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Evaluation of Next Generation Beach and Dune Erosion Model to Predict High Frequency Changes along the Panhandle Coast o...

Permanent Link: http://ufdc.ufl.edu/UFE0022342/00001

Material Information

Title: Evaluation of Next Generation Beach and Dune Erosion Model to Predict High Frequency Changes along the Panhandle Coast of Florida
Physical Description: 1 online resource (120 p.)
Language: english
Creator: Sharp, Nicole
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: erosion, hurricane, profile, storm
Civil and Coastal Engineering -- Dissertations, Academic -- UF
Genre: Coastal and Oceanographic Engineering thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: High-frequency, or shorter-term, changes can pose a significant threat to coastal structures and development along the Panhandle of Florida. In order to help mitigate this threat, a new erosion model, NEXTGEN, has been tested in order to evaluate the applicability of this model for prediction purposes. Historic storms have been analyzed and results have been compared with available survey data. Statistical analyses were performed on the predicted results to evaluate the accuracy of the predictions and sensitivity of the model to input variables. Overall, analysis of the results obtained from the model confirms its reasonableness in predicting hurricane effects at the +10 foot contour in causing recession.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Nicole Sharp.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Dean, Robert G.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022342:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022342/00001

Material Information

Title: Evaluation of Next Generation Beach and Dune Erosion Model to Predict High Frequency Changes along the Panhandle Coast of Florida
Physical Description: 1 online resource (120 p.)
Language: english
Creator: Sharp, Nicole
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: erosion, hurricane, profile, storm
Civil and Coastal Engineering -- Dissertations, Academic -- UF
Genre: Coastal and Oceanographic Engineering thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: High-frequency, or shorter-term, changes can pose a significant threat to coastal structures and development along the Panhandle of Florida. In order to help mitigate this threat, a new erosion model, NEXTGEN, has been tested in order to evaluate the applicability of this model for prediction purposes. Historic storms have been analyzed and results have been compared with available survey data. Statistical analyses were performed on the predicted results to evaluate the accuracy of the predictions and sensitivity of the model to input variables. Overall, analysis of the results obtained from the model confirms its reasonableness in predicting hurricane effects at the +10 foot contour in causing recession.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Nicole Sharp.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Dean, Robert G.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022342:00001


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EVALUATION OF NEXT GENERATION BE ACH AND DUNE EROSION MODEL TO PREDICT HIGH FREQUENCY CHANGES ALONG THE PANHANDLE COAST OF FLORIDA By NICOLE SHELBY SHARP A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2008 1

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2008 Nicole Shelby Sharp 2

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To my mother and father 3

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ACKNOWLEDGMENTS I would like to thank my supervisory comm ittee chair, Dr. Robert G. Dean, for his continuous support and guidance. His insight an d knowledge into the subject is inspiring, and his time that he has spent with me over the past tw o years has been very insightful. I also thank Dr. Arnoldo Valle Levinson for serv ing on my supervisory committee. I would also like to thank Ja mie MacMahan for introducing to me the topic of coastal engineering. If it were not for his spirit and enth usiasm for the subject, I feel as though I would not be where I am today. Lastly, I cannot forget to tha nk my parents and my sister for their patience in my schooling process and for always answering the phone in my times of need. 4

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TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................7 LIST OF FIGURES .........................................................................................................................8 ABSTRACT ...................................................................................................................................11 CHAPTER 1 INTRODUCTION................................................................................................................. .12 Coastal Processes ....................................................................................................................12 Shoreline Forecasting .............................................................................................................14 Objective and Scope ...............................................................................................................15 2 LITERATURE REVIEW.......................................................................................................18 Mean High Water (MHW) Erosion Calculation Methods ......................................................18 Hurricane Model .....................................................................................................................19 Bathystrophic Storm Tide Model ...........................................................................................21 Shoreline Change Models .......................................................................................................23 3 METHODOLOGY.................................................................................................................2 9 Hurricane Model .....................................................................................................................29 Hurricane Storm Surge Model ................................................................................................30 NEXTGEN Erosion Model .....................................................................................................35 Contour Changes ....................................................................................................................36 Measured Contour Change ..............................................................................................36 Predicted Contour Change...............................................................................................37 Statistical Analysis of Results ................................................................................................38 Measured versus Predicted ..............................................................................................39 Measured 10 Foot Contour vers us Measured Zero Foot Contour ...................................39 4 RESULTS AND ANALYSIS.................................................................................................44 Measured Shoreline Change Results ......................................................................................44 Storm Surge Results ...............................................................................................................46 Cross-Shore Transport Model .................................................................................................49 Statistical Analysis of Data .....................................................................................................53 Measured 10 Foot versus Predicted 10 Foot Predicted Contour .....................................53 Measured 10 Foot versus Measured Zero Foot Contour .................................................54 Model Sensitivity to Input Variables ...............................................................................55 5

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5 CONCLUSIONS AND RECOMMENDATIONS.................................................................77 Summary and Conclusions .....................................................................................................77 Storm Surge Model ..........................................................................................................77 Measured Contour Change ..............................................................................................78 Representation of High-Frequency Shoreline Changes ..................................................78 Recommendations for Future Study .......................................................................................79 Storm Surge Model ..........................................................................................................79 Measured Contour Change ..............................................................................................79 Representation of High-Frequency Shoreline Changes ..................................................80 APPENDIX A STORM SURGE HYDROGRAPHS.....................................................................................81 B NEXTGEN PROFILE E VOLUTION RESULTS..................................................................87 LIST OF REFERENCES .............................................................................................................117 BIOGRAPHICAL SKETCH .......................................................................................................120 6

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LIST OF TABLES Table page 4-1 Comparison between predicte d and measured storm surge ...............................................72 4-2 Individual setup values and maximum adjusted surge......................................................73 4-3 Individual R-squared and r values of pr edicted versus measured +10 contour change for six common profiles in each storm event .....................................................................74 4-4 Individual R-squared values for measured +10 contour change versus measured zero contour change for each storm event .................................................................................75 4-5 Predicted average change of +10 contour from NEXTGEN model for the three cases of storm surge ....................................................................................................................76 7

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LIST OF FIGURES Figure page 1-1 General location of study area and De partment of Environmental Protection monuments. ........................................................................................................................17 2-1 Sketch of idealized hurricane model. .................................................................................27 2-2 Basic concepts for Kriebel and Deans erosion model ....................................................28 3-1 Definition sketch of hurricane catchment zone. .............................................................41 3-2 Geometric sketch of rot l and coordinate system. ........................................................42 3-3 Example sketch of and s lnew .......................................................................................43 4-1 Average +10 and zero foot contour change over nine common Monuments. ...................57 4-2 Zero foot contour accretion due to large storms. ...............................................................58 4-3 Predicted storm surge hydrograph for Hurricane Eloise. ...................................................59 4-4 Plot of maximum predic ted un-scaled surge versus maximum measured surge at location of maximum surge...............................................................................................60 4-5 Measured storm surge hydrograph for Hurri cane Eloise from historical tide gage data. ....................................................................................................................................61 4-6 Measured storm surge hydrograph fo r Hurricane Opal from NOAA CO-OPS database. .............................................................................................................................62 4-7 Measured storm surge hydrograph fo r Hurricane Ivan from NOAA CO-OPS database. .............................................................................................................................63 4-8 Measured storm surge hydrograph fo r Hurricane Dennis from NOAA CO-OPS database. .............................................................................................................................64 4-9 Storm surge comparison between scaled and un-scaled values from one-dimensional model. .................................................................................................................................65 4-10 Adjusted maximum predicted surge ve rsus maximum measured surge at Walton County................................................................................................................................66 4-11 Example profile response from th e NEXTGEN model for Hurricane Eloise. ..................67 8

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4-12 Comparison of measured and predicted recessions of the +10 foot contour. Cumulative values are presented for Erin and Opal because no intermittent surveys are available to quantify individual measured recession. ..................................................68 4-13 Plot of predicted erosion versus measured erosion for individual profiles (6) all storm events (5). ...........................................................................................................................69 4-15 Comparison of measured and predicted reces sions of the +10 foot contour with error bars to account for the sensitivity of the model outpu t due to storm surge scaled such that the peaks varied by +/1 foot. ............................................................................71 A-1 Predicted storm surge hydrograph for Hurricane Eloise from one-dimensional storm surge model. .......................................................................................................................81 A-2 Predicted storm surge hydrograph for Hurri cane Erin from one-dimensional storm surge model. .......................................................................................................................82 A-3 Predicted storm surge hydrograph for Hu rricane Opal from one-dimensional storm surge model. .......................................................................................................................83 A-4 Predicted storm surge hydrograph for Hurricane Georges from one-dimensional storm surge model. .............................................................................................................84 A-5 Predicted storm surge hydrograph for Hurricane Ivan from one-dimensional storm surge model. .......................................................................................................................85 A-6 Predicted storm surge hydrograph for Hu rricane Dennis from one-dimensional storm surge model. .......................................................................................................................86 B-1 Calculated profile evolution fo r Monument 21 for Hurricane Eloise. ...............................87 B-2 Calculated profile evolution fo r Monument 57 for Hurricane Eloise. ...............................88 B-3 Calculated profile evolution fo r Monument 63 for Hurricane Eloise. ...............................89 B-4 Calculated profile evolution fo r Monument 66 for Hurricane Eloise. ...............................90 B-5 Calculated profile evolution fo r Monument 87 for Hurricane Eloise. ...............................91 B-6 Calculated profile evolution fo r Monument 102 for Hurricane Eloise. .............................92 B-7 Calculated profile evolution fo r Monument 21 for Hurricane Erin. ..................................93 B-8 Calculated profile evolution fo r Monument 57 for Hurricane Erin. ..................................94 B-9 Calculated profile evolution fo r Monument 63 for Hurricane Erin. ..................................95 B-10 Calculated profile evolution fo r Monument 66 for Hurricane Erin. ..................................96 9

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B-11 Calculated profile evolution fo r Monument 87 for Hurricane Erin. ..................................97 B-12 Calculated profile evolution fo r Monument 102 for Hurricane Erin. ................................98 B-13 Calculated profile evolution fo r Monument 21 for Hurricane Opal. .................................99 B-14 Calculated profile evolution fo r Monument 57 for Hurricane Opal. ...............................100 B-15 Calculated profile evolution fo r Monument 63 for Hurricane Opal. ...............................101 B-16 Calculated profile evolution fo r Monument 66 for Hurricane Opal. ...............................102 B-17 Calculated profile evolution fo r Monument 87 for Hurricane Opal. ...............................103 B-18 Calculated profile evolution fo r Monument 102 for Hurricane Opal. .............................104 B-19 Calculated profile evolution fo r Monument 21 for Hurricane Ivan. ................................105 B-20 Calculated profile evolution fo r Monument 57 for Hurricane Ivan. ................................106 B-21 Calculated profile evolution fo r Monument 63 for Hurricane Ivan. ................................107 B-22 Calculated profile evolution fo r Monument 66 for Hurricane Ivan. ................................108 B-23 Calculated profile evolution fo r Monument 87 for Hurricane Ivan. ................................109 B-24 Calculated profile evolution fo r Monument 102 for Hurricane Ivan. ..............................110 B-25 Calculated profile evolution fo r Monument 21 for Hurricane Dennis. ...........................111 B-26 Calculated profile evolution fo r Monument 57 for Hurricane Dennis. ...........................112 B-27 Calculated profile evolution fo r Monument 63 for Hurricane Dennis. ...........................113 B-28 Calculated profile evolution fo r Monument 66 for Hurricane Dennis. ...........................114 B-29 Calculated profile evolution fo r Monument 87 for Hurricane Dennis. ...........................115 B-30 Calculated profile evolution fo r Monument 102 for Hurricane Dennis. .........................116 10

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Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science EVALUATION OF NEXT GENERATION BE ACH AND DUNE EROSION MODEL TO PREDICT HIGH FREQUENCY CHANGES ALONG THE PANHANDLE COAST OF FLORIDA By Nicole Shelby Sharp August 2008 Chair: Robert G. Dean Major: Coastal and Oceanographic Engineering High-frequency, or shorter-term, changes can pose a significant threat to coastal structures and development along the Panhandle of Florida. In order to help mitigat e this threat, a new erosion model, NEXTGEN, has been tested in orde r to evaluate the applicability of this model for prediction purposes. Historic storms have been analyzed and results have been compared with available survey data. Statistical analys es were performed on the predicted results to evaluate the accuracy of the predictions and sensitiv ity of the model to input variables. Overall, analysis of the results obtained from the m odel confirms its reasonableness in predicting hurricane effects at the +10 f oot contour in causing recession. 11

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CHAPTER 1 INTRODUCTION Coastal regions are the most developed areas within the Un ited States. It has been estimated that 139 million people are currently living along the coast, and by 2015, the coastal population will reach 165 million (Cu llington et al., 1990). The coasta l zone of the United States can be described as the land regi on that is approximately 31 miles from the coast. Overall, 53 percent of all Americans live wi thin 50 miles of the coastlin e (Edwards, 1989). Living within the dynamic coastal system comes with inherent dangers; property owners are constantly threatened by shoreline retreat due to wind, wave s, and hurricanes. With such a large population in the U.S. living near our shorelines, it is impor tant that we be able to accurately predict the location of our shorelines for land-use pl anning and for the safety of human life. Coastal Processes Coastal erosion is the result of many processes both on larg e and small scales. Some of these processes have a great d eal known about them, while othe rs are still yet to be fully understood. Some coastal proce sses are actually beneficial and cause coastal land to be reclaimed from the ocean; however, most processe s lead to erosion which is detrimental to the beach and structures in the way. The erosion th at can be seen when one steps out on the beach can be the result of two causes: humans or nature. Erosion due to humans can be attributed to co astal structures such as inlets, groins, and seawalls. In some countries, mining of sand fr om the active nearshore region is still allowed. Additionally, structures placed in the coastal sy stem for erosion mitigation can have unintended adverse effects on the nearshore system. These stru ctures interrupt the natu ral sediment flow of the system and oftentimes erosion is the end result of the modification to the coastal system. As coastal engineers, it is our job to attempt to mitigate this erosional tendency and to return a 12

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natural equilibrium to the system. Systems su ch as sand bypassing plants have been used by coastal engineers to help reinst ate, to the degree possible, the natural flows within the dynamic system. Along with humans altering the dynamic coastal system, nature has its own accretional and erosional tendencies and cycles. During the winter months, the beach tends to have a bar profile characterized by a narrow and steep beachface. This is due to the highly energetic winter waves causing the beach to lose its fine material to offs hore bars. As the season changes to the summer, the waves tend to decrease in energy which allo ws the berm to grow in width by sand being transported landward. This latter type of beach profile is norma lly designated as the berm or summer profile (Dean and Dalrymple, 2002). Al though the bar and berm profiles are fairly predictable seasonal events, hur ricanes and extreme storm even ts are highly unpredictable erosional events and cause profiles similar to th e winter waves with a dditional impact to the higher contour. Much of the natural impact seen within the coastal system is caused on the short-term time scale by hurricanes or extreme winter storms whic h have a longer recovery period than that of the seasonal processes. In a majority of thes e extreme events, the storm surge, high waves, and wind can be the cause of most of the damage that occurs. Although the high waves and wind can cause a substantial amount of damage to a beac hfront property, it is the storm surge combined with the high waves that is the most co stly and deadly component of the storm. The coastal impact due to high storm surges can be devastating. The storm surge can flood land and greatly alter the shoreline within the affected area. Genera lly, on the Panhandle of Florida, storm surges can range up to 15 or more feet. However, a maximum storm surge of 25 has been reported in Mississipp i due to Hurricane Katrina in 2005 (Fritz et al, 2007). The storm 13

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surge can be broken down into four components. The strong winds associated with a hurricane are responsible for the first component of the st orm surge. These winds create shear stresses on the water surface which push the water ahead of th e storm until it is forced to pile upon the beach. The next component of su rge, wave setup, primarily occurs in the breaking wave zone in shallow water and causes an increase in the mean water level due to transfer of momentum from the breaking waves to the water column. In addition to the onshore shear stress, the winds from a hurricane also create longshore cu rrents, the third component of storm surge. The longshore current causes a force (the Coriolis force) which can either augment or reduce the overall surge. The final component of the storm surge is barometr ic tide in response to the barometric pressure reduction in the low pressure storm. The extreme low pressure in the eye of the storm acts as a suction and draws up the water surf ace in the affected re gion. Of the four components, most of the surge is attributed to the wi nd stresses (Dean and Dalrymple, 2002). Shoreline Forecasting The primary application of shoreline position data is to understand the natural and/or altered characteristics of a coastal area of intere st to develop an improved basis for management and design alternatives. One application is by la nd-use planners to esta blish regulatory coastal construction setbacks. In general, about one-third of all coastal states use shoreline-change data as a basis for setting regulatory coastal setbacks (Na tional Research Council, 1990). Regulatory setbacks and restrictions genera lly vary from state to state and are calculated by using the average annual erosion rate (AAER) at a specif ic location. This AAER is then multiplied by a specific number of years, and the computed setback is established. Recently, due to an increased interest in the re sponse of the coastline due to hurricanes, it is now necessary to be able to accurately id entify the impact of a storm on shoreline position. The shoreline location must be predicted accurately by a shoreline erosion model. Ideally, this 14

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model must be verified against historic storms to confirm accuracy of the results. Once the models accuracy has been confirmed, it will then be able to be applied to various surge levels and durations. Regulatory and management interests would then be able to apply this capability along with return periods of stor ms in order to establish coas tal setbacks from the predicted erosion data. Objective and Scope The main objective of this thesis is to ev aluate the profile resp onse model, NEXTGEN, and evaluate the model validity in predicting dune erosion. To achieve this goal, a storm surge model will be modified in order to predict the required storm surge input to NEXTGEN. Historic hurricanes will be sele cted and measured erosion from the hurricanes will be compared with the forecast contour change. Statistical an alyses will also be performed on the data to confirm the accuracy of the pred icted results against measured. The scope of the project is th e Panhandle counties of the Flor ida coast, with an emphasis on Walton County. Figure 1-1 illu strates the study area. The time period associated with the project ranges from 1872 to pr esent, with an empha sis on the 1975 to present data. The study area is located on the northern Gulf coast of Florida. Typically, th e area is associated with low wave and tide energy. Wave periods tend to have magnitudes of 6.0 seconds of less. The tides found within the Panhandle are mostly diurnal with a range of less than 1.6 feet (Morang, 1992). The measured seasonal variati on experienced in Wa lton County is approximately 30 feet annually. In the past 33 years, the study area has been impacted by nine major storms. Due to this large number of storms, the study area is in a criti cally eroded state. The Florida Department of Environmental Protection defines a critically eroded area as 15

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critically eroded area is a segment of the shoreline wh ere natural processes or human activity have caused or contributed to erosion and recession of the beach or dune system to such a degree that upland development, recrea tional interests, wildlife habitat, or important cultural resources are threatened or lost. Critically eroded areas may also include peripheral segments or gaps between identified critically eroded ar eas which, although they may be stable or slightly er osional now, their inclusion is necessary for continuity of management of the coastal system or for the design integrity of adjacent beach management projects. The main threat attributed to cr itical erosion that applies to th e Panhandle study area is recession that could damage upland development and structures In all, there are ei ght sections of Walton County that make up 14.3 miles of critically eroded s horeline resulting in 57% of the County shoreline with this designation (Bureau of Beaches and Coastal Systems, 2007). 16

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Figure 1-1. General location of study area and Department of Environmental Protection monum ents [Reprinted with permission from Foster, E.R. 2000. Shoreline Change Rate Estimates: Walton County. Repor t No. BCS-2000-02 (Page 4, Figure 1). Office of Beaches and Coastal Systems, Florida Department of Environmental Protection, Tallahassee, Florida.] 17

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CHAPTER 2 LITERATURE REVIEW Mean High Water (MHW) Erosion Calculation Methods Shoreline position is one of the most commonly available coastal descriptors available to coastal engineers and provides the basis for quantifying shoreline ch ange rates. The calculated rates can be applied to classify areas of hi gh hazard and erosion along the coastline (Dolan, Fenster, and Holme, 1991). There are many met hods utilized to calculate erosion rates by coastal engineers, scientists, and land planners. Although all methods to be discussed can predict a shoreline position at a future time, some me thods produce more reliable results than others. The simplest method used to calculate shorelin e rate-of-change is th e end point rate (EPR) method. This method uses a simple calculation i nvolving just two shoreline positions. Here, the total distance of shoreline change is divide d by the elapsed time. The two points used to calculate a rate-of-change are usually the earliest and latest data points (Genz et al, 2007). The advantage of this method is ease of calculati on and its common use among many State agencies (Dolan, Fenster, and Holme, 1991). The main di sadvantage for utilizing this method is that major shoreline changes that oc cur between the two time periods are disregarded by using the earliest and latest points. A second method that is used commonly by engi neers, scientists, and planners is linear regression (LR). With LR, a best fit line is calculated using th e method of Least Squares. The slope from the best fit line is th en used as an estimate of shor eline change rate. Unlike the EPR method, LR uses all available data points for shor eline position. The main disadvantage of this method occurs when the data sets are clustered. This can cause the clustered data to have more of an effect on the regression than the less gathered shoreline positions (Dolan, Fenster, and Holme, 1991). 18

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Foster and Savage (1989) developed the av erage of rates (AOR) method in order to calculate shoreline changes This method calcula tes individual EPRs for all shoreline position data, and averages them to determine a shoreline change rate. It is r ecommended, however, that this method not be used as a computational method alone. It is most commonly used with LR as a means to verify results. There are several other more complex methods that are currently available, but not as widely used as the three listed above. The Jackknifing (JK) method is similar to that of LR, but it uses multiple linear regression s to find a shoreline change rate (Genz et al, 2007). Fenster, Dolan, and Elder (1993) adapted the minimum de scription length (MDL) method as a way to identify influential short-term changes. This method does not assume a linear trend and uses a non-linear polynomial that best fits the data (C rowell, Douglas, and Letherman, 1993). The main disadvantages of the latter two me thods are in the complexity of calculations needed in order to find the rate of change. Hurricane Model The hurricane model utilized throughout this thesis was developed by Wilson (1957) and consists of a parameterized pressure field along with a wind field. The assumptions made within the model are that the pressure field is perfectly symmetrical with circular isobars. The pressure field is defined by the equation /()Rr oo p pppe (2-1) where o p is the central pressure, p is the ambient atmospheric pr essure that is unaffected by the hurricanes influence, R is the radius to maximum winds, and r is the distance from the hurricane center to point of interest. 19

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Wind velocities over the ocean are described in terms of three different velocities. The first of these is the cyclostrophic wind, defined as / Rr c apR U r e (2-2) where p is the difference in pressure between the am bient pressure and the central pressure and a is the density of air. The geostrophic wind velocity, g U is defined as / 22sinRr a gpR e r U (2-3) where is the angular velocity of rotation of the earth and is the latitude of the point of interest. In order to calculate the gradient wi nd speed, the wind speed at 30 feet above the water surface, the parameter must first be found by 1sin 2c cgU V UU (2-4) where V is forward velocity of the hurricane and is the angle of bearing of the point of interest. is further defined in Figure 2-1. Th e gradient wind speed is then defined as 20.83(1)GcUU (2-5) which accounts for the frictional effect of the water surface. Holland (1980) developed a parametric hurrican e model that utilized concentric pressure and wind profiles to define a standard hurricane. The model is similar to that of Wilson, but it utilizes a scaling parameter B that affects the radial reach of the maximum winds. Typical values of B can range from 1.0 to 2.5. The defining formulas for Hollands model are (/)()RrB ooprpppe (2-6) 20

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1/2 2 (/)() 22B RrB cc o arfrf BR Vr ppe r (2-7) where p(r) is the pressures at a distance r from the hurricane, and V(r) is the gradient wind at a distance r from the hurricane. The other variab les have been previously defined by Wilsons hurricane model. Bathystrophic Storm Tide Model Freeman, Baer, and Jung (1957) developed a si mple one-dimensional storm surge model termed the bathystrophic storm tide model. This model considers the governing equations along a single transect oriented perpendicular to the shore. The model is based on the following four assumptions which reduce the model to a time-dependent problem which can be solved at each point with the wind history considered to be known. 1. There is little or no cross-shore transport. 2. There is no significant change in the height to the water surface due to the divergence of the velocity field. 3. The variations in the alongshore direction are negligible. 4. The spatial derivatives of the longshore current are small enough to be neglected with respect to the Coriolis parameter. Using the above assumptions, the governing equa tions of the model are found by integrating over depth to obtain 11 ()sx cy ww p fq x gh gx (2-6) 1y s yby wq t (2-7) where is the water surface elevatio n, x and y are normal and pa rallel to the shoreline, g is gravity, h is local undisturbed water depth, s is the shear stress at th e water surface due to wind, 21

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w is the density of water, c f is the Coriolis parameter, q is the volumetric flow per unit width, p is the atmospheric pressure, and b is the shear stress due to bottom friction. Equation 2.6 allows for a hydrostatic balance of the forces associated with the surge in the cross-shore direction with the time dependent Coriolis indu ced flow in the alongshore direction and the shear stresses due to the wind in the x (onshore) direction. Equatio n 2.7 is a balance between the surface and bottom shear stresses in the alongshor e direction and the inertial force in the alongshore direction. Dean and Chui (1982) developed a two-dimensional model based on more complete representations of the equations of motion a nd a one-dimensional model from the governing equations developed by Freeman, Baer, and Jung. The two-dimensional model was applied to calibrate the one-dimensional model. Both models were calibrated against tide gage measurements. Although this thesis utilizes a one-dimensi onal model only, it is important to note that there are many two-dimensional models available. These models are more complex and require more resources. Such examples of the more complex models are the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model develope d by Jelesnianski, Chen, and Shaffer (1992) which is utilized by the National Weather Service. This model runs on a cylindrical grid system and incorporates some nonlinearities into the calculations. Luettich and Westerink (1992) developed the ADvanced CIRCulation (ADCIRC) Finite Element Hydrodynamic Model for Coastal Oceans, Inlets, Rivers and Floodplains. Th is model simulates the rise in water levels in any area of interest. ADCIRC is a two-dimensional model that solves the depth-integrated equations of momentum and continuity within a time domain. The U.S. Army Corps of 22

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Engineers and a number of other entities apply th is model to predict water levels in the United States and internationally. The more complex models mentioned above are primarily used within the United States, however, it is important to note ot her reputable models th at are utilized by European countries to predict storm surge. The Danish developed MIKE 21 which is a model that simulates currents, waves, and ecology within inland waters, coasta l areas, and seas. The hydrodynamic portion of the model simulates the water level variations due to various forcing processes. The water level response is found through the depth integrated equations of continuity and momentum on a grid system covering the coastal area (Danish Hydrau lic Institute, 2008). The Dutch have developed Delft 3D which has the ability to simulate two and three-dimensional flow, waves, morphodynamics, and water quality. Along with calculating the individual effects, the model has the capability of handling interactions of the processes mentioned ab ove (Delft Hydraulics, 2001). Shoreline Change Models The GENESIS shoreline change model (Hanson, 1989) is a one-line numerical planform model designed to predict long-term shoreline changes associated with coastal engineering structures or beach nourishment projects whic h perturb the nearshore system. The model has been generalized in comparison to previous mode ls so that it can be applied to most sandy coastlines. There are two governing equations: a co nservation equation and a transport equation. The conservation of mass equation is 1 0BcyQ q tDDx (2-9) 23

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where y is the shoreline position, t is the time, x is the longshore coordinate, is the berm height above mean water level, is the depth of closure, Q is the longshore transport rate, and q represents sources or sinks along th e coast. The longshore transport, Q in Equation 2.9 is based upon the CERC longshore transport formula. The equation can be expressed as follows BD cD 2 12()(sin2cos ) g bb sb sH QHCaa b x (2-10) where H is significant wave heig ht, Cg is wave group velocity, the b subscript denotes breaking wave condition, and bs is the angle of wave crests to the shoreline. The non-dimensional coefficients and are defined as 1a 2a 1 1 5/216(/1)(1)1.416sK a p (2-11) 2 2 5/28(/1)(1)tan1.416sK a p (2-12) where and are calibration parameters, 1K 2K s and are the densities of sand and water, p is the sediment porosity, and tan is the average bottom slope from the shoreline to the depth of minimal longshore transport. The factor of 1.416 is a conversion between significant and RMS wave heights. Larson and Kraus (1989) developed the SBEA CH numerical model to predict storminduced beach and dune erosion. The important feature included within this model is the capability to reproduce the main morphologic featur es of the beach profile, such as bars and berms. The assumptions made by the authors of the model are 1. Profile change is the result of crossshore processes due to breaking waves. 2. There is no net loss or gain of material. 24

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3. The rate of longshore transport is based upon empirical calculations from wave tank experiments. 4. Longshore processes are uniform and not considered. Like GENESIS, the model is based on the cons ervation of mass equati on where cross-shore transport rates are required. However, these rates can be either theoretical or from an empirical rate formula. Kriebel and Dean (1985) developed a two-di mensional model to predict beach and dune erosion during major storm events. The model us es a simplified set of governing equations for beach profile evolution, the complete time hist ory of the storm surge, and a more realistic representation of the beach prof ile in order to predict the sh oreline evolution. Figure 2-2 illustrates the basic concepts of the model. The model represents the general equilibrium profile by a curve that has been defined as 2/3hAx (2-13) where h is water depth related to some distance, x offshore. The parameter A depends on sediment size and governs the profile steepness a nd is related to the equilibrium wave energy dissipation per unit volume, within the surf zone. *D The model represents profile evolution thr ough the concept that a profile will attain a dynamic equilibrium for a given surge and wave conditions after a certain amount of time. Using this assumption, the net transport rate is assumed to be proportional to the disequilibrium of wave energy dissipation that is occurring at all points across the surf zone. Through these concepts, and through shallow wa ter wave theory, the cross-s hore sediment transport rate, Q is determined by the model through the difference between the actual and equilibrium levels of wave energy dissipation per unit vol ume throughout the surf zone, or by *( QKDD ) (2-14) 25

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where D and D are the actual and equilibrium time-dependent energy dissipation per unit volume, and K is a transport rate coefficient which is determined empirically. Using the calculated transport rate, the time-dependent prof ile evolution is determined by the equation of conservation of sand over a profile by an implicit finite-difference solution which is defined as x Q th (2-15) where x is the distance offshore to the depth, h 26

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Figure 2-1. Sketch of idealized hurricane model. 27

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Figure 2-2. Basic concepts for Kriebel and Deans erosion model [Reprinted with permission from Dean, R.G. 1986. Verification study of a dune erosion model. Shore and Beach 54(3), (Page 14, Figure 1).] 28

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CHAPTER 3 METHODOLOGY The primary objective of this thesis is to evaluate the accuracy of new erosion methodology in predicting high-frequency changes along the Panhandle of the Florida coast. The main long-term goal is to be able to accurately predict how beach profiles respond to major storm events, especially hurricanes. Several hi storic storms will be studied along with various contour changes associated with these storms, and from this information, a deterministic/statistical approach will be taken in order to evaluate the predicted results within the study area. The input data required to cal culate contour positions for th e profile response model and for the bathystrophic storm tide model was obtained from the Bureau of Beaches and Coastal Systems (BBCS) of the Florida Department of Environmental Protection (FDEP) (http://www.dep.state.fl.us/beaches /). The profile change model utilizes as input the initial profile and storm surge time history. To pred ict storm surge, hurricane track information was obtained from the National Hurricane Centers website (http://www.nhc.noaa.gov/pastall.shtml) in the Hurricane Best Track Files (HURDAT) directory. The information within the HURDAT file contains six hourly hurrica ne center locations in longitude and latit ude, intensities in maximum one minute surface wind speeds in knots, and for some storms, minimum central pressure in millibars for all Tropical Storms a nd Hurricanes in the Atlantic from 1851-2006. Hurricane Model In order to calculate the storm surges for individual hurricanes w ithin our study area, a hurricane program was modified to compute th e following parameters for the one-dimensional storm surge model: Hurricane position, translatio nal speed, translational direction, radius to 29

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maximum winds and pressure deficit. All values within the model are referenced with respect to a defined offshore origin. The program has been modified from its prev ious form in two ways. The first alteration of the program is to include a f ilter that selects hurricanes within a selected radius to the study area and disregards the hurricanes that occur outsi de this catchment area. The designated area is limited to 100 miles to the west of Walton County and 50 miles to the east of Walton County. Figure 3-1 provides a detailed sk etch of the catchment area. The second modification to the program is a cha nge in the coordinate system. Previously, the model had employed a left-hand coordinate sy stem; however, for our study area, the use of a right-handed system was desired. The coordinate system has also been aligned relative to the nominal coastline, and the storm coordinates determ ined from the program are also relative to this coordinate system. Figur e 3-2 provides a sketch of th e offshore coordinate system. Hurricane Storm Surge Model The hurricane storm surge model utilized throug hout this thesis was first obtained from the Florida Department of Environmental Protectio ns (FDEP) Bureau of Beaches and Coastal Systems (BBCS). The model has been altered from the original version to allow individual realworld hurricane parameters instead of rando m model hurricane parameters. The model determines the storm tide by combining calculations of wave setup, wind stress tide, barometric tide, and the Coriolis tide at grid and selected time increments 1 For calculation purposes, the model requires input of the followi ng parameters: hurricane position, pressure deficit, forward velocity, and translational dir ection. The model uses the hu rricane characteristics from the 1 The astronomical tide has not been accounted for at this point, but it is included in the final values of adjusted storm surge. 30

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hurricane track model and advances the hurricane along a track in accordance with HURDAT specifications. Theory. The governing expressions of the one-dimensional model in finite difference form are 11 11 1 1 1()i inn x nn n ii ii cy ww i p p x fq gh g (3-1) 11iinn yy wt qq BB iy (3-2) 21.0 ()in y itqf BB h (3-3) where iis grid location, n is the corresponding time step, and f is a Weisbach-Darcy bottom friction factor taken as 0.0025. The remaining te rms have been previously defined in Chapter 2 in the description of Freeman, Baer, and Jungs (1957) one-dimensional bathystrophic surge model. Continuing with the hurricane track model above, x is defined as the cross-shore location and is positive landward. The only boundary condition needed in the model is the seaward boundary condition of water surface displacement due to the barometric tide. This boundary condition is defined as 1 1 w p p g (3-4) where the subscript one represents the most seaward point for each transect. Initial conditions for the model include a condition of rest where is equal to zero a nd a zero water surface displacement. yq 31

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As mentioned above, the main governing e quations for the one-dimensional program contain the four components of surge that were described in Chapter 1. The Coriolis tide is represented within the parenthesis in the first part of Equation 3-1 by cyx f q gh (3-5) where c f is the Coriolis parameter. The Coriolis parameter is equal to 2sin where is the angular rotation of the earth ( 57.27210 rad/s), and is the latitude of Walton County (30). This portion of the storm surge can be critical if the alongshore cu rrent and the Coriolis force act in the same direction, but the Coriolis contri bution can reduce the storm induced surge if the current is flowing in the opposite direction. The barometric pressure term within the model is defined by 1ii w p p g (3-6) where the change in pressure is measured in poun ds per square foot (psf). Commonly, the surge contributed by the barometric pressure is consider ably smaller that the wind stress contribution. The wind stresses, as mentioned in Chapter 1, are normally the largest contributor to the storm surge. The contribution of wind stresses is represented in the model in the first part of Equation 3-1 by ()x wx gh (3-7) where x is the wind shear stress in th e cross-shore direction. The wind shear stress is defined as 2sin x wkW d (3-8) 32

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where k is the Van Dorn friction factor. Numer ous studies have been conducted for the relationship for k and the value employed herein is 6 2 661.210 1.2102.25101ck W W c cWW WW (3-9) where is the critical velocity (23.6 feet per seco nd). The friction factor usually has smaller values for mild winds and a greater value for la rger winds due to the in creased roughness of the water surface. The quantity cW d in Equation 3-8 is defined as ds l n e w (3-10) where s lnew is defined by s lnewrotl (3-11) where rot is the orientation of the shoreline to which the axes are rotated such that the x axis is shore normal, and l is the orientation of the shoreline at th e transect of interest that is read in from the input data file. The angle is defined in Figure 3-3 and is the angle between the shore normal x-axis and the wind vectors. Figures 3-2 and 3-3 illustrate the geometry of the angles referred to in Equation 3-10 and 3-11. The last component of storm surge calculated in the program is the total wave setup, wsu This term is defined as 20.191.02.82ob wsu bH H gT (3-12) 33

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where is breaking wave height and is the deepwater wave period. In order to apply the equation above, the Bretschneider relationship is used to find From this relationship, the following equation is obtained bH oT maxH (/100) max max0.208 16.51Rp FV He U (3-13) where R is the radius of maximum winds in nautical miles, p is the central pressure deficit, is the forward velocity of the hurricane in knots, and is the maximum wind speed in knots. The local deepwater wave height is determined from local winds, U and maximum hurricane winds, The deepwater significant wa ve height is represented by FV maxU maxU 2 max 2 max oU HH U oHd (3-14) The breaking wave height, is based on the deepwater significant wave height and approximated by bH 0.936bH (3-15) By substituting the value found from Equation 3-15 into Equation 3-12, the total wave setup is found and added to the storm surge at each time step in the shoreward grid. The volumetric longshore transport rate repr esented by Equation 3-2 is caused by wind stresses acting parallel to the coastline of intere st. Like the calculation for the wind stress tide, the volumetric transport rate is determined by sh ear stresses in the longsho re direction which are represented by the following 2cosywkW (3-16) 34

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The negative sign within Equation 3-16 is due to our coordinate system and reverses the direction of the wind stresses to be compatible with the positive onshore coordinate system. NEXTGEN Erosion Model After developing a storm surge history for our area of interest, it was then necessary to apply a cross-shore sediment transport model that could predict profile evolution due to a storm tide and elevated waves. The cross-shore transport model used within the study is the twodimensional Next Generation Beach and Dune Erosion Model, also known as NEXTGEN, developed by Dean (2004). The model contai ns both a sediment tr ansport equation and a continuity equation to re present processes in nature. The mo dels input requires a beach profile for our study area of interest, a storm surge hist ory, and the following parameters that define beach and storm characteris tics within the study area: Sediment transport coefficient Exponent in transport equation Onshore limiting slope Offshore limiting slope Beach face slope (associated with erosion) Time increment Wave height The NEXTGEN model was run with the defa ult values recommended by Dean in the programs users manual. This allowed the study to prove the applicabil ity of the model to various study areas and historic storms. The model utilized a recommended wave height of 10 feet, which affects the offshore depth to which sedi ment is moved. By using the 10 foot wave height, the predicted amount of erosion or acc retion experienced during the storm could be affected. This could possibly result in some error being factored into cross-shore transport calculations. 35

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Theory. As mentioned above, the cross-shore sediment transport equation within the model is defined as 1 MQKDDDD (3-17) Where Q is the cross-shore transport rate, K is the sediment transport coefficient, D is the wave energy dissipation per unit volume, M is an exponent that partia lly governs the rate of profile evolution, and is the equilibrium value of wave energy dissipation per unit volume. The values of M and K are 2.0 and 0.005, which are defined in the input file. *D The continuity equation within the model allo ws for a conservation of sand and is defined as hQ tx (3-18) where h is the depth at the center of a grid. E quation 3-18 is coupled wi th Equation 3-17, and both are solved simultaneously. The profile is u pdated after each computation, and the equations are repeated until completion of the simulation. Contour Changes Measured Contour Change To quantify the historic beach profile cha nges over time, methodology was developed to interpolate the contour changes at different elevations. This was accomplished by locating the shoreline position at each zero foot contour and +10 foot cont our for each desired monument within the study area. The shoreline position was found by ,1 11 1imi contouri ii iizh yyyy hh (3-19) where i is the location, m indicates measured, y is the cross-shore coordinate, h is the elevation, and z is the desired elevation of the contour line. Equation 3-19 delivers a single contour 36

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location for one individual monument. In some cases, two +10 foot contours were present within the dataset. This was accounted for in the contour change methodology by allowing the model to read in all data and retain the most seaward valu e of the +10 foot contour. In order to obtain an average contour for all monuments at one pe riod in time, the following equation was used ,_ 11mn contouravg contour iy n i mym s t o r m (3-20) where n is the number of monuments within the study area. Once an average contour location was found for a given elevation, it was then desired to determine the contour change ba sed on the initial pre-storm pr ofile and the co rresponding poststorm profile for the selected time segment. The change in the contour position is m poststorm prestorm mcontourcontour contouryyy (3-21) Equation 3-21 can be used for all individual contour positions at one time or for average position at one time. Predicted Contour Change Once results were obtained from the NEXTGE N model, it was then desired to compare shoreline erosion at different height contours. This was acco mplished by using Equations 3-19 and 3-20, but inserting predicted profiles inst ead of measured. The shoreline recession was found similar to Equation 3-21, with the equation changed to the following pp o s t s t o r mp r e p mcontourcontour contouryyy (3-22) where m indicates measured data, and p indicates predicted data. As mentioned above, Equation 3-22 can be used for all individua l contour positions at one time or for average position at one time. 37

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Statistical Analysis of Results Results obtained for both measured and pred icted contour changes were analyzed to determine the effectiveness of the model. The Pearson correlation coefficient, r, was used in order to determine how certain one can be in making predictions from the NEXTGEN model. The square of the correlation coefficient was th e last step taken in order to determine the goodness of fit. The square of the correlation coe fficient will be referred to as R-squared in following chapters. For ease of use and lack of confusion, the following notation is defined for the analysis. A contour position is defined by or or A,10 or 0(,)mpB y ij (3-23) where m is measured, p is predicted, B is before or pre-storm, A is after or post-storm, 10 indicates the 10 foot contour, 0 indicates the zer o foot contour, i is the storm event (5 total), and j is the monument number (6 total). Using Equati on 3-23, the contour change was defined for statistical analysis by ,10 ,,10 ,,10(,)(,)(,)mm Am B y ijyijyij (3-24) ,10 ,,10 ,,10(,)(,)(,)pp Am Byijyijyij (3-25) By using these definitions, the correlation equa tions can be written much more compactly. The zero foot contour change notation is represented in the same manner as Equations 3-24 and 3-25 with the subscript 10 replaced by 0. The r value was found for two different cases using two different methods. The two cases considered within the analysis were a comparison between the measured and predicted 10 foot contour data and a comparison between the meas ured 10 foot and zero contour data. The two methods performed for each case considered all data within a single storm event and data over all storm events. 38

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Measured versus Predicted The first method performed upon the measured a nd predicted data for the 10 foot contour was for each storm event, j The correlation coefficient, is defined as 1, ir 6 ,10 ,10 1 1, 66 22 ,10 ,10 11(,)(,) (,)(,)mp j i mp jj y ijyij r y ijyij (3-26) where the variables have been previously defined in the s ection above. The next method determined the correlation coefficient for all storm events and is defined as 2r 56 ,10 ,10 11 2 56 56 22 ,10 ,10 11 11(,)(,) (,) (,)mp ij mp ij ijyijyij r y ijyij (3-27) Measured 10 Foot Contour versus Measured Zero Foot Contour The comparison between the measured +10 foot contour and measured zero contour was performed in the same manner as menti oned above. The correlation coefficient, for the first method is as follows 1, ir 6 ,10 ,0 1 1, 66 22 ,10 ,0 11(,)(,) (,)(,)mm j i mm jj y ijyij r y ijyij (3-28) The second method used to calcula te the correlation coefficient, for all storm events is defined by 2r 39

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56 ,10 ,0 11 2 56 56 22 ,10 ,0 11 11(,)(,) (,) (,)mm ij mm ij ijyijyij r y ijyij (3-29) Results of these analyses are presented and interpreted in the following chapters. 40

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Figure 3-1. Definition sketch of hurricane catc hment zone. 41

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Figure 3-2. Geometric sketch of rot l and coordinate system. 42

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Figure 3-3. Example sketch of and s lnew 43

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CHAPTER 4 RESULTS AND ANALYSIS As discussed in the previous chapters, evaluating erosion pred icted by the NEXTGEN model was the main focus of this thesis. In order to complete this task, various models were utilized and numerous results were develope d. From these results, a better quantitative assessment of the shoreline eros ion model could be attained through improving the storm surge data. Measured Shoreline Change Results To determine the magnitude of changes that occur along the shoreline in Walton County, it was necessary to analyze the changes for various contour lines. A cont our change program was run for nine common monuments spaced peri odically throughout Walton County. Common monuments within our study area ar e defined as monuments that ar e located in the same position since 1973 and are common to all data sets. By using common monument s that had not been relocated, no error from this possible source was included in the calculations. The common monuments used to analyze the measured beach pr ofile data were monuments 21, 57, 60, 63, 66, 84, 87, 102, and 117. To determine contour changes since 1973, th e +10 and zero contour line positions for Walton Countys beaches were selected as the references for subsequent changes. The shoreline changes were referenced to the 1973 position. All fluctuations after 1973 on the negative y-axis indicate a recessed contour and on the positive y-axis, a contour advancement. As can be seen from Figure 4-1, there have been substantial changes in the zero and +10 foot contour positions over the past 30 years. The impact from Hurricane Eloise can be seen in late 1975 with a large amount of recession occurring in the +10 foot contour line From the time span of 1975 to 1995, this 44

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contour recovered slightly past its pre-Eloise position due to mild weather conditions. In 1995, it can be seen that the contour re sponds significantly to Hurricanes Erin and Opal. These storms bring the +10 foot contour back to a recessed lo cation of -36 feet. From the time period of 1998 to 2004, there is only a slight rec overy at the upper contour level. In 2004, there is another large contour recession due to Hurricanes Ivan and De nnis. These hurricanes moved the +10 foot contour back approximately 34 feet from its previously eroded condition. The last data point available in Walton County was in July, 2007, a nd from this point, one can note the minimal recovery that has occurred. Although the +10 foot contour indicated larg e amounts of recession due to major storm events, the zero contour line may indicate accr etion after large storms As for the 10 foot contour, the 1973 position for the zero contour is used as a datum a nd is set equal to zero. In 1975, the waterline is moved 36 f eet shoreward due to Hurricane El oise. After some time, it can be seen that the profile evolves back to within approximately seven feet from the datum. From 1981 to 1995, there is little data available to indi cate the position of the zero contour line. In 1995, Hurricanes Erin and Opal moved the zero foot contour line approximately 35 feet shoreward. The next major hurricane to impact the zero foot contour was Hurricane Georges in late 1998, which caused a retreat of approximately 30 feet. Over the next six years, the profile recovers to approximately its 1973 pre-storm conditions. Then in 2004, the zero contour experiences retreat by Hurricane Ivan. After Hurricane Ivan, the profile is impacted by Hurricane Dennis in 2005. Hurrican e Dennis, however, did not cause the zero foot contour line to be displaced seaward. The profile respons e from Dennis was a retreat of over 40 feet. However, from Figure 4-1 it can be seen that the zero foot contour li ne is recovering quite rapidly back toward the 1973 datum. 45

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One explanation for the accretion at the zero foot contour fo llowing some storms is the large amount of sediment eroded from the upper be rm during a storm. The sand is taken from the upper beach and transported seaward where it a dvances the lower contours. In response to the steep berm caused by erosion, the upper portion of the profile erodes in an attempt to form a new equilibrium profile for the elevated water levels. As the profile approaches equilibrium for the new water level, the zero contour line is disp laced farther seaward. Once the waters recede, the zero foot contour is located at the adjusted seaward position from the profile response and from the large amount of sand moved to the lowe r contours from the storm. Figure 4-2 also illustrates this concept. A second possible explan ation is that the lower contours respond to the post-storm constructive forces much more rapidly than the upper contours. Thus, during the time between the storm and the post-storm surveys, the lower contours may have experienced substantial recovery. The results for the contour changes due to stor ms are also used later in this chapter to establish conclusions between measured retreat versus predicted retreat. Storm Surge Results The storm surge model was first run with Hurricane Eloise storm parameters from the model hurricane. Hurricane Eloise was chosen as a means of calibration due to the amount of data available for that storm. For Hurricane Eloise, the model creates a 23 hour hydrograph of storm surge with it reaching its p eak surge of 5.6 feet at 18.0 hour s, which is presented as Figure 4-3. The calculated results from the one-dimensi onal model do not compare favorably with those measured during Hurricane Eloise. A tide gage at East Pass recorded a maximum storm tide of 6.4 feet, which did not include wave setu p. Other measurements include a MHW mark of 46

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13.8 feet which would indicate an under-prediction of approximately a factor of two, but this measurement may include wave r unup or setup (Clark, 2006). During hurricanes, wave runup can drastically increase the storm surges reach upon a beach. When a comparison was made between pr edicted and measured water levels, it was important that the most accurate source was used fo r comparison. It was determined that the best source for comparison would be from tide gages that were operational during the hurricane, and if they were not available, the MH W marks should be used with caution. In addition to Hurricane Eloise, the one-dimens ional model was run for nine other storms that entered the study area. For each of the st orms, the one-dimensional model produced results for the hurricanes making landfall at the center of Walton County. Appendix A contains the predicted surge for the remaini ng major hurricanes within the study area. Table 4-1 shows a comparison between calculated and measured st orm tides at several locations for Hurricane Eloise and nine other hurri canes within our study area. Error analysis done upon the measured surge values indicate that none of the model results compare favorably with recorded surge data. Fi gure 4-4 illustrates th e maximum predicted unscaled surge versus the maximum measured surge at the location of greatest surge. The predicted data was plotted agains t the measured data in order to analyze how well or how poorly the predicted data compared with the measured. As shown in Figure 4-4, a best-fit line was placed through the origin in order to see the magnit ude of variation from the line. As can be seen in Figure 4-4, all of the results fall under the line of equivalence. The lack of fit to the line indicates an under-prediction which l ead to an in-depth analysis of variables within the model. After much scrutiny, it was decided that the one-dimensional model was under-predicting the values for the wind stress tide, thereby decr easing the overall surge. This under-prediction 47

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could result in a misleading eval uation of the applicability of NEXTGEN. If too small surge values are input into the NEXTGEN mode l, the erosion will be underestimated. Several possible explanations are given for the models shortcomings in accurately predicting the surge. The study area of Walton County has a rela tively steep beach (slope of approximately 1/50) and a narro w shelf width. With these physical characteristics, the conditions are unfavorable to predict large wi nd setup values with the current equations described in Chapter 3. The calculations for wind setup are depth dependent, and with the steep slope, the water depth decreases rapidly. It is recalled that th e Bathystrophic Storm Surge Model considers the system to be in static equilibrium in the cross-shore direction. It may be that dynamic effects play a significant ro le, especially on steep profiles. Because the main purpose of this effort wa s to evaluate the profile response model, NEXTGEN, it is essential to use the best storm su rge results as possible. In order to represent more reliable storm surge values, two methods were developed. The first method utilized historic storm surge hydrographs obtained from the National Oceanic and Atmospheric Administration (NOAA) Center for Operational Oceanographic Products and Services (COOPS) (http://tidesandcurrents.noaa.gov/). Thes e hydrographs were measured by a tide gage located at the end of a pier in Panama City, Fl orida and were available for eight of the nine storms of interest. This location was chosen for its close proximity to our study area, and the lack of wave setup in the measurements due to the tide gage po sition at the end of the pier. Figures 4-5 to 4-8 illustrate the measured storm su rge for several storms at the Panama City Pier tide station. Since the gage measures the astrono mical tide, wind setup, barometric, and Coriolis components of the surge due to the hurricane, the m easured values of the surge were able to be combined with the predicted wave setup values from the model. This combination of predicted 48

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wave setup plus measured surge which includes all components other than wave setup provides more reasonable surge values. Each of the setup values along with the total surge can be seen in Table 4-2. As noted, the method described above was appl ied to eight of the nine storms; however, due to the lack of such data for Hurricane Erin, a second me thod was developed to scale the storm surge hydrograph created by the one-dimensional model. This scale f actor was applied to the Walton County centered storm surge hydrogra ph, which increased the surge levels by approximately a factor of 2 for Hurricane Erin. An example of a scaled hydrograph can be seen in Figure 4-9. The combined values of measured wind stress tide, barometric tide, Coriolis force, and predicted wave setup increased the storm surge to more reasonable levels. Figure 4-10 presents a comparison of the combined or scaled surge values and established. The values are closer to the line of equivalence in this plot, with some values falling very cl ose to the equivalence line. The values for the predicted surge ar e centered at Walton County, but the values of measured surge were for areas close to the study area. This diffe rence of location could explain why some values fall either above or below the line of equivalence. Cross-Shore Transport Model The NEXTGEN model was run for major stor ms affecting Walton County from 1975 to present. The major storms affecting the study ar ea were Hurricane Eloise (1975), Hurricane Erin (1995), Hurricane Opal (1995), Hurricane Ivan (2 004), and Hurricane Dennis (2005). Since the model uses one beach profile pe r run, it was necessary to run the model at several locations throughout the county. The average locations sel ected were Monuments 21, 57, 63, 66, 87, and 102. Through selecting various monuments spaced throughout the study area, we were able to obtain a broader representation of storm related profile response. Like the calculations made for 49

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measured contour change above, the monuments selected for use within the NEXTGEN model are all common monuments to the data set. The model predicted erosion for each of the st orms adequately when the adjusted storm surge was used as an input. Figure 4-11 illust rates the predicted prof ile evolution seen for Hurricane Eloise at Monument 66. All profile evolution plots from the NEXTGEN model are presented in Appendix B. Each figure indicates the initial, pre-storm profile by the cyan line, with the other lines representing the profile evol ution at several times during the storm event. The final post-storm equilibrium profile is repr esented in each plot by the tan dashed line. Predicted contour change. Hurricane Eloise caused a significant amount of erosion within the upper contours. The average recession of the +10 foot cont our for the six profiles included in this study was found to be -39.5 feet. Post-storm studi es done by Chui in 1977 measured an average retreat of 38 feet, which is in agreement with the calculated erosion from the model. Hurricane Erin was a weaker tropical storm wh en it impacted Walton County, and this can be seen in the amount of erosion caused by th e storm. On average, Walton Countys beaches retreated 9.4 feet at the +10 foot contour line fo r this storm. In the case of Hurricane Opal, the pre-storm beach condition was impacted by Hurricane Erin two months prior. Since there were no post-storm beach profiles taken after Erin, it is assumed that the pre-storm profile was the same as used for Erin. Under this assumption, results indicated a larger amount of erosion than that experienced by Hurricane Erin. On average, the model predicted a re treat of the +10 foot contour line of 18.6 feet for Hu rricane Opal. Overall, for the 1995 hurricane season, a combined predicted retreat was found to be -28 feet, whic h is in good agreement with the observed retreat of -36 feet. 50

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Although the predicted versus measured re sults for Hurricane Opal from this study compare well with one another. Studies done by the Bureau of Beaches and Coastal Systems observed a retreat at the +10 foot contour line at an average of 45 feet. However, it must be noted that the datum considered for pre-storm cond itions could be different than the one used in the model, and the monuments used could be different than those of our study. The next major hurricane to impact Walton C ounty occurred nine years later in 2004. The pre-Ivan shoreline had under gone gradual recovery from Hurricane Opal, and the +10 foot contour line was located at 57. 8 feet. As can be seen from a comparison from the two measurements of the +10 contour from 1975 and 1995, the beach was in an eroded state when Hurricane Ivan impacted the coast. The calculate d retreat of the +10 contour line post-Ivan was found to be 16.4 feet which compares reasonably to a measured retreat of 23 feet. The final hurricane considered in this study is Hurricane Dennis. Hurricane Dennis was the first hurricane of the season to affect Walton County, and since its close proximity to Hurricane Ivan, the pre-storm beach condition was in an eroded state. The pre-storm +10 foot contour was located approximately 50 feet s horeward of the 1973 position. The calculated average retreat for the +10 foot contour line for Hurricane Dennis was found to be 28 feet for the six Walton County profiles which is greater than the measured retreat of 16 feet. Overall, the predicted retreat at the +10 foot contour compares favorably with the observed data. Hurricane Eloise had the best comparison of predicted versus measured contour change with an over-prediction of 2.5 feet. The retr eat predicted for Hurricane Dennis contained the largest difference between measured and predicte d contour change with an over-prediction of 11 feet. In general, the model was successful in predicting reasonable retreat due to major storms at 51

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the upper contours. Figure 4-12 illustrates the compar ison between predicted and measured +10 foot contour change. Along with comparing the +10 foot contour change from the NEXTGEN model, it was also decided to analyze the zero foot contour ch ange post-storm. Hurricane Eloise was predicted to have caused a shoreline advancement of 34.3 feet at the zero contour. As mentioned above in the measured shoreline change section, accreti on about the zero contour mark is common for major storms due to the volume of sand erode d from the upper berm and possibly post-storm advancement prior to survey. This prediction compares well with the measured results of approximately 36 feet of accretion determined from the measured pre and post-storm data. After Hurricane Eloise, the zero contour wa s impacted by Hurricanes Erin and Opal. Hurricane Erin only resulted in a shoreline advancement of 4.6 feet at the contour line. However, Hurricane Opal contributed to a major portion of the advancement during the 1995 hurricane season. The overall predicted shor eline advancement due to Hurricane Opal was approximately 40 feet. However, the total m easured zero foot contour change for the 1995 hurricane season was a retreat of -35 feet, wh ich does not compare well with the predicted results. Again, this error between predicted and measured can be attributed to the elapsed time between surveys. The next predicted shoreline change about the waterline was for Hurricane Ivan. The model results indicate an advancement of a pproximately 28 feet for the six Walton County profiles. Hurricane Dennis was the last hurri cane to impact the zero foot contour with a predicted shoreline advancemen t of about 50 feet. However, the post-storm measured zero contour for the 2004-2005 hurricane segment indicat es that erosion, not accretion, occurred at the contour. Results for this segment in time do not compare favorably to one another. 52

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Reasons for the difference in magnitudes for th e predicted erosion and the measured can be attributed to several factors. The predicted erosion by the NEXTGEN mo del is for immediately after a storm. However, in the real world, it is not possible to survey th e beach profile directly after the storm. This could lead to some recovery affecting the calculations made when comparing shoreline change. Other reasons for the discrepancies within calculations have previously been described in the s ection of Measured Shoreline Change Statistical Analysis of Data The statistical analysis performed on both data sets was a central element included within the study. This portion of the thesis was necessa ry in order to evaluate NEXTGEN, as well as quantify the programs sensitivity to input variables. The major va riable that will be examined will be the storm surge input. By altering the pe ak storm surge by +/-1 foot, the sensitivity of NEXTGEN to storm surge will be established. The method to find the correlation coefficien t, r, was discussed in Chapter 3, but oftentimes in research the R-squared value is commonly used. The R-squared value is simply found by taking the square of the correlation coeffici ent. The coefficient of determination, or Rsquared, is useful because it gives the proportion of variance shared by the two sets of data. One advantage of using the coefficient of determinat ion over the correlation coe fficient is the ease of interpretation. By simply moving the decimal poi nt two places to the right, R-squared can be interpreted as a percentage, unlik e the correlation coefficient. Measured 10 Foot versus Predicted 10 Foot Predicted Contour Once values for predicted shoreline change were obtained from the NEXTGEN model, it was necessary to compare them with measured va lues to meet the objective of the study. In order to determine how well the measured +10 foot contour values compared with the predicted values, a correlation test was perf ormed. As mentioned in Chapte r 3, the correlation coefficient, 53

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r was found using two different methods. The fi rst method used all data points throughout each storm event. The five storm events analyzed were the time period of 1973 to 1975 which includes Hurricane Eloise, the next two tim e periods were from 1995 to 1997 and included Hurricanes Erin and Opal, the next time segment was 2004-2005 for Hurricane Ivan, and the last event was from early 2005 to late 2005 which ac counted for Hurricane Dennis. A list of the Rsquared and r values can be found in Table 4-3. The best value from the R-squared values was for Hurricane Opal with 2 R = 0.67, which indicates there is a 67% overlap between datasets. Overall, all the calculated r valu es were between the ranges of 0.5 to 0.8, which indicates a moderate correlation amongst the datasets. This indicates that the NEXTGEN model was able to reasonably replicate profile response due to hurricanes. This moderate correlation can possibly be attr ibuted to the uncertainty in the storm surge predictions. Figure 4-13 represen ts all of the predicted and meas ured +10 contour change data for all storm events. As can be seen from the plot, two R-squared values are shown. The value of 2 R =0.44 is for the case of a linear trend that is forced through the origin. The second value for R-squared is equal to 0.45 representing the best-f it line that is not forced through zero. Measured 10 Foot versus Measured Zero Foot Contour Along with analyzing trends in Figure 4-1 vi sually, a correlation test was performed to evaluate the correlation between the changes at the 0 and + 10 foot contours. Figure 4-14 represents the correlation betw een all measured +10 and zero contour change for all storm events. Again, there are two values for R-squared shown. The first value that contains the bestfit line passing through the origin indicates 2 R = 0.0152. The small value indicates poor agreement between the two data sets. The valu e of R-squared where th e best-fit line is not 54

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forced through the origin is 0.0285. Both values indicate weak agreements amongst all of the data. Possible reasons for this weak corre lation have previously been discussed. When the storm events are analyzed indivi dually, values for R-squared indicate better agreement among some data sets then others. Tabl e 4-4 lists the R-squared values for each of the storm events. The best correlation amongst da ta sets is for Hurricane Georges with 2 R =0.71, and the least correlation is for Hurricane Dennis with 2 R =0.01. The remaining values of Rsquared fall within the above range. Model Sensitivity to Input Variables As mentioned before, storm surge was the li miting factor in our study to accurately quantify contour changes throughout Wa lton County. In order to illustrate the extent that storm surge affected the study, storm surg e was altered by +/1 foot to te st the sensitivity of the model to the input variable. Table 45 indicates the predicted average +10 foot contour change for the adjusted storm surge and for the surge scaled such that the peak varied by +/1 foot. Results are presented in Figure 4-15. For Hurricane Eloise, the pred icted retreat was found to be -39.5 feet. By altering the storm surge +1 foot, predicted retreat was found to be -50.3 feet. When the storm surge was reduced by -1 foot, the retreat was reduced to appr oximately -26 feet. For this case, altering the storm surge resulted in at least a +10 foot diffe rence of retreat. The retreat caused by Hurricane Erin was found to be approximately -9 feet. The increased surge of +1 foot caused -18 feet of retreat, while the decreased surge caused a shore line advancement of +8 feet. Hurricane Opal was least affected by altering the storm surge by +/-1 foot. Predicted retreat without altering the storm surge was found to be -18.6 feet. When the storm surge was increased by +1 foot, the retreat was found to be -20.4 feet. By lowering the storm surge by one foot, the expected retreat 55

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was found to be -20.9 feet. Hurricane Ivan was f ound to have caused -16.4 feet of retreat. With +1 foot surge, retreat was found to be approximately -30 feet. However, when surge was reduced by one foot, predicted retr eat was only found to be -3.5 feet. The last amount of retreat that was analyzed was from Hurricane Dennis. Hurricane Dennis was predicted to have caused 28 feet of retreat. With an in creased surge of one foot, the retr eat was found to be -33 feet. By decreasing the storm surge by one foot, the amount of predicted retreat was found to be 22.5 feet. Overall, it can be seen from the results that by changing the storm surge by one foot can greatly alter the predicte d retreat. For some cases, the diffe rence between pred icted retreat and predicted retreat with altered surge was approximate ly 15 feet. This indicates that the model is sensitive to the input of storm surge, and the be st representation of the surge that occurred with each storm is necessary to obtain appropriate results. 56

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1970 1980 1990 2000 2010 Year -100 -50 0 50Average Change of 0 and 10 foot Contour from 1973 Postition (ft) 10' contour 0' contour Eloise Erin and Opal Ivan Dennis Georges Figure 4-1. Average +10 and zero foot c ontour change over nine common Monuments. 57

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Figure 4-2. Zero foot contour accretion due to large storms [Reprinted with permission from Clark, R.R. 2006. Hurricane Dennis & Hurricane Katrina: Final Report on 2005 Season Impacts to Northwest Florida. (Page 14, Figure 12). Office of Beaches and Coastal Systems, Florida Department of Environmental Protection, Tallahassee, Florida.] 58

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0 5 10 15 20 Time (hours) 0 1 2 3 4 5Storm Surge (ft) Figure 4-3. Predicted storm surg e hydrograph for Hurricane Eloise. 59

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0 5 10 15Maximum Predicted Surge Erin EarlKate GeorgesElenaFrederic Ivan Eloise Opal Dennis 0 5 10 15 Maximum Measured Surge Figure 4-4. Plot of maximum predicted un-scaled surge ve rsus maximum measured surge at location of maximum surge. 60

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0 5 10 15 20 Time (hours) 2 3 4 5 6Surge (ft) Figure 4-5. Measured storm su rge hydrograph for Hurricane Eloise from historical tide gage data. 61

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Figure 4-6. Measured storm surge hydrogr aph for Hurricane Opal from NOAA CO-OPS database. 62

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Figure 4-7. Measured storm surge hydrogr aph for Hurricane Ivan from NOAA CO-OPS database. 63

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Figure 4-8. Measured storm surge hydrogr aph for Hurricane Dennis from NOAA CO-OPS database. 64

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01 02 03 04 0 Time (hours) 0 2 4 6Storm Surge (ft) Unscaled Surge Scaled Surge Figure 4-9. Storm surge comparison between scal ed and un-scaled values from one-dimensional model. 65

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051 01 Maximum Established Surge 5 0 5 10 15Maxixmum Predicted Surge Dennis OpalErinEloiseIvan Figure 4-10. Adjusted maximum predicted surg e versus maximum measured surge at Walton County. 66

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 10 hour 16 hour 19 hour 23 hour Figure 4-11. Example profile response from the NEXTGEN model for Hurricane Eloise. 67

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01 02 03 04 0 Measured Recession of +10 Contour 0 10 20 30 40Predicted Recession of +10 Contour Erin and Opal Eloise Dennis Ivan Figure 4-12. Comparison of measured and pred icted recessions of the +10 foot contour. Cumulative values are presented for Erin and Opal because no intermittent surveys are available to quantify indi vidual measured recession. 68

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R2 = 0.4411 R2 = 0.4508 -40 -20 0 20 40 60 80 100 0102030405060708090 Measured Recession (ft)Predicted Recession (ft) Eloise Erin Opal Ivan Dennis Linear (All data for all Storm Events) Two points indicate contour advancement Figure 4-13. Plot of predicted erosion versus measured erosi on for individual profiles (6) all storm events (5). 69

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R2 = 0.0152 R2 = 0.0285 -100 -50 0 50 100 150 -20-100102030405060708090 Measured 10' Contour RecessionMeasured 0' Contour Recession Meas. 0 and 10' contour change Linear (Meas. 0 and 10' contour change) Figure 4-14. Plot of measured 0 foot and measured +10 foot cont our change for all storm events. 70

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0 10 20 30 40 50 60 051015202530354045 Measured Recession of +10 foot Contour Predicted Recession of +10 foot Contour Eloise Erin and Opal Ivan Dennis Figure 4-15. Comparison of measured and predicte d recessions of the +10 foot contour with error bars to account for the sensitivity of the model output due to storm surge scaled such that the peaks varied by +/1 foot. 71

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72 Table 4-1. Comparison between predicted and measured storm surge Storm Landfall location Max. measured surge Max. predicted surge Max. predicted surge and setup Eloise Dune Allen Beach, FL 13.8* 5.67 13.69 Frederic Dauphin Island, AL +12* 3.68 5.05 Elena Biloxi, MS 10.5* 4.46 6.07 Kate Crooked Island, FL 8.4 4.56 8.23 Erin Navarre Beach, FL 6-7* 3.06 4.25 Opal Pensacola Beach, FL 14.13* 4.80 6.27 Earl Shell Island, FL 6-7* 4.16 6.08 Georges Biloxi, MS 8* 4.16 5.66 Ivan Pensacola, FL 12.2* 5.25 8.14 Dennis Santa Rosa Island, FL 15* 5.04 6.90 indicates that measurement is a high water mark (HWM)

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73 Table 4-2. Individual setup values and maximum adjusted surge Hurricane Wind setup Wave setup Combined Surge Eloise 6.0 4.21 10.21 Opal 7.31 3.78 11.56 Ivan 5.8 1.68 7.48 Dennis 6.03 3.43 9.46

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74 Table 4-3. Individual R-squared and r values of predicted versus measured +10 contour change for six common profiles in each storm event Hurricane R-sqaured value r value Eloise 0.407 0.638 Erin 0.552 0.743 Opal 0.669 0.818 Ivan 0.254 0.504 Dennis 0.390 0.624

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75 Table 4-4. Individual R-squared values for measured +10 contour change versus measured zero contour change for each storm event Hurricane R-sqaured value Eloise 0.075 Erin and Opal 0.233 Georges 0.713 Ivan 0.316 Dennis 0.010

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76 Table 4-5. Predicted average change of +10 contour from NEXTGEN model for the three cases of storm surge Hurricane Predicted x Predicted x with +1 surge Predicted x with -1 surge Measured x Eloise -39.5 -50.3 -25.5 -37 Erin -9.4 -17.9 8.0 -36 Opal -18.6 -20.4 -20.9 Ivan -16.4 -29.9 -3.5 -23 Dennis -28.0 -33.0 -22.5 -16

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CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS The main objective of this thesis was to evaluate methodology for the prediction of highfrequency shoreline and upper dune contour changes along the Flor ida Panhandle. The objective was met with both success and failure. The projec t was successful in that we were able to predict shoreline and + 10 foot c ontour changes that compared favorably with measured data. A major shortcoming was the inability to accurately predict storm surge results. Attempting to identify and improve the calculated storm surge results occupied a sign ificant portion of the project effort. This, in return, affected the time remaining to calibrate the new methodology to predict high-frequency changes along the Panhandle. Summary and Conclusions Storm Surge Model The storm surge model was probably the largest weakness exhibited in this study. For all hurricanes within the study area, the results from the one-d imensional storm surge model underestimated the predicted water levels. The component that most lik ely contributed to the under-prediction of storm surge was the wind surge. Recall that the wind stress tide is depth dependent, and the study area wa s located on a steep and narrow shelf. Since the model considers the system to be in a state of static equilibrium, it may be that dynamic effects play a significant role in areas with steep profiles. Once the problem with the wind surge was iden tified, attempts at rectifying the small values of storm surge were made. The method us ed to increase the storm surge values was to combine the calculated wave setup from the one-dimensional model with the measured wind stress, Coriolis, and barometric tides. The second method that was used for the one case that no hydrographic data were availabl e was to scale the storm surge results from the maximum 77

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established water level. Overall, both methods worked quite well in adjusting the storm surge to more reasonable values that compared favorably with measured data. Measured Contour Change The project was successful in identifying the contour changes at both the zero and +10 foot contour from 1970 to present. Both contours have had dramatic fluctuations in recent years due to the active hurricane seasons from 1973 to presen t. The present location of the measured +10 and zero contours are in an eroded state. However, the contours appear to be recovering based on the most recent profile survey. Absent of major storms in the near term, the dunes are expected to continue re covering, albeit slowly. Representation of High-Frequency Shoreline Changes Once reasonable time histories of water leve ls had been established for the five major erosional events, NEXTGEN was, for the most part successful in predicting change of the zero foot and +10 foot contours from 1973 to present. The model adequately represented erosion at the +10 foot contour from increased water and wave activity that transported sand seaward to lower contours. Along with accurately modeling the response of the upper berm, the NEXTGEN model effectively represen ted the accretion at the waterline that is a ssociated with severe dune erosion. Statistical analysis done on the predicted resu lts from NEXTGEN indi cates that there is reasonable agreement between the predicted and measured +10 contour change. Overall, the predicted and measured +10 contour change data had a promising correlation. The scatter that occurs within the data is most likely due to the inability to accurately predict the storm surge. The NEXTGEN model is dependent upon an accurate input of storm surge, and without it, the model is limited in its ability to predict shoreline change. 78

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Recommendations for Future Study Storm Surge Model The lack of being able to predict accurate storm surges remains one of the principal limitations for hindcasting shoreline change for hist orical storms within the study. Any future attempt to model storm surge within our study area could possibly includ e the use of another storm surge model to predict the storm surges Adapting a new model to our study area and conditions was beyond the timeframe for this thesis but it would be intere sting to see if the results compare with the one-dimensional model used within this thesis. Also, the inclusion of dynamic effects could increase the values for the wind stress tide within the study area. This would help to account for the steep slope which is believed to be aff ecting the storm surge values. Measured Contour Change To better represent contour change since 1973, further recommendations are to include more monuments in the calculations. The measur ed contour change with in the study was limited by the number of common monuments availabl e throughout the period 1973 to 2005 which had not been relocated. If more monuments were ab le to be incorporated in the average, the dependence on individual monument s would be less of a possible source or error. A possible solution to this problem is to use adjusted prof iles that account for change in monument position from their 1973 positions. This solution, however, must be done car efully so that the adjusted profile does not become an additional source of error. Although it was not the focus of the study, it is interesting to note th e exponential recovery of the shoreline after major storm events. Further research could include an attempt to predict the recovery of both contours after major storm even ts. This would be quite a comprehensive task due to the dependence of the upper contours on ae olian processes. The only un-interrupted 79

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recovery that can be seen from the data is from Hurricane Eloise in 1975 to the full recovery of the beach in 1995. After this, the coast was aff ected by several hurricanes in a small time span, and the beach was not able to experience substant ial recovery. The suggested model would have to be able to account for the recove ry from a previously eroded state. Representation of High-Frequency Shoreline Changes In order to better evaluate the NEXTGEN models performance in predicting contour change, it is recommended to compare the model out put with a greater number of data sets. This would require a larger study area than that of th e current study. Perhaps a comparison between all major hurricanes impacting the state of Florida from 1975 to pr esent would allow for a larger data set for comparison. Also, by increasing the study area, more measured data would be available for comparison. The larger study area w ould also show the models ability to be used at any location within the stat e of Florida, which would be advantageous to government agencies. Additionally, storm-induced changes at additional contour elevati ons would be useful. It is possible that contours lower than +10 feet are less sensitive to storm surges. The final recommendation concerning the NEXT GEN model is related to the storm surge input from the one-dimensional model. More fa vorable comparisons will require incorporation of the most accurate storm surge data into the models input. With stor m surges that compare favorably to real-time conditions during the hur ricane, evaluation of the predictability of NEXTGEN could be accomplishe d with greater confidence. 80

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APPENDIX A STORM SURGE HYDROGRAPHS 0 5 10 15 20 Time (hours) 0 1 2 3 4 5Storm Surge (ft) Figure A-1. Predicted storm surge hydrograph fo r Hurricane Eloise from one-dimensional storm surge model. 81

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01 02 03 04 0 Time (hours) 0 1 2 3 4Storm Surge (ft) Figure A-2. Predicted storm surge hydrograph fo r Hurricane Erin from one-dimensional storm surge model. 82

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0 5 10 15 Time (hours) 0 1 2 3 4 5Storm Surge (ft) Figure A-3. Predicted storm surge hydrograph fo r Hurricane Opal from one-dimensional storm surge model. 83

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02 04 06 08 01 0 0 Time (hours) 0 1 2 3Storm Surge (ft) Figure A-4. Predicted storm surge hydrograph for Hurricane Georges from one-dimensional storm surge model. 84

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01 02 03 04 05 0 Time (hours) 0.0 0.5 1.0 1.5 2.0Storm Surge (ft) Figure A-5. Predicted storm surge hydrograph fo r Hurricane Ivan from one-dimensional storm surge model. 85

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0 5 10 15 20 25 Time (hours) 0 1 2 3 4Storm Surge (ft) Figure A-6. Predicted storm surge hydrogra ph for Hurricane Dennis from one-dimensional storm surge model. 86

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APPENDIX B NEXTGEN PROFILE EVOLUTION RESULTS 0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 10 hour 16 hour 19 hour 23 hour Figure B-1. Calculated pr ofile evolution for Monument 21 for Hurricane Eloise. 87

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30 40Elevation (ft) Initial 1 hour 10 hour 16 hour 19 hour 23 hour Figure B-2. Calculated pr ofile evolution for Monument 57 for Hurricane Eloise. 88

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 10 hour 16 hour 19 hour 23 hour Figure B-3. Calculated pr ofile evolution for Monument 63 for Hurricane Eloise. 89

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 10 hour 16 hour 19 hour 23 hour Figure B-4. Calculated pr ofile evolution for Monument 66 for Hurricane Eloise. 90

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 10 hour 16 hour 19 hour 23 hour Figure B-5. Calculated pr ofile evolution for Monument 87 for Hurricane Eloise. 91

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 10 hour 16 hour 19 hour 23 hour Figure B-6. Calculated pr ofile evolution for Monument 102 for Hurricane Eloise. 92

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0 500 1000 1500 2000 Cross-shore distance (ft) -60 -40 -20 0 20Elevation (ft) Initial 1 hour 15 hour 26 hour 30 hour 47 hour Figure B-7. Calculated profile evolution for Monu ment 21 for Hurricane Erin 93

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0 500 1000 1500 2000 Cross-shore distance (ft) -60 -40 -20 0 20Elevation (ft) Initial 1 hour 15 hour 26 hour 30 hour 47 hour Figure B-8. Calculated pr ofile evolution for Monume nt 57 for Hurricane Erin. 94

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0 500 1000 1500 2000 Cross-shore distance (ft) -60 -40 -20 0 20Elevation (ft) Initial 1 hour 15 hour 26 hour 30 hour 47 hour Figure B-9. Calculated pr ofile evolution for Monume nt 63 for Hurricane Erin. 95

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0 500 1000 1500 2000 Cross-shore distance (ft) -60 -40 -20 0 20Elevation (ft) Initial 1 hour 15 hour 26 hour 30 hour 47 hour Figure B-10. Calculated pr ofile evolution for Monument 66 for Hurricane Erin. 96

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0 500 1000 1500 2000 Cross-shore distance (ft) -50 -30 -10 10 30Elevation (ft) Initial 1 hour 15 hour 26 hour 30 hour 47 hour Figure B-11. Calculated pr ofile evolution for Monument 87 for Hurricane Erin. 97

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0 500 1000 1500 2000 Cross-shore distance (ft) -60 -40 -20 0 20Elevation (ft) Initial 1 hour 15 hour 26 hour 30 hour 47 hour Figure B-12. Calculated profile evolution for Monument 102 for Hurricane Erin. 98

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 3.5 hour 9.5 hour 14 hour 17 hour Figure B-13. Calculated pr ofile evolution for Monument 21 for Hurricane Opal. 99

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 3.5 hour 9.5 hour 14 hour 17 hour Figure B-14. Calculated pr ofile evolution for Monument 57 for Hurricane Opal. 100

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 3.5 hour 9.5 hour 14 hour 17 hour Figure B-15. Calculated pr ofile evolution for Monument 63 for Hurricane Opal. 101

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 3.5 hour 9.5 hour 14 hour 17 hour Figure B-16. Calculated pr ofile evolution for Monument 66 for Hurricane Opal. 102

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 3.5 hour 9.5 hour 14 hour 17 hour Figure B-17. Calculated pr ofile evolution for Monument 87 for Hurricane Opal. 103

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 3.5 hour 9.5 hour 14 hour 17 hour Figure B-18. Calculated profile evolution for Monument 102 for Hurricane Opal. 104

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 19 hour 24 hour 35 hour 53 hour Figure B-19. Calculated pr ofile evolution for Monument 21 for Hurricane Ivan. 105

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30 40Elevation (ft) Initial 1 hour 19 hour 24 hour 35 hour 53 hour Figure B-20. Calculated pr ofile evolution for Monument 57 for Hurricane Ivan. 106

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 19 hour 24 hour 35 hour 53 hour Figure B-21. Calculated pr ofile evolution for Monument 63 for Hurricane Ivan. 107

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 19 hour 24 hour 35 hour 53 hour Figure B-22. Calculated pr ofile evolution for Monument 66 for Hurricane Ivan. 108

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 19 hour 24 hour 35 hour 53 hour Figure B-23. Calculated pr ofile evolution for Monument 87 for Hurricane Ivan. 109

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 19 hour 24 hour 35 hour 53 hour Figure B-24. Calculated profile evolution for Monument 102 for Hurricane Ivan. 110

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 9 hour 16 hour 21 hour 29 hour Figure B-25. Calculated profile evoluti on for Monument 21 for Hurricane Dennis. 111

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30 40Elevation (ft) Initial 1 hour 9 hour 16 hour 21 hour 29 hour Figure B-26. Calculated profile evoluti on for Monument 57 for Hurricane Dennis. 112

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 9 hour 16 hour 21 hour 29 hour Figure B-27. Calculated profile evoluti on for Monument 63 for Hurricane Dennis. 113

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 9 hour 16 hour 21 hour 29 hour Figure B-28. Calculated profile evoluti on for Monument 66 for Hurricane Dennis. 114

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20 30Elevation (ft) Initial 1 hour 9 hour 16 hour 21 hour 29 hour Figure B-29. Calculated profile evoluti on for Monument 87 for Hurricane Dennis. 115

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0 400 800 1200 Cross-shore distance (ft) -10 0 10 20Elevation (ft) Initial 1 hour 9 hour 16 hour 21 hour 29 hour Figure B-30. Calculated pr ofile evolution for Monument 102 for Hurricane Dennis. 116

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LIST OF REFERENCES Burdin, W.W., 1977. Surge effects from Hurricane Eloise. Shore and Beach 45(2), 3-8. Bureau of Beaches and Coastal Systems, 2007. Critically Eroded Beaches in Florida Tallahassee, Florida: Florida Department of Environmental Protection, 76p. Chiu, T.Y., 1977. Beach and Dune Response to Hurricane Eloise of September 1975. Coastal Sediments New York: ASCE, pp. 116-134. Clark, R.R., 1981. Beach and Dune Erosion. In: Hurricane Dennis: Beach and Dune Erosion and Structural Damage A ssessment and Post-storm Recovery Recommendations for the Panhandle Coast of Florida. Florida Department of Environmental Protection, 54p. Clark, R.R. and LaGrone, J., 2006. A Comparative Analysis of Hurricane Dennis and Other Recent Hurricanes on the Coastal Communities of Northwest Florida Tallahassee, Florida: Bureau of Beaches and Coastal Systems, Florida Department of Environmental Protection, 19p. Crowell, M.; Douglas, B.C., and Leatherman, S.P., 1997. On forecasting future U.S. shoreline positions: a test of algorithms. Journal of Coastal Research 13(4), 1245-1255. Cullington, T.J.; Warren, M.A.; Goodspeed, T.R.; Remer, D.G.; Blackwell, C.M., and McDonough, III, J.J., 1990. 50 Years of Population Growth Along the Nations Coasts 1960-2010. Silver Spring, Maryland: Na tional Ocean Service, National Oceanic and Atmospheric Administration, 41p. Danish Hydraulics Institute, 2008. MIKE 21. http://www.dhigroup.com/Software/ Marine/MIKE21.aspx (accessed April 7, 2008). Dean, R.G., 2004. Next Generation Beach and Dune Eros ion Model for Applications of the Bureau of Beaches and Coastal Systems Beaches and Shores Resource Center, Florida State University, 15p. Dean, R.G. and Chiu, T.Y., 1982. Walton County Storm Surge Model Study. Beaches and Shores Resource Center, Florida State University, 64p. Dean, R.G. and Dalrymple, R.A., 2002. Coastal Processes with Engineering Applications Cambridge, MA, Cambridge University Press. Delft Hydraulics, 2001. A guide to integrat ed coastal zone management. Simulation models and modeling system s related to integrated coastal zone management. http://www.netcoast.nl/tools/rikz/d elft3d.htm (accessed April 7, 2008). Dolan, R.; Fenster, M.S., and Holme, S.J., 1991. Temporal analysis of shoreline recession and accretion. Journal of Coastal Research, 16(1), 145-152. 117

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Edwards, S.F., 1989. Estimates of Future Demographic Changes in the Coastal Zone. Coastal Management 17, 229-240. Fenster, M.S., Dolan, R., and Elder, J.F ., 1993. A new method for predicting shoreline position from historical data. Journal of Coastal Research 9(1), 147-171. Foster, E.R. and Savage, R.J., 1989. Methods of historical shoreline analysis. In : Coastal Zone New York: American Society of Civil Engineers, 4434-448. Foster, E.R., Spurgeon, D.L., and Cheng, J., 2000. Shoreline Change Rate Estimates: Walton County. Tallahassee, Florida: O ffice of Beaches and Coastal Systems, Florida Department of Environmental Protection, Report No. BCS-2000-02 59p. Freeman, J.C.; Baer, L., and Jung, G.H., 1957. The Bathystrophic Storm Tide. Journal of Marine Research 16(1), 12-22. Fritz, H.M., Blount, C., Sokoloski, R., Singleton, J., Fuggle, A., McAdoo, B.G., Moore, A., Grass, C., and Tate, B., 2007. Hurrica ne Katrina storm surge distribution and field observations on the Mi ssissippi Barrier Islands. Estuarine, Coastal, and Shelf Science 74(1-2), 12-20. Genz, A.S., Fletcher, C.H., and Dunn, R.A ., Frazer, L.N., and Rooney, J.J., 2007. The predictive accuracy of s horeline change rate methods and alongshore beach variation on Maui, Hawaii. Journal of Coastal Research 23(1), 87-105. Hanson, H. 1989. GenesisA generalized shoreline change numerical model. Journal of Coastal Research 5(1), 1-27. Holland, G.J., 1980. An analytical model of wind and pressure pr ofiles in hurricanes. Monthly Weather Review 108, 1212-1218. Jelesnianski, C.P., Chen, J., and Shaffer, W. A., 1992. SLOSH: Sea, Lake, and Overland Surges from Hurricanes. National Ocean ic and Atmospheric Administration, Technical Report NWS 48 71p. Kriebel, D.L. and Dean, R.G., 1986. Verification study of a dune erosion model. Shore and Beach, 54(3), 13-21. Kriebel, D.L. and Dean, R.G., 1985. Numeri cal simulation of time-dependent beach and dune erosion. Coastal Engineering 9, 221-245. Larson, M. and Kraus, N.C., 1989. SBEACH : Numerical Model for Simulating StormInduced Beach Change. Vicksburg, Missi ssippi: U.S. Army Corps of Engineers, WES, Technical Report DRP-92-5 115p. Morang A. 1992. Inlet migration and hydrauli c processes at East Pass, Florida. Journal of Coastal Research 8, 457. 118

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National Research Council, 1990. Managing Coastal Erosion Washington, D.C.: National Academy Press, 182p. Westerink, J.J., Luettich, R.A., Baptista, A.M., Scheffner, N.W., and Farrar, P., 1992. Tide and storm-surge predictions using finite-element model. Journal of Hydraulic Engineering 118(10), 1373-1390. Wilson, B.L., 1957. Hurricane Wave Statistics for the Gulf of Mexico U.S. Army Corps of Engineers, Beach Erosion Board, Technical Memorandum 98. 119

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BIOGRAPHICAL SKETCH Nicole Sharp was born in York, Pennsylvania. Since she was a small child, her parents brought her to the beaches of O cean City, MD, every summer. The smell of the ocean, the unforgettable feeling of exfoliation from sand ad hering to freshly applied sunscreen, and the refreshing taste of a big gulp of saltwater from a large wave are all fond memories from her childhood that she would never forget. After graduating high school, Nico le enrolled at the University of Delaware where she pursued an undergraduate degree in civil engineering. While attending the University of Delaware, she was fortunate to be offered classes in the field of coastal engineering. From those classes, a desire to pursue highe r education in coastal engineeri ng grew. After deciding that a general civil engineering degree wasnt for her, Nicole enrolled in graduate school at the University of Florida for coastal engineering. While attending UF, she obtained a well-rounded education along with a degree in coastal engineering. Wherever life takes Nicole after UF, there is one thing for certain. She will be living by the coast and will have a career she enjoys. 120