Sediment dispersal and deposition due to sand mining in the coastal waters of Korea

ARTICLE IN PRESS

Continental Shelf Research 29 (2009) 194–204 www.elsevier.com/locate/csr

Sediment dispersal and deposition due to sand mining in the coastal waters of Korea Chang S. Kim, Hak-Soo Lim Coastal Engineering Division, Korea Ocean R&D Institute, 1270 Sa2Dong, Ansan, Kyunggi 426-744, Republic of Korea Received 15 January 2007; received in revised form 11 October 2007; accepted 31 January 2008 Available online 9 February 2008

Abstract Understanding the impact of marine sand mining operations in a complex coastal environment requires a combined observational and modeling approach. Here, we use field measurements collected during mining operations in Kyunggi Bay, Korea to develop sediment parameters and source conditions for a three-dimensional (3D) sediment transport model built on the Regional Ocean Modeling System (ROMS). The model is run with realistic forcing obtained from a 9 km meteorological model, tides, and river discharges. The resulting vertical and horizontal distributions of sediment show encouraging agreement with the field data, demonstrating markedly different dispersal patterns due largely to the differential settling of the various sand classes. The resulting depositional patterns suggest that only the coarser size classes (500 and 250 mm) particles remain close to the mined site, while finer size classes are widely dispersed. These results suggest that this new methodology of multi-size class, 3D sediment transport modeling is quite promising, and further work is ongoing to include more realistic representation of sediment resuspension processes. r 2008 Elsevier Ltd. All rights reserved. Keywords: Sediment transport; Modeling; Coastal; Sand mining; Yellow Sea; Kyunggi Bay

1. Introduction Kyunggi Bay is a shallow (o40 m), semi-enclosed region located on the Korean Peninsula in the eastern part of the Yellow Sea (Fig. 1). The region is characterized by a large tidal range (4–8 m), strong tidal currents (1–2 m/s) and a large sediment supply (12.42  106 t/yr; Hong et al., 2002) provided by the Han River. Extensive mud flats are found in less energetic regions, while large sand deposits are found in more energetic environments. Approximately 25 million m3 per year of marine sand has been extracted in the last 20 years from sites within Kyunggi Bay, used mainly for construction material in the nearby Seoul metropolitan area. Hence the major composition of dredged sand comprises of 99% or 98% of sands in volume at most with 1–2% of silt and clay materials (MOMAF, 2005; Ministry of Marine Affairs and Fisheries Korea). Typically, this marine sand is removed by anchor dredgers Corresponding author. Tel.: +82 31 400 6340; fax: +82 31 400 6340.

E-mail address: [email protected] (C.S. Kim). 0278-4343/$ - see front matter r 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.csr.2008.01.017

with a loading capacity of 2000–3000 m3. Repeated field surveys have shown that dredging can result in substantial lowering of the seabed and redistribution of surface sediments due to size-dependent behavior of the disturbed sediments (MOMAF, 2005, 2006). In Kyunggi Bay, these pits can be 10–15 m deep and 2–3 km wide. Dredging also leads to the production of plumes of suspended material in the surface layer and highly turbid flows. This strong modification of the sea floor and associated environmental changes can have a dramatic affect on the local benthic community and habitat (Boyd and Rees, 2003). Public awareness of the vulnerability of coastal environments, the benthic habitats and the fishery nursery grounds have forced policy-makers to enhance regulation, and seek more environmentally safe resources in deeper and further offshore. Because the impact of these processes occurs slowly in time and widely in space, short-term monitoring has only a limited ability to quantify the impact, and a long-term combined monitoring and modeling approach should be used (Basco, 1999; Large et al., 1994; Simons and Hollingham, 2001).

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38.0

Ganghwa

LATITUDE(N)

JangbongIs. INCHEON

-10

37.5

SEOUL

DeokjeokIs. -20 -40

37.0

SungbongIs. PungIs.

-30

SongapIs.

-50 -60

TAEAN

36.5 DEPTH(m)

DAECHEON

-70 -60 -50 -40 -30 -20 -10 0

124.5

125.0

125.5 126.0 LONGITUDE(E)

126.5

127.0

Fig. 1. Bathymetry of Kyunggi Bay, Korea.

In Kyunggi Bay, there has not yet been an attempt to use a numerical model to help predict the long-term impact of the sand extraction on the change in benthic habitats. The difficulty has been the lack of quantitative information on the sediment source conditions at the surface and bottom dredging, combined with the effort required to implement a numerical model capable of representing the relevant physics with sufficient accuracy. In this study, we use the fully 3D numerical model Regional Ocean Modeling System (ROMS) developed by Rutgers University (Song and Haidvogel, 1994) to examine the sediment dynamics arising from the undersea sand mining operation. The fundamental parameters are estimated from field observations. By using the site-specific model input data obtained in Kyunggi Bay, we have formulated an effective approach for simulating the longterm behavior of the sediment plume and the change in surface sediments at the seabed. 2. Materials and methods 2.1. Study site, mining operation and field observations Kyunggi Bay has complex geometry. There are two major tidal channels on the west and the east sides of Deokjeok Island (Fig. 1), through which the shelf waters exchange with coastal waters. Numerous islands are distributed around the shallow part between the tidal channels with wide tidal flats during ebb tides. A shallow region around the Songap Island consists of tidal sand ridges and shallow sediment shoals that are several tens of kilometers long and a few kilometers wide. From the center axis of tidal channels with water depth of 30–50 m, the top

of sand ridges reaches up to the water depth of 2–5 m. Comprehensive field experiments measured with box cores and vibra-cores reveal that the sediment size ranges from coarse sand to fine silt, with composition varying between sites. However, the surface sediment extracted for construction material has been reported as the sand composition of more than 95%, indicating 1–5% of silt and clay. A hydraulically pumped mixture of water and sediment from the seabed passes through a pipe to the surface and then is poured into the vessel through a chute. A significant amount of seawater and small-size sediments spilled over the vessel, and are introduced to the surface layer of the sea. In Korea each dredge site has an identification number consisting of the site name and sequential numbers from 1 to 150 (e.g. Songap 90). Each site has dimension 10  10 (1 nautical mile  1 nautical mile). We selected three sites, Songap 90, Songap 80, and Songap 60 (Fig. 4) to investigate the dredging effects on sediment transport and surface sediment change. At these sites, more than 9 million m3 of marine sand have been extracted during the last 3 years, equivalent to 10,000 m3 per day at each site. In the present study, numerical experiment is conducted for dredging of 9 million m3 at three sites (3 million m3 at each site) in a 30-day operation to investigate long-term cumulative impacts of sediment dispersal and deposition. Since 2000, field experiments have been conducted around these sites to investigate the effects of marine sand extraction on the coastal environment. The experiments include hydrodynamic measurements and sediment measurements. In particular, the suspended sediment (SS) concentration is measured at various stages of the dredging

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process, such as mixture of seawater and bottom sediment at the chute, the over-spilled water and SS concentration profiles surrounding the dredging vessel, etc. Surface sediment samples have been collected and analyzed to characterize the size distribution. The temporal and spatial variation of the pit modeled in this study has been continuously monitored. In addition, although not used in this study, water quality, phyto- and zooplankton, and the benthic fauna have also been sampled intensively near the dredging sites. In the present study, the sediment parameters have been used to specify the source conditions for the model, and the hydrodynamic measurements have been used to assess the model performance. 2.2. The model ROMS is a 3D, free-surface, hydrostatic and primitive equation ocean model that uses stretched, terrain-following coordinates in the vertical and orthogonal curvilinear coordinates in the horizontal. The curvilinear coordinates allow some flexibility in variable cell sizes in the computation domain (Fig. 2), while the terrain-following coordinate (Fig. 3) can resolve the surface and bottom layers with higher resolution. In Kyunggi Bay, we use variable resolution in the horizontal with grid cells of approximately 1 km on the open boundary and 200 m in the vicinity of the extraction pits near the Songap Island. We use 20 levels in the vertical, with significant stretching near the top and bottom. For example, at Songap 90, in a water depth of 30 m, the bottom grid cell is 0.5 m thick and the surface grid cell is also 0.5 m thick. ROMS has a number of features that make it attractive for sediment transport simulations, including a choice of advanced turbulence closer schemes, a special scheme

for handling the advection and sinking of sediment to prevent unrealistic fluctuation and negative concentrations, a coupled wave-bottom boundary layer, handling of multiple sediment classes, and an active layer thickness that controls the amount of sediment that can be resuspended from the bottom (Blaas et al., 2007; Warner et al., 2008). The code can be run in either serial or parallel computers using openMP or MPI (Message-Passing Interface). The code uses a coarse-grained parallelization paradigm, which partitions the horizontal computational grid into tiles. For Kyunggi Bay, following Kim et al. (2004), we forced the model with high-resolution winds, heat flux and precipitation, as well as tides, river inputs, and waves. The surface forcing data are obtained from the modified MM5 hindcast result of every 6 h at every 9 km cell, and major tidal constituents are incorporated on the boundary forcing, supplied by Lee and Kim (2001). Table 1 shows the major tidal components at various points selected along the open boundary of computation domain in Fig. 2. By specifying the typical wave condition along with mostly prevailing northwesterly winds in winter, wave fields are estimated by using the Simulating Waves Nearshore (SWAN) model (Booij et al., 1999). The open boundaries are treated by nudging to data outside a sponge buffer. A detailed description of the model and its application in Kyunggi Bay is presented in Kim et al. (2004) and Kim and Lim (2007). 2.3. 3D equations of sediment transport In the s-coordinate of three-dimensional (3D) representation of ocean (x, y,s, t), the equation of sediment transport is as follows. In this study, sediment composition

38.0 SEOUL

LATITUDE(N)

37.5

INCHEON DeokjeokIs. SongapIs.

37.0

TAEAN

36.5 DAECHEON

124.5

125.0

125.5 126.0 LONGITUDE(E)

126.5

127.0

Fig. 2. The model grid, subsampled by a factor of 2, so that four actual grid cells are contained within each grid cell shown on the map. The curvilinear coordinate system grid size ranges from 200 m in the vicinity of Songap Island to more than 1 km in the outer shelf boundary region.

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0

-10 DEPTH (M)

Deokjeok Is. -20

-30

-40 126.00

125.75

126.25

126.50

LONGITUDE (E)

Fig. 3. A zonal view transecting Deokjeok Island of terrain-following vertical coordinate employed by ROMS model. The grid distribution in the vertical is stretched in a way such as to better resolve the surface and bottom layers.

Table 1 Tidal components at selected points along the open boundary Longitude (1E), latitude (1N)

124.70, 124.90, 125.50, 126.40,

38.00 37.00 36.30 36.14

S2

M2

K1

O1

Amplitude (cm)

Phase (deg)

Amplitude (cm)

Phase (deg)

Amplitude (cm)

Phase (deg)

Amplitude (cm)

Phase (deg)

86.7 111.1 147.0 203.4

174.2 114.0 87.9 80.8

29.5 38.5 50.4 70.0

220.0 162.3 136.5 130.1

32.1 26.8 27.3 32.3

322.9 303.9 284.5 275.6

21.7 18.7 19.1 22.2

296.9 280.0 262.8 254.1

of various sizes is allowed for sediment computation to discriminate the different behavior of particle size classes: qðDcÞ qðDucÞ qðDvcÞ qðDðw  ws ÞcÞ þ þ þ qt qx qy qs      q qc q qc kx þ ky ¼D qx qx qy qy   q qc kz þ þ DS w , D qs D qs

of sediment particles from the water column down to the seabed. Seabed erosion (Sb) can be expressed as a boundary condition (Harris and Wiberg, 2002): For tb4tce, Sb ¼ E o ð1  fÞ

(1)

where D(x, y, t) ¼ H(x, y)+Z(x, y, t), H(x, y) is the mean water depth, and Z(x, y, t) is the elevation of water surface. The velocities u, v, and w are horizontal and vertical components, respectively, while ws is for sinking velocity of sediment particle. c represents the concentration of each sediment size class. kx, ky, and kz are horizontal and vertical turbulent mixing coefficients, respectively. Eq. (1) is valid for each class of sediment size, which allows one to implement the model for sediment mixture composed of many different size groups. The sediment source/sink is represented by the term Sw that is comprised of two terms. The first is a surface source (Ss) arising from the surface plume spilled over the sand barge. The second is a bottom source (Sb) that is a combination of resuspension due to the action of the cutting head of the mining hydraulic pump and deposition

tb  tce , tce

(2)

where Eo and f are sediment source and porosity, tb is the combined wave and current bottom shear stress, and tce is the critical erosion stress for each sediment size class. Although a common formulation for the combined effect of waves and currents was developed by Grant and Madsen (1979), the use of this formula may be overtly complex, considering that the treatment of physical roughness is not straightforward and none of the models work particularly well (Lacy et al., 2005). Hence, in this study of using 3D ocean models, we adopt the simple formula for the combined effect of waves and currents in a tide-dominant regime (Haidvogel and Beckmann, 1999): qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi tb ¼ C D nb ðn2T þ u2b þ v2b Þ, (3) where CD is the quadratic drag coefficient, nb is the current representing the bottom layer, nT is the root mean square tidal current, and ub and nb are the wave orbital velocity components.

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The deposition at the seabed for each sediment size class can be expressed as follows: S d ¼ ws

qc qs

3. Results and discussion 3.1. Hydrodynamic simulation

at s ¼ 1,

(4) In many coastal and shelf waters, including Kyunggi Bay, the dominant factors for sediment transport are the energetic waves and strong tidal currents, which act not only to resuspend the sediment, but also to redistribute the sediment according to grain size characteristics (Davies et al., 2002; Harris and Wiberg, 2001, 2002). The sediment

where s ¼ 1 denotes the vertical position at the bottom. The surface source S is the most important parameter for quantitative sediment transport arising from the seabed sand mining and is given detailed treatment in the next section. 37.10

LATITUDE (N)

37.05 -2.5 -5 -5

37.00 Songap

36.95

2.5 -2.5 2.5 -5

90 80

60

Maximum Flood : 2m/s Variation (cm/s) -5 -2.5

36.90 126.00

0

2.5

5

126.05

126.10 126.15 LONGITUDE (E)

126.20

126.25

126.20

126.25

37.10

LATITUDE (N)

37.05

-2.5 -5

-5 2.5 Songap 90 80

37.00

36.95

2.5

2.5

-2.5

-5 60

Maximum Ebb : 2m/s Variation (cm/s) -5 -2.5

36.90 126.00

0

2.5

126.05

5 126.10 126.15 LONGITUDE (E)

Fig. 4. Modeled maximum flood currents (upper) and maximum ebb currents during spring tides, showing strong currents reaching up to 2.0 m/s flow along the tidal channels. The numbers represent the dredging sites of Songap 90, Songap 80, and Songap 60. Each dredging site is a one nautical mile square. Shaded contours are the variation of currents due to change in water depth arising from sand extraction at each site.

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the sediment that enters the environment during dredging operations and represent these conditions in a 3D model. In this study, we follow the approach suggested by MMS (1999a, b; Minerals Management Service, US Department of Interior) and Nairn et al. (2004) to estimate the sediment sources in the over-spilled water and at the bottom of Kyunggi Bay. Previous studies have found that the volume of pumped water from the seabed is approximately 10 times more than the volume of sand loaded in the barge (MMS, 1999a, b). Our field measurements show that approximately 10% of sediment discharged into the barge spills over into the surrounding water. The clamshell dredging activities (Tavolaro, 1984) in New York bight reveal that the barge-overflow volume is approximately 20% of loading capacity, and the dry mass of overflowed sediment may reach 34 t in 1-h operation. Considering the muddy sediment in shipping channel compared with the sand-rich sediment in this study, it is not surprising to show a factor of 2 differences comparable in the amount of sediment released to the plume. The over-spill sediment mixture consists mostly of medium silt (f5) and fine silt (f6) particles, where fI ¼ log2 R and R ¼ sediment diameter in millimeter. There is also a small fraction of sands in varying sizes (f1–f4) (MMS, 1999a, b; MOMAF, 2005). SS concentration and hydrodynamic processes have been measured by using the ADCP (Land et al., 1994), discrete water column samples, and continuous water column profiles using a CTD with optical backscattering sensor (OBS) and a light transmission gage.

mixture in the over-spill water is advected away from the dredging site and different size grains sink at different current speeds. Fig. 4 shows the maximum flood and ebb currents during spring tides in January 2003 in the area where the most extensive extraction has occurred. The maximum currents range from 1.3 to 1.8 m/s, with the strongest current along the tidal channel. The main axis of flow is NNE–SSW. During winter, the common northwesterly wind modifies the current speed as well as the direction, causing an eastward veering and reduction (10–20%) of the flood currents. The numbers 90, 80, and 60 in Fig. 4 represent the dredging site locations. There is a small but noticeable reduction in the simulated tidal currents due to the excavation of material in the vicinity of the simulated pits. 3.2. Sediment sources released in the surface and bottom layers The most important parameter in simulating the sediment transport arising from undersea sand mining operation is the amount of sediment released in the surface and at the bottom. Typically, environmental impact studies of dredging operations adopt a two-dimensional (2D) approach with a qualitative single-size sediment source, dealing with the surface plume only. Yet field observations reveal that there is significant three-dimensionality of sediment dispersion throughout the water column (MOMAF, 2005, 2006; Bai et al., 2003). Thus, it is essential to estimate the size class distribution of

SURFACE

2001.10.1216:00

37.12 A : Barge A B : Barge B C : Barge C

7.3

37.11 5

25

LATITUDE(N)

10

89.1

B

50

C

4.6 7.0 10

6.9

9.5 4.3

16.1

48.3 50 A 4.2

5

37.10

SS (mg/l)

5 37.09 126.22

15

25

35

45

55

126.23

126.24

126.25

LONGITUDE(E)

Fig. 5. Comparison of observed (black dots) and modeled (contour lines) sediment concentration distributions during seabed sand mining operation in Kyunggi Bay, Korea. The observed NTU units measured by OBS have been interpreted as SS in mg/l (determined by calibration).

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The observations show that in Kyunggi Bay, the sediment behavior arising from the undersea sand mining operation has significant time-evolving 3D features, as

found in several other studies of dredging operations (MOMAF, 2005; Land et al., 1994; MMS, 1999a, b). Using our data from Kyunggi Bay, we have determined

0 -5

Depth (m)

-10 -15 -20 -25 -30 -35 0

10

20 30 Turbidity (NTU)

40

50

0

10

20

40

50

0

Depth (m)

-5 -10 -15 -20 -25 -30 30 SS (mg/l) Ø3

Ø4

∑Ø

Ø5

Fig. 6. Comparison of observed (upper) and modeled (lower) vertical profiles of sediment concentration during seabed sand mining operation in Kyunggi Bay, Korea. The observed profile shows the concentration of all sizes of composition while simulated profiles show differentiation of contribution according to sediment size.

Table 2 Procedure for estimation of over-spill sediment volume released during sand mining operation in Kyunggi Bay, Korea Items

Values

Units

Remarks

Loading volume Overflow water

1000 10,000 0.0736 73,611,111 7950 7950 5300 2650 2650

m3/h m3/h t/s mg/s mg/l mg/l mg/l mg/l mg/l

2000 m3—capacity dredger 10 times of loading MMS (1999a, b)

Size Size Size Size Size

0.5 mm (30%) 0.25 mm (30%) 0.125 mm (20%) 0.0625 mm (10%) 0.0312 mm (10%)

5300 5300 5300 5300 5300

mg/l mg/l mg/l mg/l mg/l

Size Size Size Size Size

0.5 mm (20%) 0.25 mm (20%) 0.125 mm (20%) 0.0625 mm (20%) 0.0312 mm (20%)

Sediment in overflow 99%-sand; overflowing size fraction: 3:3:2:1:1

98%-sand, overflowing size fraction: 2:2:2:2:2

10% of loading MMS (1999a, b)

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3.3. Distribution of suspended sediment Fig. 7 illustrates the model result of the distribution of SS at sites Songap 90, 80, and 60 as shown in Fig. 4. The dredging sand is of 98%-sand; hence the over-spill water contains fine sands and silt/clay as f3:f4:f5 ¼ 2:2:2 as suggested in Section 3.2. The daily dredging volume at each site was 100,000 m3. The 30-day implementation (January 1–30, 2003) shows the distribution of SS dispersion in the surface layer (averaged over upper 5 m) expanding approximately 20 km in the direction of the major axis of tidal current and about 10 km in the direction of winds in winter. Surface concentrations rapidly come into equilibrium due to the relatively rapid speed with which the sediment sinks (Fig. 8). However, northwesterly surface winds and waves in winter play significant roles in the dispersal of silt/clay further eastward from the major tidal axis, which is coincident with the wave contribution to the silt dispersion in Blaas et al. (2007).

37.10 Qv = 300,000 m3/ day ∑ ∅ , DAY = 5

LATITUDE(N)

37.05 SG

90 80

60 1

2

37.00

1.5

1.5 0.5

36.95

0.5

1.5

1

2

1

1

SURFACE SS (mg/l) SS(mg/l) 0.5 0.75 1 1.25 1.5 1.75 2

126.05

126.10

126.15 126.20 LONGITUDE

126.25

126.30

37.10 0.5

3 Qv = 300,000 m / day

1

∑ ∅ , DAY = 10 1.5

LATITUDE(N)

37.05 SG

90 80

1

60 1.5

2

0.5 1

37.00

2 1.5

36.95

1

SURFACE SS (mg/l)

0.5 0.75 1 1.25 1.5 1.75 2

126.05

126.15 126.20 LONGITUDE

126.10

126.25

126.30

126.25

126.30

37.10 3 Qv = 300,000 m / day

0.5

∑ ∅ , DAY = 20

37.05 LATITUDE(N)

concentrations and particle size class distributions that we can use to specify the necessary parameters in the numerical model (Table 1). It is found that the SS source of each grain size in the overflowing water varies with the fraction of silt in the dredging sediments. For 99%-sand material the fractions (by volume) of the top 10% in the cumulative curve are estimated as f1:f2:f3:f4:f5 ¼ 3:3:2:1:1, while for the 98%-sand the ratio is f1:f2:f3: f4:f5 ¼ 2:2:2:2:2. Depending on the type of mixture, the fractions in each size class are then given different fall velocity in the numerical model. The fraction of each sediment size is used for 3D numerical simulation of sediment transport by employing a different fall velocity for each class. The f1–f2 sand falls down quickly and deposits at the seabed in the limit of a few hundred meters from the source, while the fine sands (f3 and f4) and silt and clay (f5) take longer to settle and so can be more widely dispersed before depositing, as demonstrated in Blaas et al. (2007). Fig. 5 shows the distribution of SS concentration observed (values in black dots) in the area of marine sand extraction for a situation in which three dredgers operated coincidently, and the simulated model results (in contour). The SS concentration in the surface plume of immediate vicinity to the dredging vessel is as high as 100 mg/l, and then the SS concentration decreases rapidly down to less than 5 mg/l within 1–2 km. The sediments introduced in the surface water undergo sinking and advection processes that differentiate sediment size classes. A sample of SS concentration profile at a remote station is shown in Fig. 6 (upper panel), while the lower panel shows the simulated SS profiles of different sizes. The total profiles of observed and simulated are in good agreement, indicating that prediction of 3D sediment dispersion is promising with this approach (Table 2).

201

SG

90 80

60 1

2

37.00

1.5 0.5

36.95

1

1.5

1.5

0.5 1

2

1

SURFACE SS (mg/l) SS(mg/l) 0.5 0.75 1 1.25 1.5 1.75 2

126.05

126.10

126.15 126.20 LONGITUDE

Fig. 7. Distribution of sediment concentration in the surface layer after 5, 10, and 20 days of continuous mining operation at sites Songap 90, 80, and 60. A 30-day simulation for 100,000 m3/day of 98%-sand extraction at each site has been conducted. The concentration values are averaged over the tidal cycle.

3.4. Change in surface sediments At the seabed, sediment reworking by the impacts of deposition of the dredge plume is very important to

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202

SG 90

80

0 -10

2

0.5

DEPTH (m)

-20

Qv = 300,000 m3 / d

60

2 1.5 1 0.5

2 1.5 1 0.5

1 1

1

-30 -40 ∑∅, DAY = 5

-50

SS (mg/l) -60 -70

SG 90

126.05

80

126.10

SG 90

0.5 0.75 1 1.25 1.5 1.75 2

60 126.15 126.20 LONGITUDE (E)

80

126.25

Qv = 300,000 m3 / d

60

0

DEPTH (m)

-20 -30

2 1.5 1

2 1.5

-10

0.5 1

126.30

0.5

2 1.5 1 0.5 1 2

1 2

1

0.5

-40 ∑∅, DAY = 10

-50

SS (mg/l) -60 -70 126.05

SG 90

80

126.10

SG 90 2

-10 0.5 DEPTH (m)

-20

126.15 126.20 LONGITUDE (E) 80

0

1

0.5 0.75 1 1.25 1.5 1.75 2

60

126.25

Qv = 300,000 m3 / d

60

2 1.5 1 0.5 0.5

2 1.5 1 0.5 1

126.30

0.5

-30 -40 ∑∅, DAY = 20

-50

SS (mg/l)

-60 -70 126.05

SG 90 126.10

80

0.5 0.75 1 1.25 1.5 1.75 2

60 126.15 126.20 LONGITUDE (E)

126.25

126.30

Fig. 8. Temporal variation of vertical profiles of sediment concentration under the same dredging intensity as in Fig. 7.

quantifying the redistribution of sediments and hence the change in surface sediments, even far from the dredging sites. Fig. 9 illustrates the simulation results showing the redistributed sediments of different sizes deposited in various areas away from the dredging sites. During winter, the 98%-sand delivers silt/clay to the coastal area, where it can be resuspended by the

combined action of waves and currents. The fine sands tend to deposit along the tidal channel, while the silt/clay materials are transported more widely by wind-driven currents, showing the different pattern of transport pathways as indicated in Blaas et al. (2007). Observations of sediment type around Sungbong Island (126.251E, 37.21N) showed a change in surface sediments from rocky

ARTICLE IN PRESS C.S. Kim, H.-S. Lim / Continental Shelf Research 29 (2009) 194–204

LATITUDE (N)

37.2

37.1

sediment at the seabed would assist with further investigation of benthic habitat change.

Qv = 300,000 m3 / day ∅=3 Deposition DAY = 20

4. Conclusions SG 90 80 60 10

37.0

50

50 10

10 36.9

36.8

Δη (mm) 10 20 30 40 50

125.9

LATITUDE (N)

37.2

37.1

126.0 126.1 LONGITUDE (E)

126.2

126.3

Qv = 300,000 m3 / day ∅=4 Deposition DAY = 20 SG 90 80 60 10

37.0

50

50 10

10 36.9 Δη (mm)

36.8

10 20 30 40 50

125.9

LATITUDE (N)

37.2

37.1

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Qv = 300,000 m3 / day ∅=5 Deposition DAY = 20

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The methodology established using a combination of field measurements and 3D sediment transport modeling in Kyunggi Bay appears to be promising. The model can represent the 3D structure of observed sediment concentrations as well as observed patterns of sediment redistribution. Size-dependent behavior and characterization of the sediment sources were both critical to reproduction of the observed sediment redistribution, allowing material with faster settling velocity to be differentiated from material with slower settling velocity. In the marine sand operation optimized for Kyunggi Bay, the volume of pumped water from the seabed is approximately 10 times more than the volume of sand loaded in the barge, while approximately 10% of loading sediment overflows into the surrounding water. It is found that the particle size class distribution in the overflowing water varies with the contents of silt and clay in the dredging sediment. For 99%-sand material, the fractions (by volume) of the top 10% in the cumulative curve is estimated as f1:f2:f3:f4:f5 ¼ 3:3:2:1:1, while for the 98%-sand the ratio is f1:f2:f3:f4:f5 ¼ 2:2:2:2:2. A 30-day simulation for 98%-sand extraction at 300,000 m3/day was conducted to investigate the long-term cumulative impact on the sediment dispersal and deposition in winter. During winter, the 98%-sand delivers the silt/clay to the coastal area as far as 20 km from the dredging site, where it can be resuspended by the combined action of waves and currents. The fine sands tend to deposit along the tidal channel, while the silt/clay materials are transported more widely by wind-driven currents, suggesting different transport pathways. Future work is needed to improve simulation of the resuspension process in this region for more quantitative prediction of seabed change arising from long-term dredging of marine sand.

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Fig. 9. Redistribution of sediment deposition at the seabed after 20 days of mining operation as in Fig. 7. Each plot of different grain size shows the different reworking and redistribution processes, which is directly linked to the change in surface sediments and in benthic habitats.

to muddy, and from sandy beaches to muddy beds (MOMAF, 2005). In the present study, the potentially important mechanism of resuspension by tidal currents and wind waves is not included in simulation. The qualitative change in surface

This research work is supported by the Ministry of Maritime Affairs and Fisheries Korea through Grant PM43707, and by KORDI through the Coastal Disaster Prevention Program (PM50000) and Estuary Restoration Project (PE9811A). The authors gratefully acknowledge Dr. Richard P. Signell of USGS for his scientific comments and careful scrutiny in English of the manuscript. Without his help and the editor (Prof. D. Jay of Portland State University)’s guide, this paper would not be possible. References Bai, Y., Wang, Z., Shen, H., 2003. Three-dimensional modeling of sediment transport and the effects of dredging in the Haihe Estuary. Estuarine, Coastal and Shelf Science 56, 175–186.

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Basco, D., 1999. A methodology and criteria to assess the impact of sand volume removed in Federal Waters on the nearshore waves climate. Technical Report MMS OCS 99-0046, Old Dominion University, Virginia, p. 74. Blaas, M., Dong, C., Marchesiello, P., McWilliams, J.C., Stolzenbach, K.D., 2007. Sediment-transport modeling on Southern Californian shelves: a ROMS case study. Continental Shelf Research 27, 832–853. Booij, N., Ris, R.C., Holthuijsen, L.H., 1999. A third-generation wave model for coastal regions. Part I. Model description and validation. Journal of Geophysical Research 104 (C4), 7649–7666. Boyd, S.E., Rees, H.L., 2003. An examination of the spatial scale of impact on the marine benthos arising from marine aggregate extraction in the central English Channel. Estuarine, Coastal and Shelf Science 57, 1–16. Davies, A.G., van Rijn, L.C., Damgaard, J.S., van de Graaff, J., Ribberink, J.S., 2002. Intercomparison of research and practical sand transport models. Coastal Engineering 46, 1–23. Grant, W.D., Madsen, D.S., 1979. Combined wave and current interaction with a rough bottom. Journal of Geophysical Research 84 (C4) (1), 1797–1808. Haidvogel, D.B., Beckmann, A., 1999. Numerical Ocean Circulation Modeling. Imperial College Press, London, 320pp. Harris, C.K., Wiberg, P.L., 2001. A two-dimensional, time-dependent model of suspended sediment transport and bed reworking for continental shelves. Computers and Geosciences 27, 675–690. Harris, C.K., Wiberg, P.L., 2002. Across-shelf sediment transport: interactions between suspended sediment and bed sediment. Journal of Geophysical Research 107 (C1). Hong, G.H., Zhang, J., Kim, S.H., Chung, C.S., Yang, S.R., 2002. East Asian marginal seas: river-dominated ocean margin. In: Hong, G.H., Zhang, J., Chung, CS. (Eds.), Impact of Interface Exchange on the Biogeochemical Processes of the Yellow and East China SEAS. Bum Shin Press, Seoul, pp. 233–251. Kim, C.S., Lim, H.S., 2007. Safety criteria on water depth, offshore distance and dredging volume in marine sand mining operation in Kyunggi Bay, Korea. Journal of Coastal Research SI 50, 507–510. Kim, C.S., Lim, H.S., Yoon, J.J., Qiao, F., 2004. Numerical simulation of hydrodynamics and water properties in the Yellow Sea. Journal of Korean Society of Oceanography 39 (1), 72–95. Lacy, J.R., Sherwood, C.R., Wilson, D.J., Chrisholm, T.A., Gefenbaum, C.R., 2005. Estimating hydrodynamics roughness in a wave-domi-

nated environment with a high-resolution acoustic Doppler profiler. Journal of Geophysical Research 110, C06014. Land, J., Kirby, R., Massey, J.B., 1994. Recent innovations in the combined use of ADCP and profiling silt meters for suspended solid monitoring. In: Proceedings of the Fourth Nearshore and Estuarine Cohesive Sediment Transport Conference. Hydraulic Research, Wallingford, UK, pp. 1–10. Large, W.G., McWiliams, J.C., Doney, S.C., 1994. A review and model with a non-local boundary layer parameterization. Review of Geophysics 32, 363–403. Lee, J.C., Kim, C.S., 2001. Tide computation in the northeast asian seas using Topex/Poseidon altimetry data. Journal of Korean Society of Oceanography, Bada 6, 1–12 (abstract in English). MMS, 1999a. Marine aggregate mining; benthic and surface plume study. Technical Report MMS study number 99-0029. MMS, 1999b. Guidelines for obtaining minerals other than oil, gas & sulphur on the outer continental shelf. Technical Report, MMS Report 99-0070. MOMAF, 2005. Environmental impact study for undersea sand mining in coastal/shelf waters (I). Technical Report, p. 861 (in Korean). MOMAF, 2006. Environmental impact study for undersea sand mining in coastal/shelf waters (II). Technical Report, p. 950 (in Korean). Nairn, R., Johnson, J.A., Hardine, D., Michel, J., 2004. A biological and physical monitoring program to evaluate long-term impacts from sand dredging operations in the United States outer continental shelf. Journal of Coastal Research 20, 126–137. Simons, R., Hollingham, S.M., 2001. Marine aggregate dredging: a review of current procedures for assessing coastal processes and impact at the coastline. Technical Report HYD10401, UCL, London, p. 80. Song, Y., Haidvogel, D.B., 1994. A semi-implicit ocean circulation model using a generalized topography-following coordinate. Journal of Computational Physics 115, 228–244. Tavolaro, J.F., 1984. A sediment budget study of clamshell dredging and ocean disposal activities in the new work bight. Environmental Geology and Water Science 6 (3), 133–140. Warner, J.C., Sherwood, C.R., Signell, R.P., Harris, C.K., Arango, H.G., 2008. Development of a three-dimensional, regional, coupled wave, current, and sediment-transport model. Computers and Geosciences (Accepted).