Citation
High frequency shoreline changes for the panhandle area of Florida

Material Information

Title:
High frequency shoreline changes for the panhandle area of Florida
Series Title:
UFLCOEL
Creator:
Dean, Robert G ( Robert George ), 1930-
University of Florida -- Coastal and Oceanographic Engineering Dept
Place of Publication:
Gainesville Fla
Publisher:
Dept. of Coastal and Oceanographic Engineering, University of Florida
Publication Date:
Language:
English
Physical Description:
iv, 10 leaves : charts ; 28 cm. +

Subjects

Subjects / Keywords:
Shorelines -- Florida ( lcsh )
Seashore -- Florida ( lcsh )
Beach erosion -- Florida ( lcsh )
Coast changes -- Florida ( lcsh )
Florida Panhandle (Fla.) ( lcsh )
Genre:
non-fiction ( marcgt )

Notes

General Note:
"December 28, 1999."
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.

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University of Florida
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University of Florida
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The University of Florida George A. Smathers Libraries respect the intellectual property rights of others and do not claim any copyright interest in this item. This item may be protected by copyright but is made available here under a claim of fair use (17 U.S.C. §107) for non-profit research and educational purposes. Users of this work have responsibility for determining copyright status prior to reusing, publishing or reproducing this item for purposes other than what is allowed by fair use or other copyright exemptions. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. The Smathers Libraries would like to learn more about this item and invite individuals or organizations to contact Digital Services (UFDC@uflib.ufl.edu) with any additional information they can provide.
Resource Identifier:
85844958 ( OCLC )

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.


ii








TABLE OF CONTENTS


EXECUTIVE SUM MARY .................................................... ii

LIST OF FIGURES .......................................................... iv

LIST OF TABLES ........................................................... iv

1 INTRODUCTION ......................................................1

2 GENERAL BACKGROUND ............................................. 1

2.1 G eneral .........................................................1

2.2 Statistics of Shoreline Change ......................................3

2.2.1 G eneral ................................................... 3

2.2.2 Determination of T ......................................... 4

2.2.3 Determination of 8 ... ..................................5

2.2.4 Determination of 8,,,,(j) ....................................5

3 RECOMMENDED METHOD ............................................5

4 EXAMPLE OF APPLICATION ..........................................8

5 SUM M ARY ...........................................................9

6 REFERENCES .........................................................9


APPENDICES

A ESCAMBIA (AND SANTA ROSA) COUNTY

TABULATIONS OF 8,,,() ON A MONUMENT-BY-MONUMENT BASIS ... A-1 B OKALOOSA COUNTY

TABULATIONS OF 8,,,(j) ON A MONUMENT-BY-MONUMENT BASIS .... B-1 C WALTON COUNTY

TABULATIONS OF 85,,) ON A MONUMENT-BY-MONUMENT BASIS .... C-1 D BAY COUNTY

TABULATIONS OF 8,,() ON A MONUMENT-BY-MONUMENT BASIS ... D-1


iii








LIST OF FIGURES


FIGURE


PAGE


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


1
2


PAGE


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


iv


1
2
3








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 cause(s) 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 twodimensional 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


1










400


1900


Year


1950


Figure 1. Shoreline Positions For Monument R-125,
Escambia County


--0-- Data
-...... -.-.-. .-.Best Least Squares Fit (All D ata)
- - - - B e s t L e a s t S q u a re s F it (A ll D a ta )
----- BetLesesursFitAl aa
est st
- - - - - - - - - - -s - - ---Deviati n (Typ) uares-
- LBesti e ----- -

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


c: .2
C,)


.c
0




0
_r_


300 200 100


IL


0
1850


2000








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 (deterministic 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


y..=y,+Mi(Q t,+$ (1)

in which y; is the predicted shoreline location at time t0, mi is the shoreline change rate at the i'


3








location and bij 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, 8, can be decomposed further into two components as


I, + = ,1 (2)


where the term 8,., 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
S= E ..(3) 2k +1-k


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 i" location and jth time is represented as


yij =yi + M(t -tQ + / + (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, b5l/ 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, 6, and can be determined.

2.2.2 Determination of

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 8,, 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


4








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 61(termed "delprime" in Figure 2) and -8. (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 8i. (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 8i (= 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 b, i.e.


6.2= (a, (i))2 =82=82+8 /2 (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


5















U)>


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


-. . . . . . . . . . . . . . .:. .
_f tM h ii h ''Gf1 1 9 ..:..



-


0


- - - - - - - - - - . . . . .. . . . . . . . . . . . . . . . .. . .. . - -- - - - - - - - - - -
. . . . . :. .
- - - - - - - - - - - - - -- I - - - - - - - - - - - - - - - - ... . . . . . . . .
- -- - - --- - - - -- - - - - - - - - - -- - - -- -- I - - - - - - - - - - - - - - -
Delprime
- - - - - . . . . . . . . . . .
......... Delbar
- - - - --- - - - - . . . . . - - - - - - - - -
- - - - - - - - - . . . . . . . . .. 4 1 . . . . . . . . . . . . . . . . . . . . ... . . . . . . . . .
. . . . ... . . . . . . . . . . . . . . . . . . - - - - - . . . . .. . . . . . . . . ... . . . . .
-------------. . . . . . . . . . . . . . . . . . . . . . . .
-- - - - -
M_ AA A' --- A
V.V... v
V.. v .. ...... V V .. .....
--------- -: ........... V
H


--

Note: No Data Were Available....


100


120


140


160


180


200


Monument Number

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






50

. . . . . . . . - - - - - - - -. .. . . .. . . .
0
. . ... - - . . .,. ... .. . - - - -
40

4-3


31 0 -- -10

80 100 120 140 160 180 200 Monument Number


Figure 3. Variation of delij) Along Portions of Escambia County








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


RTR(j) =FTR 8.0


(6)


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

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


___ IF, for Return Periods, TR (years) Return Periods, 5 10 15 20 25 30 35
TR (years) I I

F, 1 0.97 1.40 11.61 11.75 11.86 11.96 2.00


Appendices A D presents the recommended values of 8(j)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 8,(j) from Page A-I of Appendix A is 37.0 feet. Thus applying Eq. (6) and the Fm values in Table 1, the shoreline recessions for the various return periods are presented in Table 2.


8








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, R (TRft)


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.


9








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.


10







APPENDIX A

ESCAMBIA (AND SANTA ROSA) COUNTY

TABULATIONS OF5 (j) 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


A-1


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


A-2


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 OF8S(j) 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


B-1


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 OF5S(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


C-1


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 OFS(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


D-1


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


D-2


MON. NO.


133 136 139
142