• TABLE OF CONTENTS
HIDE
 Front Cover
 Title Page
 Acknowledgement
 Table of Contents
 List of Tables
 List of Figures
 Abstract
 Introduction
 Theory
 Beach nourishment monitoring at...
 Laboratory experiments
 Analysis of laboratory results
 Summary and conclusion
 Appendix A. Profile data from the...
 Appendix B. Measured and adjusted...
 Appendix C. Comparison of the 1991...
 Reference
 Biographical sketch














Group Title: UFLCOEL-98007
Title: The effects of sand grain size and fill placement geometry on beach nourishment performance
CITATION THUMBNAILS PAGE IMAGE ZOOMABLE
Full Citation
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Permanent Link: http://ufdc.ufl.edu/UF00091085/00001
 Material Information
Title: The effects of sand grain size and fill placement geometry on beach nourishment performance
Series Title: UFLCOEL-98007
Physical Description: xi, 134 leaves : ill. ; 28 cm.
Language: English
Creator: Donohue, Kerry Anne Beatrice, 1970-
University of Florida -- Coastal and Oceanographic Engineering Dept
Publisher: Coastal & Oceanographic Engineering Dept.
Place of Publication: Gainesville Fla
Publication Date: 1998
 Subjects
Subject: Beach nourishment -- Florida   ( lcsh )
Coast changes -- Florida   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Thesis: Thesis (M.S.)--University of Florida, 1998.
Bibliography: Includes bibliographical references (leaves 128-133).
Statement of Responsibility: by Kerry Anne Beatrice Donohue.
 Record Information
Bibliographic ID: UF00091085
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 41524965

Table of Contents
    Front Cover
        Front Cover
    Title Page
        Page i
    Acknowledgement
        Page ii
    Table of Contents
        Page iii
        Page iv
    List of Tables
        Page v
    List of Figures
        Page vi
        Page vii
        Page viii
        Page ix
    Abstract
        Page x
        Page xi
    Introduction
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
        Page 7
        Page 8
    Theory
        Page 9
        Page 10
        Page 11
        Page 12
        Page 13
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
    Beach nourishment monitoring at St. Augustine Beach
        Page 19
        Page 20
        Page 21
        Page 22
        Page 23
        Page 24
        Page 25
        Page 26
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        Page 37
        Page 38
        Page 39
        Page 40
        Page 41
        Page 42
        Page 43
    Laboratory experiments
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
        Page 50
        Page 51
        Page 52
    Analysis of laboratory results
        Page 53
        Page 54
        Page 55
        Page 56
        Page 57
        Page 58
        Page 59
        Page 60
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        Page 75
        Page 76
        Page 77
        Page 78
        Page 79
        Page 80
        Page 81
        Page 82
        Page 83
        Page 84
        Page 85
    Summary and conclusion
        Page 86
        Page 87
        Page 88
        Page 89
        Page 90
    Appendix A. Profile data from the South St. Augustine Beach (SSAB) site
        Page 91
        Page 92
        Page 93
        Page 94
        Page 95
        Page 96
        Page 97
    Appendix B. Measured and adjusted volume change, total volume density and planform change from the laboratory experiments
        Page 98
        Page 99
        Page 100
        Page 101
        Page 102
        Page 103
        Page 104
        Page 105
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        Page 113
        Page 114
        Page 115
        Page 116
        Page 117
        Page 118
        Page 119
    Appendix C. Comparison of the 1991 kamphuis sediment transport equation and the measured results from the laboratory experiments
        Page 120
        Page 121
        Page 122
        Page 123
        Page 124
        Page 125
        Page 126
        Page 127
    Reference
        Page 128
        Page 129
        Page 130
        Page 131
        Page 132
        Page 133
    Biographical sketch
        Page 134
Full Text




UFL/COEL-98/007


THE EFFECTS OF SAND GRAIN SIZE AND FILL
PLACEMENT GEOMETRY ON BEACH NOURISHMENT
PERFORMANCE





by



Kerry Anne Beatrice Donohue




Thesis


1998














THE EFFECTS OF SAND GRAIN SIZE AND FILL PLACEMENT GEOMETRY ON
BEACH NOURISHMENT PERFORMANCE












By

KERRY ANNE BEATRICE DONOHUE


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


1998















ACKNOWLEDGMENTS


I accepted a research assistantship in January, 1996, not knowing that I was about to

embark on a journey with a truly outstanding individual. I would like to express my sincere

thanks to my advisor, Dr. Robert G. Dean, for sharing his enthusiasm for learning and

discovering every aspect of our physical world and beyond. No question was a stupid question,

while no problem was unapproachable. I would also like to thank Dr. Ashish J. Mehta and Dr.

Daniel Hanes for serving on my committee. The staff at the Coastal and Oceanographic

Engineering Laboratory, especially Sidney Schofield and Jim Joiner, were an invaluable

resource. They always responded above and beyond their call of duty. Becky, Helen, Subarna,

Lucy, Sandra and Cynthia also made the road smoother.

I express my gratitude to the Florida Department of Environmental Protection, St. Johns

County, the University of Florida, and the American Association of University Women for their

financial support. I would also like to thank Dr. Gladys Humphreys, a St. Augustine Beach

resident, for her hospitality and unwavering support of beach preservation technology.

Without the help and companionship of my fellow students, I would still be on the

beach, counting grains of sand--Gus, Pete, Al, Jie, Wendy, Carrie, Adam, Greg and Roberto.

My thanks go to Hugo for being my "resident expert" and to Susan and Jamie for their editing

skills and family support. A special thanks to "Mr. Fluids" (Joel) who not only helped in the

field and laboratory, but always lifted my spirit. Lastly, I would like to thank my parents and

siblings for instilling in me the faith and strength needed to pursue my dreams.















TABLE OF CONTENTS



ACKNOWLEDGMENTS ............................................. ii

LIST OF TABLES ...................................................... v

LIST OF FIGURES ..................................................... vi

ABSTRACT ........................................................... x

CHAPTERS

1 INTRODUCTION .................................................. 1

1.1 General Description .............................................. 1
1.2 Previous Studies of Beach Nourishment Evolution ...................... 2
1.3 Predictions of Beach Nourishment Performance ......................... 4
1.4 Quantifying Large Scale Sediment Transport ........................... 6
1.5 Scope of This Thesis ............................................. 7

2 THEORY .......................................................... 9

2.1 Governing Equations ............................................. 9
2.2 Analytical Solutions ............................................. 11
2.3 Numerical Solutions ............................................. 15
2.4 Additional Sediment Transport Equations ............................. 17

3 BEACH NOURISHMENT MONITORING AT ST. AUGUSTINE BEACH ..... 19

3.1 Introduction ....................................... ......... 19
3.2 Background .................................................... 20
3.3 Monitoring Results .................. ............................28
3.3.1 Survey Results from the SSAB Site ...................... 30
3.3.2 Survey Results from the North Site, Anastasia State Park ....... 37
3.4 Sediment Analysis .............................................. 40
3.5 Comparison of the SSAB Site With Theory ...........................42









4 LABORATORY EXPERIMENTS ................................... 44

4.1 Introduction ................................................ .44
4.2 Experimental Equiptment ......................................... 44
4.3 Test Preparation ................................................. 47
4.4 Experimental Procedure .......................................... 50
4.5 Results ..................................................... .. 50

5 ANALYSIS OF LABORATORY RESULTS ........................... 53

5.1 Determination of the Sediment Transport Coefficient, K ................. 53
5.1.1 Proportion Remaining over Time Using the Rectangular Diffusion
Equation Solution ................................... 53
5.1.2 Tapered End Solution ............... ................. 56
5.1.3 Variance ............................................ 70
5.1.4 The DNRBS Model .................................... 71
5.2 Summary of Results ............................................. 73
5.3 Comparison With Previous Investigators ............................. 77
5.4 Source of Error ..................................... ........... .80
5.5 Other Sediment Transport Equations ............................... 84

6 SUMMARY AND CONCLUSION ................................... 86

6.1 Summary .................................................... 86
6.2 Conclusions ................................................... 87
6.3 Suggestions for Future Research ................................... 88

APPENDICES

A PROFILE DATA FROM THE SOUTH ST. AUGUSTINE BEACH (SSAB) SITE 91

B MEASURED AND ADJUSTED VOLUME CHANGE, TOTAL VOLUME
DENSITY AND PLANFORM CHANGE FROM THE LABORATORY
EXPERIMENTS ...................................................98

C COMPARISON OF THE 1991 KAMPHUIS SEDIMENT TRANSPORT
EQUATION AND THE MEASURED RESULTS FROM THE LABORATORY
EXPERIMENT..................................................120

LIST OF REFERENCES ............................................... 128

BIOGRAPHICAL SKETCH ......................................... 134














LIST OF TABLES


Table page

3.1 Major Storms and Hurricanes in St. Augustine Region ..................... 27

4.1 Laboratory W ave Characteristics ............... .................... 45

4.2 Summary of Test Characteristics ................................... 51

5.1 Summary of the Even and Odd Analysis .............................. 69

5.2 Summary of the Sediment Transport Coefficients Using the Various Methods ... 75

5.3 Summary of the Previous Sediment Transport Laboratory Studies ............ 78

5.4 Summary of Adjustments in the Volume Change Analysis to Conserve Sand ... 82













LIST OF FIGURES


Figure Page


1.1 Relationship Between the Immersed Weight Longshore Transport Rate and
the Longshore Component of Wave Energy Flux ........................ 6

2.1 Definition of Terms Used in the Tapered Ends Solution (Walton, 1993) .... 13

2.2 Definition of Terms Used in the DNRBS Model Derivation .............. 16

3.1 Aerial Photograph of St. Augustine Beach, Including the 1996 Nourishment
Sites ..................................................... 21

3.2 Aerial Photograph of St. Augustine Inlet in 1942 ....................... 22

3.3 Aerial Photograph of St. Augustine Inlet in 1947 ....................... 23

3.4 Aerial Photograph of St. Augustine Inlet in 1962 .................. .... 24

3.5 Monument Locations ................ .......................... 26

3.6 Historical Erosion Rates at the Nourishment Sites ...................... 27

3.7 Profile Locations ............................................... 29

3.8 Monument R147, Center of the South Site of the 1996 St. Augustine
Beach Nourishment; a) 1987; b) March, 1996 and c) May, 1997 ........... 31

3.9 Monument R147 Profiles, in the Center of the SSAB Site; a) All
Survey Dates; b) Selected Dates Marked With Asterisks ................ 32

3.10 Monument R145 Profiles, Located 250 m North of the SSAB Site ........ 32

3.11 Monument R149 Profiles, Located 300 m South of the SSAB Site ........ 33

3.12 Total Volume of Sand Above NGVD at the SSAB Site Versus Time ....... 34









Figure Page

3.13 Record of Cumulative Sand Added at the SSAB Site by the Dredge
Operators .................................................... 35

3.14 Additional Beach Width at the SSAB Site ............................ 37

3.15 Accumulation of Sand Added above NGVD Since the Pre-Project Survey, or
the Density of Added Sand Volume at the SSAB Site ................... 38

3.16 Total Volume of Sand Above NGVD Versus Time at the ASP Site ........ 39

3.17 Profiles atM onumentR141 ....................................... 39

3.18 Sand Size Distributions of the Native and Fill Sands for the 1996 Beach
Nourishment at the SSAB Site ............... ................... 41

3.19 Distribution of the Mean Diameter of Sand Over the Length of the SSAB Site
Versus Time ................ ................................ 41

3.20 Percent Remaining Versus Time Using the Pelnard-Considere Equation and the
CERC Sediment Transport Equation .............................. 42

4.1 Wave Basin Layout and Profile Lines ............................ 45

4.2 Particle Size Distributions for Sands Used in the Laboratory Experiments ... 48

4.3 Initial Fill Placement Geometry ............... .................. 49

5.1 Percent Remaining in Placement Area Versus Time for the Measured Data;
a) Shape A; b) Shape B .......................................... 54

5.2 Percent Remaining in Placement Area Versus Time Using the Best Fit K Value
and the Rectangular Diffusion Equation Solution; a) Shape A; b) Shape B .. 54

5.3 Comparison of the Sediment Transport Coefficient and the Sand Diameter
Using the Rectangular Planform Solution ............................ 55

5.4 Test 1 -Fine Sand, Shape A, After 30, 60, and 150 Minutes of Waves; a) Even
and Odd Analysis; b) Best Fit Tapered Ends Solution for the Even Analysis. 58









Figure Page

5.5 Test 2 -Medium Sand, Shape A, After 30, 60, and 150 Minutes of Waves; a)
Even and Odd Analysis; b) Best Fit Tapered Ends Solution for the Even
Analysis. ..................................................... 60

5.6 Test 3a -Coarse Sand, Shape A, After 30, 60, and 150 Minutes of Waves; a)
Even and Odd Analysis; b) Best Fit Tapered Ends Solution for the Even
Analysis....................................................... 61

5.7 Test 3b -Coarse Sand, Shape A, After 30, 60, and 150 Minutes of Waves; a)
Even and Odd Analysis; b) Best Fit Tapered Ends Solution for the Even
Analysis....................................................... 63

5.8 Test 4 -Fine Sand, Shape B, After 30, 60, and 150 Minutes of Waves; a)
Even and Odd Analysis; b) Best Fit Tapered Ends Solution for the Even
Analysis....................................................... 64

5.9 Test 5 -Medium Sand, Shape B, After 30, 60, and 150 Minutes of Waves; a)
Even and Odd Analysis; b) Best Fit Tapered Ends Solution for the Even
Analysis....................................................... 65

5.10 Test 6 -Fine Sand, Shape B, After 30, 60, and 150 Minutes of Waves; a)
Even and Odd Analysis; b) Best Fit Tapered Ends Solution for the Even
Analysis....................................................... 67

5.11 Comparison of the Sediment Transport Coefficient and the Sand Diameter
for the Tapered Ends Solution ................................... 68

5.12 Regions of Accretion and Erosion Used in Table 5.1 .................... 69

5.13 Comparison of the Sediment Transport Coefficient and the Sand Diameter
Using the Variance M ethod ....................................... 70

5.14 Computational Scheme Used in the DNRBS Numerical Model ........... 72

5.15 Best Fit K Values Using the DNRBS Model; a) Shape A Results; b) Shape B
Results ....................................................... 74

5.16 Comparison of the Sediment Transport Coefficient and the Sand Diameter
Generated by the DNRBS Model ................................. 75









Figure


Page


5.17 The Sediment Transport Coefficients Computed Using the Various Methods,
for Shape A ................................................... 76

5.18 The Sediment Transport Coefficients Computed Using the Various Methods,
for Shape B ................................................... 76

5.19 Sediment Transport Coefficients (K) from Previous Laboratory Studies Versus
Sand Diameter, Including the Present Study ........................... 78

5.20 The Amount of Sediment Transport Coefficient Laboratory Tests for Each Sand
Size ........................................................79

5.21 Bathymetry of the Entire Sand Wedge in the Wave Basin ................ 83














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


THE EFFECTS OF SAND GRAIN SIZE AND FILL PLACEMENT GEOMETRY ON
BEACH NOURISHMENT PERFORMANCE

By

Kerry Anne Beatrice Donohue

May, 1998


Chairperson: Dr. Robert G. Dean
Major Department: Coastal and Oceanographic Engineering

St. Augustine Beach, located on the Atlantic Coast of North Florida, 5-8 km

south of St. Augustine Inlet, received its first on-shore beach nourishment in 1996 in

conjunction with a U.S. Army Corps of Engineer (USACE) maintenance dredging project

of the inlet's navigational channel. The nourishment site has experienced erosional

trends since the inlet was relocated and stabilized in 1941. Although two sites were

nourished, the southern site received 112,000 m3, the bulk of the sand and was monitored

for a two year period.

The evolution of the southern site nourishment has already far exceeded its

expected lifespan calculated using conventional design and prediction methodologies.

The characteristics believed to have increased the longevity were 1) the use of fill sand








considerably coarser than the native and 2) the placement of the limited volume of sand

high on the nourished profile. A review of existing studies addressing the influence of

sand particle size is included, as well as the results of laboratory experiments which

tested existing theory while varying the fill sand size and the initial fill sand placement

geometry. Four methods which involved diffusive theory were used to analyze the

experiments. The results revealed that when the fill sand is initially placed high on the

berm, larger sand sizes are somewhat less transportable, and that placing the sand high on

the berm causes the nourishment to be less of a perturbation, thus reducing sediment

transport. When the fill sand is initially placed farther into the surfzone, the fill sand and

native sand mix. Thus, the results preclude definitive conclusions. The four methods of

analysis produced a range of results. The methods varied the initial boundary conditions

and the inclusion or exclusion of refraction effects around the nourishment. The range of

results indicates that beach nourishment evolution prediction techniques are sensitive to

initial conditions and refraction effects.














CHAPTER 1
INTRODUCTION



1.1 General Description



As the 20th Century comes to an end, the coastlines of the world have felt the stress

placed on our environment by an increasing population. In the United States alone, 85% of

the population lives within 200 miles from a major body of water. Thus, land loss in this

narrow strip has magnified consequences. In addition, there appears to be a conflict, real or

perceived, between natural coastal processes and shoreline development, which may render

a coast unstable. Beach nourishment, the process of advancing a shoreline seaward by

placing sand in the nearshore region, has become a popular solution for stabilizing a

shoreline. The process has been favored because in contrast to groins, breakwaters or other

hard structures, it has a positive effect on the adjacent beaches. Beach nourishment directly

addresses the cause of beach erosion by adding sand into a sand deficient system. However,

this solution does come with a hefty price tag. The sediment transport associated with beach

nourishment evolution theory has only been studied rigorously in the last three decades. A

more lasting investment could be achieved by a better understanding of the processes

involved.








2

St. Augustine Beach was a candidate for a beach nourishment project in 1996.

Located on the Atlantic coast in north Florida, a 842 m stretch of beach was nourished with

120,000 m3 of sand that was dredged from the inlet 6 km to the north. Despite the high sand

loss rates that are typically expected from projects of such short length, much of the sand

placed remained in its initial location. Two hypotheses for the under prediction of the

longevity of this beach nourishment were 1) the fill sand diameter was considerably larger

than the native sand diameter and thus more stable, and 2) the sand was placed high on the

beach profile geometry, reducing its accessibility to the destructive forces of the waves.

However, further explanation is needed to test the effects of these two possibilities. This

issue is explored in this study.


1.2 Previous Studies of Beach Nourishment Evolution



The first record of a beach nourishment project was in 1926 on Coney Island, NY.

In the 1930's, beach nourishment began to be recognized as a potential remedy to chronic

erosion problems, although most projects were not monitored adequately. A complete

summary of all beach nourishment projects will not be presented here, as the list would be

vast, and probably incomplete. However, significant monitored projects which address sand

size and sand placement profile location will be discussed.

Watts (1956) monitored a 1.95 million cubic meters (MCM) nourishment in Ocean

City, MD. His data indicated that 95% of the sand left the initial area in 2 years. He

attributed the use of fine grain sand fill as the cause of the accelerated loss rate. Perdikis








3

(1961) investigated 79 beach fill projects in the northeast United States. Many sites had

much higher erosion rates after nourishment than before nourishment, and many of these

sites had fill sand that was finer than the native sand. Berg and Duane (1968) concluded

from their study of a small scale beach nourishment of coarser than native sand, that coarser

than native sands are more stable than finer grained sands, and erode more slowly. In recent

decades, the beneficial effects of larger fill sand diameters on the project's longevity have

become more widely accepted, although the exact quantitative and qualitative effects of grain

size are still under investigation.

Hall and Herron (1950) monitored a nourishment in Long Branch, NJ, where 460,000

m3 of sand was placed offshore, at a water depth of 11.5 m. Similar underwater berm

nourishments took place in 1935 at Santa Barbara, CA, and in 1942 at Atlantic City, NJ. The

three projects did not identify any significant onshore movement of the sand mounds,

concluding that sand should be placed at shallower depths. More recently, the 1989-1990

Perdido Key Beach Nourishment involved the placement of 3 MCM in 6 m of water. A

1997 survey revealed that the centroid of the mound did not significantly move either

seaward or landward (Browder and Dean, 1997), although some spreading occurred. Hands

and Allison (1991) studied the migration of 11 nearshore sand mounds in depths ranging

from 2.1-21.3 m. Their general conclusion was that sand placed at shallower depths had a

greater chance of moving shoreward than nourishments placed in greater depths. Again, the

beneficial results of placing fill sand high on the beach profile is an accepted idea, but there

is a lack of quantitatively defining these benefits. It should be noted that the higher sand is

pumped on to a beach, the greater the cost. Additionally, for projects involving a large








4

placement density, it is not feasible to place a large proportion of the sand high on the profile,

especially if the beach is to be used for recreation. By quantifying of the beneficial effects

of sand placement location on project longevity, better design decisions can result.


1.3 Predictions of Beach Nourishment Performance



A number of investigators have attempted to predict the performance of beach

nourishment projects. Krumbein and James (1965) and Dean (1974) proposed quantitative

approaches of assessing the quality of nourishment material relative to the native material.

However, not all parameters critical to the project's performance are addressed in these

procedures. Pelnard-Considere (1956) developed the following one-line analytical approach

to describe beach nourishment evolution as a diffusive process:




y =G 2y (1.1)
at ax2




where


G = f(K,Hb,g,hb,s,p,,h.,B) (1.2)



where y is the cross-shore beach coordinate, x is the longshore coordinate, t is time, G is the

diffusivity coefficient, K is the sediment transport coefficient, H, is the significant breaking

wave height, g is the gravitational acceleration, hb is the depth of water at breaking, s is the








5

specific gravity of quartz sand (assumed to be 2.65), p is the porosity of the sand (assumed

to be 0.35), h. is the depth of closure, and B is the Berm height. Dean (1983) showed through

Equations 1.1 and 1.2 that in the absence of background erosion, the relationship between

the longevity (t) of the sand in its initial area and Ib,, K, and the length of the nourishment,

1, is

12
t a (1.3)
H 2.5 K




The sediment transport coefficient, K, relates the immersed weight sediment transport rate,

I, and the longshore energy flux factor, Ps,


I= KPs, (1.4)


which was developed by Inman and Bagnold in 1963. The 1974 and 1984 United States

Army Corps of Engineer's (USACE) Shore Protection Manual (SPM) recommends Equation

1.4, with K = 0.77 for all cases, based on Komar and Inman (1970) where they plotted I and

PI, using field and laboratory data (see Figure 1.1). Equation 1.4 has become known as the

CERC (Coastal Engineering Research Center) Formula. A further examination by Bodge

and Kraus (1991) of the K-coefficient revealed K not as one number, but in a range between

0.2 < K < 1.6, based on field data collected between 1977-1991. Laboratory K-coefficients

were one or two orders of magnitude less than 0.77. The reasons for the scatter of this K-

coefficient has intrigued investigators.























106 -


1


FIELD
= Walts (
N Coldwe
Komor
El M
o Silve


I I I



1953)
11 (1956)
and Inmon (1970)
oreno Beach
Ir Strand Beach *






LABORATORY
O Krumbein (1944)
/'


S' Saville (1950)
a Shay and Johnson (1951)
a *o Sauvoge and Vincent (1954]
0 P n =9 #,'


-1.4
S41.1
SSavage and Fairchild. (1959-1970)
o Price and Tomlinson (1968) p 1.35

I I I


'(A


i103 I 10* 107 108 IC

3 (ECn)b sin cb oab erg /sec cm
* From Komar (1976) p.207

Figure 1.1 Relationship Between the Immersed Weight Longshore Transport Rate and
the Longshore Component of Wave Energy Flux




1.4 Quantifying Large Scale Sediment Transport


Bajorunas (1970), Castanho (1970), van Hijum (1976), Swart (1976), Dean (1978),

and Bruno, et al. (1981) have attempted to relate K to sediment size, while Kamphuis and

Readshaw (1978), Vitale (1981), Kamphuis and Sayao (1982), Ozhan (1982), and Bodge

and Kraus (1991) have attempted to relate K to the surf similarity parameter. It is quite


!


,f1I


F m. 1








7

evident from Figure 1.1 that the K values obtained from the laboratory are less than those

obtained from field studies. More recently, Kamphuis (1991) used dimensional analysis to

obtain a relationship that included wave height (Hb), wave period (T), beach slope (mb),

median sediment size (D50) and the breaking wave angle (Ob) for both field and laboratory

conditions.

Wang, et al. (1998) compared the validity of the CERC equation, the Kamphuis 1991

equation, and two other sediment transport equations. The Kamphuis 1991 formula best

predicted the sediment transport measured by streamer traps in 29 locations on the Gulf and

Atlantic Coasts of the US, although the values were still four times larger than measured.

Schooness and Theron (1995) also discussed the uncertainties of determining K. Using the

results from 34 field tests, they compared the measured and calculated sediment transport

rates with the CERC formula, and the relationships developed by Swart (1976), Bailard

(1985), Watts (1953), Caldwell (1956), and Kamphuis (1986). Significant scatter occurred

when Schooness and Theron used all the data, for all the above relationships, although the

CERC formula fared the best, especially for grain sizes between 0.2-0.4 mm. They

suggested that a criterion for incipient motion be used, as one single description of transport

behavior can describe fine and coarse sand grain movement.


1.5 Scope of This Thesis



The goal of this thesis is to investigate the effect of sediment grain size and initial

cross-shore sand placement geometry on beach nourishment behavior. A summary of the








8

existing theory and relationships associated with assessing sediment transport relationships

involved with beach nourishment will be presented in the following chapter. Chapter 3

presents and discusses the results of the beach nourishment at St. Augustine Beach. Chapter

4 describes a laboratory experiment, intended as a scaled prototype of a beach nourishment.

Various sand sizes and initial cross shore sand placement geometries were evaluated. The

results from the experiments are found in Chapter 4, while Chapter 5 employs the theoretical

relationships developed in Chapter 2 using the laboratory results, discusses the findings, and

compares the results with previous investigations. Chapter 6 summarizes the study and

identifies further needed areas of research.














CHAPTER 2
THEORY



2.1 Governing Equations



Although sediment transport associated with beach nourishment is complex and

occurs in both the cross-shore and longshore directions, many assumptions aid in simplifying

beach nourishment evolution prediction algorithms. One assumption is that cross-shore

sediment transport occurs rapidly to achieve profile equilibrium. Thus, while deriving the

planform solution, the profiles are considered to be in dynamic equilibrium. The basic

equations governing the planform evolution of a beach nourishment project are the continuity

equation and the sediment transport equation. From these two equations, one-line models

can be developed to represent shoreline change. The continuity equation is self-explanatory.

However, parameters involved with sediment transport equations are still under

investigation. The continuity equation is



S(2.1)
at ax








10

where V is the volume per unit width of beach, or the volume density, and Q is the net

longshore sediment flow. The assumption that the profiles are in equilibrium results in a

proportion between the horizontal shoreline change, Ay, and the transport gradient, aQ/lx.

The vertical extent of the active profile is assumed to extend from h. up to the berm height,

B. Thus


1 8Q
Ay= 1 (2.2)
h.+B ax




As mentioned briefly in Chapter 1, Inman and Bagnold (1963) related sediment

transport relationships by establishing a ratio of the immersed weight sediment transport rate,

I, and the longshore energy flux factor, Pls


I = KP1s (2.3)


where


I = pg(s 1)(1 -p) (2.4)



and


Pis = Eb Cb sinabcosab (2.5)


Eb is the wave energy density at breaking, Cb is the group wave speed at breaking, and p is

the density of water. If small amplitude shallow water wave theory is assumed, and Hb is











proportional to the breaking water depth hb by the proportional constant, Hb = Kh, (K = 0.78),

then


Cb = -=
SK


(2.7)


(2.6)


H2
Eb Hb
8


Inserting Equations 2.4, 2.5, 2.6 and 2.7 into Equation 2.3 yields


K Hb2.5 Sgv sin abCOS ab
8(s-1)(1 -p)


(2.8)


Pelnard-Considere (1956) combined and linearized equations 2.8 and 2.2 to obtain


-y =G .2y
at ax2





G K KHb2.5g
G 8(-)( -p)(
8 (s 1)(1 -p)(h, + B)


(2.9)






(2.10)


and


where











2.2 Analytical Solutions



Rectangular Boundary Conditions

A number of solutions with varying boundary and initial conditions has been

developed for Equation 2.9 (Larson et al., 1997). A common simplified solution to predict

the beach planform of a rectangular beach nourishment of length (1) and width (Y) with no

structures is

Y I 2x 1 2x
y(x,t) = (erf (- +1)] erf[-I -1)])
2 4 t 4Gt
1 1 (2.11)
where: y(x,O) = Y; |xl- y(x,0) = 0 ; x>- ,
2 2

y(-,t) = 0



and where "erf ()" is the error function defined as
2 z
erf(z) = f e -udu (2.12)





One method of determining the general performance of a beach nourishment project

is by quantifying the longevity of a project by the amount of sand, or additional beach width,

still in the initial area after a given amount of time. From Equation 2.11, one could define

M(t), as the proportion of additional beach area remaining within the initial project limits:









1/2
M(t) = -f y(x,t)dx
-1/2


(2.13)


Carrying out the integration yields


2V ( I 1 )z
M(t) = 2 [e 2 -1] + erf(- )
lvi 2 G7


(2.14)


Tapered Ends Boundary Conditions


Another solution to the diffusion equation was obtained by Walton (1993), for the

case of an initial trapezoidal planform. Figure 2.1 illustrates this in planform, and the

solution follows as Equation 2.15.



Fill at t= y






-b -a a b
Figure 2.1 Definition of Terms Used in theTapered
Ends Solution (Walton, 1993)








14



M(t)= [erf(AX+A) -erj(AX-A)]
2
1 B-AX
+ B-A )[er(AX-A)-)-erj(AX-B)]
2 B-A
1 B+AX
+ I(-+A )[erAX+A)-)-erf(AX+B)] (2.15)
2 B-A
+ 1 exp[ -(AX-B)2] -exp[-(AX-A)2]
2n-(B-A)
+ --exp[-(AX+B)2] -exp[-(AX+A)2]
2#(B-A)




a b x
where A- ; B- ; X-
2 2vFGt a



Planform Variance

Another way of employing the diffusion equation (Equation 2.9) is to observe the

variance of the rectangular fill plan form spreading longitudinally on the beach. Yoo (1993)

derived the relationship between the variance of the spreading planform and the diffusivity

coefficient, G, to be


do2
d- 2G (2.17)
dt


where the variance is defined as

f(x -x) y (x,t) dx
o2- (2.18)
fry(xt) dx












One can observe from Equation 2.10 that the factors involved with the diffusivity

coefficient, G, and the length of the project, 1, control the spreading of the beach nourishment

sand. A number of attempts have been made to include other parameters thought to be

affecting beach nourishment evolution, and/or reassess the existing parameters involved with

G.


2.3 Numerical Solution



Deep Water Wave Equivalents for Shoreline Modeling

Dean and Grant (1989) were able to better predict beach nourishment shoreline

changes by considering the refraction of deep water waves. Starting with the sediment

transport equation, they assumed straight and parallel contours seaward of the depth of

closure, h., and contours parallel to the nourished shoreline landward of h.. By considering

the ratio of the wave speed at h. (C.) and the deep water wave speed (Co), they derived an

equation for G with all terms expressed in deep water wave conditions, with the exception

of a. and C..



KHo024 G2 0.4COSl.2 (P 0)COs2(Po -a,)
G = (2.19)
8(s 1)(1 -p)C, K04 (h, +B)cos(P0 a,)




The terms in Equation 2.20 are defined in Figure 2.2. This solution developed by

Dean and Grant was the basis for the numerical model DNRBS (Department of Natural




















North

\11 A


y NCon
:.- N
Shoreline aS,
Sholi~~>- Contours /



NI




A A


Region Influenced
by Beach Nourishment

Figure 2.2 Definition of Terms Used in the DNRBS Model Derivation
:,









-i

x
Figure 2.2 Definition of Terms Used in the DNRBS Model Derivation


Deep Water


tour


'Waves








17

Resources, Beaches and Shores), which predicted shoreline change in the vicinity of a beach

nourishment project. In addition to the other approaches, DNRBS will be used to predict the

shoreline changes of the beach nourishment laboratory experiments.


2.4 Additional Sediment Transport Equations



Kamphuis (1991) has conducted significant research in longshore sediment transport.

He used dimensional analysis to re-evaluate the importance of various parameters involved

with sediment transport. By examining 28 laboratory tests and field experiments from nine

previous investigations, Kamphuis and his colleagues included the effects of H, T (involved

with the surf similarity parameter and wave steepness), the slope of the beach from the

waterline to the break point (mb), the median grain size (Do0), and the breaking wave angle

ab in sediment transport. The following equation was the result.


Q = K'p( )1.25 Hb2 Tp.5 m60.75D50-0.25sin0.6(2ab) (kg/s)
2 T



Then, Q = 2.27 Hb2 1.5 mb075D5-0.25 sin06 (2ab) (kg/s)


Or, if medium dense sand is used with a porosity of 32%,



m 1.25
Q = (6.4 X 104 Hb) H,2 Tl5 b75D5-0.5 sin06(2ab) (m 3/yr) (2.22)
yr2.5








18

Most other longshore sediment transport relationships are limited to field data only,

or only for coarse or fine grain sands. The laboratory experiment discussion will evaluate the

application of the Kamphuis relationship with the model results obtained from this study.

However, because field application of sediment transport theory is the primary

motivation for this research, the monitoring results from St. Augustine 1996 Beach

Nourishment Project will be presented first.

















CHAPTER 3
BEACH NOURISHMENT MONITORING AT ST AUGUSTINE BEACH



3.1 Introduction



In the Spring of 1996, the U.S. Army Corps of Engineers (USACE) placed

approximately 135,000 m3 of beach quality material on the beach face at two locations south

of St. Augustine Inlet. This nourishment project was an "add-on" to a maintenance dredging

project of St. Augustine Inlet. (See Figure 3.1) This was the first time that a nourishment

project of this magnitude had been carried out at St. Augustine Beach. The quantity was

considerably less than the planned 240,000 m3 of sand, as dredging operations were limited

by severe weather conditions, dredging equipment malfunction, and the onset of turtle

nesting season. These problems caused the sand placement operations to extend over a four

month period, from February to June of 1996, significantly longer than planned. Both sites,

(the south St. Augustine Beach (SSAB) site and the site at Anastasia State Park (ASP)) were

monitored every four weeks during placement and for a six month duration after the dredging

and pumping operations ceased. The SSAB site received the bulk of the sand volume, and

was monitored for an additional 18 months. The study involved topographic surveys,

sediment analysis, and interpretation of the results.

19













3.2 Background



Inlet and Ebb Tidal Shoal Changes


The St. Augustine nourishment areas have many interesting facets. Before the

present St. Augustine Inlet was cut and stabilized in 1941, a natural inlet existed which

migrated 0-2 km south of the cut. A north jetty to the new inlet was built in 1941, and the

south jetty was placed in 1957. The old, natural inlet system supported a large shoal system,

with the ebb tidal shoal volume estimated to be 20 million cubic meters (MCM) in 1937

(Srinivas et al., 1995). The discontinuity of the north and south sides of the inlet in 1937

were characteristic of an updrift offset typical around inlets having a north-to-south net

littoral drift. Estimates of the net littoral transport rate in the St. Augustine Inlet area range

between 150,000 and 310,000 m3/year to the south. A time series of aerial photographs

spanning this period is presented in Figures 3.1-3.4.

The hydrodynamics associated with the stabilized inlet disturbed the shoal system.

A portion of the large ebb tidal shoal appears to have migrated landward and joined the south

shoreline. This created a reverse north-south shoreline discontinuity, which is still evident

today. The volume of the old ebb tidal shoal shrank to approximately 9 MCM in 1974. In

the 1970's, it appeared that the shoal finished its shoreward migration, and began to grow

again at a location further north. In 1995, the ebb tidal shoal volume was estimated to be

16 MCM, and growing at a rate of 210,000 m3/year (Srinivas et al., 1995). Approximately













St Augustine Inlet in 1988


Anastasia State Park
Nourishment:
Length = 300m
24,000 cubic meters

Revetment





St. Augustine Beach
Nourishment:
South Section
Length = 842m
112,000 cubic meters


Figure 3.1 Aerial Photograph of St. Augustine Beach,
Including the 1996 Nourishment Sites












St. Augustine Inlet 1942


Figure 3.2 Aerial Photograph of St. Augustine Inlet in 1942









St. Augustine Inlet 1947


Figure 3.3 Aerial Photograph of St. Augustine Inlet in 1947











St. Augustine Inlet 1962


Figure 3.4 Aerial Photograph of St. Augustine Inlet in 1962








25

900,000 m3 of material has been dredged from the inlet's navigational channels since 1970,

(excluding this project), all of which has been placed in the offshore or nearshore region

(USACE, 1990).

Wave Climate. Storms and Erosion Rates


A wave height rose produced by the U.S. Weather Bureau in Jacksonville, 50 miles

north of the sites, shows the dominant waves propagating from the northeast. The average

significant deep water wave height is approximately 1 m, with a period of 7 sec, and a deep

water wave steepness of 0.0132. In the summer, waves approach from the southeast, which

causes a temporary reversal of the littoral drift to the south-to-north direction.

The presence and maintenance of the stabilized inlet has caused erosional stress in

the study areas, which are located between 5.8-8.8 km (3.5-5.2 miles) south of the inlet. One

hypothetical explanation for this occurrence is that the northeasterly waves refract around the

large ebb tidal shoal and concentrate the energy in this region. Another cause could be that

sand is not bypassing the inlet, and the southerly bound sand is not replenishing the southern

beaches, but is contributing to the ebb tidal shoal growth.

The Florida Department of Natural Resources (FDNR) has assembled shoreline

position data at monument locations in this region, extended over a period of more than one

hundred years. The south and north study areas ranged from FDNR Monuments R145 R149

and R139-R141, respectively (see Figure 3.5). By examining the data succeeding inlet

stabilization and linearly regressing the shoreline positions at each monument with respect

to time, one finds that the beaches at the south and north sites are eroding at average rates of








26

1.16 and 7.4 m/year, respectively. (Figure 3.6). Table 3.1 lists the significant storms in the

region since 1941. It is interesting to note that with the exception of a 1973 northeaster, the

erosional trends do not seem to reflect major episodic events, such as northeasters or

hurricanes in the region.


Anastasia State Park
Nourishment:
Length = 300m
"ASP"

Revetment






St. Augustine Beach
Nourishment:
South Section
Length = 842m
"SSAB"


Figure 3.5 Monument Locations


R 14;

R 146,

R 147


R148
IZ149












EROSION RATES: ANASTASIA STATE PARK

R1
I-- R1
--*-- Ri
Av
AVERAGE EROSION: ---- -
-7.4 MIYR OR -24 FT7YR F T.1


1950


1960 1970 1980 1990
YEAR
EROSION RATES: SOUTH SECTION --- Ri45.


S1000 AVERAGE EROSION ..-- R147/
o 800 .1.2 MIYR OR -3.8 FTIYR ---- R148/
600 -V-- R149
y 600 -- R149
40 r ''-. ....... . ....... ..... A vera!
S400.....
- 200 . ...
0
1950 1960 1970 1980 1990
Figure 3.6: Historical Erosion Rates at the Nourishment
Sites


Table 3.1 Major Storms and Hurricanes in St. Augustine Region


YEAR STORM INTENSITY

1956 Hurricane Greta caused 1 m vertical scarp

1962 Ash Wednesday Northeaster lost 20-30 m of beach

1964 Hurricane Dora 100 yr Storm, landfall at St. Augustine,
210 km/hr winds, lost 30 m of beach

1973 Northeaster lost 16-20 m of beach

1984 I Thanksgiving Northeaster lost 30 m of beach,

1996 Northeaster During 2-3 m offshore waves for a 4 day
S Nourishment Placement duration


ge











Revetments


A revetment is located between the two nourishment sites (see Figure 3.5). The

revetment's southern limit is 156 m south of R145, which was the north limit of the

nourishment placement at the SSAB site. The remnants of a smaller revetment extend from

the end of the large revetment at the north end of the site, to 50 m south of R146. This

revetment was visible in January, 1996, became buried by nourished sand initially, and

became exposed again in October, 1996.

The ASP site ranged from monuments R139-R141. Rip-rap litters the beach,

located approximately 30 meters seaward from the vegetation line. The rip-rap is more

consolidated in the southern end of the park. Rip currents are known to be common in this

area (Olsen, 1988).




3.3 Monitoring Results



Topographic Surveys


A standard survey level and rod technique was used to determine the elevations,

along with a 100 m tape to measure the seaward distances. Mobilization of a boat for

offshore soundings would have increase the monitoring costs substantially. Further, it was

not justified considering the reduced accuracies attainable by sounding, the small

nourishment volumes placed, and the limited funding for this project. At the SSAB site, 11









29


profiles were surveyed each visit, between R145-R149 (see Figure 3.7). At the ASP site,

which was nourished later, 7 profiles were monitored on 7 dates. The locations of these

profiles are between R139-R141 (see Figure 3.7). The profile data from all the survey dates

can be found in Appendix A.



R139
Anastasia State Park
R140 -
--R10 (North Section) "ASP"
R141 -
R Armored
R142 Shoreline N
Fishing
Pier

R145
R146A -St Augustine Beach
R147A (South Section) "SSAB"
R148
R149 ---------Surveyed Profile Locations
Shore Baseline
Figure 3.7 Profile Locations



Sand Samples

During the first year of monitoring, a minimum of one sediment sample was collected

during each survey at the waterline from the profiles where the FDNR Monuments were

located. On occasion, samples were collected at 20 meter intervals along the profile. The

sediment size distribution was determined by using sieves and a rapid sediment analyzer, an

apparatus which makes use of the particle settling velocity to determine the sediment size

distribution. Over 100 samples were analyzed in total.










3.3.1 Survey Results from the SSAB Site

Beach Profiles

During the 1996 project, the sand was pumped hydraulically on to the berm, which

was approximately 2.5 m above the 1929 National Geodetic Vertical Datum (NGVD). A

profile in the center of the SSAB site, R147 (Figure 3.8 and 3.9) is a reasonable

representation of the profile shapes measured inside the nourishment area. The profile

fluctuated considerably during the two years of monitoring. The top graph includes all

survey dates (Figure 3.9a). The bottom graph only includes significant dates, such as the pre-

project profile (January, 1996), the complete nourished profile (May, 1996), and 12, 17 and

21 months after placement (Figure 3.9b). The "spreading out effect is very evident

(Figures 3.10 and 3.11) on both adjacent beaches. The northern- most profile gained nearly

Im in elevation 1 year after placement and then lost it 9 months late (Figure 3.10). The

summer southeasterly waves seemed to have transported the sand into this area, which

resulted in these fluctuations. Figure 3.11 is a cross-section of the most southerly profile,

R149, also outside the initial placement area. Similar trends can be seen here, but not quite

as evident as the fluctuations experienced in front of the revetment, R145.














Wall and Path


Figure 3.8a DNR 147, 1987 9 Years Before Nourishment


id Path


Figure 3.8b DNR 147, March, 1996 During Placement


Figure 3.8c DNR 147, May, 1997 1 Year After Nourishment


Figure 3.8 DNR 147 Center of the South Site of the
1996 St. Augustine Beach Nourishment
a) 1987; b) March, 1996 and c) May, 1997
















Profile 147


0 20 40 60 80 100 120
Profile 147: Selected Dates


0 20 40 60 80 100 120


140 160


-- Jan. 9, 1996
A .... February 24, 199
-U-.- March 9,1996
---*-- March 29, 1996
----- April 20, 1996
-....*- May2. 1996
--A-- June 1,1996
--0-- June29. 1996
...... <..... July 25, 1996
---- August 22, 1996
-- -- Sept. 22, 1996
**).... October 27, 199e
-.-+-.- May 24, 1997 "
---q--- Sept. 29, 1997"
.- ....- Jan. 17, 1998 **


140 160


Seaward Distance (m)

Figure 3.9: Monument R147 Profiles, in the Center of the SSAB Site; a) All

Survey Dates; b) Selected Dates Marked with Asterisks












r Profile 145: Selected Dates


Revetment


Jan 9,1996
May 23, 1997
Sept 28,1997
Jan 17, 1998


1 Year Later


21 Months Later


Pre-Project


S I I I


I I I I


0 20 40 60 80 100
Seaward Distance (m)


Figure 3.10 Monument R145
Nourishment


120 140 160


Profiles, Located 250m North of the SSAB


3 -


I(IJI IIIIIIIIIII


I I I I I I I I I I


















S 17 months later Jan 9, 1996
z
z 2 -+-- May 23, 1997
.- Sept 28, 1997
W 1 yearlater -- Jan 17, 1998

E Pre-Project
0 0


-1 21 months later

-2
0 20 40 60 80 100 120 140 160
Seaward Distance (m)

Figure 3.11 Monument R149 Profiles, Located 300 m South of the SSAB
Site



Total Sand Volumes

Interesting variations occur when the profiles are compared to the January pre-

nourishment conditions. When the changes in the profiles are added for each survey to

obtain the total volume change since the onset of the project, it shows the progression of the

sand being placed on the beach until May 2, when placement was finished (Figure 3.12).

After May 2, the sand in non-equilibrium quickly disperses to the adjacent beaches. This

"spreading out" effect remains nearly constant until September, when volume deficits were

experienced both inside and outside the nourishment area. Notice the plots just represent

the sand volumes above NGVD, or the dry beach.










Total Volume of Sand above NGVD
0o St. Augustine 1996 Beach Nourishment
0
0 so Placement
x Finished
S70 \ Total Survey Area
8 60
5 0 ..... ........
-o 50 ..-. In Placement Area


EQ
2 0 -


o '"-.---- In Adjacent Area
> 10 -
0 --- --- --- --
I- 1997 1998
-10
f0 100 200 300 400 500 600
February, 1996 Time (Days from Start of Project)

Figure 3.12: Total Volume of Sand Above NGVD on the SSAB Site
Versus Time




Various approximation methods were investigated to extrapolate the short

profiles, so the fluctuations of sand volumes in the surf zone could be compared between

each survey. However, a satisfactory method was not found. Thus, while the above

NGVD volume and density figures presented are accurate, sand bar formation and

dispersion below NGVD are only displayed in some of the profile plots.

It was unusual to find that the volume in the total survey area continued to grow even

after placement was finished (Figure 3.12). Two possible explanations exist. First, the

surveys following placement were summer profiles. Since the volume only includes

subaerial sand, this volume increase could simply be sand bars that have migrated shoreward.

Second, and related to the aforementioned, a Northeaster impacted St. Augustine on March

10-12, 1996, and appeared to cause 20,000 m3 of sand to be removed from the subaerial









35

beach. It seems as if this removed sand was subsequently transported ashore and deposited

on the subaerial beach at a later date. In the 18 months that followed placement, the sand

was slowly transported out of the area. However, the rate of sand loss is significantly less

than expected, which will be discussed later. Records maintained by the dredging operators

provide a means to compare the above NGVD sand volumes collected in this study to the

total sand documented placed on both the subaerial and subaqueous beach (Figure 3.13).

The sand was hydraulically pumped from the hopper onto the beach. The dredger's final

volume was approximately twice the volume obtained from the surveyed profiles above

NGVD. The sand not accounted for was either in sand bars, or it was carried away by

longshore or cross-shore processes.









Dredging Records
-o Sand Deposited by Hopper Dredge
S-Nourishment
4o 120 Finished -
o 110 ^
100

80
S70 -
60
L 50
o 40
S30 February 20 ,*V-March Northeaster
0 20
10

0 10 20 30 40 50 60 70
Days Since Start of Nourishment

Figure 3.13: Record of Cumulative Sand Added at the SSAB Site
by the Dredge Operators








36

A severe northeaster hit the region from March 10-13, 1996. The north Florida

Atlantic coast experiences a typical March significant wave height of 1 meter. However,

from March 10 to March 13, wave heights rose to 2.1 m. The storm halted beach pumping

operations for over two weeks. The effect of the storm is evident in all the March 29

profiles. During the 20 day interim between surveys, Figure 9 indicates that 14,000 m3 of

sand was lost above NGVD, even though the dredger's log indicate that 11,000 m3 was

placed on the beach during that same 20 day period.



Additional Dry Beach Width

On May 2, five days after the SSAB site operations ceased, the additional beach

width in the nourished area ranged from 0 to 27 meters. The additional dry beach width

evolved over time, as seen by the significant dates shown in Figure 3.14. At the north end

in front of the revetment, the fluctuations are substantial, which is consistent with previously

mentioned observations. Within the initial placement area, the beach width fluctuates with

the seasons. However, the dry beach area is slowly decreasing, as expected by the nature of

the diffusion process. There were also fluctuations in the region of the beach between

R147.5 and R149. These fluctuations were not identified from anecdotal, visual

observations. Further examination of the profiles in this region left the author to conclude

that the January, 1996 profiles (pre-project) in this region were unusually high. Since all the

surveys were compared to these pre-project profiles, Figure 3.14 creates the illusion that this

region was an erosional hot spot.









37




Additional Beach Width since January, 1996
Initial Placement Area
60 4
.-. 17 Months Later -_- May 2, 1996
S50 --- May 24, 1997
S0 -- Sept 29, 1997
S-- January 17, 1998
'- 30 Post Placement
t-
S20 -1 Year Later
-is
10

0 "21 Months Later
-10- R145 R146A R147A R148A R149
0 200 400 600 800 1000 1200 1400
Distance South from R145 (m)

Figure 3.14 Additional Beach Width at the SSAB Site





Volume Density Fluctuations

Figure 3.15 illustrates the volumetric density above NGVD of the nourished sand in

the cross sections of the profiles. It is interesting to note that the northern end gained more

from the "spreading losses", which could be explained by waves propagating from the south,

typical in the summer months when those surveys took place.




3.3.2 Results from the North Site. Anastasia State Park

The ASP site received much less sand than planned by the USACE; 24,000 m3

versus the 100,000 m3 planned. The sand was placed between May 15 and June 15, when

the dredging activity ceased due to the onset of the turtle nesting season. Most of the sand

was placed between R140 and R141 (Figure 3.16). While the magnitude of the total










p38
Accumulation of Sand in Monitored Area Above NGVD
E
CD 160
160 PLACEMENT AREA
o 140 (/--- May 2, 1996
I-" "May24,1997
c Post Placement \\ May 24, 1997
-a 120 / Sept 29, 1997
oo / ---- January 17, 1998
S 17 Months I. / '
80 so
E Later

> %
S40
S20 21 Months 1 Year Later
4--
o Later

-20
S R145 R146 R147 R148 R149
E --I--------------------I-
o 0 200 400 600 800 1000 1200 1400
< Distance South From Monument 145 (m)

Figure 3.15 Accumulation of Sand Added Above NGVD Since
Pre- Project Survey, or the Density of Added Sand Volume at the
SSAB Site




volume values are small in Figure 3.16, the profiles at R141 (Figure 3.17) clearly indicate

that the local erosion rates were large enough to cause the shoreline to retreat behind the pre-

project shoreline of January, 1996, despite the addition of sand into the nearshore system.

The presence of the rip-rap in the swash and surf zone consistently caused difficulty in

documenting the presence of any sand bars. Thus, consistent with the SSAB site, only data

above NGVD were documented for the ASB site. While there can be an argument in stating

that the post-project profile of June, 1996(summer) cannot be compared to the winter profile

of December, 1996, there is still merit in comparing the January, 1996 (winter) pre-project

profile and the December, 1996 (winter) profile, which still shows significant erosion. The

top of Figure 3.17 shows the data from all the survey dates, and the bottom graph shows two

selected dates.











Total Volume of Sand above NGVD
St. Augustine 1996 Beach Nourishment


Total Survey Area


In Adjacent Area


.2 June, 1996


December, 1996


0 20 40 60 80 100 120 140 160 180
Time (Days from Start of Project)


Figure 3.16 Total Volume of Sand Above NGVD Versus
Time at the ASP Site



- North End of Anastasia State Park
--- January 9, 1996
_---- June 1,1996
S-V-- June 28, 1996
S ,-.-0--. July25,1996
-.~ .V ---- August22,1996
.. ....- --- Sept 22,1996
........ October27, 1996
S.-1 --+- December1,1996

0 10 20 30 40 50 60 70 80 90 100110
R141: North End of Anastasia State Park: Select Dates
S-0- January9,1996
--- /Post-Project --- June 28, 1996
+~ _" \ Pre-Project -+- December 1, 1996


0 10 20 30 40 50 60 70 80 90 100 110


Distance Seaward (m)


Figure 3.17 Profiles at Monument R141


R141

21

1








40

Due to the small volume placed at the Anastasia State Park site, the focus of this

study is on the SSAB site. For more information regarding the field results from the

Anastasia State Park site, please refer to the St. Augustine Beach Nourishment Project:

Anastasia State Park and St. Augustine Beach (Donohue and Dean. 1997).



3.4 Sediment Analysis



For the SSAB site, the average mean diameter of the native beach sand was 0.18 mm,

while the average mean diameter of the fill material was 0.35 mm (see Figure 3.18). The

larger beach fill diameter should enhance the longevity of the project. The sand collected

during the placement phase (February-May) was characterized by the largest mean diameter.

As time progressed, the sand became better sorted, with the mean diameter fluctuating

around 0.18 mm, the native mean grain size (Figure 3.19). In the ASP site, the native mean

grain size diameter was 0.175 mm. It was difficult to trace the small volume of fill sand at

the ASP site. The sediment data from the ASP site can be obtained from Donohue and Dean,

(1997).












Grain Size Distribution for St. Augustine Beach


SPre
D5(
Dmn
Std

Post-Nourishment
D50 = 0.38mm
Dmean = 0.3586mm
Std. Deviation = 0.7129\


'-Nourishment
0 = 0.1746mm
lean = 0.1735mm
I. Deviation= 0.2E


0 10-1
1 10 101


-2
10


Grain Size [mml
Figure 3.18 Sand Size Distributions of the Native and Fill Sands for the 1996
Beach Nourishment at the SSAB Site


Mean Diameter of Sand, South Section


0.52



0.42


0.32 A
x
0.22

0.22 -


.... ... .. ^ I ... .
:F

o A

R146A R147A

R146A R147A


ill Sand






R148A


Feb24WL
A March 9WL
March 29WL
April 20 WL
V May2WL
O June 1 WL
A June 28WL
i July 25WL
O Aug 22 WL
V Sept 22 WL
+ Oct27WL
I Jan 9 Berm
I X Feb 24 Berm
March 29 Berm
S April 20 Berm

WL = Water Line

R149
R149


0 200 400 600 800 1000 1200 1400
Distance South from R145 (m)


Figure 3.19 Distribution of the Mean Sand Size Over the Length of the SSAB Site
Versus Time


80 F


48


20k


'











3.5 Comparison of the SSAB Site With Theory


As discussed in Chapter 2, an accepted approach to predict beach nourishment

performance has been to employ the diffusion equation (Pelnard-Considere, 1956),


aY G a(3.1)
at ax2


When theory is applied to the SSAB beach nourishment site with the standard sediment

transport coefficient (K = 0.77), the equation grossly underpredicts the projects longevity,

or equivalently, the sediment transport is overpredicted. Figure 3.20 illustrates this point,

using the typical regional values of B = 2 m and h. = 9 m to calculate G. The results for the

least square fit sediment transport coefficient, K, is also plotted.




Mvs. t

0.9 +

S0.8

0.7 \

_. 0.6 Best Fit K = 0.015

0.5-
SActual Data Points
0.4 -

E 0.3
02- CERC
0.2 Prediction
S0K = 0.77
0.1 O
a)
0 100 200 300 400 500 600 700
Time (Days Since Placement)
Figure 3.20 Percent Remaining Versus Time Using the Pelnard-Considere
Equation and the CERC Sediment Transport Equation








43

The DNRBS numerical model was not applied to the SSAB nourishment because

many of the input parameters would be estimates (e.g. wave height and direction). The

inaccurate input parameters conflict with the model's goal of providing a detailed and

accurate prediction of the nourishment's evolution. However, the results from applying the

simple analytical solution (Figure 3.20) suggest that the particular characteristics of the

SSAB site beach nourishment have resulted in an increase in the project's longevity. While

the breaking wave height and the depth of limited closure were estimates, one cannot

overlook the need to reexamine the sediment transport coefficient, or to re-evaluate the

relationship of the parameters in the CERC sediment transport equation. Two characteristics

were attributed to contributing to the success of the 1996 St. Augustine Beach Nourishment

at the SSAB site: 1) the use of a larger than native sand size for the fill and 2) the placement

of the s high on beach profile. The laboratory experiment described in the next two chapters

will attempt to assess the effect of these on sediment transport and beach nourishment

evolution.














CHAPTER 4
LABORATORY EXPERIMENTS



4.1 Introduction



The unique behavior of the nourishment at St. Augustine Beach prompted a

laboratory study which focused on the role of sand size and sand placement in beach

nourishment evolution. The study used three different fill sand sizes and two different initial

profile shapes to create six different combinations of varying characteristics. The tests were

conducted in the three dimensional wave basin at the University of Florida's Coastal and

Oceanographic Engineering Laboratory. The results of these experiments are presented in

this chapter.




4.2 Experimental Equipment



Wave Basin

The wave basin dimensions were: 20 m wide, 15 m long and approximately 50 cm

deep, with 88 wave paddles located at the deep end and a sandy beach of 0.21 mm median

diameter sand at the other end (Figure 4.1) The wave settings did not change over the coarse












VE GUIDESNAKE WAVE MAKER !
WAVE GUIDES-- -




PROFILE LINES


ai i 1l i i i i i i i i ii i i i i
SI;GAP FOR LONGSHORE CURRI
I :I: I I I I ^ I AND SAND TRANSPORT


WEST


FINE SAND TEST AREA I COARSE SAND TEST AREA


EAST


Figure 4.1 Wave Basin Layout and Profile Lines



of the study. To minimize lateral wave diffraction, two artificial wave rays were established

by removable concrete walls. A constant water level was maintained within T.3 cm by a

pump for all tests. The detailed experimental conditions are presented in Table 4.1 below.



Table 4.1 Laboratory Wave Characteristics

Deep Water Intermediate Water Depth Wave Breaking Point

T ho ao hn aIN HNT hb ab Hb

1.08 s 78 cm 260 36 cm 70 4.8 cm 7.5 cm 50 4.3 cm











Survey Method

The wave basin was large enough to conduct two tests at once. The south end of the

basin had a "native" beach of fine sand. The initial beach nourishment length for all

experiments was 2.4 m, including the tapered ends that extended 0.2 m on either side. The

total surveyed area extended 1.8 m from the tapered ends on either side, or 6 m in total beach

length in each test area. Twenty five profile lines were surveyed in each nourishment area,

after 0, 30, 60 and 150 minutes of waves, at a minimum (see Figure 4.1 for profile

locations). To facilitate the measurements, two cables were located parallel to the beach, one

fixed as a beach baseline and the other cable fixed offshore, at least 2-3 m beyond what

would be the estimated depth of closure.

The cross-shore distance was measured with a light aluminum bar with a tape

measure fastened to it. The bar slid on the cables. Using a tape measure and survey level,

marks were made on both the land and sea cable at each profile location to create a shore

perpendicular transect. The bar was aligned on the proper land and sea cable mark for the

transect, or profile of interest.

The elevations were measured by using a rotating laser level. This instrument

emitted a laser light about a horizontal plane, similar to what is normally called the "line of

sight" for a level. The accuracy of elevation readings were +-1.5 mm. A light aluminum rod

with a meter stick fastened to it, and a flat (1 in. x 1 in.) plate attached to its base served as

the level rod. A bubble level was placed next to the rod to insure the rod was held plumb.








47

The survey began with the easterly profile. Starting from the land cable, or baseline,

the cross shore distance and elevation at each break of slope on the profile were measured.

All profiles were measured out to 244 cm from the baseline.



Wave Gage

A capacitance-type wave gage was used to measure the wave height. The gage was

calibrated by measuring the voltage difference at two known heights when the water was

still. The voltage differences were converted into height differences and recorded into data

files with a computer and GlobalLab software. The data files were then input into a BASIC

computer code which computed the average period and wave height from the record. The

monochromatic waves were generated in water 78 cm deep. The basin floor sloped rapidly

to a water depth of 36 cm, which was considered intermediate water depth for the wave

length produced. Intermediate wave heights were recorded in this area, in 5 locations

spanning the offshore portion of the beach. Breaking waves were also recorded. The

averaged results can be found in Table 4.1.


4.3 Test Preparation



Maintaining a Consistent Native Sand Diameter

The experiment required the native sand diameter to be consistent for all the tests.

The native sand diameter was required to be in the range of 0.2 to 0.22 mm before each test.

When fine sand (0.21 mm) was the fill, this was not a problem. However, when medium and








48

coarse sand were used in the previous experiment, a sand layer approximately 5 cm thick was

scraped off the subaerial and subaqueous beach. The medium and coarse sand was usually

visible, and more than 5 cm was removed if necessary. Then, the removed layer was

replaced with a layer of fine (native) sand. The particle size distributions are shown in

Figure 4.2.

Sand Size Distribution
100 -
Fine/Native Sand
D50 = 0.2117mm
80-

Z Medium Sand
60- D50 = 0.5023 m

S650

0 40


20 Coarse Sand
D50 = 1.004mm

10 10 101 102
Grain Size [mm]
Figure 4.2 Particle Size Distributions for Sands Used in the Laboratory
Experiments


Creating the Equilibrium Beach Profile and Shore Parallel Contours

After the beach sand was nearly uniform in size, the wavemaker was activated for

over one hour. The analytical solutions which will be applied to the results assume shore

parallel contours. By observing the breaking wave crests with the wavemaker on, sand was

added and removed to attempt to maintain wave crest breaking simultaneously, and travel










49

towards shore in that manner. When this was completed to a satisfactory level, the

wavemaker again ran for two more hours to equilibrate the beach in the cross shore direction.



Creating the Initial Template

Before any fill sand was added to the beach, it was placed into a wheel barrel full of

water to completely saturate it. Then, using a 5 liter bucket, 20 buckets of saturated fill sand

were placed in the nourishment area. Two templates were used to shape the fill sand. These

templates are shown below.


SHAPE A


o8
> 6
4
I2

J
> 0
0
<-2


L)


20 40 60 80 100 120
Distance Seaward form Base Line (cm)


140


Figure 4.3 Initial Fill Placement Geometry





The areas under both templates were the same. The nourished beach length was 2

m long with 0.2 m tapered ends, and 0.2 m wide at MWL for the A shape, and 0.33 m wide


I


11 3.5 cm
20


-1APE B








50

for the B shape. The sand was compacted into its respective shape so its porosity was similar

to the porosity of beaches created by wave action.


4.4 Experimental Procedure



The tests commenced with a survey of the initial nourished planform. The

experiments which used sand of the same size as the native ("fine" sand) were conducted in

the updrift section (west), so the section of beach which becomes contaminated with coarser

than native sand could be contained in the downdrift section. Each test was surveyed at least

after 0, 30, 60 and 150 minutes of monochromatic wave activity.


4.5 Results



The original intention was to have two complete tests per shape/sand size scenario.

However, the first 3 tests were rejected, as the equipment and procedure required refinement.

The medium size sand tests were added to the experiment agenda, and time did not permit

those scenarios to be tested twice. Thus, there was only one scenario that has been tested

twice satisfactorily. A list of the tests included in this analysis can be found in Table 4.2










Table 4.2 Summary of Test Characteristics


An accurate method for interpretating the profile data is to calculate the area under

the profiles. If these areas are subtracted from the area under the initial profiles at each

alongshore location, information relating to the longshore sediment movement can be

inferred. If sand is conserved, then the positive changes should approximately equal the

negative changes. For some of the tests this imbalance was quite large. This non-

conservation of sand was attributed to settling of the survey rod in the unconsolidated sand

in the vicinity of the waterline, especially in the initial survey. The medium and coarse

sands were more unconsolidated than the fine sand. The area change plots were adjusted by

calculating the volume of sand that was gained or lost and distributing that amount along the

entire test area, so sand conservation was restored. The real and adjusted area change plots

are presented in Appendix B

While it is interesting to see the changes of volume density, if the initial fill volume

density is added to the change of volume density plots, the resulting plots resemble the visual


Test Fill Sand Shape

1 Fine: 0.21 mm A

2 Medium: 0.5 mm A

3a Coarse: 1.0 mm A

3b Coarse: 1.0 mm A

4 Fine: 0.21 mm B

5 Medium: 0.5 mm B

6 Coarse: 1.0 mm B








52

shape of the nourishment evolving over time. The change in volume density, the additional

volume density and the additional dry beach width plots are presented in the following

chapter, for each test, along with a detailed discussion comparing the tests with each other..














CHAPTER 5
ANALYSIS OF LABORATORY RESULTS



5.1 Determination of the Sediment Transport Coefficient. K



The objective of the laboratory experiments was to compare qualitatively and

quantitatively the associated change in transportability when the fill grain size and initial

placement profile are varied. The Pelnard-Considere and CERC sediment transport

equations were used to analyze the laboratory data. As discussed in Chapter 2, there are two

solutions to the diffusion equation which can be applied to the laboratory experimental

conditions. The results from Tests 1-6 will be compared to those solutions, and then be

compared to each other. The data obtained from previous investigators and these laboratory

analysis will be intercompared in the next chapter.


5.1.1 Proportion Remaining over Time Using the Rectangular Diffusion Equation
Solution

The proportion of sand remaining within the initial area versus time was evaluated

for each test (Figure 5.1). This analysis was used in the previous chapter to access the project

performance of the southern site at St. Augustine Beach (SSAB). The data are presented

according to their initial fill design templates. Initially, all the runs show a high rate of

erosion. The coarse (1.0 mm) sand in Shape A seems to be the most stable of all the tests.













The K values were determined by using Equation 2.11, which quantifies G, the diffusivity


coefficient (Figure 5.2), and demarcating the K value that had the least squares fit.


< SHAPE A
WY l.o 1 0 _M ; 0;21 MM
S0. .21 MM


z o0.8





S10 1.0 M
Z 0.7







u 0.5 MM . ."
S 0 .6 : : : - .-
kU 0.5 'I--- i ,i---,i--- I --,---i---- ----- i --,-i-, ^
(L 0 20 40 60 80 100 120 140 160







Figure 5.1 Percent Remaining in Placement Area Versus
Time for the Measured Data; a) Shape A; b) Shape B
PERCENT REMAINING IN PLACEMENT AREA
.0 MM K= 0.015V SHAPE
z










S1.0 MM K0.021
0.21:MM
0.8










Z 0.7 ---
w 0.21 MM= 0.0380.5 MM K= 0.024
0.0
U 0.5









aU 0 20 40 60 80 100 120 140 160
Figure 5.1 Percent Remaining in Placement Area Versus
Time for the Measured Data; a) Shape A; b) Shape B






PERCENT REMAINING IN PLACEMENT AREA









I-
S1.o 0 MM K= 0.015V SHAPE A
0 .9 ... 1.0 MM K = 0.050

0.8 -




0.8 i :': : : : .............-
0 0.21 MM K = 0.03867 0.5 MM K 0.024










0.5, 1 1 1 L I I I ,
0 20 40 60 80 100 120 140 160




TIME (MINUTES)
w 1.0 021 MM K=0.030 S









Figure 5.2 Percent Remaining in Placement Area Versus
Time Using the Best Fit K Value and the Rectangular0.050
Diffusion Equation Solution; a) Shape A; b) Shape B
0.7
0.6
0.5 MM K 0n067
0 20 40 80 80 100 120 140 180
TIME (MINUTES)

Figure 5.2 Percent Remaining in Placement Area Versus
Time Using the Best Fit K Value and the Rectangular
Diffusion Equation Solution; a) Shape A; b) Shape B









55

The K values are on the order of two magnitudes less than the CERC recommended

coefficient of 0.77. This difference is typical for laboratory experiments. There is no clear

trend in the data and it would have been beneficial to have more tests for comparison. The

effect of the K of the native sand was a common influence in all the experiments, and was

not factored out of the results. Separating out the effect from the native grain size and the

fill grain size would have been valuable, but was considered impossible to accomplish.

While the Shape A tests show a trend previously predicted, with transportability decreasing

with increasing sand size, Shape B shows a maximum K value near 0.5 mm, indicating the

greatest transportability. The average K values were less for Shape A (Figure 5.3).








Sediment Transport Coefficient (K) for the Rectangular Solution
0.00
2 .. .. . . . *: : . : .
10 8

5
4
3
2





4 . ....
3
2
SHAPE A
10 -2.00 ..... ; ... .....;.... ........... ; ......---:----- i .........: ........i .........: -- ........:-- ;---........ -------- i ..... ,--; ..... ......... .....
10 -2.00 ......- .
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Median Diameter (mm)

Figure 5.3 Comparison of the Sediment Transport Coefficient and the Sand
Diameter Using the Rectangular Planform Solution










5.1.2 Tapered End Solution

The approach for determining the K coefficient using the tapered end solution was

the same as the above analysis. It is noted that the tapered ends solution, based on the

diffusion solution, only differs from the solution for a rectangular planform by the initial

conditions. The spreading of the volume density was separated into even and odd volumetric

changes. This method was first used by Berek and Dean in 1982, to separate out those

changes which are symmetric about a selected origin, and those which are antisymmetric, and

in some cases may be interpreted as due to the presence of a coastal feature. This method

uses the equation:

AV(x) = AVven() + AVodd(x) (5.1)




Interpretation of the causes of the even and odd shoreline changes requires sound

engineering and scientific judgement. The spreading of a beach nourishment planform,

according to the diffusion equation, should be purely an even function. However, the

equation on which the diffusion equation has been based is nonlinear, and it is possible for

the protruding, nourished beach to interfere with the ambient longshore sediment transport

present with oblique waves. The different native and nourishment sand sizes could also

cause an odd effect. Each of these effects could contribute to the odd component, whereby

sand would then be impounded on the updrift side, which presumably would be lost from the

downdrift side. On the other hand, under oblique wave attack, the sand perturbation could

be prone to shift downdrift, in the direction of the incoming waves. This odd shoreline








57

change would result in updrift erosion, and downdrift accretion. Wave refraction from a

perturbation in the shore parallel contours can cause either an even or odd shoreline change.



Since the tapered end solution to diffusion theory is being applied to the data, only

the even components were tested. The top half of Figures 5.4 through 5.10 show the initial

volume density added, the change in volume density after 30, 60, and 150 minutes of waves,

and the even and odd breakdown of the changes. The bottom half adds the initial volume

density and the even changes only. The best fit K values for the tapered end solution are then

drawn through those points on the bottom plots.



Discussion of Even/Odd Analysis and Tapered End Solution

Test 1: Fine Sand, Shape A

The even component (Figure 5.4) in Test 1 is characteristic of the analytical solutions

to beach nourishment evolution, with the maximum erosion occurring at the ends of the

placement area, and the maximum accretion occurring just outside the placement area.

However, the odd component is quite significant, which increases in magnitude as time

progresses. This odd element most likely is due to the spreading sand which changes the way

the waves refract, and/or the sand moving more in the direction of the incoming waves. The

magnitude of the odd component for this test is the largest of all the tests. The location of

the largest accretion in the odd component is at the downdrift end of the initial placement

area. Perhaps the fine sand stays in suspension












Even and Odd Analysis of Volume Change, after 30, 60 and 150 min


300 400
Longshore Distance (cm)


Shoreline Evolution for Tapered Ends, after 30, 60 and 150 minutes
SK = 0.141
0.5 K .

0
0 0.5 1 1.5 2 2.5 3


0 0.5 1 1.5 2 2.5 3


u K= 0.036
0.5 -
0 ,


0 0.5 1 1.5
x/Xo


2 2.5 3


Figure 5.4 Test 1 Fine Sand, Shape A, After 30, 60 and 150
Minutes of Waves; a) Even and Odd Analysis; b) Best Fit Tapered
Ends Solution for the Even Analysis








59

longer, and is thus moved down the beach easier. This fluctuating odd component affects

the best fit sediment transport coefficient seen in the lower plots. The K coefficient

decreases with time because the changes in volume density as time progresses are not

symmetrical. Thus, the changes are not accounted for in the even component.



Test 2: Medium Sand, Shape A

In Test 2 (Figure 5.5), the erosion in the initial placement area is not isolated to just

the shoulders, or edge of the nourishment, as the analytical solution suggests. The even

component shows erosion in the entire initial area, and accretion just outside the shoulders

of the nourishment. In the odd component, the updrift accretion/downdrift erosion scenario

indicates the protruding nourishment is behaving as a littoral barrier of some sort. The K

values are smaller than Test 1, and they vary less with time.



Test 3a: Coarse Sand, Shape A

The total change in volume density for Test 3a (Figure 5.6) is smaller than the

previous tests. The odd component is close to zero. The even component indicates accretion

outside the nourishment area which increases initially, and then remains fairly steady as time

progresses. The ramifications of this come forth through computing the best fit K

coefficient, which decreases with time. Perhaps the fill sand was not compacted well when

placed, allowing the threshold force associated with sediment suspension to initially be less.













after 30, 60 and 150 min.
--Initial
-Actual
.* Even
0 0 Odd


0 100 200 300 400 500


-500
0


100 200 300 400 500
Longshore Distance (cm)


Shoreline Evolution for Tapered Ends, after 30, 60 and 150 minutes


0.5- K = 0.024

0 5 2
0 0.5 1 1.5 2 2.5 3


0 0.5 1 1.5 2 2.5 3


0 0.5 1 1.5 2 2.5 3
x/Xo

Figure 5.5 Test 2 Medium Sand, Shape A, After 30, 60 and 150
Minutes of Waves; a) Even and Odd Analysis; b) Best Fit Tapered
Ends Solution for the Even Analysis


o o
03
E

E
o -500

i 500

0 0

E
o
> -500
c
a( 500

C-
5 0s









61


Even and Odd Analysis of Volume Change, after 30, 60 and 150 min.


100 200 300 400 500


100 200 300 400 500
Longshore Distance (cm)


Shoreline Evolution for Tapered Ends, after 30, 60 and 150 minutes

1K OK =0.096
0.5 .5 2

0
0 0.5 1 1.5 2 2.5 3


0 0.5 1 1.5 2 2.5 3


0 0.5 1 1.5 2 2.5
x/Xo


Figure 5.6 Test 3a Coarse Sand, Shape A, After 30, 60 and 150
Minutes of Waves; a) Even and Odd Analysis; b) Best Fit Tapered
Ends Solution for the Even Analysis


- initial
Actual
+ Even
o Odd


E O
E
0

. -500
a) 0
0)
c 500
0 1
O j


-500
0











Test 3b: Coarse Sand, Shape B

As in Test 3a, the duplicate test, the total change in volume density, and the odd

component are small in magnitude (see Figure 5.7). There is virtually no change in volume

in the center of the nourishment. However, areas adjacent to the middle section experience

erosion. Accretion occurs outside the nourishment. The accretion in this test is unique in

that it is distributed over a large area outside the nourishment, instead of at points

immediately adjacent to the nourishment shoulders. The K coefficients are relatively

consistent over time.


Test 4: Fine Sand, Shape B

In Test 4 (Figure 5.8), the odd component is negligible at first, but it increases in

magnitude with increasing time. The shape of the odd component after 150 minutes is

peculiar, as it does not have solely erosion or accretion on one side. The even component

is characteristic of the analytical solution, although the accretion extends far outside the

nourishment area. The K coefficients are quite large, and their values do not vary with time

as much as was calculated for the fine sand, Shape B run, Test 1.



Test 5: Medium Sand, Shape B

The results from Test 5 (Figure 5.9) show a slight updrift accretion and downdrift

erosion in the odd component after 30 and 60 minutes, indicative of a partial littoral barrier.

However after 150 minutes, there is more erosion updrift than downdrift. Since the waves

are traveling in that direction, it is intuitive to believe that fill sand would also













Even and Odd Anal


E

E
o
-500
S 0
C 500-

e I
a)
Eo

o
0-

- -500
0,
r" 500 0

0-
E





0
o0


of Volume Change, after 30, 60 and 150 min.

S-Initial
--Actual
0 0 n Even
So 0o Odd


100 200 300 400 500


100 200 300 400 500


100 200 300 400 500
Longshore Distance (cm)


Shoreline Evolution for Tapered Ends, after 30, 60 and 150 minutes

01 05K = 0.039
0.5

0
0 0.5 1 1.5 2 2.5 3
I *
o K= 0.064
0.5
0-~~--
0 0.5 1 1.5 2 2.5 3
1
\ K = 0.032
0.5-

0
0 0.5 1 1.5 2 2.5 3
x/Xo

Figure 5.7 Test 3b Coarse Sand, Shape A, After 30, 60 and 150
Minutes of Waves; a)Even and Odd Analysis; b) Best Fit Tapered
Ends Solution for the Even Analysis









64


i and Odd Analysis of Volume Change, after 30, 60 and 150 min.
500
30 Min / initial
-Actua
,. --- o ^. o o n ------- Even
0 Su u u- o~~ 0 Odd


-500
0 100 200 300 400 500 600


100 200 300 400 500


0 100 200 300 400 500
Longshore Distance (cm)


Shoreline Evolution for Tapered Ends, after 30, 60 and
1.5
K = 0.2
0.5
00 1 1.5
0 0.5 1 1.5 2 2.5


150 minutes

36


3


2'
0
>> *^""s- \


K = 0.260


- _


0 0.5 1 1.5 2 2.5 3


1.5
K = 0.199
0.5 -
0
0 0.5 1 1.5 2 2.5
x/Xo


Figure 5.8 Test 4 Fine Sand, Shape B After 30, 60 and 150
Minutes of Waves; a)Even and Odd Analysis; b) Best Fit Tapered
Ends Solution for the Even Analysis


1 ---- I --


I













Even and Odd Analysis of Volume Change, after 30, 60 and 150 min.


E
o

E -500

- 500

oo
0
E
0

-500
) 500
r-
o 0o


-500


0 100 200 300 400 500


0 100 200 300 400 500
Longshore Distance (cm)


Shoreline Evolution for Tapered Ends, after 30, 60 and 150 minutes

K = 0.133
0.5 -

0
0 0.5 1 1.5 2 2.5 3


1.5
x/Xo


Figure 5.9 Test 5 Medium Sand, Shape B, After 30,60 and 150
Minutes of Waves: a)Even and Odd Analysis; b) Best Fit Tapered
Ends Solution for the Even Analysis


-Initial
-Actual
X Even
o Odd









66

move more in that direction. It is interesting that this test and Test 6 (discussed next) are the

only tests that reflects this pattern. The best fit K values are fairly large and consistent over

time.



Test 6: Coarse Sand, Shape B

As mentioned above, the odd component indicates updrift erosion and downdrift

accretion (Figure 5.10). It is as if the fill is migrating downdrift. However, the range of this

updrift erosion and downdrift accretion extends from the center of the nourishment to well

beyond the nourishment limits. This large range is difficult to explain. The even component

shows erosion evenly distributed within the nourishment area, and accretion also occurs

outside the nourishment, far beyond its boundaries. These large even and odd fluctuations

which occur far beyond the nourishment limits is a result of the unexpected downdrift

accretion associated with the total volume change. The change at a distance of 550 cm is

uncharacteristically and unrealistically large.

The time averaged K values were compared with the sediment size used in each

initial profile template (Figure 5.11). Again, the K values for Shape B are larger than those

for Shape A. The fine sand, as usual, has the highest K value for both shapes. This analysis

shows that the medium sand size has the lowest K value, while the K values for coarse sand

are less than fine sand, but more than medium sand. This plot is interesting because there

are very few laboratory and field tests that use sand sizes larger than 0.5 mm. The research

in sediment transport behavior for sand sizes smaller than 0.5 has shown an inverse

relationship between sand size and transportability. This trend







































0 100 200 300 400 500 600
Longshore Distance (cm)


Shoreline Evolution for Tapered Ends, after 30, 60 and 150 minutes
15
0 -
0.5 min K 0.313

0
-0.5
0 0.5 1 1.5 2 2.5 3

0
0.5 K= 0.263
C 6-- 3
60 min \
o0

.0.5
0 0.5 1 1.5 2 2.5 3




150 min

-0.5
0 0.5 1 1.5 2 2.5 3
x/Xo

Figure 5.10 Test 6 Even and Odd Analysis (top) and Best Fit
Tapered Ends Solution for the Even Analysis (bottom): Coarse
Sand, Shape B for the Even Analysis









68

usually is extrapolated to include larger sizes, without considering the presence of a

minimum point in the region around 0.5 mm.


Sediment Transport Coefficient (K) for the Tapered Ends Solution
10 .. .. .. ......





0(' 10-i.oo----------------------
3 SHAPE B
2


7o SHAPE A




10 c I I I I I I I I I
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Median Diameter (mm)
Figure 5.11 Comparison of the Sediment Transport
Coefficient and the Sand Diameter for the Tapered Ends
Solution


Summary of Even and Odd Analysis

A qualitative summary of the even and odd observations shows that for the even

components (Columns El and E2 on Table 5.1), Shape A concentrates the erosion and

accretion activity at the shoulders of the nourishment, and on the beach immediately outside

the nourishment, respectively. Shape B erosion and accretion occur over broader regions.

The strongest correlation in the odd component summary (Columns 01, 02 and 03) was

found between the fine sand tests for each shape. The fine sand tests both showed a strong

pattern of downdrift accretion and updrift erosion. The maximum time averaged values

(Columns E3 and 04) did not show any trends in both the even and odd.

















-0




000 k
uS '- t c d















I o N
o) a>.q


0 .


XIt8
r 0 .-


U 01 0


>I >I >I z


'cla a) m 1--
10 en -1 4

cU -- ------- ------------
oU
-.4
OCU





-I-' a &^-'gz z z

o $ -a







IS) ^ o
C^' o -. -. -.


CU
w5a
.0
(jdX\












5.1.3 Variance

The variance of the nourishment spreading can be computed using equation 2.18. For

a purely diffusive process, the speed at which the variance spreads has been analytically

proven to be equal to twice the diffusion coefficient, G (see equation 2.17). If all other

variables in G are known, then the sediment transport coefficient, K, can be obtained from

the G values. This was calculated for all the tests, and the time averaged values are shown

in Figure 5.13.



K Coefficient Computed Using the Variance Method


SHAPE B



100. :











Method
4 3 S A .. ..


10-2.00 i i i I i i i i ,
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Median Diameter (mm)

Figure 5.13 Comparison of the Sediment Transport
Coefficient and the Sand Diameter Using the Variance
Method




These results are quite different than all the other analysis methods. Shape B values

are still larger than Shape A. However, all K values are 1-2 orders of magnitude larger than

the K values obtained from all the other methods. The fine sand, Shape A run is the least









71

transportable, which is unique for Shape A. Shape B tests show very little variation in K

values.

The reason for these substantially different values could be the emphasis that this

method places on shoreline fluctuations far from the centerline. All changes in the shoreline

are multiplied by the square of their distance from the centerline. Thus, a change towards

the survey area's outer limits is accentuated. These changes are probably due to the increase

in spacing of the surveyed profiles, thus the increase in the margin of error. However, this

method magnifies that margin of error, and overshadows other processes that are occurring

simultaneously.



5.1.4 The DNRBS Model

The DNRBS model, developed by Dean and Grant (1989) is a numerical model, in

which the equations for sediment transport and continuity are solved sequentially. Referring

to Figure 5.14, the shoreline positions are held constant for a time step, while the sediment

transport values are computed. Then the transport values are held constant while the

shoreline positions are adjusted, and the procedure is repeated. The input for the initial

conditions are flexible. Thus, tapered ends can be included in the analysis. Background

erosion can be included in the model, although it is considered to be negligible for the

laboratory tests.






























Figure 5.14 Computational Scheme Used in the DNRBS Numerical
Model.



The boundary conditions that were applied to the model were fixed (Qo = constant)

sediment transport at the ends of the computational domain. The lateral boundary condition

was that the shoreline (y) was zero at x = a. In addition to the flexibility allowed in

defining the initial nourished shoreline, the model considers refraction through the change

in wave speed caused by the bathymetry surrounding the nourishment, which is not

considered in the previous two solutions. The variables involved with the planform

spreading, or the diffusivity coefficient, were defined in the deep water G equation, Equation

2.19. The berm heights away from the beach influenced by the nourishment area were

measured, and the average value was 6.5 cm. The value for h. was visually approximated

by comparing the profiles as time progressed. Most profile fluctuations occurred landward








73

of the 8 cm depth, which was the h. value used in DNRBS. The best fit sediment transport

coefficients, K were ascertained from comparing the measured data to the DNRBS output

for a range of K values (Figure 5.15) using the percent remaining in the initial area versus

time analysis. These K values are plotted against their respective fill sand size in Figure

5.16.

Again, the sediment transport coefficients are very small. In general, most of the best

fit K values generated from DNRBS closely resemble the actual percent remaining results.

Tests 1, 2 and 6 show some deviation from the DNRBS prediction. All three of those tests

show high rates of erosion in the first 30 minutes of waves, and then a decrease in the erosion

rates later. Perhaps this was because the fill sand was not compacted enough when placed.

Test 6 shows accretion during the 60-150 minute time interval, a result of updrift

impoundment. The Shape A results for the DNRBS analysis support the previously stated

theory, that K decreases inversely with the sand diameter. The Shape B results show the

opposite relationship.


5.2 Summary of Results



Sediment Transport Coefficient Values

Table 5.2 is a summary of the sediment transport coefficients computed using the

methods described previously. All of these values are plotted in Figure 5.17 and 5.18.









74


DNRBS Analysis on Laboratory Data, Shape A


0.8
S 0.7
0.8 K=0.019

E 0.0 50 100 150




S^0 50 100 150
1
E 0.9 Medium Sand
a,






0.7 -
0.8 =0.013
0.7
0.6

0 50 100 150
1









0.8 K=0.016
S0.7
0.6











0 50 100 150
0.9 Coarse Sand
0.8 --- K 0.0132
0.7
0.6





















0 50 100 150
Time (minutes)














Figure 5.15 Best Fit K Values using the DNRBS Model
DNRBa) Shape A Resunalysis on Laboratory Data, Shape B Results
0.4C- Fine Sand


0.6
*Fa 0 50 100 150
0.9 Medium Sand
U0.7 0.022
c 0.6
a) 0.5
0 50 100 150





Time (minutes)


Figure 5.15 Best Fit K Values using the DNRBS Model
a) Shape A Results; b) Shape B Results













Average K Coefficient Using the DNRBS Numerical Model


10o W -Shape B



2 ..A Shape A

10-200
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Median Diameter (mm)

Figure 5.16 Comparison of the Sediment Transport
Coefficient and the Sand Diameter as Generated by the
DNRBS Model



Table 5.2 Summary of the Sediment Transport Coefficients using the Various Methods


Sand Size K: M vs. T K: M vs. T K: K:
(mm) Rectangular Tapered Ends Solution: DNRBS Variance
Solution (Walton Analysis)

SHAPE A 0.21 mm 0.038 0.067 0.019 0.248

0.5 mm 0.024 0.022 0.013 1.244

1.0 mm 0.018 0.047 0.0014 0.781



SHAPE B 0.21 mm 0.030 0.219 0.016 2.740

0.5 mm 0.067 0.132 0.022 2.535

1.0 mm 0.050 0.168 0.032 2.974













SHAPE A

K Coefficient Computed Using Various Methods


10- .2.oo I I I I I I I I I
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Median Diameter (mm)

Figure 5.17 The Sediment Transport Coefficients
Computed using Various Methods for Shape A




SHAPE B

K Coefficient Computed Using Various Methods


-*- Rectangular
-A- Tapered Ends
--- DNRBS
-- Variance


10-2E 4 . I i I i . I . i i i ,
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Median Diameter (mm)

Figure 5.18 The Sediment Transport Coefficients
Computed using Various Methods for Shape B








77

Examining all the results from the various analysis, it is clear that the noise in the

variance method overpredicts the K values. If the variance results are ignored, the Shape A

values have a narrower band, and seem to show the inverse trend of K values with sand size

as predicted. A trend in the Shape B results is not as clear. The inconsistencies associated

with the Shape B runs would be interesting to investigate. Perhaps by extending the sand

into the surfzone it introduces more refraction effects than Shape A, the effect of which is

not considered in the analytical or the numerical solutions. Another explanation could be

that Shape B mixes more with the fine native sand, and this fine sand component increases

the sediment transport coefficient values.


5.3 Comparison With Previous Investigators



Before any conclusions can be reached, it would be valuable to compare the results

from the laboratory study with other investigators. Various investigators have computed the

sediment transport coefficient using the CERC equation. Since laboratory tests generally

result in lower K values, it is appropriate to compare only laboratory studies. Table 5.3

describes the experiments from various previous investigators, which are presented in Figure

5.19, along with the findings from this study.














Table 5.3 Summary of Previous Sediment Transport Laboratory Studies

Investigators) Sand Size No. of Method Used to Calculate H,, H, or Wave
(_ mm) Points Sediment Transport H, .. Steepness

Krumbein, 1944 0.5 15 outflow from beach feeder visual varied
average

Saville, 1950 0.3 9 sand trap with pumps average varied

Shay & 0.32 56 sand traps average varied
Johnson,1951

Sauvage & 0.5 3 sand traps average varied
Vincent,1954

CERC BEB, 0.3 2 sand traps with pumps average varied
1962

Readshaw, 1979 0.56 22 sand traps average varied

Vitale, 1981 0.22 15 sand traps H, varied

Kamphuis, 1982 0.18 46 sand traps average varied

Yoo, 1993 0.2, 0.5 8, 4 surveyed volumes average N/A


4
3
2

100.00

u 5
u- 4
L-
w 3
0
0 2
I-
0 10-1.00
a. 8
z

I- 3
k- 2
z
W
S10-2.00
u '7
3
3


LABORATORY

SEDIMENT TRANSPORT
COEFFICIENTS






.i . I.

S : : : i ; ; : :

: i m : ; :


i


o


V
A-


A





0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
MEAN DIAMETER (MM)

Figure 5.19 Sediment Transport Coefficients from Previous Laboratory
Studies vs. Sand Size, Including the Present Study.


* Krubein1944
S Saville 1950
0 Shay and Jdmsi 1951
Sauvage and rce 1954: p26
v CERCBEB1962
o Readshaw 1979
* Vitale 1981
o Kamphiis 192
* Yoo 1959
DorduA: Rectangdiar
Doriem: Tapered Ends
A Danktm: DNRBS









79

The data in Figure 5.19 are very scattered. It is quite evident that more data using

large sand diameters are needed (Figure 5.20). The K values from this study are less than

most of the previous investigators. There are many possible reasons for the significant

scatter in Figure 5.19. As mentioned in Chapter 1, many of the investigators mentioned in

Figure 5.19 note that wave steepness influences sediment transport, but is not included in the

CERC equations. Perhaps the methods used to obtain K introduce and/or eliminate

unmeasured phenomenon. Scaling effects occur in laboratory experiments, and these effects

vary with wave height, period, ripple formations, refraction, sand compaction and porosity,

etc. It also has been mentioned by a number of investigators that monochromatic waves

often exacerbate perturbations in the bathymetry, thus causing the unwanted refraction effects

described in the previous chapter. A definite conclusion from Figure 5.19 is that K is not a

single number, and it can vary by 1-2 orders of magnitude, significantly changing the

magnitude of the longshore sediment transport.


Number of Experiments Done With Each Sand Size

0 This Study

50

0) 40

S30

20



0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Sand Diameter (mm)
Figure 5.20 The Numbers of Sediment Transport
Coefficient Laboratory Tests Performed for Each Sand
Size.















5.4 Sources of Error



The aforementioned variations in K values prompts an examination of possible

sources of error. There are several potential sources of error which will be discussed.



Survey Method

The elevation was measured using a rotating laser-level. The beam width was T 1.5

mm at 30 m away from the instrument. All of the surveys were conducted within 10 m of

the instrument, where the resolution of the beam light is the greatest. However, suppose all

readings were read at a distance of 30 m, the elevation reading would have a T 1.5 mm error.

Each survey covered a 244 cm by 600 cm area. Thus, the most error introduced by the

instrument readings is 127 cm3. The volume of fill sand placed for each run was 100,000

cm3. The maximum instrument reading error would be 0.13%.

As discussed in Chapter 3, the surveys in each run did not always conserve sand. A

number of investigators have mentioned that they have encountered this problem while using

surveys to determine sand movement in the laboratory. They attributed the error to

fluctuations in the bathymetry between profiles, which were not measured. While it seems

like this source of error is very common in all environments, it becomes more pronounced

in the laboratory due to scaling effects. There was an attempt in this survey to use small

spacing (20 cm)between the profiles. However, that still leaves a 20 cm by 244 cm area








81

which was not measured. If the elevation fluctuated between 1-3 cm in the gap not

measured, that would be a 4,880 cm3 14,640 cm3 volume difference, or 5%-15% of the fill

volume. Fluctuations in that range are consistent with those found in Table 5.4. These

inconsistencies do not make as much of an impact in the field. Survey errors also occur due

to inconsistencies in the sand compaction, as the survey rod was prone to sinking in the

vicinity of the waterline. Table 5.4 summarizes the adjustments that were made to conserve

sand for those tests.



Bathymetric Effects

It is believed that the refraction of the waves has caused the evolving nourishments

to not behave as expected. As mentioned in the laboratory preparation section of Chapter

4, there was an attempt to create an initial beach with shore parallel contours. This was

achieved to some degree. However, there was a considerable amount of sand in the basin

outside the region in which the profiles were measured. Since the waves were only 4.8 cm

in deep water, perhaps the wave energy was not enough to mobilize all the sand to create an

ideal equilibrium profile. If the manpower was available, it would have been beneficial to

create an initial planar beach of 1:10 slope before each test, and run the waves for a set

period of time, say 150 minutes. It is believed that the extra sand outside the surfzone may

have dampened the waves. The deep water wave height was 4.8 cm. However, theoretically,

the waves should be larger as they approach the break point. However, the average breaking

wave height was 4.3 cm, an indication that friction is reducing the wave energy. Figure 5.20

presents the bathymetry of the test areas, extended out to the edge of the sand wedge in the











basin. This survey was done after the last tests were run, or the 150 minute survey. Those

tests were the medium sand experiments, Test 2 (between 200-400 cm) and Test 5 (between

800-1000 cm). Perhaps the decrease in wave energy caused by this excess sand is the main

reason why all the K values are so low.



Table 5.4 Summary of Adjustments in the Volume Change Analysis to Conserve Sand

SHAPE A SHAPE B
TEST SURVEY VOLUME NOT PERCENT TEST SURVEY VOLUME NOT PERCENT
CONSERVED OF FILL CONSERVED OF FILL
(CM3) VOLUME (CM3) VOLUME
1 30 4,784 4.7% 5 30 -16,157 -16.2%

1 60 -16,068 -16.1% 5 60 -29,783 -29.8%
1 150 -11,471 -11.5% 5 150 46,520 -46.5%
1 average -9.1% 5 average -37.1%
2 30 10,015 10.0% 6 30 59,078 59.1%

2 60 -2,182 -2.2% 6 60 38,615 38.6%
2 150 -18,765 -18.8% 6 150 35,773 35.8%
2 average -9.7% 6 average 41.0%
3a 30 36,065 36.1% 7 30 16,597 16.6%
3a 60 25,242 25.2% 7 60 26,721 26.7%
3a 150 10,663 10.7% 7 150 43,023 43.0%
3a average 18.7% 7 average 34.5%
3b 30 -3.433 -3.4%
3b 60 6,067 6.1%
3b 150 16,382 16.4%
3b average 10.4%































Offshore Bathymetric Variations:
Possible Source of Refraction Effi


Figure 5.21 Bathymetry of the Entire Sand Wedge in the Wave Basin.


Updrift Sediment Supply


Maintaining an updrift sediment supply was important, as the analytical approaches

applied here consider a constant ambient sediment transport. During the experiments, there

was always sand available on the updrift end of the survey area. However, the volume of

sand available did decrease over time, over the extent of the whole experiment. As the

updrift sand volume decreased, the underlying sand was more compact than the top layers.

Because of the many forces acting on the beach, it is difficult to conclude that there was a

gradient in the ambient sediment transport, which would cause updrift erosion and downdrift








84

accretion. It could be a potential source of error, as a constant sand flow was not monitored

extensively.




5.5 Other Sediment Transport Equations



The fact that sediment transport varies with sand size is an accepted concept by many

investigators. It is evident that there are more parameters involved with sediment transport

other than those present in the CERC equation. As stated previously, in addition to sand

size, investigators have correlated wave steepness, beach slope, wave period and porosity

with sediment transport. Kamphuis (1991) was perhaps the most successful in considering

all of those parameters. Equation 2.20 is a sediment transport equation which he developed

using dimensional analysis. This equation was used to analyze the sediment transport in the

laboratory experiments. The initial planform of the fill was used to calculate the change in

contours, and then the fluctuations in the breaking wave angle. The beach slope values were

calculated by determining the distance from the waterline to -7.8 cm, or the average breaking

depth, for each profile. The breaking wave height was 7.3 cm, and the wave period was 1.08

s. The medium sand diameter varied in the longshore direction, with the fill sand size in the

initial area, and the native sand size outside the placement area. These values were then

compared to the measured sediment transport. However, since only the changes in sediment

transport were measured, the ambient sediment transport was unknown. To compare these

measured and predicted values, the average Kamphuis sediment transport away from the

placement area (considered the ambient sediment transport) was subtracted from the









85

Kamphuis values. The above analysis was performed, and can be found in Appendix C.

There was not a close correlation between the measured values and the calculated Kamphuis

sediment transport values, although the measured and calculated plots had similar maxima

and minima points in the same general locations.


This chapter has analyzed a series of laboratory experiments using a variety of

methods. The results were not as decisive as desired, although they did show weak trends.

The next chapter summarizes this study and the field study, and suggest areas of needed

research.














CHAPTER 6
SUMMARY AND CONCLUSION



6.1 Summary



The purpose of this thesis was to investigate the changes in behavior of nearshore

sediment transport processes in the vicinity of beach nourishment projects when fill sand

size and initial placement geometry were varied. Although in general, cross-shore and

longshore processes occur simultaneously, this study concentrated on the longshore

sediment transport processes.

The success or failure of a beach nourishment project design is solely dependent

on the accuracy of the prediction of the spreading rates. The south site at St. Augustine

Beach (SSAB) was nourished in the Spring of 1996. Conventional design and prediction

methodologies underestimated the spreading of the nourished sand. A further analysis

was needed to re-evaluate the methods used in predicting beach nourishment planform

areas. The difference between the fill and native sand sizes, and the placement of sand

high in the initial construction template were the causes attributed to the projects

"success".

A laboratory experiment was designed and conducted to evaluate the role of fill

and native sand sizes, and the initial placement geometry in beach nourishment evolution.








87

Three sediment sizes: 0.21, 0.5, and 1.0 mm, were placed on a beach of 0.21 mm native

sand, and two different initial template shapes were employed. The results were analyzed

using four methods that employed the diffusion equation, and the sediment transport

variations were compared with a sediment transport equation which considers sand sizes

and beach slopes.


6.2 Conclusions



The monitoring results from the St. Augustine 1996 Beach Nourishment sites

challenged existing beach nourishment theory. The scatter in the experimental results

precluded definitive conclusions. Small scale prototype laboratory experiments are

known to introduce scale effects which contaminate the phenomenon one is trying to

quantify. However, the following inferences may be drawn:



St. Augustine Beach Nourishment Project

1. Both the South St. Augustine Beach (SSAB) and the Anastasia State Park (ASP)

sites are experiencing erosional trends associated with the stabilization of the St.

Augustine Inlet in 1941: -7.4 m/yr at the ASP Site, and -1.2 m/yr at the SSAB

Site.

2. Given the small volume placed and the short length of the placement area, the

SSAB site was expected to lose half of the fill sand in 4 months, based on the

Coastal Engineering Research Center (CERC) recommended design procedures.








88

However, as of January, 1998, 21 months after placement, 65% of the fill was still

on the beach.

3. The Anastasia State Park (ASP) site supported the existing beach nourishment

theory that predicts a decrease in longevity when the nourished beach segment is

short.

Beach Nourishment Laboratory Experiment

4. There was a trend in the laboratory experiments, with one of the initial

nourishment profile groups (Shape A), that supported the conclusion that

transportability increases with decreasing sand size in the fill sand size range of

0.2 mm to 0.5 mm. This was supported using 3 methods of analysis.

5. It was unexpected to find a range of different K vs. sand size trends with the three

methods of analysis used on the laboratory data (excluding the Variance method

for reasons stated previously), as the diffusion equation was the basis of all the

methods. The methods are all the same, with the exception of the initial

conditions, and the inclusion/exclusion of refraction considerations in the depth

of limiting closure region (included in DNRBS). Perhaps these variations are the

result of the sensitivity of initial conditions and nearshore refraction effects in the

predictive models and analytical solutions. The variations between the Shape A

results and the Shape B results also support the previous statement.

6. The results from the experiments showed that the tests with larger fill sand size on

the template that places the sand high on the initial profile had the least




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