JFL/COEL2002/003
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/CS39, "LongTerm 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 SSSH 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
21 Correlation of shoreline change rates from gradient of longshore transport calculated
from WIS data, to shoreline change rates from historical shoreline position
database ............................................................................................................. . 10
22 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
31 Average values of crossshore transport using accepted longshore transport values
from the USACE, and calculated from WIS data..............................................52
32 Summary of recommended A values (m1/3) for diameters from 0.10 to 1.09 mm.
(D ean and D alrym ple, 2001) ................................... .............................................56
33 Crossshore transport calculated from Eq. 34 and 38 for Little Talbot Island............61
34 List of bestfit profile scale parameters from January, 2002 survey data ....................62
35 Crossshore transport calculated from Eq. 34 using smoothed profile for January,
2002 survey. Based on UF profiles........................... ............................................63
LIST OF FIGURES
Figure page
11 Definition sketch of sediment budget............................. ..................................... 2
21 Longshore sediment transport calculated from WIS data using the energy flux
equation for Nassau County................................... ................. ........................... 21
22 Measured and calculated shoreline change rates for Nassau County...........................22
23 Longshore sediment transport calculated from WIS data using the energy flux
equation for Duval County ...................................................... .......................... 23
24 Measured and calculated shoreline change rates for Duval County ............................24
25 Longshore sediment transport calculated from WIS data using the energy flux
equation for St. Johns County.................................................. .......................... 25
26 Measured and calculated shoreline change rates for St. Johns County........................26
27 Longshore sediment transport calculated from WIS data using the energy flux
equation for Flagler County................................................... ............................ 27
28 Measured and calculated shoreline change rates for Flagler County.............................28
29 Longshore sediment transport calculated from WIS data using the energy flux
equation for V olusia County................................... ..............................................29
210 Measured and calculated shoreline change rates for Volusia County........................30
211 a Longshore sediment transport calculated from WIS data using the energy flux
equation for Cape Canaveral................................ ................. .............................31
21 lb Longshore sediment transport calculated from WIS data using the energy flux
equation for Brevard County .......................................................... ...................32
212 Measured and calculated shoreline change rates for Brevard County .......................33
213 Longshore sediment transport calculated from WIS data using the energy flux
equation for Indian River County ................................... ........................................34
214 Measured and calculated shoreline change rates for Indian River County ..................35
215 Longshore sediment transport calculated from WIS data using the energy flux
equation for St. Lucie County.................................................. .......................... 36
216 Measured and calculated shoreline change rates for St. Lucie County......................37
217 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for M artin County ................................................... ............................ 38
218 Measured and calculated shoreline change rates for Martin County .........................39
219 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for Palm Beach County ................................... ........................................40
220 Measured and calculated shoreline change rates for Palm Beach County .................41
221 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for Broward County ................................................. ........................... 42
222 Measured and calculated shoreline change rates for Broward County ......................43
223 Longshore sediment transport rates calculated from WIS data using the energy flux
equation for Dade County.................................................... .............................. 44
224 Measured and calculated shoreline change rates for Dade County............................45
225 Relationship between the immersed weight longshore sand transport rate and the
energy flux. (Komar and Inman, 1970) ................................................................47
31 Crossshore sediment transport rates from sediment budget equation with accepted
longshore transport values from the USACE. ...................................................53
32 Crossshore sediment transport rates from sediment budget equation with accepted
longshore transport values from energy flux equation using WIS data...................54
33 Profile scale parameter, A, versus sediment diameter, d, and fall velocity, w (Dean,
1987; adapted in part from M oore, 1982)..............................................................56
34 Profiles for M monument 7 of Duval County................................................................ 64
35 Profiles for M monument 10 of Duval County.................................................................65
36 Profiles for M monument 13 ofDuval County.............................................................. 66
37 Profiles for M monument 16 ofDuval County.............................................................. 67
A1 Beach nourishment volumes for the entire east coast of Florida for the period of this
study (19761995). 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, crossshore 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.
Crossshore 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.
Crossshore sediment transport was also studied in more detail for Little Talbot Island
in Duval County. The crossshore sediment transport for Little Talbot Island was
analyzed using the theory of energy dissipation rate for crossshore 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 crossshore directions and methods are available
for calculating the longshore sediment transport based on wave, sediment and shoreline
characteristics. However, accepted methods for calculating crossshore 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 longterm 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 11.
Flow in the xdirection longshoree):
Vi,, = qx (x + Ax)AyAt
Vo,, = q,(x + Ax)AyAt
Figure 11 Definition sketch of sediment budget
Similarly for the ydirection (crossshore):
V,, = q,(y)AxAt
(12)
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 (13)
ax ox
q,, (y)xAt q, (y + Ay)AxAt
=q,(y)AxAt q, (y)+ q Ay AxAt q AxAyAt (14)
(9. y y 9
Total net flow onto the element can then be expressed as follows:
j a+ > xAyAt (15)
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 (16)
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 (17)
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 (18)
( )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 (19)
at ax y )
since h+zb=constant where h is the water depth related to a fixed location:
ah azb ah aqx aq
=   = ~+ s (110)
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 (111)
AXc
in which S is the volumetric nourishment rate per unit beach length and qy, in and qy, out
are the flows in the ydirection 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 11). 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 (112)
At Ax
The simplest and most straightforward way to obtain crossshore transport is to
determine it from the sediment budget equation as is indicated in Equation 112. 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(113)
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. 112 to infer grossshore sediment transport.
A second method of calculating crossshore transport utilizes a comparison of the
wave energydissipation rate of the actual beach profile to that for the calculated
equilibrium beach profile. This method is usually reasonable for predicting the direction
of crossshore transport; however the magnitude of transport may be questionable. The
wave energydissipation 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 (21)
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. 21 can be
transferred to any point from which data are available using conservation of energy flux
(22), and Snell's Law (23)
(EC, cos O)b = (EC, cos 0 (22)
sin = (sin0 (23)
C C J0
This conversion results in,
K(E'Cg'Cos( a' ))12 8 ) sin ') 1(24)
pg(s 1p) lpJ npg I C 9 cos( b)
In Eq. (24) 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 (pob) 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
19761995, 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 threehour 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/hisshore.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 (25)
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 (26)
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 21 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 21 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 21 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= (27)
(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 of1 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 21 and 22 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 21 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 23 and 24 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 25 and 26 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 27 and 28 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 29 and 210 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 210), 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 211 a, b and 212 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 213 and 214 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 215 and 216 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 217 and 218 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 21. 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 218.
Palm Beach County
Results for this county are presented in Figures 219 and 220 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 21. 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 221 and 222 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 223 and 224 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 21 Longshore sediment transport calculated from WIS data using the energy flux equation for Nassau County
Nassau County
Shoreline Change Rate
  Measured dy/dt
dy/dtNourishment
WIS Average (X5)
Monument
Figure 22 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 23 Longshore sediment transport calculated from WIS data using the energy flux equation for Duval County
Duval County
Shoreline Change Rate
   Measured dy/dt
 dy/dtNourishment
WIS Average (X1O)
Monument
Figure 24 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 25 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 26 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 27 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 19761995)
 Measured dy/dt
WIS Average (X15)
Monument
Figure 28 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 29 Longshore sediment transport calculated from WIS data using the energy flux equation for Volusia County
Volusia County
Shoreline Change Rate
 Measured dy/dt
dy/dtNourishment
 WIS Average (X15)
Monument
Figure 210 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 21 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 21 Ib Longshore sediment transport calculated from WIS data using the energy flux equation for Brevard County
astian
let
i
20
  Measured dy/dt
dy/dtNourishment
W IS Average (X15)
Monument
Figure 212 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
II
1.00E+06
1.50E+06
2.00E+06     ____...__
Monument
Figure 213 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/dtNourishment
 WIS Average (X15)
Monuments
Figure 214 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 215 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/dtNourishment
WIS Average (X10)
Monument
Figure 216 Measured and calculated shoreline change rates for St. Lucie County
Martin County
Longshore Transport from WIS Data
Monument
Figure 217 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/dtNourishment
WIS Average (X5)
Moument
Figure 218 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 219 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/dtNourishment
WIS Average (X15)
Monument
Figure 220 Measured and calculated shoreline change rates for Palm Beach County
20
10
0
S10
S20
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 221 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 tIFN + I .
Port
verglac
I __ _ p I I  9
Nouri hment
d
7
DO "8
0 8
ourish ent
!0 130  Measured dy/dt
dy/dtNourishment (ft/yr)
S WIS Average (X10) ft/year
Monument
Figure 222 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 223 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/dtNourishment (ft/yr)
 WIS Average (X15) ft/year
Monument
Figure 224 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 "frictionpercolation coefficient," Kfp. Walton's calculations were
based on
Q = 125E,
Ea = EoC cos)K sina 24(3600) (29)
(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 = frictionpercolation 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/seccm
Figure 225 Relationship between the immersed weight longshore sand transport rate and
the energy flux. (Komar and Inman, 1970)
Table 22 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 22 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
CROSSSHORE TRANSPORT
Sediment Budget
As discussed previously, using the historical shoreline position data, a value for dy/dt
was determined for approximately the same 20year 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 (31)
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
crossshore transport can then be calculated, using the sediment budget equations from
Chapter 1 (Equation 112), where the total volume change rate is equal to AV/At.
AV 1 
yo= +V 1 Qx )+S (112)
At Ax ,
Results
The values of longshore transport from the USACE were used to obtain the qy, out
values presented in Figure 31. It can be seen in Figure 31, that when the USACE
values for longshore transport are used to solve for values of crossshore 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 crossshore
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 crossshore transport using longshore transport values calculated from
WIS data can be seen in Figure 32. The average resulting crossshore 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 crossshore 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. 112. 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 crossshore
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 31 Average values of crossshore 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
CrossShore Transport
qy=(AV/At(from dy/dt))+(AQx, USACE/AX)+(S/Ax)
Distance Along the FL Coastline (miles)
Figure 31 Crossshore sediment transport rates from sediment budget equation with accepted longshore transport values from the
USACE.
CrossShore 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 32 Crossshore sediment transport rates from sediment budget equation with accepted longshore transport values from energy
flux equation using WIS data
Beach Profiles
Crossshore 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 energydissipation 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 (32)
where
h = water depth
y = distance from mean water line (MWL) in the offshore direction
A = profile scale parameter, which is a function of energydissipation rate (D), and
indirectly sediment size (d). (Figure 33, and Table 32)
For the case of nonuniform sediment sizes, the following is valid:
h(y)= (h/2 + A /2yy,,))/3 (33)
where yn
and yn+1.
According to theory, the crossshore sediment transport is dependent upon the
difference in the energydissipation rate for the particular profile and the dissipation rate
for the equilibrium beach profile.
q, = K(D D. ) (34)
where
qy = volumetric crossshore 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 33 Profile scale parameter, A, versus sediment diameter, d, and fall velocity, w
(Dean, 1987; adapted in part from Moore, 1982)
Table 32 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 1.13x103 ft4/lb
D = energydissipation 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 energydissipation per unit water volume can be expressed as a function of grain
size:
1 dF
D(d)=
h dy'
hD(d)= (35)
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 energydissipation rate can be determined directly
from the profile scale parameter using the following equation.
2/3
24D.
S= 2 (36)
A 5 pgK2 J
It can be seen from Eq. 35 that the energydissipation is dependent upon beach slope
consistent with the Moore, Kriebel, and Dean concepts. The energydissipation 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 crossshore, 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 33,
and Table 31).
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 33 (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 = (37)
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. 33.
These profiles were then compared, using Eq. 34, to the profiles measured by the DEP in
1999, and to the profiles surveyed in January 2002. The energydissipation rates for the
measured profiles were calculated at each measurement of elevation using the individual
slopes at those points. The energydissipation rates for the equilibrium beach profiles
were calculated using the profile scale parameter, and Eq. 36. The crossshore transport
was then calculated for each measurement of elevation using Eq. 34. A weighted
average of the crossshore 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
crossshore transport rates by the Ay values separating the sample points and normalizing
as
s,Toal A (38)
qAy,
where
qs, = the individual crossshore transport calculation
Ayi = distance separating the individual crossshore transport rates in the ydirection
qs, Total = the weighted average for the section of interest
The average crossshore 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 33 Crossshore transport calculated from Eq. 34 and 38 for Little Talbot Island.
January, 2002 January, 1999 (DEP)
Profile Sieve RSA Sieve RSA
R07 1314 yd3/ft/yr 1316 yd3/ft/yr 1143 yd3/ft/yr 1302 yd3/ft/yr
R10 2427 yd3/ft/yr 1190 yd3/ft/yr 2039 yd3/ft/yr 1185 yd3/ft/yr
R13 1594 yd3/ft/yr 1659 yd3/ft/yr 13258 yd3/ft/yr 13298 yd3/ft/yr
R16 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 crossshore 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 crossshore transport are too large to be
considered realistic. A crossshore 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 crossshore sediment transport is the most
significant finding from this analysis. The energydissipation theory of crossshore
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 crossshore 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 50foot
intervals in the crossshore 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[hiAy/3 ]
ae2 Z [hi Ay4/3 A (39)
aA I I
BestFit Z 4/3
Table 34 List of bestfit 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 energydissipation 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
35 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 energydissipation is directly related to the slope, compared to the square root of the
water depth. All of the other smoothed representations of crossshore transport show
onshore transport, which agrees with the values, obtained using the DEP profiles.
Table 35 Crossshore transport calculated from Eq. 34 using smoothed profile for
January, 2002 survey. Based on UF profiles.
January, 2002
Profile Sieve RSA
R07 611 yd3/ft/yr 613 yd3/ft/yr
R10 1567 yd3/ft/yr 239 yd3/ft/yr
R13 592 yd3/ft/yr 657 yd3/ft/yr
R16 924 yd3/ft/yr 530 yd3/ft/yr
Average 924 yd3/ft/yr 510 yd3/ft/yr
R07
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 34
_~ ~__~~
R10
1000 1500
2000
2500
3000
3500
Waverunner (2002)
 DEP (1999)
 Equilibrium (Sieve)
S Equilibrium (RSA)
Best Fit (2002)
Distance from DEP Monument (ft)
Figure 35 Profiles for Monument 10 of Duval County.
R13
20
15
10
5
0C
0 Waverunner (2002)
> 500 1000 1500 2000 2500 3000 3500 4000
< DEP (1999)
25 \ \  Equilibrium (Sieve)
.0
5 ^5 V  ,
.. Equilibrium (RSA)
Best Fit (2002)
10
w
15 
20
25
30 __
Distance from DEP Monument (ft)
Figure 36 Profiles for Monument 13 of Duval County.
R16
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)
S10 .
w
15
20
30
Distance from DEP Monument (ft)
Figure 37 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 crossshore 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. 24, which is a representation of Eq. 21 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.
Crossshore 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 crossshore transport was performed for Little Talbot
Island of Duval County using concepts of equilibrium beach profiles based on wave
energydissipation 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 energydissipation 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 crossshore 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 crossshore transport calculated using the wave energydissipation model
proposed by Kriebel (1982), Moore (1982), and Kriebel and Dean (1985) also
estimates onshore crossshore 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 nonexistent 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 largescale 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 223,
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 221. 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 A1 presents the beach nourishment volumes for the period of this study, which
covers 1976 through 1995. Julie Rosati compiled the values in Figure A1 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 Ai 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 Ai 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 19761995
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 AI Beach nourishment volumes for the entire east coast of Florida for the period of this study (19761995). 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 LegonLevees 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 ThirtyYear 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, 59145927, 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 TimeDependant 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.
