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Group Title: UFLCOEL
Title: High frequency shoreline changes for the panhandle area of Florida
CITATION THUMBNAILS PAGE IMAGE ZOOMABLE
Full Citation
STANDARD VIEW MARC VIEW
Permanent Link: http://ufdc.ufl.edu/UF00091068/00001
 Material Information
Title: High frequency shoreline changes for the panhandle area of Florida
Series Title: UFLCOEL
Physical Description: iv, 10 leaves : charts ; 28 cm. +
Language: English
Creator: Dean, Robert G ( Robert George ), 1930-
University of Florida -- Coastal and Oceanographic Engineering Dept
Publisher: Dept. of Coastal and Oceanographic Engineering, University of Florida
Place of Publication: Gainesville Fla
Publication Date: 1999
 Subjects
Subject: Shorelines -- Florida   ( lcsh )
Seashore -- Florida   ( lcsh )
Beach erosion -- Florida   ( lcsh )
Coast changes -- Florida   ( lcsh )
Florida Panhandle (Fla.)   ( lcsh )
Genre: government publication (state, provincial, terriorial, dependent)   ( marcgt )
non-fiction   ( marcgt )
 Notes
Statement of Responsibility: prepared by Robert G ; Dean, Coastal & Oceanographic Engineering, University of Florida ; prepared for Offices of Beaches and Coastal Systems ; Florida Department of Environmental Protection.
General Note: "December 28, 1999."
 Record Information
Bibliographic ID: UF00091068
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 85844958

Table of Contents
    Front Cover
        Front Cover
    Title Page
        Page i
    Executive summary
        Page ii
    Table of Contents
        Page iii
        Page iv
    Main
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
        Page 7
        Page 8
        Page 9
        Page 10
    Appendix
        Page A-0
        Page A-1
        Page A-2
    Appendix
        Page B-0
        Page B-1
    Appendix
        Page C-0
        Page C-1
    Appendix
        Page D-0
        Page D-1
        Page D-2
Full Text




UFL/COEL-99/025


HIGH FREQUENCY SHORELINE CHANGES FOR THE
PANHANDLE AREA OF FLORIDA





by


Robert G. Dean


December 28, 1999



Prepared for:

Offices of Beaches and Coastal Systems
Department of Environmental Protection
State of Florida













HIGH FREQUENCY SHORELINE CHANGES FOR THE
PANHANDLE AREA OF FLORIDA




December 28, 1999








Prepared for;


Offices of Beaches and Coastal Systems
Department of Environmental Protection
State of Florida












Prepared by:

Robert G. Dean
Department of Coastal and Oceanographic Engineering
University of Florida
Gainesville, Florida 32611








EXECUTIVE SUMMARY


In addition to the long-term trends of shoreline change, the shorter-term or "high frequency" changes
can pose a threat to coastal construction. These high frequency changes are due to storms and other
unknown effects, although in the Florida Panhandle, the subject area of this report, it is well known
that large scale cuspate features contribute substantially to the changes.

There are two approaches to predicting high frequency shoreline changes. The approach that has
been applied previously is to quantify the storm hydrographs and waves associated with various
storm return periods of interest and to input these into a beach and dune erosion model. The second
approach, recommended here, is to base the high frequency shoreline changes on the variability in
the shoreline data base, i.e. the deviations form the trend line.

A simple method is presented based on the variability in the shoreline position data base maintained
by the Office of Beaches and Coastal Systems of the Florida Department of Environmental
Protection. Tables are provided for the following four Panhandle counties: Escambia (and Santa
Rosa), Okaloosa, Walton and Bay. The application of the method is illustrated with an example from
Escambia County.








TABLE OF CONTENTS


EXECUTIVE SUMMARY ......................................... .......... ii
LIST OF FIGURES .......................................................... iv
LIST OF TABLES ........................................................... iv
1 INTRODUCTION ...................................................... 1
2 GENERAL BACKGROUND ............................................ 1
2.1 General ....................................................... 1
2.2 Statistics of Shoreline Change .................................... 3
2.2.1 General ................................................. 3
2.2.2 Determination of ......................................... 4
2.2.3 Determination of .................................. .5
2.2.4 Determination of 6m, (j) .....................................5
3 RECOMMENDED METHOD ............................................ 5
4 EXAMPLE OF APPLICATION ......................................... 8
5 SUMMARY .......................................................... 9
6 REFERENCES ....................................................... 9


APPENDICES
A ESCAMBIA (AND SANTA ROSA) COUNTY
TABULATIONS OF 68,() ON A MONUMENT-BY-MONUMENT BASIS ... A-1
B OKALOOSA COUNTY
TABULATIONS OF 6m,() ON A MONUMENT-BY-MONUMENT BASIS .... B-1
C WALTON COUNTY
TABULATIONS OF 8m,(,) ON A MONUMENT-BY-MONUMENT BASIS .... C-1
D BAY COUNTY
TABULATIONS OF 8,(i) ON A MONUMENT-BY-MONUMENT BASIS ... D-1








LIST OF FIGURES


FIGURE


Shoreline Positions For Monument R-125, Escambia County .................... .2
Shoreline Change Characteristics Along Portions of Escambia County, 1996 ......... 6
Variation of del(j) Along Portions of Escambia County .......................... 7




LIST OF TABLES


TABLE


PAGE


Values of the Factor FR for Various Return Periods, TR ........................ 8
Predicted Values of Shoreline Recession for Various Return Periods, TR
Monument 125 in Escambia County ........................................ 9


PAGE







HIGH FREQUENCY SHORELINE CHANGES FOR THE
PANHANDLE AREA OF FLORIDA

1. INTRODUCTION

Shorelines change on a variety of time scales, ranging from seconds to millennia. Of primary
concern to the stewardship of the State's beaches by the Office of Beaches and Coastal Systems
(OBCS) of the Florida Department of Environmental Protection (FDEP) are the long-term
changes that can be determined as a trend through analysis of the extensive historical shoreline
position data base maintained by the OBCS. While these results capture the trend of shoreline
changes, it is evident from the data that other time scales of shoreline change are also relevant to
construction along the shoreline. Consider the idealized case in which the shoreline change trend
is zero, yet there can be substantial fluctuations about the average shoreline position due to storms
and other natural variability components of the shoreline position. The causes and
interrelationships of some of these components are unknown at present. This is especially the case
in the Panhandle area where large cuspate features occur and may migrate along the shoreline
(Sonu, 1968; Miselis and Dean, 1993). The causes) of these features is unknown; however, their
amplitudes can be on the order of 100 to 150 feet; thus they can represent a considerable threat
to coastal construction, especially along a shoreline where there is an erosional trend such that
the beach becomes narrower with time.

The purpose of the study described in this report was to develop a methodology that can be
applied to represent the high frequency shoreline changes along the Florida Panhandle. "High
frequency" as used in this report represents the deviations from the trend line as shown in Figure
1. As will be discussed and quantified in detail later, these deviations can be either reasonably
coherent along the shoreline or can occur relatively locally in which case, they may be the result
of the large scale cuspate features described above.

2. GENERAL BACKGROUND

2.1 General

Consider a storm that occurs affecting a coastal location in the Panhandle area. The resulting
beach and dune recession depends on the detailed storm surge levels and wave heights and local
factors including the three-dimensional topography, vegetation, and other local causes some of
which may not be well understood. Beach and dune erosion models developed to date are two-
dimensional representing only the cross-shore sediment transport. Additionally these models do
not account for local effects which may influence the cross-shore sediment transport. Yet it is
well known from inspecting the erosional scarp that the recession can vary substantially along the
shoreline. Dean, et al (1998) have found in a study of the shoreline changes around the State of
Florida that the average standard deviation of the variability about the shoreline change trend line
is approximately 30 ft to 40 ft except in proximity to inlets where the variability is much greater.
Zheng and Dean (1997) have examined contour changes resulting from five different storms and












S- -- Data
Best Least Squares Fit (All Data)
-------- Best Least Squares Fit (All Data)


I \^::T ^ ,4. Lea
--------- 1- -----~--- 1''..,~~a ~s~~ -------------------------~ ~ ~ '' ~'' ''' '~ '' ~~
Se t-- st



SDeviati n (Typ) Le -- g )Po S92
It


Year


1950


Figure 1. Shoreline Positions For Monument R-125,

Escambia County


400


0
.2

10
0

a)

L-
0

WO


300




200




100


nL


1850
1850


1900


2000


-


I 1 I /


. . . . . . . . - - - - - - - - -- - - -


. . . . . . . . . . . . . - - -








locations and found that the variability can vary from an average of 30% to 100% of the average
change.

Part of the variability from the average change may be a result of irregular longshore topography
prior to the storm and the tendency of the storm to straighten the shoreline. As noted, the available
models are not sufficiently detailed to account for these features. In summary, the problem of
concern here consists of both deterministic and probabilistic components with the deterministic
component which could be predicted by a beach and dune erosion model if the related processes
were understood adequately and the probabilistic component which is due to unknown and/or
unpredictable processes and causes and thus must be determined empirically.

One approach to many problems which include deterministic and probabilistic components is to
account for the deterministic component through calculation procedures and to represent the
probabilistic component statistically. Wind forces are an example of such a phenomenon. For a
given atmospheric pressure field and surface roughness, it is possible to calculate the distribution
of the average wind speed with elevation above ground level; however, the temporal variability
of the wind speed about its mean at a particular elevation can only be quantified by empirical
approaches through the statistics of this variation. Dune erosion is similar. The two dimensional
beach and dune erosion models can predict only the deterministic component of the beach and
dune recession. Thus, some other realistic empirical approach must be developed and applied to
account for the non-deterministic component. It is clear that with our present level of
understanding, this non-deterministic component must be based on measured shoreline changes.
One approach that has been applied in the establishment of the recommended position of the
Coastal Construction Control Line (CCCL) is to apply a factor to the deterministic component
(Chiu and Dean, 1984). Earlier efforts to predict high frequency shoreline changes employed
similar approaches (Dean and Malakar, 1995). A second approach and the one that will be
recommended here is to represent the total component deterministicc and non-deterministic
components) from results of analysis of historical position change. However, first the
relationships of these two components will be reviewed in the framework of shoreline change
statistics.

2.2 Statistics of Shoreline Change

2.2.1 General

The statistics of shoreline change are considered in a manner which represents the structure of
changes consistent with the causes and also consistent with the interest in predicting these high
frequency changes. Consider the shoreline position, yij at the i* location and j" time as follows


ij=Yoi+mi(t- to) +6ij (1)

in which yi is the predicted shoreline location at time to, mi is the shoreline change rate at the it







location and 6,j is the deviation at tj at the i" location from the predicted location based on the
trend line, see Figure 1. This deviation from the predicted value, 6, can be decomposed further
into two components as


6i = + 6' (2)


where the term ,., represents the local spatial average of the deviations from the predictions and
the term 8, / represents the deviation from this local average. The local average is defined as

i+k
-+ 1 ij (3)


with the value k = 5 such that the local average is based on a shoreline length of approximately
10,000 feet based on a nominal DEP monument spacing of 1,000 feet.

To summarize, the shoreline position, yij, at the id location and j't time is represented as


ij =Yoi +mi(t-to) i + (4)



The interpretation of Eq.(4) in terms of our interest is that the first two terms on the right hand
side of Eq. (4) represent the trend, that is, the long term predictable shoreline position. The next
term, 6,, is the local spatial average and the term representing storm or other longshore coherent
effects and the component that should be predicted from a beach and dune erosion model if all
of the processes were understood adequately. The final term, 68, represents the local deviation
from the predicted storm effects. Note that by definition, there will be deviations which exceed
the predicted storm effects and deviations which are less than the predicted storm effects.

The following sections discuss the manner in which the various components, 8i6 and 6j/ can
be determined.

2.2.2 Determination of i

At any time and location, this term represents the longshore coherent component of the deviation
of the shoreline position from the predicted shoreline position based on analysis of the long term
data. One approach to determining 68i is to utilize the most recent available beach profile
available and to consider this profile in equilibrium. With the increased water levels and wave
heights due to the storms, the shoreline will retreat by a maximum amount which depends on the








temporal variations of these two variables and which could be predicted by a beach and dune
erosion model. A second approach is to simply determine the quantity empirically as will be
discussed and recommended later in this report.

2.2.3 Determination of 6../

This quantity must be determined empirically through application of Eqs.(3) and (4). Figure 2
presents for 1996, plots of 6, (termed "delprime" in Figure 2) and 6. (termed "Delbar" in Figure
2) for a portion of the Escambia County shoreline It is seen that the relative magnitudes of these
two components vary considerably and that 6,. (Delbar) is predominantly negative for 1996 over
this section of shoreline.

2.2.4 Determination of 6, ()

The discussion in the preceding sections has been presented to provide a framework for the
statistics of shoreline change. The recommended method will employ the root-mean-square value
of 6, (= 6,(j)) as determined by a least squares fit to the data over all times considered accurate
at each monument. Because the earlier surveys are not considered as valid as the later surveys,
the earliest dates included in the analysis and results to be recommended here are: Escambia (and
Santa Rosa) Counties: 1920; Okaloosa County: 1934; Walton County: 1932; and Bay County:
1932. Figure 3 presents a plot of the alongshore variation of 6,(j) over the same portion of
Escambia County as portrayed in Figure 2.

3. RECOMMENDED METHOD

The total variance from the trend line includes both the variance due to storms (the predictable
or deterministic component) and the variance representing the non-deterministic component.
Thus, the recommended method is to simply apply this total variance as follows. The total
variance at one monument is defined as 6ij2, i.e.


62=( a(j))2 = ..2= 2+/2 (5)
S rj ij ij (5)


in which the averaging is over time, i.e. the i* subscript. In the application of the results, it is
assumed that the variance is representative for all deviations and that, similar to the application
to other predictions of natural events, one event occurs per year. Finally, it is assumed that the
distribution to which the variance pertains is a normal distribution. Thus deviations can occur
which are either negative or positive.

In accordance with a normal probability distribution, the recognition that the deviation from the
trend line can be either positive or negative (we are only interested in recessions which are
negative deviations) and that one extreme (positive or negative) shoreline deviation occurs per











C:
0


a,
0
U-



a>
C
(.

03


100
80
60
40
20
0
-20
-40
-60
-80
-100
8'


100


120


140


160


180


200


Monument Number

Figure 2. Shoreline Change Characteristics
Along Portions of Escambia County, 1996


L
._

-


wj fr ..V W - - -V --- --V-V..... V r

-1
-.. ... .......... .......... ...... ..... ..... .. :.Note: No Data W ere Available: --
.. .......... ......... ...... ........ for rii num ent 100 fbr 1996. --- --
i i i I i i


0


- - - - -

. . . .


.......... .Delprime
SDelbar






50


: ; i ;


- 1 0 . .. ... ...- --- I -.. . .... .---------
40




30 .. ....... ..- --------- ---------- --------------
- .. .
( 20




01
80 100 120 140 160 180 200
Monument Number

Figure 3. Variation of del(j) Along Portions of Escambia County







year, it can be shown that the recession, RR, associated with a particular return period, TR, is


RTR() =FTR 8.0)


where 6, = j 2 and the values of FR as determined from a normal distribution are presented
in Table 1. Because of the alongshore variability in 6, (), in application, it may be desirable to
employ a running average, see Figure 3.

Table 1
Values of the Factor Fm for Various Return Periods, TR

S__F, for Return Periods, TR (years)
Return Periods, 5 10 15 20 25 30 35
TR (years)
FmR 0.97 1.40 1.61 1.75 1.86 1.96 2.00


Appendices A D presents the recommended values of 6(/)on a monument-by-monument basis
for Escambia (and Santa Rosa) Counties: Appendix A; Okaloosa County: Appendix B: Walton
County: Appendix C; and Bay County: Appendix D.




4. EXAMPLE OF APPLICATION

The methodology will be illustrated with an example for Escambia County. Suppose that the
shoreline recessions are desired for return periods of 5, 10, 15, 20, 25, 30 and 35 years, for
Monument 125 in Escambia County. The value of 68(,) from Page A-i of Appendix A is 37.0
feet. Thus applying Eq. (6) and the FR values in Table 1, the shoreline recessions for the various
return periods are presented in Table 2.








Table 2
Predicted Values of Shoreline Recession for Various Return Periods, TR
Monument 125 in Escambia County

Shoreline Recessions (ft) for Return Periods, TR (years)

Return Periods, TR 5 10 15 20 25 30 35
(years)

Shoreline 35.9 51.8 59.6 64.8 68.8 72.5 74.0
Recessions, RT (ft)


5. SUMMARY

A simple and direct method is developed and illustrated with an example for estimating the high
frequency shoreline changes for the four county Panhandle shoreline of Florida. The method is
based on the statistics of the deviations of measured shoreline positions from the long-term trend
of the data in the shoreline position data base. In part this method is recommended over the
previous method developed for estimating high frequency shoreline changes due to the
documented contributions of non-deterministic large scale cuspate features along the Panhandle
shoreline and thus the need to augment any predictions based on numerical modeling.

6. REFERENCES

Chiu, T. Y. and R. G. Dean (1984) "Methodology Workshop 'Coastal Construction Control Line
Establishment"', Division of Beaches and Shores, Florida Department of Natural Resources, July.

Dean, R. G. and S. Malakar (1995) "Erosion Due to High Frequency Storm Events (18 Selected
Coastal Counties of Florida: User's Manual)", UFL/COEL-95/028, Coastal and Oceanographic
Engineering Department, University of Florida.

Dean, R. G., J. Cheng and S. Malakar."Characteristics of Shoreline Change Along the Sandy
Beaches of the State of Florida: An Atlas" Report No. UFL/COEL-98/015, Department of Coastal
and Oceanographic Engineering, University of Florida, Gainesville, FL.

Miselis, P. and R. G. Dean (1993) "Large Scale Beach Cusps on Pensacola Beach, Florida",
Report to the Mobile District of the U. S. Army Corps of Engineers, Department of Coastal and
Oceanographic Engineering, University of Florida.

Sonu, C. J. (1968) "Collective Movement of Sediment in Littoral Environment", Proceedings,
Eleventh International Conference on Coastal Engineering, American Society of Civil Engineers,
pp. 373-400.








Zheng, J. and R. G. Dean (1997) "Shoreline and Dune Recession Variability and Cross-shore
Modeling", Proceedings of the 10th National Conference on Beach Preservation Technology,
Compiled by L. S. Tait, Florida Shore and Beach Preservation Association, Tallahassee, FL,
pp.151 166.







APPENDIX A

ESCAMBIA (AND SANTA ROSA) COUNTY

TABULATIONS OF5(/8) ON A MONUMENT-BY-MONUMENT BASIS










LISTING OF MONUMENT-BY-MONUMENT DELTA VALUES FOR ESCAMBIA COUNTY


MON.
NO.


1
4
7
10
13
16
19
22
25
28
31
34
37
40
43
46
49
52
55
58
61
64
67
70
73
76
79
82
85
88
91
94
97
100
103
106
109
112
115
118
121
124
127
130


DELTA(j)



22.95
27.52
13.32
17.55
25.54
14.04
24.25
35.67
33.37
33.99
38.93
35.34
31.23
32.55
64.37
98.11
93.68
96.70
106.73
118.53
135.23
172.19
75.82
57.83
96.10
34.60
90.78
19.87
32.40
20.27
24.62
20.03
35.71
33.43
23.52
25.29
11.47
23.05
22.39
46.90
38.15
34.48
33.08
27.11


MON.
NO.


2
5
8
11
14
17
20
23
26
29
32
35
38
41
44
47
50
53
56
59
62
65
68
71
74
77
80
83
86
89
92
95
98
101
104
107
110
113
116
119
122
125
128
131


DELTA(j)



29.71
23.58
33.10
24.32
24.55
22.37
24.44
31.00
24.09
35.65
43.38
48.70
25.60
38.63
99.13
95.91
94.53
94.67
122.14
101.55
170.78
88.25
189.26
111.95
61.03
52.37
61.57
36.18
21.76
32.09
33.73
30.02
47.23
25.59
29.73
35.53
30.20
32.30
22.74
24.57
31.53
37.02
24.40
30.47


MON.
NO.


3
6
9
12
15
18
21
24
27
30
33
36
39
42
45
48
51
54
57
60
63
66
69
72
75
78
81
84
87
90
93
96
99
102
105
108
111
114
117
120
123
126
129
132


DELTA(j)



25.97
32.15
25.19
16.57
33.21
14.76
30.81
18.20
35.02
41.37
52.59
49.88
31.72
72.00
101.86
118.69
105.74
115.70
133.52
131.20
181.15
73.99
118.08
107.44
61.21
67.60
29.22
35.89
35.64
23.91
15.69
34.36
33.07
29.34
41.79
15.82
19.25
16.93
24.44
26.68
32.14
36.35
24.16
36.88










LISTING OF MONUMENT-BY-MONUMENT DELTA VALUES FOR ESCAMBIA COUNTY
(continued)


MON.
NO.


133
136
139
142
145
148
151
154
157
160
163
166
169
172
175
178
181
184
187
190
193
196
199
202
205
208
211
214


DELTA(j)



21.73
33.65
36.92
44.29
39.68
28.10
32.95
36.97
35.10
31.79
34.06
33.09
10.67
20.28
25.90
19.14
12.28
14.28
14.55
12.37
15.32
15.97
18.07
18.63
20.08
33.49
18.75
32.14


MON.
NO.


134
137
140
143
146
149
152
155
158
161
164
167
170
173
176
179
182
185
188
191
194
197
200
203
206
209
212


DELTA(j)



36.80
28.66
40.74
36.62
28.82
37.24
34.50
34.33
27.77
34.09
23.55
22.83
11.94
29.71
18.03
16.66
17.94
13.90
17.19
14.90
23.15
20.54
16.35
17.16
12.89
22.57
23.16


MON.
NO.


135
138
141
144
147
150
153
156
159
162
165
168
171
174
177
180
183
186
189
192
195
198
201
204
207
210
213


DELTA(j)



38.14
26.07
31.12
22.63
35.83
35.45
29.09
30.18
35.42
28.93
21.02
20.08
12.02
19.61
18.67
18.18
22.48
14.82
16.28
21.58
21.11
12.62
11.63
20.59
18.68
16.77
38.34







APPENDIX B

OKALOOSA COUNTY

TABULATIONS OF 6,~() ON A MONUMENT-BY-MONUMENT BASIS









LISTING OF MONUMENT-BY-MONUMENT DELTA VALUES FOR OKALOOSA COUNTY


MON.
NO.


1
4
7
10
13
16
19
22
25
28
31
34
37
40
43
46
49


DELTA(j)



26.94
18.05
19.98
18.92
10.90
19.44
201.45
178.75
28.10
38.19
32.07
38.84
28.29
32.77
37.09
30.57
14.25


MON.
NO.


2
5
8
11
14
17
20
23
26
29
32
35
38
41
44
47
50


DELTA(j)



22.97
22.67
11.97
14.10
25.95
198.37
164.12
37.11
40.48
42.46
39.43
25.92
35.40
34.27
24.85
26.67
18.67


MON.
NO.


3
6
9
12
15
18
21
24
27
30
33
36
39
42
45
48


DELTA (j)



24.17
29.44
28.31
22.76
19.98
207.44
143.56
33.84
37.69
41.34
26.14
26.12
29.84
32.77
37.20
29.40







APPENDIX C

WALTON COUNTY

TABULATIONS OF 65(j) ON A MONUMENT-BY-MONUMENT BASIS








LISTING OF MONUMENT-BY-MONUMENT DELTA VALUES FOR WALTON COUNTY


MON.
NO.


1
4
7
10
13
16
19
22
25
28
31
34
37
40
43
46
49
52
55
58
61
64
67
70
73
76
79
82
85
88
91
94
97
100
103
106
109
112
115
118
121
124
127


DELTA(j)



34.78
25.44
23.43
42.43
15.09
34.85
47.15
46.21
28.58
28.22
47.85
19.75
18.78
24.40
64.37
22.51
29.22
20.81
22.01
28.48
19.95
18.42
23.67
23.65
16.67
34.74
40.00
22.01
15.55
20.33
18.35
30.39
25.07
12.36
20.76
28.17
20.10
27.02
16.48
18.36
21.35
17.90
25.02


MON.
NO.


2
5
8
11
14
17
20
23
26
29
32
35
38
41
44
47
50
53
56
59
62
65
68
71
74
77
80
83
86
89
92
95
98
101
104
107
110
113
116
119
122
125


DELTA(j)



18.98
15.91
28.97
37.64
23.09
61.85
55.42
40.32
28.86
28.76
17.20
31.11
20.08
37.14
34.42
33.87
18.28
24.88
22.26
26.58
17.57
20.02
31.09
31.31
19.81
49.34
14.97
21.17
19.08
25.03
20.99
24.29
29.31
28.77
21.82
23.96
16.02
20.39
17.98
15.74
16.32
24.35


MON.
NO.


3
6
9
12
15
18
21
24
27
30
33
36
39
42
45
48
51
54
57
60
63
66
69
72
75
78
81
84
87
90
93
96
99
102
105
108
111
114
117
120
123
126


DELTA(j)



42.58
31.99
19.48
27.06
23.26
42.47
45.48
28.71
32.20
25.40
29.10
31.41
29.68
50.16
44.00
25.03
29.86
22.12
25.81
25.34
32.97
28.34
30.15
33.53
39.67
39.38
34.44
21.21
21.51
23.96
36.18
26.11
24.16
28.23
27.40
14.58
29.49
22.95
30.78
23.49
24.94
25.02







APPENDIX D

BAY COUNTY

TABULATIONS OF (j) ON A MONUMENT-BY-MONUMENT BASIS








LISTING OF MONUMENT-BY-MONUMENT DELTA VALUES FOR BAY COUNTY


MON.
NO.


1
4
7
10
13
16
19
22
25
28
31
34
37
40
43
46
49
52
55
58
61
64
67
70
73
76
79
82
85
88
91
94
97
100
103
106
109
112
115
118
121
124
127
130


DELTA(j)



22.64
32.61
29.26
43.92
36.93
42.39
53.77
41.91
30.65
37.46
39.66
42.11
32.56
41.67
21.02
34.85
36.97
22.07
25.29
21.06
21.45
16.18
41.77
27.41
25.54
22.18
19.39
23.00
29.32
42.66
49.77
52.85
65.08
58.45
35.52
33.88
36.17
60.69
19.32
65.92
54.18
39.48
62.20
29.99


MON.
NO.


2
5
8
11
14
17
20
23
26
29
32
35
38
41
44
47
50
53
56
59
62
65
68
71
74
77
80
83
86
89
92
95
98
101
104
107
110
113
116
119
122
125
128
131


DELTA(j)



31.26
24.40
38.22
30.53
22.88
37.43
43.55
31.70
35.35
39.64
36.65
39.26
28.60
39.84
26.83
19.35
20.20
15.51
27.15
14.12
18.66
21.20
24.42
23.55
30.24
21.55
18.91
15.88
26.89
25.99
39.89
76.52
49.27
50.12
22.73
30.94
27.08
29.05
30.35
41.07
41.36
41.81
37.31
9.41


MON.
NO.


3
6
9
12
15
18
21
24
27
30
33
36
39
42
45
48
51
54
57
60
63
66
69
72
75
78
81
84
87
90
93
96
99
102
105
108
111
114
117
120
123
126
129
132


DELTA(j)



38.09
27.32
26.37
21.02
43.62
36.98
38.71
27.55
34.16
48.56
44.91
50.54
27.80
63.35
26.34
27.83
20.79
20.41
22.72
35.78
29.24
22.25
19.70
17.34
18.37
23.17
23.60
32.52
27.39
33.91
44.27
96.32
64.12
26.15
42.10
53.30
19.75
41.44
31.01
41.67
33.44
32.78
44.16
16.65








LISTING OF MONUMENT-BY-MONUMENT DELTA VALUES FOR BAY COUNTY
(continued)


DELTA(j)



9.39
20.88
21.15
22.45


MON.
NO.


134
137
140
143


DELTA(j)



10.73
36.96
29.21
13.58


MON.
NO.


135
138
141
144


DELTA(j)



13.66
22.40
21.74
13.29


MON.
NO.


133
136
139
142




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