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Analysis of the processes creating erosional hot spots in beach nourishment projects

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Title:
Analysis of the processes creating erosional hot spots in beach nourishment projects
Series Title:
UFLCOEL-95030
Creator:
Bridges, Marshall Hayden, 1969-
University of Florida -- Coastal and Oceanographic Engineering Dept
Place of Publication:
Gainesville Fla
Publisher:
Coastal & Oceanographic Engineering Dept., University of Florida
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English
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xii, 135 p. : ill. ; 28 cm.

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Subjects / Keywords:
Beach erosion ( lcsh )
Beach nourishment ( lcsh )
Shore protection ( lcsh )
Coastal and Oceanographic Engineering thesis, M.S ( lcsh )
Dissertations, Academic -- Coastal and Oceanographic Engineering -- UF ( lcsh )
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bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (M.S.)--University of Florida, 1995.
Bibliography:
Includes bibliographical references (p. 133-135).
Statement of Responsibility:
by Marshall Hayden Bridges.

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University of Florida
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University of Florida
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
35915667 ( OCLC )

Full Text
UFL/COEL-95/030

ANALYSIS OF THE PROCESSES CREATING EROSIONAL HOT SPOTS IN BEACH NOURISHMENT PROJECTS by
Marshall Hayden Bridges Thesis

1995




ANALYSIS OF THE PROCESSES CREATING EROSIONAL HOT SPOTS IN
BEACH NOURISHMENT PROJECTS
By
MARSHALL HAYDEN BRIDGES

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
UNIVERSITY OF FLORIDA

1995




ACKNOWLEDGMENTS

I would like to express my appreciation to my advisor and supervisory committee chairman, Dr. Robert G. Dean, for his support during my tenure here at the University of Florida. I would also like to thank the members of my committee, Dr. Robert J. Thieke and Dr. Ashish J. Mehta, who have helped me through many research and class problems. I would also like to thank Coastal Planing and Engineering, Inc. for all of their assistance. Without their help, I would not have been able to complete this study.
My gratitude is also extended to the staffs of the Coastal and Oceanographic Engineering Department and the Coastal and Oceanographic Engineering Laboratory with special acknowledgment going to Becky Hudson and "J.J." Joiner.
My friends deserve a great deal of credit for helping me with my research and class endeavors. Wira Tarigan, Krassimir Doynov, Mike Krecic, "Wally" Li, Jie Zheng, Mike Bootcheck, Paul Devine, Mark Sutherland, Justin Davis, Bill Miller, Renjie Chen, Chris Jette, Gus Kreuzkamp, and Wayne Walker all deserve more thanks for than I have room to express here.
Most importantly, I wish to express to my never-ending gratitude to my parents. Their support and appreciation of the choices I have made in my life are without equal. Lastly, thanks goes out to my lifelong friends, Doug Ewell, Greg Moore, and Kent Thomas, who really do not need to be thanked.
A special acknowledgment should be given the anonymous person who owns the vending machines in Weil Hall. He or she managed to keep the frustration of my research in perspective by taking a few extra cents from me every time I used the machine.




TABLE OF CONTENTS
ACKNOWLEDGMENTS .................................................................................................. ii
L IST O F T A B L E S ............................................................................................................ vii
LIST OF FIGURES .................................................................................................. viiii
CHAPTER 1: INTRODUCTION ........................................................................................ 1
1.1 Importance of Understanding Nourishment Behavior on a Local Scale ........... 2
1.2 Importance and Explanation of Hot Spots ....................................................... 3
CHAPTER 2: BACKGROUND AND REVIEW: POSSIBLE EXPLANATIONS OF HOT SPOTS ............................................................................................................... 5
2.1 Introduction ..................................................................................................... . 5
2.2 Dredge Selectivity ............................................................................................. 5
2.2 Residual Structure-Induced Slope .................................................................... 14
2.3 Borrow Pit Location ......................................................................................... 17
2.4 Breaks in Bars .................................................................................................. 22
2.5 Mechanically Placed Fill .................................................................................. 25
2.6 Profile Lowering Adjacent to Seawalls .......................................................... 28
2.7 H eadlands ....................................................................................................... . 32
2.8 Residual Bathymetry ....................................................................................... 33
CHAPTER 3: PHYSICAL MODELING OF RESIDUAL BATHYMETRY .............. 38
3.1 Equipment Description .................................................................................... 38
3.2 T rial R uns ....................................................................................................... . 40
3.3 Experimental Runs ........................................................................................... 42
3.4 Comparison of Physical Model Results Versus Theory ................................... 50
3.5 Sum m ary ....................................................................................................... . 5 1
CHAPTER 4: NUMERICAL MODELING OF RESIDUAL BATHYMETRY ...... 53
4.1 Introduction ................................................................................................... . 53
4.2 Numerical Model Results: the Effect of Perturbation Depths on Shoreline Change ........ ,,oo.o,,,o,,,o,,,,,,o,,o.o,,oo,,o,, ............................................... 57
4.3 Numerical Model Results: the Sensitivity of Shoreline Change to Perturbation
S ize .............................................................................................................................. 6 3
4.4 Numerical Model Results: Sensitivity of Shoreline Change to A-Factor ........ 64




4.5 Numerical Model Results: Sensitivity of Shoreline Change to Berm Height...66 4.6 Numerical Model Results: Sensitivity of Shoreline Change to Wave Direction .66 4.7 Numerical Simulation of the Physical Model ....................................... 68
4.8 Summary and Conclusions............................................................ 69
CHAPTER 5: CASE STUDY SUMMARIES OF EROSIONAL HOT SPOTS.......... 70
5.1 Captiva Island, Florida ................................................................ 70
5.2 Longboat Key, Florida ................................................................ 76
5.3 Grand Isle, Louisiana.................................................................. 81
5.4 Delray Beach, Florida.................................................................8 3
5.5 Fire Island, New York................................................................. 84
5.6 Hilton Head Island, South Carolina.................................................. 85
5.7 Bald Head Island, North Carolina .................................................... 88
CHAPTER 6: POTENTIAL REMEDIAL MEASURES.................................... 92
6.1 Introduction ............................................................................ 92
6.2 Remedial Measures to Prevent Hot Spots Caused by Dredge Selectivity........ 93
6.3 Remedial Measures to Prevent Hot Spots Resulting from Residual Structure
Induced Slope .............................................................................. 94
6.4 Remedial Measures to Prevent Hot Spots Resulting from Borrow Pits........... 94
6.5 Remedial Measures to Prevent Hot Spots Resulting from Bar Breaks ........... 95
6.6 Remedial Measures to Prevent Hot Spots Resulting from Mechanically Placed
Fill ........................................................................................ 95
6.7 Remedial Measures to Prevent Hot Spots Resulting from Profile Lowering...96 6.8 Remedial Measures to Prevent Hot Spots Associated with "Headlands"......... 97 6.9 Remedial Measures to Prevent Hot Spots Created from Residual Bathymetry .... .98 6. 10 Conclusions........................................................................... 98
CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS FOR FURTHER STUDY...................................................................................... 100
7.1 Summary and Conclusions .......................................................... 100
7.2 Reco mmendations for Further Study ............................................... 101
APPENDIX A: FORTRAN PROGRAMS USED IN NUMERICAL MODEL ANALYSIS OF RESIDUAL BATHYMETRY ............................................ 103
A. 1 SIN.FOR Listing .................................................................... 103
A.l1 PARA.FOR Listing.................................................................. 110
A.3 SMALL.FOR Listing................................................................ 116
APPENDIX B: OUTPUT FROM FORTRAN PROGRAMS USED IN NUMERICAL MODEL ANALYSIS OF RESIDUAL BATHYMETRY.................................. 124
B.lI SIN.FOR Simulations with Varying Depth........................................ 125
B.2 SIN.FOR Simulations with Various Displacements .............................. 126
B.3 STN.FOR Simulations with Various A-Factors.................................... 126
B.4 SIN.FOR Simulations with Various Berm Heights ............................... 127




B.5 SIN.FOR Simulations with Non-Normally Incident Waves .............................128
B.6 PARA.FOR Simulations for Various Depths of Limiting Motion and Outer Fill
.......................... ....................................................................................... ...... .......... 12 8
B.7 PARA.FOR Results From Simulations of Various Displacements...................129
B.8 PARA.FOR Results for Various A-Factors.......................................................130
B.9 SMALL.FOR Simulations of the Physical Model ............................................132
R E FE R EN C E S ............................................................................................................... 133
BIO G RA PH ICA L SK ETCH ..........................................................................................136




LIST OF TABLES

Table E=g
2- 1: Effect Of Varying Sand Size On Equilibrium Dry Beach Width..................... 10
2- 2: Effect of Varying Added Volume on Equilibrium Dry Beach Width................ 26
2- 3: Effect of Profile Lowering on Equilibrium Dry Beach Gain........................ 31
3-1: List Of Different Parameters Used In The Trial Runs .................................. 42
3- 2: Run 1 Sept. 7, 1995 ..................................................................... 43
3- 3: Run 2 Sept. 8, 1995.................................................................... 44
3- 4: Run 3 -Sept. 9, 1995 ..................................................................... 44
3- 5: Run 4 -Sept.29, 1995..................................................................... 44
3- 6: Comparison of Theoretical Results and Experimental Results....................... 51
4- 1: Numerical Results (from SIN.FOR) and Theoretical Predictions of Maximum Shoreline Changes for Different Perturbation Depths ....................................... 60
4- 2: Numerical Results (from PARA.FOR) and Theoretical Predictions of Maximum Shoreline Change for Different Perturbation Depths......................................... 61
4- 3: Numerical Results (from SIN.FOR) and Theoretical Predictions of Maximum Shoreline Change for Different Perturbation Sizes........................................... 63
4- 4: Numerical Results (from PARA.FOR) and Theoretical Predictions of Maximum Shoreline Change for Different Perturbation Sizes........................................... 64
4- 5: Comparison of SIN.FOR Numerical Results and Theoretical Predictions for Different A-Factors ............................................................................. 65
4- 6: Comparison of PARA.FOR Numerical Results and Theoretical Predictions for Different A-Factors ............................................................................. 65




4- 7: Comparison of Numerical and Theoretical Results for Different Berm Heights ...... 66 4- 8: Numerical Simulations of the Physical M odel .......................................................... 68
5 1: Post Construction Median and Mean Sand Sizes of the Captiva Island Project ...... 74 5 2: Comparison of the Cumulative Distribution of the Average Grain Size Found in the Hot Spot and Non-Hot Spot Sections of Longboat Key .................................................... 78
5 3: Comparison of Hot Spot and Non-Hot Spot A-Factors on Longboat Key ............... 79




LIST OF FIGURES

Figure P=
2- 1: Sand Size Sorting on an Ebb Shoal ............................................................................. 7
2- 2: M odified Shields C urve ............................................................................................... 8
2- 3: Effect Of Varying Sand Size On Added Equilibrium Dry Beach Width .................. 10
2- 4: Comparison of Beach Profiles for Different Mean Grain Sizes ................................ 11
2- 5: Comparison of Pre-construction, Post Construction, and Equilibrium Post Construction Beach Profiles. Fill Has a Mean Diameter of 0.35mm .............................. 11
2- 6: Comparison of Pre-construction, Post Construction, and Equilibrium Post Construction Beach Profiles. Fill Has a Mean Diameter of 0.25min .............................. 12
2- 7: Plan View of a Hot Spot Created from Dredge Selectivity ....................................... 13
2- 8: Effect of Shore Perpendicular Structures on Beach Slope ........................................ 15
2- 9: Effect of Shore Perpendicular Structures on Beach Slope (Side View) .................... 16
2- 10: Effect of Wave Refraction behind a Borrow Pit ...................................................... 19
2- 11: Effect of Set-Up Generated Currents on the Area Behind a Borrow Pit ................. 20
2- 12: Isolines of Approximate Diffraction Coefficients for Normal Wave Incidence and a Breakw ater G ap of 2.5 W avelengths ................................................................................. 24
2- 13: Extra Fill Resulting when Hydraulically Placed Fill Is Unable to Meet the C onstruction Tem plate Slope ............................................................................................. 25
2- 14: Plan View of a Hot Spot Created by Mechanically Placed Fill ............................... 27
2- 15: Profile Lowering in Front of a Seawall ................................................................... 28




2- 16: Evolution of an Eroding Profile in Front of a Seawall ....................................... 29
2- 17: Additional Volume Required by a Profile with a Seawall ................................. 30
2- 18: Hot Spot Created due to the Headland Effect ..................................................... 33
2- 19: Creation of Irregular Bathymetry by Nourishment Placement .......................... 35
2- 20: Creation of Irregular Bathymetry by Placement of Inlet Dredge Spoil .............. 36
3- 1: W ave B asin Schem atic ......................................................................................... 39
3- 2: Side V iew of M odel Beach .................................................................................. 40
3- 3: Trial Run 5, Initial Bathym etry .......................................................................... 41
3- 4: Trial Run 5, Post-Run Bathym etry ...................................................................... 41
3- 5: Residual Bathymetry Model, Run 1 Sept. 7, 1995 (with perturbation) ............. 45
3- 6: Residual Bathymetry Model, Run 2 Sept. 8, 1995 (with perturbation) ............. 45
3- 7: Residual Bathymetry Model, Run 3 Sept. 9, 1995 (with perturbation) ............. 46
3- 8: Residual Bathymetry Model, Run 4 Sept. 29, 1995 (with perturbation) ........... 46
3- 9: Residual Bathymetry Model, Run 1 Sept. 7, 1995 ............................................ 47
3- 10: Residual Bathymetry Model, Run 2 Sept. 8, 1995 ......................................... 47
3- 11: Residual Bathymetry Model, Run 3 Sept. 9, 1995 ......................................... 48
3- 12: Residual Bathymetry Model, Run 4 Sept. 29, 1995 ......................................... 48
3- 13: Residual Bathymetry Model, Run 4 Sept. 29, 1995 (multiple contours) ...... 49 3- 14: Sept. 29, 1995 Run, Initial Bathymetry ............................................................. 49
3- 15: Sept. 29 Run, Post-Run Bathymetry ................................................................. 50
4- 1: Bathym etric Pattern in SIN .FOR ......................................................................... 55
4- 2: Bathymetric Pattern in PARA.FOR ..................................................................... 57




4- 3: Equilibrium Shoreline Resulting from a Cosine Shaped Perturbation Existing between Depths of 2.3 and 3.8 meters (7.5 and 12.5 feet) ................................... 59
4- 4: Equilibrium Shoreline Position Resulting from Parabola Shaped Bathymetry Existing between Depths of 3.1 and 5.5 meters (10 and 18 ft.).............................. 62
4- 5: Equilibrium Shoreline Position Resulting from Cosine Shaped Bathymetry and 85 Degree Incident Waves......................................................................... 67
5 1: Headland Creation at the Captiva Island Road Hot Spot ............................. 72
5 2: Shoreline Perturbation Occurring at the Captiva Island Road Hot Spot (actual planform) ...................................................................................... 73
5 3: Post Nourishment Captiva Island Sand Size ........................................... 75
5 4: Longboat Key Vicinity Map............................................................. 76
5 5: Cumulative Sand Size Distribution for the Hot Spot and Non-Hot Spot Sections of Longboat Key .................................................................................. 78
5 6: Hot-Spot-Cold-Spot Pattern at Grand Isle, December 1986......................... 82
5 7: Fire Island Bar Break..................................................................... 85
5 8: Vicinity Map of Bald Head Island ...................................................... 89
5 9: Shoreline Evolution of Bald Head Island .............................................. 91




Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science ANALYSIS OF THE PROCESSES CREATING EROSIONAL HOT SPOTS IN BEACH NOURISHMENT PROJECTS
By
Marshall Hayden Bridges
December 1995
Chairman: Dr. Robert G. Dean
Major Department: Coastal and Oceanographic Engineering
This study presents a qualitative analysis of the causative properties of erosional hot spots. Erosional hot spots are areas whose shorelines perform dramatically worse than expectations or adjacent shorelines. Atypical behavior is a main characteristic of erosional hot spots. For example, the scour created downdrift of a jetty is not a hot spot because scour is expected to occur downdrift of a jetty. The scour is typical of the behavior associated from such an installation. However, if the downdrift shoreline retreat is too great to be attributed to normal jetty behavior, an erosional hot spot may be present. Hot spots can be either natural or man-made, but the study emphasizes man-made hot spots associated with nourishment projects.
Previous studies which investigated the causes of a particular hot spot were combined into a general overview of the phenomenon. Eight processes were identified as having the potential to create erosional hot spots. The eight processes are dredge selectivity, residual structure-induced slope, borrow pits, bar breaks, mechanically placed fill, profile lowering adjacent to seawalls, headlands, and residual bathymetry. Only




residual bathymetry was developed from theory while the others are based on field observations and speculation.
To further investigate the processes associated with residual bathymetry, a numerical and a physical model were developed. Both models qualitatively confirmed the residual bathymetry theory introduced by Dean and Yoo in 1993. The numerical model employed investigated the sensitivity of shoreline change caused by residual bathymetry to various parameters.
To illustrate how each process manifests itself in nature, seven case study summaries were presented: Captiva Island (Florida), Longboat Key (Florida), Grand Isle (Louisiana), Delray Beach (Florida), Fire Island (New York), Hilton Head Island (South Carolina), and Bald Head Island (North Carolina).
The study includes speculation on how to prevent each type of hot spot. In addition, a demonstration of how some of the causative hot spot processes might be manipulated to protect the shoreline is presented. Directions for future research are suggested in conclusion.




CHAPTER 1
INTRODUCTION
Shoreline retreat is one of the most serious problems facing the world's coastlines. According to a 1995 NOAA survey, beach visitors cite beach erosion as their greatest coastal concern (USA Today, 1995). Visitors are not the only group who should be worried about the problem. With over a third of the U.S. population living in coastal counties, 4.2 billion dollars spent in coastal-zone use during the mid-i 980s, and 40% of U.S. manufacturing taking place on the coast, everyone should be concerned about beach erosion (Ross, 1988). Beach erosion side effects such as lessened storm protection and loss of recreation could have dramatic impacts on the economy and environment.
Coastal engineers employ a variety of methods to fight beach erosion. Presently, these methods can be divided into three groups: hard approaches, alternative technologies, and soft approaches. Hard approaches employ structures to accrete sand or halt erosion. However, there are many negative externalities associated with their implementation. For a structure to cause accretion, it usually must cause erosion somewhere else. In addition, structures usually decrease the aesthetics of the shoreline. For these reasons, hard approaches are presently an unpopular method to fight beach erosion. Alternative technologies include a wide array of engineering solutions such as beach dewatering. Because these technologies are relatively untested and expensive to implement, they are seldom used. In addition, those tested have not been clearly successful. Soft approaches involve processes such as beach nourishment in which sand from outside the nearshore system is placed on the beach to augment its width. Although beach nourishment is expensive, it is often the solution that provides the most benefit




2
with the least negative externalities. However, the processes controlling the behavior of beach nourishment are complicated. Research has achieved a reasonable understanding on the behavior of beach nourishments on a project sized scale. The understanding of the areas on a local scale is still developing.
1. 1 Importance of Understanding Nourishment Behavior on a Local Scale
Coastal engineers have many tools at their disposal to predict the longevity of beach nourishments on a project scale. The Pelnard-Considere equation provides an analytic method to account for "spreading out" losses. Computer programs such as DNRBS (Dean and Grant, 1989) and Genesis (Hanson and Kraus 1989) utilize many parameters to provide an accurate estimate of shoreline response and the amount of fill which will remain in a project area after a given length of time. Numerical models which use local profile inputs such as SBEACH (Larson and Kraus, 1987) and EDUNE (Kriebel and Dean, 1985) can predict the response of individual profiles. However, these models will often be inaccurate when only one profile is examined. They perform much better when many profiles are examined to yield an average response. These models can accurately predict the average behavior of the entire project. Although these tools and others like them describe nourishment behavior with reasonable accuracy on a project sized scale, they are unable to accurately describe how a project will behave locally within the project. DNRBS might give an accurate solution to the amount of fill remaining in a project while grossly over or under estimating the fill remaining at one point in that project. This inability to predict project behavior on a local scale causes many problems such as negative public image and insufficient storm protection.
The inability of coastal engineers to predict the performance of beach nourishments on a local basis has contributed to the negative image some projects have developed. The public is not concerned with the percentage of fill remaining. They expect a uniform increase in beach width. If a project does not provide the "advertised" increase in beach




width at a highly visible area, that project is often viewed as a failure even if it performs exceptionally at other areas. If the local variability can be predicted and included in the design, the reputation of nourishment projects should improve.
One of the objectives in nourishing a beach is to provide storm protection for the nearshore area. A beach's berm and dunes are designed to be high enough to prevent storm flooding. The dune and berm height are characteristics which can be reasonably predicted on a project size scale but not on a local scale. If an area of the project behaves in such a manner that its berm and dune height are significantly lower than planned, the development in that area could be destroyed by a storm. The average berm and dune height does not provide local storm protection. Only the berm and dune height at each local point in the project can perform that task. Therefore, the ability to predict nourishment performance locally is of great importance to storm protection design, which is a major reason nourishment projects are constructed.
1.2 Importance and Explanation of Hot Spots
When an area within a project performs poorly compared to expectations or neighboring areas, it is often called an erosional "hot spot." To be termed a hot spot the shoreline must behave atypically. For example, dune removal would not create a hot spot because the removal of sand from the littoral system has foreseeable detrimental effects. However, the shoreline which experienced dune removal could be termed a hot spot if its retreat exceeded the distance that could be attributed to dune removal. In a similar manner downdraft scour resulting from a jetty could not be called an erosional hot spot because scour is expected to occur downdraft of jetty installations. Although hot spots can occur on any shoreline, hot spots occurring on beach nourishment projects are emphasized here due to their visibility and resultant damage.
The presence of hot spots and their antithesis, cold spots (areas which perform much better than expected or adjacent areas), cause many of the problems associated with local




scale predictability. If the causes creating hot spots can be understood, the coastal engineer can design remedies to eliminate or control them. The elimination or control of hot spots will remove much of the variability occurring in local scale predictability.
Hot spots can be natural or man-made. Natural hot spots are a result of the normal littoral system altering the nearshore transport system. The shoreline has a distinct equilibrium position for a given bathymetry. When the bathymetry is altered, the shoreline will change. If the change is large enough, it may be termed a hot or cold spot. Natural hot or cold spots are merely shoreline changes which result from natural system alterations. Given the dynamic nature of the littoral system, natural hot or cold spots should occur quite frequently without any man-made assistance. Natural hot or cold spots may even occur on a nourishment project through no fault of the designer. However, some hot spots are man-made. Structures, borrow pits, and uneven fill placement are just some of the man-made causes of hot spots. Man-made hot spots should be easier to interpret and eliminate than natural ones. To eliminate man-made hot spots, only the changes that caused the hot spot must be altered. For natural hot spots to be controlled, the natural system must be altered, which is much more complicated. Therefore, the best way to begin improving local scale predictability is to understand man-made hot spots.
The following study investigates the causes of erosional hot spots, placing particular emphasis on man-made hot spots occurring in beach nourishment projects. The study attempts to uncover the processes creating the atypical behavior associated with hot spots. These processes are explained with theory and illustrated by use of case study summaries. In addition, numerical and physical models are employed to investigate one particular process creating an erosional hot spot.




CHAPTER 2
BACKGROUND AND REVIEW: POSSIBLE EXPLANATIONS OF HOT SPOTS
The analysis of hot spots has usually occurred on a case-by-case basis. When hot spots developed, various parties tried to explain them individually. As a result, many explanations exist for hot spots. Presently, at least eight different theories exist to explain their cause. These eight are by no means an inclusive list. Certainly, there are more causes or potential causes for erosional hot spots. However, presently, these eight have been the focus of most of the research. The eight causes are dredge selectivity, residual structure-induced slope, borrow pits, bar breaks, mechanically placed fill, profile lowering adjacent to seawalls, headlands, and residual bathymetry. Each of these is discussed below.
2.2 Dredgze Selectivity
In the preliminary stages of nourishment design, a sand search is conducted. The sand search attempts to locate the best available sand source for the project. Vibracores are taken to determine the mean diameter of the sand at each site as well as the thickness of the sand deposit. Since sand size is one of the key parameters in the design, great detail is taken in the collection of the data. The data are extensive and accurate. A borrow site is chosen based on the sand information as well as environmental effects, dredging costs, effects on wave refraction, etc. Once the project is funded and permitted, a dredge company is hired to carry out the nourishment. The contract with the dredge company specifies a borrow area. The dredge is free to mine any sand in this defined




area with the flexibility to select particular areas of the borrow site for each fill section of the project.
Dredges are costly to operate. A small percentage savings in fuel costs can result in a large decrease in operating expense. Coarser sand takes more energy to transport than fine sand and, therefore, uses more fuel. It seems logical that the dredge companies would choose the fine sand to transport long distances. The sand search data provides dredge companies an excellent view of the sand size distribution over the borrow site. They would definitely have the capability to locate the fine sand within the borrow site. Because of this, the project reaches that are the greatest distance from the borrow site could receive fine sand. In order for this process, termed dredge selectivity, to create a hot spot, significant variation in sand size must exist at the borrow site. The sand size variability will result in a dry beach width variation given that the volume placed per unit length is fairly uniforrn over the project.
Ebb shoals are a common borrow source for nourishment projects. Ebb shoals show significant variation in sand size distribution. A simple fall velocity argument can show the cause of this variation. Suspended sediment exiting the inlet on the ebb tidal current begins to drop out of suspension. The larger sediment has a higher fall velocity and will be deposited close r to the inlet. At the same time the smaller sand particles will have a lower fall velocity and will drop out of suspension farther from the inlet. Fall velocity sorts the ebb shoal's sand according to size, allowing significant variation. Figure 2-1 illustrates the sorting process.
For the example in Figure 2-1, the sand grains were assumed to be suspended in 4m of water which was moving at an average velocity of 1. 5 m/s. The 0. 3 mm and 0. 1 mm sand grain will have a fall velocities of 0.04 m/s and 0.008 m/s, respectively. This means that the 0.3 mm grain will have 100 seconds before reaching the bed while the 0.1 mm grain takes 500 seconds to reach the bottom. During this time the 1.5 m/s current takes the 0.3mm grain 150 m and the 0. 1 mm grain 750 m, respectively. In reality, there are




Z-INLET THROAT (i.e. jetty)

WATER LEVI

0.3 mm diameter suspended sand grain
/-0. 1 mm diameter suspended sand grain

I * * if * U * * * ~ p

p
p

150OM

300 M

450 M

600 M

750 M

FIGURE 2- 1: Sand Size Sorting on an Ebb Shoal
many different sized grains at different levels, but the general trend of coarser grains being found closer to the inlet will remain. From this simple fall velocity demonstration, it is easy to see that significant variation in sand size may exist on an ebb shoal. In fact, the shoal may be sorted by fall velocity.
A bed load argument can also be used to show the variation. Figure 2-2 shows a modified Shields Diagram (Madsen and Grant, 1976). The Shields' parameter, TI, can be calculated from Equation (2-1) while the formula for the diagram's sediment/fluid parameter is found in Equation (2-2).

T0.1 25p f'
(s-i1) p gd

(2-1)

where p is the water density, f is the Darcy-Weisbach friction coefficient, U is the bottom velocity, s is the specific gravity of the sediment, g is the gravitational acceleration, and d is the diameter of the sediment grain.




8
S* =- d (s-l)gd (2-2)
4v
where d is the sediment diameter, s is the specific gravity, g is the gravitational acceleration, andv is the kinematic viscosity.

5
2
E
010
E 5
2
-c2

10' 2 5
4z (;-I)gd

FIGURE 2- 2: Modified Shields Curve
Source: Madsen and Grant (1976)
If the intersection of these two values is above the Shield's curve, the grain is transported away. Values below the Shield's curve result in no grain movement. The equations show the importance of sand diameter. For example, a 0.075 m/s bottom velocity results in T values of 2.6 and 4.6 x 10.5 for 0.1 mm and 0.5 mm grains,




respectively. The 0.5 mm T is below the Shield's curve for every value of the modified Reynolds number while the 0.1 mm. T value is above the Shield's curve for each Reynolds number value. As a result, the smaller grain is transported down current until the current slows to a pace which the grain can withstand. This process results in sand size sorting. The larger grains will be located at the inlet side of the shoal. They are the only grains which can "withstand" that area's higher velocity currents. As the current progresses seaward, it slows, allowing smaller and smaller grains to stay in the bed.
Other borrow sources include offshore deposits which are most likely historic ebb shoals. These historic ebb shoals were formed by the same processes as the present ebb shoals and probably exhibit the same sand size distribution characteristics. Therefore, most borrow sites will show significant variation in sand size.
The effect of this variation on dry beach width can be shown using Dean's (1991) equilibrium beach profile equations for calculating dry beach gain. Although Dean developed equations for intersecting, non-intersecting, and submerged profiles, only the non-intersecting profile formula, Equation (2-3), is used here for illustration purposes. The other two equations would show the same trends. Equation (2-3) can be iterated to determine the added dry beach width for a given volume.
V_3W*3( A An)5/ + 3h*W*( Anl)3/
Ay=- 5W* Af 5 Af -(2.3)
B
where V is the volume added per unit width, B is the berm height, Ay is the change in dry beach width, An is the A factor based upon the native sand, Af is the A-factor based upon the fill sand, h* is the depth of closure, and W* is the cross shore distance
to the depth of closure.




10
TABLE 2- 1: Effect Of Varying Sand Size On Equilibrium Dry Beach Width

0. 0.115 0.35 0.135 212 2 j b 1 0
II 0.3 I 0.125 I 0.35 I 0.135 1 212 1 2 6 1 13.6
0 0.3 y I 0.1o3 y ] 0 1 0 3 I lz I Z 0 1 z .u

D= 0.35 mm
__ D=0.30 mm
D=0.25 m
D=0.20 mm
I I I
0 5 10 15 20 25 3(
EXTENSION TO DRY BEACH WIDTH AFTER REACHING EQUILIBRIUM (m)

FIGURE 2- 3: Effect Of Varying Sand Size On Added Equilibrium Dry Beach Width
Table 2-1 shows the effect of different sized sand on dry beach width change, Ay. Figure 2-3 illustrates this effect graphically. Figures 2-4, 2-5, 2-6 illustrate the resulting profile evolution for fill with different sand sizes. Equation (2-3) assumes the beach is in equilibrium. When fill is placed upon a beach during a nourishment project, the beach is out of equilibrium. As the beach equilibrates, the dry beach width of finer sand will retreat faster ( something greatly out of equilibrium will move toward equilibrium faster than something slightly out of it) and father than that of coarser sand. This is shown in Figures 2-4, 2-5, and 2-6 as the change from the design template profile to its post




-3 1
Profile of 0.25 mm sand after reaching equilbrium

after reaching equilbrium

FIGURE 2- 4: Comparison of Beach Profiles for Different Mean Grain Sizes

-8-

CROSS SHORE DISTANCE (METERS)

-Original profile (d=.35) before nourishment
- ------ Profile of .25mm and .35mm sand immediately after nourishment
- - Profile of .35mm sand after reaching equilbrium

FIGURE 2- 5: Comparison of Pre-construction, Post Construction, and Equilibrium Post Construction Beach Profiles. Fill Has a Mean Diameter of 0.35mm.

1)""EDP .. 100 150 200 250 3




12
construction equilibrium profile. The faster and farther movement toward equilibrium of the finer areas is interpreted as increased erosion which is one of the defining characteristics of hot spots.

CROSS SHORE DISTANCE (METERS)
-------- Original profile (d=.35) before nourishment
- -- Profile of .25mm and .35mm sand immediately after nourishment Profile of .25 mm sand after reaching equlbrium
FIGURE 2- 6: Comparison of Pre-construction, Post Construction, and Equilibrium Post Construction Beach Profiles. Fill Has a Mean Diameter of 0.25mm.
Figure 2-7 shows the plan view of a hot spot created by dredge selectivity. The project depicted in Figure 2-7 has two borrow sites, one at each end of the project. As the fill location became farther away from the borrow sites, the dredge selected finer sand to allow a savings in operating costs. Therefore, the middle of the project received finer sand than the ends. The result of this selection is seen in the plan view. After the beach

50101020203




reaches equilibrium, the areas filled with finer sand have a narrower dry beach width. This hypothetical project was 10 km in length and was nourished with 212 cubic meters of sand per meter of length. The mean diameter of the fill sand varied between 0.3 5mm. and 0.25mm. The resulting additional gain in dry beach width was 0 to 25.9 m.

-o*- Borrow Site A

3000
2000 10.00

Borrow Site B -p.

0.00 200 4.00 6.00 8.00
LONGSI-ORE DISTANCE
(KILOMETERS)
FIGURE 2- 7: Plan View of a Hot Spot Created from Dredge Selectivity

Dredge selectivity can create a hot spot if the dredge companies are interested in saving money and have accurate and detailed data concerning the sand size distribution of the borrow area. Significant sand size variation in the borrow area must also be present. Lastly, the finer sand must adversely affect dry beach width. The dredge companies




appear to have the motivation and means to undertake this process. Borrow sites can be past or present ebb shoals, which exhibit significant sand variation. Fine sand creates a smaller equilibrium beach width than coarse sand given an equal volume per unit length of beach. Clearly, the potential to create a hot spot through dredge selectivity exists. If dredge selectivity is the cause of a hot spot, that hot spot should have a smaller mean sand size than adjacent areas. This concept for hot spot creation was developed by Coastal Planning and Engineering while examining hot spots on Longboat Key and Captiva Island, Florida.
2.2 Residual Structure-Induced Slope
Many areas chosen for nourishment projects have a long history of erosion control attempts. In the past, hard measures such as groins were often employed in an attempt to control the erosion. If a nourishment project is to be constructed in an area with old groins, those groins are often removed as part of the construction process. The nourishment fill is placed over the areas where the groins were removed.
Groins take advantage of longshore transport to "trap" sand. The groin will interrupt longshore transport causing accretion on the updrift side of the groin. The groin has a definite effect on the contours it reaches. Although those contours may change as the dominant wave direction changes seasonally, they are relatively stable. The groin prevents these contours from continuing their landward retreat (except for inlets, groins would only be placed in an erosional area). However, the contours outside of the groin's reach are free to continue their landward migration. This landward recession causes profile steeping as sand is lost in front of the groin but not at it. Figures 2-8 and 2-9 illustrate this phenomenon.




6 M (original)
6 M (new)
5 M (original)
------ 5 M (new)
4 M (original)
4 M (new)
3 M (original)
2 M
I M
0OM
FIGURE 2- 8: Effect of Shore Perpendicular Structures on Beach Slope
In Figure 2-8, a groin is placed on an eroding beach in an attempt to control the retreat of the beach. The groin does limit the retreat of the contours within its extent (in this case, the groin is in contact with the "-2 in" and above contours). However, the groin can not control the retreat of the contours it does not reach. These contours continue their retreat as the nearshore area continues to erode. This movement is shown in the figure as a given contour changes from its original location to its new position. The movement causes the contours to become located more closely together. Since the contours above 2 meters are unable to move significantly, the other contours are constantly moving closer to it as they retreat, resulting in a steeper beach profile. The steeper profile is shown in Figure 2-9.




2.00
GROIN
ZERO CONTOUR IS HELD IN PLACE BY THE GROIN
0.00
1.0 M CONTOUR IS HELD IN PLACE BY THE GROIN
2.0 M CONTOUR IS HELD IN PLACE BY THE GROIN
-2.00 - - - -
P MOVEMENT OF THE 3.0 M CONTOUR
....... .... ..
MOVEMENT OF THE
4.0 M CONTOUR
-4.00 MOVEMENT OF THE
5.0 M CONTOUR
0.00 100.00 200.00
CROSS SHORE DISTANCE (METERS) FIGURE 2- 9: Effect of Shore Perpendicular Structures on Beach Slope (Side View)
In Figure 2-9, the groin holds the contours it contacts in place, but the others contours are free to continue their landward migration. The effect is seen as an increase in profile steepness. In this case, the slope to the 5 in contour increased from 45:1 to 44:1. In terms of A-factor (to the 5 in contour), the value increased from 0.135MAl/3 to 0.144 MA 1/3. Although Figures 2-8 and 2-9 use a groin to illustrate the steeping process, the result would be similar for any shore-perpendicular structure.
After the groins are removed, the beach is free to retreat to its equilibrium position since the groin is no longer present to hold the sand at an "unnatural" seaward position. However, this movement to equilibrium is not instantaneous. Nourishment fill is placed on top of the beach before it makes any significant movement toward equilibrium. The




fill is placed upon a beach receding at a much higher rate than expected. The fill may actually perform as predicted, but the beach will recede to its non-structure equilibrium. As this occurs, the fill appears to be lost more rapidly than predicted. This is not the case. The fill is performing well, but the beach it was placed upon is retreating faster than anticipated. As the beach recedes, a hot spot is produced. This hot spot creation theory was developed by Coastal Planning and Engineering while examining the hot spot on Longboat Key, Florida.
2.3 Borrow Pit Location
Borrow pits are created when the borrow site is mined for sand. As the pits are created, the bathymetry of the borrow site changes significantly. Through wave refraction and shoaling, the bathymetric pattern controls how a wave will impact the shoreline. If the bathymetric pattern is altered, a significant shoreline change may result.
Horikawa et al. (1977) studied the effects of borrow pits on the shoreline with numerical and physical models. The numerical model is based on Sasaki's numerical model for simulating changes in shorelines behind a detached breakwater. It incorporates Komar's (1969) sediment transport equation to provide a finite difference solution to the continuity equation in the longshore direction. The wave data inputs are hindcasts from the Pacific coast of Japan.
Equation (2-4) and Equation (2-5) show Komar's sediment transport equation and the longshore continuity equation, respectively.
Q= 0.77pg HCg sin 2ab (2-4)
16(p )(1- 2)
where p is the density of water, p. is the density of sand, X is the porosity of beach sands, g is the gravitational acceleration, Hb is the wave height at breaking, Cg is the group velocity at breaking, and X b is the angle between the wave orthogonal and
offshore normal.




aQ aA
-_ + = 0 (2-5)
ax a t
where Q is the volume rate of longshore sediment transport, x is the longshore distance, A is the beach cross sectional area above some arbitrary datum, and t is the
time.
Horikawa's numerical model predicts that a salient will form behind borrow pits. Adjacent to the salient, the shoreline recedes. Horikawa postulates that sand accumulates behind a dredged hole because of the reduced wave action found there. The numerical study also revealed three principal trends. First, an increase in the depth which the borrow pit is located (i.e. the original depth of the borrow pits) has an inverse effect on the amount of change in the shoreline (i.e. the greater the original depth of the borrow pit, the less shoreline change). The study also finds that for the given wave and profile data, dredged holes whose original depth is over 40 m have little effect on the shoreline. The study's second finding shows a direct relationship between an increase in pit length and shoreline change. Lastly, most of the shoreline change occurs in the first year. The study was unable to develop any relationships associating shoreline change with the side slope, width, or added depth of the hole. The physical model study confirmed the findings of the numerical model with the exception of the relationship between borrow pit length and shoreline change. The physical model examined a dredged hole of only one type.
The eroding areas adjacent to the salient feature should be considered an erosional hot spot while the salient feature can be termed a cold spot. Horikawa et al. did not undertake their study in an attempt to explain hot and cold spots. They were merely researching the effects of dredged holes on the shoreline due to the large amount of offshore dredging in Japan.
Combe and Soileau (1987) reached the same conclusion about the borrow pit effects when examining the performance of the 1984 Grand Isle nourishment project. Grand Isle developed a cuspate or salient feature behind two deeply mined areas of its borrow




pit. The areas adjacent to the borrow pits eroded rapidly. Combe and Soileau cite a diffraction pattern found around the deeply mined areas as the cause for the hot and cold spots. A complete description of the Grand Isle project can be found in Chapter 5. Combe and Soileau provide field data to confirm the theory postulated by Horikawa et al.
Motyka and Willis (1974) noticed that dredged holes should actually cause accelerated erosion in their lee if refraction is the only mechanism for creating longshore currents. The hole could be thought of as an anti-shoal. In the same manner that shoals focus wave rays, the hole will "bend" the rays away from its lee. The area behind the pit would form a nodal point of sorts in the longshore transport. Figure 2-10 illustrates this phenomenon.

SAND IS MOVED AWAY FROM THE AREA BEHIND THE BORROW PIT BY WAVE INDUCED LONGSHORE TRANSPORT
FIGURE 2- 10: Effect of Wave Refraction behind a Borrow Pit




However, Gravens and Rosati (1994) observed that the nearshore currents in this situation would not be dominated by the incident breaking wave angle. The area behind the pit will have lower wave heights and, as a result, a lower wave set-up than its adjacent areas. The lower set-up will cause circulation into the lee area of the pit. This circulation carries sediment from the adjacent areas into the area behind the dredged hole. This theory correlates better with field and physical model data. This is shown in Figure 2-1 1.

ORIGINAL
- -
I1 M
-I I
WAVE REFRACTION OVER THE BORROW PIT RESULTS IN A SPREADING OF THE WAVE'S ENERGY. THE RESULT IS A LOWER WAVE HEIGHT BEHIND THE PIT THAN IN THE AREAS ADJACENT TO IT. THIS WAVE HEIGHT DECREASE CAUSES A LOWER SET-UP
IN THE AREA

DEPTH

CURRENTS FLOW FROM AN AREA OF HIGHER SET UP TO AN AREA OF LOWER SET-UP

AREA OF LOWER SET-UP

CURRENTS FLOW FROM AN AREA OF HIGHER SET UP TO AN AREA OF LOWER SET-UP

THE SET-UP GENERATED CURRENTS TRANSPORT
[ SAND INTO THE AREA BEHIND THE BORROW PIT,
CAUSING ACCRETION IN THE AREA
FIGURE 2- 11: Effect of Set-Up Generated Currents on the Area Behind a Borrow Pit
Another study on the impact of dredged holes on the shoreline was conducted by Kojima. et al. Their study explored the possibility of a link between beach erosion occurring on the northern part of Kyushu Island, Japan and dredging activities in that area. They found that the dredged holes in their study area were refilled with sediment




coming from the hole's landward side. Therefore, the holes were removing sand from the beach littoral system. The resulting loss of sand created profile steepening. The authors are hesitant to credit the dredged holes as contributors to Kyushu Island's shoreline retreat, but suggest care should be taken when dredging due to the apparent correlation between the mining and erosion. They suggest that mining should take place in depths of 35 m or greater to avoid any effects on the shoreline. Although the study provided no additional insight into the formation of salient features like those found on Grand Isle, Kojima et al. demonstrated another possible detrimental effect of dredged holes on shoreline position (Kojima et al., 1986).
McDougal et al. (1995) also investigated the effects of dredged holes on the wave field. However, his study deals with the effectiveness of dredged pits as breakwaters. Therefore, it does not examine the effect of borrow pits on the shoreline. None-the-less, his study, which uses linear wave theory with a two-dimensional Green's function, provides some insight into the phenomenon. McDougal et al. finds that dredged holes cause a partial standing wave system immediately seaward of the pit and a shadow zone of reduced wave heights immediately landward of the pit. McDougal et al. did not examine the effect of the shadow zone on the longshore sediment transport. However, this area of lower wave height could create set-up driven currents as Gravens and Rosati proposed.
The set-up current increases in strength as the wave height gradient becomes larger. Therefore, the more effective the pit is at damping waves, the greater the set-up driven current will be. McDougal et al. examined the optimum pit parameters for wave reduction. The pit or pit group must be located in an area where small changes in incident wave angle occur. If large changes in wave direction occur, it is ineffective at providing consistent wave reduction. The pit width to wavelength ratio is directly proportional to the size of the shadow area. For example, a one wavelength pit will shelter an area one to six wavelengths long behind it, while seven to fifty wavelengths are




sheltered by a three wavelength pit. Borrow pits meeting McDougal's optimum wave reduction criteria should be considered as prime candidates for creating hot spots.
Borrow pits may be the most researched hot spot theory. None-the-less, exactly what combination of borrow pit parameters will cause a shoreline perturbation is unknown. Original water depth is one of the dominant factors in determining shoreline change. However, it seems likely that the 40 m depth given by Horikawa et al. is high for the United States (particularly the East and Gulf coasts). More research is needed to find what exact combination of parameters will cause a hot spot. The defining feature of a hot spot created by borrow pits are crenulate features. The apex of the crenulate feature, or cold spot, will be located behind the borrow pit while the areas of lower displacement, or hot spots, are found on the sides of the apex.
2.4 Breaks in Bars
Breaks in bars are one of the least researched causes of hot spots. The exact mechanism causing the break is unknown. It may be part of the natural process or it could be man-made. A man-made break might result from the use of fill material which is coarser than the native beach. Dean (1973) developed a method for predicting the presence of a bar by comparing the wave period with fall velocity. Equation (2-6) shows the comparison equation.
If Hb > bar formation will occur. If Hb < no bar will form. (2-6)
Lo P gT Lo P gT
where Hb is the wave height at breaking, Lo is the deep water wave length, wf is the fall velocity of the mean sand grain, 3 is a proportionality factor for the suspension height, g is the gravitational acceleration, and T is the wave period.
The addition of coarser-than-native fill with its larger fall velocity, Wf, will decrease the amount of time that wave conditions will build bars. If the change is great enough, it




is possible that bars present before the project will disappear. This phenomenon may be project wide (the elimination of all bars in the nourishment project) or it may be local. A bar break within a project may be a result of coarse fill being placed adjacent to fine fill. The area of coarse fill might lose its bar(s) while the fine areas keep theirs. Although this is a possible mechanism for the creation of breaks in bars, more research is needed to fully understand the phenomenon.
Even though the mechanism for bar break creation may not be well understood, their results are quite similar to the effect of gaps between breakwaters. The effects of wave diffraction through breakwater gaps is well known. Penny and Price (1952) provided the solution for many particular cases of diffraction around breakwater-like structures. Figure 2-12 shows a plot of their calculated diffraction coefficients for normal wave incidence through a 2.5 wavelength gap.
Although the breakwater diffraction coefficients may not be the same for the case of bars, the general trend of higher wave energy being located behind the gap will persist. A larger wave height relative to adjacent areas will increase the transport out of the area. Equation (2-4) shows the importance of wave height in longshore sediment transport. Equation (2-3) shows the negative effect of increased transport on beach width.
On a simpler level, the bar dissipates wave energy. Any break in the bar will result in more wave energy reaching the beach. That energy will be centered on the area generally behind the break. The higher wave energy creates an increase in sediment transport. The resulting gradient in the longshore sediment transport causes beach erosion.
Breaks in bars may be the easiest hot spot cause to detect. Aerial photos provide an effective means to search for the phenomenon. In addition, this hot spot mechanism is the simplest and most direct: a relative increase in wave height. Breaks in reefs have the same effect as breaks in bars. However, reefs are not as dynamic as bars. Therefore, the reef gap effect should be easier to predict.




FIGURE 2- 12: Isolines of Approximate Diffraction Coefficients for Normal Wave Incidence and a Breakwater Gap of 2.5 Wavelengths




25
2.5 Mechanically Placed Fill
In most nourishment projects, the fill material is placed hydraulically whereby the dredge pumps a sand-water mixture to the beach in an attempt to fill the design template. In some cases, the design template calls for sand to be placed steeper than the angle of repose for some sand-water mixtures. The dredge operator is contracted to fill the project according to the design template. If the dredge operators are unable to meet the design template because of angle of repose limitations, they overfill the area to provide the design template's construction berm width. Figure 2-13 illustrates this procedure.
PROFILE THAT CONTRACTOR
IS ABLE TO ACHIEVE WITH
2.00 - - - HYDRAULICALLY PLACED FILL
DESIGN TEMPLATE
0.00
z
0 EXTRA FILL
P MEAN SEA LEVEL
. ....... . ...... ...........
O R IG IN A L PR O FIL E ............................................
-2.00
-20.00 0.00 20.00 40.00 60.00 80.00 100.00
CROSS SHORE DISTANCE (meters)
FIGURE 2- 13: Extra Fill Resulting when Hydraulically Placed Fill Is Unable to Meet the Construction Template Slope
Even if the angle of repose can meet the template's slope, the dredge operators will often overfill the project. The cost of returning to refill an under filled area is much higher than simply overfilling every site. To guard against the cost of returning, the operators take out an "insurance policy" of sorts in the form of extra fill. Areas constructed by hydraulically placed fill have a greater volume placed on their project. The extra fill may




be necessary to meet the design template's berm width or it may be a precautionary measure taken by the contractor in an attempt to cut operating costs.
Some projects areas are filled using mechanical means. The fill might be trucked in and paced by bulldozers. Mechanical placement deposits dry sand in the fill area. Bagnold (1954) showed the angle of repose for a sand-water mixture is lower than that of sand alone. Therefore, the mechanically placed fill can meet the design template more readily with little overfill. In addition, the cost of returning to refill under filled sites is minimal. The contractor may not place extra fill as an "insurance policy." As a result, the mechanically filled areas may have less placed volume than hydraulically filled areas. Equation (2-3) shows the negative impact that a decrease in added volume has on the gain in equilibrium beach width. The areas with lower added volume will have a narrower
TABLE 2- 2: Effect of Varying Added Volume on Equilibrium Dry Beach Width

.Z U.oo V.,100 U.ou U.,oI 0I I Z I
200 0.35 I 0.135 I .3 0.135 2 6 24.5
---190 0.3577 0.350 5 I "35 1_ 2 I_ 73 I
18 .50135 0.5 015 I 2WW I
T~D~3 W33 -ins T3t 22
--T7-~ ~ 3 WS~ U
Tzo 035 I 0.35 0.5 0.3 I 29 I

added beach width at equilibrium. Table 2-2 shows the resulting equilibrium dry beach additions for different volumes of added sand. The areas with mechanically placed sand perform worse than the adjacent hydraulically extra-filled areas. They are often called erosional hot spots as a result. Figure 2-14 illustrates the hot spot. This hot spot creation theory was developed by Olsen and Associates while examining the hot spot on Hilton Head Island.




DESIGN TEMPLATE DRY BEACH WIDTH
60.0050.00~40.00EQUILIBRIUM SHORELINE OF HYDRAULICALLY FILLED AREAS ~30.00- HOT
SPOT
20.00- T
EQUILIBRIUM SHORELINE OF MECHANICALLY FILLED AREA
10.00- I
0.00 2.00 4.00 6.00 8.00 10.00
LONGSHORE DISTANCE (kmn)
FIGURE 2- 14: Plan View of a Hot Spot Created by Mechanically Placed Fill Notes: The lower added volume of the mechanically placed areas result in a narrower dry beach extension at equilibrium. The mechanically placed fill has less added volume than the hydraulically placed fill for two reasons. First, the dry sand placed mechanically has a steeper angle of repose which allows it to meet the design template. Hydraulically placed sand is often unable to meet the design template due to the smaller angle of repose of a water-sand mixture. Secondly, there are minimal costs associated with returning to place additional fill mechanically. The cost of returning is smaller than the cost of placing extra fill. Areas with hydraulically placed fill often receive extra fill. It is cheaper to place extra fill than to take a chance that the dredge will have to return to an underfilled area. In this case, areas with hydraulically placed fill received 212 cubic meters per meter of beach while the mechanically placed areas had 160 cubic meters per meter placed upon them. The fill and native sand were assumed to be 0.3 5 mm.The berm height was 2 m while 6 m was used for the depth of closure.




2.6 Profile Lowering Adjacent to Seawalls

Many nourishment projects contain areas armored by seawalls. Beaches in front of seawalls are often more eroded than those without their protection. However, this erosion is not fully reflected in the location of the mean sea level. Frequently, a beach profile in front of a seawall will have approximately the same mean sea level station as a profile without the shore-parallel structures. However, the elevation of the two mean sea level locations will be different. The elevation difference between seawall areas and normal areas is shown by use of equilibrium beach profiles (Dean, 1991) in Figure 2-15.

FIGURE 2- 15: Profile Lowering in Front of a Seawall

The upper reaches of the seawall profile are truncated. Because the origin of the profile does not really exist, it is called a virtual origin Although the virtual origin is not the "0" station, it would be if no seawall were present. As the virtual origin continues to retreat due to background erosion, the elevation is lowered in front of the seawall. This




-30.00 0.00 30.00 60.00 90.00 120.00 150.00 180.00 210.00 240.00 270.00
CROSS SHORE DISTANCE (meters)
FIGURE 2- 16: Evolution of an Eroding Profile in Front of a Seawall




process is shown in Figure 2-16. In this figure the profile shifts landward 25 in every time increment. The result of the shift is the decreased elevation at the seawall.

FIGURE 2- 17: Additional Volume Required by a Profile with a Seawall
Figure 2-17 illustrates the problem that this elevation difference creates for the nourishment designer. To create an incipient beach in the figure's seawall area, volume A must be placed on the profile. The non-seawall area already has an incipient beach. If the nourishment designer wishes the seawall area and the normal area to gain the same amount of beach from a nourishment, he or she needs to place the additional volume A on the seawall area. In some cases, this additional need is overlooked or underestimated as the design template is roughly the same for all areas. Therefore, the seawall area does not receive enough placed volume to create the desired equilibrium dry beach width. Table 2-3 compares the equilibrium dry beach gain of a normal and a seawall area for various placed volumes. For the seawall areas, Equation (2-7) is employed to calculate the volume required to create an incipient beach, VR.




]5/3 1 1A.
3y h-j"L 5/3 3 A 5. (2-7)
u -A N +__]/3 i
where VR is the volume required to create an incipient beach width for nonintersecting profiles in front of a seawall, AN is the A-factor of the native sand, AF is the A-factor of the fill sand, h is the depth of closure, and y, is the distance between
the virtual origin and the seawall.
This difference between the placed volume and the incipient beach volume, VR, is used in Equation (2-3) to calculate the resulting equilibrium dry beach gain. For the area without a seawall, Equation (2-3) is directly utilized for the table's calculations. The table shows the dramatic effect profile lowering can have on sand requirements. In some cases, there may be no equilibrium dry beach gain due to the volume used in attempting to create an incipient beach. Although the examples shown here do not account for the volume of sand above the "0" contour, the effect would be the same. However, it would be seen earlier as the sloped part of the dry beach would be truncated before the upper part of the underwater profile. Despite this inaccuracy of this assumption, the poor performance of the lowered profile area, when compared to predictions and adjacent areas, results in it being categorized as an erosional hot spot. TABLE 2- 3: Effect of Profile Lowering on Equilibrium Dry Beach Gain
1.6ew ou seawa11b b
1 25 139 0.115 61 9.1
0716.7 94 0.11T5 221.
0. 1O b. 11 25.
Areas whose mean sea level location has eroded to a seawall are candidates for this type of erosional hot spot. Although the presence of seawalls should alert a designer to a




potential hot spot situation, it is the presence of lowered profiles at the seawalls which cause the hot spot. Older seawalls in highly erosive areas are likely to have a mean sea level station without an incipient beach. Therefore, these areas should be provided with additional fill. The required additional fill may be larger than the planned fill. Overlooking this additional fill requirement could be devastating to the performance of the project in these areas. This erosional hot spot cause was developed by Coastal Planning and Engineering as well as Olsen and Associates while examining Longboat Key and Hilton Head Island, respectively (Campbell, 1995, personal communication; Bodge, Olsen, and Creed, 1993).
2.7 Headlands
Some projects contain areas that are artificially kept seaward of their natural positions. Seawalls, revetments, and other structures can be utilized to achieve this artificial seaward position. These measures are very expensive and are only deployed in an attempt to save an area of high value. The structures might be used to protect a road or a hotel. As a result, the protected areas are seaward of the adjacent areas which were not protected due to the associated cost.
Eventually, the beach recedes enough to justify a nourishment project. The nourishment design will specify a design berm width. Even though the protected area is seaward of the rest of the beach, it will be given the same beach extension. The added beach is seaward of the rest of the filled areas. This seaward perturbation acts like a headland, an area of elevated wave energy. The perturbation tends to be eliminated by the wave action as the shoreline returns to its natural platform. Figure 2-18 illustrates this process. The headland elimination causes higher erosion rates which label the area as a hot spot. Olsen and Associates as well as Coastal Planning and Engineering have introduced this concept while examining hot spots on Hilton Head Island and Captiva




Island, respectively. Hot spots which result from this process can be easily noticed by the seaward position of an armored structure. Aerial photos are an effective way to check for such a perturbation.
THE NOURISHED SHORELINE PERTURBATION OCCURRING IN FRONT OF THE HIGH VALUE STRUCTURE IS ELIMINATED
AS THE SHORELINE RETURNS TO IS ORIGINAL STRAIGHT AND PARALLEL GEOMETRY
SHORELINE AFTER NOURISHMENT
**-ORIGINAL SHORELINE

SHORELINE CONTINUES TO RETREAT IN -THE
NON-ARMORED AREAS
HIGH VALUE STRUCTURE (PERHAPS A HOTEL)
FIGURE 2- 18: Hot Spot Created due to the Headland Effect
2.8 Residual Bathymetry
Dean and Yoo (1993) introduced the concept of residual bathymetry while examining beach nourishment performance. Their study observed that nourishment fill may extend to such depths where sediment is not mobilized. If this deeply placed fill, called "residual bathymetry", is placed irregularly, it changes the bathymetric form. The resulting refraction and shoaling changes can alter the shoreline. The deeply placed fill is of more concern because the shallow irregular fill is assumed to be "planed off' by the longshore transport. Therefore, it will have no lasting effect on the wave field.
Dean and Yoo propose that equilibrium shoreline will be a damped form of the residual bathymetry's contour. Equation (2-8) presents Dean and Yoo's project related transport equation.

X' "SHORELINE RECEDES TO THE POINT WHERE THE
HIGH VALUE STRUCTURE MUST BE ARMORED

10

m

- - - - - -

!




Q K E 0 COO CC o- )C 2_ I( 1AP, +AP] (2-8)
Pg9(S- DO( -P) C2 LKC1 r~~
where K is the sediment transport factor usually taken as 0.77 (it may be a function of sediment grain size or other characteristics), E(, is the total average deep water energy per unit surface area in deep water, Cg. is the wave group velocity in deep water, P,, is the azimuth of the outward shoreline normal, a 0 is the azimuth from which the deep water wave originates, Gb is the wave celerity at breaking, C, is the wave celerity at the outer depth of placed fill, C2 is the wave celerity at the depth of limiting motion, p is the density of water, g is gravitational acceleration, s is specific gravity, p is the porosity, AP and A132 are the changes in the azimuths of the outward normals of the
perturbation at the contour specified by their subscripts.
The approximate equilibrium planform. of the shoreline will occur when QPis set equal to zero, yielding Equation (2-9) which can be used to find the equilibrium position of the shoreline given the change in azimuth of the perturbation.
Af32 =AII- 1(2-9)
It can be shown that Equation (2-9) can interpreted as Equation (2-10) which yields the maximum displacement of the equilibrium shoreline given the size of the maximum offshore perturbation, Aya
AY2mx=Ay Ima I_ (2-10)
Every different irregularity in the fill's deeper parts will cause a distinct shoreline perturbation. The perturbation will match the offshore irregularity in form and will have an amplitude given by Equation (2- 10).
The irregularity in fill placement can be caused through several mechanisms. As discussed in Section 2.5, fill is usually placed hydraulically by pumping a sand-water mixture through pipes onto the beach. As an area is filled with material, the pipe is extended to the next area. The result can be a lumpy or irregular distribution of fill. Fill




plies up in mound-like shapes which are later flattened by earth moving equipment. The earth moving equipment can not reach any of the fill which is underwater. The fill's bathymetry will have a distinct series of perturbations. The "wavelength" of the perturbations will depend on the length that the dredge pipe is extended each time as well as other factors. The "height" of the perturbations will depend on how much fill is

deposited at each extension location.

example.

PIPE POSITION AFTER SECOND EXTENSION

PIPE POSITION AFII FIRST EXTENSIO?

LOW TIDE LINE--4

/1

/ I

/ S
\/ / I
-- / \\I

FIGURE 2- 19: Creation of Irregular Bathymetry by Nourishment Placement Notes: The dredge pipe pumps a water-sand mixture on the beach. As it does, the sand piles up onto a roundish mound which is bulldozed above sea level. However, the parts of the fill which lie underwater are not arranged by the earth moving equipment. These areas remain in their mound configuration, creating irregular bathymetry.
After an area is filled with sediment, the dredge pipe is extended to the next area where the fill leaves behind the same bathymetric pattern. In this manner, a series of underwater perturbations occur.
In reality, the perturbations are not so pronounced and the spacing is not so even as they appear in the figure. Here, the perturbations are accentuated to make them more obvious. The regular spacing is presented for demonstration purposes.

Figure 2-19 illustrates a perturbation series

ORIGINAL PIPE
POSITION




Dredge spoil placement is another mechanism which could cause irregular changes in the bathymetry. When inlets are dredged to improve their navigation capacity, the spoil is sometimes placed in adjacent waters. Since inlet dredging occurs cyclically throughout time, the process could easily cause significant changes in the bathymetric pattern as spoils from multiple dredgings accumulate. Areas with dredged channels on both sides are particularly susceptible to this phenomenon. If the spoil from each channel is placed adjacent to the channel on the area side, a parabola shaped perturbation can form. From Equation (2-10), it can be shown that the shoreline would move to match the perturbation (although it would be damped). As the shoreline matched the offshore perturbation, a hot spot would occur at the area's center. Figure 2-20 illustrates this situation. Any fill placed in the nearshore area is likely to cause these perturbations. Economics and technology prohibit the fill from being placed regularly. However, the degree of such effects on shoreline irregularities may be within the degree of natural fluctuation.

IN RESPONSE TO THE OFFSHORE PERTURBATION, THE SHORELINE RECEDES, LEAVING A HOT SPOT ORIGINAL
SHORELINE
CHANNEL A
PLACEMENT OF SPOIL- / /I,
FROM DREDGING / / PLACEMENT OF SPOIL I
CHANNEL A / FROM DREDGING CHANNEL
//x / CHANNEL
/ / x
I / / AFTER PLACEMENT OF DREDGE SPOILS, THE
I f / CONTOURS OF THE AREA HAVE CHANGED
/ FROM STRAIGHT AND PARALLEL TO
PARABOLA SHAPED. I
I I I
II I '
I
FIGURE 2- 20: Creation of Irregular Bathymetry by Placement of Inlet Dredge Spoil




37
In order to test this residual bathymetry theory, a numerical sediment transport model was developed as well as a physical model. Chapter 3 deals with the physical model tests while Chapter 4 examines the numerical model results. Since the idea of the shoreline forming a damped version of the offshore perturbation is crucial to the theory, Appendix B contains the numerical model's results concerning this shoreline matching. The numerical model's results are also compared with the theoretical results from Equation (2-10).




CHAPTER 3
PHYSICAL MODELING OF RESIDUAL BATHYMETRY
A physical model of residual bathymetry was constructed to test the effect of offshore perturbations on shoreline position. Test runs were conducted in May and September, 1995 at the University of Florida Coastal and Oceanographic Engineering Laboratory in Gainesville, Florida. The model was scaled to simulate the six to eight second periods associated with higher energy waves on Florida's east coast. Based on Froude modeling, the 1.25 and 1.5 second waves used in the model result in a 1:5.3 time and velocity scale. The corresponding size scale ratio is 1:28.5. Due to the model's limitations, the cross shore dimensions of the perturbations are exaggerated when scaled at 1:28.5. Therefore, the size scale is only approximate.
3.1 Equipment Description
The tests were conducted in a rectangular wave basin 14.9 m long and 16.0 wide. A flap type wavemnaker measuring 9.2 m long and 0.6 m high was placed diagonally across the corner of the basin. The wavemaker was powered by an electric motor attached to a 0.4 m diameter fly wheel. The attachment point of the rod connecting the fly wheel to the flap structure could be changed to alter the wavemaker stroke. The period was altered through gearing changes. The flap structure consisted of wood attached to a steel frame which was hinged 38.0 cm above the basin floor.
To limit the model's length and material requirements, concrete blocks were placed to form a channel 3.0 m wide and 5.4 m long area. This area was used to construct the model beach. The beach consisted of two levels. A lower level, composed of gravel,




was placed at a 1:16 slope from the basin's floor to an elevation of 12.7 cm. Since the gravel could not be mobilized by the waves, it was used to simulate residual bathymetry below the depth of limiting motion. To simulate offshore perturbations, the gravel was organized to form contours with a cosine curve shape which could be representative of irregular fill created by dredge pipe extensions as shown in Figure 2-15. Different amplitudes of cosine curves were used, but always kept the form of a cosine curve extending from 7t to 27r. Above the gravel, sand with a median diameter of 0.21 mm was placed at a 1:8 slope with straight and parallel patterned contours oriented perpendicular to the side walls. The sand continued to an elevation of 38.1 cm. A schematic of the basin and its contents is shown in Figure 3-1. A side view of the walled-off beach area is located in Figure 3-2.
PUMP TO
PROVIDE
IN FLOW
9 SLUICE GATE TO BASIN
OTO ALLOW BASIN DRAINAGE
MODEL AREA
CATWALK
OVER THE BASIN
5.4
METERS SAND METERS
16.0 METERS
FIGURE 3- 1: Wave Basin Schematic




CINDER BLOCK GUIDE WALLS

16
1' r i "

.2 C M I l

GRAVEL

' PERTURBATION FIGURE 3- 2: Side View of Model Beach

Three methods were employed to document the model's experiments. All of the runs were video taped by camera placed on a cat walk above the model. In addition, photographic stills were taken of the beach area before and after every run. Measurements of contour locations were also taken at the end of the experimental runs.
3,2 Trial Runs
After model construction, trial runs were conducted to test the sensitivity of shoreline change to wave and bathymetric parameters. Variations in offshore perturbation and wave height were examined. Table 3-1 summarizes the different combinations of parameters which were tried. Figuress 3-3 and 3-4 show the model before and after trial run 5, respectively.

1.- 121.9 CM




FIGURE 3- 3: Trial Run 5, Initial Bathymetry

FIGURE 3- 4: Trial Run 5, Post-Run Bathymetry




TABLE 3-I1: List Of Different Parameters Used In The Trial Runs

[4 2.5 1 30.5 J25.4 CONFUSED
5 5.1 1 30.5 25.4 CONFUSED
6 J 5.1 1 120* 25.4 CONFUSED
IL -7 2.5 1 1 30.5 1 25.4 CONFUSED
*RUN 6 DID NOT USE A SIN PERTURBATION, BUT A PLACED MOUND WITH AN APPROXIMATE 120 CM PERTURBATION
The trial runs yield insight into several facets. Most importantly, the model was susceptible to developing rip currents. These currents became so powerful that they dominated the sand transport. Whatever transport was occurring due to longshore transport was insignificant compared to the transport associated with the rip currents. Although the currents existed at every wave height attempted, they seemed to worsen as wave height increased. The currents were located at beach cusps with the inflow of the current occurring at the horns of the cusps. Beach cusps in nature do not behave in this manner. Clearly, a modeling instability had occurred.
3.3 Experimental Runs
Due to the observations of the trial runs, different combinations of parameters were used during the experimental runs. The experimental parameters were required to meet three conditions. First, they had to posses a lower tendency to form rip currents. Therefore, lower wave heights and longer periods were used. The experimental runs used wave heights ranging from 1.6 cm to 3.5 cm instead of the 2.5 cm to 5.1 cm trial waves. The period was lengthened from I second to 1.25 and 1.5 seconds. Secondly, they had to increase the magnitude of the longshore transport. To find out what combinations

1 1
2
3

30.5

25.4

CONFUSED




127 147.6 138.4 9.2
190.5 147.3 151.1 -3.8
254 148.6 161.3 -12.7
295.9 148.6 165.1 -16.5

would yield the most transport the numerical model discussed in chapter 4 was employed. The model showed that longer periods, larger perturbations, and shallower perturbations resulted in increased longshore transport. As a result, the water level was lowered from the trial level of 25.4 cm to 20.3 cm; and the perturbation was increased from 30.5 cm to 121.9 cm. Lastly, the parameters had to represent reasonable natural occurrences. Obviously extremely long periods with excessive perturbations would dramatically increase transport. However, after applying Froude scaling, they would not represent any event occurring in nature. The parameters were tempered in an attempt to represent plausible conditions.
Tables 3-2, 3-3, 3-4, and 3-5 show the results of each experimental run and the parameters used in that run. The change of the mean water level, or "0", contour is compared graphically with the offshore perturbation in Figures 3-3, 3-4, 3-5, and 3-6. In each case, the figures show the shoreline changing to a damped form of the offshore perturbation. Figures 3-7, 3-8, 3-9, and 3-10 show only the "0" contour change resulting from each run. Each of these figures has a higher scale than Figures 3-3, 3-4, 3-5, and 36 to provide a more detailed picture of the shoreline change. Figure 3-11 illustrates the change of the -2.54 cm and -5.0 cm contours as well as the "0" contour for the Sept. 29, 1995 run. Figures 3-14 and 3-15 show photographs of the contours of the model before and after the Sept. 29, 1995 run, respectively.

TABLE 3- 2: Run I Sept. 7,1995

146.7

139.7




TABLE 3- 3: Run 2 Sept. 8, 1995

190.5 145.4 149.9 -4.4
254 145.4 157.5 -12.1
295.9 147.3 159.4 -12.1

TABLE 3- 4: Run 3 Sept. 9, 1995
EXF
WAVE HEIGHT 1.6cm
PERIOD 1.5 sec.
PERTURBATION 121.9 cm

SKUIN UUMA I IUN I L. .Dfl OUS 1 U 1o. I i

63.5

1467

1

38.4

127 146.7 137.2 9.5
190.5 145.4 149.9 -4.4
254 145.4 157.5 -12.1
295.9 147.3 159.4 -12.1

TABLE 3- 5: Run 4 Sept.29, 1995
WAVEHEIGHT3.5cm
PERIOD 1.25 sec
PERTURBATION 121.9cm WATER DEPTH 203cm
RUN DURATION 2.5 hours

! 14W ... .. .. ...
63.5 149.2 139.1 -10.2 1737 156.8 -16.8
127 150.2 149.9 -0.3 174.9 166.1 -8.9
190.5 149.9 156.2 6.4 170.8 176.5 5.7
254 150.5 157. 2 6.7 1734 1765 3.2
295.9 148.6 156.2 7.6 174.3 1759 1 6




0 100 200
LONGSHORE DISTANCE (cm)

ORIGINAL "" CONTOUR

-4- "( CONTOUR AFTER 2.5 HRS. PERTURBATION AT -7.6 cm

FIGURE 3- 5: Residual Bathymetry Model, Run 1 Sept. 7, 1995 (with perturbation) FIGURE 3 5: Residual Bathymetry Model, Run 1 Sept. 7, 1995 (with perturbation)

FIGURE 3- 6: Residual Bathymetry Model, Run 2 Sept. 8, 1995 (with perturbation)

0
0
0

4
300




0
I
0

100 200
LONGSHORE DISTANCE (cm)

[ ORIGINAL "0" CONTOUR

-+"' CONTOUR AFTER 2.5 HRS. PERTURBATION AT -7.6 cm

FIGURE 3- 7: Residual Bathymetry Model, Run 3 Sept. 9, 1995 (with perturbation)

-4- '' CONTOUR AFTER 2.5 HRS. PERTURBATION AT -7.6 cm

FIGURE 3- 8: Residual Bathymetry Model, Run 4 Sept. 29, 1995 (with perturbation) FIGURE 3- 8: Residual Bathymetry Model, Run 4 Sept. 29, 1995 (with perturbation)

0 100 200 300
LONGSHORE DISTANCE (cm)

II

I- ORIGINAL "0"'' CONTOUR




- U
7
7
100 200 3
LONGSHORE DISTANCE (cm)

- ORIGINAL "" CONTOUR

-+- "V CONTOUR AFTER 2.5 HRS. I

FIGURE 3- 9: Residual Bathymetry Model, Run 1 Sept. 7,1995 FIGURE 3- 9: Residual Bathymetry Model, Run 1 Sept. 7, 1995

FIGURE 3- 10: Residual Bathymetry Model, Run 2 Sept. 8, 1995

170




w
C-,
0
0
0

LONGSHORE DISTANCE (cm)

I-w ORIGINAL 'T" CONTOUR

-- "0" CONTOUR AFTER 2.5 HRS.

FIGURE 3- 12: Residual Bathymetry Model, Run 4 Sept. 29, 1995

- ..,-

FIGURE 3- 11: Residual Bathymetry Model, Run 3 Sept. 9, 1995




225 S205 185 O 165 U)
O 145
125
0

-W ORIGINAL" CONTOUR .** "0" CONTOUR, T=2.5 HRS.
-- "-25" CONTOUR, T=2.5 HRS. -e- ORIGINAL "-5.1" CONTOUR

200 225 250 275 300

-A- ORIGINAL "-25" CONTOUR
-&- "-5.1"CONTOUR, T=25 HRS.

FIGURE 3- 13: Residual Bathymetry Model, Run 4 Sept. 29, 1995 (multiple contours)

E Is.... ,, -EE .. .

FIURE 3- 14: Sept. 29, 1995 jun, Initial Bathymetry
FIGURE 3- 14: Sept. 29, 1995 Run, Initial Bathymetry

25 50 75 100 125 150 175
LONGSHORE DISTANCE (cm)


-- .................. ----------- ---............ ........
...
- o-.
.. . o '

I I I I I I I I I I I


-




FIGURE 3- 15: Sept. 29 Run, Post-Run Bathymetry

The experimental runs conducted on the physical model confirmed that the shoreline will develop a damped form of the offshore perturbation. In each of the four runs, the "0" contour shifted to approximate the damped cosine curve shape of the offshore perturbation. The shoreline did not, of course, form a perfect cosine curve, but the basic shape was present. Wall effects, imperfect cosine curve bathymetry, rip currents, etc. can account for the irregularity of the "0" contour.
3.4 Comparison of Physical Model Results Versus Theory
The theoretical predictions of Equation (2-7) proved to be reasonably accurate. The experimental shoreline displacements were less than the theoretical predictions by an average of 38% over the four runs. If the first two runs are dropped, the average difference is reduced to -23.5%. -Excluding the first two runs from the comparison is probably appropriate because their lower wave heights, in all likelihood, did not move the




shoreline to equilibrium in the 2.5 hour run duration, and thus do not provide a meaningful comparison. A dye test for longshore current showed that the last two runs did reach equilibrium, and therefore provide a more meaningful comparison. A summary of the theoretical predictions and experimental results is contained in Table 3-6. Considering the imperfections existing in any lab model, the theory predicted the experimental results with reasonable accuracy, thereby confirming the residual bathymetry theory introduced by Dean and Yoo (1993).
TABLE 3- 6: Comparison of Theoretical Results and Experimental Results

SE 95 3.8 1 12.1 1 15. 4 .-28.2 t *3 a
5.t- 1.29,lu99 -11. 1 7.3 2Z.7 33.6 -6.9 -26.5%
-t VEA LL RUNS [ j
3.5 Summary
Despite instabilities in the early runs, the laboratory model of residual bathymetry performed approximately as the theory predicted. The model not only provided theory verification, but provided insight into the process. Neglecting the rip current effects, the trial runs showed that if the offshore perturbations end in fairly deep water, such as beneath the depth of closure, the process has little effect. Although the theory states that the irregularly placed fill must extend to depths greater than the depth of limiting motion, it does not specify the wave conditions which create that depth of limiting motion. For




averaged sized waves, the depth of limiting motion might be shallow enough to allow the perturbation to affect the shoreline.
For instance, the physical model's 3.5 cm waves scale to 1.0 m prototype waves. Waves of I m are higher than the average wave on Florida's east coast. The observed depth of limiting motion in the model was 12.7 cm which scales to a 3.6 rn prototype depth. This depth is not beyond the depth of closure, but exceeds the depth affected by the average and smaller waves. As long as average to above average waves exist, the perturbation will affect the shoreline. The perturbation might be reduced by the increased littoral transport resulting from larger waves. However, large wave events are infrequent and of short duration. It is feasible that it may take several such events to reduce the perturbation substantially. Although the model was unable to simulate this reduction in residual bathymetry due to the gravel perturbations and monochromatic waves, it did provide a basis for this supposition which can be researched in the future.




CHAPTER 4
NUMERICAL MODELING OF RESIDUAL BATHYMETRY
4.1 Introduction
A numerical model was developed to investigate the possible effects of residual bathymetry. The model incorporates a shoaling and refraction program, McCowan's breaking criteria (Dean and Dalrymple, 1984), the Inman and Bagnold formula for longshore sediment transport, and the continuity equation to simulate shoreline behavior given wave and bathymetric inputs. Two basic versions of the model exist. One program (SIN.FOR) simulates cosine shaped bathymetry while the other (PARA.FOR) has parabola patterned bathymetry. The programs are written in FORTRAN and are listed in Appendix A.
As with any model, several assumptions are made. They are as follows:
1) No cross shore transport exists, all sediment transport is in the longshore direction.
2) Only one profile exists in the model. It is of the form, h = Ay2/3, as developed by Bruun (1954).
3) No transport enters or exits the model boarders.
4) Monochromatic, linear waves can simulate the true random, non-linear spectrum.
5) The cross shore movement of the underwater contours is the same as the zero contour.
These premises allow the assumption of the Inman and Bagnold formula for longshore sediment transport, Equation (4-1), and use of a simple finite difference form of the continuity equation, Equation (4-2).




Q KH:Cg cos0o sin0o (4-1)
8(s- IX1- p)
where Q is the longshore sediment transport, K is a dimensionless parameter, taken here to be 0.77, Cg is wave group velocity, g is the gravitational acceleration, 0o, is the difference between the azimuths of the deep water wave orthogonal and the shoreline's outward normal, s is the specific gravity of the sediment, and p is the
porosity of the sediment.
Q + =0 (4-2)
ax at
where Q is the longshore sediment transport, x is longshore distance, A is the beach
cross sectional area above some arbitrary datum and t is time.
In the program the beach area is represented by a grid whose dimensions are established in the input. For example, in the application to be presented here, the program using cosine bathymetry employed a grid 20 spaces in the longshore direction and 50 spaces in the cross shore direction. In that investigation, each grid area was 15.2 m (50 ft.) by 15.2 m (50 ft.). The deep water wave parameters at each grid are shoaled and refracted in accordance with linear wave theory and Snell's law. When the wave height to depth ratio exceeds 0.78 (McCowan's breaking criteria), the wave parameters present in that grid are used to calculate the sediment transport. The sediment transport gradient existing between that grid space and its adjacent (in the longshore direction) grid space yields the P-Q term. This term is used to solve Equation (4-2) for the change in beach cross sectional area which yields the cross shore position of the shoreline when divided by the sum of the depth of closure and berm height. This change in cross shore position is applied uniformly to every contour landward of the depth of limiting motion




in that grid column, modifying the bathymetric pattern. The program continues rerunning this process until the longshore sediment transport is 0.01% (0.0001% for the parabola bathymetry program) of the first longshore transport value. After meeting this criterion, the beach is considered to be in equilibrium, and the program is terminated.
In addition to the usual limitations associated with any one line explicit numerical model, this model has inaccuracies involving end effects. The last grid space can not compute the longshore sediment transport gradient because that calculation requires the presence of a subsequent grid space. Since the last grid space can not calculate its own longshore transport gradient, the gradient from the adjacent grid space is used. This end effect limits symmetry and accuracy.
CONTOURS ARE SHAPED IN A
COSINE PATTERN BETWEEN CONTOURS ARE STRAIGHT
THE DEPTH OF OUTER FILL AND AND PARALLEL TO THE
DEPTH LIMITING MOTION SHORELINE OUTSIDE THE
OUTER FILL DEPTH
.. ............ ......... .... .
CONTOUR CORRESPONDING STO THE DEPTH OF OUTER FILL(DPT2)
HEIGHT OF COSINE CURVE
- CONTOUR CORRESPONDING ..................-.. -- -- TO THE DEPTH OF LIMITING
MOTION (DPTI)
CONTOURS ARE STRAIGHT ...................-.- AND PARALLEL TO THE
SHORELINE INSIDE THE
LIMITING MOTION DEPTH I ] I I I I 1
0 61 122 183 244 305
LONGSHORE DISTANCE (meters)
FIGURE 4- 1: Bathymetric Pattern in SIN.FOR




In an attempt to simulate the irregular fill created by dredge pipe extensions (see Figure 2-19), the bathymetric pattern of SIN.FOR is made up of cosine curves. Their pattern is the same as that used in the physical model investigations. The contours represent a cosine pattern existing from 7t to 27c. Two amplitudes of the curves can exist at the same time. One is present from the zero contour to a specified contour (DPT1), while the other exists between the first specified contour (DPTl) and another given contour (DPT2). Beyond contour DPT2 the contours are straight and parallel to the shoreline. Figure 4-1 illustrates the bathymetric pattern of SIN.FOR. Every SIN.FOR simulation assigned a 0.0 value to the amplitude of the curves existing landward of DPT1, creating contours straight and parallel to the shoreline. In addition the model was set up to simulate an area 305 meters (1000 feet) (longshore direction) by and 762 meters (2500 feet) (cross shore direction).
Parabola type bathymetry is used by PARA.FOR to simulate the bathymetric pattern left from dredge spoil deposits (see Figure 2-20). As with the cosine bathymetry, two different curvatures can exist concurrently. The first is present from the shoreline to the given depth DPT1. The second curvature exists from the first given depth (DPT1) to another specified depth (DPT2). The bathymetry existing past DPT2 is straight and parallel to the shoreline. The bathymetric pattern of PARA.FOR is shown in Figure 4-2. For the simulations, the curvature was set to 0.0 inside the depth of limiting motion to create straight and parallel shorelines in this region. The PARA.FOR grid consisted of 20 longshore spaces and 50 cross shore spaces. The longshore spaces were 152 meters (500 feet) wide, resulting in a beach 3048 meters (10,000 feet) long in the longshore direction. The cross shore spacing was the same as SIN.FOR, 15.2 meters (50 feet).
The primary purpose of the model is to investigate how a shoreline will react to bathymetric perturbations. Different sets of parameters were input into the models in an attempt to investigate the sensitivity of shoreline change to each parameter. The effects of the depth of outer irregular fill, the depth of limiting motion, the A-factor, the berm




height, and the wave angle were all examined (or an attempt was made to examine these parameters). In addition, the maximum shoreline change created by the numerical model is compared with Equation (2-10). Lastly, numerical simulations of the physical model are compared to the physical model's actual results and theoretical predictions.

CONTOURS ARE SHAPED IN A
PARABOLA PATTERN BETWEEN THE DEPTH OF OUTER FILL AND
"DEPTH LIMITING MOTION
- --N-
- - - -
\TEEH FN

K

CONTOURS ARE STRAIGHT AND PARALLEL TO THE SHORELINE INSIDE THE LIMITING MOTION DEPTH

II I I I I I I
0.0 610 1219 1829 2438
LONGSHORE DISTANCE (meters)
FIGURE 4- 2: Bathymetric Pattern in PARA.FOR

CONTOURS ARE STRAIGHT AND PARALLEL TO THE SHORELINE OUTSIDE THE
OUTER FILL DEPTH
CONTOUR
CORRESPONDING
TO THE DEPTH OF OUTER
FILL(DPT2)
CONTOUR
CORRESPONDING TO THE
DEPTH OF LIMITING
MOTION (DPT1)

3048

4.2 Numerical Model Results: the Effect of Perturbation Depths on Shoreline Change
The theory introduced by Dean and Yoo (1993) states that the magnitude of the shoreline change will be a function of the celerities occurring at the depth of outer




irregular fill and at the depth of limiting motion (see Equation (2-10)). The depth of limiting motion is used because the perturbation causing the shoreline change is assumed to be dramatically diminished landward of the depth of limiting motion. Although this seems logical, it may not always be true. Therefore, in these equations, the depth of limiting motion should be assumed to be the depth where the perturbation ends. The depth at which the phenomenon occurs is crucial to the theory because celerity, based on linear wave assumptions, is shown to be a function of depth and period in Equation (4-3) (Dean and Dalrymple, 1992).
27c h
C = g T tanh __ (4-3)
27c ( CT )
where C is the celerity of the wave, g is the gravitational acceleration, T is the period
of the wave, and L is the wavelength.
However, the period, based on linear wave theory, will remain constant for a given wave. Therefore, the water depth is the only influencing factor in a given wave's celerity. Since the amount of shoreline change depends on the depth of the outer irregular fill and the depth of limiting motion alone, these two parameters were examined to determine what combinations might create significant shoreline changes.
Figure 4-3 shows the qualitative shoreline change occurring when the outer depths of irregular fill and limiting motion are 2.3 meters (7.5 feet) and 3.8 meters (12.5 feet), respectively. As the figure shows, the shoreline changes into the cosine shaped curve of the bathymetric perturbation. The only significant difference between the shoreline, or "0" contour, and the perturbation's contours is the amplitude of the curve. The perturbation has an amplitude of 15.2 meters (50 feet), creating a 30.5 meter (100 feet) maximum cross shore displacement while the shoreline amplitude is approximately 2.4 meters (7.75 feet). The 2.3/3.8 combination is typical of all the runs dealing with cosine




shaped bathymetry (except for the simulations involving non-normally incident waves). Appendix B contains the numerical model outputs from other selected runs. In each case, the shoreline evolved from a straight line into a damped version of the cosine pattern bathymetry existing in the perturbation.
3.05
INITIAL SHORELINE
z
0.0 /
0
0
-305 N EQISTUANC (tEIrs )
061 122 183 244 305
LONGSHORE DISTANCE (meters)
FIGURE 4- 3: Equilibrium Shoreline Resulting from a Cosine Shaped Perturbation Existing between Depths of 2.3 and 3.8 meters (7.5 and 12.5 feet)
Table 4-1 compares the theoretical maximum displacement from Equation (2-10) with the maximum shoreline displacement obtained from SIN.FOR for different outer fill and limiting motion depths (the other inputs were held constant at typical values). The theory always predicts a greater shoreline change than the numerical model. In fact, the numerical predictions are, on average, 34.8% lower than the theoretical predictions. This




TABLE 4- 1: Numerical Results (from SIN.FOR) and Theoretical Predictions of Maximum Shoreline Changes for Different Perturbation Depths

1.5 6.1 13.8 10.9 -21.2%
2.3 3.0 3.9 1.3 -67.4%
2.3 3.8 6.2 4.7 -23.3%
3.0 4.6 4.6 4.0 -12.7%
3.0 6.1 7.3 6.6 -10.0%
3.0 7.6 9.1 :. 970
3.8 4.6 2.2 12 -47.9%
3.8 6.1 5.2 4.2 19.9
4.6 6.1 3.2 2.2 -31.1%
b.5 7.6 3.4 2.7 -21.4%
I { AVG.ERROR -34.8%
Parameters used: H=0.61m (2 ft.), T=6 s, AmpIitude=15.2 m (50 ft.), B=1.8 m (6 ft.),
A=0.115 mA/3 (0.173 ft.Al/3),TH=90deg., P=0.35, SG= 2.65
difference could have been higher or lower depending on what wave height, period, perturbation size, etc. were chosen. The values used in this investigation represented typical conditions and gave an average deviation (it was neither in the high range nor in the low range). Despite the difference in predictions, the numerical model and the theoretical predictions generally followed the same trends. The depth of limiting motion is inversely proportional to the degree of shoreline change (i.e. a smaller depth of limiting motion results in a greater shoreline change). Another discernible trend shows that the difference between the depth of limiting motion and depth of outer irregular fill is directly proportional to shoreline change (i.e. a greater difference between the depths will result in a larger shoreline displacement). These trends are consistent with the theory's concept that the shoreline change is a function of celerity.




The program involving parabolic based bathymetry, PARA.FOR, also shows the same trends concerning limiting motion and outer fill depths. An increase in the celerity ratio occurring between the outer fill and limiting motion depths will result in a greater shoreline change. However, the numerical results were an average of 60.9% lower than the theoretical predictions. In each run, the numerical model provided results smaller than the theoretical predictions. Table 4-2 shows the numerical results and theoretical predictions for varying depths. The numerical inputs for the parabolic runs were chosen to represent typical conditions, but gave a higher than average deviation from the theoretical predictions. Other, less realistic, parameters could have yielded a much lower deviation from the theoretical values.
TABLE 4- 2: Numerical Results (from PARA.FOR) and Theoretical Predictions of Maximum Shoreline Change for Different Perturbation Depths

1.5 i 5.5

-49.9%

1.5 7.6 28.2 14.2 -49.8% I
4.6 8.6 2.9 -66.5%
5.5 12.0 4.9 -58.9%
7.6 17.1 7.4 -56.7%
6.1 6.1 1.8 -70.9%
7.6 10.0 3.7 -63.3%
.5 7.6 6.4 2.0 -69.0%
ALL MtA5UREMtNI1 ARE IN Avg. Deviation -61.1%
arameters used: H=0.61 m (2 t.), T=6 s, curvature=2.5 E-5/m (7.5 E-4/ ft),B=.8 A=0.115 mA/3 (0.173 ft.Al/3),TH=90deg., P=0.35, SG= 2.65
Figure 4-4 shows the shoreline change created from the 3.1/5.5 depth combination.
In agreement with the SIN.FOR results, the shoreline forms a parabola shaped generally
like the offshore perturbation, but with lesser curvature. The curvature of the offshore
perturbation is 7.5 x 104 which results in a maximum displacement of 57.2 meters (187.5
feet) in the contours. As the figure shows, the displacement of the shoreline is 4.9 meters




(16.2 feet). The 3.1/5.5 run is representative of all the results obtained from PARA.FOR. The results of other selected runs can be found in outputs contained in Appendix B.

3.05
U
z E 0.00
0
.0)
-3.05

EQUILIBRIUM SHORELINE PREDICTED
BY NUMERICAL PROGRAM

INITIAL SHORELINE 7

0 610 1219 1829 2438
LONGSHORE DISTANCE (meters)
FIGURE 4- 4: Equilibrium Shoreline Position Resulting from Parabola Shaped Bathymetry Existing between Depths of 3.1 and 5.5 meters (10 and 18 ft.).

3048

The numerical model results involving varying depths qualitatively confirmed the trends predicted by Dean and Yoo's residual bathymetry theory. The numerical model showed that the shoreline will equilibrate in a damped form of the bathymetric perturbation. The amount of damping also appears to be a function of the celerity ratio. However, the theoretical predictions and numerical model results differ on the magnitude of that dampened form.




4.3 Numerical Model Results: the Sensitivity of Shoreline Change to Perturbation Size
The numerical models simulated several different sized perturbations of both parabola and cosine forms to determine the sensitivity of shoreline change to perturbation size. Equation (2-10) shows that the damping coefficient, or the ratio of the maximum shoreline displacement to the maximum perturbation size should remain constant despite changes in the size of the maximum perturbation. For example, given conditions dictate that the shoreline will equilibrate at 21% of the bathymetric perturbation. If the perturbation's maximum displacement is 61.0 meters (200 feet), the shoreline will reach equilibrium when its maximum change is 12.8 meters (42 feet). However, if the perturbation's maximum displacement is increased to 305 meters (1000 feet), the shoreline should not equilibrate until its maximum displacement is 64 meters (210 feet). The numerical model would be used to test sensitivity of the damping coefficient to perturbation size.
Table 4-3 and Table 4-4 compare the results from SIN.FOR and PARA.FOR, respectively, with the theoretical predictions for different sized perturbations. The results for other selected perturbation simulations are contained in Appendix B. As Table 4-3 shows, the cosine perturbations show a definite inverse relationship between the numerical reduction coefficient and perturbation size. Although the numerical damping
TABLE 4- 3: Numerical Results (from SIN.FOR) and Theoretical Predictions of Maximum Shoreline Change for Different Perturbation Sizes

U.IVU

n '-Jfl'-~ I n ,gt~

U. 1l4I

u. 3 0.

2.9
54.8
5.5
1m T vg. De-viation

-22.8%
-54.1%
-247%

U.Uuf

Ud.Uf-

U. 4U4

U, U4

u. l V

I n n I n 4 4

I n n I i nn-J

! ,

II

U.U
3.1 6.2

U.ZUZ'




coefficients produced by PARA.FOR remain constant for the smallest three perturbations, they decrease with increasing perturbation size for the five largest perturbations.
TABLE 4- 4: Numerical Results (from PARA.FOR) and Theoretical Predictions of Maximum Shoreline Change for Different Perturbation Sizes

1. t -

-29.5% 0.210 0.148
-28.9% 0.210 0.150

3.3E-7 0.76 0.16 U0.11 -28.4% 0.210 U.Ab
1.bE-6 3.81 .8 U0.49 -39.2% 0.210 .128
33-b 7.62 1.b U.98 -38.7% .21 0.129
1.6E-5 38.10 8.02 3.75 -53.2% 0.210 .098
2.5-b 57.15 12.01 4.94 -58.9% U.21 0.086
3.3-5 16.20 16.00 -64.2% U.21T 0.0h
SAvg. Deviation -37.9%

The numerical models show a sensitivity to perturbation size which is not predicted by Dean and Yoo's residual bathymetry theory. The damping coefficients generally diminish as the perturbation size grows. The theory states that the damping coefficients should remain constant for given depths of limiting motion and outer fill.
4,4 Numerical Model Results: Sensitivity of Shoreline Change to A-Factor
Since Dean and Yoo's residual bathymetry theory is a function of celerity only, a variation in the A-factor should have no influence on the maximum displacement of the shoreline. Tables 4-5 and 4-6 compare the numerical results of SIN.FOR and PARA.FOR, respectively, with the theoretical predictions for different A-factors.




TABLE 4- 5: Comparison of SIN.FOR Numerical Results and Theoretical Predictions for Different A-Factors

Parameters used: H=U.bi m (2 tt.), I=b s, UULM=2.3 m ((.b t DOOF=3.8 m (12.5 ft.), B=1.8 m (6 ft), Amplitude=15.2 m (50 ft).,TH=90 deg., P=0.35, SG= 2.65

TABLE 4- 6: Comparison of PARA.FOR Numerical Results and Theoretical Predictions for Different A-Factors

V. I '.JU 17 0- ".L 1. 1 /
0.11b 9.4 4.93 -50.5%
0.125 9.94 4.62 -53.5%
U1Ab35 9.94 4.59 -53.8%
AVG. DEVIATION -52.2% Parameters used: H=0.61 m (2 ft.), T=6 s, DOLM=3.0 m (10.0 ft.), DOOF=5.5 m (18.0 ft.), B=1.8m (6 ft.),TH=90 deg., P=0.35, SG=
2.65, curvature=2.5E-3/m (7.5 E-4/ft.)

The outputs for other selected runs are contained in Appendix B. Although variation in maximum shoreline changes exist, there is no discernible trend. The grid system of the numerical model may account for much of this variation. As the profile becomes steeper or flatter with A-factor change, the depth of each grid changes. A different depth array will alter the shoaling and refraction process as well as the location of the irregular bathymetry.




4.5 Numerical Model Results: Sensitivity of Shoreline Change to Berm Height
Berm height has no influence on celerity and therefore can not affect the shoreline displacement predicted by Equation (2-10). The cosine based bathymetry model was employed to verify this insensitivity. Table 4-7 summarizes the numerical model results and theoretical predictions.
TABLE 4- 7: Comparison of Numerical and Theoretical Results for Different Berm Heights
186.1 4.7 -22.10/
2.4 6.1 4.7 -22.1%o
All measurements in meters I[AVG. DEVIATION -22.1% Parameters used: H=0.61 m (2 ft.), T=6 s, DOLM=2.3 m (7.5 ft.),
DOOF=3.8 m (12.5 ft.), A=O.115 mAl13 (0.173 ft.Al/3),TH=90 deg.,
P=0.35, SG= 2.65, amplitude =15.2 m (50 ft.)
The model's outputs for other selected runs of this type are contained in Appendix B. The three numerical model runs are identical, confirming that the size of the shoreline change is insensitive to berm height variation.
4.6 Numerical Model Results: Sensitivity of Shoreline Change to Wave Direction
Because the models assume that there is no sediment transport in or out of the model, the model behaves like a pocket beach between two groins. This is of little consequence when investigating the effects of normally incident waves, because the initial shoreline is in equilibrium for that wave direction. However, when the waves are not normally incident, the initial shoreline is out of equilibrium. It moves to an orientation that is perpendicular to the incoming waves. This movement towards a new equilibrium




position overshadows the effects of residual bathymetry. Figure 4-5 shows the effect of an 85 degree wave passing over cosine shaped bathymetry on the shoreline. The residual
INCIDENT WAVE
DIRECTION
85 DEGREES
c851
E EQUILIBRIUM SHORELINE PREDICTED
~BY NUMERICAL PROGRAM
z
40.0
0 INITIAL SHORELINE
-6.1 I
0 61 122 183 244 305
LONGSHORE DISTANCE (meters)
FIGURE 4- 5: Equilibrium Shoreline Position Resulting from Cosine Shaped Bathymetry and 85 Degree Incident Waves
bathymetry creates the anomaly in the new shoreline (it should be straight if the bathymetric contours were straight and parallel to the shoreline), but the shoreline's position is dominated by the wave direction.
Due to the limitations of the numerical models, they do not provide general insight into the effect of residual bathymetry on non-normally incident waves. However, the




model does simulate this effect on pocket beaches. More research is needed to investigate the sensitivity of this parameter.
4.7 Numerical Simulation of the Physical Model
The time steps of SIN.FOR were modified to create SMALL.FOR (contained in Appendix A). The smaller time steps allow it to simulate the small dimensions of the physical model. The same parameters used in the physical model were input into SMALL.FOR. Table 4-8 shows the numerical model's results and compares them with the theoretical predictions.
TABLE 4- 8: Numerical Simulations of the Physical Model
Set.,195 24.7 8.4 -66.0% MTV-3.0
Sept29,199, 26.7 8.4 -68.5% 33625.6%
NOTE: ALL VALUES ARE IN cm
Parameters used: DOLM=7.6 cm, DOOF=20.3 cm, B=10.0 cm,A=0.158 TH=90 deg., P=0.35,
SG= 2.65, H=1.6 cm, T=1.5 s (9/7/95 and 9/8/95),H= 3.5 cm, T=1.25 s (9/9/95 and 9/29/95)
The maximum shoreline change obtained from the theoretical, experimental, and numerical methods do not correlate well. Although the shoreline moves to a dampened form of the bathymetric perturbation for each method, the amount of damping varies substantially. The numerical simulations continued a trend of predicting less than the theoretical. In addition, they also underpredicted the experimental results. The different results obtained from each method make it difficult to obtain any quantitative insight into the process.




4.8 Summary and Conclusions
The numerical models were developed to provide insight into the process of residual bathymetry. Different sets of parameters were input into the models to investigate the sensitivity of shoreline change to each parameter. The results showed qualitatively that shoreline change resulting from residual bathymetry is not a function of berm height or A-factor. In addition, the reduction factor was found to be sensitive to perturbation size changes (although this trend should be considered preliminary until further research is conducted). An investigation of wave height and period as well as wave direction were conducted without any useful results. Lastly, the model qualitatively confirmed Dean and Yoo's theory that the size of shoreline change is related to the celerity ratio existing between the depth of outer fill and depth of limiting motion.
The comparison of the numerical, theoretical, and experimental physical model results reached no consensus on a quantitative value involving the size of maximum shoreline change. The discrepancies existing between them make it difficult to determine which one is most accurate. More research is needed to determine the accuracy of each method.




CHAPTER 5
CASE STUDY SUMMARIES OF EROSIONAL HOT SPOTS
A study of erosional hot spots would not be complete without field data analysis. Although laboratory, analytical, and numerical models provide insight into the mechanisms of hot spots, it is how hot spots actually work in nature that is of interest. Nature seldom works as clearly as theoretical models predict. The mechanisms controlling hot spots can be difficult to discern when mixed with the fluctuations of the natural system. Since the theories concerning hot spot creation are attempting to explain real life, it makes sense to examine hot spot behavior in nature.
The seven case studies presented here show examples of the eight erosional hot spot causes discussed in Chapter 2. Obviously, some case studies may have multiple processes creating their hot spots. These case studies cover hot spots found on Captiva Island (Florida), Longboat Key (Florida), Grand Isle (Louisiana), Delray Beach (Florida), Fire Island (New York), Hilton Head Island (South Carolina), and Bald Head Island (North Carolina). Many other hot spots exist in the United States, but these seven illustrate the most researched causes.
5.1 Captiva Island. Florid
Captive Island is a barrier island approximately 8 kilometers (5 miles) long on the southwest coast of Florida. The area has generally experienced high historical erosion rates. To combat the effects of erosion, nourishment projects in 1981 and 1988 were constructed. The latest nourishment project placed approximately 1,219,000 cubic meters (1,595,000 cubic yards) of fill on 7.6 kilometers (4.7 miles) of the island's beach between




August 1988 and April 1989 (Coastal, Planning, and Engineering. 1994). Coastal Planning and Engineering, Inc. designed the project which was constructed by the Norfolk Dredging Company. On a project level scale, the nourishment has performed quite well. Only 6.4% of the fill was lost from the project in first two years. After five and a half years, 77.7% of the fill still remained in the projects limits. However, two erosional hot spots developed on the island. The most severe hot spot was located between Department of Natural Resources (DNR) monuments R96 and R98. near the center of the island. Because the area has a revetment protecting the island's main road, it is referred to as the road hot spot. The other hot spot is centered on DNR monument R106 at the southern part of Captiva Island, and is called the southern hot spot. The berm width of these locations retreated much faster than expected and more than the adjacent areas. While the advance fill of the project was expected to erode at an average of approximately 1.52 meters (5 feet) per year, the road hot spot eroded 7.28 meters (23.9 feet) per year during the first two years. The five and a half year data did not show an improvement. The southern hot spot lost 13.35 meters (43.8 feet), or 62.5%, from its design berm of 21.34 meters (70.0 feet) while the road hot spot receded a maximum of 17.98 meters (59.0 feet), or 73.8%, from its design width of 24.4 meters (80.0 feet). The percentage loss of the construction berm is dramatically higher.
The road hot spot is an example of the headland effect (see Chapter 2, section 6). As shoreline retreat threatened the island's main road around R97, a revetment was constructed to protect it. Due to the cost of the revetment, it only extended far enough to front the area in greatest jeopardy. The adjacent areas were left unprotected and free to continue their landward retreat. As the adjacent areas retreated, the revetment behaved like a groin, halting the updrift shoreline's retreat. The areas downdrift of the revetment were able to continue their retreat (in fact, these areas may have experienced higher erosion rates as the revetment deprived them of some of their updrift sand). The result of the revetment was a shoreline "bulge" in front and to the north of the revetment. Figure




5-1 illustrates the creation of this bulge. Figure 5-2 shows the shoreline of Captiva Island where the bulge is present.

STAGE II SHORELINEROAD
I
I
SW
Eventually, the shoreline receded to the revetment

STAGE III SHORELINE---\

ROAD'

sel

As the shoreline continued to I erode, the adjacent shorelines, I which were not armored, I continue to retreat. The armored section as well as the I the section updrift of it are held at their seaward position by the revetment. REVETMENT /
ACTS LIKE A GROIN, HOLDING THE UPDRIFT SHORELINE AT A LANDWARD POSITION

FIGURE 5 1: Headland Creation at the Captiva Island Road Hot Spot




ROAD REQUIREII
PROTECTION

- - EXTENSION OF REVETEMENT SHORELINE

-THE SHORELINE IN FRONT OF THE REVETEMENT IS SEAWARD
OF ITS ADJACENT AREAS

FIGURE 5 2: Shoreline Perturbation Occurring at the Captiva Island Road Hot Spot (actual planform)
Source: Coastal Planning and Engineering, 1994
The 1988/89 nourishment project was designed to create a combined design and advance berm width of 24.40 meters (80 feet) between approximately R93 and R101. Since the berm extension was applied uniformly, the fill placed on the bulge area extended seaward of its neighboring areas, creating a perturbation in the nourished shoreline. However, unlike the pre-nourishment shoreline, no revetment was present (the revetment was buried by the project) to hold the bulge at an unnatural seaward position. Without a structure to hold the bulge in position, it returned to its natural geometry. The movement of the shoreline to its natural, non-bulge position resulted in the greater berm




width loss in the R96 to R98 segment. The recession of the shoreline slowed as the perturbation returned to its natural position and became closer to equilibrium. The 7.28 m/yr. (23.9 ft./yr.) average shoreline retreat which R97 experienced in the project's first two years slowed to an average of 3.26 m/yr. (10.7 ft./yr.) after 5.5 years. In fact, 74.2% of R97's berm loss occurred in the first two years (Coastal Planning and Engineering, 1991, 1994).
The Captiva Island road hot spot behaved in a similar manner to the hypothetical situation described in Figure 2-18 of Chapter 2, section 6. The road is in the same predicament as the hotel in Figure 2-18. The headland effect keeps nourished shorelines from retaining the uniform placed width. A shoreline which was held at an unnatural seaward position before nourishment can not expect to have the same beach width in front of it as areas which were not armored.
The southern hot spot might be a result of dredge selectivity (see Chapter 2, section 1). The contractor noted that he was dredging finer than average sediments when filling this section (Coastal Planning and Engineering, 1991). In addition, as Table 5-1 and
TABLE 5 1: Post Construction Median and Mean Sand Sizes of the Captiva Island Project

I I%-OI V.,0 I I ,tI
R-92 0.33 0.5
R-97 0.28 0.38
R-102 0.31 0.5
R-107 0.24 0.39
R-112 0.17 0.24
Source: Kheen (1995)
Figure 5-3 show, the post construction medium sand size showed has a decreasing trend
as the distance from the borrow site increases (Kheen, 1995, personal communication).




0.5
0.4 .. . . . . .
E
, 0 .3 1 1 - - - -- -- -- - -
UJ 0.2
0.1
0 i i i i
R-87 R-92 R-97 R-102 R-107 R-112
SAMPUNG LOCATION (DNR MONUMENT) SOUTH-o.
-*-- MEAN GRAIN DIAMETER -. - MEDIAN GRAIN DIAMETER
FIGURE 5 3: Post Nourishment Captiva Island Sand Size Source: Kheen, 1995, personal communication
Both pieces of evidence are consistent with dredge selectivity. However, this pattern does not prove that the contractor consciously selected finer sand to pump to the most distant areas from the borrow site. The sediment selection could have been either an attempt to save operating expenses or just coincidence. None-the-less, the southern hot spot received finer sand. Equation (2-3) shows the negative effect of sand size changes on equilibrium dry beach width. Since the area received finer sand, its equilibrium dry beach width will be significantly narrower. Therefore, the greater shoreline recession occurring in this area is a result of the profile shifting to its equilibrium position (which has a narrower berm width than coarser filled areas).
Captiva Island's hot spots resulted from a headland effect and dredge selectivity. Although the project performed well on the whole, its renourishment time table will be dictated by the performance of the hot spots. Therefore, understanding and eliminating the processes which cause hot spots could greatly prolong the life of the next project.




5.2 Longboat Key- Florid

Longboat Key is another low-lying barrier island on the southwest coast of Florida. The island is approximately 16 kilometers (10 miles) long and varies from approximately 114.30 meters (375 feet) to 1.61 kilometers (I mile) in width. The shoreline is oriented along a north north west to south south east alignment which creates a littoral drift predominantly to the south. Figure 5-4 shows a map of Longboat Key.

FIGURE 5 4: Longboat Key Vicinity Map Source: Applied Technology And Management, 1993
The area has historically experienced high erosion rates. In the island's history, many erosion control methods have been utilized such as groins and jetties. The ineffectiveness




and maintenance cost of these structures led to a town funded beach nourishment project. The project which began in February, 1993 and ended during August, 1993, placed 2,393,000 cubic meters (3,130,000 cubic yards) of fill over 14.93 kilometers (9.28 miles) of shoreline. Applied Technology and Management, Inc. designed and implemented the project (Applied Technology and Management, 1993).
After project construction, a large hot spot developed near the middle of island between Sarasota county DNR monuments R2 and R 13, and is referred to as the mid-key hot spot. This area lost an average of 19.23 meters (63.1 feet) of its post nourishment beach width in the first year while the rest of the project experienced only an average retreat of 14.81 meters (48.6 feet) (Applied Technology and Management, 1993, 1995). In terms of percentage, the hot spot area had 29.8% more shoreline recession than the rest of the island. During the retreat the area lost approximately 15% of its initial placed fill, but lost 62.2% of the initial placed volume above the "-6 ft." pre-project contour (the "-6 ft" pre-project contour is generally near the post construction water line). During the first year, some stretches of the hot spot even experienced landward retreat of the waterline to approximately the pre-project position (Truitt, 1994).
At least three mechanisms combined to create the mid-key hot spot on Longboat Key: dredge selectivity, residual structure induced slope, and profile lowering in front of seawalls. Analysis of post construction sand size points to the possibility of dredge selectivity. The evidence for residual structure induced slope comes from the presence of a pre-nourishment groin field and profile slope (A-factor) data. The presence of historical seawalls in the hot spot signaled that this hot spot might have experienced profile lowering.
The ebb shoal of Longboat Pass was mined to provide fill for the area between Manatee County DNR monument R47 and Sarasota County DNR monument R13. The remainder of the project used New Pass ebb shoal for its borrow site (Stubbs,1995). As a result, the mid-key hot spot was the stretch farthest from its borrow site. If the dredge




operators knew where finer sand was located and wanted to save money, they might have selected finer sand to fill the most distant area, the mid-key hot spot (the reasoning is explained in Chapter 2, section 1).
Sand analysis revealed that the post construction sand size was indeed finer in the hot spot area than elsewhere in the project. Table 5-2 and Figure 5-5 show the average sand size distribution for the hot spot and non-hot spot areas (Truitt, 1994). Only sand samples above the "-6" ft. contour (sand beneath this elevation would be sorted by the natural processes) were used in the calculation.
TABLE 5 2: Comparison of the Cumulative Distribution of the Average Grain Size Found in the Hot Spot and Non-Hot Spot Sections of Longboat Key
Source: Truitt, 1994
100
90 _80 ____ 80 _.........
70
60
"I
o 50
z
L_ 40
30 20
10 -_12.5 9.5 2.0 1.0 0.5 0.355 0.18 0.125 0.075 mm mm mm mm mm mm mm mm mm
GRAIN SIZE
HOT SPOT SECTIONS ...... NON-HOT SPOT SECTIONS FIGURE 5 5: Cumulative Sand Size Distribution for the Hot Spot and Non-Hot Spot Sections of Longboat Key Source: Truitt, 1994




m (15 ft.) 1 0.113 1 0.102 0.098 0.095 b.49 M (16 tt.) M I b MUb 0.099 U.U9(
Source: Coastal Planning And Engineering, 1995, personal communication
The A-factors calculated from 1993 and 1994 data are higher in the hot spot areas than in the non-hot spot areas. This is consistent with the premise that the groins increased the

Perhaps a better method to compare the sand size differences is to examine the percent finer than the native for each area. The hot spot contained sand which was 68% finer than the native 0.2 mm while the non-hot spot areas had only 54% finer than the native (Truitt, 1994). It is clear that the hot spot area received finer sand. However, it is impossible to determine if this was a random act or a result of dredge selectivity. In addition, the size difference was not extreme. It is doubtful that the area would have developed into a hot spot on this size differential alone although it certainly contributed to the poor performance of the area.
Another contributing factor was the removal of the groin field present at the mid-key hot spot. The residual structure-induced slope (see Chapter 2, section 2) of the area moved to its natural position after groin removal. This movement to a natural, flatter profile resulted in shoreline retreat. Examination of the A-factors found in hot spot and non-hot spot areas show the effect of this process. The A-factor for 1993's average hot spot profile, 1993's average non-hot spot profile, 1994's average hot spot profile, and 1994's average non-hot spot profile were calculated at depths of 3.66, 4.57, and 5.49 meters (12, 15, and 18 feet). The results of these calculations are contained in Table 5-3 (Coastal Planning and Engineering, 1995, personal communication). TABLE 5 3: Comparison of Hot Spot and Non-Hot Spot A-Factors on Longboat Key
DEPTH
USED FOR
i
CALCULATION 3.66 m (12 tt.)




slope in the hot spot area. In addition, the A-factor of the average hot spot profile decreased from 8.7 % to 9.6% (depending on which contour is chosen for the calculation) between the two surveys while the non-hot spot A-factor reduced by only 2.7% (the result was the same for each contour). The fact that both profiles became flatter during the time period should not be surprising. The beach was still equilibrating from the unnaturally steep post nourishment profile. However, the hot spot area flattened at a rate almost three times as fast. This relatively higher flattening rate is reflective of the groin field profile flattening to its natural, flatter shape and an associated loss in beach width after the groin removal.
Yet another contributing factor to the creation of the mid-key hot spot might have been profile lowering in front of seawalls (see Chapter 2, section 6). Many seawalls line the mid-key hot spot which, like most of Longboat Key, is an area with high historical erosion rates. As the profiles retreated due to erosion, some of them may have encountered seawalls and became lowered in a manner similar to the situation depicted in Figure 2-16. Lowered profiles sporadically placed in the area might decrease the performance of the entire area. Further research of this phenomenon is necessary to confirm the presence of this erosional hot spot cause at Longboat Key. However, the hot spot does contain more seawalls than any other stretch of the island.
In summary, the mid-key hot spot may have been a combined result of dredge selectivity (whether consciously or unconsciously), residual structure induced slope, and profile lowering in front of seawalls. Although the Longboat project as a whole did not perform exceptionally well, this hot spot has created the need for a hot spot maintenance project only two years after the original nourishment. A better understanding of hot spots might have prevented the need for the maintenance project as well as the negative public perception created by the performance of the beach nourishment project.




5.3 Grand Isle. Louisiana
Grand Isle is a low-lying barrier island located in the Gulf of Mexico. The island is approximately 96.6 kilometers (60 miles) from New Orleans and is approximately 12.1 kilometers (7.5 miles) long and 1219 meters (4000 feet) wide. With natural ground elevations ranging from 0.91 to 1.52 meters (3 to 5 feet), Grand Isle historically experienced significant damage from hurricanes. This need for storm protection and the presence of background erosion led to a federally funded nourishment project. Although the project was federally authorized in 1966, construction of the project did not begin until 1983. When the Grand Isle project was completed in 1984, 4.2 million cubic meters (5.5 million cubic yards) of fill had been placed over the full 12.1 kilometers (7.5 miles) of the island's shoreline. Most of the fill was mined from an offshore borrow source 914 meters (3,000 feet) from the approximate midpoint of the island. The ends of the 2,743 meter (9,000 feet) (longshore) by 457 meter (1,500 feet) (cross shore) borrow site were mined more heavily than the middle, leaving a dumbbell shaped pit whose centroids were 1,372 meters (4,500 feet) apart. The remainder of the fill came from a source off the eastern end of the island (Combe and Soileau, 1987).
In the months following completion of the project, a hot-spot-cold-spot pattern developed behind the main borrow site. The pattern had two protruding cuspate features with recessed areas in the middle and adjacent to them. The sand losses from the recessed areas amounted to 8% of the project volume. Figure 5-6 shows the hot-spotcold-spot area at Grande Isle (Combe and Soileau, 1987).
The cuspate features and their accompanying recessed areas resulted from borrow pit effects (see Chapter 2, section 3). The two heavily mined areas of the borrow site effectively acted like two separate pits which changed the wave field in their lee. Aerial photographs showed the sheltering effect of the borrow pit, providing a clear indication that the borrow pits were affecting the wave pattern of the area (Combe and Soileau,




1987). The lirmantion of these pits fit the pattern described by I lorikawa et al. in their 1976 paper about the effect on a shoreline behind a dredged hole.

HOT SPOT SAi
7 [2, ,

FIGURE 5 6: Hot-Spot-Cold-Spot Pattern at Grand Isle, December 1986
Source: Combe and Soileau, 1987




In this case, Grand Isle had two adjacent dredged holes which caused an area consisting of three hot spots separated by two cold spots. The lower set-up occurring behind the heavily mined areas may have created a circulation between the hot and cold spots which carried sediment away from the hot spot to the cold spots.
Grand Isle is a case study which generally follows theory. The hot and cold spots are located very close to where Horikawa et al. would have predicted them. If hot spots had been better understood or more of a concern (Horikawa et al. published their findings five years before the Grand Isle project was constructed) the whole hot-spot-cold-spot system could have been avoided or diminished with wiser borrow site selection or management.
5.4 Delray Beach. Florida
Delray Beach lies on Florida's southeast coast on the barrier beach stretching between Boca Raton Inlet and South Lake Worth Inlet. In response to the high historical erosion rates in the area, a nourishment program was begun. The first nourishment placed 1,249,675 cubic meters (1,634,513 cubic yards) of sand on the 4.4 kilometers (2.7 miles) of Delray Beach's shoreline in 1973. In 1978, the area underwent another nourishment which placed 536,156 cubic meters (701,266 cubic yards) of sand on two stretches of the city's shoreline. The whole shoreline was renourished again in 1984 when 994,000 cubic meters (1,300,000 cubic yards) were placed over the project's 4.4 kilometers (2.7 miles). The latest nourishment in the program was constructed in 1992 and again covered the entire Delray Beach shoreline as well. All of the borrow sites were located offshore of the project in approximately 10.7 to 18.3 meters (35 to 60 feet) of water.
An erosional hot spot existed before the nourishment program was initiated. It was centered adjacent to Atlantic Avenue around Palm Beach County DNR monument Ri 180. The beach in this area was narrower and more adversely affected by storms than its




adjacent areas. After the nourishment program started in 1973, the hot spot migrated to the south about 1.2 kilometers (0.75 miles) and appeared to visibly worsen. In an attempt to control the hot spot, extra fill was added to the area in subsequent projects. The added fill seemed to have little effect as erosion rates have remained fairly constant over the history of the program. The hot spot seems to lose a greater percentage of fill when larger amounts are placed on it, producing diminishing returns.
It has been suggested that the Delray Beach hot spot is a result of three bathymnetric influences: a reef gap, a no dredge zone, and borrow pits. First, the hot spot is located in the lee of a gap in the offshore reef. The reef gap might cause a wave field very similar to a gap in a breakwater (see Chapter 2, section 2.4). The resulting higher level of wave transmission could adversely affect the shoreline in the gap's lee. Another bathymetric influence is the presence of a no dredge zone around an outfall pipeline. The no dredge zone is located directly offshore of RI 80 or Atlantic Ave. Because the area lies between borrow pits (the third bathymetric influence), it acts like a shoal in that it focuses wave energy in its lee, leaving areas of lower wave energy behind the borrow pits. The three effects combine to create a hot spot (Gravens, 1995). However, no conclusive studies have been conducted on the cause of Delray Beach's hot spot. The hypothesis described here is only speculation until further research is conducted.
5.5 Fire Island. New York
Fire Island is an elongated, narrow barrier island off of New York's Long Island. Its shoreline is quite dynamic and suffers from man-made as well as natural erosion. The man-made erosion, which may be responsible for 50% to 67% of the total erosion, results mainly from sand capture at Moriches Inlet, the Westhampton Groins, and Shinnecock Inlet. The positive longshore transport gradient, sea level rise, and sand lost from the system due to breaches are causes of the area's natural erosion (Campbell and Vietri, 1994).




GREAT SOUTH BAY
FAIR HARBOR
FIRE ISLAND SHORELINE BEHIND THE BAR
SHORELINE-,""",,, BREAK IS LANDWARD OF ITS
BAR ADJACENT AREAS
BAR BREAK BAR
ATLANTIC OCEAN
FIGURE 5 7: Fire Island Bar Break
Although the whole Fire Island area is generally erosive, some areas experience a much higher shoreline retreat than others. One of these areas is centered in the Fair Harbour area where a bar break severely eroded the beach in its lee (Dean, 1995, personal communication). Figure 5-7 presents a schematic of the shoreline and bar position in the bar break vicinity. The mechanisms behind the bar break are unknown. However, the effects are easily seen in Figure 5-7. Because of the dynamic nature of bar breaks, this hot spot may be temporary, lasting only as long as the bar break.
5.6 Hilton Head Island- South Carolin
Hilton Head Island is a large, low lying barrier island on South Carolina's Atlantic coast. The island, which is approximately 21 kilometers (13 miles) long and 8 kilometers (5 miles) wide at its widest point, is located between Savannah, Georgia and Beaufort, South Carolina. Highly dynamic shoals surround the island, heavily influencing the coastal processes of the area. High erosion rates have plagued the island throughout its developed history.




In response to the erosion a nourishment project was constructed in 1990. The project, which was engineered by Olsen and Associates, placed 1,786,000 cubic meters (2,338,000 cubic yards) of sand over approximately 10,670 meters (35,000 feet) of shoreline, stretching from mid-Forest Beach to Port Royal Plantation (Bodge, Olsen, and Creed, 1993). Although the project as a whole performed only slightly worse than expected, one area behaved significantly worse than predicted. Because profile 19 which is located at the Hyatt Hotel in the Palmetto Dunes resort performed worse than its adjacent areas and predictions, it has been labeled a hot spot. Profile 19 was the only profile of the whole project whose 26 month mean high water location had retreated past its pre-project position. In fact, it was roughly 9.1 meters (30 feet) landward of its preconstruction location after 26 months. This location has retreated approximately 12.2 meters (40 feet) further than any other profile and 36.6 meters (120 feet) more than the profile with the minimum retreat.
The Hyatt hot spot was caused by at least three processes. The profile's beachfront acted as a headland due to its seaward location (see Chapter 2, section 7). In addition, the seawall holding the area at its seaward position caused profile lowering (see Chapter 2, section 6). Another factor in the Hyatt hot spot was the effect of placing fill mechanically between hydraulically filled areas (see Chapter 2, section 5). The three combined to dramatically decrease the performance of the nourishment in this area (Bodge, Olsen, and Creed, 1993).
Parts of the development constructed in this area were built on reclaimed oceanfront land. They were built seaward of the historical shoreline and armored with a seawall to keep their shoreline pinned at this seaward location (Bodge, Olsen, and Creed, 1993). This created a headland as this area protruded seaward more than adjacent shorelines. The adjacent shorelines, which had no seawall to pin them, continued to retreat in the face of erosion, increasing the protrusion of the armored areas. When the nourishment material was placed on the Hyatt hot spot, it filled a construction template containing




roughly the same construction width as its adjacent areas. Therefore, profile 19's post nourishment shoreline was seaward of its adjacent areas. The resulting perturbation retreated to its natural orientation without the seawall to hold it in its unnatural shape. This retreat to equilibrium explains part of the poor performance at the Hyatt hot spot.
Accompanying the headland effect was profile lowering. When the area was constructed seaward of the historical shoreline and held there by a seawall, the profile became truncated with a virtual origin (see Figure 2-16). As the area continued to erode, the position of the water level was not able to retreat. However, the virtual origin continued its landward movement as the profile lowered. Put simply, since the erosion could not create shoreline retreat, it took sand away from the profile, lowering it in the process. Olsen and Associates noticed this process which they termed "over-erosion." In the design, they allocated additional volume to be placed in this area as well as all armored sections of the beach. However, two years passed between the design and construction of the project. During this time the profile was ftirther lowered, creating the need for additional placed volume to create the desired equilibrium dry beach extension. Since the area did not receive the additional needed volume to compensate for this profile lowering, the equilibrium beach width was smaller than predicted (Bodge, Olsen, and Creed, 1993). Profile lowering or "over-erosion" contributed to create the Hyatt hot spot.
Another contributor to profile 19's poor performance may have been the use of mechanically placed fill in the area. The construction templates for the project were designed to provide a total of 1,556,900 cubic meters (2,036,300 cubic yards) of fill to the project. Because the contractor was unable to meet the construction templates with hydraulically placed fill, extra-filling occurred. The project received 1,786,000 cubic meters (2,338,000 cubic yards) of sand, approximately 15% more than the construction templates called for. However, profile 19's fill was placed mechanically to the design templates specifications. Unlike the neighboring areas, the Hyatt hot spot received no