Citation
Statistical characteristics of Florida shoreline changes

Material Information

Title:
Statistical characteristics of Florida shoreline changes
Series Title:
UFLCOEL-98009
Creator:
Cheng, Jie, 1969-
University of Florida -- Coastal and Oceanographic Engineering Dept
Place of Publication:
Gainesville Fla
Publisher:
Coastal & Oceanographic Engineering Dept., University of Florida
Publication Date:
Language:
English
Physical Description:
xiii, 111 leaves : ill. ; 28 cm.

Subjects

Subjects / Keywords:
Coast changes -- Florida ( lcsh )
Shorelines -- Florida ( lcsh )
Genre:
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (M.E.)--University of Florida, 1998.
Bibliography:
Includes bibliographical references (leaves 110-111).
Statement of Responsibility:
by Jie Cheng.

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Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
41524981 ( OCLC )

Full Text
UFL/COEL-98/009

STATISTICAL CHARACTERISTICS OF FLORIDA SHORELINE CHANGES by
Jie Cheng Thesis

1998




STATISTICAL CHARACTERISTICS OF FLORIDA SHORELINE CHANGES

By
JIE CHENG
A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIRMENTS FOR THE DEGREE OF
MASTER OF ENGINEERING
UNIVERSITY OF FLORIDA

1998




ACKNOWLEDGEMENTS

I would like to express my gratitude to my advisor and supervisory committee chairman, Dr. Robert G. Dean, for his guidance and support for this thesis. Without his help and inspiration, this work could never have been done. I would also like to thank Dr. Daniel M. Hanes, Dr. Hsiang Wang and Dr. Ashish J. Mehta (who later represented Dr. Wang who was on leave) for serving on my committee.
My thanks also go to Becky, Sandra, Lucy, Helen, Cynthia, Laura, John and Subarna for their support.
I must also thank all my friends in the Coastal and Oceanographic Engineering Department for their help in difficult times.
I am also indebted to the Florida Sea Grant Program which provided support for this work under Grant R/C-S-35. The Bureau of Beaches and Coastal Systems of the Florida Department of Environmental Protection provided the shoreline position data used in this study. These high quality data contributed greatly to the results developed in this thesis.
Finally, I want to thank my husband, Xueliang, for his help and encouragement.




TABLE OF CONTENTS
ACKNOWLEDGEMENTS ......................................................................... ii
L IST O F T A B L E S .................................................................................... v
LIST O F FIG U R ES .................................................................................. vi
A B ST R A C T ........................................................................................ xii
CHAPTERS
I INTRODUCTION ................................................................................. I
1. 1 Purpose of the Study ......................................................................... 1
1.2 Florida Shoreline Position Data Set ....................................................... 2
1.3 L iterature R eview ............................................................................ 3
1.4 R eport O rganization ......................................................................... 7
2 FLORIDA'S COAST SETTING ................................................................ 8
2.1 Longshore Sediment Transport Characteristics .......................................... 8
2.2 Sediment Characteristics .................................................................... 9
2.3 Sea Level C hange ........................................................................... 10
2.4 Human Effects 10
3 ANALYSIS PROCEDURES ................................................................... 11
3.1 Shoreline Change Trend Analysis ........................................................ 11
3.1.1 Shoreline Change Trend ............................................................ 12
3.1.2 Sand Conservation .................................................................... 12
3.1.3 Total Net Longshore Sediment Transport Difference ......................... 15
3.1.4 Local Cross-shore Sediment Transport .......................................... 16
3.2 Analysis of Standard Deviation of Shoreline Deviations ............................. 17
3.2.1 Definition of Standard Deviations of Shoreline Deviations .................. 18
3.2.2 Model consideration ................................................................ 19
3.2.3 Analysis of Normalized Standard Deviations .................................... 19
3.2.4 Analysis of Unscaled Standard Deviations ...................................... 24
3.2.5 M odel T est ............................................................................. 26
3.2.6 The Influence of Inlets ............................................................... 27
4 RESULTS AND DISCUSSION ................................................................. 28
4.1 Shoreline Change Rates and Sediment Transport ..................................... 28




4. 1.1 East Coast Counties and Islands .................................................... 28
4.1.2 West Coast Counties and Islands ................................................... 34
4.2 Standard Deviation of Shoreline Deviation .............................................. 39
4.2.1 The effects of Inlets on Standard Deviations ..................................... 39
4.2.2 Normalized Standard Deviations .................................................... 39
4.2.3 Unscaled Standard Deviations ..................................................... 41
5 SUMMARY AND CONCLUSIONS ........................................................ 107
RE FERE N C E S .................................................................................... 110
BIOGRAPHICAL SKETCH .................................................................... 112
iv




LIST OF TABLES

4-1: Summary of shoreline change rates for Florida's east coast sandy beach
counties .......................................................................43
4-2: Summary of shoreline change rates for Florida's east coast .................... 43
4-3: Summary of shoreline change rates for Florida's east coast island by island...44 4-4: Summary of shoreline change rates for Florida's west coast sandy beach
counties ..................................................................... 46
4-5: Summary of shoreline change rates for Florida's west coast ................... 46
4-6: Summary of shoreline change rates for Florida's northwest coast island by
island ................................................................................... 47
4-7: Summary of shoreline change rates for Florida's southwest island by island ...48 4-8: Summary of the Kolmogorov-Smirnov test for goodness of model fitting to
normalized standard deviations for Florida's east coast sandy beach counties .... .50 4-9: Summary of the Kolmogorov-Smirnov test for goodness of model fitting to
normalized standard deviations for Florida's west coast sandy beach counties .... .51 4-10: Summary of the parameters for the models fitting to normalized standard
deviations for Florida's east coast sandy beach counties....................... 52
4-11: Summary of the parameters for the models fitting to normalized standard
deviations for Florida's west coast sandy beach counties.......................53
4-12: Summary of the parameters for the models fitting to unscaled standard
deviations for Florida's east coast sandy beach counties ....................... 54
4-13: Summary of the parameters for the models fitting to unscaled standard
deviations for Florida's west coast sandy beach counties ...................... 55




LIST OF FIGURES

1-1: Numbers of stations for which shoreline position data are available along
Florida's coast sandy beach counties ....................................................... 4
3-1: Coordinate system for sediment transport ............................................... 13
3-2: Illustration of the iterative process ......................................................... 23
4-1: Long-term shoreline change rates along the east coast of Florida. These change
rates are determined by the best least squares fit procedures for the complete
record of data availability ................................................................................ 56
4-2: Examples of shoreline positions versus time at individual monument locations
for Florida's east coast sandy beach counties ............................................. 57
4-3: Histograms of long-term shoreline change rates in meters per year for the east
coast of Florida .................................................................................. 58
4-4: Average shoreline change over time for Florida's east coast sandy beach
counties .......................................................................................... 60
4-5: Total net longshore sediment transport difference along Florida's east coast.
Based on consideration of zero net long-term cross-shore sediment transport .... 61
4-6: Local cross-shore sediment transport along Florida's east coast. Based on
considering a uniform gradient of net longshore sediment transport. Gradient
is based on previous estimates of net transport at the northern and southern
lim its of region considered ................................................................ 62
4-7: Long-term shoreline change rates along Florida's northwest coast. These
change rates are determined by the best least squares fit procedures
procedures for the complete record of data availability ..................................... 63
4-8: Long-term shoreline change rates along Florida's southwest coast. These
change rates are determined by the best least squares fit procedures
procedures for the complete record of data availability ..................................... 64




4-9: Examples of shoreline positions versus time at individual monument locations
for Florida's west coast sandy beach counties................................. 65
4-10: Histogram of long-term shoreline change rates in meters per year for the
northwest coast of Florida...................................................... 66
4-11: Histogram of long-term shoreline change rates in meters per year for the
southwestcoast of Florida .............................................................. 67
4-12: Total net longshore sediment transport difference along Florida's northwest
coast. Based on consideration of zero net long-term cross-shore sediment
transport ................................................................................. 68
4-13: Total net longshore sediment transport difference along Florida's southwest
coast. Based on consideration of zero net long-term cross-shore sediment
transport ................................................................................ 69
4-14: Local cross-shore sediment transport along Florida's northwest coast. Based
on considering a gradient of +0.4 M3 /mlyr net longshore sediment transport
over the limits of the region considered.......................................... 70
4-15: Local cross-shore sediment transport along Florida's southwest coast. Based
on considering a zero gradient of net longshore sediment transport over the
limits of the region considered................................................. 71
4-16: Shoreline change rates and unsealed standard deviations along the coastline
of Nassau County, 1857-1991. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ................................72
4-17: Shoreline change rates and unscaled standard deviations along the coastline
of Duval County, 1853-1990. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ............................... 73
4-18: Shoreline change rates and unscaled standard deviations along the coastline
of St. Johns County, 1858-1992. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 74
4-19: Shoreline change rates and unscaled standard deviations along the coastline
of Flagler County, 1872-1987. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 75




4-20: Shoreline change rates and unscaled standard deviations along the coastline
of Volusia County, 1873-1989. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 76
4-21: Shoreline change rates and unscaled standard deviations along the coastline
of Brevard County, 1874-1993. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 77
4-22: Shoreline change rates and unscaled standard deviations along the coastline
of Indian River County, 1880-1993. The bold segment of the standard
deviation curve in the lower panel represents the shoreline portions
considered to be acceptable for analysis of standard deviations ................78
4-23: Shoreline change rates and unscaled standard deviations along the coastline
of St. Lucie County, 1860-1989. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 79
4-24: Shoreline change rates and unscaled standard deviations along the coastline
of Martin County, 1883-1986. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 80
4-25: Shoreline change rates and unscaled standard deviations along the coastline
of Palm Beach County, 1883-1991. The bold segment of the standard
deviation curve in the lower panel represents the shoreline portions
considered to be acceptable for analysis of standard deviations................ 81
4-26: Shoreline change rates and unscaled standard deviations along the coastline
of Broward County, 1883-1986. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ................................ 82
4-27: Shoreline change rates and unscaled standard deviations along the coastline
of Dade County, including period of extensive nourishment (1851-1986).
The bold segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable for analysis
of standard deviations ................................................................ 83
4-28: Shoreline change rates and unscaled standard deviations along the coastline
of Dade County, prior to period of extensive nourishment (185 1-1973).
The bold segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable for analysis




of standard deviations ................................................................ 84
4-29: Shoreline change rates and unscaled standard deviations along the coastline
of Escambia and Santa Rosa Counties, 1856-1978. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions
considered to be acceptable for analysis of standard deviations ................85
4-30: Shoreline change rates and unscaled standard deviations along the coastline
of Okaloosa County, 187 1-1990. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions
considered to be acceptable for analysis of standard deviations ................86
4-31: Shoreline change rates and unscaled standard deviations along the coastline
of Walton County, 1872-1977. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations....................................... 87
4-32: Shoreline change rates and unscaled standard deviations along the coastline
of Bay County, 1855-1977. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ...............................88
4-33: Shoreline change rates and unscaled standard deviations along the coastline
of Gulf County, 1857-1984. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ...............................89
4-34: Shoreline change rates and unscaled standard deviations along the coastline
of Franklin County, 1856-1979. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 90
4-35: Shoreline change rates and unscaled standard deviations along the coastline
of Pinellas County, 1873-1987. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ............................... 91
4-36: Shoreline change rates and unscaled standard deviations along the coastline
of Manatee County, 1874-1986. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ............................... 92
4-37: Shoreline change rates and unscaled standard deviations along the coastline
of Sarasota County, 1883-1984. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be




acceptable for analysis of standard deviations................................ 93
4-3 8: Shoreline change rates and unscaled standard deviations along the coastline
of Charlotte County, 1860-1992. The bold segment of the standard deviation
curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations ............................... 94
4-39: Shoreline change rates and unscaled standard deviations along the coastline
of Lee County, 1858-1989. The bold segment of the standard deviation curve
in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 95
4-40: Shoreline change rates and unscaled standard deviations along the coastline
of Collier County, 1885-1988. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be
acceptable for analysis of standard deviations................................ 96
4-41: Comparisons of empirical and theoretical cumulative distributions of
normalized standard deviations for Nassau, Duval and St. Johns
Counties.........................9
4-42: Comparisons of empirical and theoretical cumulative distributions of
normalized standard Deviations for Flagler, Volusia and Brevard
Counties.........................9
4-43: Comparisons of empirical and theoretical cumulative distributions of
normalized standard deviations for Indian River, St. Lucie and Martin
Counties.........................9
4-44: Comparisons of empirical and theoretical cumulative distributions of
normalized standard deviations for Palm Beach, Broward and Dade
Counties.........................100
4-45: Comparisons of empirical and theoretical cumulative distributions of
normalized standard deviations for Escambia, Santa Rosa, Okaloosa and
Walton Counties...................................................................... 101
4-46: Comparisons of empirical and theoretical cumulative distributions of
normalized standard deviations for Bay, Gulf and Franklin Counties ......... 102
4-47: Comparisons of empirical and theoretical cumulative distributions of
normalized standard deviations for Pinellas, Manatee and Sarasota
Counties............................................................................... 103
4-48: Comparisons of empirical and theoretical cumulative distributions of




normalized standard deviations for Charlotte, Lee and Collier Counties....... 104
4-49: Mean square error contour for xO = 0.0 for the Weibull cumulative
distribution fitting to normalized standard deviations of shoreline
deviations about the trend lines for Martin County..........................105
4-50: Mean square error at xO = 0.31 for the Rayleigh cumulative distribution
fitting to normalized standard deviations of shoreline deviations about
the trend lines for Martin County........................................... 106




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 Engineering
STATISTICAL CHARACTERISTICS OF SHORELINE CHANGES FOR FLORIDA'S COAST
By
Jie Cheng
May 1998
Chairman: Dr. Robert G. Dean
Major Department: Coastal and Oceanographic Engineering
A comprehensive shoreline position data base for the Florida shoreline is analyzed and the results presented and interpreted in terms of shoreline change trends, net longshore and cross-shore sediment transport components, and fits of the standard deviations of shoreline deviations about the trend line to theoretical models.
The least squares method is applied to the data to quantify shoreline change trends. It is found that, on average, the shoreline change rates for the entire time period available for the east coast, northwest coast and southwest coast are +0.22 mlyr, -0.16 rn/yr and +0.12 mlyr, respectively. For the entire period time, the shoreline change trends are interpreted in terms of longshore and cross-shore sediment transport components by employing the equation for conservation of sand. For the east coast, the result of calculation of the longshore transport difference commencing from the Florida-Georgia border strongly indicates the presence of a net landward cross-shore sediment transport




and/or significant biogenetic production. For the northwest and southwest coasts, the magnitudes of the longshore sediment transport difference are on the order of + 105 M3 /yr, which are consistent with earlier estimates. The average net cross-shore transport components for the east coast, northwest coast and southwest coast are -0.8 m 3/m/yr (landward), +0.45 M3 /m/yr (seaward), -0.68 m 3/m/yr (landward), respectively.
To examine the characteristics of shoreline deviations about the trend lines, the standard deviations of shoreline deviations along Florida's coastline are calculated. The results show that the greater standard deviations tend to be associated with the greater shoreline change rates and often occur near inlets. The statistical distributions of standard deviations are modeled and compared with two candidate models: the modified Weibull and the modified Rayleigh cumulative distributions. These distributions are fit to the empirical cumulative distributions of the standard deviations outside of the influence of inlets for each county. The Kolmogorov-Smimnov test is used to evaluate the goodness of fit of these models to the standard deviations. This statistical analysis of the cumulative distributions of the standard deviations for each county results in good agreement between the empirical and theoretical distributions proposed in this study.




CHAPTER I
INTRODUCTION
1. 1 Purpose of the Study
With increasing human activities and investment in the coastal zone, including recreation, tourism, residential and industrial installations, there is a greater need for understanding shoreline changes and coastal processes. Due to this investment and the possible impact on adjacent shorelines, rational coastal management that scientifically and economically determines whether a coastal engineering project is feasible becomes more important. Shoreline change can be decomposed into coherent and fluctuating components. The former is the long-term shoreline change trend, and the latter is shoreline deviation about this trend. Shoreline stability, the quantification of shoreline change trend including both shoreline advancement and shoreline recession and their causes are significant elements in the decision making process. The statistics of shoreline deviations about the shoreline change trends can be used as a basis for the prediction of shoreline fluctuations which is an important basis for coastal zone management. An understanding of the causes and characteristics of shoreline changes is essential for interpreting the effects of coastal engineering works and shoreline protection. The characteristics of shoreline changes along the coast of Florida are a result of the natural and human "forces" exerted on this shoreline. Natural effects include sea level rise, seasonal wave and water level variations, and episodic storms. The dominant human




interventions in the area of interest are the construction of new inlets and the modification of existing inlets. Within the approximately last two decades, beach nourishment has played an extensive role. These processes and constructed elements can cause both shoreline erosion and shoreline accretion. This study provides general views on these causes and factors along the Florida coastline, and based on the Florida shoreline position data set, analyzes the statistical characteristics of shoreline changes for the coast of Florida.
1.2 Florida Shoreline Position Data Set
The original shoreline position data were obtained from the following organizations: The U. S Coastal and Geodetic Survey (U.S.C. & G.S.) The Division of Beaches and Shores (B & S) of the Florida Department of Natural
Resources (FDNR, now Bureau of Beaches and Coastal Systems of the Florida
Department of Environment & Protection, FDEP)
Historical shoreline positions have been digitized and compiled by FDNR, which were obtained from aerial photographs, maps and charts, and hydrographic and beach surveys. Shoreline position is defined by the intersection of land and water. The datum for measuring shoreline position is mean high water (MHW), which is the average height of the high waters over a 19-year period. The shoreline position data are referenced to the FDNR monuments. The Florida data set includes historical shoreline positions for the 25 predominantly sandy shoreline counties. There are approximately 3785 individual monuments that are located at nominal spacings of 300 m along Florida's coastline of about 1320 km. Historical shoreline position data are available on a county-by-county




basis for most counties. Because of the FDEP precedent of combining Escambia and Santa Rosa Counties in the shoreline position data base, these counties are treated as a single county in this study. Figure 1-1 identifies these twenty-five counties and shows the numbers of monuments corresponding to each county. As shown in Figure 1-1, these counties are distributed over three segments of Florida's coastline. The sandy east coast of Florida extends approximately 570 km from the Florida-Georgia border south to Key Biscayne, along which there are 12 predominantly sandy shoreline counties and 19 inlets. The upper part of Florida's west coast has seven predominantly sandy shoreline counties and 12 inlets, extending approximately 400 km from Escambia County at the Florida Alabama border through Franklin County. The lower part of Florida's west coast has six predominantly sandy shoreline counties and 28 inlets, extending approximately 300 km from Pinellas County at the north through Collier County at the south.
1.3 Literature Review
Several investigators have developed and applied methods for interpreting shoreline change trends. Crowell et al. (199 1) have evaluated errors in available data sources which depict historical shorelines, including "T" sheets, aerial photographs of various scales and ground surveys. Error estimates are recommended for the various data sources. Dolan et al. (1991) compared various methods of analysis of shoreline position data, including: end-point, average of rates, linear regression, and jackknife. The potential errors associated with the various methods were examined for data of different characteristics and by application to the Outer Banks of North Carolina. Crowell et al. (1993) have




Nassau (82)

0U 0 a
0 0 0eq M
4jL

(386)

Pinellas (193)

aarasua k I 0 Martin (127)
Charlotte (68) aB
- Palm Beach
Lee (239)" (127)
Collier (148) Broward (128)
Dade (112)
Figure 1-1 Numbers of stations for which shoreline position data are available
along Florida's coastal sandy beach Counties.




compared the merits of using long term (>60 years) versus short term (<10 years) data to establish shoreline change trends. That paper was motivated in part by conclusions by Dolan et al. (1980) that errors associated with the "T" sheets preclude their use in the computation of shoreline change trends. Crowell et al. (1993) found significant advantages in incorporating the long term data, including increasing both the accuracy and smoothing. Fenster et al. (1993a) have considered the appropriateness of several methods of extracting trends from shoreline data and recommended the use of a so-called "Minimum Descriptor Length" method (MDL) in which a linear trend is fit to the more recent data based on consideration of the times when changes occurred in more complete polynomial fits to the data. In the simplest situation, all available data provide a reasonable fit to a linear line; and in such cases, all data are used in establishing the line used in projections. In more complicated and realistic cases, various tests tempered by judgement are applied to the data to establish that recent portion of the data from which a linear trend line is to be established. Fenster et al. (I 993b) applied this method to identify changes in shoreline changes along the Outer Banks of North Carolina. Crowell et al. (1997) have compared the merits of the MDL method proposed by Fenster et al. (1993a) with the least squares method using tide gage data as a surrogate to shoreline positions and have concluded that for projections of shoreline change, the least squares method is superior to the MDL method. Foster and Savage (1989) have suggested a method by which the end point slopes of various qualifying pairs of data are averaged to establish the appropriate trend. In order for a pair of data points to be included in the average, the time separating the two points must be large enough that the associated trend change is large




compared to the uncertainties in the shoreline positions. If N data points are available and if all pairs of data points qualify, there would be N(N- 1)/2 slopes to be averaged. Fenster and Dolan (1996) have examined the longshore extent of the influence of inlets on the adjacent barrier islands using three criteria, all of which employed shoreline change rates. Two sites were examined and it was found that along the outer banks of North Carolina, the influence of Oregon Inlet extended up to 13.0 km from the inlet whereas for the tide dominated inlets of the Virginia shoreline, the influence extended up to 6.1 km from the three inlets examined.
Overall, the results of examinations of various methods of shoreline position analysis have shown linear regression based on the best least squares fit to be a very reasonable method unless known changes have occurred that will induce a different trend over recent times. These changes could include modifications of an inlet, beach nourishment, placement of a structure that will impede the natural flow of sand along the shoreline, or a landslide or flood that delivers a large source of new sand to the shoreline. Although natural shorelines exhibit cyclic behavior which is not captured by a linear trend, a priori knowledge of the future timing of the cycles is required to appropriately incorporate this cyclicity into the analysis.
Knowledge of the trends of shoreline change and the fluctuations about these trends are both important in considerations of rational coastal management policies. Although the magnitudes of the fluctuations about the trend can amount to several decades of the trend component, there have been very few studies focused on shoreline variability. No studies have been found which examined the character of the shoreline deviations about




the trend line and the relationship between the magnitudes of these deviations to inlet proximity.
1.4 Report Organization
This study consists of 5 chapters. Chapter 2 provides general views on causes of shoreline changes and factors related to shoreline changes along the coast of Florida. Chapter 3 discusses shoreline change analysis procedures. In Chapter 3.1, long-term shoreline change trends along the coast of Florida are analyzed, and based on these results and various considerations, interpreted in terms of net longshore and cross-shore sediment transport components. The best least squares fit method is used to analyze the shoreline change trends and the conservation of sand equation is applied in the analysis of sediment transport. In Chapter 3.2, the standard deviation of shoreline deviations is calculated for each location and the empirical cumulative distribution of the standard deviations for each county is modeled by two best-fit theoretical distributions: the modified Rayleigh distribution with two parameters and the modified Weibull distribution with three parameters. The Kolmogorov-Smirnov test is employed to evaluate the goodness of fit of these theoretical distributions to the standard deviations. The effects of inlets on the standard deviations are identified. Chapter 4 presents and discusses results. All of the results are presented county by county, and some are also shown island by island, regionally. Chapter 5 provides the summary and conclusion for this study. Because of the large numbers of tables and figures in Chapter 4, the tables and figures are orgnized at the end of this chapter rather than after first-mention.




CHAPTER 2
FLORIDA'S COAST SETTING
There are twenty-five predominantly sandy shoreline counties along Florida's coastline of 1270 km. In this study, the Florida's coastline is considered in three segments: the east coast with 12 sandy counties, the north west coast with 7 sandy counties and south west coast with 6 sandy counties, see Figure 1- 1, which also shows the number of DNR numbers in each county. These monuments denote the locations at which long-term shoreline positions are available and to which the shoreline position data are referenced. The characteristics of Florida coast setting are addressed in the following sections.
2.1 Longshore Sediment Transport Characteristics Coastal sediment transport includes components of longshore and cross-shore transport. The former is dominantly the result of oblique waves generating wave-induced longshore currents, while the latter is due to wave-induced cross-shore water particle motions and the undertow. Cross-shore transport is most pronounced during periods of storm-induced elevated water levels and severe waves. Longshore sediment transport can occur along a coastline in two directions, depending on the wave direction. For Florida, southerly directed transport is defined as positive for the east coastline, while westerly and northerly directed transports are defined as positive for the northwest and southwest coastlines respectively. Net transport is the difference between the longshore transport in




the two directions. Gross transport is the sum of the absolute transports in the two directions, thus oniy net transport has an associated sign. Both net and gross transports are important quantities in coastal engineering design. The U. S. Army Corps of Engineers (1954) estimated that the total westward longshore transport amounts to an average of about 140,000 m 3/yr at the state's western boundary. Dean and 0' Brien (1987) presented comprehensive estimates of net annual longshore sediment transport along Florida's coast. Considering shoreline change trends and previous estimates of longshore transport, this paper will provide a detailed examination of sediment transport along Florida's coast.
2.2 Sediment Characteristics
The beach generally consists of a variety of materials, although the dominant components are quartz, and shell. Sediment characteristics, which include grain size, density, shape, and surface texture, or fall velocity that contains comprehensive information of sediment behavior, play an important role in the shoreline response to storms and human activities. Along Florida's east coast, the average sediment size ranges from 0. 1 mm to 1 mm. Most average sediment sizes of the northern sandy counties range from 0. 1 mm to 0.2 mm (Charles, 1994). For the southern sandy counties, the variation of average sediment size is relatively greater, and the increase in the average sediment size from north to south is due dominantly to the increasing shell content. This longshore gradient in sediment size affects the equilibrium beach profile, response to storms and possibly sediment transport rates. Along Florida's west coast, however, no comprehensive studies of sediment characteristics have been conducted.




2.3 Sea Level Change
Sea level change is a long-term process, which affects shoreline stability. Generally, increases and decreases in relative sea level will cause the shoreline to recede and advance, respectively. There are 6 long-term tide stations in Florida, from which the average annual sea level change rates can be obtained. In Florida, contrary to the above relationship, the average shoreline is advancing while the long-term average relative sea level is rising at approximately 2 mm/year (Dean, 1994).
2.4 Human Effects
Human effects on shorelines can cause beach erosion or accretion. The dominant erosion cause in the area of concern by far is the result of construction of new entrance channels and the modification of existing entrance channels for navigational purposes. Usually these entrances include two jetties to prevent sand from entering the channel and dredging of the channel to a depth greater than natural. Additionally, past practices of placing channel maintenance material in deep water have left a legacy of erosion near many entrances along Florida's coast. Groins, and in some cases seawalls, can redistribute sand available in the nearshore system. Nourishment, the placement of large quantities of good quality sediment in the nearshore system to advance the shoreline seaward can cause accretion over fairly large segments of shoreline.




CHAPTER 3
ANALYSIS PROCEDURES
3. I-Shoreline Change Trend Analysis
The long-term shoreline change rates at individual locations are first examined directly from the data set using the linear regression based on the best least squares fit procedure, which is described in the following section. To obtain an overall assessment of shoreline stability, the average long-term shoreline change rates are calculated by averaging the shoreline change rates at individual monument locations within the regions of interest. Two different geographic entities are considered in developing shoreline change characteristics: (1) counties and (2) the various islands along Florida's coast. For these counties and islands, the analyses are carried out for two periods: (1) the complete period for which the shoreline position data are available and (2) pre-1970s. The latter data are of interest as they preceded the extensive nourishment activities that have occurred over the last 25 or so years. For comparison and verification, the average shoreline change rates for the complete period are also computed by the second approach (Method 2), which is based on the best least squares fit to the average shoreline positions within the regions of interest. The average shoreline position for a series of monuments is determined by averaging the shoreline positions of the individual locations for each survey. Method 2 is somewhat less suitable for analysis since it requires more complete data sets for the particular county or island under consideration. Based on the shoreline




change trends, the conservation of sand equation, and various reasonable considerations, net longshore and cross-shore sediment transport components are calculated to interpret shoreline changes.
3.1.1 Shoreline Change Trend
The long-term shoreline change rate at each location is determined by the linear model to fit the available shoreline position with time:
(Y)ij = a j ti + b j (3.1)
where (Yt)v is the predicted shoreline position corresponding to a given value of time ti at a longshore position, xj, and aj is the long-term shoreline change rate. A zero value of aj indicates that the shoreline position is stable over time whereas positive or negative values of aj denote an advancing or receding shoreline, respectively. The quantities aj and bj in this model can be calculated based on the least-squares method, in which the sums of squares of the differences in shoreline position between the measured data and the best-fit straight line are minimized.
3.1.2 Sand Conservation
The changes in shoreline position are interpreted separately as if they were caused entirely by either gradients in longshore sediment transport or cross-shore sediment transport; both interpretations are based on considerations of sand conservation. It is realized that the actual changes are due to a combination of longshore and cross-shore sediment transport components.




Sediment transport is computed in a local coordinate system in which the x-axis is oriented along the shoreline and the y-axis is directed offshore, as illustrated in Figure 3h.
Figure 3-1. Coordinate system for sediment transport
For Florida's east coast, the origin of the coordinate system is located at the north border of Nassau County, the northernmost county on Florida's east coast. For Florida's northwest coast and southwest coast, the origins of the coordinate systems are located at the western end of Franklin County and at the southern end of Collier County, respectively (Figure 1-1).
The following governing equation is based on the conservation of sediment volume for a control area and is the basis for computing transport components.
h qx s (3.2)
at ax ay




where q, and qy denote the local sediment transport rates per unit width in the longshore and offshore directions respectively, h and s denote the local depth of water and an additional source term representing any material added per unit area per unit time.
Integrating Eq. (3.2) across the profile from y = yj to y = Y2 leads to
a __ X Y2
tw X Q +qy(X, y2,t)-qy(x, yl,t)- fsdy (3.3)
E) t a x YI
and since
a vw avs
+ = 0 (3.4)
a t ax
a Q, _a ~V Y2
Qx__ qy(x,y2,t)+qy(x,yl,t)+ fsdy (3.5)
a3x a t Y1
where Vw is the volume of water per unit length of shoreline; Vs is the volume of sand per unit length of shoreline; Qx denotes total volumetric longshore sediment transport rate; qy (x, Y2, t) is the sand transport rate out of the control volume at the offshore limit, Y2, and qy (x, yl, t) is the transport rate into the control volume at the inshore end ( yj ) of the profile, the latter of which is considered to be zero. If no material is added to the profile artificially, such as beach nourishment, or removed by dredging, the value of the fourth term on the right hand side of Eq. (3.5) is also zero.
For a shoreline position, y(x, t), relative to a fixed reference, it is assumed that as y(x, t) changes, the entire profile moves without change of form over the active vertical dimension, h.+B, where h. is the so-called "depth of closure" and B is the berm height (see Figure 3-1). Thus AV, can be expressed as AV, = Ay(h, + B) (3.6)




The following equation can be established from Eqs. (3.5) and (3.6).
8 Y 8 Qx+qyX
-(h. + B) + qY xy2,t) (3.7)
a t OX
3.1.3 Total Net Longshore Sediment Transport Difference
With the above framework, we will first examine the longshore sediment transport distribution along Florida's east coast, northwest coast and southwest coast, respectively, considering the influence of cross-shore transport to be negligible (q( y2 )=0) in Eq. (3.7), which results in
x = -(h. + B) Y (3.8)
Now, integrating along the beach from one end of the study area (at x = x, ) to another xi, we have
Q (xi,t)- Q (x,t) ( h* + B)-d (3.9)
xi t
where h. and B for Florida's coast are obtained from Dean and Grant (1989). The partial derivative -, from Eq. (3.1) is
Bt
8 y(x,t) )
y(x, tj) a(x) (3.10)
at
where a(x) is obtained from Eq. (3.1).
The integral of Eq. (3.10) is approximated by the trapezoidal rule Xi 1 i
J f(x, tj )dx = I[f(xk-ltj) + f(xk,tj)](xk -Xk-1) (3.11) X1 2 k=2

where k = 2,3,4,..., i.




Based on Eqs. (3.9), (3.10) and (3.11) the difference in net longshore sediment transport at point xi from that at xl can be determined by
Q (xi,tj) Q (xI,tj) = --(h, + B) I[a(xk-l) + a(xk)](Xk xk-1) (3.12)
2 k=2
where i = 2,3,4,...,n.
3.1.4 Local Cross-Shore Sediment Transport
Local cross-shore sediment transport is computed using Eq. (3.13) obtained from rewriting Eq. (3.7) with the consideration of a uniform average gradient of longshore sediment transport.
qy(x, Y2,t) = -a(h. + B) -- Q(3.13)
where a is the long-term value obtained from Eq. (3.1) and -Q is calculated based on previous estimates of net longshore sediment transport along Florida's coast. For the east coast, these estimates were obtained predominantly of sand impoundment against the updrift sides of newly constructed jetties. The net longshore sediment transport at the northern end of the state on the east coast is believed to be on the order of 460,000 m3/yr (south), whereas near the southerly terminus of the sandy beaches, the value is estimated to be approximately 7,000 m3/yr (south) (Dean and O'Brien, 1987a). Thus the approximate gradient in longshore sediment transport can be obtained based on the length of 570 km along the east coast of Florida, resulting in
- 0.8 (M2 / year) (3.14)
OX




For the northwest coast, the approximate gradient in longshore sediment transport is +0.4 m 3/mlyr based on a transport of 140,000 m 3/yr (U. S. Army Corps of Engineers, 1954) at the state's western boundary and zero transport at the eastern limit of the northwest counties. An average zero gradient in longshore sediment transport is assumed for the southwest counties.
3.2 Analysis of Standard Deviation of Shoreline Deviations
The previous section discusses the long-term shoreline change trend, which can be represented by a best-fit straight line. However, the shoreline positions exhibit large deviations about the trend lines. The shoreline deviations could be due to many factors, for example, seasonal variations, storm events, cumulative storm effects, migrating sand waves, anthropogenic alterations, such as construction of jetties, etc., and of course, errors in the recorded shoreline positions. The processes that govern shoreline fluctuations are far from being completely understood. This section addresses measurements of shoreline deviations and the characterization of the distributions of the standard deviations of shoreline deviations about the trend lines. Each standard deviation is associated with one profile, which quantifies the distribution of shoreline deviations about the trend line at that particular location. The statistics of the standard deviations can be used as a basis for the prediction of shoreline deviations which in turn is applicable to coastal zone management. For this purpose, based on a combination of the features of the standard deviations and some knowledge of the processes, this section focuses on two components: (1) the statistical cumulative distribution of the standard deviations of shoreline deviations and a test whether or not the Rayleigh and Weibull distributions fit




the standard deviations reasonably, and (2) the effects of inlets on shoreline deviations. In this study, both normalized data and unscaled data are considered. Since the influence of inlets on shoreline changes is great and may belong to a different statistical distribution, in (1), only the shoreline position data outside of the influence of inlets are analyzed based on the criterion that the standard deviations of shoreline deviations must be approximately uniform along the shoreline. It will be shown that the standard deviations of shoreline changes are substantially greater in the vicinity of inlets. The examinations described above are carried out for all of the twenty-four Florida predominantly sandy shoreline counties, see Figure 1 -1.
3.2.1 Definition of Standard Deviations of Shoreline Deviations
The shoreline deviation about the trend line is defined by
(Ay)ij= (Ym)ij (Yr),y (3.15)
where ym, and y, indicate the measured shoreline position data and the shoreline position based on Eq. (3. 1), respectively. It is significant to note that this approach forces the mean of shoreline deviations over time for all locations to be zero, as well as the average value of shoreline deviations over time to be 0 for a fixed location.
Based on Eq. (3.15), the standard deviation of shoreline deviations for each location is computed by
j k ((Ay1 )j-(Ay)j)2 1(k 1) (3.16)




where Ay, is the shoreline change deviation about the best-fit line with time at each j location and Ay is the average of Ay,; i = l,2,3,...,k., and k denotes the number of the years for which shoreline position data are available at the examined location.
3.2.2 Model Consideration
Since the standard deviations of shoreline deviations are positive, the Weibull and Rayleigh cumulative distributions, which use random variables, the values of which are greater than 0, are considered as candidate models to fit the standard deviation distributions. To improve the goodness of fit of these models, the Weibull and Rayleigh modes are proposed which allow for zero offsets for these distributions. The solution for the normalized standard deviations is easier to obtain and also provides a basis for the more difficult solution of the unscaled results. Thus, the normalized data are analyzed first, followed by an examination of the unscaled data. The normalized data are calculated by scaling the individual values of the unscaled data by the same constant, which is the root-mean-square value of unscaled standard deviation within the group being considered.
3.2.3 Analysis of Normalized Standard Deviations
This section focuses on comparisons of the cumulative distribution functions (CDF) (also called probability distribution functions) of sample normalized standard deviations for all locations within each county with the Weibull and Rayleigh distributions.
Since the size of the data set of interest is relatively small and every individual in the data has the same chance of being selected, the CDF is calculated by a step function,




F(xi) = i 1/n, where xi and n are the normalized standard deviation and the data size, respectively; X, in ascending order: X1 < x2 <... < xi <... Xn
The Weibull probability density function is defined as
f(x)=Anx"-'e-", 0 Integrating from 0 to x yields the cumulative distribution function F(x) = 1-e-a 0< x where n is the parameter that determines the shape of the distribution and A is the scale parameter that determines the spread. Both A and n are positive and non-dimensional. These parameters can be estimated by fitting data to the model based on the best least squares method and Newton-Raphson procedure. However, with the estimated parameters, it was found that the distribution does not provide a good fit to the individual points corresponding to the smaller data values. One way of addressing this deficiency is to include an "offset". Thus a new parameter, x0, is introduced to yield a modified Weibull distribution, called a three-parameter Weibull distribution, as shown below.
F(x)= -e -A(xxoY', 0--< XO< Xmin 0 where n and A have the same definitions as those in the two-parameter Weibull distribution; x0 is the non-dimensional offset parameter; Xmin represents the minimum of the normalized data values. The reasons for the range of x0 are (1) a restriction of the CDF is that the probability represented must increase from 0 to 1 monotonically, and (2) all the parameters should be real numbers. If x0 is equal to or greater than Xmin, based on the iterative process for solving the parameters, the probability could be multivalued or the numerical solution could become unstable or imaginary. Based on the best least




squares method and Newton-Raphson procedure, the iterative process determining the three parameters is described as follows.
(1) Fix x0 = 0. For the trial values of Ak and nk, the theoretical cumulative frequency is equal to
F(xi) = 1 e-Ak(xi-xo)nk (3.20)
where for this starting case, x0 = 0 and xi is an individual data value; i = 1,2,..., m, m is data size; k = 1,2,..., K, K is number of iterations. Then, the error between data and model is defined as
S i (Ak nk) = Fe(xi) -1 + e-Ak(xi-xo)nk (3.21)
OJ~i i .
Si+1(Ak + AAj, nk +Anj) = Fi (Ak, nk) + i Anj + AAj (3.22)
where Fe (xi) denotes the empirical cumulative frequency; AA and An are unknown F-i -'_._ are the partial derivatives changes of A and n, respectively; j denotes locale; and are the partial derivatives aA an
of s i with respect to A and n, respectively, given by =a = -(x-xo)nk e-Ak(xi-x0o)nk (3.23)
aA
a = -Ak(Xixo)nk e-Ak(xi-xo)nk ln(xi x0) (3.24)
an
k
To find the minimum of ,-2(Ak+AAj,nk+Anj), differentiate with respect to the i=1
increase of each parameter and equate to zero. Differentiating with respect to AA and equating to zero gives




m = i A~i D= i _i) 0
m-, i, aP-' +An jm I -i)+ ~ Y(- =0(3.25)
i a A "=1 na = AD
Differentiating with respect to An and equating to zero gives
M: aE i= i E i = aEi 0i
(Ei + An j ( b AAj ( (3.26)
a= n an an i= A an
Anj and AAj can be solved from the two basic equations obtained above. Therefore,
Ak+I = Ak + AAj (3.27)
nk+l = nk + Anj (3.28)
We may now use Ak+l and nk+1 and repeat the process to obtain improved A and n values until a check on the sizes of AA and An indicates that additional iterations are not necessary. The final values of AA and An should be very small. Calculate the mean square error after obtaining the solutions. This procedure for estimating parameters under constraint is illustrated in Figure 3-2.
(2) The value of x0 is increased in steps of 0.01. For each x0, repeat 1) until the smallest error for the range of x0 is obtained when A, n and x0 corresponding to this error are the solutions.
Also, the parameters may be examined graphically by a two-dimensional error contour plot, which portrays the magnitude of the error and provides an estimate of the unknowns and demonstrates the sensitivity of the solution to the parameters. The objective is to display the error as a function of the two variables A and n at a given x0 that describes the error resulting from the modeling,




Figure 3-2 Illustration of the iterative process




error(xo,A,n)=-Y' (xo,A,n) (3.29)
m i=1
The function can then be evaluated directly and graphed. Compared with the iteration process, more work and less accuracy are associated with obtaining estimates A and n by using error contour plotting. However, the error contour plotting has the advantage over the iteration process of allowing visualization of the magnitude of the error and the solutions of the parameters. Therefore, the error contour plotting may be employed to verify the solutions and character of the error surface resulting from the iteration process.
For comparison and verification, a two-parameter Rayleigh distribution, which is a particular case of a three-parameter Weibull distribution, is used as a model.
F(x) = 1 e-a(xx), 0 < XO < Xmin, 0 The Rayleigh distribution is equivalent to n=2 of the Weibull distribution described above. The approach to determining parameters for this model is similar to that for the Weibull distribution, and similarly, the error plotting method can also be used to examine the variation of the error as a function of the parameters for this model. Compared to the Weibull model, the error associated from the Rayleigh model is a single curve, instead of contours, due to only one variable, A, for a given x0.
3.2.4 Analysis of Unscaled Standard Deviations
For the unscaled standard deviations, the parameters in the above models also can be obtained via the iteration process. However, if the parameters for the models fitting to the normalized standard deviations are available, an easier method may be employed to




determine the parameters for the models for the unscaled standard deviations. This method is given as follows.
As described in the previous section, the Weibull cumulative distribution model fitting to the normalized data is
F(x) = 1 e-A(x-xo', 0 x0 < Xmin, 0x where x'= Xr,,,s x or x=x'/xrmn and Xrs is the root-mean-square value of the unscaled data; x' denotes the unscaled data values; A', n' and x0' are the parameters for this model. It is noted that in Eq. (3.31), A' has units corresponding to the units of x', for example, the units of A' are 1/mn if the unit of x' is m, while n' is non-dimensional. Since x is obtained by dividing x' by the root-mean-square value of the unscaled data that is constant, random variables X' and X must be identically distributed.
F' (x') F(x) (3.32)
Then,
A'(x'-xo')'" (X'-XoXrms) (3.33)
Xrms
Thus,
n'- n (3.34)
A'- A/xns (3.35)
xo'= xo Xrms (3.36)




By the same approach above, the analysis of the Rayleigh cumulative distribution model fitted to the unscaled data leads to
A A/xrmS (3.37)
xo XOXrms (3.38)
3.2.5 Model Test
To evaluate the significance of the fits to the cumulative distribution function models described above, the Kolmogorov-Smirnov (K-S) test is employed. This procedure evaluates the goodness of fit of a model to the data of interest. It is a comparison between two quantities: (1) the K-S statistic, Dn, which is the maximum absolute difference between observed and expected cumulative frequencies obtained based on a proposed model, and (2) a critical value K corresponding to different significance levels and different sample sizes. The proposed model is the null hypothesis (Ho) against the alternative (HI) that it is not correct. A certain significance level, a, is the probability that we erroneously reject Ho if it is true, which can be expressed as x = P(Rejecting Ho /Ho is correct} (3.39)
The larger the value of ox, the higher the risk of erroneous rejection. Therefore, the significance levels used in the test are very small. If the sample size is greater than 35, the relationship between a critical value K and a certain significance level corresponding to K can be expressed approximately as
K = ln(a/2) / 2n (3.40)

Three commonly used standards are




=0.10,K = 1.22/-,n
cc = 0.05, K = 1.36/-,n
ac = 0.01,K = 1.63/n
Another standard which will be used in this study is x= 0.001, K = 1.95/VIf Dn > K(a, n), which means that the probability that we get a Dn value, if the null hypothesis is true, is smaller than the significance level X, the null hypothesis will be rejected. If Dn < K(ox, n), on the contrary, the null hypothesis will be accepted. The significance level a may be called a Type I error. On the other hand, if we fail to reject it when it is not correct, a Type II error occurs. However, in this study, only a Type I error is considered.
3.2.6 The Influence of Inlets
Both natural and constructed inlets can result in significant interruptions of longshore sediment transport patterns and alterations of cross-shore sediment transport. In general, these effects of jettied inlets on shoreline changes will typically lead to updrift accretion and downdrift erosion, whereas for unmodified inlets, the effects are an increase in the variance in the adjacent shoreline positions. It will be demonstrated that the shoreline change trends in proximity to inlets are significantly greater than those outside the influence of inlets. The magnitudes of shoreline changes near inlets are usually greater than those far away from inlets and the shoreline deviations including the influence of inlets tend to have large variances.




CHAPTER 4
RESULTS AND DISCUSSION
4.1 Shoreline Change Rates and Sediment Transport Shoreline change rates at individual monument locations along Florida's coast are calculated by the linear regression method. The average of the best least squares fit to individual shoreline positions at each location ( Method 1) results in the average shoreline change rates for the regions of interest. For comparison and verification, the average shoreline change rates for the 12 counties on the east coast are also computed by the second method (Method 2), which is based on the best least squares fit to average shoreline positions. Additionally, the averages are obtained over two different regions: county-by-county and island-by-island, and for two different time periods: all data and pre-1970 data. Based on the shoreline change rates, the longshore and cross-shore sediment transport components are examined by using the conservation of sand equation. The following two sections present the shoreline change rates and sediment transport for Florida's east coast and west coast, respectively. As noted previously, due to their large numbers the figures and tables in this chapter are grouped at the end of the chapter.
4. 1.1 East Coast Counties and Islands
Figure 4-1 presents the variation of long-term shoreline change rates along Florida's east coast. Duval County has the most severe localized shoreline erosion and it also has a much larger shoreline accretion. The largest positive shoreline change occurs in St. Johns




County. Both Volusia County and Martin County have significant shoreline changes, advancing for the former and retreating for the latter. In general, the larger shoreline change rates occur near inlets, usually accretion updrift and erosion downdrift. Without exception, all of the "spikes" observed in Figure 4-1 are at inlet locations. Figure 4-2 presents 12 examples of shoreline positions at individual monuments versus time, one for each county on the east coast. The dashed line presents the trend line based on the best least squares fit, while the solid line connects the measured shoreline positions. These examples were selected to be reasonably representative of the long-term shoreline change rates for the individual counties. These results also demonstrate the variability in shoreline positions with time at individual monuments. To better understand the distribution of the recession or advancement rates along each county on the east coast, histograms of long-term shoreline change rates (all data) are provided in Figure 4-3. In each histogram, the horizontal axis represents shoreline change rates, with the vertical axis indicating the number of monuments that have the corresponding erosion or accretion range in that county. The horizontal scales in Figure 4-3 are the same for all counties to facilitate comparison.
Table 4-1 summarizes the long-term shoreline change rates for each county on the east coast using the two procedures and the periods of time for which data are available. With the concern of effects of beach nourishment projects which started in the 1970's on the east coast of Florida, the long-term shoreline change rates limited to pre- 1970s obtained by Method 1 are also presented in this table. As shown in this table, the values of the shoreline change rates for the two periods based on Method 1 are approximately equal for




all sandy beach counties except Dade County. For Dade County, the shoreline change rate including the 1986 data is +0.30 mlyr, whereas, the shoreline before 1970 exhibited a long-term retreat trend at 0.01 rn/yr. The absolute difference between these two values are very large relative to those for other counties. In a more detailed examination of the long-term shoreline change rates at 74 individual monument locations available north of Government Cut within Dade County, 24 of the 74 beach profiles have a recessionary trend before the 1976-1981 Beach Nourishment Project, whereas, including the 1986 data, 72 of the 74 beach profiles were characterized by long-term advancement. Obviously, this is due to the effect of the major Miami Beach Nourishment Project constructed north of Government Cut from 1976 to 1981. The Miami Beach Nourishment Project is considered a major success with over 20 years experience (Wiegel, 1992). To illustrate the shoreline change trends more completely, the following discussions are based on the entire period of time for which data are available unless noted otherwise. Of the 12 counties, 10 are characterized by average shoreline advancements based on the results from Method 1. The maximum rate of shoreline advancement rate is + 1.01 rn/yr for Duval County while the minimum value is +0.0 1 rn/yr for Broward County. Only two counties, St. Lucie County and Martin County, which are contiguous on the central east coast of Florida, have a long-term shoreline retreat trend. In comparison with the results from Method 1, Method 2 results in 9 counties with advancing shorelines and 3 counties with receding shorelines. The results obtained by the two methods are approximately the same for most counties. Although the shoreline change rate at Broward County is negative (-0.02 mlyr) by Method 2 and positive (0.01 rn/yr) by Method 1, the magnitudes




of these two values are very small relative to those for other counties. Therefore, Broward County can be considered to be characterized by an approximately neutral shoreline. Figure 4-4, based on Method 2, provides the detailed average shoreline change over time for each county on the east coast. As shown in this figure, all of the counties except Martin County exhibit either a trend of advancement or a nearly neutral condition. Also for some of the counties, especially Dade County, the recent effects of beach nourishment are evident. These results presented in Figure 4-4 are consistent with those in Table 4-1.
The following discussions of results in Tables 4-2 and 4-3 are based on Method 1 since there are no significant differences between results obtained from the two methods and Method 2 requires more complete data sets.
As shown in Table 4-2, the shoreline change rates for the complete time period available for the upper east coast (6 counties, 1113 profiles) and lower east coast (6 counties, 828 profiles) are 0.48 rn/yr and -0. 12 rnlyr, respectively. On average, Florida's east coast shoreline is advancing at a rate of 22 centimeters per year. The average erosion on the lower east coast counties is due to Martin County where St. Lucie Inlet (cut in 1892) has resulted in severe beach erosion to the southerly Jupiter Island. Limiting considerations to pre-1970 data, the average rate of advancement of the east coast of Florida is 16 cm/yr. Thus, by inference, the effects of the extensive beach nourishment projects have resulted in an average shoreline advancement rate of 6 cm/year prorated over the approximately 120 year period or 0.52 m/yr prorated over the approximately 20 years of nourishment activity. It is noted that the increasing trend toward shoreline advancement over the past 20 years is much greater in the southern six counties than in




the northern six counties which is consistent with the concentration of extensive nourishment activities in the southern portion of the state.
Grouping the data by islands results in the shoreline change rate of each island presented in Table 4-3. Comparing the shoreline change rates limited to pre-1970s with that limited to the more complete period leads to a result similar to that in Table 4-1. Based on the more complete period of time, of the 20 islands, 12 exhibit long-term advancement and 8 have a recessional trend. The maximum value (2.02 m/yr) for advancing shoreline occurs at Island No.2 (Little Talbot Island) and the maximum recessional value (-1.69 m/yr) occurs at Island No.10 (Jupiter Island) which is south (downdrift) of St. Lucie Inlet.
The longshore variation of long-term net longshore sediment transport difference along the eastern coast of Florida is presented in Figure 4-5. Recall that this result, based on Eq. (3.12), considers the cross-shore sediment transport and source terms to be zero. Only two counties, Martin County and St. Lucie County, clearly show positive values of longshore gradient of longshore sediment transport, implying a long-term shoreline recessional trend. Most other counties have negative values of longshore gradients of longshore sediment transport, due to long-term shoreline advancements. Since these results are based on the conservation of sediment, they are consistent with the shoreline change characteristics in Table 4-1 and Figure 4-1. Based on the considerations here, the longshore transport decreases along the northeast coast and increases along the coastlines of St. Lucie and Martin Counties. The gradient of the longshore transport along the southeast coast is relatively small. The maximum value of the longshore transport




differences occurs at the border between Nassau County and Duval County, while the minimum occurs at St. Lucie County. Figure 4-5 is based only on long-term shoreline position changes, with the consideration of zero cross-shore transport. Considering the net southerly transport at the north end of the State to be 460,000 M3 /yr, Figure 4-5 indicates the net transport to change direction (to northerly) somewhat south of the midpart of St. Johns County and to remain northerly to the southern end of the region considered, where the net transport would be northerly at a rate of approximately 480,000 m 3 /yr. This unrealistic result supports the presence and significance of a net cross-shore (landward) sediment transport as a major contribution of shoreline advancement along the east coast of Florida.
Figure 4-6 presents local cross-shore sediment transport along the east coast of Florida under the assumption of a uniform gradient in longshore sediment transport based on previously estimated values, see Eq. (3.13). Large values of local cross-shore transport along this coast are not evident, except at locations of inlets. The maximum local crossshore transport is approximately 220 m 3/mlyr and occurs in Duval county, while the minimum (approximately -155 mn3 /mlyr ) is in St. Johns County. Since these local crossshore rates are based on the conservation of sediment, they are consistent with the total average net longshore sediment transport considered and shoreline changes. The average cross-shore transport is -0.8 mn3 /m/yr (directed onshore), some of which could be accounted for by biogenetic production (shells and coral) representing a continuing source term.




4.1.2 West Coast Counties and Islands
Figures 4-7 and 4-8 present the variation of long-term shoreline change rates along Florida's northwest and southwest coasts, respectively. For the northwest coast, Franklin County has the largest positive shoreline change rate and it also has a large shoreline recession; Gulf County has the most severe localized shoreline erosion. For the southwest coast, the largest positive and negative shoreline changes occur near Hurricane Pass at Pinellas County. Compared with Pinellas County, other counties have much smaller shoreline changes, but they all have substantial shoreline fluctuations around zero. With one exception all of the "spikes" observed in Figure 4-7 and Figure 4-8 are at inlet locations. This exception is near a cape (Cape San Blas in Gulf County). Figure 4-9 presents 12 examples of shoreline positions at individual monuments versus time, one for each county on the west coast. Histograms of long-term shoreline change rates (all data) are provided in Figures 4-10 and 4-11 for each county on the west coast. The information shown in Figures 4-9, 4-10 and 4-11 is similar to that shown in Figures 4-2 and 4-3 for the counties on the east coast.
Table 4-4 summarizes the long-term shoreline change rates for each county on the west coast using the two periods of time described earlier by Method 1. It is seen that the values of the shoreline change rates for the pre-1970s and total period are approximately equal for most counties. Any differences attributable to beach nourishment would indicate a greater advancement/less recession for the total period compared to the pre1970s. There has been much less nourishment on Florida's west coast compared to its east coast with only Pinellas, Sarasota and Lee Counties on the west coast receiving




substantial nourishment during the periods encompassed in the data base. Of these three counties, only Pinellas and Lee Counties show significant differences consistent with anticipated nourishment effects. The relative increase for Pinellas and Lee Counties are 0.55 m/yr and 0.26 rn/yr, respectively, prorated over the full period of record. Over the post-1970 period, the change in rates for Pinellas and Lee Counties are +3.4 rn/yr and +1.5 rn/yr, respectively. For the entire period, of the 12 counties, 6 are characterized by average shoreline advancements and 6 are characterized by average shoreline retreats based on the "All Data" results in Table 4-4. The maximum rate of shoreline advancement rate is +0.50 m/yr for Okaloosa County and the maximum rate of shoreline retreat rate is -0.51 m/yr for Gulf County.
Table 4-5 summarizes the long-term shoreline change rates for the northwest coast, the southwest coast and the entire west coast, respectively. The shoreline change rates for the complete time period available for the northwest coast (6 counties, 936 profiles) and southwest coast (6 counties, 892 profiles) are -0.16 m/yr and +0.12 rn/yr, respectively, whereas, the shoreline change rates before 1970 for the northwest coast and southwest coast are -0.27 m/yr and -0.03 m/yr, respectively. On an overall average, Florida's west coast shoreline is eroding at a rate of 2 cm/year for the complete time period. Limiting considerations to pre-1970s data, the average rate of erosion of the west coast of Florida is 15 cm/yr. Thus, considering this difference to be due to beach nourishment, the effect prorated over the full 110 year time period is a relative advancement of 13 cm/year. Prorated over the approximate 20 years encompassing beach nourishment, the prorated effect is a relative advancement of 56 cm/year.




Grouping the data by islands results in the shoreline change rate for each island on the west coast presented in Tables 4-6 and 4-7 for the northwest and southwest coasts, respectively. Comparing the shoreline change rates limited to pre-1970s with those for the more complete period leads to a result similar to that in Table 4-4. For the northwest coast, based on the more complete period of time, of the 11 islands for which shoreline position data are available, 5 exhibit long-term advancement and 6 have a recessional trend. The maximum value (1.36 m/yr) for shoreline advancement occurs at Island No. 5 which is west of Mexico Beach Inlet and the maximum recessional value (-2.34 m/yr) occurs at Island No. 4 which is west of East Pass into St. Andrews Bay. For the southwest coast, based on the more complete period of time, of the 28 islands, 15 exhibit long-term advancement and 13 have a recessional trend. The maximum value (2.32 m/yr) for shoreline advancement occurs at Island No. 2 (Caladesi Island) and the maximum recessional value (-2.33 m/yr) occurs at Island No. 22 which is north of Big Hickory Pass.
The longshore variations of long-term net longshore sediment transport rate difference along the northwest coast and southwest coast, of Florida, are presented in Figures 4-12 and 4-13, respectively. For those sandy beach segments without data (e.g., western end of Franklin County, Figure 4-12) or segments across inlets (e.g., Tampa Bay, Figure 4-13), it is considered for purposes here, that the shoreline changes and/or volumetric storage are zero. However, the potential contributions of entrances to longshore sediment transport can be substantial. For the northwest coast, Bay County clearly shows a positive value of longshore gradient of longshore sediment transport, implying a long-term shoreline recessional trend; Okaloosa County clearly shows a negative value of longshore gradient




of longshore sediment transport, implying a long-term shoreline advancement trend; the maximum value of the longshore transport differences occurs at Gulf County, while the minimum occurs at Franklin County; the longshore transport difference values are between -1.4x 105 +1.4x 105 m3/year. This range of values is considered reasonable and considering the transport to be small at the eastern end of Franklin County, the positive transport values (westward) in western Bay County and further west are consistent with previous estimates of 140,000 m3/yr (U. S. Army Corps of Engineers, 1955). For the southwest coast, Collier County and Pinellas County clearly show negative values of longshore gradients of longshore sediment transport, due to long-term shoreline advancements; the maximum value of the longshore transport differences occurs at the south end of Collier County while the minimum occurs at Lee County; the longshore transport decreases along the coastlines of Collier County and the south part of Lee County, whereas, the gradient of the longshore transport along the remaining part of the southwest coast is relatively small; the magnitudes of longshore sediment transport difference are on the order of 105 m3/yr. Again this range of sediment transport values is considered reasonable compared to existing estimates (Dean and O'Brien, 1987). These results are consistent with the shoreline change characteristics in Tables 4-4, and 4-5 and Figures 4-7 and 4-8.
Figures 4-14 and 4-15 present local cross-shore sediment transport along the northwest and southwest coastlines, of Florida, respectively, under the assumption of an average zero gradient in longshore sediment transport for the southwest counties and a gradient +0.4 m3/m/yr based on a transport of 140,000 m3/yr (U. S. Army Corps of Engineers,




1954) at the state's western boundary and zero transport at the eastern limit of the northwest counties for the northwest counties, see Equations (3.13) and (3.14). Large values of inferred local cross-shore transport along this coast are not evident, except at locations of inlets. For the northwest coast, the maximum local cross-shore transport is approximately 115 m 3/mlyr and occurs in Gulf County, while the minimum (approximately -80 M3 /mlyr ) is in Franklin County. For the southwest coast, Pinellas County has the maximum and minimum local cross-shore transport, which are approximately 45 M3 /mlyr and -180 m 3/mlyr, respectively. These results are consistent with the total average net longshore sediment transport gradient considered and shoreline change rates. On an average basis, the net cross-shore sediment transport for the northwest and southwest counties are +0.45 m 3/mlyr (offshore) and -0.68 M3 /mlyr (onshore) respectively. The latter is similar to the value found for the east coast of Florida.
It is noted that county maps are provided for reference in Figures 4-1, 4-5, 4-6, 4-7, 48, 4-12, 4-13, 4-14, and 4-15, respectively. As shown in these figures, the county lines approximate those shown in the plots on the left hand side of each figure. However, the locations of the county lines shown in the data plots are to be used for accurate positional reference.




4.2 Standard Deviation of Shoreline Deviations
4.2.1 The Effects of Inlets on Standard Deviations
Figures 4-16 to 4-40 present shoreline change rates (upper panels) and standard deviations (lower panels) versus monument number for each county. These lower panels in these figures also provide the basis for considering the shoreline position data without the influence of inlets. The vertical scales of these figures vary for each county to provide greater detail. Two features which these figures portray are noteworthy. One is that the greater the shoreline change rates are, in general, the greater the standard deviations. The second is that the larger standard deviations often occur near inlets. For these shoreline segments considered to be outside the major influence of inlets / entrances those portions of the standard deviation plots are indicated by a bold line. It is noted that one figure has been presented for Dade County for the period 1851-1986 (Figure 4-27) and Figure 4-28 represents the period 1851-1973, a period prior to the extensive 1976-1981 nourishment project.
4.2.2 Normalized Standard Deviations
The shoreline position data at monument locations which have approximately uniform standard deviations are considered as those without the influence of inlets, see Figures 4-16 to 4-40 for the bold line segments. Based on these selected shoreline position data, the standard deviations of the shoreline deviations at each predominantly sandy county along Florida's coastline have been analyzed by the techniques described earlier.




Figures 4-41 to 4-48 present the empirical cumulative distribution of normalized standard deviations compared with two models: the modified Weibull and Rayleigh cumulative distributions. All these figures show good agreement between the empirical cumulative distribution and the theoretical results. It is evident that the Weibull cumulative distribution fits the normalized standard deviations better than the Rayleigh cumulative distribution, since the Weibull cumulative distribution has one more parameter to be adjusted to fit the data. Tables 4-8 and 4-9 include results from applying the K-S test to test the goodness of fit for the models. It is interesting to see that at any significance level equal to or less than 0.01, the models are accepted for all counties.
The parameters of the models for the normalized deviations are summarized in Tables 4-10 and 4-11 for the east coast and west coast counties respectively. For the Rayleigh distributions, the least squares error values range from 1.87 x 10-4 to 6.1 x 10-3. For the Weibull cumulative distributions, the least squares error values range from 1.31 x 10-4 to 4.4 x 10-3. As shown in these tables, for each county, the errors associated with the Weibull model are dump less than those for the Rayleigh model due to one more fitting parameter in the Weibull model, and it appears that the errors associated with the two models approach certain limits. Additionally, the model parameters appear to be within certain ranges except for Nassau County. For the Rayleigh distributions, the range of A is from 0.96 to 7.85 with an average of 2.20; the range of xO is from 0.00 to 0.67 with an average of 0.29. For the Weibull distributions, the range of n is from 1.44 to 5.82 with an average of 2.79; the range of A is from 0.79 to 7.28 with an average of 1.67; the range of xO is from 0.00 to 0.62 with an average of 0. 17. No relationship is apparent between the




error and the maximum deviation between the empirical CDF and the theoretical CDF. In other words, if the model has a smaller error, that does not mean its maximum deviation is smaller, or vice versa.
Figures 4-49 and 4-50 provide two examples for examining graphically the error dependency on the parameters. Figure 4-49 shows the mean square error contour at x0 = 0 for the Weibull cumulative distribution fitting to normalized standard deviations for Martin County. Figure 4-50 presents the mean square error line at xo = 0.31 for the Rayleigh cumulative distribution fitting to normalized standard deviation for Martin County. These graphical relationships between the parameters and the mean square errors are consistent with the best fit values of the parameters in Table 4-10 for Martin County.
4.2.3 Unscaled Standard Deviations
The comparisons between the empirical cumulative distributions of unscaled standard deviations and the Weibull and Rayleigh cumulative distributions demonstrate the same information as represented in Figures 4-41 to 4-48, which is consistent with the method by which the normalized data are obtained and the method by which the empirical cumulative distributions are calculated; therefore, the figures presenting the comparisons of these distributions are not shown in this paper. Tables 4-12 and 4-13 summarize the parameters and errors for the Rayleigh and the Weibull cumulative distributions. It is significant to note four expected features: (1) for the unscaled data, the n' values for the Weibull cumulative distributions are the same as n for the normalized data, (2) For the unscaled data, the value of the parameter A' for the two models can be obtained by dividing A for the normalized data by the nth power of the root-mean-square value of the




42
unscaled data, (3) For the unscaled data, the value of the parameter x0' for the two models can be obtained by multiplying x0 for the normalized data by the root-mean-square value of the unscaled data, and (4) For the unscaled data, the errors from the models are the same as those for the normalized data. These features are consistent with the relationships between the model for the normalized data and the unscaled data, which are presented in Equations (3.34) to (3.38).




Table 4-1 Summary of shoreline change rates for Florida's east coast sandy
beach counties

All Data

Pre-1970 Data

Method I Method 2 Method I

Nassau

1857-1991

+0.50

+0.52

+0.64

Duval 1853-1990 78 +1.01 +1.61 +1.17
St.John 1858-1992 209 +0.88 +0.86 +0.92
Flagler 1872-1987 100 +0.04 +0.03 +0.03
Volusia 1873-1989 272 +0.33 +0.21 +0.26
Brevard 1874-1993 386 +0.36 +0.40 +0.27
Indian River 1880-1993 119 +0.18 +0.18 +0.15
St.Lucie 1860-1989 115 -0.14 -0.13 -0.24
Martin 1883-1986 127 -1.23 -1.37 -1.36
Palm Beach 1883-1991 227 +0.06 +0.05 -0.08
Broward 1883-1986 128 +0.01 -0.02 +0.00
Dade 1851-1986 112 +0.30 +0.25 -0.01
Note:
Method 1 represents the average of the shoreline change rates at individual monument locations. These change rates are determined by the best least squares fit procedure. Method 2 is based on the best least squares fit to the average shoreline positions for each county. The average shoreline position is obtained by averaging the shoreline positions of the individual locations for each survey.

coast

All Data

1853-1993

1~

+0.48

1851-1993 828 -0.12 -0.24
1851-1993 1941 +0.22 +0.16

Pre-1970 Data

+0.45




Table 4-3 Summary of shoreline change rates for Florida's east coast island by island I hoaaft mthnA 1'

All Data

St. Marys River to Nassau Sound

(Amelia)

1857-1991

+0.49

Pre-1970 Data

+0.64

Nassau River #2 1853-1990 23 +2.02 +2.75
to St. George Inlet (Little Talbot)
St. George Inlet #3 1858-1992 173 +0.15 +0.09
to St. Augustine Inlet
St. Augustine Inlet #4 1859-1986 73 +2.21 +2.22
to Matanzas Inlet
Matanzas Inlet #5 1869-1989 262 +0.15 +0.13
to Ponce De Leon Inlet
Ponce De Leon Inlet #6 1874-1989 290 +0.46 +0.35
to Port Canaveral Entrance
Port Canaveral Entrance #7 1876-1993 219 +0.23 +0.13
to Sebastian Inlet
Sebastian Inlet #8 1860-1993 152 +0.29 +0.24
to Ft. Pierce Inlet
Ft. Pierce Inlet #9 1860-1989 124 -0.26 -0.41
to St. Lucie Inlet (Hutchinson)
St. Lucie Inlet #10 1883-1991 97 -1.69 -1.72
to Jupiter Inlet (Jupiter)
Jupiter Inlet #11 1883-1991 63 +0.21 +0.10
to Port of Palm Beach Entrance
Port of Palm Beach Entrance #12 1883-1991 76 -0.14 -0.40
to South Lake Worth Entrance (Palm Beach)
South Lake Worth Entrance #13 1883-1991 71 +0.17 +0.13
to Boca Raton Inlet
Boca Raton Inlet #14 1884-1991 29 -0.14 -0.19
to Hillsboro Inlet
Hillsboro Inlet #15 1883-1972 61 +0.26 +0.25
to Port Everglades Entrance
Port Everglades Entrance #16 1883-1986 69 -0.09 -0.19
to Bakers Haulover Inlet
Bakers Haulover Inlet #17 1867-1986 48 +0.90 +0.43
to Government Cut (Miami Beach)




All Data

Government Gut to Norris Cut

#18
(Fisher Island)

1883-1972

-0.12

Pre-1970 Data

Norris Cut #19 j1883-1986 10 -1.32 -1.62
to Bear Cut (Virginia Key) ______ _____I____________Bear Cut #20 j1867-1986 24 -0.07 -0.22
*~'to South End of Key Biscayne _(Key Biscayne) _________________________Note:
The method represents the average of the shoreline change rates at individual monument locations. These change rates are determined by the best least squares fit procedure.




46
Table 4-4 Summary of shoreline change rates for Florida's west coast sandy

Escambia+Santa Rosa

1856-1978

All Data
-0.12

Pre-1970 Data
-0.19

Okaloosa 1871-1990 50 +0.50 +0.26
W TWalton 1872-1977 127 -0.14 -0.18
FLORDA Bay 1855-1977 144 -0.24 -0.39
Gulf 1857-1984 162 -0.51 -0.59
Franklin 1856-1979 239 -0.06 -0.23
Pinellas 1873-1987 187 +0.29 -0.26
Manatee 1874-1986 67 -0.14 +0.17
STSarasota 1883-1994 183 +0.04 -0.07
Charlotte 1860-1992 68 +0.18 +0.41
Lee 1858-1989 239 + 0.01 -0.25
Collier 1885-1988 148 +0.27 +0.39
Note:
Shoreline change rates shown above are the average of the shoreline change rates at individual monument locations within each county. These change rates are determined by the best least squares fit procedure.

rhanal ratpe fnr FIt

All Data

1855-1990

1858-1994 892 +0.12 -0.03
1855-1994 1828 -0.02 -0.15

Pre-1970 Data

-0.27




47
Table 4-6 Summary of shoreline change rates for Florida's northwest coast island by island

State Line
to Pensacola Pass

#1
(Perdido Key)

1858-1979

All Data
-0.04

Pre-1970 Data
-0.12

Pensacola Pass #2 1859-1989 163 -0.11 -0.17
to East Pass. Destin (Santa Rosa Island)
t East Pass. Destin #3 1855-1990 258 +0.03 -0.06
W to Panama City Channel (Mainland)
Panama City Channel #4 1855-1978 24 -2.34 -3.02
to St. Andrew Bay Entrance. East Pass (Shell Island)
to St. Andrew Bay Entrance. East Pass #5 1855-1978 6 +1.36 +1.02
to Mexico Beach Inlet (Crooked Island)
Mexico Beach Inlet #6 1868-1984 48 +0.60 +0.41
to Entrance to St. Joseph Channel (Mainland)
Entrance to St. Joseph Channel #7 1857-1984 131 -0.80 -0.85
to Indian Pass St. Joe Spit
Indian Pass #8 No Data
to West Pass (St. Vincent Island)
West Pass #9 1857-1980 51 +0.18 -0.12
to Saint George Island Channel (St. George Island)
Saint George Island Channel #10 1856-1980 98 -0.22 -0.39
to East Pass (St. George Island)
East Pass #11 1858-1980 44 0.24 -0.30
to Unnamed Channel (Dog Island)
Unnamed Channel to #12 1858-1980 46 -0.26 0.01
Ochlochnee River (Alligator Point)
Note:
Shoreline change rates shown above are the averages of the shoreline change rates at individual monument locations for each island. These change rates are determined by the best least squares fit procedure.




Table 4-7 Summary of shoreline change rates for Florida's southwest coast island by island

All Data

Pre-1970 Data

Gulf of Mexico to Hurricane Pass

#1
(Honeymoon Island)

1873-1987

+0.86

-0.08

Hurricane Pass #2 1873-1987 16 +2.32 +0.44
to Dunedin Pass (Big Pass) (Caladesi Island)
Dunedin Pass (Big Pass) #3 1873-1987 19 +0.54 +0.07
to Clearwater Pass (Little Pass) (Clearwater Beach Island)
Clearwater Pass (Little Pass) #4 1873-1987 73 -0.27 -0.56
to John's Pass (Sand Key)
John's Pass #5 1873-1987 17 +0.87 +0.14
to Blind Pass (Treasure Island)
Blind Pass #6 1873-1987 22 +0.34 +0.23
to Bunces Pass (Long Key)
Bunces Pass #7 1873-1987 25 -0.40 -0.84
to Tampa Bay Entrance (Mullet Key)
Tampa Bay Entrance #8 1874-1986 41 -0.36 -0.02
to Longboat Pass (Anna Maria Key)
Longboat Pass #9 1883-1987 55 -0.27 -0.07
to New Pass (Longboat Key)
New Pass #10 1883-1987 15 +0.71 +0.09
to Big Sarasota Pass (Lido Key)
Big Sarasota Pass #11 1883-1993 33 +0.83 +0.79
to Midnight Pass (Siesta Key)
Midnight Pass #12 1883-1994 37 +0.00 -0.26
to Venice Inlet (Casey Key)
Venice Inlet #13 1883-1993 90 -0.01 -0.08
to Stump Pass (Manasota Peninsula,
Manasota Key)
Stump Pass #14 1860-1992 36 -0.71 -0.87
to Gasparilla Pass (Knight,Bocilla,DonPedro,Little Gasparilla
Islands)
Gasparilla Pass #15 1860-1992 37 +0.23 +0.67
to Boca Grande Pass (Gasparilla Island)
Boca Grande Pass #16 1859-1989 39 +0.22 +0.24
to Captiva Pass (Lacosta Island)




Table 4-7--continued

All Data

Captiva Pass to Redfish Pass

#17
(North Captiva Isalnd)

1859-1989

Pre-1970

Data
-1.05 -0.72

Redfish Pass #18 1859-1989 27 -0.86 -0.81
to Blind Pass (Captiva Island)
Blind Pass #19 1858-1989 65 +0.90 +0.88
to Entrance to San Carlos Bay (Sanibel Island) I
Entrance to San Carlos Bay #20 1858-1989 36 +0.22 -0.38
to Big Carlos Pass (Estero Island)
Big Carlos Pass #21 1885-1989 12 -0.68 -3.87
to New Pass (Lovers Key)
New Pass #22 1885-1989 3 -2.33 -2.64
to Big Hickory Pass (Big Hickory Island)
Big Hickory Pass #23 1885-1989 30 +0.04 -0.16
to Wiggins Pass (Bonita Beach)
Wiggins Pass #24 1885-1988 25 -0.07 +0.12
to Clam Pass (Vanderbilt Beach )
Clam Pass #25 1885-1988 16 -0.05 +0.14
to Moorings (Doctors) Pass (Naples Island)
Moorings (Doctors) Pass #26 1885-1988 32 -0.05 +0.09
to Gordon Pass (Naples Island)
Gordon Pass #27 1885-1988 38 +0.37 +0.47
to Big Marco Pass (Keewaydin Island)
Big Marco Pass #28 1885-1988 21 +1.53 +1.73
to Caxambas Pass (Marco Island)
Note:
Shoreline change rates shown above are the averages of the shoreline change rates at individual monument locations for each island. These change rates are determined by the best least squares fit procedure.




Table 4-8 Summary of the Kolmogorov-Smirnov test for goodness of model fitting to
normalized standard deviations for Florida's east coast sandy beach counties

The Kolmogorov-Smirnov Test of Goodness of Fit
Reject (X) or Accept (V) the Proposed Models
Number Significance Level
County Years of Rayleigh CDF Weibull CDF
Profiles Significance Level Significance Level
0.10 0.05 0.01 IFR-Fl n IFw-Fslax
0.10 0.05 0.01 0.10 0.05 0.01
Nassau 1871-1991 44 0.1839 0.2050 0.2457 0.1217 V 6/ V 0.0680 V V V
Duval 1858-1990 48 0.1761 0.1963 0.2353 0.0774 V V V 0.0536 V I
North St. Johns 1858-1992 170 0.0936 0.1043 0.1250 0.0631 V V V 0.0507 V V V
East I
Florida Flagler 1872-1987 100 0.1220 0.1360 0.1630 0.0859 V V V 0.0682 V V V
Coast
Volusia 1873-1989 241 0.0786 0.0876 0.1050 0.0518 V V V 0.0257 V V V
Brevard 1876-1993 198 0.0867 0.0967 0.1158 0.1047 X X V 0.0351 V V V
IndianRiver 1880-1993 119 0.1118 0.1247 0.1494 0.0691 V V V 0.0477 V V V
St. Lucie 1860-1987 84 0.1331 0.1484 0.1778 0.0544 6/ V V 0.0299 V V V
South Martin 1883-1986 82 0.1347 0.1502 0.1800 0.0951 VV V 0.0673 V V V
East I I
Florida PalmBeach 1883-1991 197 0.0869 0.0969 0.1161 0.0695 S/ V V 0.0350 V IV V
Coast
Broward 1883-1986 94 0.1258 0.1403 0.1681 0.0365 V V V, 0.0403 V V V
Dade 1851-1973 81 0.1360 0.1509 0.1808 0.0984 V V V 0.0662 V V 6




Table 4-9 Summary of the Kolmogorov-Smirnov test of goodness of model fitting to
normalized standard deviations for Florida's west coast sandy beach counties

The Kolmogorov-Smirnov Test of Goodness of Fit
Number Reject (X) or Accept (V) the Proposed Models
County Years of Significance Level
Profiles Rayleigh CDF Weibull CDF
Significance Level Significance Level
0.10 0.05 0.01 IFR-FSIn.( IFwFslna
0.10 0.05 0.10 0.10 0.05 0.10
Escambia 1856-1978 181 0.0907 0.1011 0.1212 0.0908 X V V 0.0455 6 V
Santa Rosa
Okaloosa 1871-1990 39 0.1954 0.2178 0.2610 0.0588 V V V 0.0536 V V V
North
West Walton 1872-1977 127 0.1083 0.1207 0.1446 0.0369 V V V 0.0416 V V V
Florida
Coast Bay 1855-1977 39 0.1954 0.2178 0.2610 0.0719 V V V 0.0699 V V V
Gulf 1868-1984 87 0.1308 0.1458 0.1748 0.0636 V V V 0.0522 V / V
Franklin 1856-1979 149 0.0999 0.1114 0.1335 0.0296 V V V 0.0364 V V V
Pinellas 1873-1987 31 0.2191 0.2443 0.2928 0.0588 V V V 0.0443 t/ 6/ V
Manatee 1874-1986 21 0.2662 0.2968 0.3557 0.1412 V V V 0.1278 V V V
South Sarasota 1883-1994 78 0.1381 0.1540 0.1846 0.0466 V V V 0.0379 V V V
West
Florida Charlotte 1883-1988 12 0.3522 0.3926 0.4705 0.1332 6/ V / 0.1028 V V V
Coast
Lee 1858-1989 53 0.1676 0.1868 0.2239 0.0814 V V V 0.0530 V / V
Collier 1885-1988 80 0.1364 0.1521 0.1822 0.0637 V V V 0.0605 V V V




Table 4-10 Summary of the parameters for the fitting of models to normalized standard deviations
for Florida's east coast sandy beach counties
BEST-FIT WEIBULL CUMULATIVE DISTRIBUTION: F(x) = 1 eA(xx0)n
BEST-FIT RAYLEIGH CUMULATIVE DISTRIBUTION: F (x) = 1- e-A(x-xo)2
Number Rayleigh CDF Weibull CDF
County Years of X,
Profiles A x0 Error n A x0 Error
Nassau 1871-1991 44 0.68 7.85 0.67 3.00x103 5.82 7.28 0.31 9.76x104
Duval 1858-1990 48 0.37 2.23 0.37 1.60x103 3.81 0.86 0.00 6.04x104
North
East St. Johns 1858-1992 170 0.24 1.58 0.24 4.75x104 2.41 1.34 0.15 3.72x104
Florida Flagler 1872-1987 100 0.30 1.75 0.30 1.40x103 3.19 0.82 0.00 9.28x104
Coast I
Volusia 1873-1989 241 0.28 1.79 0.28 5.98x104 2.27 1.99 0.28 1.31x104
Brevard 1876-1993 198 0.44 2.61 0.44 3.20x103 3.37 3.07 0.33 1.58x104
Indian River 1880-1993 119 0.34 2.27 0.34 6.85x104 2.23 2.57 0.34 3.66x104
St. Lucie 1860-1987 84 0.40 2.40 0.40 5.15x104 3.04 1.60 0.19 1.91x104
South
East Martin 1883-1986 82 0.31 1.76 0.31 2.50x103 3.77 0.79 0.00 7.36x104
Florida Palm Beach 1883-1991 197 0.20 1.32 0.19 8.82x104 2.90 0.85 0.00 2.20x104
Coast
Broward 1883-1986 94 0.28 1.87 0.27 2.99x104 2.04 1.90 0.27 2.91x104
Dade 1851-1973 81 0.15 1.25 0.15 2.40x103 3.09 0.94 0.01 6.69x10




Table 4-11 Summary of the parameters for the fitting of models to normalized standard deviations
for Florida's west coast sandy beach counties
BEST-FIT WEIBULL CUMULATIVE DISTRIBUTION: F(x) 1 e-A(x-xo)n
BEST-FIT RAYLEIGH CUMULATIVE DISTRIBUTION: F (x) = 1- e-A(x-x0)2
Number Rayleigh CDF Weibull CDF
County Years of x.
Profiles A x0 Error n A xo Error
Escambia 1856-1978 181 0.15 1.21 0.14 2.80x10-3 3.15 1.05 0.04 2.91x104
Santa Rosa
Okaloosa 1871-1990 39 0.38 2.13 0.35 1.10x103 2.43 1.67 0.23 9.96x104
North Walton 1872-1977 127 0.00 0.96 0.00 2.70x10-4 1.96 0.96 0.00 2.55x104
West
Florida Bay 1855-1977 39 0.31 1.83 0.23 8.08x10- 1.98 1.82 0.23 8.06x104
Coast
Gulf 1868-1984 87 0.23 1.14 0.05 5.88x10-4 1.59 1.46 0.19 4.14x104
Franklin 1856-1979 149 0.12 1.00 0.00 1.87x10 1.93 0.99 0.00 1.44x104
Pinellas 1873-1987 31 0.28 1.82 0.28 9.19x104 2.22 2.00 0.28 5.90x104
Manatee 1874-1986 21 0.34 1.66 0.29 6.10x103 3.27 0.79 0.00 4.40x103
South
West Sarasota 1883-1994 78 0.50 3.02 0.46 4.25x104 2.97 2.02 0.25 2.02x104
Florida Charlotte 1883-1988 12 0.53 2.65 0.42 4.40x103 3.99 0.85 0.00 2.70x103
Coast
Lee 1858-1989 53 0.68 4.56 0.53 9.19x104 1.44 4.08 0.62 6.17x104
Collier 1885-1988 80 0.31 2.14 0.31 6.88x104 2.05 2.19 0.31 6.70x104




Table 4-12 Summary of the parameters for the fitting of models to unscaled standard deviations
for Florida's east coast sandy beach counties
BEST-FIT WEIBULL CUMULATIVE DISTRIBUTION: F(x) = 1 e-A(x-x)n
BEST-FIT RAYLEIGH CUMULATIVE DISTRIBUTION: F(x) = 1- e-A(x-x0)2
Number Rayleigh C.D.F Weibull C.D.F
County Years of x, xm
Profiles A x0 Error n A xo Error
Nassau 1871-1991 44 18.86 12.75 0.0221 12.64 3.00x103 5.82 2.71x107 5.85 9.76x1lO
Duval 1858-1990 48 20.24 7.57 0.0054 7.49 1.60x103 3.81 9.14x106 0.00 6.04x104
North
East St. Johns 1858-1992 170 13.35 3.27 0.0089 3.20 4.75x104 2.41 2.60x103 2.00 3.72x104
Florida
FlCoast Flagler 1872-1987 100 10.03 3.04 0.0174 3.01 1.40x103 3.19 5.22x104 0.00 9.28x10
Coast
Volusia 1873-1989 241 9.30 2.65 0.0207 2.60 5.98x104 2.27 1.26x102 2.60 1.31x104
Brevard 1876-1993 198 11.68 5.19 0.0191 5.14 3.20x103 3.37 7.56x104 3.86 1.58x104
Indian River 1880-1993 119 9.31 3.18 0.0262 3.17 6.85x104 2.23 1.76x102 3.17 3.66x104
St. Lucie 1860-1987 84 9.94 4.00 0.0243 3.98 5.15x104 3.04 1.50x103 1.89 1.91x104
South
East Martin 1883-1986 82 9.34 2.93 0.0201 2.90 2.50x103 3.77 1.74x104 0.00 7.36x104
Florida Palm Beach 1883-1991 197 12.05 2.38 0.0091 2.29 8.82x104 2.90 6.18x104 0.00 2.20x104
Coast
Broward 1883-1986 94 10.34 2.89 0.0175 2.79 2.99x104 2.04 1.63x10-2 2.79 2.91x104
Dade 1851-1973 81 14.06 2.11 0.0063 2.11 2.40x103 3.09 2.67x104 0.14 6.69x104




Table 4-13 Summary of the parameters for the fitting of models to unscaled standard deviations
for Florida's west coast sandy beach counties
BEST-FIT WEIBULL CUMULATIVE DISTRIBUTION: F (x) = 1 e-A(-xo)n
BEST-FIT RAYLEIGH CUMULATIVE DISTRIBUTION: F (x) = 1 e-A(x-x0o)2
Number Rayleigh C.D.F Weibull C.D.F
County Years of X, Xm
Profiles A xo Error n A x0 Error
Escambia 1856-1978 181 17.82 2.64 0.0038 2.50 2.80x103 3.15 1.21x104 0.71 2.91x10
Santa Rosa
Okaloosa 1871-1990 39 9.84 3.70 0.0220 3.44 1.10x103 2.43 6.40x103 2.26 9.96x104
North Walton 1872-1977 127 13.66 0.04 0.0051 0.00 2.70x104 1.96 5.80x103 0.00 2.55x10-4
West
Florida Bay 1855-1977 39 7.11 2.24 0.0362 1.63 8.08x104 1.98 3.72x102 1.63 8.06x104
Coast
Gulf 1868-1984 87 9.42 2.17 0.0129 0.47 5.88x104 1.59 4.13x102 1.79 4.14x10-4
Franklin 1856-1979 149 12.23 1.51 0.0067 0.00 1.87x104 1.93 8.00x103 0.00 1.44x104
Pinellas 1873-1987 31 5.26 1.50 0.0659 1.47 9.19x104 2.22 4.98x102 1.47 5.90x104
Manatee 1874-1986 21 11.47 3.95 0.0127 3.33 6.10x103 3.27 2.71x104 0.00 4.40x103
South
West Sarasota 1883-1994 78 10.26 5.09 0.0288 4.72 4.25x104 2.98 2.00x103 2.56 2.02x104
Florida Charlotte 1883-1988 12 12.03 6.39 0.0183 5.05 4.40x103 3.99 4.14x105 0.00 2.70x103
Coast
Lee 1858-1989 53 14.72 9.95 0.0210 7.80 9.19x104 1.44 8.50x102 9.13 6.17x104
Collier 1885-1988 80 11.66 3.67 0.0157 3.61 6.88x104 2.05 1.42x102 3.61 6.70x10-4




....... ......... s s a u .' ........I... .... .
D uval..............
St.Johns ....... ......a.er..
Volusia.
Brevard'
.. ..................... a H v ............... ........
Indian River
:St. Lucie i
.. . .......... ... .~ ...... .......... ..............
Martin
Palm Beach .
. ...................... .............. 4
Broward
Dade
I

i,
-30 -25 -20 -15 -10 -5 0 5 10 15 20
Shoreline Change Rate (meters/year)
Figure 4-1 Long-term shoreline change rates along the east coast of Florida. These
change rates are determined by the best least squares fit procedure
for the complete record of data availability.

1 .

I

. . . . . . . .
.. . . . . . . . . . .
. . . . . . . . . . .
. . . .
. . . . ..-. . .
L . .. .. . .. ...-. . .
L ........ ...I...... .........
. . . . . . . . . . .

I




------------------------.-..-.-------------------------.. .. .. .. . a. ..... .. ; 5
- - -- - -- -- ---- -- - - -- -- - -- - - - -

2

Year

St.JohnsR-Il 72
-- - - - - - - - - -- - - - . -- - - . . .i
j --
-- - - - - - -- - - - - - - - - - - -
. . . . . . . -- - - - - - -- - - - - - - -
.... '- ----...... ..... -.-... .... .......

Year

- - - - 7 - - - . . . . T - - - - - - - - - -. . .
VolusleR-35
. .. . . ..- --!- - - - - - "- . .
- - - --- - - - - ---Z - .2~ ~ . - - - --- - - - -- . .
- - --- - - --.- --.-. i - - --.. . . . .

1220 1.00 1.20 1-40 1.0
Year

*110
A10l.
z
so9

Flag Ir.R-49
. -.. . - - --- - - -
.. . . . ... : . . 7 - i . -. . . .- - --

140 T lrlR 2 ;_i....]......
!0 I~adR-2fl
1 s o --- -7 - - - -: - - - --
- .. ---- -- : -- -- - - - - - --- -- ---
120 - -.-.--- -- .
-. . . -- - - - - --.. - - - . - - - - -
Ko - -- - - -I- - -- -
110 -

Is.* 2000 -..o I .. .. 0
10 0 120 10 100 1020 1040
Yeer

2.2-

Indiani River,ER43
' 7.
--- -- ---- -- -- 7 . .7 . . --- -----r -- 7
. ....---- .. .. ..----- ---- ) ; -- ---------_ - -- - ----- -- - -- - -
----- --- --- - - - -- .... ... -- .. .. .. .. --- 8 o

1220 100 1 20 1040 1 0 120

1s0
15 140 120
so
:'80
1o

- - - - - ---- -- 7- - - - --- - - - q.. . . . . . .
........ --- --- = --- -------- -- ...... 7 ... .
- - - --. - - - - - - -.. . . -.. . .
-- ---.... ... --- ---0 1001020 1040 10 1020 200
Year

-044
.2
Caso

22 -- 40 -- -
B ro w e d -R-1*4 --------------2-z----i4
V = so
a
a.~---- -----r& L fle Lb. c --------2
os ----- ----- -- ---- ---so0 - -- 7 - - - - -T - - - - -7 - -

1200 10o 1020 VI 1 1o 0202 00oo

p al ,m B eclo. R-4
20 1000o 1020 1040 1020o 1000 2000 Year
DadeTR-12 ] = _---- ----.0.1.........o 00

-V0 100

Figure 4-2 Examples of shoreline positions versus time at individual monument
locations for Florida's east coast sandy beach counties.

so

120
lo so

.. . . + . ... . - - - - 2 -- - . - - - -.. . . - - . . . - - - . ..- -. .
20 -- - -t- - -
-120 1-- 0 1- 00 1020 1040 10 0 1000 20
1880 ls 0Year

1.0 1220 1000 1020 1040 1000 1020 2000
Yeer

- - - - - - - - - - - 7 - - 7 . . . . . . . . 1.. .
Gt.Lucle.R-7
------ ----- -- ---- -------- - - - - - - - - -- - - - - - -. -

1.20 -0

4Q

o0

I...

2000

Is..

2000

I... 1.s0 2000

2000

I... 2000ZOU




14.
Nassau County (68) 12 10
0
z
4
2
-30 -20 -10 0 10 20 3
Shoreline Change Rate
12,

100)-

0 -20 -10 0 10
Shoreline Change Rate

20 3

0
Shoreline Change Rate

Duval County (78) 25
2 0 .... ...... ............ .......... ........... .... .......... . . . . . . . . .
10
-30 -20 -10 0 10 20 3
Shoreline Change Rate
n

0'
-30 -20 -10 0 10 20 3C
Shoreline Change Rate
1ar.

160 .. .... ........

-30 -20 -10

0
Shoreline Change Rate

20 30

Figure 4-3 Histograms of long-term shoreline change rates in meters per year
for the east coast of Florida. (Values in parenthesis indicate total
number of locations).

Flagler County (100)

St. Johns County (209)

nl I nn-. imI.e n -- --

Brevard County (386)
..........
. .1 .... ............. I .. .. .. .. .. ... .. ..
.. H . .. . .... .. . . .
.L ........... .. .

g




Indian River County (119) 50
a 40
0
-530
z 20 ...... ... ......
10- ........................... ......... ...................... ..........
10
-30 -20 -10 0 10 20 30
Shoreline Change Rate
o
Martin County (127) 40
35
' 30 ....... . .. ..
-25 E20
z
15
1 0 . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .
5- .....................................................
10
-30 -20 -10 0 10 20 3(
Shoreline Change Rate
600
Broward County (128)
50
40
-30
z
20
10

-30 -20

-10 0
Shoreline Change Rate

10 20 30

An

-30 -20 -10 0 10 20 30
Shoreline Change Rate 140 Palm Beach County (227) 120 100 80 60
40 20
-30 -20 -10 0 10 20 3
Shoreline Change Rate

S 0
Shoreline Change Rate

Figure 4-3 Continued

St. Lucie County (115)

0




Year

-150'
1850 1900

1950

2000

Year

Average shoreline change over time for Florida's east coast sandy beach counties based on method 2.

Figure 4-4




-12 -10 -8 -6 -4 -2 0 2
Longshore Sediment Transport Difference (cubic meters x 1 0A-5 / year)

Figure 4-5 Total net longshore sediment transport difference along Florida's
east coast. Based on consideration of zero net long-term crossshore sediment transport.




I I

-200 -150 -100 -50 0 50 100 150 200 250 300
Local Cross Shore Sediment Transport (m.A3/m/yr)

Figure 4-6 Local cross-shore sediment transport along Florida's east coast.
based on considering a uniform gradient of net longshore
sediment transport. Gradient is based on previous estimates of net transport at the northern and southern limits of region
considered.

A

................ I
.: . . . . .. . .
. . . . . . . . . .
. . . .. . . .. . . .
. . . . . . .
. . .. .. .

........ ..... 'N assau : ........ .....
.. .. ... .. ..D u v a .. . . .. . .. . .
St.Johns
r . . .... . . . .. :. . . . . ,.. . . . .... . . . . . . . .
..........F.......... F la e r ...... .......
Volusia'
Brevard
................... Indian R iver ........................
......... :.......... .. .i........... . .......... :.........
... .. ... . ri... .......... ......... .........
'Palm Beach
... ................... ....
Broward
-Dade
I I




-30 -25 -20 -15 -10 -5 0 5 10 15 20
Shoreline Change Rate (metersNear)

Figure 4-7 Long-term shoreline change rates along Florida's northwest coast. These
change rates are determined by the best least squares fit procedure for
the complete record of data availability.




I -

I I I

Pinellas, Manatee Sarasota Charlotte
....'T. ............ ........... ........... ........... ................ .......
Lee
Collier

-10 -5 0 5 10 15 20 25 30 35 40
Shoreline Change Rate (meters/year)

Figure 4-8 Long-term shoreline change rates along Florida's southwest coast. These
change rates are determined by the best least squares fit procedure for
the complete record of data availability.

62.5
T,
x
(/)
2
E
C
1.5
0
J
L
0 C
0) 1

0.5

.. . -.. . .




2 : : : : -- - - - - - - - - - - - - - - - - - - - - - S
Ea a S. Sata R &a, ft1 138
e80
oSo
s 20
- - - - - - . . . . - - - - -

0) 1 .5
a'

Wael n. R--3
- .-- ..... .
---- - -- F
.... -- 4: ... ------ --- ----- .- ---- /
-------. -------.-----.

-g
a
a

1880 1900 1020 1940 1080 1so
Year

Okateo osa. R-24
- - - - - - - - - --. - --. . . -- - - - --. .
- - - - - - - - - - - - - -
--- --- i -- ------- -- ---- --. ..-- ... ... .. .... .. 7 -- -- - 1
lo 1s.8 1000 1820 1040 10.0 1080 2000
Yer

SO .; .. -- . ---':.----.-- -- - --- -- -- ---- ... -----4o
- - - - - - - - - 7O O - - - 7~ - - - -- - - - - - -- - - - -

1. -o -9~200 1eo
170 IS. 4)lS0 .5
140
12,0 1:i0

A
110
I1o.
* 104
(#0100-

PIneillas.l ftR-8 .O
- . - - - . . - - - . . 7.. - - - - - - . .
. . . - - - - - I.. a_;- . . - - - - - -
o 1oo 101o 100 1.40 100 100 .. 000
Year

0 -- - -- -- - --- 7 - - - --- 7 - - 1 IS O
Sarnata. A- 181
-0- 1 _a 05r e Li yo 0
148. 100. 2 -10 ... 1 8I .. .0 2000 O0
Year

Year

7.. . . . . 7. . . . .
- - - - - - - --.. .

go 1880 180 100 1920 1040 1980 1i0
Year

Manatee R-510
1880 180 1000 1000 10i401000o 180 2000
Year

Trend Line* -1019-I~r ,0 180 100 00 04 08718

so t80 ISO. t1o 14 -S e I o ISOYear
. .- --- --- --- --- --- -- -

2000 10 1000 1 2014010 1080
Year

Figure 4-9 Examples of shoreline positions versus time at individual monument
locations for Florida's west coast sandy beach counties.

ISO* 1- 1.100 1.20 1.4. 1... I..
,Year

Year

10

I...

I1...

a000

2000

----------------------------- ------- 7 ------------------ 1 :
----------- R I a --- ---------- ----------------------------------- ----------------- 7: -----------------rr d Ine: -0.01 rvj: yr
------- ---------- ------------ ------------- L ----------------- ---- ------------------------------ ----------------- -- ------------

ZOO0

I1...

I1...

IS,

------ --------------------- ------------- -------




Escambla + Santa Rosa County (214) s o ....... . .. . .. . . . . . . . . . . . . . . . . . .
70
60 .....
40
30
2 0 .. ... .
2o0 ................. ...............................
-30 -20 -10 0 10 20 30
Shoreline Change Rate
Walton County (127)

-30 -20 -10 0 10 20 30
Shoreline Change Rate 40
Gulf County (162) 35
30
25
20
5
1 0 . ... ... .. . ... .. .... ... ... .. ... ...... .. .. .. .... .
15 ................................................
n[ n, fi lmn ,

-30 -20 -10 0 10
Shoreline Change Rate

-30 -20 -10 0 10 20 30
Shoreline Change Rate
l00
Bay County (144)
9 0 .............. ......... .. .................... .. ........ ....................................
80
70
60 .........
40
0 . . . . . .. . . . .. . . .. . .. . . . . . . .
1 0 . . . . . . . . . . . . . . . . . . . . . . . .

-10 0 10
Shoreline Change Rate

-10 0 10
Shoreline Change Rate

Figure 4-10 Histograms of long-term shoreline change rates in meters per year
for the northwest coast of Florida. (Values in parenthesis indicate
total number of locations).

35o
0Okalo os a C ou nty 50)

-30 -20

20 30

20 30




50 Pinellas County (187) 45-.
403530 252015
5
-30 -20 -10 0 10 20 30
Shoretline Change Rate 4a ... . . . . . . . . . . . . . . . . . . . . . . . .

-30 -20

-10 0 11
Shoreline Change Rate

20 30

10 0 10
Shoreline Change Rate

Figure 4-11

-10 0 10
Shoreline Change Rate

10 0 10
Shoreline Change Rate

-30 -20 -10 0 10
Shoreline Change Rate

Histograms of long-term shoreline change rates in meters per year for the southwest coast of Florida. (Values in parenthesis indicate total number of locations).

Manatee County (67) 0
5.
0
2 . . . . . . . . ... . . . . . . . . . . . . . . .
n . . . . . . . . . . . . . . . . . . . . . . . .

Sarasota County (183)
.......... ........ .. ..........

20- .....

80
Collier County (148) 70
80
40
30
2 0 1 . . . . I . . . . . . . . ... . . . . . . . ... . . . . . . . . . . . .
nn
10! n i [

-30 -20

20 30

20 30




-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2
Longshore Sediment Transport Difference (cubic meters x 10A-5 / year)

Figure 4-12 Total net longshore sediment transport difference along Florida's
northwest coast. Based on consideration of zero net long-term
cross-shore sediment transport.




-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2
Longshore Sediment Transport Difference (cubic meters x 1 QA-5 / year)

Figure 4-13 Total net longshore sediment transport difference along Florida's
southwest coast. Based on consideration of zero net long-term
cross-shore sediment transport.




4
Escambia
Santa Rosa

Okaloosa Walton

Bay Gulf

Franklin

l............................. ............
.I
I

-150 -100 -50 0 50
Local Cross-shore Sediment Transport (mA2/yr)

100 150

Figure 4-14

Local Cross-shore sediment transport along Florida's northwest coast. Based on considering a gradient of 0.4m3/mlyr net longshore sediment transport over the limits of the region considered.

tO
0
x
2.5
E
u 2
C U)
15
0 1.5
0
0
J
ol

II I

P

..........

. . . . . . . . . . .




Pinellas

Manatee

Sarasot Charlott

a
!...........
te
. . . . . . . .

tO
o2.5
x 4,
0 2
E
C
0 40 1.5
0
C
0
-J

UI
200 -150 -100 -50 0 50 100 1
Local Cross-shore Sediment Transport (mA2/yr)

Figure 4-15 Local cross-shore sediment transport along Florida's southwest
coast. Based on considering a zero gradient of net longshore
sediment transport over the limits of the region considered.

Lee Collier

05 ....

I L

r
i

K

. . . . . . . . . . .
. . . .
. . . .
....... ..............

.............
..........................

. . . . .




72
Nassau County

E 10
0
EI
(D
L
o -5

09 19

29 39 49 59 69
Monument Number

Figure 4-16 Shoreline change rates and unscaled standard deviations
along the coastline of Nassau County, 1857-1991. The bold segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.

19 29 39 49 59 69
Monument Number

150 100

I I I I I




Duval County

E
b) ~ South lo
S outh
10 S0)
'-0
' NsuFort George Inlet
SSt. Johns River Entrance 0-30 U 02 12 22 32 42 52 62 72
Monument Number 400
E
o 300 ,
4) 200
L,.
"o 100
CO 01

02 12 22 32 42 52
Monument Number

Figure 4-17

62 72

Shoreline change rates and unscaled standard deviations along the coastline of Duval County, 1853-1990. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be acceptable for analysis of standard deviations.




St. Johns County

E
15
o 10
1
S-5
CO 0

50 100 150 200
Monument Number

Figure 4-18

Shoreline change rates and unscaled standard deviations along the coastline of St. Johns County, 1858-1992. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be acceptable for analysis of standard deviations.

50 100 150 200
Monument Number

""600
0
400
200
CO 0




Flagler County

E 0.4 m 0.2 0 0
-0.2
5 -0.4
'20
C
-o
015
Cu
'10
I-ol
CIn

20 40 60 80
Monument Number

100

20 40 60 80
Monument Number

Figure 4-19 Shoreline change rates and unscaled standard deviations
along the coastline of Flagler County, 1872-1987. The bold
segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.

100




Volusia County

E
6 tO 4
-2
0
5 -2
C,-

50 100 150 200 250
Monument Number

Figure 4-20 Shoreline change rates and unscaled standard deviations
along the coastline of Volusia County, 1873-1989. The bold
segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.

- South

Ponce De Leon Inlets ,

50 100 150 200 250
Monument Number

-200
C
.0 150 (a
o 100
I
-50
CO n

I I

F -




77
Brevard County

E 6 S4
=2
0 o -2 U 0

50 100 150 200 250 300 350
Monument Number

0 50 100 150 200 250 300 350
Monument Number

Figure 4-21 Shoreline change rates and unsealed standard deviations
along the coastline of Brevard County, 1874-1993. The bold
segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.

-" 100
E
C
0
S50
I
cc
C
CU W1 n




Indian River County

I-.
E 2
1
o 0
, 03
" 0
E
a,
10
0
(U

20 40 60 80 100
Monument Number

Figure 4-22 Shoreline change rates and unsealed standard deviations
along the coastline of Indian River County, 1880-1993. The bold
segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.

20 40 60 80 100
Monument Number




St. Lucie County

E 3
(D
0
o g40
4-,
0 0
f2O
E
0r 40M
"3 302010
COU

20 40 60 80 100
Monument Number

Figure 4-23

Shoreline change rates and unsealed standard deviations along the coastline of St. Lucie County, 1860-1989. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be acceptable for analysis of standard deviations.

20 40 60 80 100
Monument Number




80
Martin County

I 5
d)
0 (D
0
0-5
o)
0-10 U)
150
E
0
25 100
- 50
U-' ci, n

20 40 60 80 100 120
Monument Number

Figure 4-24 Shoreline change rates and unscaled standard deviations
along the coastline of Martin County, 1883-1986. The bold segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.

20 40 60 80 100 120
Monument Number




81
Palm Beach County

E
d)
2
tU

0-10 CO 0

50 100 150 200
Monument Number

040
3 30
a
"ao200
L
0 50 100 150 200
Monument Number

Figure 4-25 Shoreline change rates and unscaled standard deviations
along the coastline of Palm Beach County, 1883-1991. The bold
segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.




Broward County

E
0
4)-2
o -3 CO 0
-150
E
0

25 100'I
0
150
o
'- 50 (
c,) n-

20 40 60 80 100 120
Monument Number

Figure 4-26

Shoreline change rates and unscaled standard deviations along the coastline of Broward County, 1883-1986. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be acceptable for analysis of standard deviations.

20 40 60 80 100 120
Monument Number




83
Dade County

.
E
2
0
0-2
d)
o-4
'

-'60
0
20
C
0 20 40 60 80 100
Monument Number

Figure 4-27 Shoreline change rates and unscaled standard deviations
along the coastline of Dade County, including period
of extensive nourishment (1851-1986).

20 40 60 80 100
Monument Number

- South
(1) Bakers Haulover Cut
(2) Government Cut
- (3) Norris Cut
(4) Bear Cut (1)

)

r

----------




84
Dade County

E
- 2
4)
-,
(U
G" 0
0
a
0
~4
0 20 C 0

0 20 40 60 80 100
Monument Number

Figure 4-28

Shoreline change rates and unscaled standard deviations along the coastline of Dade County, including period of extensive nourishment (1851-1973). The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be acceptable for analysis of standard deviations.

20 40 60 80 100
Monument Number




Escambia+Santa Rosa County

L.
E
0 5_0-2 W 0

50 100 150 200
Monument Number

-" 100 ,-,
E
C
..
0 5
0,
"~0
0 50 100 150 200
Monument Number

Figure 4-29

Shoreline change rates and unscaled standard deviations along the coastline of Escambia and Santa Rosa Counties, 1856-1978. The bold segment of the standard deviation curve in the lower panel represents the shoreline portions considered to be acceptable for analysis of standard deviations.




Okaloosa County

E 3 M 24')
4
0
0
0-1 CO 0

10 20 30 40
Monument Number

Figure 4-30 Shoreline change rates and unscaled standard deviations
along the coastline of Okaloosa County, 1871-1990. The bold
segment of the standard deviation curve in the lower panel
represents the shoreline portions considered to be acceptable
for analysis of standard deviations.

10 20 30 40
Monument Number

" 150
E
0
-W
100
50
CO 50
(
ci n