Seasonal variation in sandy beach shoreline position and beach width

State of Florida
Department of Environmental Protection
David B. Struhs, Secretary

Division of Administrative and Technical Services

lorida Geological Survey
Walter Schmidt, State Geologist and Chief

lorida Geological Survey
Speiial Publication No. 43

Seasonal Variation in Sandy Beach Shoreie Position and Beach Width
by

James H. Basillie

and

Open-Ocean Water Level Datum Planes: Use and Misuse
in Coastal Applications

by

James H. Balsillie

Published for the
Florida Geological Survey
Talahassee, Florida
1999

LETTER OF TRANSMITTAL

Florida Geological Survey
Tallahassee

Governor Jeb Bush
Florida Department of Environmental Protection
Tallahassee, Florida 32304-7700

Dear Govemor Bush:

The Florida Geological Survey, Division of Administrative and Technical Services,
Department of Environmental Protection is publishing two papers: "Seasonal variation in
sandy beach shoreline position and beach width" and "Open-ocean water level datum planes:
Use and misuse in coastal applications".

The first paper identifies a methodology for predicting seasonal shifts in Florida's
shorelines. A number of practical uses emerge from the research, two of which are the
analytical assessment of long-term shoreline erosion data, and determination of the seaward
boundary of public versus private ownership.

The second paper is a companion paper to "Open-ocean water datum planes for
monumented coasts of Florida" published by the Florida Geological Survey as a separate
work. It identifies erroneous applications made when considering mean sea level (MSL),
mean high water (MHW), mean low water (MLW), etc., tidal datum planes, illustrating why
they are erroneous using practical examples, and details how proper applications should be
determined.

Respectfully yours,

Walter Schmidt, Ph.D., P.G.
State Geologist and Chief
Florida Geological Survey

CONTENTS

Page
SEASONAL VARIATION IN SANDY BEACH
SHORELINE POSITION AND BEACH WIDTH

ABSTRACT .......................................................... 1
INTRODUCTIO N ....................................................... 1
SEASONAL VARIABILITY ....................................... ........ 2
DATA AND RESULTS .................................................. 3
Data .......................................................... 3
Results ........................................................ 7
DISCUSSIO N ......................................................... 9
The Single Extreme Event and the Combined Storm Season ............... 9
Beach Sedim ents ............................................... 11
Astronom ical Tides .............................................. 14
APPLICATION OF RESULTS ............................................ 15
General Knowledge ............................................. 16
Seaward Boundary of Public versus Private Ownership .................. 16
Long-Term Shoreline Changes ..................................... 17
Project Design and Performance Assessment ......................... 19
CONCLUDING REMARKS ............................................. 20
ACKNOW LEDGEMENTS ...... .................. ...................... 20
REFERENCES ......................................................20

LIST OF FIGURES

Figure 1. Relationship between seasonal shoreline variability, V., and mean range
of tide, h. .................................................. 4
Figure 2. Monthly time series for Torrey Pines Beach, California, for shoreline
variability, V; breaker height, Hb,, and wave period, T. .................... 5
Figure 3. Monthly time series for Stinson Beach, California, for shoreline variability,
V; breaker height, Hb, and wave period, T. ............................ 5
Figure 4. Monthly time series for Jupiter Beach, Florida, for shoreline variability, V;
breaker height, Hb, and wave period, T. .............................. 6
Figure 5. Monthly time series for Gleneden Beach, Oregon, for shoreline variability,
V; breaker height, Hb, and wave period, T. ............................ 6
Figure 6. Illustration of mathematical fit for equation (1). ...................... 9
Figure 7. Illustration of mathematical fit for equation (2). ...................... 9
Figure 8. Example of the quick response and recovery of the beach to storm wave
activity, Pensacola Beach, Florida, December 1974. ................... 10
Figure 9. Monthly average occurrences of extreme event wave events for the Outer
Banks of North Carolina ............................. ............ 11

Figure 10. Typical examples of time series relation of monthly data for breaker
height, wave period, and foreshore slope grain size for California and
northwestern Florida panhandle. ...............................
Figure 11. Monthly variation in sea level for the contiguous United States. ......
Figure 12. Example of long-term shoreline change rate temporal analysis using
seasonal shoreline shift data ................................

LIST OF TABLES

Table 1. Force, response, and property elements for seasonal shoreline shift analysis. .. 4
Table 2. Assessment of the wave steepness ratio for a selection of expressions
related to VS. ................... ................. .......... 8
Table 3. Mean annual beach grain size (foreshore slope samples) from monthly
data, and range in size. ........................................ 12
Table 4. Two cases of sedimentologic response of moment measures to wave
energy levels. ................................................ 12
Table 5. Seasonal range in monthly average water levels. ................... .. 15

APPENDIX

APPENDIX: PROPAGATION OF ERRORS IN COMPUTING .........

OPEN-OCEAN WATER LEVEL DATUM PLANES:
USE AND MISUSE IN COASTAL APPLICATIONS

A BSTRACT ...................................
INTRODUCTION ................................
INLETS/OUTLETS AND THE ASTRONOMICAL TIDE .......
WATER LEVEL DATUM PLANES ....................
SYNERGISTIC TIDAL DATUM PLANE APPLICATIONS .....
EXTREME EVENT IMPACT ...................
LONGER-TERM BEACH RESPONSES ............
Seasonal Beach Changes ...............
Long-Term Beach Changes ..............
THE SURF BASE ..........................
SEA LEVEL RISE ..........................
MONERGISTIC TIDAL DATUM PLANE APPLICATIONS . . .
DESIGN SOFFIT ELEVATION CALCULATIONS ......
EROSION DEPTH/SCOUR CALCULATIONS ........
SEASONAL HIGH WATER CALCULATIONS .......
BEACH-COAST NICKPOINT ELEVATION ..........
BOUNDARY OF PUBLIC VERSUS PRIVATE PROPERTY
INLETS AND ASSOCIATED ASTRONOMICAL TIDES ......
CONCLUSIONS ................................
ACKNOWLEDGEMENTS ..........................
REFERENCES ..................................

......... 28

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

. . . . .
. . . . .

.. . . . .o
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.........

.........
.........,

. . . . . .

OWNERSHIP

. . . .= ,

LIST OF FIGURES

Figure 1. Relationship between open coast tidal datums and National Geodetic
Vertical Datum for the Florida East Coast ............................. 31
Figure 2. Relationship between open coast tidal datums and National Geodetic
Vertical Datum for the Florida Lower Gulf Coast ..................... .. 32
Figure 3. Relationship between open coast tidal datums and National Geodetic
Vertical Datum for the Northwest Panhandle Gulf Coast of Florida .......... 32
Figure 4. Erosion volumes, Qe, above MHW for identical profiles impacted by
identical storm events, but with different local MHW planes ............... 37
Figure 5. Beach profile-related terms...................................... 39
Figure 6. Seasonal horizontal shoreline shift analysis ........................ 41
Figure 7. Long-term shoreline shift analysis ............................... 43
Figure 8. Semidiurnal tide curves for 6 tidal days .................. ........ 46
Figure 9. Actual damage to the Flagler Beach Pier from the Thanksgiving Holiday
Storm of 1984 (Balsillie, 1985c) used to test the Multiple Shore-Breaking
Wave Transformation Computer Model for predicting wave behavior,
longshore bar formation, and beach/coast erosion ...................... 49
Figure 10. Beach/Coast nickpoint elevations for Florida ...................... 50
Figure 11. Comparison of Seasonal High Water (SHW) and Median Beach/Coast
Nickpoint Elevation (N) for the Florida East Coast ..................... 51
Figure 12. Comparison of Seasonal High Water (SHW) and Median Beach/Coast
Nickpoint Elevation (N,) for the Florida Lower Gulf Coast ................ 51
Figure 13. Comparison of Seasonal High Water (SHW) and Median Beach/Coast
Nickpoint Elevation (Ne) for the Florida Panhandle Gulf Coast ............. 51
Figure 14. Departure of Florida inlet tide data and open coast tide data ........... 53
Figure 15. Open ocean and inside astronomical tides for Ft. Pierce and St. Lucie
Inlets ........................................ ................ 54

LIST OF TABLES

Table 1. Tidal Datums and Ranges for Open Coast Gauges of Coastal Florida ...... 30
Table 2. Selected North American Datums and Ranges Referenced to MSL ........ 38
Table 3. Florida Foreshore Slope Statistics by County and Survey .............. 40
Table 4. Moment Wave Height Statistical Relationships ....................... 45

SPECIAL PUBLICATION NO. 43

SEASONAL VARIATION IN SANDY BEACH

SHORELINE POSITION AND BEACH WIDTH

by

James H. Balsillie, P. G. No. 167

ABSTRACT

Annual cyclic fluctuations in beach width due to seasonal variability of forcing elements
(e.g., wave energy) have been a subject of concerted interest for decades. Seasonal variability
can be used to 1) identify and evaluate the accuracy of historical, long-term shoreline data
interpretations, 2) aid in the identification of the boundary of sovereign versus private land
ownership, and 3) predict expected seasonal behavior of beach nourishment projects, which
should be a stated up-front design anticipation.

In this paper, data representing monthly averages are used to compare "winter" and
"summer" wave height and wave steepness as they relate to seasonal shoreline shifts. Coupled
with astronomical tide conditions and beach sediment size, two quantifying relationships are
proposed for predicting seasonal shift of shoreline position (i.e., beach width).

INTRODUCTION

The configuration of the beach in
profile view is primarily due to tidal
fluctuations which cause periodic changes in
sea level, and shore-breaking wave activity.
Any change in wave characteristics and
direction of approach will, depending on tidal
stage, result in a change in the sandy beach
configuration.

Systematic beach changes through a
single astronomical tidal cycle are well noted
(Strahler, 1964; Otvos, 1965; Sonu and
Russell, 1966; Schwartz, 1967). Cyclic cut
and fill associated with spring and neap tides
(Shepard and LaFond, 1940; Inman and
Filloux, 1960), and the effect of such
phenomena as sea breeze (Inman and Filloux,
1960; Pritchett, 1976), can contribute
additional modifying influences.

Beach changes are noted to occur at
time intervals longer than a tidal cycle (e.g.,
Dolan and others, 1974). Smaller beach
cusps, for example, may range from 10 to
50 meters apart, while sinuous forms may

span distances of from 450 to 700 meters,
and such features often migrate alongshore
at time scales on the order of days or weeks
(Morisawa and King, 1974). As the bay
between cusp horns passes a profile line, the
beach becomes narrower, and as a horn
passes, the beach widens. A prediction
model for daily shoreline change has been
suggested by Katoh and Yanagishima
(1988).

Of the possible cyclic changes,
perhaps the most pronounced is that
occurring on the seasonal scale. During the
"winter" season, when incident storm wave
activity is most active, high, steep waves
result in shoreline recession. Generally, the
berm is heightened with a gentle foreshore
slope, although erosion scarps may form.
Sand removed from the beach is deposited
offshore in one or more submerged
longshore bars. During the "summer"
season lower waves with smaller wave
steepness values transport sand stored
offshore back onshore, resulting in a wider
beach. It should be noted that along some
coasts such as the approximately east-west

FLORIDA GEOLOGICAL SURVEY

trending coastline of Long Island, New York
(Bokuniewicz, 1981; Zimmerman and
Bokuniewicz, 1987; Bokuniewicz and
Schubel, 1987), no seasonal variability can
be detected (H. J. Bokuniewicz, J. R. Allen,
personal communications). Such lack of
seasonal variability may be symptomatic of
sub-seasonal storm wave groups combined
with an almost imperceptible climatic change
(J. R. Allen, personal communications),
possibly exacerbated by changes in oceanic
storm front azimuths relative to shoreline
azimuths (Dolan and others, 1988).
Similarly, the east-west trending shoreline of
the northwestern panhandle coast of Florida,
while having annual net longshore transport
to the west, appears to be characterized by
daily to weekly rather than seasonal
reversals in longshore current direction
(Balsillie, 1975). It appears, therefore, that
east-west trending shorelines pose
considerations deserving further attention.
However, for much of the Earth's open,
ocean-fronting shoreline seasonal changes
are clear, which constitutes the subject of
this paper.

SEASONAL VARIABIUTY

Classically, seasonal variability is
associated with California beaches where
their geometric character changes noticeably
from "summer" to "winter" (e.g., Shepard
and LaFond, 1940; Shepard, 1950; Bascom,
1951, 1980; Trask, 1956, 1959; Trask and
Johnson, 1955; Trask and Snow, 1961;
Johnson, 1971; Nordstrom and Inman,
1975; Aubrey, 1979; O'Brien, 1982;
Thompson, 1987; Patterson, 1988; Collins
and McGrath, 1989). A considerable
number of such studies have also been
conducted along the U. S. east coast (e.g.,
Darling, 1964; Dolan, 1965; Urban and
Galvin, 1969; DeWall and Richter, 1977;
DeWall, 1977; Everts and others, 1980;
Bokuniewicz, 1981; Miller, 1983;
Zimmerman and Bokuniewicz, 1987).

Geometric characteristics of seasonal

change have been described in terms of sand
volume changes (Ziegler and Tuttle, 1961;
Dolan 1965; Eliot and Clarke, 1982; Aubrey
and others, 1976; Davis, 1976; DeWall and
Richter, 1977; DeWall 1977; Thorn and
Bowman, 1980; Everts and others, 1980;
Bokuniewicz, 1981; Miller, 1983;
Zimmerman and Bokuniewicz, 1987;
Samsuddin and Suchindan, 1987), by
contour elevation changes (Shepard and
LaFond, 1940; Ziegler and Tuttle, 1961;
Gorsline, 1966; Urban and Galvin, 1969;
Nordstrom and Inman, 1975; Aubrey, 1979;
Felder and Fisher, 1980; Clarke and Eliot,
1983; Berrigan, 1985; Brampton and Beven,
1989), and in terms of horizontal shoreine
shifts or beach width changes (Darling,
1964; Johnson, 1971; DeWall and Richter,
1977; DeWall, 1977; Aguilar-Tunan and
Komar, 1978; Everts and others, 1980;
Clarke and Eliot, 1983; Miller, 1983;
Garrow, 1984; Berrigan and Johnson, 1985;
Patterson, 1988; Kadib and Ryan, 1989).

Potential legal ramifications of
seasonal shoreline changes as they relate to
the jurisdictional shoreline boundary position
have been addressed by Johnson (1971),
Hull (1978), O'Brien (1982), and Collins and
McGrath (1989). While there are other
seasonal shoreline change applications
(discussed in the section on Application of
Results), the motivation for this work centers
about derivation of a least equivocal
methodology for identifying probable real
shifts in historical long-term shoreline
change.

In addition to wave height and wave
steepness, wave direction and beach
sediment characteristics can influence the
degree of seasonal beach change. Wave
direction is particularly influential for pocket
beaches found along the U. S. west coast.
Along some beaches (e.g., Oceanside Beach
just north of Cape Meares, Oregon) a sandy
"summer" beach is removed during the
"winter" season exposing a cobble beach.
In such cases, "summer" to "winter" grain

SPECIAL PUBLICATION NO. 43

size differences are significant. In this study,
however, we shall deal with relatively
straight, ocean-fronting beaches composed
entirely of sand-sized material.

DATA AND RESULTS

In an investigation of seasonal beach
changes at Torrey Pines Beach, California,
Aubrey and others (1976) state: "No field
studies to date have been able to adequately
quantify these wave-related sediment
redistributions." In approaching a
quantitative solutions) to the problem, it
becomes prudent to identify the force and
response elements involved. Basic force
elements are identified to be: 1) astro-
nomical tides, 2) wave height, and 3) wave
steepness. Response elements are: 1) vol-
ume change, 2) change in beach elevation,
or 3) horizontal shoreline shift. While the
beach sediment might be viewed as a
response element, given the paucity of
information about temporal/spatial sediment
variation as it impacts this problem, it may
be prudent to treat sediment characteristics
(within the sand-sized range) as a property
element (see section on Beach Sediments for
further discussion).

The response element used here is
the horizontal shoreline shift. Fortunately,
we are dealing with a measure which,
compared to the others, has the largest
range in possible values. For example,
vertical contour changes are less than 1-1/2
to 2 meters, and volumetric changes would
be 3 to 4 times less than horizontal shift
("rule-of-thumb" guidance suggested by U.
S. Army (1984) and Everts and others
(1980)), while horizontal shift may range up
to tens of meters.

Data

While the amount of data available to
quantify seasonal variation in shoreline
position is not large, 14 data sets for which
sufficient information appears to exist were

located to search for a solution (Table 1).

First, it might be reasonable to
inspect the relationship between
astronomical tidal conditions and horizontal
seasonal shoreline shift, Vs, since the tidal
condition essentially constitutes a signature
characteristic for each site (i.e., it can vary
considerably depending on the coast under
study). Horizontal seasonal shoreline shift is
defined as Vs = Vmax -Vmi, where Vma is
the largest measurement representing the
widest seasonal beach, and Vm,, is smallest
measurement representing the narrowest
beach (in this paper V is the distance from
an arbitrary permanent coastal monument to
the shoreline at any one time). The mean
range of tide, h,, (i.e., the difference
between mean low water and mean high
water), is plotted against Vs in Figure 1.
While there is scatter in the plot, a general
trend is apparent.

In addition to astronomical tide
conditions, we know that wave climate must
be considered and that it, like tidal
conditions, varies widely from coast to
coast. Selection of values for variables
given in Table 1 can be illustrated using time
series plots of monthly averages for
shoreline shift and wave data. An example
for Torrey Pines Beach, California, is plotted
in Figure 2, which represents two years of
concurrently observed monthly averages for
shoreline position, wave height, wave period,
and sediment data (Nordstrom and Inman,
1975; Pawka and others, 1976). Further,
the data have been smoothed by a three-
point moving averaging sequence.
Comparison of horizontal shoreline shifts and
wave heights suggests that for the months
from about December through April storm
wave activity prevailed, resulting in a
narrower beach, with lull conditions from
about May through October coinciding with
beach widening. Hence, the average storm
wave height, Hs, is that occurring from
December through April, and the average lull
wave height, HL, is that occurring from May

FLORIDA GEOLOGICAL SURVEY

Table 1. Force, response, and property elements for seasonal shoreline shift analysis.

Sit V, Hs H, T TL hT, D L/Q,
t (m) (m) (m) (s) (s) m (mm)
Gleneden, OR 46.9 1.14 0.72 9.2 8.1 1.91 0.35 0.815
Stinson Beach, CA 42.7 1.28 0.99 16.1 12.1 1.21 0.30 1.370
Atlantic City, NJ 32.0 1.04 0.77 7.4 7.0 1.40 0.30 0.820
Torrey Pines, CA 29.0 1.34 0.99 11.8 11.4 1.28 0.28 0.794
Goleta Point, CA 22.9 1.07 0.73 12.5 14.0 1.28 0.21 0.547
Duck, NC (1982) 18.6 1.10 0.75 8.8 8.1 1.00 0.40 0.808
(1983) 20.4 1.26 0.73 9.2 8.1 0.98 0.40 0.749
(1984) 17.4 1.15 0.70 8.7 8.4 0.96 0.40 0.654
Surfside-Sunset, CA 20.1 1.10 0.73 10.2 13.2 1.07 0.26 0.398
Huntington Beach, CA 18.3 1.14 0.99 11.6 10.4 1.15 0.21 1.078
Holden Beach, NC 15.2 0.70 0.50 6.5 7.0 1.30 0.30 0.614
Jupiter Beach, FL 10.7 1.00 0.63 5.4 5.5 0.92 0.42 0.614
Boca Raton, FL 2.4 0.64 0.51 4.9 4.5 0.84 0.90 0.933
Hollywood, FL 2.1 0.49 0.47 4.7 4.5 0.79 0.60 1.037
Vs = Seasonal range in shoreline position or beach width; Hs = Storm season average wave height;
H, = Lull season average wave height; Ts = Storm season average wave period; TL = Lull season average wave
period; h,, = Mean range of tide; D = Swash zone mean grain size: q, = Lull season wave steepness; (p =
Storm season wave steepness; CA = California, FL = Florida, NC = North Carolina, NJ = New Jersey, OR =
Oregon. Sources of data are given by beach in the text.
=1 ii ....

through October. Note
wave period varies
throughout the year for
site.

that
little
this

The classic example of (m) o2
seasonal shoreline shift
(Johnson, 1971; O'Brien, 1982) 0
for Stinson Beach, California,
represents a 22-year period Figure 1.
(1948-1970), suggesting an variability,
average shoreline shift of about
43 meters annually. These data are plotted
against six years of wave data for the period
1968 to 1973 (Schnieder and Weggel,
1982) in Figure 3. Sediment data are from a
separate source (Szuwalski, 1970). Note
that unlike the data plotted in Figure 2, wave
period shows a concerted seasonal trend.
The inference may be made, therefore, that
special attention should be given to seasonal
wave steepness values. More recent
shoreline surveys published by Collins and
McGrath (1989) for three years (1984-1986

hmrt (m)
Relationship between seasonal shoreline
VS, and mean range of tide, hmrt.

inclusive) consistently result in the 43-meter
seasonal shoreline shift reported by Johnson
(1971) and O'Brien (1982).

Concurrently observed data for four
years at Jupiter Beach, Florida (DeWall,
1977; DeWall and Richter, 1977) are plotted
in Figure 4. It is apparent from Figure 4 that
lull wave heights occur from about May
through September resulting in a wider
beach, with storm waves occurring from
about October through at least January

VS 40

SPECIAL PUBLICATION NO. 43

11
0 -.

,)o

M J J A S 0 N D J F M A M

Figure 2. Monthly time series for Torrey
Pines Beach, California, for shoreline
variability, V; breaker height, Hb, and wave
period, T.

producing a narrower beach. Monthly
averages for wave heights and periods were
concurrently measured, with a reported
representative grain size.

A single year of monthly wave data
were collected (Aguilar-Tunan and Komar,
1978) at Gleneden Beach, Oregon, from
which a seasonal shoreline shift of about 47
meters is evident. Because wave data
reported by the authors are probably
inappropriate (i.e., they strongly appear to
represent the initial offshore breaking wave
height), the multi-year data reported by the
U. S. Army (1984) are used. A single swash
zone sediment size was reported by Aguilar-
Tunan and Komar (1978). Shoreline shift
and wave data are plotted in Figure 5.

These four examples illustrate how
wave data values were determined to
represent each season, where the lull season

70 *

so -
65 k Ii

O : -'; \

1.4 -
1.3 -
b 12
(M) -

16

12 ---
I'

J F M A M J J A S 0 N 0 J

Figure 3. Monthly time series for Stinson
Beach, California, for shoreline variability, V;
breaker height, Hb; and wave period, T.

wave height and period are given by H,, and
TL, respectively; similarly, storm season
variables are given by Hs, and Ts. Wave
heights and periods were selected to
represent conditions for the lead flanks of
seasonal accretion/recession trends, since it
is under these force element conditions that
responses are produced.

Similar analyses were conducted for
Boca Raton and Hollywood Beaches in
Florida (DeWall, 1977; DeWall and Richter,
1977) for four years of monthly data for V,
wave height and period, with mean grain
sizes for swash zone sediment.

Data published for Holden Beach,
North Carolina (Miller, 1983) were plotted by
the original author so that seasonal changes

FLORIDA GEOLOGICAL SURVEY

10 .0

Hb 0.9
0.86
(m) 0.6
0.5
0.4

(S)

i F M A M J J A S 0 N D J
month
Figure 4. Monthly time series for Jupiter
Beach, Florida, for shore variability, V;
breaker height, Hb; and wave period, T.

could be directly assessed by measuring
peaks of change. The data represent four
years of approximately monthly profiles for
16 alongshore profiles, with concurrently
measured wave data. Sediment data are
from the U. S. Army (1984).

Results for Goleta and Huntington
Beaches, California (Ingle, 1966) include
approximately monthly surveys for a one-
year period, including beach profiles, wave,
and sediment data. Unfortunately, wave
information for these sites represents
only those conditions for the day profiles
were surveyed. While information for these
sites generally was consistent, wave period
data from Schneider and Weggel (1982)
were used for Goleta Beach due to
unresolvable dispersion in the few daily data.

Seasonal shoreline shift data for
Atlantic City, New Jersey (Darling, 1964)
were measured for a two-year period along

30 -

8) -

Untie
1.3
1.2

Figure 5. Monthly time series for Gleneden
Beach, Oregon, for shoreline variability, V;
breaker height, Hb; and wave period, T.
(,)

Month
Rgure 5. Monthly time series for Gleneden
Beach, Oregon, for shoreline variability, V;
breaker height, Hb; and wave period, T.

with simultaneously measured seasonal
wave data. Sediment data are from the U.
S. Army (1984).
Perhaps the most complete data sets
are for Duck, North Carolina, at the Coastal
Engineering Research Center's Field
Research Facility. All information necessary
for this study was collected simultaneously
to result in data for three years (Miller, 1984;
Miller and others, 1986a, 1986b, 1986c).

For a 4-1/2 year period, Patterson
(1988) reports a Vs of 20.1 meters for
Surfside-Sunset Beach, Orange County,
California, along with seasonal wave
information. Sediment grain size information
is from Szuwalski (1970).

Where the specific studies discussed
above did not provide the necessary
astronomical tide information, these data
were obtained from other sources (Harris,

c5s ab

SPECIAL PUBLICATION NO. 43

1981; U. S. Department of Commerce,
1987a, 1987b).

It is worthwhile to note that Berrigan
and Johnson (1985) compared wave power
computations to shoreline position for seven
years of data at four localities along Ocean
Beach, San Francisco, California. Deep
water wave data were measured at sites
ranging from 3.9 to 26.7 kilometers offshore
(Berrigan, 1985). While some refraction
effects may have occurred due to the San
Francisco entrance bar, there appears to be
a correlation between an increase in wave
power and decrease in beach width.

Results

There is, from Figure 1, an indication
that astronomical tides play a role in
seasonal variability. The mean range of tide,
hmrt and seasonal wave height difference,
AH = Hs H,, might be expressed as a sum,
i.e., h,, + AH, or as a product, i.e., hn,,
(AH). Since energy according to classical
wave theory is proportional to the height
squared, the product, i.e., hi, (AH), might
be more appropriate. On the other hand, the
sum has merit because laboratory data, if
available, could be used (i.e., since tides are
almost never modelled in laboratory studies,
a product would be meaningless because the
result would always be zero). In either
event, many combinations of parameters
were investigated (Balsillie, 1987b; see also
Table 2 for some of the equations), and it
was found that the sum was not nearly as
successful as the product; either scatter was
excessive as indicated by a low correlation
coefficient, r, and/or the fitted regression line
did not pass through the origin of the plot.

Many researchers have emphasized
the importance of wave steepness in
influencing the shore-normal direction of
sand transport (e.g., Johnson, 1949; Ippen
and Eagleson, 1955; Saville, 1957; Dean,
1973; Sunamura and Horikawa, 1974;
Hattori and Kawamata, 1980; Sawaragi and

Deguchi, 1980; Watanabe and others, 1980;
Quick and Har, 1985; Kinose and others,
1988; Larson and Kraus, 1988; and
Seymour and Castel, 1988). In this paper,
the "summer" or lull season wave steepness
is expressed as CL = HL/(g TL2), and the
"winter" or storm season steepness as Cs =
Hs/(g Ts2). It became apparent that
incorporation of the wave steepness ratio
induced numerical consistency in
quantitative prediction. Whether the ratio is
evaluated as Q,/Ps or PS/q)L becomes
important. The form of the ratio for various
arrangements of relating expressions for
assessment purposes is given in Table 2.
Hence, if ((P/S) < 1.0 then wave height
during the storm season must be more
important; if (0P/Qs) > 1.0 then wave
steepness plays a stronger role. In fact, it
would be expected that Pj/Ps results in
better correlation, since beaches are eroded
by steeper waves, with lower steepness
waves resulting in accretion.

In addition, beach sediment
characteristics have been touted to play a
significant role. The general view is that,
holding force elements constant, a beach
composed of coarser sediment is more stable
than a beach composed of finer material
(e.g., Krumbein and James, 1965; James,
1974, 1975; Hobson, 1977), ie., a beach
comprised of coarser sediment should exhibit
less seasonal variability than a beach
composed of finer sediment (note that this
explanation is not so straightforward, and
will be addressed in greater detail in the
following section). Since a number of
investigators have published general
quantifying relationships which in addition to
wave height and steepness, incorporate sand
size (e.g., Dean, 1973; Hattori and
Kawamata, 1980; Sawaragi and Deguchi,
1980; Watanabe and others, 1980), it would
be prudent to consider granulometry in this
study.

Again, it is to be noted that many
forms of possible relating parameters were

FLORIDA GEOLOGICAL SURVEY

Table 2. Assessment of the wave steepness ratio for a selection of expressions
related to V.
Expressions Using q)L/gS r Expressions Using (gS/PL r

hA [((H) 0,/,] hmn + [(H ) 0/J
0.9339 0.7445

[hm + (AH)] 0.8843/ [hm, + (A/)] s 0.4071
0.8843 0.4071

hr (AH) 0.9047 h (A s 0.5498

h + [((A) /s] hr + [(HA) es/*]
D 0.8567 D 0.3837

h, ,,, (A) *0,/1s h,, (AH) s/,L
0 0.9672 D 0.5478

r = Pearson product-moment correlation coefficient between each expression evaluated
using measured force and property element data of Table 1, and measured VS response
data of Table 1.

considered in an earlier study, but that only
the most successful are presented here.
Incorporating the preceding considerations,
two equations are presented, the first which
includes force elements only, which posits:

V, = 78.5 h,, (AH) *e/Os (1)

and is plotted in Figure 6. The cubic least
squares regression coefficient (forced
through the origin) of 78.5 is in units of mr1
where the mean range of tide, h,,, and
seasonal wave height difference, AH, are in
meters. The standard deviation of the data
from the equation (1) regression line in the
vertical direction (Ricker, 1973) is 11.4 m.
The second equation includes the mean
swash zone grain size, D, to yield :

V = 0.025 h,,"tAH)
D

plotted in Figure 7, wherein all variables are
expressed in consistent units. In terms of
dimensions, one will note that when all
dimensional cancellations are made in
equations (1) and (2), length only remains.
The coefficient of 0.025 was determined
using the same fitting procedure as for
equation (1). It is apparent from the figures
that equation (2) reduces some of the scatter
of equation (1). The standard error (Ricker,
1973) of equation (2) in the vertical direction
is 6.8 m. It may also be of interest to note
that the coefficient of equation (1) when
expressed relative to the coefficient of

SPECIAL PUBLICATION NO. 43

equation (2) results in a mean
grain size of 0.318 mm which,
using the Wentworth
classification scheme, is a
medium-sized sand (Wentworth,
1922).

DISCUSSION

A favorable result from
many of the prediction equations
tested during the course of this
investigation is that most showed
a trend between Vs and the relating
parameters (e.g., column 1 of
Table 2). Ostensibly, such
consistency should not be
surprising since the major factors
known to cause seasonal
variability were considered, and
the remainder of the work
involved rearranging the variables
scatter. Further, the goal to
seasonality was a simplified

VS 40 r 0.9047

( 20 It
(m) 20,
oI-^' l l ; a J ,
0 0 I 2 0o3 04 0.5 0.6 07
hm,,, mathematical / (m2)
Figure 6. Illustration of mathematical fit for equation (1).

(m) 20

1500

2000

hmrt(AH) 4L/S (m)
Figure 7. Iustration of mathematical fit for equation (2).
Figure 7. Illustration of mathematical fit for equation (2).

to reduce
delineate
approach

(compared to relating the entire time series
of monthly values which becomes
increasingly complex).

Equations (1) and (2) engender some
heterogeneity that needs discussion. Both
AH and 0/0s are seasonal parameters.
Granulometry as it appears in equation (2) is
a property element application, although a
seasonal response element application is
possible and is discussed in a later section.
The quantity, hmrt, however, is not a
seasonal measure. It is, rather, an average
approximate hourly measure where one tide
(diurnal) or two tides (semi-diurnal) occur in
one tidal day of 24 5/6 hours. Hence, hmrt
is also a property element that is a signature
value for each site, noting that it can vary
significantly depending upon the locale.
Seasonal mean sea level change for which
there are no site-specific data for Table 1
localities, is discussed in a following section.

The results of this work might be best
viewed as a first appraisal until more data

become available to further test and/or
enhance the prediction relationships.
Nevertheless, the results presented here are
statistically valid; one should not be timid in
applying resulting computational values
pending future refinement in prediction
methodology. One purpose of this paper is
to act as a plea for more data. Following are
discussions of a few concerns related to
seasonal shoreline variation predictions.

The Single Extreme Event and
the Combined Storm Season

The sandy littoral zone is comprised,
from offshore-to-onshore, of the nearshore,
the beach, and the coast. Each of these
three subzones is created and maintained by
sets of force elements normally different
from each other within the long-term
temporal framework. When a storm or
hurricane impacts the littoral zone, the
following scenarios are possible: 1) the
extreme event produces a combined total
storm tide which rises above the beach-coast
interface elevation to affect all three
subzones, 2) the combined total storm tide
does not rise above the beach-coast

I I I I .J r F I J
s hmrt (AN) *L1S a
r = 0.9672

* i , i | 1 , ,

0

L

FLORIDA GEOLOGICAL SURVEY

interface elevation but does persist long
enough for the beach to be eroded and the
coast is attacked by storm waves, 3) the
combined storm tide does not rise above the
beach-coast interface elevation and is short
enough in duration so that only the
nearshore and beach are affected, and 4) the
extreme event remains out at sea so that
impact is indirect (i.e., a combined total
storm tide does not or only fractionally
reaches the shore) and storm waves
primarily affect the nearshore and beach.
The combined total storm tide used here is
defined by Dean and others (1989) as the
storm surge due to astronomical tide, wind
stress, barometric pressure, and breaker
zone dynamic setup, which defines the
active phenomena for scenarios 1, 2, and 3
(i.e., the storm ide event). Scenario 4
includes only the effects of breaking wave
activity, including dynamic wave setup, and
is termed the storm wave event. Scenarios
1 and 2 are those which, depending on
storm strength, duration, continental slope,
and approach angle, usually produce the
design erosion event (Balsillie, 1984, 1985a,
1985b, 1986). Probabilistically, the
frequency of occurrence increases from
scenario 1 to 4.

Under certain circumstances of event
longevity, astronomical tides, and nearshore
slopes, exceptions can occur. One such
exception occurred when Hurricane Gilbert
struck Cancun, Mexico in 1988. Because
there is essentially no continental shelf and
nearshore slopes are steep, all eroded sand
from Cancun's beaches was removed and
natural beach recovery was not possible.
Potentially, other exceptions can occur
where, for instance, submarine canyons
might act as a sediment transport conduit
and sand is irremeably lost from the littoral
system. For most shores, however,
continental shelves are wide and nearshore
slopes gentle enough that beach recovery to
pre-storm dimensions following single storm
impact occurs in a period of one to several
days (Birkemeier, 1979; Bodge and Kriebel,

(m) s5 \ -

40'
1 2 3 4 5 6 7 8 9 101112
Day
Figure 8. Example of the quick response and
recovery of the beach to storm wave
activity, Pensacola Beach, Florida, December
1974;the storm peak occurred on December
7 (data courtesy of James P. Morgan,
personal communications).

1986; Savage and Birkemeier, 1987), for
events described by scenarios 1, 2 and 3
above. Beach recovery following the effects
of a storm wave event (i.e., scenario 4) was
recorded by James P. Morgan at his
Pensacola Beach, Florida, home (Figure 8);
within a day following storm wave
abatement, the beach had recovered to its
pre-storm width.

The magnitude of seasonal shoreline
change may vary from year-to-year, since for
any site some years may have more frequent
and intense storm tide and wave activity
than other years. Horizontal shoreline shifts
due to direct storm and hurricane impacts
are now usually recorded. However, for
storms that do not directly impact the shore
(i.e., are far out at sea, for example Tropical
Storm Juan (Clark, 1986) which affected
Florida) but generate storm waves that do

SPECIAL PUBLICATION NO. 43

cause shoreline erosion, such
erosion is usually not measured.

Dolan and others (1988)
conducted an extensive study on
extratropical storm activity,
assessed also in terms of storm a
wave hours, for 41 years of data g
(1942 to 1984) along the Outer 4
Banks of North Carolina. These .
data (Figure 9) show a concerted 2
seasonal trend. In addition, the g
author extracted from Neumann 3
and others (1981) tropical storms
and hurricanes whose tracks A
E
came within about 250 miles of I
the Outer Banks for the period & 2-
1940 to 1980. These latter data,
also plotted in Figure 9, are added
to the extratropical data (plotted
as a bold, solid line). Hence, the .
total storm record is nearly
represented and, except for only
a few direct impacts, represent
storm wave events (i.e., scenario o
4 above). For the mid-Atlantic, JA
about 35 storms occur per year
on the average (about 26 winter Figure 9.
events and 9 summer events), wave eve
93% of which are extratropical
events. In terms of storm wave duration,
Dolan and others (1988), determined using
hindcast techniques that on the average,
storm waves occur for about 571 hours per
year (i.e., 24 days per year) for extratropical
storms off of the Outer Banks; winter storm
waves persist for an average of 433 hours
(i.e., 18 days), and summer storm waves
about 156 hours (i.e., 6.5 days). These data
strongly correlate with the expectation of
wider mid-Atlantic east coast summer
beaches and narrower winter beaches, and
illustrate the important fact that a large
number ... not a few ... winter storm events
are required to maintain a narrower winter
beach relative to a wider summer beach.

I I I V I I I

EXTREME EVENT TYPE
o Extratroplcal (Dolan, Line, and
Hayden, 1988) 1942-1984
Tropical (Neumann et al.
*Hurricane 1981) 1940-1980

\ /

o -
0
Total P

/

/\

So' I
ap--.,iA

. .-r -".--r" e ..
N FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Month
Monthly average occurrences of extreme event
nts for the Outer Banks of North Carolina.

Beach Sediments

Beach sediments engender some
interesting concerns. How we consider
sediments depends upon whether
granulometry is applied as a property
element or a response element, which in turn
has an effect on the dimensional
configuration of a numerical representation.
As an example, equation (1) requires an
additional parameter with units of L'' for the
equation to be unit consistent. Equation (2)
was rendered unit consistent by dividing by
a granulometric parameter with a length
dimension. If this is to be the applied case,
it is useful to note that when sedimentologic
grain size is specified in S. I. units, the mean
grain size and standard deviation moment
measures have units of mm, while

FLORIDA GEOLOGICAL SURVEY

skewness and kurtosis are Tat
dimensionless. Otherwise, the slope
granulometric moment measures can
be specified all in dimensionless phi
units.

Beach sands characteristically
St
have a range in size from 0.1 mm to Gr
1.0 mm (U. S. Army, 1984) which Cr
occupies about 46% of the sand- J.
sized range of Wentworth (1922; Na
i.e., 0.0625 to 2.0 mm). From Table Fo
3, it is apparent that the range in
mean grain sizes occurring over an Du
annual period is less than 1/3 of the
commonly found range in beach sand
size (i.e., 0.9 mm). Therefore, the Gc
Trn
typical annual mean grain size, D, for Sa
any beach might be an appropriate Hu
measure to consider as a property La
element provided that sufficient
samples are available annually to
obtain a reliable measure (e.g., a suite of
monthly samples). This implies that there
needs to be a real difference in mean grain
sizes from site-to-site for the application to
have meaning. Even so, the use of mean
grain size alone without consideration of
standard deviation, skewness and kurtosis
remains somewhat of a curiosity other than:
1. its use results in a good fit for equation
(2), 2. is properly applied in equation (2)
(i.e., the larger the value of D, the smaller
becomes Vs), 3. produces the proper unit
dimensions for the equation, and 4. has
been a considered variable in other research
results.

It is generally the case (CASE 1 of
Table 4) that the coarsest beach sand is
found in the swash zone, and which is the
only type of sample considered here since it
directly represents energy expenditures of
the littoral hydraulic environment. One
might suspect that swash samples are
coarser during the storm than the lull
season. However, the range in sediment
size within the sand-sized range is limited for
any beach to the coarsest available material

le 3. Mean annual beach grain size (foreshore
samples) from monthly data, and range in size.
Annual Range
Site D (mm) of D Source
(mm)
FLORIDA
.Andrews St. Pk. 0.29 0.04 Balsillie, 1975
ayton Beach 0.37 0.13
ystal Beach 0.37 0.15
C. Beasley St. Pk. 0.40 0.11
varre Beach 0.41 0.14
rt Pickens Beach 0.43 0.27
NORTH CAROLINA
ick 0.40 0.19 Miller, 1984
CALIFORNIA
)leta Pt. Beach 0.21 0.16 Ingle, 1966
ancas Beach 0.22 0.18 "
nta Monica Beach 0.26 0.29
ntington Beach 0.21 0.14
Jolla Beach 0.17 0.04

Table 4. Two cases of sedimentologic

response of moment
energy levels.

measures to wave

commensurate with bulk properties meeting
conservation of mass and energetic
constraints (Passega, 1957, 1964). In fact,

CASE 1 CASE 2
Energy Levels Are Eegy evels Ae
Excessive to t Excessive to
s~senengicllit seenousalogic
ResponSe Resmpose
MEAN GRAIN SIZE

Ds = DL sI > DL
SKEWNESS
Sks SkL Sks < SkL
KURTOSIS

K < KL KS < KL
NOTES: Subscripts S and L refer to the storm season
and lull season, respectively. The corresponds to
symbol, -, is meant to signify that the measure did
not change due any recognizable response to energy
level force element changes.

SPECIAL PUBLICATION NO. 43

the negligible effect of sand-sized material on
runup for larger waves has been noted by
Savage (1958). His results strongly imply
that relative to sand size, as the wave height
increases there is reached a point beyond
which sediment size within the sand-sized
range no longer discriminately responds.
That is, the level of wave energy is
overpowering even to the coarsest fraction
of sediment available within the sand-size
range.

Hence, unless the wave climate is
closely in equilibrium with sediment
comprising the beach, one would not
necessarily expect to find significantly
correlative seasonal changes in mean grain
size (or for that matter skewness, although
it might be somewhat less sensitive to
energy) within the sand-size range. The
author located data where at least monthly
sand samples were collected with concurrent
wave data for sites along the U. S. west,
east, and Gulf coasts. There was no
discernible seasonal correlation between
waves and mean sediment grain size.
Several typical examples are illustrated in
Figure 10.

Samsuddin (1989), however, reports
to have found correlation between seasonal
changes in wave conditions, foreshore slope,
and sand-sized textural changes along the
southwest Kerala coast of India, wherein
mean grain size increased and kurtosis
decreased during higher seasonal wave
energy conditions (CASE 2, example 1).
Samsuddin's one-year investigation, in which
beach foreshore sand was seasonally
sampled, may have been a fortuitous year in
which equilibrium conditions were more
nearly manifest. Kerala sand samples are
also characterized by a consistently large
standard deviation which allows for greater
leeway in sorting potential (0.6 to 0.7 phi
compared to 0.2 to 0.55 phi commonly
found for U. S. beach sands). Unfortunately,
Samsuddin did not describe the mineralogy
or shape characteristics of the samples

J F MA J J SO D J F MA M J J AS ON O
Figure 10. Typical examples of time series relation
of monthly data for breaker height, wave period,
and foreshore slope grain size for California (data
from Ingle, 1966) and northwestern Florida
panhandle (data from Balsillie, 1975) sites.

which may or may not differ from the
characteristically rounded, quartzose-
feldspathic U. S. beach sands considered in
this work.

There also occurs the case (CASE 2,
example 2) where a beach is comprised of
sediments exceeding the sand-sized range.
An example is Oceanside Beach, Oregon,
mentioned earlier, in which all the sand-sized
summer beach material is removed to expose
a winter cobble beach. Under such
conditions, one would expect that sediment
coarsening, as reflected by the mean grain
size and skewness, would result from higher
wave energy levels because of the excessive
size of coarser sediments.

When singularly considered, the 1st
moment measure (mean grain size) tells us
nothing about the nature of the distribution.

FLORIDA GEOLOGICAL SURVEY

The 2nd moment measure (standard
deviation) tells us about the dispersion about
the 1st moment measure, but leaves no
insight as to how the distribution departs
either symmetrically or asymmetrical from
the normal bell-shaped frequency curve (or
from the straight line for the cumulative
curve plotted on standard probability paper).
Such departure is a characteristic of the tails
of the distribution about which knowledge is
progressively imparted to us by considering
the 3rd moment measure skewnesss), 4th
moment measure, kurtosiss), and higher
moment measures (Tanner, personal
communication; Balsillie, 1995). It is, in
fact, the tails of the distribution which can
provide a great deal of environmental
information. It has been demonstrated, for
instance, that there is an inverse relationship
between the kurtosis and the level of surf
wave energy expenditure (Silberman, 1979;
Rizk, 1985; Rizk and Demirpolat, 1986;
Tanner, 1991, 1992). Tanner (1992) has
reported a correlation between sea level rise
and kurtosis, because the rise component is
attended by an increase in surf wave energy
expenditure.

From the preceding discussion, it is
apparent that two general cases can be
identified where wave energy levels either
exceed stability constraints of the coarsest
fraction of the sedimentologic distribution, or
they do not. For three moment measures
considered to best represent sedimentologic
response to the wave energy force element,
storm and lull season responses are listed in
Table 4. For the two cases (Table 4) only
the kurtosis persists in providing a response,
because the 4th moment measure is not
rendered ineffective to register a change by
excessive wave energy levels. Therefore, a
parameter for consideration that more nearly
quantifies sedimentologic response might be
given by:

S20 + Sk) K (3)
D

where the moment measures are defined in
Table 4. The 3rd moment measure
skewnesss) of equation (3) has a value of 20
added to it in order to assure that positive
values will result. The parameter 0 when
evaluated using S. 1. units has units of L-1
(dimensionless units result when
granulometric measures are evaluated in phi
units). By using seasonal values of 8, that
is, 0s for the storm season and 6L for the lull
season, it may be possible to compile a
sedimentologic response element parameter
that can be incorporated into equation (1).
The proper form of the parameter, including
equation (3), however, requires additional
data, research, and testing.

Astronomical ides

That mean astronomical tide
elevations exhibit cyclic seasonal variability
has long been established (Marmer, 1951;
Swanson, 1974; Harris, 1981) and is
included in tide predictions. The U. S.
Department of Commerce (1987a, 1987b)
states, however, that at "... ocean stations
the seasonal variation is usually less than
half a foot." Marmer (1951) notes that
seasonal variation in terms of monthly mean
sea level for the U. S. can be as much as
0.305 m (1 foot; Table 5); some examples
for the U. S. east, Gulf, and west coasts are
illustrated in Figure 11. Based on the many
years of monthly data, researchers (Marmer,
1951; Harris, 1981) note slight variations in
the seasonal cycle from year-to-year, but
also recognize the periodicity in peaks and
troughs over the years. For much of our
coast, lower mean sea levels occur during
the winter months and higher mean sea
levels during the fall. Harris (1981)
inspected the record to determine if storm
and hurricane occurrence was in any way
responsible for the seasonal change, but
found "... no systematic variability". Galvin
(1988) reports that seasonal mean sea level
changes are not completely understood, but
suggests that there appears to be two
primary causes for lower winter mean tide

SPECIAL PUBLICATION NO. 43

levels for the U. S. east coast: 1. strong
northwest winter winds blow the water
away from shore, and 2. water contracts as
it cools. He notes that winds are more
important in shallow water where tide
gauges are located, but that contraction
becomes important in deeper waters.
Swanson (1974) also notes "... seasonal
changes resulting from changes in direct
barometric pressure, steric levels, river
discharge, and wind affect the monthly
variability."

Seasonal variation in tides is usually
attributed to two harmonic constituents:
one with a period of one year termed the
solar annual tidal constituent, and the other
with a period of six months termed the solar
semiannual constituent (Cole, 1997). Some
consider these to be meteoroligical in nature,
rather than astronomic. However, because
the root cause of cyclic seasonal weather is
the changing declination of the sun, they
should more nearly be astronomical in origin.
Harmonic analysis of the annual tidal record
can easily determine the amplitude and
phase of each of these constituents, thereby
providing a mathematical definition of the
seasonal variation. (George M. Cole,
personal communications.)

Comparing the closest appropriate
curve from Figure 11 to Figures 2 through 5,
it is apparent that the lowest seasonal stand
of mean sea level and, therefore, average
astronomical tide effects occurs when the
beach is narrowest for Stinson Beach and
Torrey Pines Beach, California, and Jupiter
Beach, Florida. For Gleneden Beach,
Oregon, narrow beach widths and monthly
average tidal highs seem to be more nearly in
phase. Therefore, it is not clear that
seasonal changes in astronomical tides
significantly affect seasonal shoreline
variability, at least not in terms of average
monthly measures. Quite clearly, however,
such data needs to be procured for each site
to confirm a correlation or lack thereof.
Should the proper correlation consistently

Table 5. Seasonal range in monthly
average water levels.

ite No h
hYeLrs (m)

U. East Coast
New York 19 0.177 Feb Sep
Atlantic City 19 0.165 Feb Sep
Baltimore 19 0.238 Feb Sep
Norfolk 19 0.177 Feb Sep
Charleston 19 0.253 Mar Oct
Mayport 19 0.314 Mar Oct
Miami Beach 17 0.259 Mar Oct

U. s. Ci coast
Key West 19 0.216 Mar Oct
Cedar Key 10 0.244 Feb Sep
Pensacola 19 0.232 Feb Sep
Galveston 19 0.247 Jan Sep
Port Isabel 4 0.262 Feb Oct

U. West Coast
Seattle 19 0.159 Aug Dec
Astoria 19 0.219 Aug Dec
Cresent City 14 0.180 Apr Dec
San Francisco 19 0.104 Apr Sep
Los Angeles 19 0.152 Apr Sep
La Jolla 19 0.143 Apr Sep
San Diego 19 0.152 Apr Sep
Notes: 1. h = seasonal range based on average of n
years of monthly means where monthly means are
average of hourly heights; 2. San Diego gauge is
located in San Diego Bay; 3. Astoria gauge is located 15
miles upstream from the mouth of the Columbia River.

occur (e.g., low monthly average mean sea
level wider beaches, and high monthly
average mean sea level narrower beaches)
then a relating parameter needs to be
incorporated in the quantifying predictive
relationshipss. It is of consequence to note,
for the data of Tables 1 and 4, that the
seasonal range of monthly average mean sea
level is from 9 to 33% of the mean range of
tide (hmrt).

APPLICATION OF RESULTS

While horizontal shoreline shift (or
beach width change) addresses only one

FLORIDA GEOLOGICAL SURVEY

KEY WEST

rr~ZEY

U. L. EAST COAST
I l l i ,

- 7! M !! M 1 A 1 O jD

U. S. GULF COAST

JF M AM J J a SIO N U
MONTH

SAN IEGO
U. 5. WEST COAST
I I .

J FUAMJJAUONO

Figure 11. Monthly variation in sea level
Manner, 1951).

dimension of a measure of beach change, it
does serve to straightforwardly punctuate
the nature of the phenomenon. The manner
of approaching quantification of the
phenomenon here, allows for a simply
applied methodology that is useful for
educational, technical, and planning
purposes.

General Knowledge

Seasonal beach shifts are not
generally known by the layman. In Florida,
with 35,000 new residents arriving monthly
(Shoemyen and others, 1988), new coastal
property owners have been alarmed after
purchasing ocean-fronting property during
the "summer" when their beach is wide, to
find or return to find a narrow "winter"
beach, believing that they have unwittingly
purchased eroding property. Ostensibly, this
might result in an application for a permit to
construct a coastal hardening structure such
as a bulkhead or seawall without
investigating seasonal beach width variation
on the part of the applicant, the applicant's
design professional, or the permitting

for the contiguous United States (after

agency. The results of this paper provide a
quantitative basis upon which to inform the
public, and a method to assess a permit
application.

Seaward Boundary of Pubc
versus
Private Ownership

The boundary between private (i.e.,
upland) and public (i.e., seaward) beach
ownership is fixed by some commonly
applied tidal datum. For most of the U. S.
this is the plane of mean high water (MHW)
which, when it intersects the beach or coast
forms, the mean high water line. However,
unlike other riparian ownership
determinations (i.e., fluvial, lacustrine and
estuarine), littoral properties must, in
addition, contend with significant wave
activity that seasonally varies. Hence,
ocean-fronting beaches all-too-often
experience cyclic seasonal width changes of
a magnitude long recognized as problematic
in affixing an equitable boundary (Nunez,
1966; Johnson, 1971; Hull, 1978; O'Brien,

LOS AN ELES

6A JOLLA

f l l i l

Ps0c

CREIEsT CITY

SPECIAL PUBLICATION NO. 43

1982; Graber and Thompson, 1985; Collins
and McGrath, 1989).

Many investigators have suggested
that the legal boundary for ocean-fronting
beaches should not be continuously moving
with the seasonal changes, but should be
the most landward or "winter" line of mean
high water (Nunez, 1966). Selection of the
"winter" MHW line would be the most
practical to locate and would be the most
protective of public interest by maintaining
maximum public access to the shoreline
(Collins and McGrath, 1989).

In Florida, the ocean-fronting legal
boundary seasonal fluctuation issue was
deliberated upon in State of Florida,
Department of Natural Resources vs Ocean
Hotels, Inc. (State of Florida, 1974) as it
related to locating the MHW line from which
a 50-foot setback was to be determined.
Judge J. R. Knott, upon consideration of all
the options, rendered the following decision:

This court therefore concludes that the winter
and most landward mean high water lne
must be selected as the boundary between
the state and the upland owner. In so doing
the court has had to balance the pubic policy
favoring private littoral ownership against the
public policy of holding the tideland in trust
for the people, where the preservation of a
vital public right is secured with but minimal
effect upon the interests of the upland owner.

A 1966 California Court of Appeal
decision rejected the application of a
continuously moving boundary in People vs
Kent Estate (State of California, 1966).
However, no decision has been rendered as
to what line to use (Collins and McGrath,
1989). More recently, however, Collins and
McGrath (1989) report:

The Attorney General's Office in California
has offered its informal opinion that, if
squarely faced with the issue, California
courts would follow the reasoning in the
Forida case and adopt the 'winter and most
landward line of mean high tide' as the legal

boundary between public tidelands and
private uplands ... (it should be understood
that such a boundary, while relatively stable,
would not be permanently fixed but would be
ambulatory to the extent there occurs long-
term accretion or erosion).

Collins and McGrath also discuss
special issues such as shore and coastal
hardening structures, artificially induced
accretion of sand, etc., and their work is
highly recommended for further reading.

However, no formal legal adoption of
the littoral MHW boundary has found nation-
wide acceptance. This is symptomatic of
mankind's tendency to give credence to
codes of anthropic conduct through the
LawsofMan (published in local codes, state
statutes, and federal regulations, etc.) but to
essentially ignore the environment and how
it works through the Laws of Nature
(published in scientific papers and journals).
Until a balance is more nearly achieved, we
shall continue to exacerbate the
environmental crisis that has befallen us all.
The results of this paper provide for one
small aspect of the behavior of nature an
opportunity to achieve a balance between
the two sets of laws.

Long-Term Shorelne Changes

The initial motivation to investigate
this subject was the development of a
methodology to analyze and assess long-
term shoreline changes. Quantitative
behavior of long-term shoreline change to
assess coastal stability is best accomplished
using actual historical surveys. In Florida, as
many surveys as possible are located for the
period from about 1850 to present (aerial
photography is used where an historical
hiatus occurs), usually resulting in from 8 to
14 points to represent the historical shoreline
position (Balsillie, 1985a, 1985b; Balsillie
and Moore, 1985; Balsillie and others,
1986). These data are assessed alongshore
at a spacing of approximately 300 m.
Hence, historical change rate analysis

FLORIDA GEOLOGICAL SURVEY

requires both a temporal
component and a spatial
component.

analytical
analytical

Of the numerical methods available to
analyze such data, many can actually
magnify the uncertainty and/or error
associated with the final results of an
involved computational approach. Caution
with respect to this aspect of analysis
cannot be over emphasized. In fact, the
topic is so important that a series of
standard equations for assessing the
propagation of error in computing have been
provided in the Appendix.

The nature of historical shoreline
location data is such that there is associated
error and variability. Surveying error
includes inherent closure errors, error due to
older technologies, and non-adjustment error
for more recent vertical and horizontal epoch
readjustments. Survey nets established for
county surveys may not precisely relate to
adjacent county nets as they would in a
state-wide net. Long-term sea level
changes, though slight, affect long-term
shoreline changes. These sources of error

may be called map-source errors
after Demirpolat and others
(1989), for which a magnitude of
9 to 15 m may be appropriate
(Demirpolat and others, 1989).
Interpretive plotting of errors of
shoreline location (depending on
data concentration) on original
survey maps must be assumed,
especially for older maps.
Present digitizing technology
results in an error of 3 to 4 m
(Demirpolat and others, 1989).

Except for recent
technologies, magnitudes of
errors for examples suggested
above are not known with
certainty in the majority of cases. I
Even so, it can be envisioned that
they are of sufficiently large s

300

200

100

magnitude that we must keep the number of
computational steps to a minimum in order
to minimize the propagation of error in
computing (bear in mind that in addition to
the temporal analytical component a spatial
component remains, which further increases
analytical computation).

The "bottom line" is that we need to
use the most appropriate and
computationally simple analytical
methodology available. The most
appropriate statistical analytical tool is
undoubtedly &end analysis which already
includes measures of determining the
associated error or variability. In addition,
what we might learn and quantify about
nature's own systematic variability can be
used to our advantage both in terms of
assessing the acceptability of data, and as
an analytical tool. Such is the usefulness of
horizontal seasonal shoreline change.

An example of temporal analysis is
illustrated in Figure 12 for a locality about
2.7 kilometers south of a major inlet on the
east coast of Florida. Equation (1) was
evaluated using the appropriate wave data of

a: -6.25 m/yr c: -0.45 m/yr
b: +110 m/yr d: +1.64 m/yr
Artificial Nourishment Began;
-t
SJetty Construction Began- N
- Inlet Artificially Cut

-,..-- "-

i- "^ i -

1900

2000

1950
Year

Figure 12. Example of long-term shoreline change rate
solid lines) temporal analysis using seasonal shoreline
;hift data (dashed lines); see text for explanation.

SPECIAL PUBLICATION NO. 43

Thompson (1977) and tidal data from
Balsillie (1987a). To the result, one standard
deviation was added to yield a predicted
seasonal variability measure of 50.5 m.
Starting with the most recent data and
moving back in time, regression techniques
are used to determine a trend line (solid line
in Figure 12) about which plus and minus
one-half the seasonal variability measure is
affixed in the vertical direction (dashed lines
in Figure 12). The slope of the trend line of
the time series is the rate of erosion or
accretion (a zero slope or horizontal line
represents stability). Now the seasonal
variability measure becomes a valuable asset
towards identifying spurious data or long-
term change segments in shoreline behavior.
For instance, if a point lies outside the
seasonal variability envelop in the middle of
segment d, one would conclude that either
seasonal variability was extreme for that
year (for which there are undoubtedly no
records) or the survey was made
immediately following extreme event impact
(either storm tide or wave event for which
there are probably no records). In either
case, we have reason to not include the data
point in our analysis, since there are
sufficient data points for the segment to
suggest a strong trend. Interactively, trends
in segment d at localities up- and down-
coast can be used to verify such a trend in
the spatial component of the change rate
analysis.

We also can use historical information
about the area to assist in analysis. For
instance, we know that the inlet was
artificially constructed in 1951, and jetty
construction began in 1953. Furthermore,
artificial nourishment south of the inlet began
in 1974. Each of these events is coincident
with a new episode in shoreline behavior,
and may be verified with similar analyses at
nearby up- and down-coast sites. Note that
there are too few data points to quantify the
shoreline change trend for segment c; either
additional data points are required or
verification/readjustment from analyses at

nearby adjacent sites are required to assure
quantification of representative shoreline
change.

Project Design and
Performance Assessment

Both long-term changes and extreme
event impacts have long been considered in
assessing coastal development design
activities (until recently the former has by-
and-large been qualitative). In proper order,
long-term changes should first be
determined, followed by the design extreme
event impact. The first determination allows
for prudent siting of the development
activity, and the second for responsible
structural design solutions to withstand
storm tide, wave, and erosion event impacts.
However, without knowledge of seasonal
shaoree sifts for a particular locality,
uncertainty will be introduced into such
assessment. Following long-term
determination of where the shore will be
(e.g., say, a standard 30-year mortgage
period) it would, for instance, be prudent to
adjust the beach width of a given
topographic survey to its narrowest expected
seasonal dimension, then to apply extreme
event analyses. Considering the significant
outlay of resources for beach nourishment
projects, it would seem appropriate to
consider seasonal shoreline variability both in
project design and in assessing performance.

The controversial issue of whether
coastal hardening structures (e.g., seawalls,
bulkheads, revetments) promote the erosion
of beaches fronting them, is one of complex
proportions. Without being long-winded, the
issue might finally be resolved by inspecting
long-term shoreline location data. Again,
however, seasonal shoreline shifts would
require quantification and application in the
analysis. At the very least, methodology
developed here would allow one to
determine if seasonal shoreline change was
of significant proportions that it should be
considered in design applications. Using

FLORIDA GEOLOGICAL SURVEY

known wave, tidal, and sedimentological
data it would be a straightforward task to
compile such results, particularly in Florida
where the coast has been monumented.

CONCLUDING REMARKS

For much of our shoreline, seasonal
shifts in shoreline position occur. While the
phenomenon has been the subject of
considerable concern, no specific
quantification has, until now, surfaced.

It has been noted earlier that some
shorelines (e.g., east-west trending shores)
apparently do not exhibit seasonal shifts.
This may be due to storm wave impacts
occurring in groups for periods of less than
monthly and/or due to climatic change
affecting storm front azimuths relative to
shoreline azimuths. Correlation might be
attained by selecting most and least active
monthly averages, or by applying moment
statistics.

An historical study of Gulf of Mexico
storm wave and direct coastal impacts, as
Dolan and others (1988) conducted for the
Atlantic Ocean off North Carolina, is needed.
Results of such a study would shed light on
the regional behavior of east-west trending
shores of the central Gulf, and would also be
applicable to the more nearly north-south
trending shores of the lower Gulf coasts of
Florida and Texas.

While the methodology for assessing
average seasonal shoreline and beach width
variability can be used for a variety of
important applications, the developments
presented here are a first appraisal. The
intent of this work is to invoke interest in the
subject and to act as a plea for additional
data on which to test existing predictive
methodology and/or develop more exacting
technology. For instance, while this work
treats straight ocean-fronting beaches
composed of sand, seasonal changes of
pocket beaches might be treated by

including seasonal wave approach angle
changes, and data for beaches composed of
sand and pebbles (i.e., a very large standard
deviation) would help in understanding the
role of the sedimentologic property element.

ACKNOWLEDGEMENTS

Review of an earlier manuscript
leading to this paper provided significant
guidance, and those comments and
suggestions from Paul T. O'Hargan, Joe W.
Johnson, George M. Cole, Alan W.
Niedoroda, and Gerald M. Ward are gratefully
acknowledged. James R. Allen and Ralph R.
Clark, and William F. Tanner reviewed the
present form of the paper and made several
valuable suggestions. Special thanks are
also extended to Kenneth Campbell, Ed
Lane,Jacqueline M. Lloyd, Frank Rupert, and
Thomas M. Scott of the Florida Geological
Survey for the many useful editorial
comments.

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Science, v. 238, p. 272-285.

Shoemyen, A. H., Floyd, S. S., and Drexel,
L. L., 1988, 1988 Florida Statistical
Abstract, University Presses of
Florida, Gainesville, FL.

Silberman, L. Z., 1979, A sedimentological
study of the Gulf beaches of Sanibel
and Captiva Islands, Florida: M. S.
Thesis, Geology Department, Florida
State University, Tallahassee, Fl,
132 p.

Sonu C. J., and Russell, R. J., 1966,
Topographic changes in the surf
zone profile: Proceedings of the
10th Conference on Coastal
Engineering, p. 504-524.

State of California, 1966, People vs Kent
Estate: California Appellate Reports
(2d), p. 156, 160.

State of Florida, 1974, Department of
Natural Resources vs Ocean Hotels,
Inc.: Circuit Court of the 15th
Judicial Circuit of Florida, Case No.
78 75 CA (L) 01 Knott.

Strahler, A. N., 1964, Tidal cycle changes in
an equilibrium beach, Sandy Hook,
New Jersey: Columbia University,
Department of Geology, Office of
Naval Research Technical Report No.
4, 51 p.

Sunamura, T., and Horikawa, K., 1974,
Two-dimensional beach
transformation due to waves: in
Proceedings, 14th International
Coastal Engineering Conference, p.
920-938.

SPECIAL PUBLICATION NO. 43

Swanson, R. L., 1974, Variability of tidal
datums and accuracy determining
datums from short series of
observations: U. S. Department of
Commerce, National Oceanic and
Atmospheric Administration, National
Ocean Service, NOAA Technical
Report NOS 64, 41 p.

Szuwalski, A., 1970, Littoral Environment
Observation Program in California,
preliminary report, February-
December 1968: Coastal
Engineering Research Center
Miscellaneous Paper No. 2-70, 242
p.

Tanner, W. F., 1991, The relationship
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in Proceedings, Ninth Symposium of
Coastal Sedimentology: Geology
Department, Florida State University,
Tallahassee, FL, p. 41-50.

1992, 3000 years of sea level
change: Bulletin of the American
Meteorological Society, v. 73, p.
297-303.

Thorn, B. G., and Bowman, G. M., 1980,
Beach erosion accretion at two
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Coastal Engineering Conference, v.
1, p. 934-945.

Thompson, E. F., 1977, Wave climate at
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No. 77-1, 364 p.

Thompson, W. C., 1987, Seasonal
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Shore and Beach, v. 55, p. 67-70.

Trask, P. D., 1956, Changes in configuration
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Pipe profile data and wave
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1121.

FLORIDA GEOLOGICAL SURVEY

Wentworth, C. K., 1922, A scale of grade
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sediments: Journal of Geology, v.
30, p. 377-392.

Ziegler, J. M., and Tuttle, S. D., 1961,
Beach changes based on daily
measurements of four Cape Cod
beaches: Journal of Geology, v. 69,
p. 583-599.

Zimmerman, M. S., and Bokuniewicz, H. J.,
1987, Multi-year beach response
along the south shore of Long Island,
New York: Shore and Beach, v. 55,
p. 3-8.

APPENDIX: PROPAGATION OF
ERRORS IN COMPUTING

(compiled from formulations in Barry, 1978)

Where R is the result of some numerical
operation (e.g., addition, subtraction,
multiplication, division, power function,
average, etc.) for measured quantities N,,
N2, N3,...,N,, each with associated
measurement errors E,, E2, E3, ...,E,,
respectively, then the total error E., is
applied as:

R E,,o

where E,, is determined according to:

ADDITION OR SUBTRACTION

AVERAGE

EAV

CONSTANT ERROR

where E = E, = E2 = E, =...= E.

POWER

where (R + E,)" = (N, + E,)m

PRODUCT OR QUOTIENT

= E 4, ... )+ 2
14 Nj IY N, N"

where (R + E,)'1" = (N, + E,)'/"
E = m-' E, 1

ROOT

SPECIAL PUBLICATION NO. 43

OPEN-OCEAN WATER LEVEL DATUM PLANES:

USE AND MISUSE IN COASTAL APPLICATIONS

by

James H. Balsillie, P. G. No. 167

ABSTRACT

Swanson (1974) notes that tidal datum planes "... are planes of reference derived from the rise
and fall of the oceanic tide". There are numerous tidal datum planes. Commonly used datums
in the United States include the planes of mean higher high water (MHHW), mean high water
(MHW), mem tideievf (MTL), mm i w eew f (MSL), men ew water (MLW), and mnn power
low water (MLLW). Each datum is defined for a specific purpose or to help describe some tidal
phenomenon. For instance, MHW high water datums have been specified by cartographers in
some states (e.g., Florida) as a boundary of property ownership. Low water datum planes
have been used as a chart datum because it is a conservative measure of water depth and,
hence, provides a factor of safety in navigation. High water tidal stages have historically been
of importance because they identified when sailors should report for duty when "flood tide"
conditions were favorable for ocean-going craft to leave port, safely navigate treacherous ebb
tidal shoals, and put to sea. Not only do tidal datum specifications vary geographically based
on local to regional conditions for purposes of boundary delineation, cartographic planes, design
of coastal structures, and land use designations, etc., but they have changed historically as
well. Moreover, given ongoing technological advancements (e.g., computer-related capabilities
including the advent of the personal computer), how we approach these data numerically is
highly important from a data management viewpoint.

INTRODUCTION

Tide gauges are usually located in water
bodies connected to the oceans, such as
estuaries and rivers, and may even be used to
record seiches such as those occurring in the
Great Lakes. Here, however, the concem is
with open ocean tides. Open ocean tide
gauges are defined "... as those gauges sited
directly upon the open ocean nearshore
waters and subject to the influence of ocean
processes, excluding those under the
influence of inlet hydrodynamics..." (Balsillie
and others, 1987a, 1987b, 1987c). The
latter constraint in the definition is included
even though it is difficult to determine the
extent of influence from inlet to inlet.

Open ocean tidal datum applications in

Florida are problematic because there are a
limited number of gauging stations to
represent astronomical tidal phenomena.
While it has been standard practice to
linearly interpolate open ocean tidal datums
between gauges, such an approach is not
recommended should the gauges be spaced
further apart than about 6.2 miles (Balsillie
and others, 1987a). Of the 33 currently
available open ocean gauges in Florida (Table
1), only three pairs of stations meet this
constraint. In fact, the average distance
between Florida open ocean tide gauges is
27.4 miles. Ostensibly, the 6.2-mile
constraint is recommended since
concurrently similar tidal stage datum
elevations can vary significantly over
segments of the coastline when this distance

FLORIDA GEOLOGICAL SURVEY

Table 1. Tidal Datums and Ranges for Open Coast Gauges of Coastal Florida
(Updated in 1992 after Balsie, Caden and Watters, 1987a, 1987b, 1987c).

Open tate Plane MHHW MHW MTL MLW MLLW
Coast Coinate MTR X
Station Name oast
Gauge Easting Northing (Feet) (Miles)
I. D. t) (et) (Ft. NOVO)
(Feet) (Feat)

FLORIDA EAST COAST

Femandina Beach 0061 362649.81 2287406.62 3.52 3.11 0.25 -2.61 -- 5.72 5.831
Little Tabot Island 0194 372355.76 2216450.20 3.60 3.30 0.55 -2.19 -2.35 5.49 19.753
Jacksonville Beach 0291 377952.02 2163090.54 3.25 2.94 0.39 -2.17 -2.33 5.11 30.150
St. Augustine Beach 0587 417053-67 2008422.56 2.73 2.48 0.15 -2.17 -2.33 4.62 60.491
Daytona Beach 1020 498405.18 1779242.33 2.52 227 0.19 -1.88 -2.06 4.15 106.820
Daytona Beach Shores 1120 511704.59 1749549.40 2.44 2.06 0.07 -1.89 -2.06 3.98 112.990
Patrick Air Force Base 1727 628785.91 1421930.52 2.27 2.09 0.32 -1.45 -1.61 3.54 185.030
Eau Gallie Beach 1804 619782.34 1383121.82 2.25 2.07 0.33 -1.33 -1.49 3.40 191.810
Vero Beach 2105 707153-65 1213218.30 2.01 1.89 0.19 -1_51 -1.67 3.40 227-560
Lake Worth Pier 2670 815854.41 829171.49 1.93 1.87 0.47 -0.93 -1.10 2.80 304.910
Hillsboro Inlet 2862 800981.65 700015.89 1.79 1.73 0.43 -0.87 -1.03 2.60 329-700
Lauderdale-by-the-Sea 2899 797331.41 675151.18 1.99 1.93 0.63 -0.67 -0.83 2.60 334.580
North Miami Beach 3050 789219.52 581194.67 1.77 1.71 0.46 -0.79 -0.96 2.50 352.520
Miami Beach (City Pier) 3170 785773.29 522409.95 1.76 1.67 0.42 -0.84 -1.00 2.51 363.780

NOTE: X is the shoreline distance in miles south of the center line of St. Marys Entrance
Channel (origin: nothing = 2317969.50 feet: eating = 366516.31 feet).

FLORIDA LOWER GULF COAST

Bay Port 7151 291286.83 1527111.33 2.31 1.88 070 -0.48 -0.97 2.36 4.472
Howard Park 6904 241667.70 1389244.60 1.87 1.50 0.43 -0.64 -1.19 2.14 33.555
Clearwater 6724 231561.35 1325079.09 1.62 129 0.33 -0.64 -1.17 1.88 46.634
Indian Rocks Beach Pier 6623 224898.87 1295432.55 1.50 1.13 0.25 -0.63 -1.15 1 76 52.650
St. Petersburg Beach 6430 261046.14 1218243.36 1.52 1.16 0-42 -0.32 -0.83 1.48 69.560
Anna Maria 6243 268746.05 1150335.15 1.52 1.20 0.45 -0.29 -0.76 1.49 83.284
Venice Airport 5858 352475.83 995445.81 1.35 1.07 0.36 -0.35 -0.84 1.42 117.918
Captiva Island, South 5383 351707.10 779777.00 1.52 1.27 0.42 -0.42 -0.94 1.69 163.464
Naples 5110 563431.54 652958.84 1.81 1.55 0.50 -0.54 -1.17 2.09 205.226
Marco Island 4967 589299.92 572441.43 1.96 1.71 0.56 -0.59 -1.20 2.30 222.015

NOTES: 1- X is the shoreline distance in miles south of an arbitrary location in Hemando County, FL.
(origin: nothing = 1551271.53 leet; eating = 287952.53 teet).
2. State Plane Coordinates and distances are based on Zone 3 transformations where necessary.

FLORIDA NORTHWEST PANHANDLE COAST

Dauphin Island 5180 472269.39 871380.81 0.87 0.82 0.26 -0.29 -0.34 1.11 -33.347
Gulf Shores 1269 467866.88 999712.52 1.20 1.13 0.50 -0.12 -0.18 1.25 -9.228
Navare Beach 9678 508373.97 1254261.65 1.20 1.13 0.50 -0.14 -0,21 1.27 39.737
Panama City Beach 9189 434604.55 1579274.67 125 1.18 0.54 -0.09 -0.14 1.27 104.489
St. Andrews Park 9141 414248.96 161065122 1.16 1.06 0.47 -0.12 -0.23 1.18 111.489
Mexico Beach 8995 346061.53 1706517.15 1-06 1.00 0.41 -0.17 -0.22 1.17 134.479
Cape San Bias 8942 244076.07 1726862.58 1.01 0.99 0.30 -0.38 -0.38 1.37 162.615
Alligator Point 8261 325491.24 2035385.12 1.73 1.49 0.53 -0.44 -1.02 1.93 232.302
Bald Point 8237 344903.70 2050145.99 2.09 1 76 0.62 -0.52 -0.98 2.28 238.633

NOTE: X is the shoreline distance in miles east of the Alabama/Florida border
(origin: nothing = 478050.00 feet: easing = 1047360-00 feet).

GENERAL NOTES:
1. Tidal datums are referenced to NGVD of 1929.
2. Source of information Bureau of Survey and Mapping. Division of State Lands,
Florida Department of Environmental Protection, for the National Tidal Datum Epoch of 1960-1978.
3. MLLW = mean lower low water MLW = mean low water MTL = mean tide level, which along the open coast = MSL = mean sea level;
MHW = mean high water: MHHW = mean higher high water: MTR = mean range of tide (/ie.. MTR = MHW MLW).

SPECIAL PUBLICATION NO. 43

is exceeded. In addition, it was found that
linear interpolation led to results that simply
do not reflect the natural behavior of coastal
processes. Hence, in 1987, a non-linear nth-
order polynomial numerical methodology
was introduced and utilized to determine
quantitatively open ocean tidal datums for a
significant portion of Florida's ocean-fronting
coasts (Balsillie and others, 1987a, 1987b,
1987c). Updated results (Balsillie and
others, 1998) are plotted in Figures 1, 2, and
3.

This work is a companion paper to tidal
datums listings for Florida originally
published by Balsillie and others (1987a,
1987b, and 1987c) and updated by Balsillie
and others (1998). It was determined
necessary to undertake the present
compilation because of an increasing number
of misapplications of tidal datums appearing
in the coastal engineering literature. For
example, Foster (1989, 1991), Foster and

Savage (1989a, 1989b), and Schmidt and
others (1993) consistently used MHW as
their vertical reference from which
volumetric beach changes were measured.
Komar (1998) used NGVD (it is assumed
that this is NGVD of 1929, although such is
not stated) but stated that for his site NGVD
"... is approximately equal to mean sea level
...". Lee and others (1998) used NGVD at a
North Carolina coastal location; they did not
state, however, how NGVD departs from
MSL at their site. These exemplify
instances in which tidal datums referencing
can introduce significantly compounded
error. One illustrates other cases where no
explanation detailing how tidal datums are
applied is given, and one cannot be sure if
he or she can have confidence in final
results.

To one extent or another, misapplication
of tidal datums may be due to a lack of
understanding as to how they have been

North

South

100 150 200 250 300 350
Alongshore Distance (statute miles)

Figure 1. Relationship between open coast dial datums and National Geodetic Vertical Datum
of 1929 for the Florida East Coast. Alongshore distance is measured from the center line of
St. Mary's Entrance Channel proceeding south to Cape Florida. (Updated in 1992 after
Balsillie and others, 1987a).

--* -

FLORIDA GEOLOGICAL SURVEY

North

3.5
a-

0 50 100 150
Alongshore Distance (statute miles)

Figure 2. Relationship between open coast tidal datums and National Geodetic Vertical Datum
of 1929 for the Florida Lower Gulf Coast. Alongshore distance is measured from north to
south with the origin located at the north end of Pinellas County (i.e., north end of Honeymoon
Island) and terminating to the south at Caxambas Pass. (Updated in 1992 after Balsillie and
others, 1987b).
West East

-0.

-1.

_-i

3*---------------
.5

,5 -__ __ I __------------------
5

o ML

5
21

-3
5

__ L __ I __ __ _

0i 0 50
Alongshore

100 150
Distance (statute

miles)

Figure 3. Relationship between open coast tidal datums and National Geodetic Vertical Datum
of 1929 for the Northwest Panhandle Gulf Coast of Florida. Alongshore distance is measured
from the Florida-Alabama border east to Ochlockonee River Entrance. (Updated after Balsillie
and others, 1987c).

South

SPECIAL PUBLICATION NO. 43

established, and what they represent. The
first part of this work, therefore, discusses
the history of tidal datums determination and
definition in U. S. coastal waters.

Guidance illustrating proper tidal datums
applications for coastal scientists and
engineers is available for important basic
tidal datums applications (e.g., Cole, 1983,
1991, 1997; Pugh, 1987; Lyles and others,
1988; Brown and others, 1995; Gorman and
others, 1998; Stumpf and Haines, 1998).
For other specific cases it is absent. Verbal
communications by a few professionals
reach only a small audience. Even then, the
latter often results in a blank stare, leaving
the instructor with the message that the
explanation was not comprehended by the
informant, that he or she has predetermined
that it is not important, or that the informant
has already predetermined just what is
proper. The author has, therefore, in the
latter portion of this work presented a series
of selected examples and discussion about
tidal datums applications. At the outset, one
needs to understand that the surveying
profession, in large part, is concerned with
the management of error and variability
associated with horizontal and vertical
control. It is often the case that one is not
convinced by simple directive that there is a
proper methodology, so evidenced by recent
improper uses of datum applications in
coastal engineering works cited above. This
occurs because there isnothing to convince
one that the methodology is better or best at
reducing error or variability. Therefore, the
author has opted to present a series of
common improper tidal datums applications
and to demonstrate, relative to the proper
application, just why, numerically, they are
inappropriate.

INLETS/OUTLETS AND
THE ASTRONOMICAL TIDE

The preceding definition of open ocean
tides excludes the influence of inlets (perhaps
more appropriately termed outlets after Carter,

1988, p. 470). Hence, exclusion of inlets
might be an oversight, particularly in view of
the current inlet management effort
undertaken by the State. At a most basic
level, the classification of inlets is well
known depending upon the effect of
astronomical tides relative to volume of
fluvial discharge (e.g., van de Kreeke, 1992).
In fact, for many inlets, selection of the
proper datum plane assists in providing a
least equivocal representative design water
reference level. Hence, a section on inlets
as they relate to astronomical tides in Florida
is herein developed.

WATER LEVEL DATUM PLANES

In endeavors conceding hydraulic
phenomena with a free fluid surface, many
practitioners have lost perspective in selection
of the reference fluid plane across which force
elements propagate, in both the prototypical
setting and the natural environment. Given
this assertion, perhaps it would be appropriate
to review the basics of historical development
of tidal datum plane quantification that has
withstood the practicable tests of time.

The first recorded effort of geodetic
leveling in the United States began in 1856-
57. During ensuing years surveying control
become better. As chronicled by Schomaker
(1981), by the first quarter of this century:

After the previous period of
comparatively short intervals between
adjustments, 17 years elapsed before
the network was adjusted again. In the
meantime, it had become more
extensive and complex, and included
many more sea-level connections. The
General Adjustment of 1929
incorporated 75,159 km of leveling in
the United States and, for the first time,
31,565 km of leveling in Canada. The
U.S. and Canadian networks were
connected by 24 ties between Calais,
Me./Brunswick, New Brunswick; and
Blaine Wash./ Colebrook, British
Columbia. A fixed elevation of zero

FLORIDA GEOLOGICAL SURVEY

was assigned to the points on mean sea
level determined at the following 26 tide
stations.

Father Point, Quebec
Halifax, Nova Scotia
Yarmouth, Nova Scotia
Portland, Me.
Boston, Mass.
Perth Amboy, N.J.'
Atlantic City, N.J.
Baltimore, Md.
Annapolis, Md.
Old Point Comfort, Va.
Norfolk, Va.
Brunswick, Ga.

Femandina, Fla.

'There was no tide

St. Augustine, Fla.
Cedar Keys, Fa.
Pensacola, Fla.
Biloxi, Miss.
Galveston, Tex.
San Diego, Calif.
San Pedro, Calif.
San Francisco, Calif.
Fort Stevens, Ore.
Seattle, Wash.
Anacortes, Wash.
Vancouver,
British Columbia
Prince Rupert,
British Columbia

station at Perth

Amboy, but the elevation of a bench mark at
Perth Amboy was established by leveling
from the tide station at Sandy Hook.

The 1929 adjustment provided the
basis for the definition of elevations
throughout the national network as itexisted
in 1929, and the resulting datum is still used
today.

The elevation adjustment of 1929 was
referred to as the "Sea Level Datum of 1929",
although it commonly became known as the
"Mean Sea Level". In coastal work, however,
there are two standard Design Water Levels
(DWLs) that are applied. These and their
definitions (Galvin, 1969) are:

Mean Water Level (MWL) the time-averaged
water level in the presence of waves, and

Still Water Level (SWL) the time-averaged
water level that would exist if the waves are
stopped but the astronomical tide and storm
surge are maintained.

These water levels (i.e., MWL and SWL)
apply for any length of time over which a
field study or experiment is conducted, while
Mean Sea Level and other tidal datums are
determined as an average of measurements
made over the 19-year National Tidal Datum

Epoch (i.e., the Metonic cycle; shorter series
are appropriately named, e.g., Monthly Mean
Sea Level, etc.). It was not until 1973 that
the confusion over the Sea Level Datum or
"Mean Sea Level" as it popularly came to be
known and Mean Water Level was resolved
by assigning the more appropriate name of
"National Geodetic Vertical Datum of 1929"
(NGVD) to replace "Sea Level Datum of
1929". NGVD of 1929 is additionally
defined (Harris, 1981) as a fixed reference
adopted as a standard geodetic datum for
elevations determined by leveling. It does
not take into account the changing stands of
sea level. Because there are many variables
affecting sea level, and because the geodetic
datum represents a best fit over a broad
area, the relationship between the geodetic
datum and local mean sea level is not
consistent from one location to another in
either time or space. For this reason NGVD
should not be confused with mean sea level,
even though it has always been defined by a
mean sea level (Schomaker, 1981).

The various North American tidal datum
planes are defined (e.g., Marmer, 1951;
Swanson, 1974; U. S. Department of
Commerce, 1976; Anonymous, 1978;
Harris, 1981; Hicks, 1984) as follows:

National Tidal Datum Epoch the specific 19-
year period adopted by the National Ocean
Service as the official time segment over
which tide observations are taken and reduced
to obtain mean values for tidal datums. It is
necessary for standardization because of
periodic and apparent secular trends in sea
level. It is reviewed annually for possible
revision and must be actively considered for
revision every 25 years.

Mean Higher High Water (MHHW) the
average of the higher high water heights of
each tidal day observed over the National
Tidal Datum Epoch.

Mean High Water (MHW) the average of all
the high water heights observed over the

SPECIAL PUBLICATION NO. 43

National Tidal Datum Epoch.

Mean Sea Level (MSL) the arithmetic mean
of hourly heights observed over the National
Tidal Datum Epoch. Shorter series are
specified in the name; e.g., monthly mean
sea level and yearly mean sea level.

Mean Tide Level (MTL) a plane midway
between Mean High Water and Mean Low
Water that may also be calculated as the
arithmetic mean of Mean High Water and
Mean Low Water. MTL and MSL planes
approximate each other along the open coast
(Swanson, 1974, p. 4).

Mean Low Water (MWL) the average of all
the low water heights observed over the
National Tidal Datum Epoch.

Mean Lower Low Water (MLLW) the
average of the lower low water heights of
each tidal day observed over the National
Tidal Datum Epoch.

Mean astronomical tide elevations exhibit
cyclic seasonal variability (Marmer, 1951;
Swanson, 1974; Harris, 1981) and are
included in tide predictions. Marmer (1951)
notes that seasonal variation in terms of
monthly mean sea level for the U. S. can be
as much as one foot. Based on the many
years of monthly data, researchers (Marmer,
1951; Harris, 1981) note slight variations in
the seasonal cycle from year-to-year, but
also recognize the periodicity in peaks and
troughs over the years. For much of our
coast, lower mean sea levels occur during
the winter months and higher mean sea
levels during the fall. Harris (1981)
inspected the record to determine if storm
and hurricane occurrence was in any way
responsible for the seasonal change, but
found "... no systematic variability". Galvin
(1988) reports that seasonal mean sea level
changes are not completely understood, but
suggests that there appears to be two
primary causes for lower winter mean tide
levels for the U. S. east coast: 1) strong

northwest winter winds blow the water
away from shore, and 2) water contracts as
it cools. He notes that winds are more
important in shallow water where tide
gauges are located, but that contraction
becomes important in deeper waters.
Swanson (1974) also notes "... seasonal
changes resulting from changes in direct
barometric pressure, steric levels, river
discharge, and wind affect the monthly
variability." Cole (1997) notes that seasonal
variation in tides is usually attributed to two
harmonic constituents: one with a period of
one year termed the solar annual tidal
constituent, and the other with a period of
six months termed the solar semiannual
constituent. Some consider these to be
meteoroligical in nature, rather than
astronomic. However, because the root
cause of cyclic seasonal weather is the
changing declination of the sun, they should
more nearly be astronomical in origin.
Harmonic analysis of the annual tidal record
can easily determine the amplitude and
phase of each of these constituents, thereby
providing a mathematical definition of the
seasonal variation. (George M. Cole, personal
communications.) Shorter-term changes
occur bi-weekly and monthly; longer-term
changes occur in the relative levels of land
and sea that are of eustatic or isostatic
origins (e.g., Embleton, 1982). It is
apparent, therefore, that there is natural
variability associated with any average
representation of tidal datums. Given these
natural insensitivities associated with
averages, it is important that we do not
exacerbate them through improper
manifestations of our own making when
applying tidal datums as references.

At this point it is necessary to define
certain terms. If one is interested in merely
referencing a vertical distance without a
requirement of spatial comparability, the
result is termed a monegistic appecation.
That is, the result of the application is good
only for that particular location. If, however,
in addition to a vertical datum, one has a

FLORIDA GEOLOGICAL SURVEY

need that the resulting application will have
spatial comparability (i.e., it can be
compared to the same application at any
other site), the result is a synergisc
appliatin. We shall discuss this latter class
of application first.

SYNERGISTIC TIDAL
DATUM PLANE APPUCATIONS

It has been widely recognized, as
demonstrated in the introduction to this paper,
that selection of the proper tidal datum
depends upon the purpose to which it is to be
applied. The main purpose of this work is to
determine the proper tidal datum for use in
coastal science and engineering for
referencing littoral force and response
elements. Force elements include
astronomical tides, storm tides, nearshore
currents, waves, etc. Response elements
include extreme event beach and coast
erosion, foreshore slope changes, long-term
shoreline changes, seasonal shoreline
changes, etc. It became apparent during the
course of preparation of this paper that
determination of the proper datum plane is
probably best accomplished by discussing
application/use examples.

EXTREME EVENT IMPACT

From the preceding description of tidal
datum planes we must, from the scientific
perspective, be quite careful in selecting a
reference water level from which we define
such response elements as beach and coast
erosion due to extreme event impact, and
such force elements as the peak combined
storm tide accompanying extreme events that,
in part, induces such erosion. As noted
previously, water level datum planes include
certain insensitivities regardless of the
rigorous nature of statistical methods applied.
It is necessary that we do not further
exacerbate these insensitivities, creating
additional variability and error through
selection of improper reference datums.

As an example, suppose that we are
analyzing and interpreting profile data to
determine volumetric erosion of sandy
beaches and coasts due to extreme event
impact. Further, let us select as our reference
water level datum Mean High Water, MHW.
That is, we shall assess erosion volumes
above MHW to an upland point that must be
carefully deliberated depending upon whether
the coast was non-flooded (interpretations are
normally straightforward) or flooded and/or
breached (interpretations can be problematic)
as discussed by Balsillie (1985b, 1986). It
must be recognized that MHW can be
assigned the status of a signature value for a
particular locality, representing its National
Tidal Datum Epoch. This assessment can be
levied because MHW can change significantly
from locality-to-locality. For instance, in
Florida MHW varies from +3.12 feet MSL (or
+3.36 feet NGVD; Balsillie and others, 1987a)
along the northern portion of Nassau County
on the Atlantic east coast, to +0.66 feet MSL
(or +0.90 feet NGVD; Balsillie and others,
1987c) along the westem portion of Franklin
County on the northwestern panhandle Gulf of
Mexico coast of Florida. This embodies a
potential maximum difference of almost 2.5
feet in MHW elevation about the State of
Florida. Suppose that for the above two
areas, profile conditions are comparable.
Furthermore, suppose that extreme events
embodying precisely the same magnitudes
and characteristics producing identical force
elements impacted the two areas, resulting in
identical response elements, that is, the same
erosion volumes (i.e., the area above the
dashed lines and below the solid lines of
Figure 4). If, however, we reference the
erosion volumes to MHW (shaded areas) as
illustrated in Figure 4, 8.12 cubic yards of
sand per foot are eroded above MHW along
the northern portion of Amelia Island, 33 per
cent less than the 12.05 cubic yards of sand
per foot eroded above MHW along western
St. George Island. It becomes quite clear,
therefore, that erosion volumes around the
state cannot be compared using MHW, since
the MHW base elevation is not only

dsz~e

SPECIAL PUBLICATION NO. 43

-120 -100 *80 40 40 -20 0 20 40 60
instance from Oh MSL 9Inrcpt (tot)
Figure 4. Erosion volumes Q, above MHW for identical
proles impacted by identical storm events, but with
different local MHW planes.

geographically variable, but significantly so. term fc
One will note further that, for other North Notwithst
American MHW datums (see Table 2), the convention
problem can become even further impact, th
exaggerated. In fact. it has been to long
demonstrated that MSL is the best datum application
from which to reference erosion volumes; event imf
"... at the seaward extremity of the post- event imp
storm profile, some material of the seaward beach an
sink (also including some degree of post- transcend
storm beach recovery) may reside above That is, th
MSL (determined to be about 6% of the and hurri
seaward sink volume from 245 analyzed constraint
profile pairs), the analytical method is fairly the beach
unbiased since it is applied equally to all foreshore
profiles investigated" (Balsillie, 1986). slope; se
Seaward datums or depth of profile closure impose li
are not suitable references, if only because littoral
survey response is slow compared to the physiogra
response of subaqueous sand-sized more neai
sediments in the energetic force element surf most imp
environment (e.g., Pugh, 1987; Lyles and foreshore
others, 1988). discussion
synergist
It becomes apparent, therefore, that namely, s

12 -
lo Case A: Northrn Amela Iwend,
\ Nssau County, MHW = +3.12 ft MSL
8
SQe = -4.12 yd3/ft

2
6..W

a \"-: Cafue Wstern St. George keand,
6 ,. Franklin Cowrnty, MHW = +0.SS ft MSL
0. =-12.05 yd3/ft
4 ... --' --
4--

2 -- ':.
-2
JI t

I I I I l I

MHW is not the proper reference
water level datum to apply for
erosion volumes. It also becomes
apparent that it is not proper to
use the datum for reference for
such a force element as the peak
combined storm tide. Similar
logic results in the conclusion
that use of the MHHW, MLW,
and MLLW datum planes would
also be improper. It should, in
fact, be clear that MSL (or MTL)
is the only tidal datum that is to
be used for reference.

LONGER-TERM BEACH
RESPONSES

It is clear why the MSL datum
is the desired convention to apply
for extreme event impacts to which
force and response elements are
to be referenced. MSL datum
should also be applied to longer-
)rce and beach responses.
ending the need for a standardized
n already required for extreme event
ere is sound reasoning that it applies
r-term scenarios, although, such
n is more subtle than for the extreme
)act case. The preceding extreme
'act scenario has dealt with physical
d coast conditions of a sort which
Certain physiographic limitations.
e energetic associated with storms
canes so exceed physical stability
s that individual gradients comprising
:h and coast (e.g., shoreface,
slope, berm(s), dune or bluff stoss
e Figure 5) do not, in themselves,
miting conditions. Under normal
force conditions, however,
phic slope characteristics become
rly a limiting condition. Perhaps the
lortant of these gradients is the
slope, a subject that needs some
n prior to addressing two additional
:ic application/use examples,
seasonal beach changes and long-

*

,I

FLORIDA GEOLOGICAL SURVEY

Table 2. Selected North American Datums and Ranges Referenced to MSL (after Harris,
1981).
Station MHHW MHW NGVD MTL MLW MLLW M
Eastport, ME 9.32 8.88 -0.20 -0.10 -9.01 -9.41 18.20
Portland, ME 4.87 4.45 -0.22 0.00 -4.46 -4.80 8.91
Boston, MA 5.16 4.72 -0.31 -0.15 -4.86 -5.19 9.58
Newport, RI 2.18 1.93 -0.23 +0.15 -1.69 -1.75 3.62
New London, CN 1.48 1.22 -0.43 -0.10 -1.34 -1.45 2.60
Bridgeport, CN 3.61 3.31 -0.54 -0.05 -3.36 -3.52 6.70
Willets Point, NY 3.85 3.59 -0.58 -0.05 -3.58 -3.78 7.10
New York, NY 2.51 2.19 -0.49 +0.05 -2.29 -2.42 4.50
Sandy Hook, NJ 2.66 2.33 -0.51 0.00 -2.34 -2.47 4.60
Breakwater Harbor, DE 2.46 2.04 -0.41 -0.05 -2.08 -2.15 4.10
Reedy Point, DE 3.07 2.73 -0.35 -0.10 -2.77 -2.85 5.51
Baltimore, MD 0.74 0.51 -0.43 -0.03 -0.52 -0.64 1.03
Washington, DC 1.54 1.39 -0.54 0.00 -1.37 -1.42 2.76
Hampton Roads, VA 1.41 1.22 -0.02 +0.03 -1.22 -1.26 2.44
Wilmington, NC 2.26 2.02 -0.38 +0.02 -2.24 -2.33 4.26
Charleston, SC 1.88 2.87 -0.05 +0.21 -2.67 -2.81 5.17
Savannah River Entr. 3.77 3.38 -0.28 -0.15 -3.56 -3.70 6.94
FLORIDA Listed i Table 1.
Mobile, AL 0.73 0.65 -0.05 -0.05 -0.62 -0.70 1.27
Galveston, TX 0.57 0.47 -0.10 -0.05 -0.44 -0.85 0.91
San Diego, CA 2.90 2.11 -0.21 -0.05 -2.09 -3.06 4.10
Los Angeles, CA 2.63 1.91 -0.08 0.00 -1.87 -2.82 3.80
San Francisco, CA 2.59 2.04 +0.06 +0.30 -1.93 -3.14 4.00
Cresent City, CA 3.22 2.56 -0.12 0.00 -2.49 -3.75 5.10
South Beach, OR 3.22 2.56 -0.49 +0.02 -3.09 -4.48 6.30
Seatle, WA 4.83 3.94 -0.35 0.00 -3.75 -6.48 7.60
NOTES:
MTR = Mean range of tide; average value of MTL is -0.01 feet MSL; average value of NGVD (1929) is -0.29 feet MSL;
these stations do not necessarily represent open coast gauging sites.

term beach changes.

The foreshore slope or beach face slope
(Figure 5) is defined by the Share Protecfton
Manual (U. S. Army, 1984) as "... that part
of the shore lying between the crest of the
seaward berm (or upper limit of wave wash
at high tide) and ordinary low water mark,
that is ordinarily traversed by the uprush and
backwash of waves as tides rise and fall."
Komar (1976) elaborates further, stating that
the foreshore slope "... is often nearly

synonymous with beach face but is
commonly more inclusive, containing also
some of the beach profile below the berm
which is normally exposed to the action of
the wave swash." The berm or beach berm
is the "... nearly horizontal part of the beach
or backshore formed by the deposit of
material by wave action ... some beaches
have no berms, others have one or several"
(U. S. Army, 1984). The berm and
foreshore (or beach face) are separated at
the berm crest or berm edge.

SPECIAL PUBLICATION NO. 43

Coastal arag

NeBershor lane
defines oare of nearurote currents
Coast ah or shot& a
BckLheore fteriw Inshore or Shore foce _ffshre
or (extends through breaker Zone
Beoch
Bluff a0ce
or
erpm
^eech^ 8ereaker# _

Cr' of bermat o

Plunge point
Bottom

Figure 5. Beach profl-related terms (from U. S. Army, 1984).

In Florida, the foreshore slope is defined
(Chapter 16B-33, Florida Administrative
Code, State of Florida) as:

... that portion of the beach or coast
that is, on a daly basis, subject to the
combined influence of high and low
tides, and wave activity including wave
uprush or backwash. For purposes of
this Chapter, it includes that part of the
beach between mean higher high water
(MHHW) and mean lower low water
(MU W).

The slope of the foreshore, the steepest
portion of the beach profile, is a useful design
parameter since along with the berm elevation
it determines beach width (U. S. Army, 1984,
p. 4-86). As a response, element the
foreshore is a function of force elements such
as astronomical tides, waves, currents, and
property elements such as grain size,
sediment porosity, and sediment mass
density.

The slope of the foreshore tends to
increase with an increase in the grain size of
the sediment ( U. S. Army, 1933; Bascom,
1951; King, 1972). Dubois (1972) found an
inverse relationship between grain size and
foreshore slope where the foreshore
sediments contain appreciable quantities of
heavy minerals. Sediment porosity and
permeability effects on the foreshore are
discussed by Savage (1958).

Generally, foreshore slope increases with
an increase in nearshore wave energy (all
other factors held constant), and an inverse
relationship is found when wave steepness is
applied (e.g., Bascom, 1951; Rector, 1954;
King, 1972). For instance, steeper eroding
waves such as winter waves will result in
flatter foreshore slopes, while longer (less
steep) accretionary waves such as post-
storm or summer waves produce steeper
slopes. Average foreshore slope statistics
for Florida are listed in Table 3. While this
treatment of foreshore slopes is general, it

FLORIDA GEOLOGICAL SURVEY

Table 3. Florida Foreshore Slope Statistics by County and Survey.

Average Standard
County Survey Type Survey Date n Averae Standard
I I I I Slope Deviation
FLORIDA EAST COAST
Nassau Control Line Feb 1974 81 0.0359 0.0235
Nassau Control Line Sep-Oct 1981 85 0.0474 0.0344
Duval Control Line Mar 1974 68 0.0199 0.0178
St. Johns Control Line Aug-Sep 1972 203 0.0523 0.0322
St. Johns Control Line Feb-May 1984 210 0.0339 0.0384
Flagler Control Line Jul-Aug 1972 99 0.1077 0.0273
Volusia Control Line Apr-Jun 1972 227 0.0348 0.0306
Brevard Control Line Sep-Nov 1972 217 0.0798 0.0413
Brevard Control Line Aug 1985-Mar 1986 219 0.0719 0.0347
Indian River Control Line Nov 1972 116 0.1163 0.0335
Indian River Control Line 1986 119 0.1201 0.0793
St. Lucie Control Line Jun 1972 115 0.1012 0.0358
St. Lucie Condition Jan-Feb 1983 36 0.0919 0.0248
Martin Control Line Oct-Nov 1971 115 0.0939 0.0378
Martin Control Line Jan-Feb 1976 96 0.0867 0.0287
Martin Control Line Feb-Apr 1982 104 0.0845 0.0301
Palm Beach Control Line Nov 1974-Jan 1975 226 0.1011 0.0347
Palm Beach Condition Aug 1978 24 0.1113 0.0334
Broward Control Line 1976-1976 127 0.1099 0.0423
Dade Condition Nov 1985-Feb 1986 28 0.1243 0.0328
Total n and Weighted Averages 2,515 0.0760 0.0359
FLORIDA LOWER GULF COAST
Pinellas Control Line Sep-Oct 1974 185 0.0747 0.0447
Manatee Control Line Aug 1974 67 0.1009 0.0419
Manatee Control Line Aug 1986 67 0.0942 0.0377
Sarasota Control Line Jun-Aug 1974 181 0.0983 0.0375
Sarasota Condition Apr 1985 62 0.1051 0.0469
Charlotte Control Line May 1974 67 0.0757 0.0343
Charlotte Control Line Dec 1982 68 0.1127 0.0363
Lee Control Line Feb 1974 238 0.0843 0.0415
Lee Control Line May-Sep 1982 236 0.0980 0.0419
Collier Control Line Mar-Apr 1973 144 0.0796 0.0265
Collier Condition Sep 1984 40 0.0927 0.0277
Total n and Weighted Averages 1,355 0.0903 0.0389
FLORIDA NORTHWEST PANHANDLE COAST
Franklin Control Line May-Jul 1973 147 0.0933 0.0349
Franklin Control Line Jun-Sep 1981 244 0.1155 0.0472
Franklin Condition Oct 1982 31 0.0769 0.0322
Gulf Control Line Jul-Sep 1973 161 0.1032 0.0540
Gulf Condition Jan 1983 45 0.0785 0.0327
Bay Control Line Feb 1971-Feb 1973 141 0.0707 0.0255
Walton Control Line Oct 1973 130 0.0991 0.0699
Walton Control Line May 1981 130 0.1060 0.0578
Okaloosa Control Line Nov-Dec 1973 49 0.0650 0.0406
Escambia Control Line Jan-Feb 1974 213 0.0988 0.0429
Total n and Weighted Averages 1,219 0.0970 0.0458
Grand Total n and Weighted Average 5.089 0.0848 0.0391
NOTE: n = number of profiles per survey.

SPECIAL PUBLICATION NO. 43

will suffice for the following use/application
examples.

Seasonal Beach Changes

Beach changes due to extreme impacts
from storms and hurricanes are considered to
more nearly represent isolated events. There
are, however, beach changes that are more
nearly episodic or cyclic. For instance,
systematic beach changes through an
astronomical tidal cycle (e.g., Strahler, 1964;
Sonu and Russell, 1966; Schwartz, 1967),
cut and fill associated with spring and neap
tides (e.g., Shepard and LaFond, 1940;
Inman and Filloux, 1960), and effects of sea
breeze (e.g., Inman and Filloux, 1960;
Pritchett, 1976), are well known. Of the
possible cyclic occurrences, however,
perhaps the most pronounced
is that occurring on the
seasonal scale. Using the +
above prescribed rules, the 4
following scenarios can be +2
suggested. During the winter o
season, when incident storm -2
wave activity is most active, 4
high, steep waves result in +6 e
shoreline recession. Normally, +4
the berm is eroded and a +2
gentle foreshore slope is tan
-'2
produced. Sand removed .4
from the beach is stored MHV
offshore in one or more --
longshore bars. During the c +*
summerseason smallerwaves = +4
with smaller wave steepness I +2
values transport the sand E 0
stored in longshore bars back -2
onshore, resulting in a wider
beach berm and steeper +4
+4-
foreshore. +2
w
Seasonal beach changes .2 t
have been described in terms -4
of sand volume changes, -4 MHV
contour elevation changes, 12o l
and horizontal shoreline shift
or beach width changes (see Figure 6. Sea

Balsillie, 1998). Here, however, beach width
is used since, compared to the others, it
offers the largest range in magnitudes.

Let us investigate such seasonal changes
for two localities with identical profile
conditions and average seasonal MSL
shoreline variations, but different MHW
datums. First, however, we need some
representative foreshore slope data. From
Table 3, let us select the average foreshore
slope of tan afs = 0.085 to represent a
winter foreshore slope and a maximum of
tan afs = 0.2 (i.e., 0.085 + 3 standard
deviations) to represent a summer foreshore
slope. The two cases, each with a summer
and winter profile are illustrated in Figure 6.

Like Figure 4, Figure 6 is a simplification,

Distance (feet)
asonal horizontal shoreline shift analysis.

FLORIDA GEOLOGICAL SURVEY

albeit representative since the slopes and
distances presented are precise. First, let us
focus our attention on the CASE I locality
where MHW = +2.5 feet MSL. One will
see that if we utilize MSL as the reference
datum, the seasonal variability in beach
width shifts by 40 feet. If, however, one
uses MHW as the reference datum, the shift
is 56.9 feet. The two values depart from
each other by 30 per cent. If, on one hand,
the CASE I locality were to be singularly
assessed using the MHW reference plane
shoreline, consistent results would emerge.
If, on the other hand, one would wish to
relate force elements (e.g., wave and tide
characteristics) to the shoreline response,
the use of MHW would pose problems (more
about this later).

Similar assessment for the CASE II
locality (MHW = + 4.0 feet MSL) results in
a departure of the MHW MSL shoreline
change of 40 per cent. As for CASE I,
application results similarly apply.

Now let us compare the results of
shoreline shift at the two localities. MSL
shoreline shifts would remain comparable
from locale to locale, since they directly
represent both the tide base and surf base.
MHW shoreline shifts, however, depart from
each other by 15 per cent. Again, as with
extreme event impact, MHW shoreline shifts
can not be compared from locality to locality
(the same would hold true for other datums
such as MHHW, MLW, MLLW, etc.). In fact,
if we evaluated seasonal beach changes
volumetrically, MHW or any of the other site-
specific variable datums would result in
precisely the same non-comparability
problems of the extreme event example
previously given.

Long-Term Beach Changes

Long-term beach changes pose some
highly important concerns. Profile type
surveys provide a source of detailed coast,
beach, and nearshore conditions. Such data

offer the opportunity for calculation of
volumetric changes which, if sufficient
alongshore profiles are surveyed, allows for
sediment budget determinations.

Profile surveying for temporal beach
changes, however, requires a monument
system maintained over many years. For
instance, Florida's coastal monument system
has been in place for some 26 years. Other
such efforts occur on a site-specific basis. For
most of our coasts there is insufficient
monumentation, or it has not been in place for
enough time to assure long-term records.
Even the 26 years for the Florida program is
not lengthy. Moreover, early surveys
measured shoreline positions. In order to
obtain volumetrics from shoreline position
data, horizontal shoreline change (AX) and
volumetric change (AV) have been related in
the Shore Protecton Maual (U. S. Army,
1984) according to:

AX= cAV

where c is a relating coefficient. If not very
carefully applied, such an approach can
produce highly misleading results (Balsillie,
1993a).

Long-term shoreline change rate data for
Florida (Balsillie and Moore, 1985; Balsillie,
1985f, 1985g; Balsillie, and others, 1986)
are determined from shoreline position data
for the period from about 1850 to present.
Commonly up to about a dozen data points
are available from which to conduct temporal
analyses.

By way of example, let us inspect the
application of MHW as the reference datum
plane for determination of horizontal
shoreline change. Let us select an average
MHW value of + 1.7 feet MSL and a
maximum value for MHW of + 3.0 feet MSL,
both of which are representative of Florida
conditions (from Table 1). Using these data,
three cases of combinations of MHW and
foreshore slope values are illustrated in

SPECIAL PUBLICATION NO. 43

Figure 7. Additional data
could have been selected
as well as additional 3
combinations; however, 2 Sr
the three illustrated ,
cases will more than
suffice for our purposes.
The profiles of the three
examples are plotted so *2 -
that the MSL (Surf Base) -2
intercepts define the i
origins of the plots that
0-
they may be compared. -
Horizontal differences of -1 -
MHW intercept locations 2 -
are identified by vertical
dashed lines. Deviations 3
range from 10.2 to 25.6 2
feet, all of which are
significant illustrating the
inappropriate nature of t.l
using MHW for such a
purpose. Again, as with *2
extreme event impact -3
and seasonal shoreline .4 -e
change, MHW shoreline .40 .30
shifts are not comparable
from locality to locality
(the same would hold Figure7. Long-te
true for other datums
such as MHHW, MLW, MLLW, etc.). In fact,
if we evaluated long-term beach changes
volumetrically, MHW or any of the other site
specific extremal variable datums would
result in precisely the same non-
comparability problems of the extreme event
and seasonal shoreline shift examples
previously given.

We can approach the subject from a
different perspective. If MSL is not used as
a reference Surf Base plane, then what
should be used? If one selects an extreme
tidal datum plane such as MHW, does it
represent a base to which aktological force
and response elements can be based? Does
it have spatial continuity? Is it applied in a
conceptually correct sense? All of these
questions need be directed toward coastal

CASE 3 S

Siyi

-20 -10 0 10
Daence frmm SURF BASE btoept

nn shoreline shift analysis.

([t)

processes.

THE SURF BASE

The preceding application/use examples,
while rigorously identifying inconsistencies
resulting from the use of extreme datum
planes for coastal science and engineering
purposes, have not specifically addressed
coastal processes in terms of the forces that
cause beach responses.

In order to understand how the srf base
applies, one needs a basic understanding of
how wave statistics are derived and applied.
At a given water depth a wave tram is a
near-periodic set of waves with a
characteristic average wave crest height H,
wave length L, period T, and having a

FLORIDA GEOLOGICAL SURVEY

specific direction of propagation. Where
water depths are such that waves remain
relatively stable, the wave record (such as
that measured by a wave gauge) will
represent all wave trains (i.e., multiple trains)
passing the gauge. Multiple wave train
height and period measurements are termed
the spectral wave record or wave field.
Short-breaking waves, however, do not
conform to spectral wave statistics. This
occurs because in nearshore waters, waves
are ultimately limited by water depth
according to db = 1.28 Hb (McCowan,
1894; Balsillie, 1983a; Balsillie, 1999b;
Balsillie and Tanner, 1999) where Hb is the
wave crest height at shore-breaking and db
is the water depth where the wave breaks.
Hence, shore-breaking waves engender
moment wave statistics for singl wave
trains since a wave train with larger waves
will break further offshore than one with
smaller waves.

It follows, then, that moment wave
statistics vary depending upon whether they
represent the spectral wave record or single
shore-breaking wave trains. The most
commonly applied nearshore wave height
statistics are the average wave height H,
root-mean-square wave height Hrms,
significant wave height Hs (average of the
highest 30 per cent waves of record), H10
(average of the highest 10 per cent waves
ofrecord), and H1 (average of the highest 1
per cent waves). Each of these moment
measures is applied in the design of coastal
engineering solutions by defined prescription.
Relating moment measures for spectral and
shore-breaking wave cases are listed in Table
4 to illustrate the variability of relating
coefficients.

Let us look at an example of tide
conditions to which we might superimpose
certain wave conditions. Figure 8 illustrates
6 days of an astronomical tide record.
Suppose one inspects the case where MHW
and Hs are, for whatever reasonss, selected
for use. From the plots, each peak of the

tide might be considered to be maintained,
say, for 1/2 to 1 hour. Doubling this value,
since two highs occur in each tidal day for
the semidurnal tide, then MHW is actually
maintained for about 4 to 8 per cent of the
time (e.g., 14 and 28 days a year).
Superimposed upon MHW is the significant
wave height which, by definition, neglects
70 per cent of the wave record (assuming
that Hs adequately includes any significant
zero wave energy component; Balsillie,
1993b). Clearly, such an application would
be inappropriate for one applying such force
elements to annual or long-term conditions.
Unfortunately, however, such misapplica-
tions, of which this is just one example, are
commonplace. On the other hand, such an
application might have more viable
application if it included a storm surge i.e.,
peak combined storm tide minus the
astronomical tide) to represent the peak
combined storm tide and attendant wave
activity which occurred coincident with the
peak astronomical tide. This latter case,
however, has application only to identify a
conservative design elevation for a structure
(e.g., perhaps a pier) which is a monergistic
tidal datums application, but certainly not to
profile response which constitutes a
synergistic application.

Previously discussed use/application
examples have already led to the elimination
of extreme datum planes (i.e., MHHW,
MWH, MLW, MLLW) as has the preceding
example, and MSL and NGVD remain for
consideration. The NGVD reference is not,
of course, a tidal datum. It is rather, for all
practical purposes a geodetic datum for
computational reference, that although for
open-coast gauges has a departure generally
less than 0.5 of a foot from MSL for Florida,
the long-term primary departure of MSL and
NGVD is subject to influences of sea level
rise or fall (shorter-term natural deviations
have been discussed above). Hence, it
should not be utilized as a datum,
particularly where global data are involved
(i.e., where the non-tidal vertical reference

---~-

SPECIAL PUBLICATION NO. 43

Tabe 4. Moment Wave Height Statistical Relationships
1984b).

represents a conceptual plane not located
and/or not calculated such that it is not
necessarily comparable to NGVD). The
remaining tidal datum is, then, MSL. Other
than its identification by elimination of other
datums, there are strong motivating reasons
why MSL is the proper tidal datum reference
to use when dealing with coastal processes
(i.e., force and response elements). As we
have already learned, principal force
elements include astronomical tides, storm
tides, and waves. Astronomical tides are, by
definition, already accounted for when using
MSL, and storm tides are extreme events
though accounted for as described in the
preceding section. Waves, however,
constitute an ubiquitous phenomenon near
constant in nearshore coastal waters (except
for coasts with a substantial zero wave
energy component).

(after Balsae and Carter. 1984a,

Therefore, by the process of
elimination MSL is defined as the srf base
(it is also the tide base, not to be confused
with the concept of the wave base). Upon
inspection of Figures 1, 2, and 3, it is readily
apparent that MSL, like the other datums,
has variability. Why, then, would we select
it as a convention for reference? Water
levels are not globally coincident in the
vertical sense for very real reasons.
However, MSL is a measure representative
of the entire distribution of the metonic
astronomical tide, and is the only one of the
tidal datums that has statistical continuity
and comparability of results from place to
place. Noting that for open coastal waters
MSL is equivalent to MTL (Swanson, 1974,
p.4), then the MTL measure remains to
represent the central tendency of the tide
distribution since metonic measures of highs
and lows are used in its determination. The

Portion of Wave Record Spectral Relationships Shore-Breaking Relationships
Considered

All Waves Average Wave Average Breaker
Height = H Height = Hb

All Waves H= 0. 885 H, Hb = 0. 98 H

Highest 30% H= 0. 625 H H = 0. 813 H,

Highest 10% H= 0. 493 /0 H, = 0. 73 H/a

Highest 1% H= 0. 375 /- H, = 0. 637 /,

Definitions:

Average Wave Root-Mean-Square Wave
SN H, = significant
Height = H= H H H = J wave height

NOTE: Formulas apply to both H and Hb; H,, H0,, and H, are calculated
using the form of the equation as for the average wave height.

FLORIDA GEOLOGICAL SURVEY

' |
12

II0I

s7 t

Figure 8. Semidiunal tide curves for 6 tidal d
Manner, 1951).

issue becomes particularly poignant from
inspection of Figure 1 where the behavior of
low waters (i.e., MLW and MLLW) and high
waters (i.e., MHW and MHHW) are anything
but symmetrical in their relationship to MSL
(or MTL), signifying a need for an average
surf base measure. Statistically extreme
average point measures providing numerical
values of upper (i.e., MHW and MHHW) and
lower (i.e., MLW and MLLW) tidal datums
are robustly founded. Corresponding
extremes of such physiographic features as
the foreshore may not be so robustly
founded, since its formation and
maintenance has not been rigorously defined
in terms of forces and responses (e.g., Kraus
and others, 1991, p. 3). Given the manner
in which we currently define the foreshore,

ays (from

one should view it in the
statistical sense where we know
more about its central tendency
than we do about the behavior of
the lower foreshore (corres-
ponding to MLW or MLLW) or
higher foreshore (corresponding
to MHW or MHHW). When we
approach the extremes of the
slope, exceptions due to
physiographic irregularities can
occur. Hence, one needs to view
the surf base foreshore slope
intersection as a focal point about
which the foreshore rotates. In
this context, the focal point is
directly related to incoming force
elements. Furthermore, it is
conceptually not subject to
variations to which the upper and
lower parts of the foreshore are
subject, since it is an origin both
common and comparable to the
focal point at other localities.

From a slightly different
viewpoint, one argument
proffered by a colleague who
took the "devil's advocate'

position, is that the MHW
intercept represents the most
stable portion of the foreshore slope. While
this may appear appropriate to the layman,
from the geological perspective it is not. It
is, in fact, the least stable in terms of
representing a normal slope. The most
stable position of the foreshore is probably at
the MSL intercept (i.e., relative to other
submerged portions of the profile) since it is
reflective of average, ongoing force elements
to which it is modified as a response
element. By comparison, the foreshore in
the vicinity of the MHW or MHHW intercepts
is affected only during high tide stages and
can be reflective of extremal impacts (e.g.,
storm wave events). Extreme impacts
affecting the MHW foreshore are likely to
result in relict features which persist until
continual average force conditions finally

,;2,_0

SPECIAL PUBLICATION NO. 43

return the upper portions of the slope to
normal slope status.

What point estimator of wave
parameters, representing the appropriate
force element, does one subscribe for an
extreme average measure of the
astronomical tide, say for MHW? One does
not apply such point estimators for wave
transformation synergistic applications,
because none would be appropriate. Hence,
unless an average sea level (MSL or MTL) is
combined with an average wave height, one
is mixing "apples and oranges". It is
imperative when undertaking such a task,
we render the task to simplest terms. For
instance, when transforming waves to the
point of shore-breaking, including any wave
reformation and rebreaking, the waves
should be expressed as an average wave
height or, perhaps, root-mean-square wave
height since these measures include all
waves of record. Do not use the significant
wave height, average of the highest 10 per
cent of heights, average of the highest 1 per
cent of wave heights, etc. Whether or not a
significant zero wave energy component is
included depends on the purpose of the work
(Balsillie, 1993b). Any conversion of the
average wave height to extreme wave height
measures of Table 4, say for design
purposes, is accomplished by converting the
average measure, but only after wave
transformation as an average height has
occurred. Kraus and others (1991) note the
importance of the average wave height and
tout its use to be the "... "Rosetta stone"
for conversion ...", no less important is the
proper application of the surf base (MSL)
which becomes the Rosetta Stone for
referencing tide and wave phenomena.
Another good reason for using averages
throughout any numerical transformation
process is because one is often unable to
determine from published results if the
transformation methodology is truly
commutative.

MSL is, therefore, the only datum

plane that is relevant to the surf base. For a
relatively short experiment or field study,
MWL or SWL references are suitable to
represent the time frame of the experiment
or study. Such referenced results, however,
may not be comparable to results referenced
to MSL at other localities. For this reason,
all applicable datums ... MSL, MWL, and
SWL, where known ... collectively termed
Design Water Levels (DWLs), should be
provided in documentation of results.

SEA LEVEL RISE

So far, we have but in passing
mentioned the effects of sea level rise,
recalling that the primary difference between
NGVD and MSL (or MTL) is sea level rise. In
an historical context, the effect of sea level
rise on the current metonic period has, thus
far, been insignificant from a surveying
perspective. Its future effect, however,
remains controversial (e.g., Titus and Barth
(1984) and Titus (1987) versus Michaels
(1992), to mention but only several
published works among a vast number on
the subject). Other work indicates details of
sea level reversals or pulses (Tanner, 1992,
1993), also characterized as crescendos
(Fairbridge, 1989).

There are certain applications where
temporal specifications of sea level rise are
of potential consequence. Hence, from a
data management and processing viewpoint,
it becomes in certain cases necessary to
start with NGVD and calculate the relative
date-certain sea level rise component. The
result, of course, becomes the date-certain
MSL (or MTL). For the 1960-1978 National
Tidal Datum Epoch, the following relationship
assessed in British Imperial units is posited:

MSL, = NGVD + c (D 1969.5)

where MSLo is the date-certain value for
MSL (or MTL), c = 0.0060 for Florida's east
Coast), c = 0.0064 for Florida's Lower Gulf
Coast, and c = 0.0069 for the Florida

FLORIDA GEOLOGICAL SURVEY

Panhandle Gulf Coast (Balsillie and others,
1987a, 1987b, and 1987c, respectively),
and D is the survey date. Please note that
the value of c changes with time and
location; the current value of c for a
particular coast is a representative regression
value.

MONERGISTIC TIDAL DATUM
PLANE APPUCA TIONS

Thus far, the above application/use
examples have been described as syner-
gistic. That is, horizontal shoreline shift and
volumetric change results are referenced to
a datum so that they can be compared
spatially within a North American or global
context. The scientific need to do so has
been robustly demonstrated. Even more,
considerable analytical work is required to
determine such synergistic results which
cannot be simply recalculated to another
datum.

As described in the introduction there
are, however, other quite different concep-
tual applications of astronomical tidal datum
planes. Some of these are not necessarily
bound by the need for a spatial tidal datum
convention. These are described as
monergistic applications. The purpose, here,
is to demonstrate several such examples.

DESIGN SOFFIT ELEVATION
CALCULATIONS

"Soffit elevation" is a generic term
meaning the elevation to the underside of the
lowest supporting structural member exclud-
ing the piling foundation, say, for a pier or
single- or muti-family dwelling. Such
elevations are calculated for extreme
elevations associated with the impact of
extreme events (i.e., storms and hurricanes).
The goal is to raise the structure to an
elevation so that it is above the destructive
hydraulic force elements which will pass
below the soffit and through the piling
foundation. For a pier, for instance, a peak

combined storm tide (super-elevated water
level including contributions of wind stress,
barometric pressure decrease, dynamic wave
setup and astronomical tides) corresponding
to a 50-year return period elevation is
normally used for design calculations.
Superimposed upon the storm tide still water
level is a design wave height, normally a
breaking wave height corresponding to Hblo
or Hbl. As previously noted, where a wave
shore-breaks is dependent on the water
depth which, in turn, is dependent on pat-
terns of sediment redistribution occurring
during event impact. Sediment redistribution
is largely a function of offshore sediment
transport and longshore bar formation
(Balsillie, 1982a, 1982b, 1983a, 1983b,
1983c, 1984a, 1984b, 1984c, 1985a,
1985b, 1985c, 1985d, 1985e, 1986;
Balsillie and Carter, 1984a, 1984b, etc.). An
example is illustrated in Figure 9.

Such design work calculations are
site-specific because results will be
influenced by the pre-impact site-specific
profile configuration. There is no intention,
nor at this time a need to compare such
results to other localities. Should such an
application need arise (e.g., a generalized
modeling effort or an accounting need to
assure consistency in design applicationss),
then the reference base should be MSL.
However, such transformations to other
datums can be easily accomplished,
compared to much more involved re-
calculation of synergistic data (i.e., volumes
or horizontal distances).

EROSION DEPTH/SCOUR CALCULATIONS

Site-specific design work such as
minimum pile embedment requires
knowledge of the design surface elevation.
This elevation necessarily includes erosion
depth (e.g., longshore bar trough elevation or
beach erosion elevation), additional scour
caused by the pile, and sediment
liquefaction. In essence these design
elevation calculations are treated in the same
manner as design soffit elevation

SPECIAL PUBLICATION NO. 43

40

S30

20

I 10

0 o

u1 in a 0 3 ...

100 200 300
Distance from NGVD Shoreline (feet)

400 500 600

Figure 9. Actual damage to the Fagler Beach Pier from the Thanksgiving Holiday Storm of
1984 (Balsillie. 1985c) used to test the Multiple Shore-Breaking Wave Transformation
Computer Model for predicting wave behavior, longshore bar formation, and beach/coast
erosion (after Balsillie. 1985b).

calculations.

SEASONAL HIGH WATER CALCULATIONS

In addition to short-term erosive
impacts due to extreme events, our coasts
are subject to long-term changes. In 1972,
the State of Florida incorporated
consideration of storm/hurricane erosion in
affixing the location of Coastal Construction
Setback Lines. In 1978, it adopted a posture
in which quantitative extreme event erosion
became the primary means by which Coastal
Construction Control Lines were located. It
was not until 1984, however, that long-term
erosion was officially recognized by the
State of Florida (Balsillie and Moore, 1985;
Balsillie, State of Florida (Balsillie and Moore,
1985; Balsillie,1985f; 1985g; Balsillie and
others, 1986; etc.,). In 1985, the Growth
Management Amendment required
assessment of erosion at any coastal site for
which a permit application was tendered to
be assessed for a 30-year period.
Associated with 30-year long-term erosion
projections is the local Seasonal High Water
(SHW) defined as ... the line formed by the

intersection of the rising shore and the
elevation of 150 percent of the local mean
tidal range above local mean high water ...
(para. 161.053(6)(a)1,F. S.). That is:

SHW = (1.5 MRT) + MHW

in which MRT is the mean range of tide
(commonly referred to as the mean tide
range). One might assume that the 30-year
erosion projection is to be assessed at the
SHW elevation. This is simply not true and,
in fact, as we have seen earlier would be a
misapplication leading to spatial discontinuity
introducing computational error (Balsillie and
Moore, 1985). Rather, the erosion
projection needs to be assessed at MSL.
The required methodology specified by rule
(para. 16B-33.024(3)(h), F. A. C.,
republished as State of Florida, 1992, 62B-
33.024(3)(h)1., F. A. C.) specifies NGVD as
the assessment elevation. The original rule,
however, was written before compilation of
datum elevations, foreshore slope, and sea
level rise information for the State.
Subsequent work (Balsillie, Carlen, and

Damaged
SSection Destroyed Section

Hbl
SHb

FLAGLER BEACH PIER

:--- \^^^ ^----------

: Porto m ?7 n ............. . ...o ... ..
.. ...ST SWL

rPre-Storm Profiea -.
Bar mough Envelop.e- '
I I I I I I I ~ I

-200

""'

--

-100

FLORIDA GEOLOGICAL SURVEY

Watters, 1987a, 1987b, 1987c) has remedied
the situation, and the rule needs to be
reassessed. Following is an alternative for
consideration.

BEACH-COAST NICKPOINT ELEVATION

In reality, Seasonal High Water is a
misnomer. First, the components necessary
for computation are metonically derived (i.e.,
19-year averages). Second, the results have
not been demonstrated to represent seasonal
variation in astronomical tide behavior.
Third, it has been demonstrated that upon
application, only about 13% to 15% of
undeveloped beach property in Florida would
be affected by the SHW application (Curtis
and others, 1985).

An alternative consideration for such
an application, and others, is the
beach/coast nickpoint elevation. The
nickpoint represents the point where the
beach intersects the coast, normally
identified as the base of a dune or bluff.
Generation and maintenance of the nickpoint

is primarily a function of
event impact. These
elevations for Florida are
probabilistically
investigated; the results
are plotted in Figure 10.
Median (i.e., 50th
percentile) nickpoint
elevations, N,, for Florida
are as follows: 1) East
Coast: +7.15 feet NGVD
(1929), 2) Lower Gulf
Coast: +5.65 feet NGVD
(1929), and 3) Panhandle
Gulf Coast: +6.45 feet
NGVD (1929).

The relationship
between nickpoint
elevations and SHW
elevations for Florida is
illustrated in Figures 11,
12, and 13. It is apparent

direct extreme

from the figures that only the upper east
coast is significantly affected by the SHW,
attesting to the low impact figure of Curtis
and others (1985).

BOUNDARY OF PUBUC VERSUS PRIVATE
PROPERTY OWNERSHIP

The boundary between private (i.e.,
upland) and public (i.e., seaward) beach
ownership is normally fixed by some
commonly applied tidal datum. For most of
the U. S. this boundary is determined by the
plane of MHW which when it intersects the
beach or coast forms the line of mean high
water. However, unlike other riparian
ownership determinations (i.e., fluvial,
lacustrine and estuarine), littoral properties
must, in addition, contend with significant
wave activity that seasonally varies. Hence,
ocean-fronting beaches all too often
experience cyclic seasonal width changes of
a magnitude long recognized as problematic
in affixing an equitable boundary (Nunez,
1966; Johnson, 1971; O'Brien, 1982;
Graber and Thompson, 1985; Collins and
McGrath, 1989).

co..t B-each :: nar.orf

BN.

S10
.- .
0 H.e- = 43.7 +mP

10 LOWER GULF COAST --' "+ a -

0- N, =4.3+4. P
10 -PANHANDLE GULF COAST r -

o 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Exc s kce Probsaby. P
Figure 10. Beach/coast nickpoint elevations for Florida.

SPECIAL PUBLICATION NO. 43

15
uj
I,
a
.3

ODtonce (mSe)
Figure 11. Comparison of Seasonal High Water (SHW) and Medan
Beach/Coast Nickpoint Bevation (NJ for the Forida East Coast.

Dince (mvn)
figure 12. Comparison of Seasonal High Water
(SHW) and Medan Beach/Coast Nickpoint Bevation
(N.) for the Florida Lower Gulf Coast.

U

JI-

01 1 i 0 1 , I I I i ' *
0 100 200
Distanc (nLes)
Rgure 13. Comparison of Seasonal High Water (SHW) and
Medan Beach/Coast Nickpoint Bevation (N,) for the Horida
Panhandle Gulf Coast.

0S

meco N0
3- - - - - - - -
i^i^ I I[ 'i^

* MW--"

BAY GULF

I

SMean N,
- H ----- ------

FRAWUN

FLORIDA GEOLOGICAL SURVEY

Many investigators have suggested
that the legal boundary for ocean-fronting
beaches should not be continuously moving
with the seasonal changes, but should be
the most landward or "winter" line of mean
high water (Nunez, 1966). Selection of the
"winter" MHW line would be the most
practical to locate and would be the most
protective of public interest by maintaining
maximum public access to the shore (Collins
and McGrath, 1989).

In Florida, the ocean-fronting legal
boundary seasonal fluctuation issue was
deliberated upon in State of Florida,
Department of Natural Resources vs Ocean
Hotel, Inc. (State of Florida, 1974) as it related
to locating the MHW line from which a 50-foot
setback was to be required. Judge J. R. Knott
rendered the following decision:

This court therefore concludes
that the winter and most
landward mean high water line
must be selected as the
boundary between the state and
the upland owner. In so doing
the court has had to balance the
public policy favoring private
littoral ownership against the
public policy of holding the
tideland in trust for the people,
where the preservation of a vital
public right is secured with but
minimal effect upon the interests
of the upland owner.

A 1966 Califomia Court of Appeals
decision rejected the application of a
continuously moving boundary in People vs
Kent Estate. However, no decision has been
rendered as to what line to use (Collins and
McGrath, 1989). More recently, Collins and
McGrath (1989) report:

The Attorney General's Office in
California has offered its informal
opinion that, if squarely faced
with the issue, California courts
would follow the reasoning in the

Florida case and adopt the
"winter and most landward line
of mean high tide" as the legal
boundary between public
tidelands and private uplands ...
(it should be understood that
such a boundary, which relatively
stable, would not be permanently
fixed but would be ambulatory to
the extent there occurs long-term
accretion or erosion).

The use of the MHW datum plane for
the determination of a boundary is
straightforwardly a monergistic application;
one must be careful, however, to note that
determination of the seasonal shoreline shift
(or beach width) is not. This will require a
synergistic application using MSL. Similarly,
any periodic review and boundary relocation
due to long-term shoreline changes will
require the synergistic approach.

INLETS AND ASSOCIATED
ASTRONOMICAL TIDES

It has been speculated that tidal inlets
can significantly affect the character of open
coast tide behavior. There are, however,
insufficient alongshore data crossing inlets,
both upcoast and downcoast, upon which to
assess the effect of inlets (termed the
"shadow effect"). In addition, flow
characteristics vary from inlet to inlet and a
multitude of such investigations would be
required to investigate the alongshore
influence of inlets. There are, however, some
isolated open coast tide data near inlets or
within inlet throats close to the shoreline.
There are more data interior to inlets. Such
information for 24 Florida tidal inlets and
passes are plotted in Figure 14 from which
some significant elucidating conclusions may
be gleaned.

The data of Figure 14 are displayed in
terms of the measured inlet tide data minus
the open coast tide data of Balsillie and others
(1987a, 1987b, 1987c). In this way the

SPECIAL PUBLICATION NO. 43

0.4
0.2
0
-0.2
:-0.4
-06
-0.-
-1.0
o -1.2
o,4!

a 0.2
0
S
o.-0.2
'4'
0.8

i0.6
S0.4

a

-4.*i -- --

0 0.5 1.0 1.s
es from Shorlne

2.0 2

Figure 14. Departure of Florida inlet tide data a
open coast tide data (measured tide data from DN

Bureau of Survey and Mapping).
discussion.

See text

acceptability of the data within the dashed
lines (i.e., plus and minus 0.1 ft.) can be
easily assessed. Data for MHHW and MLLW
plot similar to MHW and MLW data with
somewhat greater variability, and are not
shown.

The first conclusion to be drawn from
Figure 14, is that the amplitude of the tide is
attenuated by the inlet (i.e., MHW becomes
lower in elevation and MLW gains elevation);
this is illustrated in a different manner for
two Florida inlets in Figure 15. Hence, if one
were (as before) to use MHW as the

p - p )

* 0
p0 0 0

referenced specifically to MSL.
Ideally, the alongshore "shadow
effect" of inlets on astronomical tides should
be quantitatively assessed. Such work is,
however, expensive and time consuming and
is not expected to be forthcoming any time
soon.

It is also of significance to note that
Cole (1997, p. 38) has found that nth order
polynomial equations precisely determine
tidal datums within estuaries. The order of
the best fit polynomial for an estuary was

reference plane for a synergistic
application (e.g., storm impact,
seasonal, or long-term beach
changes), the amount of error
introduced is potentially highly
significant. It would, in addition,
occur over a quite short segment of
shoreline. For MHW,
39% of the data are acceptable (i.e.,
lie with +0.1 ft. of the open coast
data) with 61% of the data being
unacceptable. For MLW 76% of the
data are unacceptable. However, for
MTL almost 70% of the data are
acceptable. This shift in data
acceptability for MTL is not aberrant.
Rather, it is to be a moderating
expectation since MTL is the plane
lying halfway between MHW and
MLW and should, therefore much
more closely approach open coast
MTL values than any of the other
extremal tidal datum planes.
Therefore, depending on the
application, the locally measured
MSL (MTL) datum plane or the open
coast MSL (MTL) datum plane should
be used for synergistic applications in
the vicinity of inlets (which is used
should be clearly specified). Hence,
nd MTL (or the MSL surf base) is, once
IR, again, the proper datum plane to use
For for inlets. In fact, O'Brien (1931)
intentionally included in his
definitions for tidal characteristics
g., flow area, tidal prism) that they be

MHW

MTL

.* i

0*

#LW 0
MIW
r00
0
~ ** *
8.. O

ur- .

---

, ,

FLORIDA GEOLOGICAL SURVEY

2.00 ---------- ---

1.00 -- --- IJ .

gu 15 a ins de ',trlomical :tie f,
I $ A 1

0.00 7'

___I A - -I - -- -

b\ . I 1 I 1 I I I II

.I 30.00 40.00 50.00 60.00 70.00
Time (Hours)

Figure 15. Open ocean and inside astronomical fides for Ft. Pierce
and St. ucie Inlets, Florida (from Anonymous, 1992).

found to be predictable based on the length
of the estuary and the travel speed of the
tidal wave within the estuary.

CONCLUSIONS

A considerable amount of information,
hopefully simplified as much as possible, has
been presented in the above application/use
examples. It would not serve further purpose
to restate conclusions here that could be more
succinctly touted, other than to state that MSL
(or open-coast MTL) is the proper datum to
employ for synergistic coastal engineering
applications. It is hoped that this work has
rendered it apparent that how we perceive and
treat such subject matter in a scientific context
is sensitively critical. The considerations
presented herein embody not just philosophy,
but engender intellectual contemplation and
deliberation necessary to arrive at a deductive,
reasonable, and robustly correct convention
for application. In this day and age, it is
unfortunate that while we are finally realizing
such enhanced data processing capabilities,
we are fraught with misapplication that all-too-
often render good data to inaccurate results.

ACKNOWLEDGEMENTS

Review of this work by selected staff
of the Florida Geological Survey is gratefully
acknowledged, in particular those editorial
contributions of Jacqueline M. Lloyd,
Thomas M. Scott, Kenneth M. Campbell, Jon
Arthur and Walter Schmidt. Review by the
Bureau of Beaches and Coastal Systems is
also acknowledged with special thanks to
Ralph R. Clark and Thomas M. Watters for
their interest in the subject and/or editorial
comments. Special thanks are extended to
George M. Cole who reviewed the
manuscript and encouraged its publication.

REFERENCES

Anonymous, 1978, Definitions of surveying
and associated terms: Joint
committee of the American Congress
on Surveying and Mapping and the
American Society of Civil Engineers,
210 p.

1992, St. Lucie Inlet manage-
ment plan: Applied Technology and
Management, Inc., Gainesville, FL.

SPECIAL PUBLICATION NO. 43

Balsillie J. H., 1982a, Offshore profile
description using the power curve fit,
Part I: explanation and discussion:
Florida Department of Natural
Resources, Beaches and Shores
Technical and Design Memorandum
No. 82-1-1,23 p.

1982b, Offshore profile
description using the power curve fit,
Part II: standard Florida offshore
profile tables: Florida Department of
Natural Resources, Beaches and
Shores Technical and Design
Memorandum No. 82-1-11.71 p.

1983a, On the determination of
when waves break in shallow water:
Florida Department of Natural
Resources, Beaches and Shores
Technical and Design Memorandum
No. 83-3, 25 p.

1983b, The transformation of
the wave height during shore-
breaking: the alpha wave peaking
process: Florida Department of
Natural Resources, Beaches and
Shores Technical and Design
Memorandum No. 83-4, 33 p.

1983c, Wave crest elevation
above the design water level during
shore-breaking: Florida Department
of Natural Resources, Beaches and
Shores Technical and Design
Memorandum No. 83-5, 41 p.

1984a, Wave length and wave
celerity during shore-breaking:
Florida Department of Natural
Resources, Beaches and Shores
Technical and Design Memorandum
No. 84-1, 17 p.

1984b, Attenuation of wave
characteristics following shore-
breaking on longshore sand bars:
Florida Department of Natural
Resources, Beaches and Shores
Technical and Design Memorandum
No. 84-3, 62 p.

1984c, A multiple shore-
breaking wave transformation
computer model: Florida Department
of Natural Resources, Beaches and
Shores Technical and Design
Memorandum No. 84-4, 81 p.

1985a, Redefinition of shore-
breaker classification as a numerical
continuum and a design shore-
breaker: Journal of Coastal
Research, v. 1, p. 247-254.

1985b, Calibration aspects for
beach and coast erosion due to storm
and hurricane impact incorporating
event longevity: Florida Department
of Natural Resources, Beaches and
Shores Technical and Design
Memorandum No. 85-1, 32 p.

1985c, Post-storm report: the
Florida East Coast Thanksgiving
Holiday Storm of 21-24 November
1985: Florida Department of Natural
Resources, Beaches and Shores Post-
Storm Report No. 85-1, 74 p.

1985d, Post-storm report:
Hurricane Elena of 29 August to 2
September 1985: Florida Department
of Natural Resources, Beaches and
Shores Post-Storm Report No. 85-2,
66 p.

FLORIDA GEOLOGICAL SURVEY

1985e, Verification of the
MSBWT numerical model: coastal
erosion from four climatological
events and littoral wave activity from
three storm-damaged piers: Florida
Department of Natural Resources,
Beaches and Shores Technical and
Design Memorandum No. 85-2, 33 p.

1985f, Establishment of
methodology for Florida growth
management 30-year erosion
projection and rule implementation:
Florida Department of Natural
Resources, Beaches and Shores
Technical and Design Memorandum
No. 85-4, 79 p.

1985g, Long-term shoreline
change rates for Gulf County, Florida:
a first appraisal: Florida Department
of Natural Resources, Beaches and
Shores Special Report No. 85-3, 42
p.

1986, Beach and coast erosion
due to extreme event impact: Shore
and Beach, v. 54, p. 22-37.

1993a, Relationship between
shore-normal horizontal shoreline shift
and volumetric beach change: Florida
Department of Natural Resources,
Division of Beaches and Shores
Memorandum.

1993b, Lower Gulf Coast of
Florida wave data its use as a
design force element and for
sediment budget determinations:
Florida Department of Natural
Resources, Division of Beaches and
Shores Memorandum.

1999a, Seasonal variation in
sandy beach shoreline position and
beach width: Florida Geological
Survey, Special Publication No. 43, p.
1-29.

1999b, On the breaking of
nearshore waves: Florida Geological
Survey, 155 p.

Balsillie, J. H., Carlen, J. G., and Watters, T.
M., 1987a, Transformation of
historical shorelines to current NGVD
position for the Florida East Coast:
Florida Department of Natural
Resources, Division of Beaches and
Shores Technical and Design
Memorandum No. 871, 177 p.

1987b, Transformation of
historical shorelines to current NGVD
position for the Florida Lower Gulf
Coast: Florida Department of Natural
Resources, Division of Beaches and
Shores Technical -and Design
Memorandum No. 87-3, 141 p.

1987c, Transformation of
historical shorelines to current NGVD
position for the Florida Panhandle
Gulf Coast: Florida Department of
Natural Resources, Division of
Beaches and Shores Technical and
Design Memorandum No. 87-4, 152
p.

1998, Open-ocean water level
datum planes for monumented coasts
of Florida: Florida Geological Survey,
Open File Report 73, 92 p.

Balsillie, J. H., and Carter, R. W. G., 1984a,
Observed wave data: the shore-
breaker height: Florida Department of
Natural Resources, Beaches and
Shores Technical and Design
Memorandum No.84-2, 70 p.

1984b, The visual estimation of
shore-breaking wave heights:
Coastal Engineering, v. 8, p. 367-
385.

SPECIAL PUBLICATION NO. 43

Balsillie, J. H., and Moore, B. D., 1985, A
primer on the application of beach
and coast erosion to Florida coastal
engineering and regulation: Florida
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Beaches and Shores Technical and
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Balsillie, J. H., O'Neal, T. T., and Kelly, W.
J., 1986, Long-term shoreline change
rates for Escambia County, Florida:
Florida Department of Natural
Resources, Beaches and Shores
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Balsillie, J. H., and Tanner, W. F., 1999,
Stepwise regression in the earth
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Bascom, W. N., 1951, The relationship
between sand size and beach-face
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Brown, C. M., Robillard, W. G., and Wilson,
D. A., 1995, Brown's boundary
control and legal principles, New
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Carter, R. W. G., 1988, Coastal
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Cole, G. M., 1983, Water boundaries,
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1991, Tidal water boundaries,
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1997, Water boundaries, New
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Collins, R. G., and McGrath, J., 1989, Who
owns the beach? Finding a nexus
gets complicated: Coastal Zone '89,
v. 4, p. 3166-3185.

Curtis, T. D., Moss, R. L., and Shows, E.
W., 1985, Economic impact
statement: the 30-year erosion rule:
Florida Department of Natural
Resources, Beaches and Shores
Economic Impact Statement No. 85-
2, 84 p.

Doodson, A. T.,
geodesy:
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1960, Mean sea level and
Bulletin Gkod6sique, v. 55,

Dubois, R. N., 1972, Inverse relation
between foreshore slope and mean
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Embleton, C., 1982, Mean sea level: in M. L.
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Fairbridge, R. W., 1989, Crescendo events
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Foster, E. R., 1989, Historic shoreline
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in Tanner, W. F., ed., Coastal
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1991, Coastal processes near
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FLORIDA GEOLOGICAL SURVEY

Foster, E. R., and Savage, R. J., 1989a,
Methods of historical shoreline
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4448.

1989b, Methods for analysis of
historic shoreline data: in W. F.
Tanner, ed., Coastal Sediment
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Tallahassee, Fl, Department of
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Galvin, C. J., Jr., 1969, Breaker travel and
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1988, The annual tide in
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Gorman, L., Morang, A., and Larson, R.,
1998, Monitoring the coastal
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Graber, P. H. F., and Thompson, W. C.,
1985, The issues and problems of
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Harris, D. L., 1981, Tides and tidal datums
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Hicks, S. D., 1984, Tide and current
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Inman, D. L., and Filloux, V., 1960, Beach
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1971, The significance of
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King, C. A. M., 1972, Beaches and Coasts,
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570 p.

Komar, P. D., 1976, Beach Processes and
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1998, Wave erosion of a
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Earth Surface Processes and
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Kraus, N. C., Larson, M., and Kriebel, D. L.,
1991, Evaluation of beach erosion
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Lee, G., Nicholls, R. J., and Birkemeier, W.
A., 1998, Storm-driven variability of
the beach-nearshore profile at Duck,
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Lyles, S. D., Hickman, L. E., and Debaugh,
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Marmer, H. A., 1951, Tidal datum planes:
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SPECIAL PUBLICATION NO. 43

McCowan, J., 1894, On the
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Nunez, P., 1966, Fluctuating shorelines and
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O'Brien, M. P., 1931, Estuary tidal prisms
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1982, Our wandering high-tide
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Pritchett, P. C., 1976, Diurnal variations in
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Pugh, D. T., 1987, Tides, surges and mean
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Rector, R. L., 1954, Laboratory study of
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Savage, R. P., 1958, Wave run-up on
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Schmidt, D. V., Taplin, K. A., and Clark, R.
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Schomaker, M. C., 1981, Geodetic Leveling:
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Schwartz, M. L., 1967, Littoral zone tidal-
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Shepard, F. P., and LaFond, E. C., 1940,
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1985b, Rules and procedures
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1992, Rules and procedures for
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Strahler, A. M., 1964, Tidal cycle changes in
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FLORIDA GEOLOGICAL SURVEY

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