Comprehensive sediement budget for the east coast of Florida

JFL/COEL-2002/003

COMPREHENSIVE SEDIMENT BUDGET FOR THE EAST COAST
OF FLORIDA

by

Jonathan James Brown

THESIS

2002

COMPREHENSIVE SEDIMENT BUDGET
FOR THE EAST COAST OF FLORIDA

By

JONATHAN JAMES BROWN

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

2002

For all of their support, love and encouragement, I would like to dedicate this to my
family and friends, especially my parents. They all have a big part in this, and I couldn't
have done this without all of them.

ACKNOWLEDGMENTS

I would like to sincerely thank everyone who played a part in my education at the

University of Florida. I would like to thank my advisor, Dr. Robert G. Dean, for his

support, and for giving me direction so I could complete this thesis. His door was always

open, and he was always willing to answer any question, not matter how simple, or

difficult. I would also like to thank the other members of my committee, Dr. Daniel M.

Hanes, and Dr. Robert J. Thieke. They may not realize it, but they provided a great deal

of help, not just in the courses that they taught, but also with their availability to answer

questions.

Special thanks go to everyone in the Coastal Engineering Lab, especially Sidney

Schofield, Jimmy Joiner, and Viktor Adams. Their constant help and unselfishness were

extremely valuable. Very special thanks go to Jamie MacMahan and Jason Engle for

their help and their time with the surveys and analysis of the data from the surveys.

Lastly, I would like to thank the Florida Sea Grant College Program for generously

funding this project. Without funding from R/C-S-39, "Long-Term Sediment Budget for

Florida's East Coast for Coastal Management," this thesis would not have been possible.

TABLE OF CONTENTS
page

A CKN OW LEDGM EN TS ................................................................................................. iii

LIST OF TABLES ....................................................................................................... vi

LIST OF FIGU RES .......................................................................................................... vii

IN TRODU CTION ......................................................................................................... 1

LON G SH ORE TRAN SPORT ........................................ ................. ............................ 6

Comparison of Qualitative Results for Longshore Transport (WIS Data) ................... 11
N assau County ................................................................................................. 11
Duval County ................................................................................................... 12
St. Johns County .............................................................................................. 13
Flagler County.................................................................................................. 14
Volusia County ................................................................................................ 14
Brevard County ................................................................................................ 15
Indian River County ......................................................................................... 16
St. Lucie County .............................................................................................. 17
M martin County .................................................................................................. 17
Palm Beach County.......................................................................................... 18
Brow ard County............................................................................................... 19
Dade County .............................................. .............................. ....................... 20
Com prison of Longshore Transport at East Coast Inlets ......................................... 46

CRO SS-SH ORE TRAN SPORT ............................................................ ....................50

Sedim ent Budget ..................................................................................................... 50
Results........................................................................................................................... 51
Beach Profiles ......................................................................................................... 55
Results........................................................................................................................... 57

SU M M A RY AN D CON CLU SION S ................................... .........................................68

Sum m ary....................................................................................................................... 68
Conclusions................................................................................................................... 69

BEACH N OU RISHM EN T ................................................................................................71

iv

LIST O F REFEREN CES..............................................................................................74

BIOGRAPHICAL SKETCH ........................................................... ...........................76

LIST OF TABLES

Table page

2-1 Correlation of shoreline change rates from gradient of longshore transport calculated
from WIS data, to shoreline change rates from historical shoreline position
database ............................................................................................................. . 10

2-2 Comparison of longshore transport values at the inlets of the east coast of Florida
obtained from Walton (1973) and values obtained from WIS data from this study.
(x15 filtered from WIS data by averaging 7 points on either side of the
m onum ent in question) ........................................................................................ 48

3-1 Average values of cross-shore transport using accepted longshore transport values
from the USACE, and calculated from WIS data..............................................52

3-2 Summary of recommended A values (m1/3) for diameters from 0.10 to 1.09 mm.
(D ean and D alrym ple, 2001) ................................... .............................................56

3-3 Cross-shore transport calculated from Eq. 3-4 and 3-8 for Little Talbot Island............61

3-4 List of best-fit profile scale parameters from January, 2002 survey data ....................62

3-5 Cross-shore transport calculated from Eq. 3-4 using smoothed profile for January,
2002 survey. Based on UF profiles........................... ............................................63

LIST OF FIGURES

Figure page

1-1 Definition sketch of sediment budget............................. ..................................... 2

2-1 Longshore sediment transport calculated from WIS data using the energy flux
equation for Nassau County................................... ................. ........................... 21

2-2 Measured and calculated shoreline change rates for Nassau County...........................22

2-3 Longshore sediment transport calculated from WIS data using the energy flux
equation for Duval County ...................................................... .......................... 23

2-4 Measured and calculated shoreline change rates for Duval County ............................24

2-5 Longshore sediment transport calculated from WIS data using the energy flux
equation for St. Johns County.................................................. .......................... 25

2-6 Measured and calculated shoreline change rates for St. Johns County........................26

2-7 Longshore sediment transport calculated from WIS data using the energy flux
equation for Flagler County................................................... ............................ 27

2-8 Measured and calculated shoreline change rates for Flagler County.............................28

2-9 Longshore sediment transport calculated from WIS data using the energy flux
equation for V olusia County................................... ..............................................29

2-10 Measured and calculated shoreline change rates for Volusia County........................30

2-11 a Longshore sediment transport calculated from WIS data using the energy flux
equation for Cape Canaveral................................ ................. .............................31

2-1 lb Longshore sediment transport calculated from WIS data using the energy flux
equation for Brevard County .......................................................... ...................32

2-12 Measured and calculated shoreline change rates for Brevard County .......................33

2-13 Longshore sediment transport calculated from WIS data using the energy flux
equation for Indian River County ................................... ........................................34

2-14 Measured and calculated shoreline change rates for Indian River County ..................35

2-15 Longshore sediment transport calculated from WIS data using the energy flux
equation for St. Lucie County.................................................. .......................... 36

2-16 Measured and calculated shoreline change rates for St. Lucie County......................37

2-17 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for M artin County ................................................... ............................ 38

2-18 Measured and calculated shoreline change rates for Martin County .........................39

2-19 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for Palm Beach County ................................... ........................................40

2-20 Measured and calculated shoreline change rates for Palm Beach County .................41

2-21 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for Broward County ................................................. ........................... 42

2-22 Measured and calculated shoreline change rates for Broward County ......................43

2-23 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for Dade County.................................................... .............................. 44

2-24 Measured and calculated shoreline change rates for Dade County............................45

2-25 Relationship between the immersed weight longshore sand transport rate and the
energy flux. (Komar and Inman, 1970) ................................................................47

3-1 Cross-shore sediment transport rates from sediment budget equation with accepted
longshore transport values from the USACE. ...................................................53

3-2 Cross-shore sediment transport rates from sediment budget equation with accepted
longshore transport values from energy flux equation using WIS data...................54

3-3 Profile scale parameter, A, versus sediment diameter, d, and fall velocity, w (Dean,
1987; adapted in part from M oore, 1982)..............................................................56

3-4 Profiles for M monument 7 of Duval County................................................................ 64

3-5 Profiles for M monument 10 of Duval County.................................................................65

3-6 Profiles for M monument 13 ofDuval County.............................................................. 66

3-7 Profiles for M monument 16 ofDuval County.............................................................. 67

A-1 Beach nourishment volumes for the entire east coast of Florida for the period of this
study (1976-1995). Compiled by Julie Rosati from data obtained from Valverde,
Trembanis, and Pilkey (1999), and Kevin Bodge (2000) ........................................73

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

COMPREHENSIVE SEDIMENT BUDGET
FOR THE EAST COAST OF FLORIDA

By

Jonathan James Brown

August 2002

Chair: Dr. Robert G. Dean
Department: Civil and Coastal Engineering

The goal of this thesis is to provide a sediment budget encompassing the sandy beach

portions of the east coast of Florida. The sediment budget includes analysis of the

longshore transport, cross-shore transport, and beach nourishment. Longshore sediment

transport was calculated using data from the Wave Information Study (WIS) conducted

by the Waterways Experiment Station of the U. S. Army Corps of Engineers. The WIS

data were evaluated using the energy flux equation for longshore sediment transport.

Cross-shore sediment transport is implied using sediment budget concepts, known values

of beach nourishment, the calculated values of longshore sediment transport, and total

sediment transport values obtained from shoreline position data. Using this method, it

was found that a net onshore sediment transport exists for the northeast coast of Florida.

Cross-shore sediment transport was also studied in more detail for Little Talbot Island

in Duval County. The cross-shore sediment transport for Little Talbot Island was

analyzed using the theory of energy dissipation rate for cross-shore transport proposed by

Moore, Dean, and Kriebel. The energy dissipation rate concept relates the energy-

dissipation rate of the actual measured profile to the calculated equilibrium beach profile.

Little Talbot Island was surveyed on January 20, 2002. Sediment samples were taken in

conjunction with this survey to calculate the equilibrium beach profiles. An onshore

transport trend for Little Talbot Island is inferred based on comparison of actual profiles

and calculated equilibrium beach profiles.

CHAPTER 1
INTRODUCTION

Consistent with conservation of sediment principles, shorelines change due to the net

flows of sediment into and out from a defined control volume, including the effects of

beach nourishment and sand mining where present. The sediment inflows and outflows

can be represented in the longshore and cross-shore directions and methods are available

for calculating the longshore sediment transport based on wave, sediment and shoreline

characteristics. However, accepted methods for calculating cross-shore transport are not

generally available and these rates must be based on unproven methodology or inferred

from accepted longshore sediment transport rates.

One theory for barrier island formation proposed by de Beaumont (1845) is based on

the presence of onshore sediment transport. Simply stated, his theory simply stated

expresses that a barrier island is formed from the long-term presence of a sustained

onshore transport. The rate of this transport may be low, but when integrated over

thousands of years, the onshore transport volumes can be extremely large.

The sediment budget equation (Dean and Dalrymple 2001) can be used to infer cross-

shore transport as developed below and as illustrated in Figure 1-1.

Flow in the x-direction longshoree):

Vi,, = qx (x + Ax)AyAt
Vo,, = q,(x + Ax)AyAt

Figure 1-1 Definition sketch of sediment budget

Similarly for the y-direction (cross-shore):

V,, = q,(y)AxAt
(1-2)
Vo, := Q ,(y + Ay)AxAt

Net flow into the element can be represented in the x and y directions as follows:

q (x)AyAt q x(x + Ax)AyAt

= q(x)AyAt- q.(x)+ aqx xAyAt=- q AxAyAt (1-3)
ax ox

q,, (y)xAt q, (y + Ay)AxAt

=q,(y)AxAt q, (y)+ q Ay AxAt -q AxAyAt (1-4)
(9. y y 9

Total net flow onto the element can then be expressed as follows:

-j a+ > xAyAt (1-5)
aIx ay )

There is also the possibility of sand being added to the profile as nourishment.

Denoting this in terms of volumetric rate per unit area, s(x,y), the net volumetric increase

on the element Ax by Ay in time At

(9q 9q,.
+ AxAyAt + sAxAyAt (1-6)
ax ay )

The volume of sand on the element can be expressed as follows:

V,(t )= zb(t)AAy

V,(t2 = z(t+At)AxAy= z(t)+ At AxAy (1-7)

Where Zb is the bed elevation of the control volume.

The net volumetric increase can be written as follows:

Zb (t + At)AxAy b (t)AAy =

Z +- t AXAy Zb (t)Axy = z AxAyAt (1-8)
( )at at

Combining the total net flow and the net volumetric change, the conservation of

volume equation can be written as follows:

-Z= -a + a, +s (1-9)
at ax y )

since h+zb=constant where h is the water depth related to a fixed location:

ah azb ah aqx aq-
-= -- -- = ~+-- -s (1-10)
at at at ax Oy

Where h is depth, or -z.

This equation can be integrated across the profile (in the y direction) to yield

AV + =(y aql )At + SAt (1-11)
AXc

in which S is the volumetric nourishment rate per unit beach length and qy, in and qy, out

are the flows in the y-direction at the landward and seaward ends of the control volume,

respectively, and Qx, i, and Qx, out are the inflow of sand and out flow of sand in the x-

direction (Figure 1-1). Selecting qy, in to be sufficiently landward such that it is zero, qy,

out can be expressed as follows:

-AV I(
q1= +-(Q -Q )+s (1-12)
At Ax

The simplest and most straightforward way to obtain cross-shore transport is to

determine it from the sediment budget equation as is indicated in Equation 1-12. This

method requires an accepted value for the longshore transport, knowledge of the total

sediment volume change, and the beach nourishment. The total volumetric change per

unit length of shoreline (AV) can be based on a historical shoreline position database.

Since this shoreline database is a direct measurement of the shoreline position, it will

include all three components of sediment transport. Rosati summarized beach

nourishment placement volumes from data obtained by Valverde, Trembanis, and Pilkey

(1999), and Bodge (2000). Accurate longshore transport values are difficult to calculate.

Longshore transport occurs in three modes: bedload, suspended load, and swash load. It

is still not clear which of these three processes is the dominant factor in longshore

transport due to the variability of wave conditions and sediment characteristics.

Longshore transport cannot be measured directly, so it either needs to be predicted; or

solved for indirectly using shoreline change, or by measuring deposition at some area

such as a jetty, breakwater, inlet, or harbor. Dredging logs at inlets can also be used to

estimate longshore transport, but these cannot be depended on to be accurate due to

inaccuracies in dredging records and bypassing of sediment past the inlet. One method

for calculating longshore transport is based on the energy flux model

K(EC, cos ) Cb in(1-13)
g(S s- lX1- p) Cb

This model uses the energy flux in the longshore direction (ECgcosO)sinO to predict

the longshore transport. This energy flux is based on wave data, which includes wave

height, wave direction, and wave period. This study uses both the values of longshore

sediment transport from U. S. Army Corps of Engineers, and values obtained by the

energy flux method using Wave Information Study (WIS) data from the Waterways

Experiment Station of the U. S. Army Corps of Engineers. These results can then be

employed in Eq. 1-12 to infer gross-shore sediment transport.

A second method of calculating cross-shore transport utilizes a comparison of the

wave energy-dissipation rate of the actual beach profile to that for the calculated

equilibrium beach profile. This method is usually reasonable for predicting the direction

of cross-shore transport; however the magnitude of transport may be questionable. The

wave energy-dissipation rate on the profiles is dependent upon the slope of the profiles.

In general, if the measured beach profile lies above the equilibrium beach profile,

onshore transport exists, and the opposite is true if the measured profile lies below the

calculated equilibrium beach profile. This is demonstrated for Little Talbot Island, which

was surveyed in January, 1999 by the Florida Department of Environmental Protection

(DEP), and January, 2002 by Jason Engle of The University of Florida Civil and Coastal

Engineering Department. Sediment samples were collected at the same time as the

survey taken in 2002 for a concurrent equilibrium beach profile analysis.

CHAPTER 2
LONGSHORE TRANSPORT

Sand transport is usually represented as a function of the wave energy available to the

surf zone system. Longshore transport can be predicted using an energy model, or

determined empirically, within an additive constant, using a historic shoreline database.

The energy flux model relates the longshore transport to the amount of wave energy in

the longshore direction. The energy flux model is expressed as follows:

K(EC, os )b inB (2-1)
pg(S lX1- P) cb

Where, subscript 'b' denotes breaking conditions

Q = Longshore transport

K = Dimensionless Parameter, 0.33 expressed in terms of significant wave height

K = 0.77 for periodic waves.

E = Wave energy

Cg = Group velocity

0 = Wave angle relative to the local contours

C = Wave velocity

p = mass density of medium (e.g. sea water)

g = Acceleration of gravity

s = Specific gravity of sand 2.65

p = Porosity 0.3

For bathymetry characterized by straight and parallel bottom contours, Eq. 2-1 can be

transferred to any point from which data are available using conservation of energy flux

(2-2), and Snell's Law (2-3)

(EC, cos O)b = (EC, cos 0 (2-2)

sin = (sin-0 (2-3)
C C J0

This conversion results in,

K(E'Cg'Cos( -a' ))12 8 ) sin ') 1(2-4)
pg(s -1-p) lpJ npg I C 9 cos(- b)

In Eq. (2-4) denotes the location of the measurement, 3 = azimuth of the outward

normal to the shoreline, a = wave angle relative to North ((P 0a) = 0), and K = 0.78

(breaking wave criterion). Assuming that the waves break approximately perpendicular

to the shoreline, cos (p-ob) 1. Positive transport represents transport from left to right

for an observer looking in the offshore direction.

In this study, the wave data used in the energy flux equation is from the Wave

Information Study (WIS) database developed by the U. S. Army Corps of Engineers

(USACE) Waterways Experiment Station. WIS data is produced from a hindcast

computer model with "stations" represented as points in the model taken at particular

offshore locations. WIS data are available for the Pacific, Gulf of Mexico, Great Lakes,

and Atlantic Coasts of the United States. This study uses the WIS data from the South

Atlantic Coast, which includes the area of interest. The WIS Phase II data set covering

1976-1995, which includes hurricanes and tropical storms, is used for this study. The

WIS data set includes significant wave height, peak period and direction; mean period

and direction, a primary and secondary component of the spectrum, and wind speed and

direction, all presented at three-hour intervals. The significant wave height and mean

period and direction were used in the energy flux model.

The shoreline has been characterized using the latest shoreline positions from the

Florida Department of Environmental Protection Historic Shoreline Database, which is

obtained from their website (www.dep.state.fl.us/beaches/data/his-shore.htm). The

coordinates of the shoreline position were given in the State Plane, NAD 27 horizontal

datum. This allows a simple trigonometric analysis to find the shoreline angle azimuth

(P) between monuments, as the azimuth of the perpendicular of the line connecting the

mean high water (MHW) shorelines between adjacent monuments.

Considering the longshore transport component only, a decrease in longshore transport

(negative gradient in Q) with distance results in a deposition of sand and a corresponding

advancement of the shoreline, whereas an increase in longshore transport (positive

gradient in Q) with distance is associated with erosion. This is based on the equation of

sediment continuity.

S=-v (2-5)
ax 9t

Where

S = Volume rate of beach nourishment per unit shoreline length, and

V = Total volume of sand, per unit beach length

The predicted longshore transport using WIS data was converted to a change in

shoreline position by considering the profile to move landward or seaward without

change in form, ie

s =- -(h. + B)

faQ Sax = -(h. + B) ax
t (2-6)
AQ- SAx= -(h. + B)Ax
dt
dy AQ- SAx
dt Ax(h. + B)

These calculated shoreline change rates were compared to values obtained from the

historic shoreline position database, which were averaged over the same time period.

The historic shoreline position database includes any beach nourishment since the

database reports a direct measurement of MHW shoreline. Because of this, the

contribution of the nourishment quantities (obtained by Rosati from Valverde,

Trembanis, and Pilkey (1999), Bodge (2000)) were subtracted from the historic shoreline

change rate in an attempt to quantify the values of shoreline change caused only by

longshore transport. The plots of shoreline change differ from the measured in the

vicinity of the nourishment areas because nourishment spreading was not taken into

account by the calculation procedure; however, this should not affect the overall results in

the nourishment/spreading regions. Table 2-1 presents the correlation between the

measured and calculated change rates. As seen from this table, two counties correlated

well (max of 0.542), while others did not. The shoreline change rates obtained from the

gradient of the longshore transport calculated from WIS data were smoothed by taking a

moving five point average (2 points north and 2 points south of point in question), 10 (4

points north and 5 points south), and 15 (7 points north and 7 points south). The results

of this correlation can be seen in Table 2-1 with the values for the optimum moving

average displayed. The correlation is noted in the last column of the table with the level

of significance taken from Emery and Thompson, 1997.

Table 2-1 Correlation of shoreline change rates from gradient of longshore transport
calculated from WIS data, to shoreline change rates from historical shoreline position
database.
County Optimum Correlation Coefficient of Degrees of Significance
Filter (r) Determination Freedom (Yes/No)*
(r2)
Nassau x5 0.224 0.05 77 Y(5%)
Duval xl1 0.300 0.09 77 Y(1%)
St. Johns x15 0.179 0.03 205 Y(1%)
Flagler x15 0.083 0.01 97 N
Volusia x15 -0.202 0.04 232 Y(1%)
Brevard x15 0.530 0.28 216 Y(1%)
Indian x15 0.542 0.29 116 Y(1%)
River
St. Lucie xl0 0.210 0.04 112 Y(5%)
Martin x5 -0.312 0.10 124 Y(1%)
Palm Beach x15 -0.119 0.01 224 N
Broward x10 -0.150 0.02 124 N
Dade x15 0.143 0.02 102 N
*Emery and Thompson (1997),

The equation for the correlation coefficient is:

x,-x y, y)
r = 'i= (2-7)
(xi 2 Yg 2

Where x and y denote the two different datasets, and the bar over the x and y represent

the associated mean values.

Correlation is a measure of the strength of the relationship between the two variables,

showing whether large values of one variable are related to large values of another. The

correlation coefficient can range from -1 to +1. Values of-1 and +1 show a perfect

linear relationship between the two data sets. Negative values of the correlation

coefficient represent a linear relationship with a negative slope, meaning that the two

datasets are perfectly inversely correlated. To test the correlation, a level of significance

is determined. The level of significance is dependent on the sample size, and the

correlation. For example, if the level of significance were found to be 5%, it can be

assumed that there is a 95% probability that the correlation between the two variables is

not zero. This does not mean that there is a 95% chance that the two variables are

related, it just means that there exists a 95% chance that the correlation is not zero. The

square of the correlation, r2, represents the sample coefficient of determination (Table 2-

1). The sample coefficient of determination represents the proportion of variation of one

variable that can be accounted for by a linear relationship with the other.

Comparison of Qualitative Results for Longshore Transport (WIS Data)

Nassau County

Results for this county are presented in Figures 2-1 and 2-2 for calculated longshore

sediment transport and shoreline change rates respectively.

Nassau County is the northern county on the east coast of Florida. Monuments 1

through 10 of Nassau County are located inside St. Mary's Entrance and are not included

in this analysis (Figure 2-1 includes these monuments). The longshore transport

calculated from the WIS data increases sharply from Monument 10 to Monument 11.

Rapid changes in calculated longshore transport occur in the immediate vicinity of many

of the inlets along the east coast, and are due to the local changes in shoreline orientation.

South of this monument, from Monument 40 to 74, a steady decrease can be seen. This

reduction signifies a negative gradient, which should cause a shoreline accretion (Eq. 2-

5). This accretion can also be seen in the historical shoreline data, where a positive value

of dy/dt is present of approximately 7 ft/yr. The shoreline of Nassau County has been

nourished throughout, but the largest nourishments occurred from Monument 14 through

Monument 34 with volumes ranging from 110 yd3/ft to 210 yd3/ft. A large amount of

nourishment also occurred between Monuments 55 and 77 with volumes ranging from

180 yd3/ft to almost 340 yd3/ft. Even though the longshore transport gradient suggests

the measured accretion, when the nourishment is subtracted from the shoreline change,

the data indicate that the shoreline would erode without the nourishment. Another large

increase can be seen from Monument 74 to Monument 79, where a large increase in

shoreline angle exists, followed by a decrease at Nassau Sound, located at Monument 82,

where the tidal currents and shoals certainly play a significant role, which is not taken

into account in this analysis. The positive gradient from Monuments 74 to 77 is reflected

in the shoreline data, both with and without nourishment.

For the shoreline change rate plot of Nassau and all subsequent counties if the method

were exact, the curve of shoreline change rate minus nourishment would match the curve

of the shoreline change rate calculated from the gradient of the longshore transport.

Duval County

Results for this county are presented in Figures 2-3 and 2-4 for calculated longshore

sediment transport and shoreline change rates respectively.

A rapid increase in longshore transport from WIS data is evident at the north end of

Duval County, at Nassau Sound. From Monuments 3 to 16, the trend of the longshore

transport is relatively constant, south of which a negative gradient exists. This negative

gradient is also evident in the historical shoreline data, which shows an accretion from

Monument 16 until it approaches the inlet at Monument 22. The longshore transport is

extremely dynamic due to the presence of Ft. George Inlet, and the St. Johns River

entrance, which are located at the south end of Little Talbot Island from Monuments 25

through 31. Another negative trend in the gradient in longshore transport can be seen

from Monument 32 to the south end of the Duval County shoreline. This is also

supported by the positive value of dy/dt from the historical shoreline data with

nourishment included, but when the nourishment was taken into consideration, the

shoreline change based on longshore transport was negative at the locations of the

nourishment. Duval County was nourished with over 160 yd3/ft from Monument 31 to

Monument 50, and over 190 yd3/ft from Monument 60 though Monument 80.

St. Johns County

Results for this county are presented in Figures 2-5 and 2-6 for calculated longshore

sediment transport and shoreline change rates respectively.

The calculated longshore transport rates are relatively uniform to Monument 73, south of

which the longshore transport steadily decreases to the St. Augustine Inlet at Monument

122. The shoreline changes based on historical data do not reflect this negative gradient,

i.e. an accretion. St. Augustine Inlet, ajettied inlet located at Monument 122, is evident

in the calculated longshore transport with the signature change in direction of transport.

The fact that the shoreline advances on the updrift side, and erodes on the downdrift side

is caused by the blockage of longshore transport by the jetties. The shoreline shape

between St. Augustine Inlet and St. Augustine Pier can explain the calculated longshore

transport changes seen between Monuments 122 and 142. The St. Augustine Pier is

located at Monument 142, and the shoreline is heavily armored from Monument 142 to

145. After the initial drop in longshore transport at the pier, the trend is relatively

constant to Monument 156, south of which a negative gradient can be seen towards

Matanzas Inlet at Monument 196/197. This negative gradient is supported by the positive

shoreline changes shown in the historical shoreline data. St. Johns County has been

nourished just south of St. Augustine inlet, but the nourishment occurred in 1996, which

is not within the time frame for this study.

Flagler County

Results for this county are presented in Figures 2-7 and 2-8 for calculated longshore

sediment transport and shoreline change rates respectively.

No inlets exist in Flagler County, because of this; the calculated longshore transport is

relatively constant with the only minor variation caused by differences in shoreline angle.

The shoreline change rates support this with relatively low values close to zero, which

vary randomly along the shoreline, with an average value of approximately zero for

Flagler County. The calculated longshore transport using WIS data is shown to be to the

north throughout Flagler County, which is opposite to the accepted southerly direction.

Volusia County

Results for this county are presented in Figures 2-9 and 2-10 for calculated longshore

sediment transport and shoreline change rates respectively.

The calculated longshore transport using WIS data is shown to be to the north

throughout Volusia County, i.e. opposite to the southward longshore transport which is

the generally accepted direction of longshore transport for the east coast of Florida. The

calculated longshore transport rates for the northern part of Volusia County are quite

variable; however the trend is relatively constant to Monument 84 where a large change

in magnitude occurs. This is likely due to the pier located between Monuments 83 and

84. South of the pier the transport decreases, predicting an accretion of the shoreline.

Once again, the historic shoreline data support this with an accretion of the shoreline

from the pier at Monuments 84 and 85 to Ponce de Leon Inlet between Monuments 148

and 149, which is jettied. The shoreline was heavily nourished with over 190 yd3/ft just

north of this inlet, from Monument 142 to Monument 148 in 1985 and 1989. This can be

seen on the plot of shoreline change minus the nourishment (Figure 2-10), which does not

agree with the gradient in longshore transport obtained based on the WIS database.

Immediately south of this inlet the gradient is once again negative which predicts

accretion on the south side of the inlet, which is consistent with results from the shoreline

data.

Brevard County

Results for this county are presented in Figures 2-11 a, b and 2-12 for calculated

longshore sediment transport and shoreline change rates respectively.

Cape Canaveral is located south of the Volusia/Brevard County border; however,

historic shoreline data do not exist after 1970 for this segment of the shoreline. A

combination of the change in shoreline shape and the wave angle causes the longshore

transport to shift from relatively constant to abruptly changing direction at Monument 90

of Cape Canaveral, after which the transport reaches a peak, then decreases to change

direction at Monument 118. At the most seaward extent of Cape Canaveral, the transport

once again changes direction, drops off, then increases to the inlet at Monument 167 of

the Cape Canaveral data set, and the first regular monument of Brevard County, i.e. south

jetty of Port Canaveral Entrance.

Based on shoreline orientation, the calculated longshore transport (based on WIS data)

initially increases southward then becomes approximately constant at slightly less than

1,000,000 m3/yr to approximately Monument 40. However, the shoreline advances from

Monument 12 through 35 because of beach nourishment from Monument 1 to Monument

82. With the nourishment removed from the shoreline change, the data still show

positive shoreline change rates. South of Monument 40, the transport shows a slight

negative gradient. The historical shoreline data show very little shoreline change, which

is consistent with the relatively low gradient in the transport calculations, and

nourishment. The beach has also been nourished relatively lightly from Monument 1

through 52 with 16 yd3/ft, from Monument 55 through Monument 82 with 6.5 yd3/ft, and

from Monument 106 through Monument 137 with 23 yd3/ft.

Indian River County

Results for this county are presented in Figures 2-13 and 2-14 for calculated longshore

sediment transport and shoreline change rates respectively.

Sebastian Inlet is the only inlet in Indian River County and is located at the northern

county boundary. The effect of Sebastian Inlet, which has sediment bypassing, can be

seen in both the calculated longshore transport, and the shoreline change data. The

shoreline change data do not show erosion south of the inlet; however when the

contribution of the nourishment of 44 yd3/ft was subtracted from the shoreline change

results, the effects of the inlet are evident as erosion south of Sebastian Inlet. Two large

decreases in transport are predicted. The first occurs at Monument 42, which is an area

where the shoreline angle decreases rapidly from 60 and 63 degrees to 56 degrees on

either side at the monument. The second drop occurs between Monuments 88 and 98,

also due to a change is shoreline angle. The decrease in longshore sediment transport

coincides with a predicted accretion of the shoreline, shown in the historical shoreline

data, as expected. The accretion ranges from Monument 88 to 101, then the shoreline

erodes from Monument 101 to 108. This is a good example of the correlation between

the historical shoreline data, and the longshore transport calculations.

St. Lucie County

Results for this county are presented in Figures 2-15 and 2-16 for calculated longshore

sediment transport and shoreline change rates respectively.

Fort Pierce Inlet, located between Monuments 33 and 34, is evident with the signature

reduction of longshore transport north of the inlet, then a rapid increase in longshore

transport south of the inlet. This can also be seen in the shoreline change data with an

accretion on the updrift side and erosion on the downdrift side caused by the lack of

bypassing sand at this jettied inlet. The shoreline just south of this inlet was nourished,

but with inadequate quantities to compensate for the transport deficit. The nourishment

of 87 yd3/ft of sand from 1971 to 1990 has resulted in approximately 5 feet of shoreline

advancement per year. The downdrift side of this inlet has a relatively small amount of

erosion because of the nourishment between Monuments 34 and 46. Other than in the

vicinity of this inlet, the longshore transport and the shoreline are relatively stable.

Martin County

Results for this county are presented in Figures 2-17 and 2-18 for calculated longshore

sediment transport and shoreline change rates respectively.

The effect of St. Lucie Inlet, which is located between Monuments 42 and 43, is not

immediately evident in the calculated longshore transport. The historic shoreline data

show the effect of St. Lucie Inlet more clearly with accretion on the updrift side of the

inlet, and extreme erosion immediately downdrift of the inlet. The calculated longshore

transport rates do not show a negative trend in the gradient north of Monument 60;

however, the shoreline data show a deposition of sand from Monuments 45 through 60

and erosion from Monument 60 to 112. According to the nourishment data, the beach

has only been nourished from Monument 60 to Monument 111. This causes the negative

correlation shown in Table 2-1. This odd correlation can be caused by the heavy amount

of nourishment from Monument 60 to 111 and also the inlet itself. The effect of the

nourishment of 100 yd3/ft of sand from Monument 60 through Monument 111 can be

seen in Figure 2-18.

Palm Beach County

Results for this county are presented in Figures 2-19 and 2-20 for calculated longshore

sediment transport and shoreline change rates respectively.

There is a general trend of decreasing calculated longshore sediment transport in Palm

Beach County, from the WIS database. This general negative gradient should be

associated with positive shoreline advancement, which is also evident in the historical

data prior to the subtraction of the nourishment contributions from the shoreline data.

With nourishment taken into account, the shoreline change rate is negative. The effect of

Jupiter Inlet can be seen in the calculated longshore transport at Monuments 12 and 13;

however the shoreline is eroded on the updrift side, and advances on the downdrift side.

This is the opposite of what is expected from the longshore transport gradient calculated

from the WIS data. The accretion on the downdrift side is attributed to the large

nourishment volume of approximately 70 yd3/ft in 1995. When the effects of the

nourishment are removed from the shoreline data, the erosion on the south side of Jupiter

Inlet is evident even though sediment is bypassed across this inlet. The effect of the Lake

Worth Inlet at Monument 75, which also has sediment bypassed across it, is evident in

the gradient of the longshore transport, and is also evident in the shoreline change data

after the nourishment of approximately 60 yd3/ft is subtracted. These anomalies can be

seen in the negative correlation coefficient in Table 2-1. Additionally, the data do not

pass the significance requirements of the correlation test. The effects of the South Lake

Worth Inlet at Monuments 150 and 151 can be seen in the calculated longshore transport,

but are reasonably small in the shoreline change rate data because sediment is bypassed

across this inlet. The effects of Boca Raton Inlet at Monuments 222 and 223, which also

has sediment bypassed across it, are evident in both the calculated longshore transport,

and the shoreline change data. The effects of the jetties at Boca Raton Inlet can be seen

in the fact that the shoreline is accreting on the updrift side and eroding on the downdrift

side of the inlet. The Palm Beach County shoreline was also nourished from Monument

177 to Monument 189 with approximately 180 yd3/ft, and from Monument 204 through

Monument 213 with approximately 90 yd3/ft.

Broward County

Results for this county are presented in Figures 2-21 and 2-22 for calculated longshore

sediment transport and shoreline change rates respectively.

The effects of Hillsboro Inlet between Monuments 24 and 25, and Port Everglades

Entrance between Monument 84 and 85 are evident in the calculated longshore sediment

transport. Similar to Palm Beach County, the shoreline change is the opposite of that

expected at Hillsboro Inlet which has sediment bypassing. This is reflected in the

negative correlation coefficient. The shoreline change responds in the expected way at

the Port Everglades Entrance, i.e. the shoreline advances on the updrift side of the inlet,

and erodes on the immediate downdrift side based on both the historical shoreline data,

and on the gradient of longshore sediment transport obtained from the WIS database.

The longshore transport gradients for the rest of Broward County are relatively small.

The shoreline data however show erosion for most of the county's shoreline. This net

erosion is apparent after accounting for the large amount of nourishment from

Monuments 40 through 60 (90 yd3/ft), and from Monument 85 through 128 (100 yd3/ft).

Thus, assuming that the nourished areas were eroding, since it is perceived from the

calculated longshore transport that there is no erosion, or accretion, the nourishment has

stabilized the shoreline. Thus, the beach nourishment has spread out, and evolved the

shoreline such that the longshore transport gradients are minimal.

Dade County

Results for this county are presented in Figures 2-23 and 2-24 for calculated longshore

sediment transport and shoreline change rates respectively.

Other than near the north end of the Dade County, the calculated longshore transport is

relatively uniform north of Monument 40. The shoreline data show considerable erosion.

The nourishment of 250 yd3/ft near the north end of Dade County from Monument 5

through Monument 10, and 77 yd3/ft north of Baker's Haulover Inlet account for this.

The effect of Bakers Haulover Inlet, at Monuments 26 and 27, is evident in the longshore

transport calculations. A large number of inlets are present at the south end of the Dade

County shoreline, which account for the large variability of longshore transport.

Government Cut at Monuments 74 and 75 is evident in the shoreline data, which is then

followed southward by a decrease of shoreline advancement on the south side of the inlet.

This is likely due to the small amounts of beach nourishment of approximately 16 yd3/ft

placed in this region, which is subtracted from the historic shoreline data, but still causes

an anomaly in the data. South of Bear Cut at Monuments 89 and 90 the shoreline shows

a net advancement, again due to the large amount of beach nourishment.

Nassau County
Longshore Transport from WIS Data

2.00E+06

1.50E+06-
St. Mary's
Ent ance
1.00E+06 ----

5.00E+05 ----- ----- ----- .....--- ------_

"^O.OOE+O0 ....... ,J-- ". .-------.....-- ^---------------

S20 30 40 50--. 60 70

-5.00E+05 -

-1.00E+06

-1.50E+06

-2.00E+06
Monument

Figure 2-1 Longshore sediment transport calculated from WIS data using the energy flux equation for Nassau County

Nassau County
Shoreline Change Rate

- --- Measured dy/dt
dy/dt-Nourishment
WIS Average (X5)

Monument

Figure 2-2 Measured and calculated shoreline change rates for Nassau County

Duval County
Longshore Transport from WIS Data

2.00E+06

1.50E+06

Ft. George
assau Inlet
1.00E+06 foundd

I I

S.00E+00
S10 20 30 40 50 60 70

-5.00E+05 ,

St. Johns
-1.00OE+06iver
river

-1.50E+06

-2.00E+06
Monument

Figure 2-3 Longshore sediment transport calculated from WIS data using the energy flux equation for Duval County

Duval County
Shoreline Change Rate

- - - Measured dy/dt
- dy/dt-Nourishment
--WIS Average (X1O)

Monument

Figure 2-4 Measured and calculated shoreline change rates for Duval County

St. Johns County
Longshore Transport from WIS Data

2.00E+06- -

1.50E+06

St. Augustir e M ta
1.00E+06 let. r

5.00E+05 -- -

o 0.00E+00. 00_-- -
0 10 20 30 4 50 60 70 80 90 0 10 1 10 1i0 1(0 10 10

-5.00E+05 -- -

-1.00E+06

-1.50E+06

-2.00E+06 -- -
Monument

Figure 2-5 Longshore sediment transport calculated from WIS data using the energy flux equation for St. Johns County

St. Johns County
Shoreline Change Rate
(St. Johns County was not nourished between 1976 and 1995)

-Measured dy/dt
-WIS Average (X15)

Monument

Figure 2-6 Measured and calculated shoreline change rates for St. Johns County

Flagler County
Longshore Transport from WIS Data

2.00E+06

1.50E+06

1.00E+06

5.00E+05

O.OOE+00

-5.00E+05

-1.00E+06

-1.50E+06

-2.00E+06

1
V-~

0, 2

!.. ,,_., 40o 5
V --

*- 1 r

E

0 7

Monument

Figure 2-7 Longshore sediment transport calculated from WIS data using the energy flux equation for Flagler County

I I ( I I )

0

0 f
"/-^y

0-~,,ch/49

Flagler County
Shoreline Change Rate
(Flagler County was not nourished from 1976-1995)

- Measured dy/dt
-WIS Average (X15)

Monument

Figure 2-8 Measured and calculated shoreline change rates for Flagler County

6

4

2

0

-2

-4

-6

-8

Volusia County
Longshore Transport from WIS Data

2.00E+06

1.50E+06 -

1.00E+06 --.

Ponce
deeon Inlet
5.00E+05

S0.00E+00 ---- 1---
a0 (10.0 1 1 130 140 1 0 1(100 10 100 200 20 20 230 240

-5.00E+05 4 -

-1.00E+06

-1.50E+06

-2.00E+06
Monument

Figure 2-9 Longshore sediment transport calculated from WIS data using the energy flux equation for Volusia County

Volusia County
Shoreline Change Rate

----- Measured dy/dt
dy/dt-Nourishment
- WIS Average (X15)

Monument

Figure 2-10 Measured and calculated shoreline change rates for Volusia County

Cape Canaveral
Longshore Transport from WIS Data

2.00E+06

1.50E+06- --

1.00E+06

5.00E+05 -

o 0.00E+00 ------------------------------ ---
0 6) 10 20 30 40 50 60 70 80 9D 100 1'0 1A 10 I 0 0 1'

-5.00E 10f5 V_

-1.00E+06

-1.50E+06

-2.00E+06 ------
Monument

Figure 2-1 la Longshore sediment transport calculated from WIS data using the energy flux equation for Cape Canaveral

Brevard County
Longshore Transport from WIS Data

2.00E+06

1.50E+06

1.00E+06

5.00E+05

S0OOE+00 -- ----
010 20 31 40 51 60 70 80 90 100 1 0 1!0 130 140 1!0 1 0 1 iO .I0OA2 0

-5.00E+05

-1.00E+06

-1.50E+06 -

-2.00E+06 --.
Monument

Figure 2-1 Ib Longshore sediment transport calculated from WIS data using the energy flux equation for Brevard County

astian
let

i

20

- --- Measured dy/dt
dy/dt-Nourishment
W IS Average (X15)

Monument

Figure 2-12 Measured and calculated shoreline change rates for Brevard County

Brevard County
Shoreline Change Rate

Indian River County
Longshore Transport from WIS Data

2.00E+06
Se astian
nlet
1.50E+06

1.00E+06

5.00E+05 ------- -- '- A ... _-- --

0 1 20 0 50 60 70 80 90 1 100 110

-5.00E+05
I-I

-1.00E+06

-1.50E+06

-2.00E+06 ---- -- ---- ----- ____...__--
Monument

Figure 2-13 Longshore sediment transport calculated from WIS data using the energy flux equation for Indian River County

Indian River County
Shoreline Change Rate

----- Measured dy/dt
- dy/dt-Nourishment
- WIS Average (X15)

Monuments

Figure 2-14 Measured and calculated shoreline change rates for Indian River County

St. Lucie County
Longshore Transport from WIS Data

2.00E+06 ---

1.50E+06 -

1.00E+06--
\

5.00E+05 j-- -,

O.OOE+OO0
a( 10 20 30 40 50 60 70 80 9 100 10
:t. Pierce
-5.00E+05 Inlet- -- -

-1.00E +06

-1.50E+06

-2.00E+06
Monument

Figure 2-15 Longshore sediment transport calculated from WIS data using the energy flux equation for St. Lucie County

St. Lucie County
Shoreline Change Rate

----- Measured dy/dt
dy/dt-Nourishment
WIS Average (X10)

Monument

Figure 2-16 Measured and calculated shoreline change rates for St. Lucie County

Martin County
Longshore Transport from WIS Data

Monument

Figure 2-17 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Martin County

2.00E+06

1.50E+06

1.00E+06

5.00E+05

O.OOE+00

-5.00E+05

-1.00E+06

-1.50E+06

-2.00E+06

Martin County
Shoreline Change Rate

----- Measured dy/dt
dy/dt-Nourishment
WIS Average (X5)

Moument

Figure 2-18 Measured and calculated shoreline change rates for Martin County

Palm Beach County
Longshore Transport from WIS Data

2.00E+06 ---
Jupiter
nlet

1.50E+06 ..

SLake Worth
1.00E+06 --nle Lake -Boc Rato
S". Worth Inlet nlet

5.00E+05 ------------------------------------

a; ...'* """ '1' 4, 7,
5.00E+05 -

O O O E + O 0 0 --

C( 10 20 30 40 50 60 70 80 90 100 110 1:0 11:0 1-.0 11i0 1(>0 1'0 160 10 20 200 2"0 2:!0 23

-5.00E+05 -

-1.00E+06 O

-1.50E+06

-2.00E+06
Monument

Figure 2-19 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Palm Beach County

Palm Beach County
Shoreline Change Rate

.---- Measured dy/dt
- dy/dt-Nourishment
--WIS Average (X15)

Monument

Figure 2-20 Measured and calculated shoreline change rates for Palm Beach County

20

10

0

S-10

S-20

-30

-40

-50

Broward County
Longshore Transport from WIS Data

2.00E+06

1.50E+06 -

1.00E+06 Hillsboro Port
Inlet Everglades

5.00E+05
5.00E+05 -- -------- ----- ------------- ------ -- --

'- 0.OOE+00
S0 10 20 30 40 50 6 70 80 90 100 1 0 1 0 130

-5.00E+05

-1.00E+06

-1.50E+06

-2.00E+06-
Monument

Figure 2-21 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Broward County

Broward County
Shoreline Change Rate

-10

-15

-20

Hillsbor
Inlet

i ----t-------IF-N-- ---+ I .

Port
verglac

I __ -_ p I I - -9

Nouri hment
d

7

DO "8
0 8

ourish ent

!0 130 --- Measured dy/dt
dy/dt-Nourishment (ft/yr)
S WIS Average (X10) ft/year

Monument

Figure 2-22 Measured and calculated shoreline change rates for Broward County

V~J

," 2d '

d ~1..1~

1

Dade County
Longshore Transport from WIS Data

2.00E+06 --

1.50E+06

1.00E+06 Baker's Government
Haulover Cut Bear
Cul
5.00E+05

O.OOE+00 L ---
0' 10 20 30 40 50 60 70 B0 9 100 1 0

-5.00E+05
Norris
Cut
-1.00E+06

-1.50E+06 -

-2.00E+06
Monument

Figure 2-23 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Dade County

Dade County
Shoreline Change Rate

- - - Measured dy/dt
dy/dt-Nourishment (ft/yr)
- WIS Average (X15) ft/year

Monument

Figure 2-24 Measured and calculated shoreline change rates for Dade County

Comparison of Longshore Transport at East Coast Inlets

The longshore transport values calculated by Walton (1973) were compared to the

longshore transport calculated from WIS data. This will provide a more direct

comparison of two different methods of calculation. Walton used a longshore energy

flux model which was very similar to the one used in this study, except the waves were

based on SSMO observations, i.e. ship board observations of wave height, period and

direction, and the waves were transformed to shore accounting for friction and

percolation with the "friction-percolation coefficient," Kfp. Walton's calculations were

based on

Q = 125E,

Ea = EoC cos)K sina 24(3600) (2-9)
(np b 106

Where,

Q = Longshore transport in cubic years per day

Ea = Longshore energy flux in millions of ft. lbs. per day per foot of beach

Eo = yHo2/8 = the deep water surface energy density

y = specific weight of seawater = 64 lbs/ft3

Ho = deep water wave height in feet

Cgo = deep water wave group velocity in ft/sec

(o = deep water angle of wave approach to coastline

ab = breaking angle of wave approach to coastline

Kfp = friction-percolation coefficient, Bretschneider and Reid (1954)

In 1973, when Walton conducted his studies, there were only 5 wave gages along the

Florida coast. None of those wave gages measured wave direction, which is a critical

47

parameter for calculating the longshore transport. The only wave data that existed which

included wave direction was data taken by ships at sea, and assembled by NOAA.

The longshore sediment transport model applied in this report uses the dimensionless

parameter K = 0.77 for breaking wave height found by Komar and Inman (1970), which

was converted to 0.33 since significant wave heights are presented in the WIS data.

Komar and Inman found their coefficient by plotting the immersed weight sediment

transport rate to the longshore component of the energy flux. The dimensionless

coefficient of 0.77 was the value that fit the data best.

o El Moreno Beach
Silver Strand Beach

Y loo
.i i

SI I I

10' 0 10' 10- 10'
(ECn)b cos ab erg/sec-cm

Figure 2-25 Relationship between the immersed weight longshore sand transport rate and
the energy flux. (Komar and Inman, 1970)

Table 2-2 presents the values of longshore sediment transport obtained by Walton

(1973), the USACE, and values obtained in this study using WIS data. Even though both

Walton's values, and the values calculated from the WIS data are based on the energy

Table 2-2 Comparison of longshore transport values at the inlets of the east coast of
Florida obtained from Walton (1973) and values obtained from WIS data from this study.
(xl5 filtered from WIS data by averaging 7 points on either side of the monument in
question)
Inlet Qnet from Walton Qnet from USACE Q from WIS Data
(yd3/yr) (yd3/yr) (yd3/yr) (x 5)
St. Mary's Entrance 200,000 550,000 N/A
St. John's River 250,000 480,000 123,000
St. Augustine Inlet 380,000 440,000 -265,000
Matanzas Inlet 290,000 440,000 -326,000
Ponce De Leon Inlet 180,000 500,000 -616,000
Port Canaveral Inlet 250,000 360,000 153,000
Sebastian Inlet 160,000 300,000 -5,000
Ft. Pierce Inlet 140,000 225,000 553,000
St. Lucie Inlet 200,000 230,000 623,000
Jupiter Inlet 240,000 230,000 739,000
Lake Worth Inlet 380,000 230,000 293,000
S. Lake Worth Inlet 280,000 230,000 151,000
Boca Raton Inlet 280,000 150,000 176,000
Hillsboro Inlet 280,000 100,000 167,000
Port Everglades Inlet 270,000 50,000 179,000
Baker's Haulover 270,000 20,000 178,000
Inlet
Government Cut 270,000 20,000 91,000

flux model, the two sets of results do not correlate well, especially for the northern

inlets of Florida. The discrepancy is most likely due to the two different sources of wave

data for the studies. When compared to actual measured wave heights from the National

Data Buoy Center, at similar points in space, the WIS hindcasts correlate relatively well

(r = 0.509, for 2759 degrees of freedom); however predictions of longshore sediment

transport also require wave direction, and wave period. The results obtained by Walton

are much less variable along the coast. Walton stated that it has been shown that the

wave observers are biased to characterizing the wave direction as N, E, S, W, NE, SE,

SW, and NW. This bias as well as the incompleteness of this dataset is probably the

major reason for the lack of variability. WIS hindcast data include wave direction every

49

three hours reported to the degree compared to the 45 degree segments of the observed

wave data used by Walton. The values of longshore transport provided by the USACE

are the most direct measurement of longshore transport of the three, and are based on the

rate of updrift sediment accumulation at the jetties of the inlets (Dean and O'Brien,

1987).

CHAPTER 3
CROSS-SHORE TRANSPORT

Sediment Budget

As discussed previously, using the historical shoreline position data, a value for dy/dt

was determined for approximately the same 20-year period of the WIS data. In this

chapter the sediment transport is calculated from the shoreline change rate using the

continuity equation, and assuming an equilibrium beach profile.

aQ av
(h.+ B)d (3-1)
ax at dt

where

h* = Depth of closure

B = Berm height

= Average shoreline change rate between Xo and x
dt

The value calculated from the shoreline change data are considered to be the total

volume change rate into the system, which includes the longshore transport, the cross-

shore transport, and the beach nourishment. With the assumed amount of volume change

rate, the accepted values for longshore transport, and the beach nourishment volumes, the

cross-shore transport can then be calculated, using the sediment budget equations from

Chapter 1 (Equation 1-12), where the total volume change rate is equal to AV/At.

-AV 1 -
yo= +V 1 -Qx )+S (1-12)
At Ax ,

Results

The values of longshore transport from the USACE were used to obtain the qy, out

values presented in Figure 3-1. It can be seen in Figure 3-1, that when the USACE

values for longshore transport are used to solve for values of cross-shore transport, the

general result is onshore transport for the section of the Florida coastline north and south

of Cape Canaveral. A gap in the results occurs at Cape Canaveral because the historical

shoreline database does not include surveys after 1975. The average cross-shore

transport value for the entire east coast of Florida is in the onshore direction at

approximately 2.8 yd3/year per foot of shoreline. An onshore transport of 2.8 yd3/year

per foot of shoreline translates to approximately 3 feet/year of shoreline accretion,

considering (h*+B) = 25 feet. It is emphasized that this value accounts for the effect of

beach nourishment.

The values of cross-shore transport using longshore transport values calculated from

WIS data can be seen in Figure 3-2. The average resulting cross-shore transport using

longshore transport values derived from WIS data is just over 1.7 yd3/year per foot of

shoreline in the onshore direction. An average onshore transport of 1.7 yd3/year per unit

length of shoreline translates to approximately 1.8 feet of shoreline accretion, considering

(h*+B) = 25 feet. Since both of the representations of cross-shore transport result in

onshore transport, the shoreline should accrete, on average, over time without any

disturbances.

Large values of calculated onshore and offshore transport occur at the inlets along the

east coast of Florida. This is caused by the large shoreline change rates that occur at

these inlets which cause large values for AV/At which in turn cause large values of cross-

shore transport when calculated from Eq. 1-12. These variations at the inlets cancel when

considering the large scale of the entire east coast of Florida. The trend line for the

values calculated using USACE results for longshore transport shows a decrease of

onshore transport from Nassau County toward Cape Canaveral. South of Cape Canaveral

to Dade County, the trend line shows an increase of onshore transport. The cross-shore

transport calculated using the longshore transport values obtained from WIS data have a

constant trend which is dominated by the average onshore transport of approximately 1.8

yd3/year per foot of shoreline.

Table 3-1 Average values of cross-shore transport using accepted longshore transport
values from the USACE, and calculated from WIS data.
Qy, USACE Qy, WIS
Nassau -9.6 yd3/ft/yr -2.0 yd3/ft/yr
Duval -7.9 yd3/ft/yr -10.5 yd3/ft/yr
St. Johns -0.85 yd3/ft/yr -2.2 yd3/ft/yr
Flagler 0.25 yd3/ft/yr 2.6 yd3/ft/yr
Volusia -3.1 yd3/ft/yr -5.7 yd3/ft/yr
Brevard 0.048 yd3/ft/yr 4.2 yd3/ft/yr
Indian River -0.47 yd3/ft/yr -2.7 yd3/ft/yr
St. Lucie -0.82 yd3/ft/yr 3.5 yd3/ft/yr
Martin -2.9 yd3/ft/yr -2.5 yd3/ft/yr
Palm Beach -1.7 yd3/ft/yr -0.20 yd3/ft/yr
Broward -3.6 yd3/ft/yr -4.2 yd3/ft/yr
Duval -6.0 yd3/ft/yr -5.0 yd3/ft/yr
Total -2.8 yd3/ft/yr -1.7 yd3/ft/yr

Cross-Shore Transport
qy=(-AV/At(from dy/dt))+(AQx, USACE/AX)+(S/Ax)

Distance Along the FL Coastline (miles)

Figure 3-1 Cross-shore sediment transport rates from sediment budget equation with accepted longshore transport values from the
USACE.

Cross-Shore Transport
qy=('AV/At(from dyldt))+(AQx, Wis/AX)+(S/Ax)

2500

2000

1500

1000

500

0

-500 _= II '

-1000

-1500

-2000
Distance Along the FL Coastline (miles)

Figure 3-2 Cross-shore sediment transport rates from sediment budget equation with accepted longshore transport values from energy
flux equation using WIS data

Beach Profiles

Cross-shore transport can also be implied from a comparison of beach profiles. Moore

(1982) was the first to develop this hypothesis, followed by Kriebel (1982), and Kriebel

and Dean (1985). The theory is based upon the concept that for a uniform sand size

across a profile, the wave energy-dissipation rate per unit water volume is uniform. This

is the same basis used to develop the equilibrium beach profile, which is represented by;

h(y)= Ay2/3 (3-2)

where

h = water depth

y = distance from mean water line (MWL) in the offshore direction

A = profile scale parameter, which is a function of energy-dissipation rate (D), and

indirectly sediment size (d). (Figure 3-3, and Table 3-2)

For the case of nonuniform sediment sizes, the following is valid:

h(y)= (h/2 + A /2yy,,))/3 (3-3)

where yn
and yn+1.

According to theory, the cross-shore sediment transport is dependent upon the

difference in the energy-dissipation rate for the particular profile and the dissipation rate

for the equilibrium beach profile.

q, = K(D D. ) (3-4)

where

qy = volumetric cross-shore transport in the offshore direction

Sediment Fall Velocity, w (cm/s)

0.01 I _I I I I I
0.01 0.1 1.0 10.0 100.0
Sediment Size, D (mm)

Figure 3-3 Profile scale parameter, A, versus sediment diameter, d, and fall velocity, w
(Dean, 1987; adapted in part from Moore, 1982)

Table 3-2 Summary of recommended A values (mi/3) for diameters from 0.10 to 1.09
mm. (Dean and Dalrymple, 2001)
d(mm) 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09
0.1 0.063 0.0672 0.0714 0.0756 0.0798 0.084 0.0872 0.0904 0.0936 0.0968
0.2 0.100 0.103 0.106 0.109 0.112 0.115 0.117 0.119 0.121 0.123
0.3 0.125 0.127 0.129 0.131 0.133 0.135 0.137 0.139 0.141 0.143
0.4 0.145 0.1466 0.1482 0.1498 0.1514 0.153 0.1546 0.1562 0.1578 0.1594
0.5 0.161 0.1622 0.1634 0.1646 0.1658 0.167 0.1682 0.1694 0.1706 0.1718
0.6 0.173 0.1742 0.1754 0.1766 0.1778 0.179 0.1802 0.1814 0.1826 0.1838
0.7 0.185 0.1859 0.1868 0.1877 0.1886 0.1895 0.1904 0.1913 0.1922 0.1931
0.8 0.194 0.1948 0.1956 0.1964 0.1972 0.198 0.1988 0.1996 0.2004 0.2012
0.9 0.202 0.2028 0.2036 0.2044 0.2052 0.203 0.2068 0.2076 0.2084 0.2092
1.0 0.210 0.2108 0.2116 0.2124 0.2132 0.2140 0.2148 0.2156 0.2164 0.2172

K = dimensional constant (different from K in longshore transport equation)

= 2.2x106 m4/N (Moore, 1982), or 1.13x10-3 ft4/lb

D = energy-dissipation rate for the profile, and the subscript "*" represents the

equilibrium beach profile

When D is greater than D., the turbulence will be greater than when D is equal to D*,

and will cause offshore sediment transport. When D is less than D., the opposite is true,

and onshore sediment transport is implied.

The energy-dissipation per unit water volume can be expressed as a function of grain

size:

1 dF
D(d)=
h dy'

hD(d)= (3-5)
dy'
-h(dj > 2 gdh
D(d)= 5 pgK2 gh-
16 dy

where

F = wave energy flux

y' = shore normal directed onshore

For equilibrium beach profiles, the energy-dissipation rate can be determined directly

from the profile scale parameter using the following equation.

2/3
24D.
S= 2 (3-6)
A 5 pgK2 J

It can be seen from Eq. 3-5 that the energy-dissipation is dependent upon beach slope

consistent with the Moore, Kriebel, and Dean concepts. The energy-dissipation is also

dependent upon water depth, but to a lesser degree due to the square root.

Results

This study concentrates on Little Talbot Island, which is located just north of

Jacksonville, FL, in Duval County. Little Talbot Island is bounded by Nassau Sound on

the north, and Fort George Inlet on the south and encompasses Monument 1 through 25

in Duval County. The last shoreline survey of Little Talbot Island conducted by the

Florida Department of Environmental Protection (DEP) was in January, 1999 and

includes profiles at each of the 25 monuments on Little Talbot Island. Jason Engle of the

University of Florida Department of Civil and Coastal Engineering also surveyed profiles

on January 20, 2002 in conjunction with the present study. This survey was conducted

using the Department's wave runner, which was equipped with an echo sounder and a

Global Positioning System (GPS). The data logger onboard the wave runner coordinates

the depth from the echo sounder with the GPS position to generate the data file for the

profile. This is relatively automated and provides a much more precise survey with more

data points that is accurate to within approximately plus or minus 5 cm vertically

(MacMahan, 1991). To provide the basis for calculating equilibrium profiles, surface

sediment samples were taken every third monument, starting with Monument 7, by

dragging a bucket at approximate 1000 ft intervals cross-shore, along with grab samples

taken from the beach face. The sediment samples were analyzed for sediment size using

two methods as described below.

The first method of sediment characteristic measurement and analysis was through the

use of sieves, a common method among geotechnical engineers, and involves the uses of

screens with different size openings to segregate different sediment sized particles. Since

sieve analysis is impractical for sediment sizes less than 0.075 mm the sediment is first

washed through the number 200 sieve to remove any sediment less than 0.075 mm in

diameter. Sediments smaller than 0.075 mm are considered silts and clays, which are

relatively easily suspended in the surf zone. Because silts and clays remain suspended

they tend to be transported out of the surf zone, and do not contribute to the profile

stability. After the sediment is washed, and dried in an oven, it is sorted through the

sieves using a RoTap. The sizes of sieves that were used for this analysis were number

10 (2 mm), 20 (0.841 mm), 30 (0.595 mm), 50 (0.297 mm), 60 (0.25 mm), 70 (0.212

mm), 80 (0.177 mm), 100 (0.149 mm), 120 (0.125 mm), 140 (0.106 mm), 170 (0.09 mm),

and 200 (0.075 mm). The sieves are then weighed to measure the amounts of the various

sized sediments remaining on the sieves. This distribution is then used to obtain the

median sediment size, on which the profile scale parameter (A) is dependent (Figure 3-3,

and Table 3-1).

The second method used to analyze the sediment is based on fall velocity. This should

provide a more direct link to the equilibrium beach profile since for the equilibrium beach

profile theory, the profile scale parameter is linearly related to the fall velocity (on a log-

log plot), as can be seen in Figure 3-3 (Dean 1987). The rapid sediment analyzer (RSA)

was used for this analysis. The RSA functions by dropping a sample of sediment from a

specified height through a column of water. A pan at the bottom of the water column

collects the sediment, which is weighed by a load cell at certain intervals of time. The

distance the sediment travels through the water column (246 cm for our apparatus) is

divided by the time required for the sediment to reach the pan to find the fall velocity

through water. The approximate sediment sizes can then be determined from this

distribution of fall velocities using the following formula by Gibbs (1971).

3v + 9v2 + gd2(s- 10.003869 + 0.02480d)
Wo = (3-7)
0.011607 + 0.07440d

where

wo = settling velocity (cm/s)

d = sediment grain size diameter (cm)

v = fluid viscosity (cm2/s)

Just as was done with the distribution obtained by sieve analysis, the median grain size

is extracted from the distribution obtained from the RSA.

These sediment sizes were used to calculate equilibrium beach profiles using Eq. 3-3.

These profiles were then compared, using Eq. 3-4, to the profiles measured by the DEP in

1999, and to the profiles surveyed in January 2002. The energy-dissipation rates for the

measured profiles were calculated at each measurement of elevation using the individual

slopes at those points. The energy-dissipation rates for the equilibrium beach profiles

were calculated using the profile scale parameter, and Eq. 3-6. The cross-shore transport

was then calculated for each measurement of elevation using Eq. 3-4. A weighted

average of the cross-shore transport was taken from the MWL to the point corresponding

to 15 ft of depth. The average was only taken to 15 ft of depth due to the fact that

equilibrium beach profiles have been found to be representative to only 13 to 16.5 feet of

depth. (Charles, 1994) The weighted average is found by multiplying the individual

cross-shore transport rates by the Ay values separating the sample points and normalizing

as

s,Toal A (3-8)
qAy,

where

qs, = the individual cross-shore transport calculation

Ayi = distance separating the individual cross-shore transport rates in the y-direction

qs, Total = the weighted average for the section of interest

The average cross-shore transport values calculated from profiles and sediment

sampled from January, 2002 was 1,841 yd3/ft/yr onshore from the sieve data, and 1,451

Table 3-3 Cross-shore transport calculated from Eq. 3-4 and 3-8 for Little Talbot Island.
January, 2002 January, 1999 (DEP)
Profile Sieve RSA Sieve RSA
R-07 -1314 yd3/ft/yr -1316 yd3/ft/yr -1143 yd3/ft/yr -1302 yd3/ft/yr
R-10 -2427 yd3/ft/yr -1190 yd3/ft/yr -2039 yd3/ft/yr -1185 yd3/ft/yr
R-13 -1594 yd3/ft/yr -1659 yd3/ft/yr -13258 yd3/ft/yr -13298 yd3/ft/yr
R-16 -2030 yd3/ft/yr -1637 yd3/ft/yr -2288 yd3/ft/yr -1715 yd3/ft/yr
Average -1841 yd3/ft/yr -1451 yd3/ft/yr -4682 yd3/ft/yr -4375 yd3/ft/yr

yd3/ft/yr onshore from the fall velocity data. This can be compared to the values

calculated using the DEP's profiles taken in January of 1999. The cross-shore transport

values calculated from the DEP profile are both onshore with quantities of 4,682 yd3/ft/yr

using the sieve data, and 4,375 yd3/ft/yr using the RSA data. This large difference

between the 2002 and 1999 surveys can be attributed to Monument 13. The sediment

used to determine the equilibrium beach profile at the beach face was coarse relative to

the other profiles. The reason this anomaly does not show up in the calculations using

the 2002 profile is the fact that the 2002 profile was not defined in as shallow water as the

DEP profiles. This means that the section of the equilibrium beach profile represented by

this large sediment size was not taken into account with the analysis for the 2002 profile.

The profile at Monument 19 was excluded because of the close proximity to the Ft.

George Inlet. The values calculated for cross-shore transport are too large to be

considered realistic. A cross-shore transport value on the order of magnitude of 4,000

yd3/ft/yr would translate into an annual accretion of 4,000 feet of shoreline with an

(h.+B) value of 25 feet. Thus direction of the cross-shore sediment transport is the most

significant finding from this analysis. The energy-dissipation theory of cross-shore

sediment transport is not considered to be sufficiently accurate to yield valid transport

magnitudes; however, the basic concept of the theory can be accepted to provide good

approximations for the direction of cross-shore transport.

The profiles surveyed by the wave runner are more precise with measurements at one

to two foot intervals, while the DEP profiles are reported at an average of 50-foot

intervals in the cross-shore direction. The irregularities associated with the closely

spaced data can result in undesirable interpretation effects. For this purpose a "best fit"

profile scale parameter was determined using the method of least squares.

h, = Ay2/3

2 2[hi-Ay/3 ]
ae2 Z [hi Ay4/3 -A (3-9)
aA I I
BestFit Z 4/3

Table 3-4 List of best-fit profile scale parameters from January, 2002 survey data.
Monument Best fit profile scale
parameter (m1/3)
7 0.098715
10 0.116039
13 0.115551
16 0.078604
This representative profile scale parameter determined by the least squares method is

then used to find an associated energy-dissipation rate using the same equation as for the

individual profile scale parameters. This smoothing removes profile irregularities such as

bars, and any other features that could cause slope anomalies. It can be seen from Table

3-5 that the smoothed data shows, on average, onshore transport. At Monument 10, even

though the representative equilibrium profile is above the equilibrium profile based on

the sediment samples analyzed with the RSA, the data show offshore transport because

the representative profile has a steeper slope. The same is true for the profile at

Monument 13 when comparing the profile from the sieve data. This is due to the fact that

the energy-dissipation is directly related to the slope, compared to the square root of the

water depth. All of the other smoothed representations of cross-shore transport show

onshore transport, which agrees with the values, obtained using the DEP profiles.

Table 3-5 Cross-shore transport calculated from Eq. 3-4 using smoothed profile for
January, 2002 survey. Based on UF profiles.
January, 2002
Profile Sieve RSA
R-07 -611 yd3/ft/yr -613 yd3/ft/yr
R-10 -1567 yd3/ft/yr -239 yd3/ft/yr
R-13 -592 yd3/ft/yr -657 yd3/ft/yr
R-16 -924 yd3/ft/yr -530 yd3/ft/yr
Average -924 yd3/ft/yr -510 yd3/ft/yr

R-07

1000 1500 2000

2500 3000

3500 4
3500 40

Waverunner (2002)
-- DEP (1999)
- - Equilibrium (Sieve)
----- Equilibrium (RSA)
--Best Fit (2002)

Distance from DEP Monument (ft)

Profiles for Monument 7 of Duval County.

Figure 3-4

_~ ~__~~

R-10

1000 1500

2000

2500

3000

3500
Waverunner (2002)
-- DEP (1999)
- Equilibrium (Sieve)
S----- Equilibrium (RSA)
Best Fit (2002)

Distance from DEP Monument (ft)

Figure 3-5 Profiles for Monument 10 of Duval County.

R-13

20

15

10

5

0C

0 Waverunner (2002)
> 500 1000 1500 2000 2500 3000 3500 4000
<- DEP (1999)
2-5 -\ \ - Equilibrium (Sieve)

.0
5 ^-5-- V -------- ,--------------------

-.--. Equilibrium (RSA)
Best Fit (2002)
-10

w
-15 -

-20

-25

-30 -__
Distance from DEP Monument (ft)

Figure 3-6 Profiles for Monument 13 of Duval County.

R-16

20

15

10 A

5
00
0)
0 ... T Waverunner (2002)
1000 1500 2000 2500 3000Waveru r
2 DEP (1999)
z
-5 - Equilibrium (Sieve)
.- .----- Equilibrium (RSA)
10 -- Best Fit (2002)
S-10 -.

w

-15

-20

-30
Distance from DEP Monument (ft)

Figure 3-7 Profiles for Monument 16 of Duval County.

CHAPTER 4
SUMMARY AND CONCLUSIONS

Summary

A sediment budget is based on a conservation of mass analysis, incorporating the

longshore and cross-shore sediment transport components, beach nourishment, and

change with a defined control volume. This thesis accounts for all four of these

components. Two representations of longshore transport are employed. The first is

based on the energy flux equation using WIS data to calculate the longshore transport,

Eq. 2-4, which is a representation of Eq. 2-1 transferred to the point at which the WIS

data are provided, by using the conservation of energy flux and Snell's law. The second

is a published distribution of the net longshore sediment transport along the Florida east

coast. This sediment budget methodology was applied to the twelve sandy beach

counties on the east coast of Florida.

Shoreline changes were calculated from gradients in the longshore sediment transport

and correlated with values obtained from the State of Florida shoreline position database.

This analysis shows that for eight of the twelve counties the correlation is statistically

significant; however, the small correlation values represent a small proportion of the

variation in shoreline change rates accounted for by a linear relationship with the gradient

in calculated longshore sediment transport rates. Additionally, for two of the counties

with significant correlation, the correlation is negative.

Cross-shore transport was calculated from the sediment budget equation using the

same two different sets of accepted values of longshore transport. The net sediment

transport was found to be in the onshore direction using both sets of longshore sediment

transport. A more local analysis of cross-shore transport was performed for Little Talbot

Island of Duval County using concepts of equilibrium beach profiles based on wave

energy-dissipation rate. This approach also results in sediment transport in the onshore

direction but of an unrealistically large magnitude. These unrealistically large onshore

transport rates can be attributed to the fact that the wave energy-dissipation rate theory is

based on breaking across the entire profile; however, for the measured profiles, waves are

only breaking a small fraction of the time for larger depths.

Conclusions

* Although the correlation between gradients of longshore sediment transport calculated

from WIS data using the energy flux equation, and measured shoreline change rates

may have a level of significance of 5% for eight of the twelve counties on the east

coast of Florida, the correlation values of ten of these counties are low and/or

negative. This means that while the correlations are of a level of significance of 5%,

only a small proportion of the total variation of measured shoreline change rates can

be explained by a linear relationship with the longshore sediment transport values

from WIS data. For example, if the level of significance is 5%, there is a 95% chance

that the correlation is not zero. This does not mean that the calculated longshore

sediment transport gradients provide a good representation of the measured shoreline

change rates, thus the longshore sediment transport values calculated from WIS data

using the energy flux equation cannot be considered applicable to engineering

projects.

* Because the USACE values for longshore sediment transport are based on a direct

measurement of sediment accumulation on the updrift sides of inlets, they are besed

on estimates only at several locations along the Florida east coast. In an attempt to

include analysis of longshore sediment transport for the coastline between inlets, the

energy flux equation was used with WIS data, but yielded poor results. When

gradients were compared to the measured shoreline change rate, a low correlation was

found. (Previous conclusion) Walton's data is based on an energy flux equation

similar to the one used in this report, but is based on ship observations which are

subject to several Imitations. However, they agree better with the USACE

representation than the WIS based transport values.

* The average yearly cross-shore sediment transport was found to be primarily in the

onshore direction using the sediment budget methodology with accepted values of

longshore sediment transport from the USACE and the energy flux equation using

WIS data.

* The cross-shore transport calculated using the wave energy-dissipation model

proposed by Kriebel (1982), Moore (1982), and Kriebel and Dean (1985) also

estimates onshore cross-shore transport, but clearly overestimates transport

magnitudes. The overestimation of magnitudes can be attributed to the infrequency of

breaking waves in the deeper portions of the surf zone

APPENDIX
BEACH NOURISHMENT

Beach nourishment, or beach fill, is becoming the accepted solution to many coastal

erosion problems; however, there is still some controversy over the use and performance

of beach nourishment. It can be seen that when a beach is nourished with sediments of a

compatible size, at an appropriate interval, nourishment can be extremely effective at

stabilizing an otherwise eroding shoreline, while still maintaining a relatively natural

appearance. Hard structures such as groins and jetties have been found to stabilize

shorelines, but sometimes at an extreme cost to shorelines downdrift of the project.

Additionally, hard structures can be obtrusive to the eye, and cause public safety

concerns.

A sediment budget can be useful to determine the need for beach nourishment, and it

can show whether a beach nourishment project has been effective in stabilizing a

shoreline. Dade County beaches used to be practically non-existent with seawalls lining

the shoreline, rather than sandy beaches. Due to the lack of sandy beaches in Dade

County, tourism plummeted causing the county, state and federal agencies to commence

a large-scale nourishment project in 1976. The project has been considered a success

with tourism up, and the beaches stabilized. This stabilization can be seen in Figure 2-23,

which shows that in the northern half of the county, the longshore sediment transport is

relatively constant. This lack of gradient of longshore transport along the coast of Dade

County signifies a lack of erosional trends, which can infer a stabilization of the coastline

due to the large beach nourishment project. This can also be seen in Broward County in

Figure 2-21. Broward County has also placed large volumes of sand to nourish its

shorelines, which results a relatively constant trend for the distribution of longshore

sediment transport throughout the county. Similar to Dade County, this constant trend

results in small gradients, which result in little variation in shoreline change.

Figure A-1 presents the beach nourishment volumes for the period of this study, which

covers 1976 through 1995. Julie Rosati compiled the values in Figure A-1 from data

obtained by Valverde, Trembanis, and Pilkey (1999), and Kevin Bodge (2000). These

data encompass the entire period from 1944 through 2000; however, the values for 1976-

1995 were utilized since the purpose of this study was to compile a sediment budget for

the same period of the WIS data. The values were presented as yearly totals for each

monument along the east coast of Florida. Figure A-i represents the total for the 20 year

period covering 1976 to 1995 divided by the distance between monuments to give a

representation of the total nourishment density in yd3/ft during this 20 year period. It can

be seen in Figure A-i that Nassau County, the southern part of Martin County, the

southern part of Palm Beach County, Broward County, and Dade County have all been

nourished heavily during this 20 year period.

Beach Nourishment for 1976-1995

r
o C)
Co
U) 0)
D*;C
iy u

E u a
J 2 'a 2
0 -

0 50 100 150 200 250
Distance Along the FL Coastline (miles)

400

350

. 300
o
(A
- 250

E 200

o
S150
0
m
I 100

50

0

r

Figure A-I Beach nourishment volumes for the entire east coast of Florida for the period of this study (1976-1995). Compiled by
Julie Rosati from data obtained from Valverde, Trembanis, and Pilkey (1999), and Kevin Bodge (2000)

ft

LIST OF REFERENCES

Bretschneider, C. L. and R. O. Reid, "Modification of Wave Height Due to Bottom
Friction, Percolation, and Refraction," Beach Erosion Board (CERC), U. S. Army
Corps of Engineers, Technical Memorandum No. 45, 1954.

Charles, L. L., "Applications of Equilibrium Beach Profile Concepts to Florida's East
Coast," Master's Thesis, University of Florida Department of Coastal and
Oceanographic Engineering, 1994.

Dean, R. G., "Sediment Budget Principles and Applications," University of Florida
Department of Coastal and Oceanographic Engineering, Technical Report 86/019,
1986.

De Beaumont, L. E. "Lecons de Geologie Pratique," 7me Legon-Levees de Sables et
Galets, Paris, 1845.

Dean, R. G. and L. Charles, "Equilibrium Beach Profiles: Concepts and Evaluation,"
University of Florida Coastal and Oceanographic Engineering Department,
Technical Report 94/013, 1994.

Dean, R. G. and R. A. Dalrymple, "Coastal Processes with Engineering Applications,"
Cambridge University Press, 2001.

Dean, R. G. and J. Grant, "Development of Methodology for Thirty-Year Shoreline
Projections in the Vicinity of Beach Nourishment Projects," University of Florida
Coastal and Oceanographic Engineering Department, Technical Report 89/026,
1989.

Dean, R. G. and M. P. O'Brien, "Florida's East Coast Inlets: Shoreline Effects and
Recommended Action," University of Florida Department of Coastal and
Oceanographic Engineering, Technical Report 87/017, 1987.

Emery, W. J. and R. E. Thompson, "Data Analysis Methods in Physical
Oceanography,"Gray Publishing, 1997.

Komar, P.1 D. and D. L. Inman, "Longshore Sand Transport on Beaches," Journal of
Geophysical. Research, 75, 30, 5914-5927, 1970.

Kriebel, D. L., "Beach and Dune Response to Hurricanes," M.Sc. Thesis, University of
Delaware, 1982.

Kreibel, D. L. and Robert G. Dean, "Numerical Simulation of Time-Dependant Beach
and Dune Erosion," Coastal Engineering, 9, 3, 1985.

Moore, B. D., "Beach Profile Evolution n Response to Changes in Water Level and Wave
Height," MCE Thesis, Department of Civil Engineering, University of Delaware,
1982.

Nicholls, R. J., W. A. Birkemeier, and R. J. Hallermeier, "Application of the Depth of
Closure Concept," Proceedings of the 25th International Conference of Coastal
Engineering, ASCE, Orlando, 1996.

Thornton, E. B., "Distribution of Sediment Transport Across the Surf Zone," Proceedings
of the 13th International Conference of Coastal Engineering, ASCE, Vancouver,
1972.

Trembanis, A. C., Pilkey, O. H., and Valverde, H. R., "Comparison of Beach
Nourishment Along the U. S. Atlantic, Great Lakes, Gulf of Mexico, and New
England Shorelines," Coastal Management, v 27, n 4, 1999.

Walpol, R. E. and R. H. Meyers, "Probability and Statistics for Engineers and
Scientists," MacMillan Publishing Company, 1985.

Walton, T. L., "Littoral Drift Computations Along the Coast of Florida by Means of Ship
Wave Observations," Florida Sea Grant Program Report No. 15, 1973.

Walton, T. L., "Littoral Drift Estimates Along the Coastline of Florida," Florida Sea
Grant Program Report No. 13, 1976.

BIOGRAPHICAL SKETCH

I was born on August 15th, 1977 in Richmond, VA. When I was 10 years old, my

parents bought a house on Topsail Island, in North Carolina. Being a barrier island,

Topsail Island is exposed to many dynamic features along its coastlines, especially

adjacent to the inlets on either end. During my freshman year of high school, also in

Richmond, I participated in a weekend trip to the Tangier Islands in the Chesapeake Bay.

The main purpose of the trip was to learn about the features of the wetlands, and

coastlines of a unique island just north of the fishing town of Tangier. This combined

with my exposures at Topsail Island increased my interest in the shorelines, and the

processes associated with them. In the fall of 1995, I began my studies at Rensselaer

Polytechnic Institute in Troy, NY. After many rough years in the cold of Upstate New

York, and an internship in Connecticut, I graduated in May of 2000 with a Bachelor of

Science degree in Civil Engineering from Rensselaer Polytechnic Institute, after which I

enrolled at the University of Florida to pursue a Master of Science degree in Civil and

Coastal Engineering. After receiving my Masters degree from the University of Florida,

I plan to pursue a Ph.D. in Geotechnical Engineering at Virginia Polytechnic Institute and

State University.

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0	cached_data_manager.retrieve_item_aggregation
0	cached_data_manager.retrieve_item_aggregation	Found item aggregation on local cache
0	item_aggregation_builder.get_item_aggregation	Found 'all' item aggregation in cache
0	system.web.ui.page.page_load (ufdc.page_load)
0	sobekcm_page_globals.constructor.on_page_load
0	html_echo_mainwriter.add_style_references	Adding style references to HTML
0	html_echo_mainwriter.add_text_to_page	Reading the text from the file and echoing back to the output stream
2	html_echo_mainwriter.add_text_to_page	Finished reading and writing the file