Predictability of Seabed Change du Predictability of Seabed Change du e to Underwater Sand Mining in e to Underwater Sand Mining in Coastal Waters of Korea Coastal Waters of Korea Chang S. Kim, Hak Soo Lim and Jinah Chang S. Kim, Hak Soo Lim and Jinah Kim Kim Korea Ocean R&D Institute Korea Ocean R&D Institute Coastal Engineering Division Coastal Engineering Division 1270 Sa2Dong Ansan 426-744 South Ko 1270 Sa2Dong Ansan 426-744 South Ko rea. rea. [email protected][email protected]2006ROMS/TOMS Europe Nov 6-8, 2006 Alcala De Henares Spain
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Predictability of Seabed Change due to Underwater Sand Mining in Coastal Waters of Korea Predictability of Seabed Change due to Underwater Sand Mining.
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Predictability of Seabed Change due to UnderwaPredictability of Seabed Change due to Underwater Sand Mining in Coastal Waters of Korter Sand Mining in Coastal Waters of Koreaea
Chang S. Kim, Hak Soo Lim and Jinah KimChang S. Kim, Hak Soo Lim and Jinah Kim
AbstractAbstract Numerical modeling and field experiment have been conducted to predict the seabed change due to underwater sand mining in coastal waters of Korea. The macro-tidal Kyunggi Bay is approximately 20,000 km2, where underwater sand has been extracted approximately more than 20 million m3 annually. Suspended sediment (SS) transport in the water column and sea bed has been a critically important issue to many concerns. In this study, we present the numerical prediction of sediment transport processes such as SS dispersion and consequent change in sediment types in sea bottom. We use full 3-D model ROMS to implement the sediment dynamics by adopting the extensively observed field data associated with modeling inputs and model validation.
Seabed Sand Mining Area Seabed Sand Mining Area in Kyunggi Bay, Koreain Kyunggi Bay, Korea
Source Concentrations of SS in Source Concentrations of SS in Kyunggi BayKyunggi Bay
Dredging Dredging Volume /hrVolume /hr
1,0001,000 mm33/hr/hr 300,000m300,000m33//
12.5 days12.5 days
SS Flux in Over-SS Flux in Over-spilled Waterspilled Water
73.6173.61 kg/skg/s Pumping Water VolumPumping Water Volume : 10 x Loading Volue : 10 x Loading Volumeme
SS Spilled : 10% od LSS Spilled : 10% od Loading Volume (MMS, oading Volume (MMS, 1999)1999)
99%Sand: 99%Sand: Composition of Composition of Spilled SSSpilled SS
0.5:0.25:0.125:0.5:0.25:0.125:
0.0625:0.031250.0625:0.03125
mmmm
3:3:2:1:3:3:2:1:11
7950:7950:7950:7950:
5300:2650:5300:2650:
2650 mg/l2650 mg/l
98%Sand 98%Sand Composition of Composition of Spilled SSSpilled SS
0.5:0.25:0.125:0.5:0.25:0.125:
0.0625:0.031250.0625:0.03125
mmmm
2:2:2:2:2:2:2:2:22
5300:5300:5300:5300:
5300:5300:5300:5300:
5300 mg/l5300 mg/l
Volume =3,000,000 m3 / 12.5day
Ø1:Ø2:Ø3:Ø4:Ø5 = 2:2:2:2:2
SS Dispersion (Started during Spring Tide)SS Dispersion (Started during Spring Tide)
BottomBottom
SurfaceSurface
Volume =3,000,000 m3 / 12.5day
Ø1:Ø2:Ø3:Ø4:Ø5 = 2:2:2:2:2
SS Dispersion (Started During Neap Tide)SS Dispersion (Started During Neap Tide)
BottomBottom
SurfaceSurface
126.22 126.23 126.24 126.2537.09
37.10
37.11
37.12
LA
TIT
UD
E(N
)
LONGITUDE (E)
2001.10.12 16:00
BC
A
505
SURFACE
126.22 126.23 126.24 126.2537.09
37.10
37.11
37.12
LA
TIT
UD
E(N
)
LONGITUDE (E)
2001.10.12 18:00
BC
A5
5
SURFACE
126.22 126.23 126.24 126.2537.09
37.10
37.11
37.12
LA
TIT
UD
E(N
)
LONGITUDE (E)
2001.10.12 20:00
BC
A
5
5
SURFACE
5
126.22 126.23 126.24 126.2537.09
37.10
37.11
37.12
LA
TIT
UD
E(N
)
LONGITUDE (E)
2001.10.12 14:00 ~16:00
A
BC
4.3mg/l
89.0mg/l
: Barge C
9.5mg/l4.6mg/l
16.1mg/l
A
6.9mg/l
CB
: Barge A: Barge B
4.2mg/l
48.3mg/l
7.3mg/l
7.0mg/l
Field Experiment conducted between 14:00 -16:00 on October 12, 2001 in Kyunggi Bay.
Model Validation with Field Observed DataModel Validation with Field Observed Data (2,000 m (2,000 m3 3 3 3 Barges )Barges )
Vertical Profiles of SS Concentration Observed and Simulated for 14:00-16:00 on October12, 2001 in Kyunggi Bay.
Comparison of Model Results and Field Comparison of Model Results and Field Observed DataObserved Data
Tidal current of 0.5 m/s Extractuin Volume 300,000 m3
15 20 25 30 355
10
15
X (km)
Y (km)
SS (mg/l)
BOTTOMTidal Current = 0.5 m/sQ = 300,000 m /12.5daysD + 1
3v
5
1Ø3
+
15 20 25 30 355
10
15
X (km)
Y (km)
SS (mg/l)
BOTTOMTidal Current = 0.5 m/sQ = 300,000 m /12.5daysD + 1
3v
51
1
15
1
Ø4
+
15 20 25 30 355
10
15
X (km)
Y (km)
SS (mg/l)
BOTTOMTidal Current = 0.5 m/sQ = 300,000 m /12.5daysD + 1
3v
1
Ø5
+
15 20 25 30 355
10
15
1 2 3 4 5
X (km)
Y (km)
SS (mg/l)
BOTTOMTidal Current = 0.5 m/sQ = 300,000 m /12.5daysD + 1
3v
∑Ø
+
SS Redistribution at Seabed Based on Particle Size SS Redistribution at Seabed Based on Particle Size (Model Results)(Model Results)
ConclusionsConclusions In this study, a numerical approach using the fully 3-D model ROMS In this study, a numerical approach using the fully 3-D model ROMS
has been conducted to investigate the sediment dynamics arising has been conducted to investigate the sediment dynamics arising from the undersea sand mining operation. Fundamental parameters from the undersea sand mining operation. Fundamental parameters required for model implementation have been obtained through required for model implementation have been obtained through extensive field experiments done in Kyunggi Bay in Korea. extensive field experiments done in Kyunggi Bay in Korea.
The estimation of sediment source concentration adapted in this The estimation of sediment source concentration adapted in this study might be very useful for application to other site-specific area. study might be very useful for application to other site-specific area.
The bottom sediment composition is very important to predict the The bottom sediment composition is very important to predict the habit change at the seabed. Three-dimensional evolution of habit change at the seabed. Three-dimensional evolution of sediment transport shows a variety of dependent parameters on sediment transport shows a variety of dependent parameters on environmental impacts, particularly on the geologic change in environmental impacts, particularly on the geologic change in benthic habitat. benthic habitat.