OCS Study 

MMS-2001-098 

FINAL REPORT – November 2001 

NUMERICAL MODELING EVALUATION OF THE 

CUMULATIVE PHYSICAL EFFECTS OF OFFSHORE 

SAND DREDGING FOR BEACH NOURISHMENT 

Prepared by: 

Sean W. Kelley 

John S. Ramsey 

Mark R. Byrnes 

Applied Coastal Research and Engineering, Inc. 

766 Falmouth Road, Suite A-1 

Mashpee, MA 02649

Prepared for: 

U.S. Department of the Interior 

Minerals Management Service 

International Activities and Marine 

Minerals Division (INTERMAR) 

Funded Under Contract Number 1435-01-99-CT-30993 
DISCLAIMER 

This report has been reviewed by the Minerals Management Service and approved for 

publication. Approval does not signify that the contents necessarily reflect the views and 

policies of the Service, nor does mention of trade names or commercial products 

constitute endorsement or recommendation for use. 

SUGGESTED CITATION 

Kelley, S.W., J.S. Ramsey, M.R. Byrnes, 2001. Numerical Modeling Evaluation of the 

Cumulative Physical Effects of Offshore Sand Dredging for Beach Nourishment. U.S. 

Department of the Interior, Minerals Management Service, International Activities and 

Marine Minerals Division (INTERMAR), Herndon, VA. OCS Report MMS 2001-098, 95 

pp. + 106 pp. appendices. 
OCS Study 

MMS-2001-098 

FINAL REPORT 

Numerical Modeling Evaluation Of The Cumulative Physical 

Effects Of Offshore Sand Dredging For Beach Nourishment 

November 2001 

Sean W. Kelley 

John S. Ramsey 

Mark R. Byrnes

Prepared by: 

Applied Coastal Research and Engineering, Inc. 

766 Falmouth Road, Suite A-1 

Mashpee, MA 02649 

Prepared for: 

U.S. Department of the Interior 

Minerals Management Service 

International Activities and Marine 

Minerals Division (INTERMAR) 

Funded Under Contract Number 1435-01-99-CT-30993 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

ACKNOWLEDGMENTS 

This project was funded by the U.S. Department of the Interior (DOI), Minerals 

Management Service (MMS), International Activities and Marine Minerals Division 

(INTERMAR) under Contract #1435-01-99-CT-30993. Mr. Barry S. Drucker was the 

MMS Contracting Officer’s Technical Representative (COTR) and provided valuable 

assistance throughout the project. Ms. Jane Carlson served as the MMS Contracting 

Officer. Mr. Barry Drucker and Mr. Roger Amato of the MMS reviewed the draft 

document. 

 Mr. Sean W. Kelley authored Sections 3.0 (Modeling Approach and Applications), 

4.0 (Cumulative Impacts), and Appendices B through E. Mr. John S. Ramsey authored 

Sections 2.0 (Physical Processes) and 5.0 (Conclusions). Dr. Mark R. Byrnes served as 

Project Manager and Editor of the report, and authored Section 1.0 (Introduction). Ms. 

Elizabeth Hunt was responsible for report compilation and editorial assistance during 

production of the report. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

i 

TABLE OF CONTENTS 

1.0 INTRODUCTION........................................................................................................1

1.1 STUDY PURPOSE.................................................................................................2

1.2 STUDY AREAS AND BORROW SITE CHARACTERISTICS ................................2

1.3 STUDY APPROACH ..............................................................................................6

1.4 DOCUMENT ORGANIZATION ..............................................................................7

2.0 PHYSICAL PROCESSES..........................................................................................8

2.1 NEARSHORE WAVE TRANSFORMATION ..........................................................8

2.2 NEARSHORE SEDIMENT TRANSPORT PATTERNS........................................10

2.3 IDEALIZED OFFSHORE BORROW SITE ...........................................................11

2.4 SIGNIFICANCE OF BORROW SITE IMPACTS ..................................................16

2.4.1 Available Methods for Assessing Borrow Site Impacts..................................17

2.4.2 Reference Line Statistical Approach..............................................................18

2.4.3 Potential Uncertainties in Wave Information Approach .................................19

2.4.4 Spatial and Temporal Variations in Wave Climate Approach ........................20

3.0 MODELING APPROACH AND APPLICATIONS....................................................23

3.1 ANALYSIS APPROACH.......................................................................................23

3.1.1 Wave Modeling ..............................................................................................23

3.1.2 Input Spectra Development ...........................................................................25

3.1.2.1 Southern New Jersey WIS Data..............................................................25

3.1.2.2 Southeastern Virginia WIS Data..............................................................25

3.1.2.3 North Carolina WIS Data.........................................................................27

3.1.2.4 Cape Canaveral WIS Data......................................................................28

3.1.2.5 Development of Model Spectra from WIS Data ......................................28

3.1.2.6 Spectral Development from Wave Buoy Data.........................................33

3.1.3 Grid Development..........................................................................................35

3.1.4 Sediment Transport Potential ........................................................................44

3.2 MODEL RESULTS ...............................................................................................45

3.2.1 Wave Modeling ..............................................................................................45

3.2.1.1 Offshore New Jersey...............................................................................48

3.2.1.2 Offshore Southeastern Virginia ...............................................................52

3.2.1.3 Offshore North Carolina ..........................................................................57

3.2.2 Sediment Transport Potential ........................................................................64

3.2.2.1 Model Comparison with Historical Shoreline Change .............................64

3.2.2.2 Modeled Transport and Dredging Impacts..............................................73

3.2.2.3 Dredging Impacts at East Coast Sites.....................................................80

4.0 CUMULATIVE IMPACTS ........................................................................................82

4.1 SITES IN CLOSE PROXIMITY.............................................................................82

4.2 MULTIPLE DREDGING EVENTS AT A SINGLE SITE ........................................85

5.0 CONCLUSIONS.......................................................................................................88

5.1 WAVE MODEL ASSESSMENT.............................................................................88

5.2 MANAGEMENT TOOL FOR ASSESSING IMPACT SIGNIFICANCE...................89

5.3 WAVE AND SEDIMENT TRANSPORT ANALYSIS ..............................................90

5.4 APPLICATION OF MANAGEMENT TOOL ...........................................................91

5.5 CUMULATIVE EFFECTS ......................................................................................92

6.0 REFERENCES.........................................................................................................93
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

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APPENDIX A: COMPARISON OF NUMERICAL SPECTRAL WAVE 

TRANSFORMATION MODELS FOR EVALUATING THE 

PHYSICAL ENVIRONMENTAL IMPACTS OF OFFSHORE 

SAND MINING..................................................................................... A-1 

APPENDIX B: NEW JERSEY WAVE MODEL OUTPUT............................................ B-1

APPENDIX C: VIRGINIA WAVE MODEL OUTPUT ................................................... C-1 

APPENDIX D: NORTH CAROLINA WAVE MODEL OUTPUT................................... D-1

APPENDIX E: FLORIDA WAVE MODEL OUTPUT.................................................... E-1
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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LIST OF FIGURES 

Figure 1-1. Location diagram illustrating sand borrow sites M8 (USACE 

designation), A1 and A2 (NJ State designation), and State-Federal 

boundary relative to 1934/77 bathymetry. ................................................. 3

Figure 1-2. Location diagram illustrating sand borrow sites A and B and StateFederal boundary relative to 1934/77 bathymetry. .................................... 4

Figure 1-3. Location diagram illustrating sand borrow sites 3 West and 3 East 

and State-Federal boundary relative to 1934/77 bathymetry. ................... 5

Figure 1-4. Location diagram illustrating sand Borrow Site II and StateFederal boundary relative to 1934/77 bathymetry. .................................... 6

Figure 2-1. Diagram illustrating the effects of refraction and diffraction as 

waves approach the coastline (from Svendsen and Jonsson, 

1976). ...................................................................................................... 10

Figure 2-2. Surface plot with 2.5 m contours of bathymetry grid used for 

idealized borrow site model runs. ............................................................ 12

Figure 2-3. Example color contour plot of modeled wave heights, with vectors 

indicating mean wave direction for idealized borrow site (incident 

wave height of 1.2 m and period of 8 sec approaching shoreline at 

-30o from shore-normal)........................................................................... 13

Figure 2-4. Color surface plot of wave height difference (Hpost - Hpre) resulting 

from borrow site excavation, for wave case shown in Figure 2-3............ 13

Figure 2-5. Computed annualized longshore sediment transport potential for 

idealized borrow site for five wave cases. ............................................... 14

Figure 2-6. Change in computed longshore sediment transport potential for 

idealized borrow site................................................................................ 14

Figure 2-7. Computed cross-shore change in shoreline position based on 

modifications to longshore sediment transport potential by 

idealized borrow site................................................................................ 15

Figure 2-8. Change in computed longshore sediment transport potential 

based on alternate distribution of wave percent occurrences. ................ 16

Figure 2-9. Computed cross-shore change in shoreline position based on 

modifications to longshore sediment transport potential using 

alternate distribution of wave percent occurrences. ................................ 16

Figure 2-10. Percent change in wave energy showing regions of acceptance 

and rejection of the null-hypothesis using ≥ 4.0 percent as the cutoff value (from Basco, 1999). .................................................................. 18

Figure 2-11. Example of results for spatial/temporal variability method for 

determining significance of borrow site dredging impacts. Plots of 

modeled net transport potential and post-dredging change in 

transport for borrow sites located offshore Sandbridge, Virginia. 

Middle plot shows dredging significance criterion envelope (±σ) 

determined for this shoreline. The left plot of the shoreline is 

given for reference................................................................................... 21

Figure 3-1. Diagram of wave and current vectors used in STWAVE (from 

Smith et al., 1999). Subscript a denotes values in the absolute

frame of reference, and subscript r denotes values in the relative

frame of reference (with currents). .......................................................... 24
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

iv 

Figure 3-2. Shoreline from New Jersey to North Carolina with coarse grid 

limits and wave input data stations used to determine dredging 

impacts from offshore sand mining.......................................................... 26

Figure 3-3. Wave height and period for hindcast data from WIS station 

AU2067 (offshore New Jersey) for the 20-year period between 

January 1976 and December 1995. Direction indicates from 

where waves were traveling, relative to true north. Radial length 

of gray tone segments indicates percent occurrence for each 

range of wave heights and periods. Combined length of segments 

in each sector indicate percent occurrence of all waves from that 

direction................................................................................................... 27

Figure 3-4. Wave height and period for hindcast data from WIS station 

AU2058 (offshore southern Virginia) for the 20-year period 

between January 1976 and December 1995. Direction indicates 

from where waves were traveling, relative to true north. Radial 

length of gray tone segments indicates percent occurrence for 

each range of wave heights and periods. Combined length of 

segments in each sector indicate percent occurrence of all waves 

from that direction.................................................................................... 27

Figure 3-5. Wave height and period for hindcast data from WIS station 

AU2056 (offshore North Carolina) for the 20-year period between 

January 1976 and December 1995. Direction indicates from 

where waves were traveling, relative to true north. Radial length 

of gray tone segments indicates percent occurrence for each 

range of wave heights and periods. Combined length of segments 

in each sector indicate percent occurrence of all waves from that 

direction................................................................................................... 28

Figure 3-6. East Florida shoreline at Cape Canaveral with coarse grid limits 

and wave input data station used to determine dredging impacts 

from offshore sand mining. ...................................................................... 29

Figure 3-7. Wave height and period for hindcast data from WIS station 

AU2019 (Cape Canaveral) for the 20-year period between 

January 1976 and December 1995. Direction indicates from 

where waves were traveling, relative to true north. Radial length 

of gray tone segments indicates percent occurrence for each 

range of wave heights and periods. Combined length of segments 

in each sector indicate percent occurrence of all waves from that 

direction................................................................................................... 29

Figure 3-8. Example of STWAVE input spectrum developed using WIS 20-

year hindcast data and Goda method of computing frequency and 

direction spectrum. Plots show a) frequency distribution of energy 

at peak direction, b) directional distribution of energy at peak 

frequency, and c) surface plot of two-dimensional energy 

spectrum. Example is model case 5 (Hmo = 0.9 m, θmean = 130° 

grid relative)............................................................................................. 31
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

v 

Figure 3-9. Wave height and wave period roses for data recorded by NDBC 

buoy 44014 (offshore Virginia Beach) for the 5-year period 

between January 1996 and December 2000. Direction indicates 

the direction waves were propagating from relative to true north. 

Radial length of gray tone segments indicates percent occurrence 

of each range of wave condition (height or period). Combined 

length of segments in each sector indicates percent occurrence of 

all waves from that direction.................................................................... 33

Figure 3-10. Color contour plot of coarse model grid (200 m x 200 m grid 

spacing) of offshore New Jersey. Depths are relative to NVGD. 

Borrow site locations are indicated by solid black lines, and fine 

grid limits are indicated by a dashed line................................................. 36

Figure 3-11. Color contour plot of the nested fine model grid (20 m x 20 m grid 

spacing) used with STWAVE for offshore New Jersey. Depths are 

relative to NVGD. Borrow site location is indicated by solid black 

line, and fine grid limits are indicated by dashed line. ............................. 37

Figure 3-12. Color contour plot of coarse model grid (200 m x 200 m grid 

spacing) of offshore southeastern Virginia. Depths are relative to 

NVGD. Borrow site locations are indicated by solid black lines, 

and fine grid limits are indicated by a dashed line................................... 38

Figure 3-13. Color contour plot of the nested fine model grid (20 m x 20 m grid 

spacing) of offshore southern Virginia used with STWAVE. 

Depths are relative to NVGD. Borrow site location is indicated by 

solid black line, and fine grid limits are indicated by dashed line. ........... 39

Figure 3-14. Color contour plot of coarse model grid (200 m x 200 m grid 

spacing) for offshore North Carolina. Depths are relative to 

NVGD. Borrow site locations are indicated by solid black lines, 

and fine grid limits are indicated by a dashed line................................... 40

Figure 3-15. Color contour plot of the nested fine model grid (20 m x 20 m grid 

spacing) for offshore North Carolina. Depths are relative to 

NVGD. Borrow site location is indicated by solid black line, and 

fine grid limits are indicated by dashed line............................................. 41

Figure 3-16. Color contour plot of coarse model grid (200 m x 200 m grid 

spacing) for offshore Cape Canaveral, FL. Depths are relative to 

NVGD. Borrow site locations are indicated by solid black lines, 

and fine grid limits are indicated by a dashed line................................... 42

Figure 3-17. Color contour plot of the nested fine model grid (20 m x 20 m grid 

spacing) for offshore Cape Canaveral, FL. Depths are relative to 

NVGD. Borrow site location is indicated by solid black line, and 

fine grid limits are indicated by dashed line............................................. 43

Figure 3-18. Example of coarse grid wave height difference plot between 

existing and post-dredging bathymetry conditions offshore 

Townsends Inlet, NJ. This result is for NJ wave case 7; 1.6 m 

wave height and 11.1 sec period............................................................. 46

Figure 3-19. Example of fine grid wave height difference plot between existing 

and post-dredging bathymetry conditions offshore Townsends 

Inlet, NJ. This result is for NJ wave case 7; 1.6 m wave height 

and 11.1 sec period................................................................................. 47
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

vi 

Figure 3-20. Coarse grid model results for offshore North Carolina (wave case 

9; 1.3 m wave height, 11.3 sec period) illustrating area of reduced 

wave heights resulting from refraction of wave energy due to 

bottom bathymetry................................................................................... 48

Figure 3-21. Coarse grid model results for Sandbridge Shoal, Virginia for wave 

case 10 (1.8 m wave height, 10.0 sec wave period) showing wave 

focusing effect of natural shoal deposits and area of reduced wave 

heights to the southwest of the shoals. ................................................... 49

Figure 3-22. Fine grid model results for Sandbridge Shoal, Virginia for the 

same wave case presented in Figure 3-21. Detailed analysis 

illustrates nearshore refraction of waves and wave height 

reductions through the width of the surf zone.......................................... 49

Figure 3-23. Plot of STWAVE model output for southern New Jersey wave 

Case 4 (Hs=1.2 m, Tpeak=7.1 sec, θpeak=131 deg). Color contours 

indicate wave height, and vectors show mean direction of wave 

propagation.............................................................................................. 50

Figure 3-24. Plot of STWAVE model output for southern New Jersey wave 

Case 7 (Hs=1.6 m, Tpeak=11.1 sec, θpeak=81 deg). Color contours 

indicate wave height, and vectors show mean direction of wave 

propagation.............................................................................................. 51

Figure 3-25. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at indicated borrow sites for STWAVE 

model output of southern New Jersey wave Case 4 (Hs=1.2 m, 

Tpeak=7.1 sec, θpeak=131 deg)................................................................... 52

Figure 3-26. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at indicated borrow sites for STWAVE 

model output of southern New Jersey wave Case 7 (Hs=1.6 m, 

Tpeak=11.1 sec, θpeak=81 deg)................................................................... 53

Figure 3-27. Plot of STWAVE model output for southeastern Virginia wave 

Case 7 (Hs=2.8 m, Tpeak=11.1 sec, θpeak=39 deg). Color contours 

indicate wave height, and vectors show mean direction of wave 

propagation.............................................................................................. 54

Figure 3-28. Plot of STWAVE model output for southeastern Virginia wave 

Case 10 (Hs=1.8 m, Tpeak=10.0 sec, θpeak=134 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................... 55

Figure 3-29. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at borrow sites A and B for STWAVE 

model output for southeastern Virginia wave Case 7 (Hs=2.8 m, 

Tpeak=11.1 sec, θpeak=39 deg)................................................................... 56

Figure 3-30. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at borrow sites A and B for STWAVE 

model output for southeastern Virginia wave Case 10 (Hs=1.8 m, 

Tpeak=10.0 sec, θpeak=134 deg)................................................................. 57

Figure 3-31. Plot of STWAVE model output for offshore North Carolina wave 

Case 2 (Hs=1.9 m, Tpeak=6.0 sec, θpeak=21 deg). Color contours 

indicate wave height, and vectors show mean direction of wave 

propagation.............................................................................................. 58
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

vii 

Figure 3-32. Plot of STWAVE model output for offshore North Carolina wave 

Case 8 (Hs=1.5 m, Tpeak=12.8 sec, θpeak=71 deg). Color contours 

indicate wave height, and vectors show mean direction of wave 

propagation.............................................................................................. 59

Figure 3-33. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at borrow sites 3 East and 3 West for 

STWAVE model output for offshore North Carolina wave Case 2 

(Hs=1.9 m, Tpeak=6.0 sec, θpeak=21 deg)................................................... 60

Figure 3-34. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at borrow sites 3 East and 3 West for 

STWAVE model output for offshore North Carolina wave Case 8 

(Hs=1.5 m, Tpeak=12.8 sec, θpeak=71 deg)................................................. 61

Figure 3-35. Plot of STWAVE model output for Cape Canaveral, Florida wave 

Case 3 (Hs=1.0 m, Tpeak=7.7 sec, θpeak=100 deg). Color contours 

indicate wave height, and vectors show mean direction of wave 

propagation.............................................................................................. 62

Figure 3-36. Plot of STWAVE model output for Cape Canaveral, Florida wave 

Case 6 (Hs=1.6 m, Tpeak=14.3 sec, θpeak=65 deg). Color contours 

indicate wave height, and vectors show mean direction of wave 

propagation.............................................................................................. 63

Figure 3-37. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at Borrow Site 2 for STWAVE model 

output for Cape Canaveral, Florida wave Case 3 (Hs=1.0 m, 

Tpeak=7.7 sec, θpeak=100 deg)................................................................... 65

Figure 3-38. Plot of wave height change between existing and post-dredging 

(∆=Hpost-Hpre) conditions at Borrow Site 2 for STWAVE model 

output for Cape Canaveral, Florida wave Case 6 (Hs=1.6 m, 

Tpeak=14.3 sec, θpeak=65 deg)................................................................... 66

Figure 3-39. Comparison of historical shoreline change and gradient of 

modeled transport potential (dQ/dy) for the southern New Jersey 

shoreline. Color bars indicate whether the shoreline is 

accretional, stable, or erosional............................................................... 69

Figure 3-40. Comparison of historical shoreline change and gradient of 

modeled transport potential (dQ/dy) for the southeastern Virginia 

shoreline. Color bars indicate whether the shoreline is 

accretional, stable, or erosional............................................................... 70

Figure 3-41. Comparison of historical shoreline change and gradient of 

modeled transport potential (dQ/dy) for the North Carolina 

shoreline. Color bars indicate whether the shoreline is 

accretional, stable, or erosional............................................................... 71

Figure 3-42. Comparison of historical shoreline change and gradient of 

modeled transport potential (dQ/dy) for the Cape Canaveral 

shoreline. Color bars indicate whether the shoreline is 

accretional, stable, or erosional............................................................... 72

Figure 3-43. Plots of modeled net transport potential and post-dredging change 

in transport for borrow sites located offshore southern New 

Jersey. The middle plot shows the dredging significance criterion 

envelope (±σ), and the plot of the shoreline and bathymetry is 

given for reference................................................................................... 75
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

viii 

Figure 3-44. Plots of modeled net transport potential and post-dredging change 

in transport for borrow sites located offshore southeastern 

Virginia, the middle plot shows the dredging significance criterion 

envelope (±σ), and the plot of the shoreline and bathymetry is 

given for reference................................................................................... 76

Figure 3-45. Plots of modeled net transport potential and post-dredging change 

in transport for borrow sites located offshore North Carolina, north 

of Oregon Inlet. The middle plot shows the dredging significance 

criterion envelope (±σ), and the plot of the shoreline and 

bathymetry is given for reference. ........................................................... 77

Figure 3-46. Plots of modeled net transport potential and post-dredging change 

in transport for borrow sites located offshore Florida, near Cape 

Canaveral. The middle plot shows the dredging significance 

criterion envelope (±σ), and the plot of the shoreline and 

bathymetry is given for reference. ........................................................... 78

Figure 4-1. Difference plot of wave heights for existing and post-dredging 

conditions at sites A and B for Sandbridge model wave case 3.............. 83

Figure 4-2. Difference plot of wave heights for existing and post-dredging 

conditions at sites 3 East and 3 West for North Carolina model 

wave case 4............................................................................................. 84

Figure 4-3. Plot of sediment transport potential difference between existing 

and post-dredging model runs including Sites A and B 

(southeastern Virginia) modeled together (solid black line) and 

separately (solid blue and red lines). The sum of transport 

difference computed for the separate runs of A and B (dotted 

black line) is presented for comparison with the curve of A and B 

modeled together (coefficient of determination, r2

=0.970)....................... 84

Figure 4-4. Plot of sediment transport potential difference between existing 

and post-dredging model runs including sites 3 East and 3 West 

(North Carolina) modeled together (solid black line) and 

separately (solid blue and red lines). The sum of transport 

difference computed for the separate runs of 3 East and 3 West 

(dotted black line) is presented for comparison to the curve of 3 

East and 3 West modeled together (coefficient of determination, 

r

2

=0.990).................................................................................................. 85

Figure 4-5. Plot of change in sediment transport potential computed for five 

excavated depths at site M8, offshore Corsons Inlet, New Jersey. 

The shaded area represents the envelope of maximum transport 

influence that is allowed by the impact significance criterion. ................. 86

Figure 4-6. Plot of excavation depth versus change in modeled sand transport 

potential. Dotted lines represent linear least squares fits of the 

model output (for black line r2

=0.999, and for the red line 

r

2

=0.954).................................................................................................. 87

APPENDIX B: NEW JERSEY WAVE MODEL OUTPUT 

Figure B-1. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 1 (Hs=1.4 m, Tpeak=7.7 sec, θpeak=61 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation.................................................................B-1
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Figure B-2. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 2 (Hs=1.1 m, Tpeak=8.3 sec, θpeak=86 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation.................................................................B-2

Figure B-3. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 3 (Hs=1.2 m, Tpeak=7.7 sec, θpeak=111 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation.................................................................B-3

Figure B-4. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 4 (Hs=1.2 m, Tpeak=7.1 sec, θpeak=131 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation.................................................................B-4

Figure B-5. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 5 (Hs=0.8 m, Tpeak=5.0 sec, θpeak=161 

deg). Color contours indicate wave height, and vectors show 

mean direction of wave propagation.......................................................B-5

Figure B-6. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 6 (Hs=1.3 m, Tpeak=11.1 sec, θpeak=61 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation.................................................................B-6

Figure B-7. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 7 (Hs=1.6 m, Tpeak=11.1 sec, θpeak=81 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation.................................................................B-7

Figure B-8. Plot of STWAVE model output for southern New Jersey, existing 

conditions, wave Case 8 (Hs=2.0 m, Tpeak=10.0 sec, θpeak=96 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation.................................................................B-8

Figure B-9. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 1 (Hs=1.4 m, Tpeak=7.7 

sec, θpeak=61 deg)...................................................................................B-9

Figure B-10. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 2 (Hs=1.1 m, Tpeak=8.3 

sec, θpeak=86 deg).................................................................................B-10

Figure B-11. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 3 (Hs=1.2 m, Tpeak=7.7 

sec, θpeak=111 deg)...............................................................................B-11

Figure B-12. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 4 (Hs=1.2 m, Tpeak=7.1 

sec, θpeak=131 deg)...............................................................................B-12

Figure B-13. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 5 (Hs=0.8 m, Tpeak=5.0 

sec, θpeak=161 deg)...............................................................................B-13
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 

x 

Figure B-14. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 6 (Hs=1.3 m, Tpeak=11.1 

sec, θpeak=61 deg).................................................................................B-14

Figure B-15. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 7 (Hs=1.6 m, Tpeak=11.1 

sec, θpeak=81 deg).................................................................................B-15

Figure B-16. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of New Jersey wave Case 8 (Hs=2.0 m, Tpeak=10.0 

sec, θpeak=96 deg).................................................................................B-16

APPENDIX C: VIRGINIA WAVE MODEL OUTPUT 

Figure C-1. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 1 (Hs=1.6 m, Tpeak=7.7 sec, θpeak=359 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-1

Figure C-2. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 2 (Hs=1.6 m, Tpeak=8.3 sec, θpeak=34 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-2

Figure C-3. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 3 (Hs=1.4 m, Tpeak=9.1 sec, θpeak=54 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-3

Figure C-4. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 4 (Hs=1.1 m, Tpeak=8.3 sec, θpeak=104 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-4

Figure C-5. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 5 (Hs=1.1 m, Tpeak=8.3 sec, θpeak=119 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-5

Figure C-6. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 6 (Hs=1.2 m, Tpeak=8.3 sec, θpeak=149 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-6

Figure C-7. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 7 (Hs=2.8 m, Tpeak=11.1 sec, θpeak=39 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-7

Figure C-8. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 8 (Hs=2.0 m, Tpeak=11.1 sec, θpeak=64 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-8
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Figure C-9. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 9 (Hs=1.6 m, Tpeak=11.1 sec, θpeak=79 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ............................................................................. C-9

Figure C-10. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 10 (Hs=1.8 m, Tpeak=10.0 sec, θpeak=134 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ........................................................................... C-10

Figure C-11. Plot of STWAVE model output for Virginia, existing conditions, 

wave Case 7 (Hs=2.4 m, Tpeak=10.0 sec, θpeak=144 deg). Color 

contours indicate wave height, and vectors show mean direction 

of wave propagation. ........................................................................... C-11

Figure C-12. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 1 (Hs=1.6 m, Tpeak=7.7 sec, 

θpeak=359 deg). .................................................................................... C-12

Figure C-13. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 2 (Hs=1.6 m, Tpeak=8.3 sec, 

θpeak=34 deg). ...................................................................................... C-13

Figure C-14. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 3 (Hs=1.4 m, Tpeak=9.1 sec, 

θpeak=54 deg). ...................................................................................... C-14

Figure C-15. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 4 (Hs=1.1 m, Tpeak=8.3 sec, 

θpeak=104 deg). .................................................................................... C-15

Figure C-16. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 5 (Hs=1.1 m, Tpeak=8.3 sec, 

θpeak=119 deg). .................................................................................... C-16

Figure C-17. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 6 (Hs=1.2 m, Tpeak=8.3 sec, 

θpeak=149 deg). .................................................................................... C-17

Figure C-18. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 7 (Hs=2.8 m, Tpeak=11.1 sec, 

θpeak=39 deg). ...................................................................................... C-18

Figure C-19. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 8 (Hs=2.0 m, Tpeak=11.1 sec, 

θpeak=64 deg). ...................................................................................... C-19

Figure C-20. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 9 (Hs=1.6 m, Tpeak=11.1 sec, 

θpeak=79 deg). ...................................................................................... C-20
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Figure C-21. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 10 (Hs=1.8 m, Tpeak=10.0 sec, 

θpeak=134 deg). .................................................................................... C-21

Figure C-22. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Virginia wave Case 11 (Hs=2.4 m, Tpeak=10.0 sec, 

θpeak=144 deg). .................................................................................... C-22

APPENDIX D: NORTH CAROLINA WAVE MODEL OUTPUT 

Figure D-1. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 1 (Hs=1.1 m, Tpeak=5.1 sec, θpeak=1 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation................................................................ D-1

Figure D-2. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 2 (Hs=1.9 m, Tpeak=6.0 sec, θpeak=21 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation................................................................ D-2

Figure D-3. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 3 (Hs=1.5 m, Tpeak=6.7 sec, θpeak=56 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation................................................................ D-3

Figure D-4. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 4 (Hs=1.2 m, Tpeak=7.4 sec, θpeak=86 deg). 

Color contours indicate wave height, and vectors show mean 

direction of wave propagation................................................................ D-4

Figure D-5. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 5 (Hs=0.9 m, Tpeak=7.6 sec, θpeak=106 

deg). Color contours indicate wave height, and vectors show 

mean direction of wave propagation...................................................... D-5

Figure D-6. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 6 (Hs=0.6 m, Tpeak=4.6 sec, θpeak=131 

deg). Color contours indicate wave height, and vectors show 

mean direction of wave propagation...................................................... D-6

Figure D-7. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 7 (Hs=1.9 m, Tpeak=11.5 sec, θpeak=66 

deg). Color contours indicate wave height, and vectors show 

mean direction of wave propagation...................................................... D-7

Figure D-8. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 8 (Hs=1.5 m, Tpeak=12.8 sec, θpeak=71 

deg). Color contours indicate wave height, and vectors show 

mean direction of wave propagation...................................................... D-8

Figure D-9. Plot of STWAVE model output for North Carolina, existing 

conditions, wave Case 9 (Hs=1.3 m, Tpeak=11.3 sec, θpeak=101 

deg). Color contours indicate wave height, and vectors show 

mean direction of wave propagation...................................................... D-9
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Figure D-10. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 1 (Hs=1.1 m, Tpeak=5.1 

sec, θpeak=1 deg).................................................................................. D-10

Figure D-11. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 2 (Hs=1.9 m, Tpeak=6.0 

sec, θpeak=21 deg)................................................................................ D-10

Figure D-12. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 3 (Hs=1.5 m, Tpeak=6.7 

sec, θpeak=56 deg)................................................................................ D-11

Figure D-13. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 4 (Hs=1.2 m, Tpeak=7.4 

sec, θpeak=86 deg)................................................................................ D-11

Figure D-14. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 5 (Hs=0.9 m, Tpeak=7.6 

sec, θpeak=106 deg).............................................................................. D-12

Figure D-15. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 6 (Hs=0.6 m, Tpeak=4.6 

sec, θpeak=131 deg).............................................................................. D-12

Figure D-16. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 7 (Hs=1.9 m, 

Tpeak=11.5 sec, θpeak=66 deg)............................................................... D-13

Figure D-17. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 8 (Hs=1.5 m, 

Tpeak=12.8 sec, θpeak=71 deg)............................................................... D-13

Figure D-18. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of North Carolina wave Case 9 (Hs=1.3 m, 

Tpeak=11.3 sec, θpeak=101 deg)............................................................. D-14

APPENDIX E: FLORIDA WAVE MODEL OUTPUT 

Figure E-1. Plot of STWAVE model output for Cape Canaveral, Florida, 

existing conditions, wave Case 1 (Hs=1.7 m, Tpeak=7.7 sec, 

θpeak=55 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. ............................................E-1

Figure E-2. Plot of STWAVE model output for Cape Canaveral, Florida, 

existing conditions, wave Case 2 (Hs=1.4 m, Tpeak=7.7 sec, 

θpeak=80 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. ............................................E-2
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Figure E-3. Plot of STWAVE model output for Cape Canaveral, Florida, 

existing conditions, wave Case 3 (Hs=1.0 m, Tpeak=7.7 sec, 

θpeak=100 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. ............................................E-3

Figure E-4. Plot of STWAVE model output for Cape Canaveral, Florida, 

existing conditions, wave Case 4 (Hs=1.5 m, Tpeak=6.3 sec, 

θpeak=130 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. ............................................E-4

Figure E-5. Plot of STWAVE model output for Cape Canaveral, Florida, 

existing conditions, wave Case 5 (Hs=1.7 m, Tpeak=12.5 sec, 

θpeak=60 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. ............................................E-5

Figure E-6. Plot of STWAVE model output for Cape Canaveral, Florida, 

existing conditions, wave Case 6 (Hs=1.6 m, Tpeak=14.3 sec, 

θpeak=65 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. ............................................E-6

Figure E-7. Plot of STWAVE model output for Cape Canaveral, Florida, predredge conditions, wave Case 7 (Hs=1.5 m, Tpeak=11.1 sec, 

θpeak=100 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. ............................................E-7

Figure E-8. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Cape Canaveral, Florida wave Case 1 (Hs=1.7 m, 

Tpeak=7.7 sec, θpeak=55 deg)....................................................................E-8

Figure E-9. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Cape Canaveral, Florida wave Case 2 (Hs=1.4 m, 

Tpeak=7.7 sec, θpeak=80 deg)....................................................................E-9

Figure E-10. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Cape Canaveral, Florida wave Case 3 (Hs=1.0 m, 

Tpeak=7.7 sec, θpeak=100 deg)................................................................E-10

Figure E-11. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Cape Canaveral, Florida wave Case 4 (Hs=1.5 m, 

Tpeak=6.3 sec, θpeak=130 deg)................................................................E-11

Figure E-12. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Cape Canaveral, Florida wave Case 5 (Hs=1.7 m, 

Tpeak=12.5 sec, θpeak=60 deg)................................................................E-12

Figure E-13. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Cape Canaveral, Florida wave Case 6 (Hs=1.6 m, 

Tpeak=14.3 sec, θpeak=65 deg)................................................................E-13

Figure E-14. Plot of wave height change between pre- and post-dredge 

(∆=Hpost-Hpre) conditions at indicated borrow sites, for STWAVE 

model output of Cape Canaveral, Florida wave Case 1 (Hs=1.5 m, 

Tpeak=11.1 sec, θpeak=100 deg)..............................................................E-14
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LIST OF TABLES 

Table 1-1. Borrow site characteristics for the four sand resource areas. ................... 4

Table 2-1. Redistributed wave energy for idealized borrow site case 

illustrating the effects of a case dominated by one wave direction.......... 15

Table 3-1. Significant parameters of input wave spectra used for existing and 

post-dredging STWAVE model runs for New Jersey model grid............. 32

Table 3-2. Significant parameters of input wave spectra used for existing and 

post-dredging STWAVE model runs for Virginia model grid.................... 32

Table 3-3. Significant parameters of input wave spectra used for existing and 

post-dredging STWAVE model runs for North Carolina model grid. ....... 32

Table 3-4. Significant parameters of input wave spectra used for existing and 

post-dredging STWAVE model runs for Florida model grid..................... 33

Table 3-5. Significant parameters for input wave spectra used for existing 

and post-dredging STWAVE model runs for offshore southeastern 

Virginia sites. ........................................................................................... 35

Table 3-6. Maximum estimated cumulative borrow site excavation 

dimensions for the four sand resource areas. ......................................... 37

Table 3-7. Numerical grid dimensions for offshore (coarse) and nearshore 

(fine) grids. Dimensions are given as (cross-shore x alongshore). ........ 44
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1 

1.0 INTRODUCTION 

 The Minerals Management Service (MMS), a bureau within the U.S. Department of 

the Interior, has responsibility for managing all mineral resources on the Federal Outer 

Continental Shelf (OCS), a zone that extends three (3) miles seaward from State 

coastline boundaries to 200 miles offshore. Although most interest in this zone relates to 

oil and gas resources, the potential for exploitation of sand resources as a source for 

beach and barrier island restoration has grown rapidly in the last several years as similar 

resources in State waters are being depleted or polluted. Extraction of sand resources 

in Federal waters may be preferred relative to State waters due to concerns over 

changes in physical oceanographic conditions resulting from large quantities of material 

dredged from resource sites impacted by waves and currents. This has generated a 

need for technical information to ensure that offshore minerals are developed with due 

concern for potential environmental considerations. 

 In 1983, the MMS established the Office of Strategic and International Minerals for 

evaluating the prospects for and conditions under which sand and gravel mining would 

develop in the U.S. In 1991, the Office of International Activities and Marine Minerals 

(INTERMAR; now referred to as the International Activities and Marine Minerals 

Division) was created to develop strategies for addressing specific concerns regarding 

offshore sand and gravel mining operations (Hammer et al., 1993). The MMS has 

significant responsibilities with respect to potential environmental impacts of sand and 

gravel mining. Existing regulations governing sand and gravel mining provide a 

framework for comprehensive environmental protection during operations. Specific 

requirements exist for evaluations and lease stipulations that include appropriate 

mitigation measures (Hammer et al., 1993). Guidelines for protecting the environment 

stem from a wide variety of laws, including the OCS Lands Act (OCSLA), National 

Environmental Policy Act (NEPA), and others. Regulations require activities to be 

conducted in a manner which prevents or minimizes the likelihood of any occurrences 

that may cause damage to the environment. The MMS takes a case-by-case approach 

in conducting environmental analyses, as required by NEPA and the Council on 

Environmental Quality (CEQ) regulations. 

 In recent years, there has been increasing interest in sand and gravel mining on 

the OCS. Currently, eight State-Federal task forces, several cooperative agreements, at 

least five negotiated agreements, and seven environmental surveys exist to ensure 

substantive government and public involvement and attention to regional, State, and 

local concerns regarding leasing, engineering, economic, and environmental aspects of 

sand and gravel mining (to obtain specific information regarding these activities, visit 

http://www.mms.gov/intermar/marineac.htm). Under the OCSLA, the MMS is required to 

conduct environmental studies to obtain information useful for decisions related to 

negotiated agreements and lease activities. As such, the MMS pursues its 

responsibilities for management of offshore sand and gravel mining vigorously by: 

• protecting ocean and coastal environments by ensuring that all OCS sand and 

gravel mining activities are environmentally acceptable; 

• ensuring the OCS sand and gravel activities are compatible with other uses of 

the ocean; 

• involving coastal States in all aspects of sand and gravel mining activities; and 

• evaluating the potential of the OCS as a domestic source for sand and gravel. 
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1.1 STUDY PURPOSE 

 The overall study purpose addresses the need for physical environmental 

information to support potential lease decisions offshore the east coast of the U.S. from 

southern New Jersey to Cape Canaveral, Florida. Specifically, the study examines the 

potential for negative impacts to coastal and nearshore environments, particularly from 

alterations to the local wave and sediment transport regime, due to long-term dredging 

and significant removal of sand from shoals offshore southern New Jersey, southeastern 

Virginia (Sandbridge Shoal), North Carolina (north of Oregon Inlet), and Cape 

Canaveral, Florida. Shoals in these areas are expected to serve as long-term and 

continual sources of borrow material, due to existing beach renourishment cycles, and to 

repair damage from severe coastal storms. In certain instances, such as Sandbridge 

Shoal offshore southeastern Virginia, several jurisdictions or entities want to use the 

same borrow area(s) on different cycles. This raises the issue of cumulative effects of 

multiple sand dredging events and/or dredging at multiple sites, particularly related to 

alterations to the local wave and sediment transport regime. In natural continental shelf 

settings, wave energy typically concentrates at shoals and diverges at holes due to wave 

refraction and diffraction. The interaction between waves and bathymetric surface 

geometry dictates the resultant pattern of wave energy propagation. As such, patterns 

of wave energy transformation across the continental shelf depend on changes in 

bathymetry and the level of incident energy. 

 The most effective means of quantifying incremental and cumulative physical 

environmental effects of sand dredging from shoals on the continental shelf is through 

the use of wave transformation numerical modeling tools that recognize the random 

nature of incident waves as they propagate onshore. Spectral wave models, such as 

STWAVE, REF/DIF-S, SWAN, and others, typically provide more realistic results than 

monochromatic wave models relative to field measurements (see Appendix A). As such, 

spectral wave transformation modeling was applied in this study to evaluate the potential 

negative impacts to coastal and nearshore sites from long-term dredging and significant 

removal of sand from offshore sand borrow sites. Although the interpretation of wave 

modeling results is relatively straightforward, evaluating the significance of predicted 

changes for accepting or rejecting a borrow site is more complicated. A substantial part 

of this study was aimed at assessing the significance of simulated changes between 

existing and post-dredging conditions versus natural variability in wave climate and 

potential sediment transport rates to determine the relative importance of predicted 

changes. It is expected that information generated will enable the MMS to assess 

potential impacts of long-term offshore dredging and to identify potential dredging 

alternatives aimed at minimizing or precluding adverse physical environmental impacts. 

1.2 STUDY AREAS AND BORROW SITE CHARACTERISTICS 

 The inshore portion of the continental shelf, seaward of the State-Federal OCS 

boundary and within the Exclusive Economic Zone (EEZ), encompasses the project 

study areas offshore southern New Jersey (Figure 1-1), southeastern Virginia (Figure 1-

2), North Carolina (north of Oregon Inlet; Figure 1-3), and Cape Canaveral, Florida 

(Figure 1-4). The seaward limit of all borrow sites is generally within about 30 km of the 

shoreline and located between the 10- and 20-m depth contours. 

 The continental shelf surface offshore southern New Jersey contains many first-, 

second-, and third-order morphologic features formed during the Holocene transgression 

(McKinney et al., 1974; Figure 1-1). Sand ridges 2- to 5-m high and 0.5- to 1.5-km apart 
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Figure 1-1. Location diagram illustrating sand borrow sites M8 (USACE designation), A1 and 

A2 (NJ State designation), and State-Federal boundary relative to 1934/77 

bathymetry. 

represent second-order features that are the primary sand resource targets of this study. 

Average shoal relief is about 3 m. Three potential borrow sites were modeled for 

southern New Jersey to evaluate the cumulative effects of multiple simultaneous 

dredging operations and repetitive dredging with time at one site. Table 1-1 lists 

proposed maximum dredging volumes and depths for sites A-1, A-2, and M8. 

 Continental shelf topography offshore southeastern Virginia is dominated by ridge 

and swale features formed during the Holocene (Williams et al., 1987; Kimball et al., 

1991). Many potential sand resource sites are associated with ridges approximately 20 

km offshore Virginia Beach (known as the Virginia Beach Ridges) and seaward of False 

Cape (False Cape Ridges). Kimball and Dame (1989) identified Sandbridge Shoal as a 

viable sand resource site for beach nourishment along the southeastern Virginia coast. 

The horseshoe-shaped shoal was characterized as a northward and eastward thinning 

wedge of sand approximately 48 km2

 in area and up to 6 m thick. Maximum relief over 

the ambient shelf surface was about 4 m (Kimball et al., 1991). Two sand borrow sites 

were identified on this shoal (Sites A and B; Figure 1-2), and approximately 1.5 MCY has 

been extracted from Site A for beach nourishment along Dam Neck Beach and 

Sandbridge Beach to date. Table 1-1 lists proposed maximum dredging volumes and 

depths for sites A and B. 
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Figure 1-2. Location diagram illustrating sand borrow sites A and B and State-Federal 

boundary relative to 1934/77 bathymetry. 

Table 1-1. Borrow site characteristics for the four sand resource areas. 

Region Site Designation Volume 

(106

 m3) 

Area 

(106 m2) 

Average Excavation 

Depth (m) 

A1 8.8 2.2 4.0 

A2 7.8 2.6 3.0 Southern 

New Jersey M8 8.0 4.0 2.0 

Southeastern A 5.3 1.8 3.0 

Virginia B 6.9 2.3 3.0 

3 East 1.4 0.7 2.0 North Carolina 3 West 2.5 0.8 3.0 

Offshore Cape 

Canaveral, Florida 2 26.0 5.0 5.2 
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Figure 1-3. Location diagram illustrating sand borrow sites 3 West and 3 East and StateFederal boundary relative to 1934/77 bathymetry. 

 In the vicinity of Oregon Inlet, North Carolina shelf topography is characterized by 

sub-parallel ridges and swales that trend approximately north-south making an angle of 

about 20° to 30° with the shoreline trend (Inman and Dolan, 1989). The ridges are about 

1.5 to 6 km apart, extend 12 to 60 km, and have an average relief of 2 to 6 m (Swift et 

al., 1972). The North Carolina Geological Survey identified four sand resource areas in 

OCS waters northeast of Oregon Inlet (Hoffman, 1998). Two sand borrow sites were 

selected in Resource Area 3 (3 East and 3 West; Figure 1-3) for evaluating the potential 

impact of simultaneous dredging at multiple sites on coastal wave and sediment 

transport processes. Table 1-1 lists proposed maximum dredging volumes and depths 

for sites 3 West and 3 East. 

 Cape Canaveral Shoals was the fourth sand resource area evaluated in this study. 

A potential offshore borrow site was identified by the U.S. Army Corps of Engineers, 

Jacksonville District, (USACE, 1999). Borrow Area 2 is located along the seaward 

margin of Canaveral Shoals about 15 to 20 km offshore in an area referred to 
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Figure 1-4. Location diagram illustrating sand Borrow Site II and State-Federal boundary 

relative to 1934/77 bathymetry. 

as “Southeast Shoals”, in water depths ranging from 7 to 14 m (Figure 1-4). Core data 

from the borrow site suggest that beach quality sand is present at thicknesses of 3 to 5 

m. Average median grain size is about 0.35 mm. Table 1-1 lists the proposed maximum 

dredging volume and depth for sand Borrow Site 2. 

1.3 STUDY APPROACH 

 To address the overall study purpose, a four-phase approach was implemented. 

First, a detailed evaluation of three readily-available, project-tested spectral wave 

models was conducted to determine the most effective simulation routine for predicting 

potential wave impacts due to dredging at offshore borrow sites. Appendix A contains 

the final report for the spectral wave model evaluation task. Our analysis recommended 

that the U.S. Army Corps of Engineer STeady-state spectral WAVE model (STWAVE) 

be used on future MMS wave transformation modeling studies. Second, a standard 

method was developed to qualify the significance of changes associated with borrow site 
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MMS Study 2001-098 

7 

excavation to determine the influence of borrow site geometry on local wave refraction 

and sediment transport patterns. Because large natural spatial and temporal variability 

exists within the wave climate at a particular site, determination of physical impacts 

associated with sand mining must consider the influence of process variability. The 

method developed for this study is based on historical wave climate variability, as well as 

local wave climate changes directly attributable to borrow site excavation. 

 The third phase of the project focused on wave spectra development, wave 

transformation modeling, and coastal sediment transport calculations. This phase of the 

project represents the bulk of analyses performed to document potential impacts 

associated with dredging at selected offshore sand borrow sites. Wave transformation 

modeling and sediment transport potential calculations were performed for existing and 

post-dredging bathymetric conditions. Comparison of computations for existing and 

post-dredging conditions are used to illustrate the relative maximum impact of borrow 

site excavation on wave-induced coastal processes. 

 The fourth and most significant phase of the project addressed potential 

cumulative effects and significance of sand dredging from offshore sand borrow sites. A 

site-specific determination of acceptable limits of borrow site impacts relative to 

sediment transport potential was determined for each case. In addition to the sitespecific investigations, two model studies of incremental cumulative impacts from 

different borrow site configurations were investigated. The first study group of 

incremental impacts involved the interaction of multiple sites in close proximity to one 

another, such that overlapping areas of shoreline impact exist. The second study 

grouping of incremental impacts involves multiple dredging events at a single site, and 

how effects vary as excavation depth is increased (e.g., due to multiple dredging events 

over time). These analyses were designed to determine how potential wave impacts at 

individual sites may interact to produce additive physical environmental effects along the 

coast. 

1.4 DOCUMENT ORGANIZATION 

 Information presented in this document represents the culmination of a year and a 

half of work among experts in the fields of oceanography, coastal processes, and 

numerical wave and sediment transport modeling, under the direction of Mr. Barry 

Drucker (MMS INTERMAR). This document was organized into six major sections as 

follows: 

• Introduction 

• Physical Processes 

• Modeling Approach and Applications 

• Cumulative Effects 

• Conclusions 

• Literature Cited 

 In addition to the main document, appendices were prepared in support of many of 

the analyses presented in each section of the report. Furthermore, an Executive 

Summary, a Technical Summary, and a Non-Technical Summary will be prepared as 

separate documents to provide a brief description of study methods and findings for 

audiences ranging from researchers to non-technical people. 
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2.0 PHYSICAL PROCESSES 

 During the past few decades, there has been increased focus on the nearshore 

zone due to rapid development of this region and the need to protect infrastructure from 

devastating storm impacts and long-term coastal erosion. A significant portion of this 

effort has been concentrated on developing analytical tools to evaluate the 

transformation of waves in shallow water and to quantify sediment transport induced by 

breaking waves along the shoreline. Although our understanding has improved, 

evaluation of coastal processes still requires a blend of analytical capability, 

interpretation of many complex and often apparently conflicting data sets, and 

experience gained from analyzing a variety of shorelines. The primary reason for this 

relevance on qualitative and quantitative approaches is that the equations governing 

sediment movement by waves are not yet fully known. 

 The primary quantitative technique used to evaluate nearshore processes is wave 

transformation modeling. Wave models have been developed to numerically solve the 

equations governing changes in wave height and direction (through processes such as 

refraction, shoaling, and breaking). As better offshore wave data sets become available 

(e.g., wave gauge and hindcast information), wave transformation models have become 

standard tools for evaluating changes in nearshore wave climate. Due to the 

complexities of surf zone hydrodynamics, sediment transport analysis techniques 

typically depend on information from wave models at the line of wave breaking. 

Unfortunately, calculations involving sediment transport are dependent on empirical or 

semi-empirical relationships; therefore, these techniques are not as theoretically rigorous 

as wave modeling. In addition, shoreline modifications (e.g., coastal engineering 

structures, natural hardbottom, and beach nourishment projects) are not included and 

sediment transport equations assume that an infinite supply of material is available, 

hence the term “sediment transport potential”. Although these simplifications can limit 

the applicability of the approach, proper interpretation of wave modeling and associated 

longshore sediment transport analysis results can provide a powerful tool for coastal 

engineering design and assessment of shoreline dynamics. 

 The analysis techniques presented in this report involve spectral wave modeling, 

based primarily on wave hindcast information, combined with standard longshore 

sediment transport equations to evaluate impacts associated with offshore sand mining. 

A general description of nearshore wave transformation and longshore sediment 

transport is provided. In addition, nearshore wave transformations and alterations to 

longshore sediment transport potential are shown for an idealized borrow site. 

2.1 NEARSHORE WAVE TRANSFORMATION 

 Open ocean waves primarily are generated by wind that induces drag across the 

water surface. Over time, persistent strong winds can generate long waves with large 

heights, replacing less energetic waves initially created. Because wind patterns are 

complex, blowing in various directions with different speeds for varying amounts of time, 

the resulting sea is complicated as well. Due to the restoring force provided by gravity, 

ocean waves can travel long distances across the surface of the ocean with relatively 

little change in shape. As waves travel, energy is exchanged between the different 

component waves of the spectrum, and a small amount of wave energy is dissipated 

through surface tension and whitecapping. However, waves in the open ocean remain 

fairly uniform as they travel through deep water. As waves propagate into intermediate 
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and shallow water depths, the effects of the seafloor tend to dominate wave 

transformations. Although a small amount of energy is lost through bottom stresses 

(frictional drag), most nearshore wave transformation results from six processes: 1) 

refraction, 2) shoaling, 3) breaking, 4) diffraction, 5) reflection, and 6) wave-current 

interactions. These processes determine the size and incident angle of breaking waves, 

the dominant driving force for nearshore sediment transport. Although minor wave 

diffraction and reflection may occur at an offshore borrow site, wave refraction, shoaling, 

and breaking dominate transformation processes associated with offshore sand mining. 

Therefore, consideration of wave refraction, shoaling, and breaking are critical 

components of any spectral analysis used to evaluate alterations to a wave field 

associated with offshore sand mining. 

 As a wave propagates into shallow water, the wavelength shortens and the wave 

period remains constant (assuming the wave field is constant in time). The wave period 

is defined as the time required for successive wave crests to pass a particular location. 

Consequently, waves travel at slower speeds in shallow water. This process causes 

wave crests to bend, or refract, toward regions of shallow water and away from regions 

of deep water. As shown in Figure 2-1, wave crests approaching the beach at an angle 

become more parallel to the shoreline as they approach the beach and the water depth 

decreases. Refraction also serves to focus wave energy on headlands, reefs, and 

shoals, while diverting energy from deep holes and channels. This, in turn, directly 

impacts the erosional pressures on the shoreline. Because longshore sediment 

transport rates are dependent upon the wave angle at breaking, determined by the 

effects of refraction, underwater features such as troughs and ridges can serve to 

exacerbate erosion in certain regions. These erosional hot spots will exist where the 

bathymetry tends to focus wave energy. Along a wave crest, variations in wave height 

may occur due to a focusing of wave energy from refraction processes, a change in 

wave height from shoaling processes, or a shielding of wave energy from an obstruction. 

 Neglecting small energy losses due to frictional effects, the total energy in a 

propagating waveform is conserved. As a wave enters shallow water its propagation 

speed tends to slow. Because wave energy is dependent upon wave height and wave 

speed, and wave speed slows with decreasing depth, wave height increases as the 

wave propagates into shallow water. Depending on offshore bottom slope, the change 

in wave height due to shoaling can be significant. Computation of the longshore 

transport rate is dependent on the incident wave angle at breaking and wave height. 

Therefore, shoaling characteristics are important for evaluating beach erosion. In 

general, areas with relatively gentle offshore slopes allow wave energy to concentrate 

over a wide surf zone, and sediment transport volumes are high relative to incident wave 

height. However, beaches with gentle slopes usually have a significant sediment 

volume in storage, and because the wide surf zone causes transport to be distributed 

over a large area, the effects of sediment movement may not be evident. Conversely, 

beaches with very steep offshore slopes do not allow waves to completely shoal before 

breaking takes place. Thus, wave heights at breaking are reduced; however, breaking 

wave energy is dissipated within a narrow surf zone. Although transport volumes may 

not be as high as beaches with gentle slopes, the concentration of transport within a 

narrow region may cause the effects of beach erosion to be more pronounced. 
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Figure 2-1. Diagram illustrating the effects of refraction and diffraction as waves approach 

the coastline (from Svendsen and Jonsson, 1976). 

 The most significant nearshore wave transformation occurs when waves break. In 

very shallow water (proportional to the wave height), the combined effects of refraction, 

shoaling, diffraction, and reflection produce a wave form that is unstable. When a wave 

becomes too steep, and the speed of the crest exceeds that of the entire wave form, the 

wave topples over and breaks. Breaking drastically reduces the wave height. Much of 

the wave energy is dissipated through the breaking process in a very narrow surf zone, 

where large amounts of sediment are lifted from the bottom and transported by 

nearshore waves and currents. 

2.2 NEARSHORE SEDIMENT TRANSPORT PATTERNS 

 Nearshore wave and current motions are complex, and the surf zone system is 

further complicated by the capability of these motions to lift and transport beach 

sediment. An integrated study of wave processes, shoreline geometry, and sediment 

characteristics is required for predicting erosional trends and naturally occurring beach 

profile and planform shapes. Qualitatively, an understanding of the nearshore littoral 

system is obtained by focusing on cross-shore and longshore sediment transport trends, 

and on the influence of severe storm events versus typical wave conditions. 

 Generally, beach profile shape is governed by relatively short-term catastrophic 

events such as severe storms. For example, on the East Coast of the United States, 

beach profile shapes are dramatically changed by northeast storms and hurricanes. 
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Large volumes of sand are eroded from the beach face and deposited offshore in sand 

bars during these storm events. However, much of this material is recovered over 

longer time scales as milder waves move sediment landward, causing the beach face to 

accrete. Seasonal trends in wave climate influence cross-shore sediment transport as 

well. Typically, larger winter waves erode the beach face and milder summer waves 

build the beach. Therefore, the beach profile is dynamic, and the best estimate of a 

typical profile is the stable beach shape that forms when exposed to average annual 

waves. A stable beach is defined as an equilibrium condition and may be predicted 

using coastal engineering analyses. Cross-shore transport (or profile) modeling is 

usually based on the concept of equilibrium conditions forming a "stable" profile. This 

condition is used as a baseline for determining the potential changes in shoreline 

position due to a severe storm. 

 While large volumes of beach sediment are moved during isolated storm events, it 

is seasonal or average annual waves that dictate beach planform shape. Planform 

shape can be evaluated using longshore sediment transport models based on average 

annual wave conditions. Although large storm events may transport large volumes of 

sand along the coast, the short-term effects of storms tend to be minimal when long-term 

transport is evaluated. Waves incident from the north transport sediment to the south 

and vice-versa. Seasonal trends exist on the East Coast because winter waves 

generally are incident from the north, and summer waves generally are incident from the 

south. Of course, transport trends are highly dependent upon shoreline orientation. 

Varying volumes of sediment transported north and south may be estimated over time 

and superimposed to determine the net annual longshore sediment transport direction 

and volume. Another approach is to estimate the net annual transport from average 

annual wave conditions. 

2.3 IDEALIZED OFFSHORE BORROW SITE 

 To assess alterations to wave patterns and associated longshore sediment 

transport processes, evaluation of an idealized offshore borrow site was performed using 

the spectral wave model STWAVE (described in Section 3) and standard sediment 

transport potential equations. A comparison of wave/sediment transport modeling 

results between transformations resulting from typical nearshore bathymetric conditions 

and those created by the existence of an offshore borrow site reveals the potential 

influence of sand mining on the littoral system. 

 First, a bathymetric grid was developed to represent generalized variations in 

water depth. Based on a typical cross-shore profile for New Jersey (Dean, 1977), the 

grid was developed assuming straight and parallel bathymetric contours using the 

equation: h = Ay m , where h is the water depth, y is the distance offshore, A is a profile 

scale factor (indirectly related to beach grain size), and m is profile shape factor. For the 

southern New Jersey shoreline example, A was set at 0.0793 and m was set at 0.822. 

The idealized borrow site was centered on the 10 m bathymetric contour (see Figure 2-

2) and consisted of an excavation of approximately 3 m. The borrow site was assumed 

to be square in the x-y direction with dimensions of 225 by 225 m. Total volume of the 

borrow site was approximately 153,000 cu m (200,000 cu yds). 

 The grid used for spectral wave refraction modeling extended 2,000 m alongshore 

and 850 m in the cross-shore direction, with a grid spacing of 5 m. A series of wave 

model runs were developed to provide conditions consistent with the southern New 
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Jersey shoreline: an incident spectral significant wave height of 1.2 m, a peak wave 

period of 8 sec, relatively narrow directional spreading, and a frequency distribution 

based on the work of Bretschneider (1968) and Mitsuyasu (1975). Wave model runs 

were performed for conditions with no borrow site (referred to as existing conditions) and 

for conditions with the borrow site described above (referred to as post-dredging 

conditions). To assess the range of wave transformations possible, wave spectra 

centered at -30°, -15°, 0°, 15°, and 30° relative to shore normal were modeled. 

Figure 2-2. Surface plot with 2.5 m contours of bathymetry grid used for idealized borrow site 

model runs. 

 As an example of the wave modeling results, Figure 2-3 illustrates the influence of 

the idealized borrow site on the nearshore wave field for the -30o condition. Waves 

propagating across the borrow site tend to refract toward shallower water along the 

edges; therefore, areas of wave energy focusing (increase in wave heights) occur along 

each side of the borrow site. In addition, the wave refraction effect for the various 

spectral components generally creates a shadow zone landward of the borrow site. Due 

to the proximity of this borrow site to the beach (approximately 350 m offshore), the 

influence of the idealized borrow site on nearshore wave processes is much more 

pronounced than for a sand borrow site further offshore. However, the nearshore 

location of the borrow site creates a rather limited longshore region of influence. For the 

wave model case shown in Figure 2-3, the influence of the borrow site on the wave 

climate can be seen most clearly by comparing existing and post-dredging conditions as 

shown in Figure 2-4 (Hpost - Hpre). For this wave modeling case, the longshore influence 

of the borrow site extends for an approximate distance of 900 m measured at the 

breaker line. In addition, the maximum increase and decrease in wave height created by 

the borrow site excavation are of similar magnitude (approximately ±0.3 m). 

 Although the influence of a borrow site excavation on the wave field is important, 

an evaluation of the wave field alterations alone does not directly provide information 

needed to assess potential borrow site impacts. Calculation of longshore sediment 

transport potential for a series of wave cases provides a method for determining the 

extent and magnitude of alterations to nearshore processes. For the idealized borrow 

site, annualized sediment transport potential curves were generated for each of the five 

spectral wave conditions (Figure 2-5). As expected, the influence of the borrow site for 

the 0° case is distributed evenly, where positive sediment transport is from left-to-right. 

Cases with a negative approach angle relative to shore normal (-15° and -30°) illustrate 
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Figure 2-3. Example color contour plot of modeled wave heights, with vectors indicating 

mean wave direction for idealized borrow site (incident wave height of 1.2 m and 

period of 8 sec approaching shoreline at -30o from shore-normal). 

Figure 2-4. Color surface plot of wave height difference (Hpost - Hpre) resulting from borrow 

site excavation, for wave case shown in Figure 2-3. 

the influence of the borrow site shifted to the right and a left-to-right transport potential. 

Cases with a positive approach angle relative to shore normal (15° and 30°) show the 

opposite trend. 

 As part of the idealized borrow site evaluation, it first was assumed that each of 

the five modeled wave conditions occurred for 20% of the time. By superimposing each 

of the sediment transport potential curves shown in Figure 2-5 and weighting them by 

the appropriate percent occurrence (20%), a composite sediment transport potential 

curve can be developed (Figure 2-6). Because the modeled borrow site is so close to 

the shoreline, the influence of the borrow site on wave refraction and associated 

nearshore sediment transport patterns is substantial. Without the borrow site influence, 
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Figure 2-5. Computed annualized longshore sediment transport potential for idealized 

borrow site for five wave cases. 

Figure 2-6. Change in computed longshore sediment transport potential for idealized borrow 

site. 

the even distribution of wave conditions would cause a net sediment transport potential 

of zero for this shoreline; however, Figure 2-6 indicates that peak transport rates would 

increase to nearly 100,000 cu m annually at an alongshore distance of approximately 

350 m from the center of the borrow site. These large increases in sediment transport 

potential directed away from the borrow site are a result of wave focusing. In contrast, 

the small peaks in sediment transport potential in between the two large peaks result 

from the “shadowing” effect of the borrow site created by the wave condition 

combinations. For example, waves propagating over the borrow site from the right (15° 

and 30° wave conditions) create a shadow region along the shoreline that is centered 

slightly to the left of the borrow site (the +50,000 cu m/yr transport peak in Figure 2-6). 

This shadow region is characterized by a decrease in left-directed sediment transport for 

these cases. Therefore, the overall effect is to create an increase in net right-directed 

(left-to-right) transport. 

 By computing the change in sediment transport potential over the shoreline 

distance (dQ/dy), a normalized curve of anticipated shoreline change resulting from 

excavation of an offshore borrows site can be developed. Figure 2-7 illustrates shoreline 
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change resulting from wave conditions presented above. Due to wave focusing caused 

by the borrow site configuration, increased erosion occurs along the shoreline on either 

side of the borrow site. Material eroded from these two areas feeds the central “shadow 

zone”, as well as shoreline regions further from the borrow site center. 

Figure 2-7. Computed cross-shore change in shoreline position based on modifications to 

longshore sediment transport potential by idealized borrow site. 

 To illustrate the influence of variable wave conditions on nearshore sediment 

transport dynamics, a second evaluation for the idealized borrow site was performed 

with a different distribution of input wave conditions. The percent occurrence for wave 

conditions presented above were altered to represent conditions dominated by a single 

direction as shown in Table 2-1. Figures 2-8 and 2-9 represent results from this 

redistribution of wave energy. As expected, the higher percent occurrence of the rightdirected wave cases (-30° and -15°) increases the influence of these conditions on 

sediment transport potential (Figure 2-8). Although the longshore location of sediment 

transport and erosion/accretion peaks remains the same, the magnitude is different. For 

this case, the higher percent occurrence of right-directed transport creates a greater 

increase in shoreline erosion potential to the right of the borrow site. 

Table 2-1. Redistributed wave energy for idealized borrow site case illustrating the 

effects of a case dominated by one wave direction. 

Wave Direction (center of wave spectra) 

-30° -15° 0° 15° 30° 

% Occurrence 20 35 20 15 10 

 Because actual wave conditions at a borrow site are dominated by a single 

direction, the asymmetric distribution of sediment transport potential and associated 

shoreline change are characteristic of conditions expected at borrow sites along the U.S. 

East Coast. This asymmetric distribution naturally causes impacts associated with sand 

mining to be focused along a shoreline area that generally is not directly landward of the 

borrow site. By performing a wave refraction and longshore sediment transport analysis 

based on site conditions, the anticipated influence of a specific borrow site on local 

littoral processes can be determined. In this manner, the numerical modeling process 

can be used to optimize borrow site excavation strategies, or alternatively, to determine 

acceptable volume limits of a sand mining operation. 
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Figure 2-8. Change in computed longshore sediment transport potential based on alternate 

distribution of wave percent occurrences. 

Figure 2-9. Computed cross-shore change in shoreline position based on modifications to 

longshore sediment transport potential using alternate distribution of wave 

percent occurrences. 

2.4 SIGNIFICANCE OF BORROW SITE IMPACTS 

 As part of any offshore sand mining effort, the MMS requires an evaluation of 

potential environmental impacts associated with alterations to nearshore wave patterns. 

To determine potential impacts associated with borrow site excavation, the influence of 

borrow site geometry on local wave refraction patterns is evaluated; however, standard 

methodologies have not been developed to determine the significance of changes 

associated with these impacts. Because large natural spatial and temporal variability 

exists within the wave climate at a particular site, determination of physical impacts 

associated with sand mining must consider the influence of process variability. A 

method based on historical wave climate variability, as well as local wave climate 

changes directly attributable to borrow site excavation, has been applied to determine 

appropriate criteria for assessing impact significance. 
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 Over the past two decades, advances in numerical wave modeling techniques 

have resulted in more accurate analysis of nearshore wave field transformation. In 

addition, the availability of long-term wave data and hindcast information has improved 

the boundary conditions necessary to drive these models. Although future work likely 

will improve some of the simplifying assumptions inherent in nearshore wave models, as 

well as the limitations associated with wave model input data (wave and bathymetric 

information), available spectral wave models can be used to develop reliable estimates 

of impacts associated with offshore sand mining. As shown in Appendix A, spectral 

wave models are reliable tools for simulating observed wave conditions affected by 

rapidly changing nearshore bathymetry (e.g., shoals and/or channels). 

2.4.1 Available Methods for Assessing Borrow Site Impacts 

 One standard method for evaluating borrow site impacts is to perform wave and 

sediment transport modeling. Information developed from these modeling efforts is used 

to quantify potential physical environmental impacts associated with dredging activities. 

Although changes in sediment transport potential and wave energy flux associated with 

re-direction of wave energy generally are used as impact evaluation criteria, determining 

acceptable limits for these impacts is not a straightforward process. First, the wave 

climate in the vicinity of a borrow site exhibits temporal and spatial variations. Therefore, 

appropriate evaluation criteria must include the temporal and spatial variability of the 

wave field. Additionally, although past methodologies have described alterations to the 

wave field at various locations (e.g., immediately landward of the borrow site, at a fixed 

reference line, at the breaker line), the shoreline or breaker line appears to be most 

appropriate. In this manner, calculated longshore transport rates (based on wave 

modeling results) can be validated through evaluation of observed shoreline change. 

 Over the past few years, the MMS has employed two techniques for determining 

the significance of borrow site impacts associated with re-direction of nearshore wave 

energy. In 1999, a statistical approach was developed to evaluate changes in wave 

climate at a pre-defined offshore reference line, as well as a method for determining the 

statistical significance of impacts (Basco, 1999). For borrow site studies in Alabama 

(Byrnes et al., 1999) and New Jersey (Byrnes et al., 2000), the significance of borrow 

site impacts were evaluated relative to potential error estimates associated with wave 

height and direction (Rosati and Kraus, 1991). It was concluded that if percent changes 

in longshore sediment transport caused by offshore sand mining were less than the 

percent error determined for wave height/direction estimates, the impact was 

insignificant. 

 Although the above methodologies provide reasonable quantitative estimates of 

impact significance associated with offshore sand mining, the present study introduces a 

new methodology for evaluating borrow site impacts that incorporates temporal and 

spatial changes in the wave field. All three approaches use site-specific wave analyses 

as the basis for quantifying potential alterations to nearshore processes; however, the 

method presented in this study incorporates natural, site-specific variability in wave 

climate as a basis for determining impact significance. The following sections describe 

each method in more detail and provide the benefits and shortcomings, associated with 

each evaluation technique. 
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2.4.2 Reference Line Statistical Approach 

 To quantify changes in wave climate associated with sand mining, Basco (1999) 

applied a linear wave transformation model that incorporated a unit offshore wave height 

at the model domain boundary. Fifty (50) direction/period band combinations 

represented the wave climate for the chosen site (Sandbridge Shoal, Virginia), each with 

appropriate wave height multiplier coefficients. A reference line was defined landward of 

the borrow area, but seaward of the breaker line for 99% of the incident waves. In this 

manner, the use of a unit offshore wave height could be justified. The frequencyweighted wave energy variation along the reference line was then calculated to 

determine the percent change in total wave energy between existing and post-dredging 

conditions. 

 Following the development of wave energy changes, basic statistical theory was 

used to test for the significance of impacts. The method tests the difference in median 

wave energy between existing and post-dredging conditions at a 95% confidence level 

for various locations along the reference line. The length of the reference line is chosen 

to ensure that no wave energy change exists at either end. The evaluation criterion 

imposed indicates that if more than 50% of the total reference line is negatively impacted 

under the 95% confidence level, the borrow site should be rejected (Basco, 1999). 

Figure 2-10 illustrates the application of this significance criterion for Sandbridge Shoal, 

where borrow site dredging creates significant wave energy change for 12.6 km of the 

20-km-long reference line (63% of the reference line length). Therefore, the report 

concluded “that since over 50 percent of the reference line experiences a wave climate 

modification, long-term dredging of sand from Sandbridge Shoal will significantly alter 

the wave climate.” Based on this assumption, it was suggested that the site should be 

rejected. 

Figure 2-10. Percent change in wave energy showing regions of acceptance and rejection of 

the null-hypothesis using ≥ 4.0 percent as the cut-off value (from Basco, 1999). 
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 Although the above methodology incorporates a significant numerical wave 

modeling effort and is statistically rigorous, it requires use of arbitrary limits. For 

example, rejection of the borrow site was based on greater than 50% of the reference 

line experiencing significant wave climate modifications. The 50% modification criteria 

and the length of the reference line are based on the user’s judgment rather than 

scientific principles. Although some type of acceptable limit is required to make the 

process useful, it should be based on similar statistical arguments as the remainder of 

the methodology. In addition, waves approach the coast from all directions facing the 

shoreline. Generally, wave modelers make the decision to limit the angle of wave 

approach because waves propagating nearly parallel to the shoreline generally occur 

infrequently and contain little wave energy. However, the selection of reference line 

length is heavily dependent on the modeler’s choice of wave direction limits. For a 

relatively narrow range of wave directions, the reference line becomes shorter, and the 

more likely wave impacts will be determined significant for a dredging project (and vice 

versa). 

2.4.3 Potential Uncertainties in Wave Information Approach 

 Rather than focusing on the differences between wave and/or sediment transport 

processes directly associated with sand mining, borrow site studies offshore Alabama 

(Byrnes et al., 1999) and New Jersey (Byrnes et al., 2000) determined the significance 

of borrow site impacts from the error associated with wave height and direction 

estimates (Rosati and Kraus, 1991). Using conservative estimates for error associated 

with wave height and wave direction of 10%, sediment transport rates can be predicted 

to within ±35%. These errors can be attributed to the inherent uncertainties in the WIS 

data set (wave height and directional accuracy) used to develop offshore wave 

conditions. The ±35% value is significantly higher than the impacts associated with any 

of the borrow sites evaluated for either Alabama or New Jersey. 

 

 Analysis of uncertainties related to longshore sediment transport estimates 

indicates that variations in transport associated with potential dredging scenarios are an 

order of magnitude lower than the uncertainty associated with sediment transport 

calculations. Therefore, the potential effects of offshore sand mining on longshore sand 

transport rates was determined to be insignificant for the scenarios tested in Alabama 

and New Jersey. Alternative scenarios were not expected to pose any greater effects 

unless the quantity of sand dredged from a site was substantially larger than potential 

dredged volumes selected for these studies. 

 One advantage of using the above methodology for estimating dredging impact 

significance is the direct incorporation of sediment transport calculations, rather than the 

indirect impact associated with changes in wave energy. Impacts to sediment transport 

patterns can be readily observed, since modifications to longshore transport patterns will 

alter the shoreline position along a sandy coast. Basco (1999) indicated that calculation 

of sediment transport quantities and volumes would improve the utility of the reference 

line statistical approach as a management tool. However, incorporation of shoreline 

change and sediment transport calculations was left to future work. 

 Although use of wave information uncertainties offers a simple tool to address 

borrow site impacts, it also contains inherent shortcomings. The method indicates the 

potential errors in wave information; however, it does not evaluate any potential errors 

directly associated with the wave models. If the same offshore wave field is defined for 
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existing and post-dredging conditions, the error associated with wave measurements 

(direction and wave height) may not be the best indicator of borrow site impacts. 

2.4.4 Spatial and Temporal Variations in Wave Climate Approach 

 To directly assess the impacts to coastal processes associated with sand mining, 

a new approach has been developed that considers spatial (longshore) and temporal 

aspects of the local wave climate. This method uses a similar wave modeling effort as 

those needed for the previous two methods; however, modeling of waves is performed 

for the entire 20-year WIS record and five 4-year blocks of the WIS record. In this 

manner, temporal variations in the wave climate are considered relative to average 

annual conditions. From these wave model runs, sediment transport potential curves 

are derived for average annual conditions (based on the full 20-year WIS record) and 

each 4-year period (based on the five 4-year wave records parsed from the full record). 

Applying this information, the average and standard deviation in calculated longshore 

sediment transport potential is determined every 200 m along the shoreline. 

 Assuming the temporal component of sediment transport potential is normally 

distributed, the suggested criterion for accepting or rejecting a potential borrow site is 

based on a range of one standard deviation about the mean. If any portion of the 

sediment transport potential curve associated with a sand mining project exceeds one 

standard deviation of the natural temporal variability (which incorporates 2/3 of the 

variability) in sediment transport potential, the site would be rejected. Although using 

the standard deviation of each 4-year period is more conservative than using a 1-year 

period, the methodology provides a useful indication of sediment transport variability 

relative to the natural system. 

 An example of this method is shown in Figure 2-11, where the alterations in wave 

climate caused by dredging of Sandbridge Shoal, Virginia were determined to be 

insignificant relative to natural variability. The maximum variation in sediment transport 

potential caused by dredging Sandbridge Shoal was determined to be approximately 

25,000 m3

 per year, where the standard deviation of the natural sediment transport 

variability was approximately 100,000 m3

/yr. Due to the orientation of the shoreline and 

the relatively high natural variability in wave climate, an observer on the shoreline is 

unlikely to notice alterations in shoreline position caused by borrow site dredging. For 

this reason, sites with large natural variation in wave climate and associated sediment 

transport potential would be allowed to have larger impacts associated with an offshore 

sand mining project. 

 As a management tool for the MMS, this methodology provides several 

advantages over methods previously employed to assess the significance of borrow site 

impacts. The primary advantages include: 

1. Observed long-term shoreline change is compared with computed longshore 

change in sediment transport potential. Close comparison between these 

two curves indicates that longshore sediment transport potential calculations 

are appropriate for assessing long-term natural change. Therefore, this 

methodology has a model-independent component (observed shoreline 

change) used to ground truth the model results. 

 
21 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 2-11. Example of results for spatial/temporal variability method for determining significance of borrow site dredging impacts. Plots of modeled net transport potential and post-dredging change in transport for borrow sites located offshore Sandbridge, Virginia. Middle plot shows dredging significance criterion envelope (

±

σ) determined for this shoreline. The left plot of the shoreline is 

given for reference. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098

22 

2. The method is directly related to sediment transport potential and associated 

shoreline change. Therefore, impacts associated with borrow site excavation 

can be directly related to their potential influence on observed coastal 

processes (annualized variability in shoreline position). 

3. Site-specific temporal variability in wave climate and sediment transport 

potential is calculated as part of the methodology. For sites that show little 

natural variability in inter-annual wave climate, allowable coastal processes 

impacts associated with borrow site dredging similarly would be limited, and 

vice versa. In this manner, the inter-annual temporal component of the 

natural wave climate is a major component in the determination of impact 

significance. 

4. Similar to methodologies incorporated in previous MMS studies, the 

longshore spatial distribution of borrow site impacts is considered. However, 

the allowable limit of longshore sediment transport variability is computed 

from the temporal component of the analysis. Therefore, the final results of 

this analysis provide a spatially-varying envelope of allowable impacts in 

addition to the modeled impacts directly associated with borrow site 

excavation. The methodology accounts for spatial and temporal variability in 

wave climate, as well as providing a defensible means of assessing 

significance of impacts relative to site-specific conditions. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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23 

3.0 MODELING APPROACH AND APPLICATIONS 

 Excavation of a nearshore borrow site can affect wave heights and the direction of 

wave propagation. The existence of an offshore trough or trench can cause waves to 

refract toward the shallower edges of the borrow site. This alteration to the wave field by 

a borrow area may change local sediment transport rates along the shoreline, where 

some areas may experience a reduction in longshore transport and other areas may 

show an increase. In this study, four offshore areas were investigated to determine the 

potential cumulative physical impacts associated with dredging selected borrow sites to 

their maximum design limits, including 1) southern New Jersey, in the vicinity of 

Townsends and Corsons Inlets; 2) southeastern Virginia, in the vicinity of Sandbridge 

Shoal off Virginia Beach; 3) the North Carolina Outer Banks, between Duck, NC and 

Oregon Inlet; and 4) Canaveral Shoals, southeast of Cape Canaveral, Florida. Wave 

transformation modeling and sediment transport potential calculations were performed 

for existing and post-dredging bathymetric conditions. Comparison of computations for 

existing and post-dredging conditions are used to illustrate the relative maximum impact 

of borrow site excavation on wave-induced coastal processes. 

3.1 ANALYSIS APPROACH 

Sediment transport rates along a coastline are dependent on the wave climate in 

that area. For this study, nearshore wave heights and directions along the shoreline 

landward of proposed borrow sites were estimated using the spectral wave model 

STWAVE to simulate the propagation of offshore waves to the shoreline. Offshore wave 

conditions used as input for wave modeling were derived from two sources: 1) measured 

spectral wave data from offshore data buoys, and 2) hindcast simulation time series 

data, available from the U.S. Army Corps of Engineer’s (USACE) Wave Information 

Study (WIS). 

3.1.1 Wave Modeling 

 Developed by the U.S. Army Engineer Waterways Experiment Station (WES), 

STWAVE v2.0 is a steady state, spectral wave transformation model (Smith, et al., 

1999). Two-dimensional (frequency and direction vs. energy) spectra are used as input 

to the model. STWAVE is able to simulate wave refraction and shoaling induced by 

changes in bathymetry and by wave interactions with currents. The model includes a 

wave breaking model based on water depth and wave steepness. Model output 

includes significant wave height (Hs), peak period (Tp), and mean wave direction (θ ). 

 STWAVE is an efficient program that requires moderate computing resources to 

run well. The model is implemented using a finite-difference scheme on a regular 

Cartesian grid (grid increments in the x and y directions are equal). During a model run, 

the solution is computed starting from the offshore open boundary and is marched in the 

onshore direction in a single pass of the model domain. This is why STWAVE can 

propagate waves only in directions within the ±87.5° half plane. A benefit of using this 

single pass approach is that it uses minimal computer memory, because the only 

memory-resident spectral data are for two grid columns. As such, the changing wave 

spectra across each grid column are in turn computed using the information solely from 

the previous grid column. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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24 

 STWAVE is based on a form of the wave action balance equation. For this model 

the wave action density spectrum, which includes the effects of currents, is conserved 

along wave rays. In the absence of currents, wave rays, correspond to wave 

orthogonals, and the action density spectrum is equivalent to the wave energy density 

spectrum. A diagram showing the relationship between wave orthogonal, wave ray and 

current directions is shown in Figure 3-1. The governing equation of wave 

transformation, using the action balance spectrum, in tensor notation is written as (Smith 

et al., 1999) 

( ) = ∑ −

∂

∂

r r

a ga

i

i ga

C C E S

x

C

ω ω

cos(μ α) (3.1) 

where 

E = E(f,θ) wave energy density spectrum, 

S = energy source and sink terms (e.g., whitecapping, breaking, wind input), 

α = wave orthogonal direction, 

μ = wave ray direction (direction of energy propagation), 

ωr = relative angular frequency (2πfr), 

Ca, Cga = absolute wave celerity and group celerity, respectively. 

The breaking model in STWAVE is based on a form of the Miche criterion as discussed 

by Battjes and Janssen (1978). It sets a maximum limit on the zero-moment wave 

height (Hmo), the wave height based on the distribution of energy in the wave spectrum. 

The formulation of this model is 

Hmo(max) = 0.1L tanh (kd) (3.2) 

where L is the wavelength, k is the wave number (k = 2π/L), and d is the depth at the 

point where the breaking limit is being evaluated. This equation is used with a simpler 

Figure 3-1. Diagram of wave and current vectors used in STWAVE (from Smith et al., 1999). 

Subscript a denotes values in the absolute frame of reference, and subscript r

denotes values in the relative frame of reference (with currents). 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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25 

breaking model, as applied in earlier versions of STWAVE, where the maximum Hmo 

wave height is always expressed as a constant ratio of water depth 

Hmo(max) = 0.64 d . (3.3) 

An advantage to using Equation 3.2 versus Equation 3.3 is that it accounts for increased 

wave breaking resulting from wave steepening caused by wave-current interactions. 

Once model wave heights exceed Hmo(max), STWAVE uses a simple method to reduce 

the energy spectrum, essentially to set the value of Hmo = Hmo(max). Energy at each 

frequency and direction is reduced by the same percentage. As a result, non-linear 

transfers of energy to high frequencies during breaking are not included in STWAVE. 

3.1.2 Input Spectra Development 

 Spectral wave input for STWAVE model runs performed for each of the study 

areas was developed using WIS hindcast data for borrow sites offshore southern New 

Jersey, Dam Neck/Sandbridge Beach (Virginia), Dare County North Carolina, and Cape 

Canaveral (Florida). Alternatively, for the Sandbridge Shoal area offshore southeastern 

Virginia, a five-year spectral wave data record from an offshore buoy maintained by the 

National Data Buoy Center (NDBC) was used to develop model input spectra. The 

NDBC data were used over available WIS data for southeastern Virginia because the 

buoy record was adequately long and represented actual long-term wave conditions in 

the area. In general, buoy data are the preferred source of wave information for 

modeling, because they represent actual offshore measurements rather than hindcast 

information derived from large-scale models. However, very few sites along the U. S. 

East Coast have wave measurement records of sufficient length to justify their use as a 

source of long-term information. 

3.1.2.1 Southern New Jersey WIS Data 

 Wave data for model runs offshore southern New Jersey and Townsends Inlet 

were developed using WIS station AU2067 (Figure 3-2), located approximately 22 km 

southeast of Townsends Inlet, NJ. This WIS record covers a 20-year period from 

January 1976 to December 1995 and includes 58,440 wave events (eight records per 

day). Two wave roses showing percent occurrence of different wave conditions are 

shown in Figure 3-3. The first rose shows how wave height distribution varies with 

direction. The majority of waves (68%) in the WIS record fall within the compass sector 

between 90° and 180°. The dominant wave direction is east-northeast, from which 28% 

of waves in the record propagate. The mean height for all waves in the record is 1.2 m, 

with a standard deviation of 0.7 m. The mean height for waves along the dominant wave 

direction is 1.1 m, with a standard deviation of 0.8 m. The second rose in Figure 3-3 

shows the distribution of peak periods in the record. The mean peak periods for the 

entire record is 7.7 sec, and 26% of the simulated waves in the record have peak period 

greater than 9 sec. 

3.1.2.2 Southeastern Virginia WIS Data 

 Wave input conditions for model simulations offshore southern Virginia were 

developed using WIS hindcast data from station AU2058 (Figure 3-2), The data from 

this station were used to develop the dredging significance envelope discussed in the 

following sections. Station AU2058 is located approximately 17 km offshore Sandbridge, 

VA. The hindcast data for this site cover the same 20-year period as the New Jersey 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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26 

record from WIS station AU2067. The two wave roses showing wave height and wave 

period distributions for station AU2058 are presented in Figure 3-4. Most waves in this 

record (68%) are from the 60 degree compass sector around due east. The prevailing 

wave direction is east-northeast, where 38% of the wave of the WIS record propagate. 

The mean wave height for all waves in the record is 1.2 m, with a standard deviation of 

0.7 m. From the prevailing east-northeast compass sector, the mean wave height is 1.3 

m, with a standard deviation of 0.9 m. The second plot of Figure 3-4 shows the 

distribution of wave periods in the WIS record. The mean period for the entire hindcast 

record is 8.7 sec. 

Figure 3-2. Shoreline from New Jersey to North Carolina with coarse grid limits and wave 

input data stations used to determine dredging impacts from offshore sand 

mining. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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27 

Figure 3-3. Wave height and period for hindcast data from WIS station AU2067 (offshore 

New Jersey) for the 20-year period between January 1976 and December 1995. 

Direction indicates from where waves were traveling, relative to true north. 

Radial length of gray tone segments indicates percent occurrence for each range 

of wave heights and periods. Combined length of segments in each sector 

indicate percent occurrence of all waves from that direction. 

Figure 3-4. Wave height and period for hindcast data from WIS station AU2058 (offshore 

southern Virginia) for the 20-year period between January 1976 and December 

1995. Direction indicates from where waves were traveling, relative to true north. 

Radial length of gray tone segments indicates percent occurrence for each range 

of wave heights and periods. Combined length of segments in each sector 

indicate percent occurrence of all waves from that direction. 

3.1.2.3 North Carolina WIS Data 

 Wave input conditions for simulations offshore North Carolina were developed 

using hindcast data from WIS station AU2056 (Figure 3-2), which is located 

approximately 33 km northeast of Bodie Island, NC. This WIS record covers a 20-year 

period from January 1976 to December 1995. Two wave roses showing percent 

occurrence of different wave conditions are shown in Figure 3-5. The first rose shows 

how wave height distribution varies with direction. The majority of waves (52%) in the 

WIS record fall within the compass sector between 60° and 120°. The dominant wave 

direction is east-northeast, from which 32% of waves in the record propagate. The 

mean height for all waves in the record is 1.5 m, with a standard deviation of 0.9 m. The 

mean height for waves along the dominant wave direction is 1.2 m, with a standard 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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28 

deviation of 0.8 m. The second rose in Figure 3-5 shows the distribution of peak periods 

in the record. A significant number of wave events (32%) have peak periods greater 

than 9 sec, and the mean peak period for the entire record is 8.3 sec. 

Figure 3-5. Wave height and period for hindcast data from WIS station AU2056 (offshore 

North Carolina) for the 20-year period between January 1976 and December 

1995. Direction indicates from where waves were traveling, relative to true north. 

Radial length of gray tone segments indicates percent occurrence for each range 

of wave heights and periods. Combined length of segments in each sector 

indicate percent occurrence of all waves from that direction. 

3.1.2.4 Cape Canaveral WIS Data 

 Wave data for model runs offshore Cape Canaveral were developed using WIS 

station AU2019 (Figure 3-6), which is located approximately 29 km east-northeast of 

Cape Canaveral, FL. Two wave roses showing percent occurrence of different wave 

conditions are shown in Figure 3-7. The first rose shows how wave height distribution 

varies with direction. Most waves (90%) in the record fall within the compass sector 

between 30° and 120°, and the greatest percentage of waves (43%) are from the eastnortheast sector. The mean height for all waves in the record is 1.3 m, with a standard 

deviation of 0.7 m. The mean height for waves along the dominant wave direction is 1.4 

m, with a standard deviation of 0.7 m. The second rose in Figure 3-7 shows the 

distribution of peak periods in the record. The mean peak period for the entire record is 

9.3 sec, and 38% of simulated waves in the record have peak periods greater than 9 

sec. 

3.1.2.5 Development of Model Spectra from WIS Data 

 In order to reduce the offshore extent of the computational grid used by STWAVE, 

the program WAVETRAN was used to propagate WIS waves closer to shore. For the 

New Jersey WIS data, waves were propagated from a depth of 18 m at the station to a 

depth of 17 m, the mean depth along the offshore open boundary of the coarse model 

grid. For the North Carolina data, waves were propagated from a 37-m water depth to a 

24-m water depth approximately 17 km offshore (the seaward limit of the STWAVE grid). 

For the Cape Canaveral model grid, WIS data were propagated from a depth of 27 m to 

24-m water depth at the offshore boundary of the coarse model grid. WAVETRAN is 

part of the Shoreline Modeling System (SMS) developed by WES (Jensen, 1983). 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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Figure 3-6. East Florida shoreline at Cape Canaveral with coarse grid limits and wave input 

data station used to determine dredging impacts from offshore sand mining. 

Figure 3-7. Wave height and period for hindcast data from WIS station AU2019 (Cape 

Canaveral) for the 20-year period between January 1976 and December 1995. 

Direction indicates from where waves were traveling, relative to true north. 

Radial length of gray tone segments indicates percent occurrence for each range 

of wave heights and periods. Combined length of segments in each sector 

indicate percent occurrence of all waves from that direction. 
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 STWAVE input spectra were developed using a second numerical routine which 

re-creates a two dimensional spectrum for each individual wave condition in the 

transformed WIS record. This program computes the frequency and directional spread 

of a wave energy spectrum based on significant wave parameters (i.e., wave height, 

peak period, and peak direction), as well as wind speed. This method is described by 

Goda (1985). The frequency spectrum S(f) is computed using the relationship 

[ ] 4

1/ 3

5

1/ 3 1/ 3

2

1/ 3 ( ) 0.257 ( ) exp 1.03( ) − − S f = H T T f − T f (3.4) 

known as the Bretschneider-Mitsuyasu spectrum, where H1/3 is the significant wave 

height, f is the discrete frequency where S(f) is evaluated, and T1/3 is the significant 

period, estimated from the peak wave frequency (fp) by 

( ) p T 1/ 1.05f 1/ 3 = . (3.5) 

To compute the two-dimensional energy spectrum, a directional spreading function 

G(f,θ) must be applied to the frequency spectrum such that 

S(f,θ ) = S(f )G(f,θ ) . (3.6) 

In this method, the directional spreading function is computed using the relationship 





 



 = 2 ( , ) cos2 θ θ s Go G f (3.7) 

where s is a spreading parameter related to wind speed and frequency, θ is the azimuth 

angle relative to the principle direction of wave travel, and Go is a constant dependent 

upon θ and s. The spreading parameter s is evaluated using the expression 









⋅ ≥

⋅ ≤ = −

p p

p p

s f f f f

s f f f f

s

( / ) :

( / ) :

2.5

max

5

max (3.8) 

where 2.5

max 11.5(2 / )

− s = πfpU g . Wind speed U is therefore used to control the 

directional spread of the spectrum by increasing the directional spread with increasing 

wind speed. Finally, the constant Go is computed by evaluating the integral 

1

max 2

min 2

cos

−















 



 



 = ∫

θ

θ

θ θ G d s

o . (3.9) 

The result is a wave energy spectrum that is based on parameters from the WIS record, 

where spectral energy is distributed based on wave peak frequency and wind speed. An 

example of a two-dimensional spectrum generated by this method is presented in Figure 

3-8. 
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31 

Figure 3-8. Example of STWAVE input spectrum developed using WIS 20-year hindcast data 

and Goda method of computing frequency and direction spectrum. Plots show a) 

frequency distribution of energy at peak direction, b) directional distribution of 

energy at peak frequency, and c) surface plot of two-dimensional energy 

spectrum. Example is model case 5 (Hmo = 0.9 m, θmean = 130° grid relative). 

 After re-creating a two-dimensional spectrum from the parameters given in the 

WIS record, each individual spectrum is sorted (or binned) by peak direction and peak 

period. Wave spectra computed from wave parameters that fall within the limits of 

individual direction and period bins are added together, and a mean spectrum for all 

waves in each bin is computed based on the total number of wave events in the bin. In 

total, six direction bins and two period bins were used to characterize wave data. From 

the 12 total bins, conditions used in the model runs of STWAVE were selected based on 

the percent occurrence and percent energy for conditions in each bin. Selected 

conditions have a percent occurrence greater than two percent and contain more than 

2.5 percent of the energy of the entire wave record. For the four modeled regions 

conditions selected for model runs are shown in Tables 3-1 through 3-4, with significant 

parameters for each input spectrum. 

a) b) c) at peak direction at peak frequency 
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Table 3-1. Significant parameters of input wave spectra used for existing 

and post-dredging STWAVE model runs for New Jersey model grid. 

STWAVE 

model input 

condition 

% occurrence Hmo 

wave height

Mean wave 

period, Tp

Peak wave 

direction, θp

Peak wave 

direction, θp 

Direction 

bin

 m sec deg. true 

north grid relative grid relative

1 6.4 1.4 7.7 61 25 0-30 

2 14.1 1.1 8.3 86 50 30-60 

3 14.1 1.2 7.7 111 75 60-90 

4 17.7 1.2 7.1 131 95 90-120 

Period 

Band 1 

5 6.6 0.8 5.0 161 125 120-150 

6 5.1 1.3 11.1 61 25 0-30 

7 14.5 1.6 11.1 81 45 30-60 

Period 

Band 2 

8 5.8 2.0 10.0 96 60 60-90 

Table 3-2. Significant parameters of input wave spectra used for existing 

and post-dredging STWAVE model runs for Virginia model grid. 

STWAVE 

model input 

condition 

% occurrence Hmo 

wave height

Mean wave 

period, Tp

Peak wave 

direction, θp

Peak wave 

direction, θp 

Direction 

bin

 m sec deg. true 

north grid relative grid relative

1 5.4 0.5 4.4 14 30 0-30 

2 9.1 1.3 5.3 34 50 30-60 

3 8.2 1.4 6.7 64 80 60-90 

4 10.4 1.1 7.3 89 105 90-120 

5 14.2 0.9 7.6 114 130 120-150 

Period 

Band 1 

6 3.4 1.0 4.8 139 155 150-180 

7 9.7 1.5 11.8 74 90 60-90 

8 18.8 1.5 12.9 79 95 90-120 

Period 

Band 2 

9 6.1 1.3 11.2 109 125 120-150 

Table 3-3. Significant parameters of input wave spectra used for existing 

and post-dredging STWAVE model runs for North Carolina model grid. 

STWAVE 

model input 

condition 

% occurrence Hmo 

wave height

Mean wave 

period, Tp

Peak wave 

direction, θp

Peak wave 

direction, θp 

Direction 

bin

 m sec deg. true 

north grid relative grid relative

1 9.4 1.1 5.1 1 25 0-30 

2 8.1 1.9 6.0 21 45 30-60 

3 8.7 1.5 6.7 56 80 60-90 

4 10.1 1.2 7.4 86 110 90-120 

5 16.3 0.9 7.6 106 130 120-150 

Period 

Band 1 

6 8.1 0.6 4.6 131 155 150-180 

7 6.0 1.9 11.5 66 90 60-90 

8 19.2 1.5 12.8 71 95 90-120 

Period 

Band 2 

9 6.3 1.3 11.3 101 125 120-150 
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Table 3-4. Significant parameters of input wave spectra used for existing 

and post-dredging STWAVE model runs for Florida model grid. 

STWAVE 

model input 

condition 

% occurrence Hmo 

wave height

Mean wave 

period, Tp

Peak wave 

direction, θp

Peak wave 

direction, θp 

Direction 

bin

 m sec deg. true 

north grid relative grid relative

1 8.2 1.7 7.7 55 55 30-60 

2 20.8 1.4 7.7 80 80 60-90 

Period 

3 24.6 1.0 7.7 100 100 90-120 

Band 1 

4 2.3 1.5 6.3 130 130 120-150 

5 6.5 1.7 12.5 60 60 30-60 

6 28.5 1.6 14.3 65 65 60-90 

Period 

Band 2 

7 3.4 1.5 11.1 100 100 90-120 

3.1.2.6 Spectral Development from Wave Buoy Data 

 An alternate method was used to develop wave spectra for the southeastern 

Virginia region model. In addition to the WIS record, which was used in model runs to 

determine the dredging significance envelope, spectral input for the Sandbridge Shoal 

STWAVE model was developed using NDBC spectral wave buoy data (NDBC buoy 

44014), which is located approximately 95 km east of False Cape, VA. The buoy record 

was used for model runs executed to determine post-dredging impacts caused by the 

two sites offshore Sandbridge, VA. This buoy record covers a 5-year period from 

January 1996 to December 2000. Wave roses showing the percent occurrence of 

different wave conditions is illustrated in Figure 3-9. 

Figure 3-9. Wave height and wave period roses for data recorded by NDBC buoy 44014 

(offshore Virginia Beach) for the 5-year period between January 1996 and 

December 2000. Direction indicates the direction waves were propagating from 

relative to true north. Radial length of gray tone segments indicates percent 

occurrence of each range of wave condition (height or period). Combined length 

of segments in each sector indicates percent occurrence of all waves from that 

direction. 

 The first rose shows how wave height distribution varies with direction. The 

majority of waves (69%) in the buoy record fall within the broad compass sector between 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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60° and 180°. The dominant wave direction is south-southeast, where 18% of waves in 

the record propagate. The mean significant wave height for all conditions in the record 

is 1.4 m, with a standard deviation of 0.9 m. The second rose in Figure 3-8 shows the 

distribution of peak periods in the record. A significant number of wave events (22%) 

have peak period greater than 10 sec, and the mean dominant periods for the entire 

record is 7.9 sec. 

 In order to reduce the offshore extent of the computational grid used by STWAVE, 

a computer program was developed to propagate buoy spectra, from 47.5-m water 

depth at the buoy to 16.6-m water depth approximately 15 km offshore (the seaward limit 

of the coarse STWAVE grid). The method employed to refract buoy spectra also was 

used in WIS Phase III (Jensen, 1983). This method is based on the conservation of 

energy along wave rays and Snell’s law. For monochromatic waves, assuming straight 

and parallel bottom contours, shallow water wave height after shoaling and refraction is 

expressed as the product of the offshore wave height H0 with the shoaling and refraction 

coefficients (Ks and Kr respectively): 

H = H0KsKr (3.10) 

where the shoaling coefficient is determined using the group velocity of offshore (Cg0)

and shallow water (Cg) wave conditions, expressed as Ks=(Cg0/Cg)

0.5, and the refraction 

coefficient is determined using the approach angle of the incident offshore wave θ0 and 

the angle of the refracted shallow water wave θ, expressed as Kr=(cosθ0/cosθ)

0.5. In 

terms of energy for a wave spectrum, the total energy of the refracted spectrum can be 

expressed in terms of the initial two-dimensional (f frequency, and θ direction) energy 

spectrum E(f, θ) (Jensen, 1983), 

∫ ∫

∞

∂

∂ =

0

2

0 0

0

( )

( ) ( , )

π

θ

θ

θ θ d df

cc

cc

E E f

g

g

t (3.11) 

where the term 

0

0

( )

( )

θ

θ

∂

∂

g

g

cc

cc

 (3.12) 

is essentially the combined refraction and shoaling coefficients. Therefore, Equation 

3.11 is applied to individual spectral components, using Snell’s law to determine ∂θ/∂θ0

for each direction bin in the spectrum. Finally, the shallow water wave angle of the 

refracted component is determined using Snell’s law directly, θ(f, d, θ0)=sin-1(c/c0sinθ0). 

 Before transforming buoy spectra to the offshore limit of the computational grid, an 

additional numerical routine was used to sort the spectral data for each individual wave 

record in the transformed buoy data. Each wave record was sorted by peak direction 

and peak period. Wave spectral components computed from wave parameters that fall 

within the limits of individual direction and period bins are summed, and a twodimensional (frequency and direction) mean spectrum for all waves in each bin is 

computed based on the total number of wave events in the bin. In total, a matrix of six 

direction bins versus two period bins were used to characterize the wave data. From the 

12 total bins, conditions used in the STWAVE model runs were selected based on 
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35 

percent occurrence and energy content of conditions in each bin. The 11 conditions 

selected for model runs are shown in Table 3-5, with significant parameters for each 

input spectrum. 

Table 3-5. Significant parameters for input wave spectra used for existing 

and post-dredging STWAVE model runs for offshore southeastern Virginia sites. 

STWAVE 

model input 

condition 

% occurrence Hmo 

wave height

Peak wave 

period, Tp

Peak wave 

direction, θ

p 

Peak wave 

direction, 

 θp 

Direction 

bin

 m sec deg. true 

north grid relative grid relative

1 7.2 1.6 7.7 359 15 0-30 

2 7.7 1.6 8.3 34 50 30-60 

3 8.1 1.4 9.1 54 70 60-90 

4 10.1 1.1 8.3 104 120 90-120 

5 13.2 1.1 8.3 119 135 120-150 

Period 

Band 1 

6 15.2 1.2 8.3 149 165 150-180 

7 2.0 2.8 11.1 39 55 30-60 

8 7.5 2.0 11.1 64 80 60-90 

9 5.2 1.6 11.1 79 95 90-120 

10 3.4 1.8 10.0 134 150 120-150 

Period 

Band 2 

11 1.2 2.4 10.0 144 160 150-180 

3.1.3 Grid Development 

 Along with input spectra, bathymetry grids were developed for existing and postdredging scenarios. Plots of coarse and fine-nested grids for modeled regions are 

shown in Figures 3-10 through 3-17. For each of the four modeled areas, two coarse 

grids were developed that have the same geographical coverage and differ only by 

modifications to bathymetry in the borrow area. The maximum cumulative dredged 

volumes and mean depths for the modeled borrow sites for each region are shown in 

Table 3-6. The National Ocean Service (NOS) was the primary source of bathymetric 

data used to create the grids (NOS, 1998). However, these data were supplemented by 

other sources of data when needed (i.e., digitized NOAA chart bathymetry for areas 

along the North Carolina shoreline), or when more recent survey data were available 

(i.e., recent USACE surveys of the nearshore region along Cape Canaveral, FL). 

Depths at the offshore open boundary of the coarse grids vary between 9.2 and 21.4 m 

for the southern New Jersey coarse grid, 10.5 and 24.6 m for the southeastern Virginia 

coarse grid, 19.0 and 31.0 m for the North Carolina grid, and 19.3 and 29.7 m for the 

Cape Canaveral grid. 

 The spatial extent of each model coarse grid is given in Table 3-7. The 

geographical limits of the grids were chosen based on wave conditions available for 

model runs. Wave conditions with relatively small angles to the shoreline require a large 

grid in the longshore direction so the site of interest (i.e., the borrow site and affected 

shoreline) does not fall within the “shadow” of lateral grid boundaries. The grids all have 

a node spacing of 200 m. Grid axes are rotated to match the orientation of the shoreline 

in the modeled area. 

 Fine grids also were developed for each region in order to obtain greater resolution 

of waves in the nearshore behind the borrow site (Figure 3-11, 3-13, 3-15, and 3-17), 
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particularly in the surf zone. For each region, the same fine grid was used for existing 

and post-dredging conditions. Alongshore and cross-shore node spacing for fine grids is 

20 m for all four regions. Boundary conditions (wave spectra) at the offshore and lateral 

boundaries of the fine grids were extracted from coarse-grid model runs. Therefore, 

boundary conditions vary along the length of the open boundary of the fine grid (nested 

into the coarse grid model solution). 

Figure 3-10. Color contour plot of coarse model grid (200 m x 200 m grid spacing) of offshore 

New Jersey. Depths are relative to NVGD. Borrow site locations are indicated 

by solid black lines, and fine grid limits are indicated by a dashed line. 
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Figure 3-11. Color contour plot of the nested fine model grid (20 m x 20 m grid spacing) used 

with STWAVE for offshore New Jersey. Depths are relative to NVGD. Borrow 

site location is indicated by solid black line, and fine grid limits are indicated by 

dashed line. 

Table 3-6. Maximum estimated cumulative borrow site excavation 

dimensions for the four sand resource areas. 

Region 

Site 

Designation 

Volume 

(106 m3) 

Area 

(106 m2) 

Excavation 

Mean Depth 

(m) 

New Jersey A1 8.8 2.2 4.0 

 A2 7.8 2.6 3.0 

 M8 8.0 4.0 2.0 

Virginia A 5.3 1.8 3.0 

 B 6.9 2.3 3.0 

North Carolina 3 east 1.4 0.7 2.0 

 3 west 2.5 0.8 3.0 

Florida 2 26.0 5.0 5.2 
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Figure 3-12. Color contour plot of coarse model grid (200 m x 200 m grid spacing) of offshore 

southeastern Virginia. Depths are relative to NVGD. Borrow site locations are 

indicated by solid black lines, and fine grid limits are indicated by a dashed line. 

Dam Neck 

Sandbridge 
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Figure 3-13. Color contour plot of the nested fine model grid (20 m x 20 m grid spacing) of 

offshore southern Virginia used with STWAVE. Depths are relative to NVGD. 

Borrow site location is indicated by solid black line, and fine grid limits are 

indicated by dashed line. 
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Figure 3-14. Color contour plot of coarse model grid (200 m x 200 m grid spacing) for offshore 

North Carolina. Depths are relative to NVGD. Borrow site locations are 

indicated by solid black lines, and fine grid limits are indicated by a dashed line. 
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Figure 3-15. Color contour plot of the nested fine model grid (20 m x 20 m grid spacing) for 

offshore North Carolina. Depths are relative to NVGD. Borrow site location is 

indicated by solid black line, and fine grid limits are indicated by dashed line. 
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Figure 3-16. Color contour plot of coarse model grid (200 m x 200 m grid spacing) for offshore 

Cape Canaveral, FL. Depths are relative to NVGD. Borrow site locations are 

indicated by solid black lines, and fine grid limits are indicated by a dashed line. 
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Figure 3-17. Color contour plot of the nested fine model grid (20 m x 20 m grid spacing) for 

offshore Cape Canaveral, FL. Depths are relative to NVGD. Borrow site location 

is indicated by solid black line, and fine grid limits are indicated by dashed line. 
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Table 3-7. Numerical grid dimensions for offshore (coarse) and nearshore (fine) 

grids. Dimensions are given as (cross-shore x alongshore). 

Coarse Grid 

(200 m spacing) 

Fine Grid 

(20 m spacing) Region 

nodes distance 

(km) nodes distance 

(km) 

grid angle (deg 

CW from north) 

New Jersey 90 x 325 18 x 65 200 x 1800 4 x 36 36 

Virginia 85 x 250 17 x 50 150 x 1360 3 x 27 -16 

North Carolina 87 x 425 17 x 85 210 x 1250 4 x 25 -24 

520 x 730 10 x 15 Florida 141 x 434 28 x 87 160 x 1400 3 x 28 0 

3.1.4 Sediment Transport Potential 

 Initially, calculations of sediment transport potential were performed to indicate the 

maximum quantity of transport possible based on a sediment-rich environment. Results 

from spectral wave modeling formed the basis for evaluating changes in sediment 

transport rates along the beach. Longshore transport depends on long-term fluctuations 

in incident wave energy and the resulting longshore current. Therefore, annual transport 

rates were calculated from long-term wave statistics. 

 The longshore sediment transport equation employed in this study is based on the 

formulation presented by the U.S. Army Corps of Engineers (USACE, 1984). In general, 

the longshore sediment transport rate is assumed to be proportional to the longshore 

wave energy flux at the breaker line, which is dependent on wave height and direction. 

Because the transport equation was developed using data from sediment-rich 

environments (no hardened structures), it typically over-predicts sediment transport rates 

along many coasts. However, the formula provides a useful technique for comparing 

erosion/accretion trends along a shoreline of interest. 

 The volumetric longshore transport, Q, past a point on a shoreline is computed 

using the relationship: 

s ga

I Q − ′ = ( 1)ρ

 (3.13) 

where I is the immersed weight longshore sediment transport rate, s is the specific 

gravity of sediment, a’ is the void ratio of the sediment, and ρ is the density of seawater. 

 The immersed weight longshore sediment transport, I, can be computed using the 

CERC formula (USACE, 1984), 

KP s I = l (3.14) 

where K is a dimensionless coefficient and Pls is the longshore energy flux factor 

computed using the following relationship: 

s Hsb b

g P α

γ

ρ sin2

16

5 / 2

3 / 2

l = (3.15) 
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where Hsb is the significant wave height at breaking, γ is the coefficient for the inception 

of wave breaking (γ=Hb/hb), and αb is the breaking wave angle. Generally, a value of 

K=0.4 is used with significant wave heights (as computed by STWAVE), or the more 

familiar value K=0.77 is used with RMS wave height. 

 For this study, an alternate method was used to compute immersed weight 

longshore sediment transport, as described by Kamphuis (1990). This method is a 

modification to the original CERC formula that adds a dependency on the median grain 

diameter of beach sediment and incorporates the surf similarity parameter, ξb, expressed 

as 

( )0.5

0 H / L

m

b

ξ b = (3.16) 

where m is the bottom slope and Lo is the deep water wavelength. The complete 

expression of Kamphuis is given by 

( ) () bT md Hs b

g I K g ξ θ

π

ρ sin 2

2

0.25 2.5 0.6

50

0.5

0.75

* −





 



 = (3.17) 

where the coefficient K* = 0.0013. 

 Sediment transport computations were based on wave information at breaking for 

each grid cell along the modeled coastline. The shoreline segment incorporates the 

influence of all changes to nearshore wave climate associated with proposed dredging 

activities. Computations of sediment transport rates for each wave condition were 

performed and then weighted by the annual percent occurrence. Sediment transport 

potential was computed for existing and post-dredging conditions. 

3.2 MODEL RESULTS 

 Due to the redistribution of wave energy and alteration of wave directions resulting 

from offshore sand excavation, changes to longshore sediment transport patterns will 

occur. Depending on the net direction of local sediment transport, the influence of 

borrow site conditions can either increase or decrease net littoral drift. Example model 

cases for each of the four sites are discussed in the following subsections. Complete 

wave model output for the four modeled regions, showing wave heights and wave height 

difference plots between existing and post-dredging conditions for all modeled wave 

cases, are given in Appendices B through E. 

3.2.1 Wave Modeling 

 Overall, post-dredging wave model output for the four study sites illustrates 

reduced wave heights landward of borrow sites and increased wave heights at the 

longshore limits of the borrow site. This effect is more pronounced for cases with larger 

wave heights and longer periods. As waves propagate across a borrow site (deeper 

water than the surrounding area), wave refraction bends waves away from the center of 

the borrow site and toward the shallower edges. The net effect is to create a shadow 

zone of reduced wave energy immediately landward of the borrow site and a zone of 

increased wave energy updrift and downdrift of the borrow site. 
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 This shadowing effect is apparent in model results presented in Figure 3-18 for 

offshore southern New Jersey. In this figure, color contours represent coarse grid wave 

height differences between model results computed for existing and post-dredging 

conditions. In the immediate vicinity of the borrow site, wave heights increased by a 

maximum of 0.20 m at the northern and southern edges of the borrow site and 

decreased by a maximum of 0.19 m behind the borrow site. In Figure 3-19, fine grid 

model results for the same wave condition (case 7) show how waves propagate toward 

shore landward of proposed borrow sites. The wave shadow generated by Site M8 is 

most prominent. For this wave case, the maximum wave height difference between 

existing and post-dredging conditions is 0.27 m at the borrow site, but closer to shore 

within the fine grid, the maximum wave height difference is reduced to 0.06 m. 

Figure 3-18. Example of coarse grid wave height difference plot between existing and postdredging bathymetry conditions offshore Townsends Inlet, NJ. This result is for 

NJ wave case 7; 1.6 m wave height and 11.1 sec period. 

 Because these are spectral wave model results, and because different frequencies 

in the spectrum are refracted by varying degrees at the borrow area, the areas of 

increased and reduced wave height gradually diffuse as the wave field approaches 

shore. As a result, the extent of this energy diffusion can be considerably longer than 

the borrow area. For this particular example, the length of shoreline affected by Site M8 

is approximately three times greater than the alongshore dimension of the borrow site. 

 Although borrow sites that are further offshore impact a longer length of shoreline, 

the actual magnitude of impact is lower because the affected wave field has had a 

greater distance over which to diffuse energy. This is illustrated in a comparison of wave 

transformation impacts for borrow sites M8 and A1 in Figure 3-18. Borrow Site A1 

causes a greater local difference in wave heights primarily because it has a greater 

excavated depth. However, because the borrow site is further offshore, wave height 

change from existing to post-dredging conditions at the shoreline is less than the 

changes that are caused by borrow Site M8, as seen in Figure 3-19. 

Townsends Inlet 
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Figure 3-19. Example of fine grid wave height difference plot between existing and postdredging bathymetry conditions offshore Townsends Inlet, NJ. This result is for 

NJ wave case 7; 1.6 m wave height and 11.1 sec period. 

 In addition to wave impacts resulting from borrow site excavation, wave heights 

and directions are modified by natural offshore bottom features as well. From the 

existing conditions model results for offshore North Carolina, it is seen how bottom 

features offshore the Outer Banks modify the wave field as it propagates shoreward. 

Model output presented in Figure 3-20 shows how waves respond to offshore shoals, 

even in relatively deep water (>15 m). For example, an area of reduced wave heights 

starting in the vicinity of 450,000 E, 3,985,000 N is caused by shallower areas 

immediately north and south. The shoal areas refract the wave field, causing a slight 

focusing of wave energy behind each feature. Because energy is conserved, the 

focusing of wave energy behind the shoal causes a reduction in energy at the northern 

and southern edges of the shoal, which is apparent by reduced wave heights in these 

areas. Another example of energy focusing caused by offshore features is show in 

Figure 3-21, for Sandbridge Shoal offshore Virginia Beach. The focusing effect of shoals 

is clear in this southeast wave condition. As wave energy is focused on the shoreline in 

the vicinity of Rudee Inlet in this example, there is a concurrent decrease in wave energy 

to the southwest of the shoals. 

 In addition to the effects of bottom features far offshore, waves are refracted by the 

straight and parallel bottom contours in the nearshore. In Figure 3-22, fine grid results 

show how wave directions change as the wave field propagates shoreward. For this SE 

wave condition (as in Figure 3-21) waves refract and the mean direction of wave 
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propagation becomes more shore-normal (perpendicular to the shoreline). In addition to 

the change in wave direction, wave heights are also modified by nearshore bathymetry. 

Waves begin to shoal (increase in height) about 440 m offshore, and increase in height 

by 0.1 m before breaking begins. Wave heights are reduced as energy is dissipated in 

the surf zone, which is about 120 m wide in this example. 

 The following discussion summarizes wave modeling results for the most common 

wave approach conditions at each potential sand resource area. Existing and postdredging model results are described with reference to natural offshore bottom features 

and bathymetry changes resulting from proposed sand dredging. 

Figure 3-20. Coarse grid model results for offshore North Carolina (wave case 9; 1.3 m wave 

height, 11.3 sec period) illustrating area of reduced wave heights resulting from 

refraction of wave energy due to bottom bathymetry. 

3.2.1.1 Offshore New Jersey 

 Examples of wave model output for existing conditions offshore southern New 

Jersey are shown in Figures 3-23 and 3-24 (wave cases 4 and 7 of Table 3-1). Case 4 

has 1.2 m waves with a 7.1 sec peak period propagating from the southeast. The 

coarse grid results presented in Figure 3-23 illustrate that the direction of wave 

propagation is directly onshore; therefore, the effects of wave refraction are not 

discernable until waves are well within a kilometer of the shoreline. Waves increase in 

height and break on the shoals present in the vicinity of each of the modeled inlets. The 

highest refracted wave height for this case is about 1.5 m, which occurs in the shoals 

near Great Egg Harbor Inlet. Immediately offshore the coastline between Townsends 

and Great Egg Harbor Inlet, wave height reductions are observed that result from wave 

energy spreading by refraction along the gently crescent-shaped bottom contours of this 

area. 

area of reduced 

wave heights 
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Figure 3-21. Coarse grid model results for Sandbridge Shoal, Virginia for wave case 10 (1.8 m 

wave height, 10.0 sec wave period) showing wave focusing effect of natural 

shoal deposits and area of reduced wave heights to the southwest of the shoals. 

Figure 3-22. Fine grid model results for Sandbridge Shoal, Virginia for the same wave case 

presented in Figure 3-21. Detailed analysis illustrates nearshore refraction of 

waves and wave height reductions through the width of the surf zone. 

 

Rudee Inlet 
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 In Figure 3-24, the results of wave Case 7 illustrate how 1.6 m, 11.1 sec waves 

propagating from the east are transformed as they approach the coast. The effects of 

wave refraction are more pronounced in this example as wave rays are seen to 

gradually arc toward shore-normal about 4 km offshore. Offshore wave height 

differences are more dramatic than the previous example due to the combination of the 

higher wave height, longer wavelength, and a more oblique offshore approach angle. In 

several offshore regions, wave heights have been reduced by approximately 0.25 m due 

to spreading of wave energy by refraction. In contrast to Case 4, where highest wave 

heights in the model grid occur are associated with inlet ebb shoals, the highest wave 

heights for Case 7 occur on the offshore shoal in the vicinity of borrow site A2. At this 

shoal, wave heights reach 2.1 m, a half-meter increase over the offshore boundary 

condition. 

Figure 3-23. Plot of STWAVE model output for southern New Jersey wave Case 4 (Hs=1.2 m, 

Tpeak=7.1 sec, θpeak=131 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. 

 Plots of wave height difference between existing and post-dredging conditions for 

Cases 4 and 7 are presented in Figures 3-25 and 3-26. For Case 4, the maximum 

change in wave heights is ±0.05 m. Borrow Site A1 has a greater influence on wave 

Townsends Inlet 

Corsons Inlet 

Hereford 

Inlet 

Great Egg 

Harbors Inlet
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heights than other sites, where wave heights increase at the northeast and southwest 

edges due to wave refraction, and a corresponding decrease in wave heights is present 

between these margins. For wave Case 4, the length of shoreline impacted by the 

combination of the three borrow sites is approximately 20 km between Townsends and 

Great Egg Harbor Inlets. 

Figure 3-24. Plot of STWAVE model output for southern New Jersey wave Case 7 (Hs=1.6 m, 

Tpeak=11.1 sec, θpeak=81 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. 

 The wave difference plot for Case 7 in Figure 3-26 again shows that site A1 has 

the greatest influence on wave heights. Maximum wave height changes are ±0.25 m, 

near Site A1. The greatest increase in wave heights occurs long the southwestern 

margin of Site A1. For Site A2, the resulting wave shadow from the borrow site is much 

more focused than what is indicated for Case 4. This results from the geometry of the 

site, which is long and narrow, because waves are propagating along the major axis of 

the site in this case. Because offshore waves propagate from a more oblique angle 

relative to the shoreline than in Case 4, the area of shoreline influence for the three sites 

is considerably longer. For this case, approximately 30 km of shoreline between 

Hereford and Great Egg Harbor Inlets is in the zone of influence of the three sites. 

Townsends Inlet 

Corsons Inlet 

Hereford 

Inlet 

Great Egg 

Harbors Inlet
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Figure 3-25. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at indicated borrow sites for STWAVE model output of southern New 

Jersey wave Case 4 (Hs=1.2 m, Tpeak=7.1 sec, θpeak=131 deg). 

3.2.1.2 Offshore Southeastern Virginia 

 Wave model output for wave Cases 7 and 10 (see Table 3-5) for southern Virginia 

are presented in Figures 3-27 and 3-28. The results of Case 7 are for a 2.8 m wave with 

a peak period of 11.1 sec, propagating from the northeast. Because these waves 

basically are moving directly onshore and nearshore bathymetric contours are generally 

parallel to the shoreline, wave directions do not change significantly until they are very 

close to shore. The maximum refracted wave height in the model grid is 3.3 m, which is 

0.5 m greater than the boundary condition. These maximum wave heights occur just 

outside the seaward extent of the surf zone, prior to the inception of wave breaking. 

Aside from wave height reductions seen near the top lateral boundary of the model grid 

(at the entrance to Chesapeake Bay), significant differences in offshore wave heights 

are not present due to the limited effect of refraction in this onshore wave condition. 

Townsends Inlet 

Corsons Inlet 

Hereford 

Inlet 

Great Egg 

Harbors Inlet
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Figure 3-26. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at indicated borrow sites for STWAVE model output of southern New 

Jersey wave Case 7 (Hs=1.6 m, Tpeak=11.1 sec, θpeak=81 deg). 

 A second example of model output for southeastern Virginia is shown in Figure 3-

28, for Case 10 (see Table 3-5). The offshore wave condition used for this model run 

was a 1.8 m high, 10 sec peak period wave that propagates from the southeast. The 

plot of this wave condition shows significant modifications to the offshore wave field that 

result from complex bathymetric features present at Sandbridge Shoal. Wave energy in 

this case is focused by the shoals, which results in an area of increased wave heights in 

the vicinity of Rudee Inlet. Maximum increased wave heights in this zone are 0.5 m 

above the offshore condition, or 2.3 m. This zone of increased wave heights extends 

approximately 10 km on either side of Rudee Inlet. As a result of the wave focusing by 

the shoals, there is a corresponding decrease in wave heights south of the shoals, 

shoreward to Sandbridge. An area of maximum decrease in wave height is indicated 

just seaward of Sandbridge, where wave heights are approximately 0.8 m less than at 

the offshore boundary. The full extent of the area of reduced wave heights is 

approximately 15 km. 

 Additional plots showing wave height changes that result from dredging the full 

design volumes at sites A and B for Cases 7 and 10 are shown in Figures 3-29 and 3-

30. For waves modeled in Case 7, a case where waves are propagating almost directly 

onshore, maximum wave height changes are ±0.35 m. The largest decreases in wave 

heights after dredging are illustrated near Site B, at the western vertex of the triangle 

Townsends Inlet 

Corsons Inlet 

Hereford 

Inlet 

Great Egg 

Harbor Inlet 
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that defines this site. The region of maximum wave height increase is found in the area 

between the two sites, resulting from the combined influence of Sites A and B. Wave 

energy is refracted by Site B to the south, where it combines with wave energy that has 

been refracted to the northwest by Site A, resulting in the observed increased wave 

heights. The shoreline potentially impacted by the presence of the two sites for wave 

model case 7 extends approximately 10 km alongshore in the vicinity of Sandbridge. 

Figure 3-27. Plot of STWAVE model output for southeastern Virginia wave Case 7 (Hs=2.8 m, 

Tpeak=11.1 sec, θpeak=39 deg). Color contours indicate wave height, and vectors 

show mean direction of wave propagation. 

Dam Neck 

Sandbridge 
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Figure 3-28. Plot of STWAVE model output for southeastern Virginia wave Case 10 (Hs=1.8 

m, Tpeak=10.0 sec, θpeak=134 deg). Color contours indicate wave height, and 

vectors show mean direction of wave propagation. 

Dam Neck 

Sandbridge 
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Figure 3-29. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at borrow sites A and B for STWAVE model output for southeastern 

Virginia wave Case 7 (Hs=2.8 m, Tpeak=11.1 sec, θpeak=39 deg). 

 A plot of wave height changes for Case 10 between existing and post-dredging 

model conditions is shown in Figure 3-30. Modeled wave height changes range 

between 0.2 and -0.35 m. The zone of influence along the shoreline for the two sites 

extends approximately 12 km, from just north of Rudee inlet to Sandbridge. Maximum 

wave height reductions occur near Site A for this case, and the greatest increased wave 

heights occur in the area between the two sites. The shadow zones (areas of reduced 

wave height) from each borrow site merge to form a single shadow zone at about 3 km 

offshore. 

Dam Neck 

Sandbridge 
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Figure 3-30. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at borrow sites A and B for STWAVE model output for southeastern 

Virginia wave Case 10 (Hs=1.8 m, Tpeak=10.0 sec, θpeak=134 deg). 

3.2.1.3 Offshore North Carolina 

 Examples of wave model output for offshore North Carolina are illustrated in 

Figures 3-31 (Case 2) and 3-32 (Case 8). For Case 2, shoals offshore Oregon Inlet 

produce a small increase in wave heights landward of the shoals, with a corresponding 

small decrease in wave heights seaward of the shoals. Otherwise, no significant 

shoaling or refraction is observed in this relatively short period wave case. 

 

Dam Neck 

Sandbridge 
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Figure 3-31. Plot of STWAVE model output for offshore North Carolina wave Case 2 (Hs=1.9 

m, Tpeak=6.0 sec, θpeak=21 deg). Color contours indicate wave height, and 

vectors show mean direction of wave propagation. 
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Figure 3-32. Plot of STWAVE model output for offshore North Carolina wave Case 8 (Hs=1.5 

m, Tpeak=12.8 sec, θpeak=71 deg). Color contours indicate wave height, and 

vectors show mean direction of wave propagation. 

 Model output for wave Case 8 (see Table 3-5) is shown in Figure 3-32. This wave 

condition has a significantly longer period than the previous example, and as a result, 

waves are much more affected by offshore bathymetry gradients. Although the direction 

of wave propagation is not modified as much as was indicated in previous examples, 
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wave heights have changed significantly (e.g., a maximum height of 2.4 m at the 

southern side of Oregon Inlet) relative to offshore conditions. At the offshore shoals 

directly east of the inlet, wave heights increase approximately 0.7 m over the offshore 

boundary condition. Several shoal areas along the modeled coastline show similar 

impacts on wave heights, including the area encompassing the two modeled borrow 

sites. 

 Plots of wave height change from existing and post-dredging conditions at the two 

borrow sites are shown in Figures 3-33 and 3-34 for wave Cases 2 and 8. For Case 2 

results (Figure 3-33), the area of influence for sites 3 East and 3 West extends 

approximately 20 km around Oregon Inlet. The extent of influence is the result of the 

approach angle for offshore waves. The greatest increase in wave heights resulting 

from the potential dredging was south of the western borrow site, where wave heights 

increased 0.04 m over existing conditions. The area of greatest wave height reduction 

also is located near the western borrow site, where wave heights decreased 0.07 m from 

existing conditions. 

Figure 3-33. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at borrow sites 3 East and 3 West for STWAVE model output for 

offshore North Carolina wave Case 2 (Hs=1.9 m, Tpeak=6.0 sec, θpeak=21 deg). 
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 Figure 3-34 presents the wave height difference plot for Case 8 (see Table 3-5). 

The two borrow sites have an overlapping region of influence, as site 3 West is located 

directly landward of the site 3 East along the direction of wave propagation. The area of 

maximum increased wave heights for post-dredging conditions is located at the northern 

corner site 3 West, where wave heights increase 0.06 m over existing conditions. 

Similar to the southeastern Virginia examples, wave height increase is the result of the 

combined influence of the two sites. The area of maximum wave height decrease is 

located landward of site 3 West, where wave heights are reduced by 0.07 m from 

existing conditions. Again, this maximum wave height reduction results from the 

combined impacts of the two sites. In a later section of this report (Section 4), it is 

determined that the cumulative impact of changes at each site are simply additive. 

Figure 3-34. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at borrow sites 3 East and 3 West for STWAVE model output for 

offshore North Carolina wave Case 8 (Hs=1.5 m, Tpeak=12.8 sec, θpeak=71 deg). 

3.2.1.4 Offshore Cape Canaveral 

 The results of two example wave cases are presented for offshore Florida in 

Figures 3-35 and 3-36. Output for existing conditions offshore Cape Canaveral for wave 

Case 3 (Table 3-4) is presented in Figure 3-35. Canaveral Shoals, the complex of 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098

62 

ridges and troughs that extend southeast from Cape Canaveral, cause significant 

increases in wave heights as waves propagate over this area. As waves refract over the 

shoals, wave heights increase by 0.5 m over the offshore boundary condition. In the 

 Figure 3-35. Plot of STWAVE model output for Cape Canaveral, Florida wave Case 3 (Hs=1.0 

m, Tpeak=7.7 sec, θpeak=100 deg). Color contours indicate wave height, and 

vectors show mean direction of wave propagation. 

Canaveral Inlet

Cape Canaveral 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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63 

Figure 3-36. Plot of STWAVE model output for Cape Canaveral, Florida wave Case 6 (Hs=1.6 

m, Tpeak=14.3 sec, θpeak=65 deg). Color contours indicate wave height, and 

vectors show mean direction of wave propagation. 

Canaveral Inlet

Cape Canaveral 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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64 

shoal areas located northeast of the Cape, wave heights increase by about 0.3 m above 

offshore wave heights. Wave direction changes also are observed at the shoals. 

 A greater degree of direction change is seen in the model output for Case 6 

(Figure 3-36). The offshore wave boundary condition is a 1.6 m, 14.3 sec wave 

propagating from the east-northeast. Vectors indicating wave direction illustrate that for 

some nearshore regions adjacent to the Cape, the direction of wave propagation 

changes more than 45 degrees, following the gradient in bathymetric contours. The 

largest waves in the model domain occur at the shoals north of Cape Canaveral, and are 

1.3 m higher than offshore waves. At shoals in the vicinity of the borrow site, wave 

heights increase to a maximum of 2.8 m, 1.2 m above offshore conditions. Shoals tend 

to refract wave energy and focus it near the cusp of the Cape. Wave energy is focused 

away from the coast south of Cape Canaveral, and an area of reduced wave heights is 

created. 

 Wave height change plots are shown in Figures 3-37 and 3-38 for Cases 3 and 6, 

respectively. For Case 3, maximum wave height increase resulting from dredging the 

borrow site is 0.2 m, and the maximum decrease in the shadow zone of the site is 0.3 m. 

The overall area of influence of this borrow site extends approximately 14 km north of 

the Cape to about 4 km south of Port Canaveral. 

 Similar wave difference results are illustrated for Case 6 (Figure 3-38). Maximum 

changes in post-dredging wave heights were ±0.7 m, which are substantially greater 

than changes observed at previous sites. The area of greatest wave height increase 

occurs at the northwest corner of the site. Wave heights do not increase by the same 

amount at the southwest corner, likely due to the geometry and bathymetry of the site. 

Deeper excavation depths at the northwest corner cause a greater degree of wave 

refraction. The alongshore extent of influence is similar to that of Case 3, but it is shifted 

slightly southward due to the different direction of wave propagation. 

3.2.2 Sediment Transport Potential 

 Comparisons of average annual sediment transport potential were performed for 

existing and post-dredging conditions to indicate the relative impact of dredging to 

longshore sediment transport processes. Sediment transport potential is a useful 

indicator of shoreline impacts caused by offshore borrow sites because the 

computations include the borrow site influence on wave height and direction. For each 

study area, the net sediment transport potential associated with average annual 

conditions was computed. Post-dredging model conditions in each study area are listed 

in Table 3-7. These values represent the recommended maximum excavation depths 

for each individual site, whether dredged during the course of one project or over the 

coarse of several projects. 

3.2.2.1 Model Comparison with Historical Shoreline Change 

 To ensure that the spectral wave modeling and the associated longshore sediment 

transport potential could be utilized effectively to evaluate long-term alterations to the 

littoral system, a comparison of model predictions with observed shoreline change was 

performed. This analysis provides a semi-quantitative method for determining whether 

a) longshore wave-induced transport is responsible for observed shoreline change, and 

b) the long-term shoreline change trends are consistent with the shorter time-period (20-

year) sediment transport potential analyses. For the four potential sand resource areas, 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098

65 

Figure 3-37. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at Borrow Site 2 for STWAVE model output for Cape Canaveral, 

Florida wave Case 3 (Hs=1.0 m, Tpeak=7.7 sec, θpeak=100 deg). 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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66 

Figure 3-38. Plot of wave height change between existing and post-dredging (∆=Hpost-Hpre) 

conditions at Borrow Site 2 for STWAVE model output for Cape Canaveral, 

Florida wave Case 6 (Hs=1.6 m, Tpeak=14.3 sec, θpeak=65 deg). 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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67 

an evaluation of model output was performed using a comparison of computed gradients 

in sediment transport to historical shoreline change data. The basis for this comparison 

is the relationship between shoreline movement and the longshore gradient of sediment 

transport. Simply expressed, this relationship is 

t

x

y

Q

∂

∂

∝

∂

∂ (3.17) 

where Q is sediment transport, y is alongshore distance, x is the cross-shore position of 

the shoreline, and t is time. A comparison of results should illustrate similar trends in 

long-term shoreline change and transport potential computed using wave conditions that 

represent long-term average conditions. Good general agreement between these two 

quantities would suggest that the transport potential model reasonably represents longterm costal processes for a given area, and thus, the model’s ability to predict the likely 

impacts that would result from offshore dredging. 

 The time variation in shoreline position was determined from an analysis of 

historical shoreline data for each of the study areas. Regional change analysis provides 

a without-project assessment of shoreline response for comparison with predicted 

changes in wave-energy focusing at the shoreline resulting from potential offshore sand 

dredging activities. Because continuous measurements of historical shoreline change 

are available at 50-m alongshore intervals, model results (wave and sediment transport) 

at discreet intervals along the coast can be compared with historical data to develop 

process/response relationships for evaluating potential impacts. In this study, shoreline 

data covering the periods 1842 to 1977 for southern New Jersey (Byrnes et al., 2000); 

1859 to 1980 for Sandbridge, southeastern Virginia (completed as part of this study); 

1849 to 1980 for Dare County, North Carolina (Byrnes et al., 2001); and 1877 to 1996 for 

the shoreline south of Cape Canaveral, Florida (Byrnes and Kraus, 1999; Kraus et al., 

1999) was used to quantify trends. Methods used for compiling and analyzing historical 

data sets are described in Byrnes and Hiland (1994). Alongshore variations in sediment 

transport were determined using the computed values of transport potential for each 

shoreline for modeled existing conditions. Comparisons of shoreline change to the 

modeled transport gradient are shown in Figures 3-39 to 3-42. 

Southern New Jersey. For the modeled New Jersey shoreline shown in Figure 3-39, 

there is general agreement between shoreline change and transport gradient. Shoreline 

change data from Great Egg Harbor Inlet to Corsons Inlet show a trend from stable to 

erosional at the northeast side of Corsons Inlet. This trend is indicated in the transport 

gradient as well. From Corsons to Townsends Inlets, the shoreline change trend is from 

slightly erosional to slightly accretional, which is also the general trend documented in 

the gradient of transport potential. At the southwestern side of Townsends Inlet, a highly 

erosional area followed by an area of accretion is illustrated in shoreline change data 

and the modeled transport gradient. However, south of this area, agreement between 

modeled shoreline change trends and measured shoreline change do not appear to 

match well. Although the modeling predicts an area of significant accretion centered at 

approximately UTM Northing 4,325,000 meters, measurements indicate a stable 

shoreline in this region. Other than this one portion of the grid, which is not influenced 

by proposed borrow sites, agreement between the modeled gradient in transport 

potential and measured shoreline change is good. Even erosion and accretion trends 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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68 

are predicted well in the vicinity of tidal inlets, where tidal current processes often 

dominate nearshore sediment transport patterns. 

Southeastern Virginia. For the modeled shoreline of southeastern Virginia, the 

comparison of modeled transport gradient and measured shoreline change is shown in 

Figure 3-40. Shoreline change data and model results indicate a fairly stable shoreline 

between Rudee Inlet (north end of the plot) and Sandbridge (immediately landward of 

Borrow Sites A and B). South of Sandbridge, both analyses show a change to an 

erosional shoreline. Farther south from the maximum negative gradient in transport 

potential, the gradient changes to an accretional trend where shoreline change data 

indicate a change to a stable shoreline. Overall, the agreement between trends in 

longshore sediment transport potential gradient and observed shoreline change was 

good for the Virginia coast. This suggests that the 5-year offshore wave record used for 

calculating sediment transport potential represented long-term wave conditions 

responsible for regional shoreline change. 

North Carolina. Trends in shoreline change generally agree with modeled transport 

gradients for the North Carolina coast north of Oregon Inlet (Figure 3-41). Results of 

both analyses illustrate a stable to erosional shoreline, with an area of maximum erosion 

between 5 and 7 km north of Oregon Inlet. For the modeled transport gradient, there is 

an area of accretion approximately 3 km north of the point of maximum erosion that is 

not indicated in the shoreline change analysis. This may be due to al lack of detailed 

nearshore bathymetry data for a 2 km section of coastline at this location. Bathymetry 

data used for developing the model grid was digitized from a NOAA navigational chart 

and does no have a high level of detail as is available in the data used for adjacent 

sections of coast. In addition, severe erosion observed immediately north of Oregon 

Inlet may have created an erosion hot-spot that has propagated to the north as shoreline 

orientation changed over the past century. The gradient in sediment transport potential 

was not expected to simulate this process that likely occurs over a time period spanning 

several decades. Significant migration of Oregon Inlet also may be responsible for some 

of the differences between observed and modeled shoreline change trends, where the 

peak in erosion likely has migrated south with the inlet. Therefore, the peak erosion 

area determined from the gradient of modeled transport potential, based on 20 years of 

recent wave information, may be more representative of present conditions than the 

long-term shoreline change (based on more than 100 years of shoreline data). Overall, 

good agreement exists between observed shoreline change and longshore gradient in 

modeled transport potential. Minor differences between the two methods, especially in 

the region of maximum erosion, likely are due to long-term alterations (spanning several 

decades) in shoreline position and the historical migration of Oregon Inlet. 

Cape Canaveral. Model results and shoreline change data for the Cape Canaveral area 

are shown in Figure 3-42. Both analyses show that the shoreline is stable about 6 km 

south of Canaveral Inlet. In the shoreline change results, the trend from the Cape 

headland south to Port Canaveral is highly accretional to accretional. This trend is not 

duplicated in the modeled transport gradient, which shows an area of high accretion at 

the cusp of the Cape, followed by an area of significant erosion between the Cape and 

the Inlet. The model likely has difficulty in this area due to complex offshore bathymetric 

features associated with Canaveral Shoals and limitations related to wave modeling 

(wave diffraction presently not included in STWAVE). In addition, STWAVE propagates 

wave energy within a ±90 degree sector from the cross-shore axis of the grid, which is 

important in areas where the shoreline angle is steeply inclined from the axis of the grid 
69 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-39. Comparison of historical shoreline change and gradient of modeled transport potential (dQ/dy) for the southern New Jersey shoreline. Color bars indicate whether the shoreline is accretional, stable, or erosional. 

highly erosional stable to erosional stable stable to accretional 

Townsends 

Inlet 

Corsons Inlet 
70 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-40. Comparison of historical shoreline change and gradient of modeled transport potential (dQ/dy) for the southeastern Virginia shoreline. Color bars indicate whether the shoreline is accretional, stable, or erosional. 

highly erosional stable to erosional stable stable to accretional 

Dam Neck 

Sandbridge 
71 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-41. Comparison of historical shoreline change and gradient of modeled transport potential (dQ/dy) for the North Carolina shoreline. Color bars indicate whether the shoreline is accretional, stable, or erosional. 

highly erosional stable to erosional stable stable to accretional 

Oregon Inlet 
72 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-42. Comparison of historical shoreline change and gradient of modeled transport potential (dQ/dy) for the Cape Canaveral shoreline. Color bars indicate whether the shoreline is accretional, stable, or erosional. 

highly erosional stable to erosional stable stable to accretional 

Port Canaveral 

Cape Canaveral 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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73 

 (e.g., just south of the cusp of the Cape). Based on the curvature of the shoreline north 

of Port Canaveral, significant erosion is anticipated immediately south of the cusp of 

Cape Canaveral (as indicated by the modeled gradient of transport potential). However, 

shoreline change data indicate substantial accretion in this area. The primary reason for 

this accretion likely is due to the shoal serving as a sediment source for beaches to the 

south. This cross-shore transport mechanism is not considered in longshore sediment 

transport analyses. For shorelines where nearshore shoals exhibit significant diffraction 

and potentially serve as a sediment source to the beach system, modeled sediment 

transport potential cannot match observed trends in shoreline change. South of Port 

Canaveral, away from the influence of the Cape’s topographic and bathymetric features, 

the trends predicted by the sediment transport potential model match well with historical 

shoreline change. 

3.2.2.2 Modeled Transport and Dredging Impacts 

 To quantitatively assess impacts to coastal processes associated with sand 

mining, a new approach was developed that considers the spatial (longshore) and 

temporal variability of local wave climate. This methodology uses similar wave modeling 

results as those required for two previous analyses (Basco, 1999 and Byrnes, et al., 

1999); however, wave modeling is performed for the entire 20-year WIS record as well 

as five 4-year blocks of the WIS record. In this manner, temporal variations in wave 

climate are considered relative to average annual conditions. From these wave model 

runs, sediment transport potential curves are derived for average annual conditions 

(using the full 20-year WIS record) and each 4-year period (using five 4-year wave 

records parsed from the full record). Based on this information, the average and 

standard deviation in calculated longshore sediment transport potential is determined 

every 200 m along the shoreline. Results of each of the four investigated areas are 

shown in Figures 3-43 through 3-46. 

 The purpose of segmenting the wave time series into five 4-year segments was to 

reduce the number of wave model runs without sacrificing information and to compute a 

more conservative estimate of wave variability (smaller range) for determining the 

significance of predicted impacts. Because the evaluation of sediment transport 

potential was performed to indicate long-term trends and not seasonal variations, the 

minimum length of wave record needed is one complete year. By grouping the 20-year 

wave record into 4-year blocks rather than into individual years, a more conservative 

standard deviation (smaller range) about the mean transport rate was derived. By 

definition, the standard deviation of a normally distributed variable would be reduced if 

the number of variables were reduced by grouping the original data. 

 Assuming the temporal component of sediment transport potential is normally 

distributed, the suggested criterion for accepting or rejecting a potential borrow site is 

based on one standard deviation about the mean. If any portion of the sediment 

transport potential curve associated with a sand mining project exceeds one standard 

deviation of the natural temporal variability (which incorporates 2/3 of the variability) in 

sediment transport potential, the site would be rejected. Because the standard deviation 

of each 4-year period is more realistic for documenting long-term variability than using a 

1-year period, the methodology provides a useful indication of sediment transport 

variability relative to the natural system. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

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74 

 The methodology used to determine impact significance depended on a region’s 

site-specific wave characteristics by considering temporal (inter-annual) and spatial 

variability in wave conditions. For this reason, the statistical envelope defining the limits 

of acceptable borrow site impacts varies along a given shoreline. A shoreline that 

experiences a wide variety of wave conditions (in direction, peak period, and significant 

wave height) from year to year naturally experiences large variability in sediment 

transport rates; therefore, the level of acceptable borrow site impacts would be relatively 

high. Conversely, a shoreline that experiences a limited range of wave conditions 

cannot accept a high level of borrow site impacts. An offshore site that is dominated by 

swell conditions from a single narrow direction band would be a good example of this 

latter case. Because the natural variability in inter-annual shoreline migration changes 

along the coast, certain portions of the shoreline will be more tolerant of alterations to 

the wave climate and associated sediment transport patterns. The methodology used to 

evaluate borrow site impacts provides a reliable quantitative technique for developing 

acceptable site-specific limits associated with changes in sediment transport potential. 

Offshore Southern New Jersey. An illustration of sediment transport potential for 

existing and post-dredging conditions for the southern New Jersey coastline is plotted 

with the acceptable limits for post-dredging based on the dredging significance criterion 

(Figure 3-43). Typically, net transport potential values are around 300,000 m3

/yr to the 

south, with minimum values occurring in the vicinity of Townsends and Corsons Inlets. 

Post-dredging changes fall within the limits of the dredging significance criterion 

envelope, and therefore, the proposed excavation depths would be acceptable in terms 

of impact on transport patterns in the modeled area. For this section of modeled 

coastline, the significance criterion envelope is ±10 to 15% of the modeled annualized 

net transport potential, with values of about ±30% close to Great Egg Harbor Inlet, north 

of Corsons Inlet. Overall, the significance criterion envelope (representing plus or minus 

one standard deviation about the mean) for southern New Jersey was relatively narrow 

compared with the other three modeled areas. This results from the limited variability in 

inter-annual wave climate along this portion of the New Jersey coast. 

 Figure 3-43 includes the difference between existing and post-dredging conditions 

for all borrow sites (cumulative impacts). Generally, the greatest impact is indicated 

between Townsends and Corsons Inlets, with maximum changes in net transport 

potential of about -22,000 m3

/yr. In this case, negative transport changes mean that 

there has been an increase in southerly-directed transport. Based on the model results, 

nearly all of the borrow sites cause an increase in southerly-directed transport with the 

exception of regions immediately south of Townsends and Corsons Inlets. Because the 

magnitude of impacts north and south of Corsons Inlet appears to be significantly larger 

than the impacts south of Townsends Inlet, borrow sites A1 and M8 appear to have 

greatest influence on transport rates. The impact of offshore site A2 likely is distributed 

over a longer stretch of shoreline; however, the magnitude is reduced. 

Offshore Southeastern Virginia. The results from wave model runs encompassing 

Sandbridge Shoal are presented in Figure 3-44. Sediment transport potential is directed 

to the north, with a maximum value of around 300,000 m3

/yr. A nodal point exists in the 

model output near False Cape. The significance criterion envelope is typically ±20 to 

35% of the modeled annualized net transport potential, which is larger than that for the 

modeled New Jersey shoreline. This means that borrow sites in this area would be able 

to impact sediment transport by a greater percentage than in the New Jersey 

simulations, because the sediment transport potential is more variable than it is in New 
75 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-43. Plots of modeled net transport potential and post-dredging change in transport for borrow sites located offshore southern New Jersey. The middle plot shows the dredging significance criterion envelope (

±

σ), and the plot of the shoreline and bathymetry is 

given for reference. 

Corsons Inlet 

Townsends Inlet 
76 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-44. Plots of modeled net transport potential and post-dredging change in transport for borrow sites located offshore southeastern Virginia, the middle plot shows the dredging significance criterion envelope (

±

σ), and the plot of the shoreline and bathymetry is 

given for reference. 

Sandbridge 

False Cape 
77 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-45. Plots of modeled net transport potential and post-dredging change in transport for borrow sites located offshore North Carolina, north of Oregon Inlet. The middle plot shows the dredging significance criterion envelope (

±

σ), and the plot of the shoreline and 

bathymetry is given for reference. 
78 

Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098 Figure 3-46. Plots of modeled net transport potential and post-dredging change in transport for borrow sites located offshore Florida, near Cape Canaveral. The middle plot shows the dredging significance criterion envelope (

±

σ), and the plot of the shoreline and 

bathymetry is given for reference. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098

79 

Jersey. For the modeled borrow sites (see Table 3-7, with depths not to exceed 50 ft 

NGVD), change in sediment transport potential for post-dredging conditions falls within 

the limits of the dredging significance criterion. So again, these proposed excavation 

depths (and sediment volumes) would be acceptable. 

 The existing and post-dredging difference plot shows that the greatest impact from 

the two borrow sites is located in the vicinity of Sandbridge and Dam Neck 

(approximately 25,000 m3

/yr decrease in northerly directed transport), while 

approximately a 20 km segment of shoreline is affected in total. The shoreline region of 

borrow site impacts exists within the area of maximum inter-annual variability in 

sediment transport potential. In this area, the standard deviation of the sediment 

transport potential variability exceeds ±100,000 cubic meters per year. Based on the 

difference plot, it is not possible to discern the impacts associated with Sites A and B 

separately; however, the greatest influence of sand mining at both sites is to decrease 

northerly-directed littoral drift. Therefore, the region to the north of Dam Neck will have a 

reduced supply of sand and the region immediately landward of the borrow sites will 

experience in increase in shoreline stability as a result of the dredging. The magnitude 

of these anticipated alterations to the local sediment transport regime is within one 

standard deviation of the natural inter-annual variability. 

Offshore North Carolina. Figure 3-45 illustrates model output to estimate the impact of 

sites 3 East and 3 West offshore North Carolina. North of the inlet, simulated net 

potential transport is to the north at approximately 250,000 m3

/yr. Gross annualized 

north and south transport values are about 450,000 m3

/yr and 200,000 m3/yr, 

respectively. Closer to the inlet, net transport values are primarily to the south, with 

largest potential transport values around 600,000 m3

/yr and very little north-directed 

transport (approaching zero). The dredging significance criterion generally falls within 

±30 to 40% of the computed net transport values, suggesting that the transport climate is 

similar to, but slightly more variable than, the southeastern Virginia example. For the 

modeled sand excavation conditions (Table 3-7), post-dredging model results fall within 

the significance criterion envelope, so again the modeled dredging plan would be 

acceptable. 

 The plot that presents transport differences between existing to post-dredging 

conditions at the two modeled sites indicates that the maximum impact from sand 

dredging at both borrow sites is an approximate 20,000 m3

/yr increase in south directed 

transport. These borrow sites represent the smallest sand mining sites evaluated, with 3 

East containing approximately 1,400,000 m3 and 3 West containing approximately 

2,500,000 m3

. Although the borrow sites are relatively small, impacts associated with 

sand mining in this region are comparable in magnitude to the Dam Neck/Sandbridge 

Shoal sites described above. This impact magnitude likely is a result of the combined 

influence of the two borrow sites along a relatively short section of shoreline, where the 

longshore region of influence is approximately 10 km. A more complete discussion of 

combined impacts associated with borrow sites in close proximity to each other is 

presented in Section 4 (Cumulative Effects). 

 Because the region of impacts associated with the North Carolina borrow sites 

straddles a sediment transport nodal point, the influence of an increase in south-directed 

transport (between UTM northing 3,967,500 and 3,970,000 m) will reduce the supply of 

sediment north of this region and increase the amount of sediment leaving this region to 

the south. Therefore, simulated sand dredging at 3 East and 3 West may generate an 
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MMS Study 2001-098

80 

erosion hot spot. However, the magnitude of impacts to sediment transport patterns is 

anticipated to be small relative to natural inter-annual variability of the local littoral 

processes. 

Offshore Cape Canaveral. Due to the influence of Cape Canaveral and the series of 

migrating ridges and troughs on Canaveral Shoals, a direct relationship between the 

observed shoreline change and the longshore gradient in sediment transport potential 

could not be established. Therefore, the utility of comparing the changes in sediment 

transport potential associated with sand mining to the natural variability of sediment 

transport patterns may have limited applicability in the region north of Port Canaveral. 

This is most clearly illustrated by the change in transport rates at the northern limit of the 

model grid, where a decrease in south-directed transport of 80,000 m3

/yr is predicted. 

Because the STWAVE model used for analysis does not include the influence of wave 

diffraction, modeled transport rates in regions influenced by diffraction effects are 

suspect. For Brevard County, this region influenced by wave diffraction would be north 

of Canaveral Inlet. 

 Model output for the region south of Port Canaveral (Brevard County) illustrates 

that in the area of greatest impact from the borrow site, the significance envelope is 

approximately ±20% of the mean computed net transport potential (Figure 3-46). The 

maximum modeled change for post-dredging conditions at the borrow site is about a 

40,000 m3

/yr decrease in south directed transport, just south of Port Canaveral. The 

modeled sand excavation volume of 26 MCM is considerably greater than the estimated 

3.4 MCM for present beach nourishment requirements in Brevard County (USACE, 

1999). Though the modeled difference is within the transport significance envelope, the 

magnitude of impact resulting from cumulative dredging of the full volume at this site 

suggests further analysis should be required to ensure that no detrimental impacts would 

occur. 

 3.2.2.3 Dredging Impacts at East Coast Sites 

 To establish useful criteria for estimating impacts of sand mining on the nearshore 

littoral system, a comparison of sediment transport potential analysis and long-term 

shoreline change was performed at each of the four sand borrow sites. The analysis 

provided a quantitative method for determining whether longshore wave-induced 

transport was responsible for observed shoreline change and whether the long-term 

shoreline change trends were consistent with the shorter time-period (20-year) sediment 

transport potential analysis. In general, the comparison indicated that the longshore 

gradient in computed wave-induced sediment transport followed similar trends as 

observed long-term shoreline change for nearly all cases. Exceptions occurred at 

locations where STWAVE modeling was not applicable (areas where wave diffraction 

was important) or where wave-induced processes may not govern sediment transport (in 

the vicinity of tidal inlets). 

 For the southern New Jersey shoreline, erosion and accretion trends are predicted 

well at all locations, including in the vicinity of tidal inlets. Along the southeastern 

Virginia coast, model results predict similar trends as observed long-term shoreline 

change, where much of the coastline is stable or slightly erosional. The location of 

highest erosion rates is predicted accurately by the modeling analysis. Overall 

agreement between modeled trends and measured shoreline change also was achieved 

for the North Carolina coast north of Oregon Inlet. Discrepancies between predicted and 
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MMS Study 2001-098

81 

measured results likely are a result of the significant historical migration of Oregon Inlet. 

Therefore, the peak erosion area determined from the gradient of modeled transport 

potential, based on 20 years of recent wave information, may be more representative of 

present conditions than long-term shoreline change (based on more than 100 years of 

shoreline data). Along the Cape Canaveral coast, STWAVE modeling was not capable 

of evaluating changes in wave climate resulting from wave diffraction processes across 

Canaveral Shoals. In addition, these shoals likely serve as a sediment source to the 

beach in this region. For shorelines where nearshore shoals exhibit significant 

diffraction and potentially serve as a sediment source to the beach system, modeled 

sediment transport potential cannot match observed trends in shoreline change. South 

of Port Canaveral, away from the influence of the Cape’s topographic and bathymetric 

features, the trends predicted by the sediment transport potential model match well with 

historical shoreline change. 

 Because modeled longshore gradients in sediment transport potential generally 

matched the trends in observed shoreline change, wave and sediment transport 

modeling provided an appropriate basis for evaluating long-term impacts associated with 

offshore sand mining. The methodology utilized to determine impact significance 

depended on a region’s site-specific wave characteristics, where the method considered 

temporal (inter-annual) and spatial variability in wave conditions. Because the natural 

variability in inter-annual shoreline migration changes along the coast, certain portions of 

a given shoreline naturally will be more tolerant of alterations to the wave climate and 

associated sediment transport. The methodology used to evaluate borrow site impacts 

provided a reliable quantitative technique for developing acceptable site-specific limits 

associated with changes in sediment transport potential. 

 Based on site-specific analyses for each of the four sites, the impacts associated 

with dredging at all borrow sites were deemed acceptable. For the southern New Jersey 

coastline, the significance criterion envelope was typically ±10 to 15% of the modeled 

annualized net transport potential, with values of about ±30% close to Great Egg Harbor 

Inlet. Overall, the significance criterion envelope (representing plus or minus one 

standard deviation about the mean) for New Jersey was relatively narrow compared with 

the other three modeled areas. This results from limited variability in inter-annual wave 

climate along the southern New Jersey coast. 

 For southeastern Virginia and North Carolina coastal regions, the dredging 

significance criterion envelope generally falls within ±20 to 40% of the computed net 

transport values. For the modeled sand excavation conditions (Table 3-7), postdredging model results fall within the significance criterion envelope for both cases, so 

again the modeled dredging plan would be acceptable. Model output for the region 

south of Port Canaveral, Florida (Brevard County) illustrates that in the area of greatest 

impact from the borrow site, the significance envelope is approximately ±20% of the 

mean computed net transport potential. Again, the modeled impacts in this region 

associated with potential offshore dredging are well within the significance envelope. 

However, due to limitations with the wave modeling effort, further analyses would be 

required to accurately assess impacts caused by dredging for the shoreline north of Port 

Canaveral. 

 
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4.0 CUMULATIVE IMPACTS 

 The borrow site analyses described in Section 3 document potential impacts 

associated with large-scale dredging of various offshore borrow areas. As shown in 

Table 3-6, all borrow sites contain a substantial volume of sand, most in excess of 

5,000,000 m3

. Because typical beach nourishment projects require significantly less 

sand than exists within these borrow sites, it is likely that several dredging events will 

occur before the entire borrow site is excavated. The analysis in Section 3 assumes that 

the entire borrow site is excavated at one time; therefore, this analysis provides the 

cumulative impacts associated with potentially numerous dredging events at a single 

site. 

 To evaluate cumulative impacts associated with incremental dredging of a single 

site and/or the combined effects of dredging borrow sites in the same region, a 

cumulative assessment strategy was developed. For evaluating cumulative impacts of 

sand dredging at an offshore borrow site, two types of borrow site configurations were 

investigated. The first group of cumulative impacts involves the interaction of multiple 

sites in close proximity, such that they have overlapping areas of shoreline impact. The 

second grouping of cumulative impacts involves multiple dredging events at a single site. 

4.1 SITES IN CLOSE PROXIMITY 

 An investigation of cumulative impacts resulting from borrow sites in close 

proximity was performed to determine how potential wave impacts at individual sites 

may interact to produce additive effects along the coast. The assumption is that net 

changes in sediment transport patterns along a section of coast, where multiple borrow 

sites have an overlapping influence, can be evaluated by superimposing individual 

changes resulting from excavation at each borrow site, as if the other sites in the 

grouping did not exist. 

 To determine the validity of the stated assumption, two areas were studied, 1) 

Sandbridge Shoal, offshore southeastern Virginia, and 2) offshore North Carolina, in the 

vicinity of Oregon Inlet. At Sandbridge Shoal, the two borrow sites are oriented side-byside and parallel to the shoreline. An example of wave model output for these sites is 

given in Figure 4-1, which shows wave height changes between existing and postdredging conditions. It appears that the two sites have an overlapping influence on 

offshore wave heights. For offshore North Carolina, sites 3 East and 3 West are 

oriented front-to-back in a line perpendicular to the shoreline. Wave model output for 

this simulation illustrates how site 3 East has an area of influence which includes the 

perimeter of site 3 West (Figure 4-2). 

 Wave model runs were executed for the wave conditions presented in Section 3.2. 

However, each borrow site was modeled independently, so that each site’s own area of 

influence could be determined. Sediment transport potential computations also were 

performed. Figure 4-3 shows the results of model runs for Sandbridge Shoal. Transport 

potential difference for three modeled cases is shown for Sites A and B modeled 

individually and for these two sites modeled together. In addition, the sum of the 

differences computed for Sites A and B alone is included. In this case, the influence on 

sediment transport potential along the shoreline by these two sites individually is roughly 

of the same magnitude, which would be expected in a case where the borrow sites are 

positioned similar distances offshore and are similar in size. Differences resulting from 
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the two sites modeled together is similar to differences derived by adding the results of 

the two sites modeled independently (i.e., both methods correlate well). These results 

suggest that any possible interaction of sites positioned side-by-side is weak. 

 

 For sites 3 East and 3 West in North Carolina, Figure 4-4 shows transport potential 

difference computed for cases similar to the Sandbridge Shoal model runs. In this case, 

the eastern borrow site has much less influence on transport potential change than the 

western site, which is located closer to the shoreline. Similar to the southeastern 

Virginia example, the sum of transport potential difference, computed for model runs at 

each site modeled separately, correlates well with differences computed using model 

output from the two sites modeled together. Therefore, for sites positioned front-to-back 

and perpendicular to the shoreline, interaction between these sites also is limited. 

 

 The results from these two cases (Virginia and North Carolina) suggest that 

borrow sites located in close proximity illustrate additive impacts. Therefore, the 

influence of multiple sites on sediment transport along a coastline is a simple additive 

effect, rather than a more complicated non-linear effect or amplification. 

 Figure 4-1. Difference plot of wave heights for existing and post-dredging conditions at sites 

A and B for Sandbridge model wave case 3. 

Dam Neck 

Sandbridge 

Rudee Inlet 
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Figure 4-2. Difference plot of wave heights for existing and post-dredging conditions at sites 

3 East and 3 West for North Carolina model wave case 4. 

Figure 4-3. Plot of sediment transport potential difference between existing and postdredging model runs including Sites A and B (southeastern Virginia) modeled 

together (solid black line) and separately (solid blue and red lines). The sum of 

transport difference computed for the separate runs of A and B (dotted black line) 

is presented for comparison with the curve of A and B modeled together 

(coefficient of determination, r2

=0.970). 
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Figure 4-4. Plot of sediment transport potential difference between existing and postdredging model runs including sites 3 East and 3 West (North Carolina) modeled 

together (solid black line) and separately (solid blue and red lines). The sum of 

transport difference computed for the separate runs of 3 East and 3 West (dotted 

black line) is presented for comparison to the curve of 3 East and 3 West 

modeled together (coefficient of determination, r2

=0.990). 

4.2 MULTIPLE DREDGING EVENTS AT A SINGLE SITE 

 The second type of cumulative impact analysis evaluated the effect of multiple 

dredging events at a single site. As a borrow site is excavated to greater depths, the 

impact that it has on sediment transport along the shoreline will increase. Taken to 

extreme depths, the magnitude of impacts would be expected to reach some asymptotic 

value, but how these impacts vary through a range of reasonable depths was the 

emphasis of this study. In addition, the performance significance criterion established in 

Chapter 3 was tested to see what depths of excavation the criterion would be violated. 

Site M8, offshore southern New Jersey, was used in this analysis because the site is 

positioned close to shore and it has a relatively large perimeter. Therefore, deep 

excavations at this location would have pronounced (and therefore easily observable) 

effects on modeled sediment transport patterns at the shoreline. 
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 Model runs were made for several excavated depths at Site M8, including 2, 3, 5, 

7, and 9 m. The results of sediment transport potential calculations from these model 

runs are shown in Figure 4-5. This figure shows transport potential computed for Site 

M8 alone, without sites A1 and A2 included in the analysis. Included with the plot of 

transport difference is a shaded area that represents the envelope of maximum change 

allowed by the impact significance criterion. According to the significance criterion, 

excavation depths greater than 5 m would not be permitted, as the allowable limit 

criterion is exceeded along the shoreline south of Corsons Inlet. In this case, borrow site 

excavations greater than 5 m would be rejected no matter how small a section of 

shoreline that the significance criterion is exceeded. 

Figure 4-5. Plot of change in sediment transport potential computed for five excavated 

depths at site M8, offshore Corsons Inlet, New Jersey. The shaded area 

represents the envelope of maximum transport influence that is allowed by the 

impact significance criterion. 

 

 From the five model runs, change in transport potential is seen to vary linearly with 

depth of excavation. Figure 4-6 is a plot showing this relationship. The maximummodeled differences are plotted with a least squares fit of the data. The fit correlates 

very well with the model data. 

Corsons Inlet 
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Figure 4-6. Plot of excavation depth versus change in modeled sand transport potential. 

Dotted lines represent linear least squares fits of the model output (for black line 

r

2

=0.999, and for the red line r2=0.954). 
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5.0 CONCLUSIONS 

 A four-phase approach was implemented to assess the potential for negative 

impacts from alterations to the local wave climate and sediment transport regime 

associated with offshore sand mining. First, a detailed evaluation of three readilyavailable, project-tested spectral wave models was conducted to determine the most 

effective simulation routine for predicting potential wave impacts due to dredging at 

offshore borrow sites. Second, a standard method was developed to qualify the 

significance of changes associated with borrow site excavation to determine the 

influence of borrow site geometry on local wave refraction and sediment transport 

patterns. The method developed for this study is based on historical wave climate 

variability, as well as local wave climate changes directly attributable to borrow site 

excavation. The third phase of the project focused on wave spectra development, wave 

transformation modeling, and coastal sediment transport calculations. Wave 

transformation modeling and sediment transport potential calculations were performed 

for existing and post-dredging bathymetric conditions at four sites along the U.S. East 

Coast. In addition, a site-specific determination of acceptable limits of borrow site 

impacts relative to sediment transport potential was determined for each case. The 

fourth and most significant phase of the project addressed potential cumulative effects of 

sand dredging from offshore sand borrow sites. These analyses were designed to 

determine how potential wave impacts at individual sites may interact to produce 

additive physical environmental effects along the coast. 

5.1 WAVE MODEL ASSESSMENT 

 The primary quantitative technique used to evaluate nearshore processes is wave 

transformation modeling. Wave models have been developed to numerically solve the 

equations governing change in wave height and direction (through processes such as 

refraction, shoaling, and breaking). As better offshore wave data sets have been 

developed (both wave gauge and hindcast information), wave transformation models 

have become standard tools for evaluating the nearshore wave climate. The analysis 

techniques presented in this report involve spectral wave modeling, based primarily on 

wave hindcast information, combined with standard longshore sediment transport 

equations to evaluate impacts associated with offshore sand mining. 

 A comparison of numerical wave transformation models was performed to 

determine the most appropriate tool for assessing impacts associated with offshore 

borrow sites. The results of this analysis are shown in Appendix A. STWAVE, REF/DIF 

S, and SWAN were selected for this comparison because they all are spectral wave 

models and are easily accessible to the coastal engineering community. Spectral 

models can simulate real ocean wave conditions, where waves of varying frequency and 

direction propagate simultaneously through the same physical domain. These models 

can be described as either action density models, like STWAVE and SWAN, or as 

propagation models like REF/DIF S. Action density models use the distribution of 

energy in a spectrum to compute wave transformations, whereas propagation models 

propagate individual waves through the model domain, each with a different frequency 

and different initial direction. 

 Based on this model comparison and other factors, it is recommended that future 

MMS wave modeling projects use STWAVE. This recommendation is provided 

because: 
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• STWAVE is a fully spectral model with an efficient numerical scheme that 

requires a minimum of computing resources and which has acceptable 

accuracy when compared to physical model data. 

• The USACE is actively updating STWAVE for its own use, and further 

improvements to the model will be made (e.g., diffraction is currently being 

added). 

• STWAVE is able to compute mean wave angles, which is necessary input in 

sediment transport modeling, whereas currently available versions of 

REF/DIF S do not have a rigorous method for mean wave angle 

computations. 

• Though the basic model approach of SWAN is very similar to STWAVE, it 

has many additional features that are not included in STWAVE. However, 

these advanced capabilities will not be required in the wave modeling 

projects for the MMS. Otherwise SWAN offers no performance advantage 

over STWAVE. 

5.2 MANAGEMENT TOOL FOR ASSESSING IMPACT SIGNIFICANCE 

 To directly assess the impacts of offshore sand mining to coastal wave and 

sediment transport processes, an approach was developed that considers spatial 

(longshore) and temporal aspects of the local wave climate. This method uses a similar 

wave modeling effort as that applied by Basco (1999) and Byrnes et al. (1999); however, 

wave modeling is performed for the entire 20-year WIS record and five 4-year blocks of 

the WIS record. As such, temporal variations in wave climate are considered relative to 

average annual conditions. From these wave model runs, sediment transport potential 

curves are derived for average annual conditions (based on the full 20-year WIS record) 

and each 4-year period (based on the five 4-year wave records parsed from the full 

record). Based on this information, the average and standard deviation in calculated 

longshore sediment transport potential is determined every 200 m along the shoreline. 

 Assuming the temporal component of sediment transport potential is normally 

distributed, the suggested criterion for accepting or rejecting a potential borrow site is 

based on a range of one standard deviation about the mean. If any portion of the 

sediment transport potential curve associated with a sand mining project exceeds one 

standard deviation of the natural temporal variability (which incorporates 2/3 of the 

variability) in sediment transport potential, the site would be rejected. Although using 

the standard deviation of each 4-year period is more conservative than using a 1-year 

period, the methodology provides a useful indication of sediment transport variability 

relative to the natural system. 

 As a management tool for the MMS, this methodology provides several 

advantages over methods previously employed to assess the significance of borrow site 

impacts. The primary advantages include: 

• Observed long-term shoreline change is compared with computed longshore 

change in sediment transport potential. Close comparison between these two 

curves indicates that longshore sediment transport potential calculations are 

appropriate for assessing long-term natural change. Therefore, this methodology 

has a model-independent component (observed shoreline change) used to 

ground truth the model results. 
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• The method is directly related to sediment transport potential and associated 

shoreline change. Therefore, impacts associated with borrow site excavation 

can be directly related to their potential influence on observed coastal processes 

(annualized variability in shoreline position). 

• Site-specific temporal variability in wave climate and sediment transport potential 

is calculated as part of the methodology. For sites that show little natural 

variability in inter-annual wave climate, allowable coastal processes impacts 

associated with borrow site dredging similarly would be limited, and vice versa. 

In this manner, the inter-annual temporal component of the natural wave climate 

is a major component in the determination of impact significance. 

• Similar to methodologies incorporated in previous MMS studies, the longshore 

spatial distribution of borrow site impacts is considered. However, the allowable 

limit of longshore sediment transport variability is computed from the temporal 

component of the analysis. Therefore, the final results of this analysis provide a 

spatially-varying envelope of allowable impacts in addition to the modeled 

impacts directly associated with borrow site excavation. The methodology 

accounts for spatial and temporal variability in wave climate, as well as providing 

a defensible means of assessing significance of impacts relative to site-specific 

conditions. 

5.3 WAVE AND SEDIMENT TRANSPORT ANALYSIS 

 Spectral wave input for STWAVE model runs performed for each of the study 

areas was developed using WIS hindcast data for borrow sites offshore southern New 

Jersey, Dam Neck/Sandbridge Beach (Virginia), Dare County North Carolina, and Cape 

Canaveral (Florida). Alternatively, for the Sandbridge Shoal area offshore southeastern 

Virginia, a five-year spectral wave data record from an offshore buoy maintained by the 

National Data Buoy Center (NDBC) was used to develop model input spectra. The 

NDBC data were used over available WIS data for southeastern Virginia because the 

buoy record was adequately long and represented actual long-term wave conditions in 

the area. Along with input spectra, bathymetry grids were developed for existing and 

post-dredging scenarios. For each of the four modeled areas, two coarse grids were 

developed that have the same geographical coverage and differ only by modifications to 

bathymetry in the borrow area. The maximum cumulative dredged volumes and mean 

depths for the modeled borrow sites for each region are shown in Table 3-6. 

 Overall, post-dredging wave model output for the four study sites illustrates 

reduced wave heights landward of borrow sites and increased wave heights at the 

longshore limits of the borrow site. This effect is more pronounced for cases with larger 

wave heights and longer periods. As waves propagate across a borrow site (deeper 

water than the surrounding area), wave refraction bends waves away from the center of 

the borrow site and toward the shallower edges. The net effect is to create a shadow 

zone of reduced wave energy immediately landward of the borrow site and a zone of 

increased wave energy updrift and downdrift of the borrow site. The effect of this 

redirected wave energy is to alter nearshore wave patterns responsible for longshore 

sediment transport. 

 By developing average annual sediment transport potential curves from wave 

modeling results, the influence of borrow site excavation on nearshore sediment 

transport quantitatively can be quantified. Comparisons of average annual sediment 

transport potential were performed for existing and post-dredging conditions to indicate 
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the relative impact of dredging to longshore sediment transport processes. Sediment 

transport potential is a useful indicator of shoreline impacts caused by offshore borrow 

sites because the computations include the borrow site influence on wave height and 

direction. 

5.4 APPLICATION OF MANAGEMENT TOOL 

 To establish useful criteria for estimating impacts of sand mining on the nearshore 

littoral system, a comparison of sediment transport potential analysis and long-term 

shoreline change was performed at each of the four sand borrow sites. The analysis 

provided a quantitative method for determining whether longshore wave-induced 

transport was responsible for observed shoreline change and whether the long-term 

shoreline change trends were consistent with the shorter time-period (20-year) sediment 

transport potential analysis. In general, the comparison indicated that the longshore 

gradient in computed wave-induced sediment transport followed similar trends as 

observed long-term shoreline change for nearly all cases. Exceptions occurred at 

locations where STWAVE modeling was not applicable (areas where wave diffraction 

was important) or where wave-induced processes may not govern sediment transport (in 

the vicinity of tidal inlets). 

 For the southern New Jersey shoreline, erosion and accretion trends are predicted 

well at all locations, including in the vicinity of tidal inlets. Along the southeastern 

Virginia coast, model results predict similar trends as observed long-term shoreline 

change, where much of the coastline is stable or slightly erosional. The location of 

highest erosion rates is predicted accurately by the modeling analysis. Overall 

agreement between modeled trends and measured shoreline change also was achieved 

for the North Carolina coast north of Oregon Inlet. Discrepancies between predicted and 

measured results likely are a result of the significant historical migration of Oregon Inlet. 

Along the Cape Canaveral coast, STWAVE modeling was not capable of evaluating 

changes in wave climate resulting from wave diffraction processes across Canaveral 

Shoals. In addition, these shoals likely serve as a sediment source to the beach in this 

region. South of Port Canaveral, away from the influence of the Cape’s topographic and 

bathymetric features, the trends predicted by the sediment transport potential model 

match well with historical shoreline change. 

 Because modeled longshore gradients in sediment transport potential generally 

matched the trends in observed shoreline change, wave and sediment transport 

modeling provided an appropriate basis for evaluating long-term impacts associated with 

offshore sand mining. The methodology utilized to determine impact significance 

depended on a region’s site-specific wave characteristics, where the method considered 

temporal (inter-annual) and spatial variability in wave conditions. Because the natural 

variability in inter-annual shoreline migration changes along the coast, certain portions of 

a given shoreline naturally will be more tolerant of alterations to the wave climate and 

associated sediment transport. The methodology used to evaluate borrow site impacts 

provided a reliable quantitative technique for developing acceptable site-specific limits 

associated with changes in sediment transport potential. Based on site-specific 

analyses for each of the four sites, the impacts associated with dredging at all borrow 

sites were deemed acceptable. However, due to limitations with the wave modeling 

effort, further analyses would be required to accurately assess impacts caused by 

dredging for the shoreline north of Port Canaveral. 
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5.5 CUMULATIVE EFFECTS 

 To evaluate cumulative impacts associated with incremental dredging of a single 

site and/or the combined effects of dredging borrow sites in the same region, a 

cumulative assessment strategy was developed. For evaluating cumulative impacts of 

sand dredging at an offshore borrow site, two types of borrow site configurations were 

investigated. The first group of cumulative impacts involves the interaction of multiple 

sites in close proximity, such that they have overlapping areas of shoreline impact. The 

second grouping of cumulative impacts involves multiple dredging events at a single site. 

 For the analysis of borrow sites in close proximity to each other, two case studies 

were evaluated: 1) Sandbridge Shoal, offshore southeastern Virginia, and 2) offshore 

North Carolina, in the vicinity of Oregon Inlet. At Sandbridge Shoal, the two borrow sites 

are oriented side-by-side and parallel to the shoreline. For offshore North Carolina, sites 

3 East and 3 West are oriented front-to-back in a line perpendicular to the shoreline. To 

evaluate the influence of individual borrow sites relative to the combined influence of 

both borrow site excavations, wave model runs were performed for cases where each 

borrow site was excavated individually and both borrow sites were excavated in a single 

event. Annual sediment transport calculations were then performed for each wave 

modeling scenario. Superimposing the effects of individual borrow site excavations onto 

the sediment transport potential curve developed from the combined excavation model 

run was used as the basis for comparison. The results from these two cases (Virginia 

and North Carolina) suggest that borrow sites located in close proximity illustrate 

additive impacts. Therefore, the influence of multiple sites on sediment transport along a 

coastline is a simple additive effect, rather than a more complicated non-linear effect or 

amplification. 

 The second type of cumulative impact analysis evaluated the effect of multiple 

dredging events at a single site. As a borrow site is excavated to greater depths, the 

impact that it has on sediment transport along the shoreline will increase. Taken to 

extreme depths, the magnitude of impacts would be expected to reach some asymptotic 

value, but how these impacts vary through a range of reasonable depths was the 

emphasis of this study. In addition, the performance significance criterion established in 

Chapter 3 was tested to see what depths of excavation the criterion would be violated. 

Site M8, offshore southern New Jersey, was used in this analysis because the site is 

positioned close to shore and it has a relatively large perimeter. Therefore, deep 

excavations at this location would have pronounced (and therefore easily observable) 

effects on modeled sediment transport patterns at the shoreline. From the five model 

runs, change in transport potential varied linearly with depth of excavation. 
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6.0 REFERENCES 

Basco, D.R., 1999. A methodology and criteria to assess the impacts of sand volume 

removed in federal waters on the nearshore wave climate. Coastal Engineering 

Centre, Old Dominion University, Norfolk, VA. 

Battjes, J.A. and J.P. Janssen, 1978. Energy loss and set-up due to breaking of random 

waves. Proc. 23rd Int. Conf. Coastal Engineering, ASCE, pp. 569-587. 

Bretschneider, C.L., 1968. Significant waves and wave spectrum. Ocean Industry, pp. 

40-46. 

Byrnes, M.R. and M.W. Hiland, 1994. Compilation and analysis of shoreline and 

bathymetry data (Appendix B). In: N.C. Kraus, L.T. Gorman, and J. Pope (editors), 

Kings Bay Coastal and Estuarine Monitoring and Evaluation Program: Coastal 

Studies. Technical Report CERC-94-09, Coastal Engineering Research Center, 

Vicksburg, MS, p. B1-B90. 

Byrnes, M.R. and N.C. Kraus, 1999. Regional sediment transport patterns adjacent to 

Canaveral Harbor, Florida. In: N.C. Kraus and W.G. McDougal (editors), Coastal 

Sediments '99, American Society of Civil Engineers, New York, NY, pp. 750-760. 

Byrnes, M.R., R.M. Hammer, B.A. Vittor, J.S. Ramsey, D.B. Snyder, K.F. Bosma, J.D. 

Wood, T.D. Thibaut, and N.W. Phillips, 1999. Environmental Study of Identified 

Sand Resource Areas Offshore Alabama: Volume I: Main Text, Volume II: 

Appendices. U.S. Department of the Interior, Minerals Management Service, 

International Activities and Marine Minerals Division (INTERMAR), Herndon, VA. 

OCS Report MMS 99-0052, 326 pp. + 132 pp. appendices. 

Byrnes, M.R., R.M. Hammer, B.A. Vittor, J.S. Ramsey, D.B. Snyder, J.D. Wood, K.F. 

Bosma, T.D. Thibaut, N.W. Phillips, 2000. Environmental Survey of Potential 

Sand Resource Sites: Offshore New Jersey. U.S. Department of the Interior, 

Minerals Management Service, International Activities and Marine Minerals 

Division (INTERMAR), Herndon, VA. OCS Report MMS 2000-052, Volume I: Main 

Text 380 pp. + Volume II: Appendices 291 pp. 

Byrnes, M.R., R.M. Hammer, B.A. Vittor, J.S. Ramsey, D.B. Snyder, J.D. Wood, T.D. 

Thibaut, N.W. Phillips, 2001. Collection Of Environmental Data Within Sand 

Resource Areas Offshore North Carolina And The Implications Of Sand Removal 

For Coastal And Beach Restoration. U.S. Department of the Interior, Minerals 

Management Service, International Activities and Marine Minerals Division 

(INTERMAR), Herndon, VA. OCS Report MMS 2000-056, Volume I: Main Text + 

Volume II: Appendices. 

Dean, R.G., 1977. Equilibrium beach profiles: U.S. Atlantic and Gulf coasts. Dept of 

Civil Engineering, Ocean Engineering Rept. No. 12, Univ. of Delaware, Newark, 

DE. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098

94 

Goda, Y., 1985. Random Seas and Design of Maritime Structures. University of Tokyo 

Press, Tokyo, Japan. 

Hammer, R.M., B.J. Balcom, M.J. Cruickshank, and C.L. Morgan, 1993. Synthesis and 

Analysis of Existing Information Regarding Environmental Effects of Marine 

Mining. Final Report by Continental Shelf Associates, Inc. for the U.S. Department 

of the Interior, Minerals Management Service, Office of International Activities and 

Marine Minerals, Herndon, VA, OCS Study MMS 93-0006, 392 pp. 

Hoffman, C.W., 1998. Preliminary Assessment of Potential Sand Resource Areas 

Offshore of Nags Head, Kitty Hawk, and Kill Devil Hills, North Carolina. North 

Carolina Geological Survey, Raleigh, NC, 12 pp. 

Inman, D.L. and R. Dolan, 1989. The Outer Banks of North Carolina: Budget of 

sediment and inlet dynamics along a migrating barrier system. Journal of Coastal 

Research, 5(2): 193-237. 

Jensen, R.E., 1983. “Methodology for the calculation of a shallow-water wave climate.” 

WIS Report 8, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS. 

Kamphuis, J.W., 1990. Alongshore sediment transport rate. Proc. 22nd Coastal 

Engineering Conference, ASCE. 

Kimball, S.M. and J.K. Dame, 1989. Geotechnical Evaluation of Sand Resources on the 

Inner Shelf of Southern Virginia. Final Report to the City of Virginia Beach, Two 

Volumes. Virginia Institute of Marine Science, College of William and Mary, 

Gloucester Point, VA. 

Kimball, S.M., J.K. Dame, and C.H. Hobbs, 1991. Investigation of Isolated Sand Shoals 

on the Inner Shelf of Southern Virginia. Final Contract Report. Virginia Institute of 

Marine Science, College of William and Mary, Gloucester Point, VA, 73 pp. plus 

Appendices. 

Kraus, N.C., M.R. Byrnes, and A.L. Lindquist, 1999. Coastal processes assessment for 

Brevard County, Florida, with special reference to test plaintiffs. Technical Report 

CHL-99-6, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS. 

McKinney, T.G., W.L. Stubblefield, and D.J.P. Swift, 1974. Large-scale current 

lineations, central New Jersey shelf: Investigations by sidescan sonar. Marine 

Geology, 17: 79-102. 

Mitsuyasu, H. et al., 1975. Observation of the directional spectrum of ocean waves 

using a cloverleaf buoy. Journal of Physical Oceanography, 5(4), 750-760. 

National Ocean Service, 1998. Geophysical data system for hydrographic survey data. 

Version 4.0, National Ocean Service, Washington, DC. 

Rosati, J.D., and N.C. Kraus, 1991. Practical Considerations in Longshore Transport 

Calculations. CETN II-24, U.S. Army Engineer Waterways Experiment Station, 

Coastal and Hydraulics Laboratory, Vicksburg, MS, 6 pp. 
Numerical Modeling Evaluation Of The Cumulative Physical Effects Of Offshore Sand Dredging For Beach Nourishment 

MMS Study 2001-098

95 

Smith, J.M., D.T. Resio, and A.K. Zundel, 1999. STWAVE: Steady-state spectral wave 

model. Instruction Report CHL-99-March 1999, U.S. Army Engineer Waterways 

Experiment Station, Vicksburg, MS. 

Svendson, I.A., and I.G. Jonsson, 1976. Hydrodynamics of Coastal Regions. Technical 

University of Denmark, 285 pp. 

Swift, D.J.P., J.W. Kofoed, F.P. Salsbury, and P. Sears, 1972. Holocene evolution of the 

shelf surface, central and southern Atlantic shelf of North America. In: D.J.P. 

Swift, D.B Duane, and O.H. Pilkey (editors), Shelf Sediment Transport: Process 

and Pattern. Dowden Hutchinson, and Ross. Stroudsburg, PA, p. 499-575. 

USACE, 1984. Shore Protection Manual. U.S. Army Engineer Waterways Experiment 

Station, Coastal Engineering Research Center, Vicksburg MS. 

USACE, 1999. Final Environmental Assessment and Finding of No Significant Impact, 

Canaveral Shoals Borrow Area II. USACE-Jacksonville District, Jacksonville, FL, 

13 pp. 

Williams, S.J., 1987. Geological Framework and Sand Resources of Quaternary 

Deposits Offshore Virginia, Cape Henry to Virginia Beach. U.S. Geological Survey 

Open-File Report 87-667, 60 pp.