8. The displaced volume, the maximum erosion and maximum accretion all decrease with increasing water depth, as expected. As the dredged pit is moved into deeper water, its influence on the shoreline becomes less significant. The dredged pit geometry was idealized by four parameters Fig. 9. These are the length, L, measured in the longshore direction, the width, W, measured in the cross-shore direction, the hole depth, D, measured from the original sea bottom down to the Fig. 8. Effect of water depth at dredged pit location on shoreline change. Pit geometry constant closure depth 5.6 m Fig. 10. Effect of pit length measured in longshore direction on shoreline change JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING ASCE / JUL/AUG 2004 / 175

7 Fig. 11. Effects of different dredging strategies on shoreline change. D, WL, and tan are depth, width, length, and side slope of pith, respectively. While changing width, water depth at center of pit remains constant. bottom of the pit, and the side slope of the dredged hole, tan, measured in the longshore direction on each end of the hole. When the pit length is increased, meaning that the dredged hole becomes longer in the longshore direction, some unexpected results are found Fig. 10. The displaced volume at the shore increases with increasing pit length, up to a certain value, but then it stabilizes and does not increase any further. More interestingly, it is found that the maximum shoreline recession decreases for increasing values of pit length. With increasing pit length, the two edges of the pit are separated away from each other. Because the edges act as sources of wave scattering, moving them away from each other reduces the superposition effect of the scattered waves. Consequently, maximum shoreline change decreases. In practice, sand production can be increased by increasing either one of the pit dimensions, L, W, and/or the pit depth D, or by decreasing the slope tan. Using the modeling procedure defined above, all four parameters were adjusted systematically to define their relative impact on shoreline change Fig. 11. The slope of each line shows the effect of a specific strategy on the shoreline change; the slope increases with the effect. The results indicate that the pit depth is the parameter to which the shoreline change due to indirect effects is most sensitive. It is followed by the width of the dredged hole in the cross-shore direction. The least critical parameter is the side slope, followed by the longshore extent of the dredged hole. When the side slopes of the dredged hole become milder, the wave refraction across the sides of the hole becomes less intense and therefore the perturbations at the shore become smaller. Conclusions Two mechanisms were identified by which offshore dredging can lead to shoreline change. These were termed direct and indirect effects. The direct effect is simply a result of infilling of the pit via cross-shore sediment transport from the beach. The indirect effect is a more complicated function of how the dredging alters wave heights and directions and therefore changes longshore sediment transport patterns. The direct effect of the dredging is quantified by assuming that the beach profile will recede landward after dredging to retain an arbitrary equilibrium shape. The magnitude of the resulting erosion is proportional to the dredged volume of sediment, and independent of the dredged pit depth and geometry if the pit is placed at a depth less than the depth of closure. Moving the dredged pit to greater depths 1 increases the time scale for infilling and 2 can prevent the direct shoreline erosion entirely, if the pit depth exceeds the depth of closure. Based on a stochastic analysis of waves in the Kilyos site that served as a case study, the 1 and 10 year closure depths are 12 m and 26 m extrapolated, respectively. Wave transformation around and across the dredged hole indirectly affects the longshore sediment transport patterns by altering breaking wave conditions. The induced perturbation in the littoral drift causes erosional spots on adjacent shorelines; this is termed the indirect effect of the dredged pit. The physics of this mechanism is controlled by refraction and diffraction processes. For the cases considered here, refraction dominated the shoreline change patterns. The typical features of shoreline change due to refraction are the leeside erosion landward of the pit and the edge deposition on either side of the eroded area. Diffraction is expected to be less important than refraction when the pit depth is small compared to water depth or the side slopes are mild. Diffraction effects appear in the form of multiple undulations of the shoreline, which are generated by wave scattering from the two edges of the pit. The undulations along the shoreline tend to die out away from the central axis of the pit, or as the side slopes of the pit become milder. Numerical sensitivity tests indicate that shoreline response is extremely sensitive to water depth at the dredging location, moderately sensitive to the cross-shore width of the pit, and nearly independent to the longshore length of the pit once the ends of the pit are far enough that their effects do not superpose. Thus, one should place the pit in the deepest water that is practical and minimize both the change in depth due to dredging and the side slopes of the pit. If the dimensions must be increased to dredge a larger volume and the direct effects are insignificant, our results suggest that the best way to do this is to increase the longshore length of the pit. Acknowledgments The writers would like to thank the Geodesy Department at Boğaziçi University, especially Prof. Onur Gürkan and Dr. Haluk Özener, for their technical support in surveying, the Boğaziçi University Scuba Club BUSAS for their assistance with instrument installations, and Dr. Stephen Barstow from Oceanor for supplying the EUROWAVES data. This work was funded by the Boğaziçi University Research Fund Project Nos. 98A403 and 01A402, the Turkish National Science Foundation TUBITAK- INTAG/837, and the Istanbul Sandminers Association. Their support is gratefully acknowledged by the writers. Paul A. Work was also supported by a scholarship from the U.S. Fulbright Commission. Notation The following symbols are used in this paper: B berm height; 176 / JOURNAL OF WATERWAY, PORT, COASTAL AND OCEAN ENGINEERING ASCE / JUL/AUG 2004

8 D dredged pit depth measured from original sea bottom down to bottom of pit; g acceleration of gravity; H wave height; H b wave height at breaking; H e (t) wave height exceeded 12 h in time t; H s significant wave height; h water depth; h c depth of closure or cut depth; h d water depth above dredged hole; K 1,K 2 sediment transport coefficients; k wave number; L length of pit measured in longshore direction; p sediment bed porosity; Q longshore sediment transport rate; s specific gravity of sediment; T e (t) wave period exceeded 12 h in time t; mean wave period; T m T p peak wave period; t time; tan side slope of dredged pit measured in longshore direction; tan( ) beach slope; U b wave orbital velocity at bed; W width of pit measured in cross-shore direction; V cross sectional area of filled region volume per unit length ; y max maximum potential net shoreline erosion due to cross-shore transport; impact factor; b angle between breaking wave crests and shoreline; mean wave direction; spilling breaker constant used to relate breaking wave height to water depth; and wave angular frequency. m References Bakker, W. 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