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## Material Information- Title:
- Comprehensive sediement budget for the east coast of Florida
- Series Title:
- Comprehensive sediement budget for the east coast of Florida
- Creator:
- Brown, Jonathan James
- Place of Publication:
- Gainesville, Fla.
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- Coastal & Oceanographic Engineering Dept. of Civil & Coastal Engineering, University of Florida
- Language:
- English
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- University of Florida
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- University of Florida
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UFL/COEL-2002/003
COMPREHENSIVE SEDIMENT BUDGET FOR THE EAST COAST OF FLORIDA by Jonathan James Brown THESIS 2002 COMPREHENSIVE SEDIMENT BUDGET FOR THE EAST COAST OF FLORIDA By JONATHAN JAMES BROWN A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2002 For all of their support, love and encouragement, I would like to dedicate this to my family and friends, especially my parents. They all have a big part in this, and I couldn't have done this without all of them. ACKNOWLEDGMENTS I would like to sincerely thank everyone who played a part in my education at the University of Florida. I would like to thank my advisor, Dr. Robert G. Dean, for his support, and for giving me direction so I could complete this thesis. His door was always open, and he was always willing to answer any question, not matter how simple, or difficult. I would also like to thank the other members of my committee, Dr. Daniel M. Hanes, and Dr. Robert J. Thieke. They may not realize it, but they provided a great deal of help, not just in the courses that they taught, but also with their availability to answer questions. Special thanks go to everyone in the Coastal Engineering Lab, especially Sidney Schofield, Jimmy Joiner, and Viktor Adams. Their constant help and unselfishness were extremely valuable. Very special thanks go to Jamie MacMahan and Jason Engle for their help and their time with the surveys and analysis of the data from the surveys. Lastly, I would like to thank the Florida Sea Grant College Program for generously funding this project. Without funding from R/C-S-39, "Long-Term Sediment Budget for Florida's East Coast for Coastal Management," this thesis would not have been possible. TABLE OF CONTENTS pMg ACKNOWLEDGMENTS ...................................................................... iii LIST OF TABLES............................................................................... vi LIST OF FIGURES............................................................................. vii INTRODUCTION..............................................................................1. LONGSHORE TRANSPORT ................................................................... 6 Comparison of Qualitative Results for Longshore Transport (WIS Data)............11I Nassau County.........................................................................11 Duval County ............................................................................ 12 St. Johns County......................................................................... 13 Flagler County ........................................................................... 14 Volusia County .......................................................................... 14 Brevard County.......................................................................... 15 Indian River County..................................................................... 16 St. Lucie County......................................................................... 17 Martin County ........................................................................... 17 Palm Beach County...................................................................... 18 Broward County ......................................................................... 19 Dade County............................................................................. 20 Comparison of Longshore Transport at East Coast Inlets ................................ 46 CROSS-SHORE TRANSPORT................................................................ 50 Sediment Budget ............................................................................. 50 Results......................................................................................... 51 Beach Profiles ................................................................................ 55 Results......................................................................................... 57 SUMMARY AND CONCLUSIONS.......................................................... 68 Summary .................................................................................... 68 Conclusions .................................................................................. 69 BEACH NOURISHMENT ..................................................................... 71 iv LIST OF REFERENCES ................................................................................................... 74 BIOGRAPHICAL SKETCH ............................................................................................. 76 LIST OF TABLES Table pnge 2-1 Correlation of shoreline change rates from gradient of longshore transport calculated from WIS data, to shoreline change rates from historical shoreline position database ................................................................................... 10 2-2 Comparison of longshore transport values at the inlets of the east coast of Florida obtained from Walton (1973) and values obtained from WIS data from this study. (xi15S filtered from WI S data by averaging 7 points on either side of the monument in question).................................................................... 48 3-1 Average values of cross-shore transport using accepted longshore transport values from the USACE, and calculated from WIS data ....................................... 52 3-2 Summary of recommended A values (in11) for diameters from 0. 10 to 1.O9 mm. (Dean and Dalrymple, 2001).............................................................. 56 3-3 Cross-shore transport calculated from Eq. 3-4 and 3-8 for Little Talbot Island ........ 61 3-4 List of best-fit profile scale parameters from January, 2002 survey data................ 62 3-5 Cross-shore transport calculated from Eq. 3-4 using smoothed profile for January, 2002 survey. Based on UF profiles ...................................................... 63 LIST OF FIGURES Figure p_ge I-1 Definition sketch of sedim ent budget ........................................................................ 2 2-1 Longshore sediment transport calculated from WIS data using the energy flux equation for N assau County ................................................................................. 21 2-2 Measured and calculated shoreline change rates for Nassau County ....................... 22 2-3 Longshore sediment transport calculated from WIS data using the energy flux equation for D uval County ................................................................................... 23 2-4 Measured and calculated shoreline change rates for Duval County ......................... 24 2-5 Longshore sediment transport calculated from WIS data using the energy flux equation for St. Johns County ............................................................................... 25 2-6 Measured and calculated shoreline change rates for St. Johns County ..................... 26 2-7 Longshore sediment transport calculated from WIS data using the energy flux equation for Flagler County ................................................................................. 27 2-8 Measured and calculated shoreline change rates for Flagler County ........................ 28 2-9 Longshore sediment transport calculated from WIS data using the energy flux equation for V olusia County ................................................................................. 29 2-10 Measured and calculated shoreline change rates for Volusia County ..................... 30 2-11 a Longshore sediment transport calculated from WIS data using the energy flux equation for Cape Canaveral ................................................................................. 31 2-1 lb Longshore sediment transport calculated from WIS data using the energy flux equation for Brevard County ................................................................................. 32 2-12 Measured and calculated shoreline change rates for Brevard County .................... 33 2-13 Longshore sediment transport calculated from WIS data using the energy flux equation for Indian River County ........................................................................ 34 2-14 Measured and calculated shoreline change rates for Indian River County ............. 35 2-15 Longshore sediment transport calculated from WIS data using the energy flux equation for St. Lucie County ............................................................................... 36 2-16 Measured and calculated shoreline change rates for St. Lucie County ................... 37 2-17 Longshore sediment transport rates calculated from WIS data using the energy flux equation for M artin C ounty ................................................................................. 38 2-18 Measured and calculated shoreline change rates for Martin County ...................... 39 2-19 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Palm Beach County .......................................................................... 40 2-20 Measured and calculated shoreline change rates for Palm Beach County .............. 41 2-21 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Brow ard County ............................................................................... 42 2-22 Measured and calculated shoreline change rates for Broward County ................... 43 2-23 Longshore sediment transport rates calculated from WIS data using the energy flux equation for D ade County .................................................................................... 44 2-24 Measured and calculated shoreline change rates for Dade County ........................ 45 2-25 Relationship between the immersed weight longshore sand transport rate and the energy flux. (Komar and Inman, 1970) .............................................................. 47 3-1 Cross-shore sediment transport rates from sediment budget equation with accepted longshore transport values from the USACE ........................................................ 53 3-2 Cross-shore sediment transport rates from sediment budget equation with accepted longshore transport values from energy flux equation using WIS data ................ 54 3-3 Profile scale parameter, A, versus sediment diameter, d, and fall velocity, w (Dean, 1987; adapted in part from M oore, 1982) ............................................................. 56 3-4 Profiles for M onument 7 of Duval County ............................................................... 64 3-5 Profiles for M onument 10 of Duval County ............................................................... 65 3-6 Profiles for Monument 13 of Duval County ............................................................. 66 3-7 Profiles for M onument 16 of Duval County ............................................................. 67 A-I Beach nourishment volumes for the entire east coast of Florida for the period of this study (1976-1995). Compiled by Julie Rosati from data obtained from Valverde, Trembanis, and Pilkey (1999), and Kevin Bodge (2000) ..................................... 73 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science COMPREHENSIVE SEDIMENT BUDGET FOR THE EAST COAST OF FLORIDA By Jonathan James Brown August 2002 Chair: Dr. Robert G. Dean Department: Civil and Coastal Engineering The goal of this thesis is to provide a sediment budget encompassing the sandy beach portions of the east coast of Florida. The sediment budget includes analysis of the longshore transport, cross-shore transport, and beach nourishment. Longshore sediment transport was calculated using data from the Wave Information Study (WIS) conducted by the Waterways Experiment Station of the U. S. Army Corps of Engineers. The WIS data were evaluated using the energy flux equation for longshore sediment transport. Cross-shore sediment transport is implied using sediment budget concepts, known values of beach nourishment, the calculated values of longshore sediment transport, and total sediment transport values obtained from shoreline position data. Using this method, it was found that a net onshore sediment transport exists for the northeast coast of Florida. Cross-shore sediment transport was also studied in more detail for Little Talbot Island in Duval County. The cross-shore sediment transport for Little Talbot Island was analyzed using the theory of energy dissipation rate for cross-shore transport proposed by Moore, Dean, and Kriebel. The energy dissipation rate concept relates the energydissipation rate of the actual measured profile to the calculated equilibrium beach profile. Little Talbot Island was surveyed on January 20, 2002. Sediment samples were taken in conjunction with this survey to calculate the equilibrium beach profiles. An onshore transport trend for Little Talbot Island is inferred based on comparison of actual profiles and calculated equilibrium beach profiles. CHAPTER 1 INTRODUCTION Consistent with conservation of sediment principles, shorelines change due to the net flows of sediment into and out from a defined control volume, including the effects of beach nourishment and sand mining where present. The sediment inflows and outflows can be represented in the longshore and cross-shore directions and methods are available for calculating the longshore sediment transport based on wave, sediment and shoreline characteristics. However, accepted methods for calculating cross-shore transport are not generally available and these rates must be based on unproven methodology or inferred from accepted longshore sediment transport rates. One theory for barrier island formation proposed by de Beaumont (1845) is based on the presence of onshore sediment transport. Simply stated, his theory simply stated expresses that a barrier island is formed from the long-term presence of a sustained onshore transport. The rate of this transport may be low, but when integrated over thousands of years, the onshore transport volumes can be extremely large. The sediment budget equation (Dean and Dalrymple 2001) can be used to infer crossshore transport as developed below and as illustrated in Figure 1-1. Flow in the x-direction (longshore): V,, q., (x)AyAt 1o1,, = q.(x + Ax)AyAt Qy,2 Figure 1-1 Definition sketch of sediment budget Similarly for the y-direction (cross-shore): V, = q,. (y)AxAt (1-2) VO,, =q (y + Ay)AxAt Net flow into the element can be represented in the x and y directions as follows: q, (x)AyAt q, (x + Ax)AyAt =qx(x)AyAt- q,(x)+ aq, Ax AyAt= Lq AxAyAt (1-3) ax 8x q, (y)AxAt q,. (y + Ay)AxAt =q,.(y)At q,.(y)+ q Ay AxAt= q AxAyAt (1-4) Total net flow onto the element can then be expressed as follows: < x + 9MAxAyAt (1-5) &x 8- y y,1 There is also the possibility of sand being added to the profile as nourishment. Denoting this in terms of volumetric rate per unit area, s(x,y), the net volumetric increase on the element Ax by Ay in time At 8q. aq_,. ( x + AxAyAt + sAxAyAt (1-6) 8x ay The volume of sand on the element can be expressed as follows: V, (t) = zb (t)WAXAy V (t2= z (t + At)AxAy= zb(t)+ t AtjAxAy (1-7) Where Zb is the bed elevation of the control volume. The net volumetric increase can be written as follows: Zb (t + At)AxAy z (t)AxAy = zb (W+ Dz At)AxAy- z, (t)AxAy = aZb AxAyAt at at Combining the total net flow and the net volumetric change, the conservation of volume equation can be written as follows: b aqx + + (1-9) at ax ay since h+zb=constant where h is the water depth related to a fixed location: ah aZb ah aq., aq, Oh +- -s (1-10) at at at ax ay Where h is depth, or -z. This equation can be integrated across the profile (in the y direction) to yield AV = (" ) At+ + SAt (1-11) AX in which S is the volumetric nourishment rate per unit beach length and qy, in and qy, out are the flows in the y-direction at the landward and seaward ends of the control volume, respectively, and Q,, in and Qx, out are the inflow of sand and out flow of sand in the xdirection (Figure 1-1). Selecting qy, in to be sufficiently landward such that it is zero, qy, out can be expressed as follows: -AV If ...- + (Q,,- ..... -V 1Q ,)+s (1-12) At Ax The simplest and most straightforward way to obtain cross-shore transport is to determine it from the sediment budget equation as is indicated in Equation 1-12. This method requires an accepted value for the longshore transport, knowledge of the total sediment volume change, and the beach nourishment. The total volumetric change per unit length of shoreline (AV) can be based on a historical shoreline position database. Since this shoreline database is a direct measurement of the shoreline position, it will include all three components of sediment transport. Rosati summarized beach nourishment placement volumes from data obtained by Valverde, Trembanis, and Pilkey (1999), and Bodge (2000). Accurate longshore transport values are difficult to calculate. Longshore transport occurs in three modes: bedload, suspended load, and swash load. It is still not clear which of these three processes is the dominant factor in longshore transport due to the variability of wave conditions and sediment characteristics. Longshore transport cannot be measured directly, so it either needs to be predicted; or solved for indirectly using shoreline change, or by measuring deposition at some area such as a jetty, breakwater, inlet, or harbor. Dredging logs at inlets can also be used to estimate longshore transport, but these cannot be depended on to be accurate due to inaccuracies in dredging records and bypassing of sediment past the inlet. One method for calculating longshore transport is based on the energy flux model K(ECg cosO)hCb (sinO, (1-13) 1 s9(S-iXi-P) (Gb) This model uses the energy flux in the longshore direction (ECgcosO)sinO to predict the longshore transport. This energy flux is based on wave data, which includes wave height, wave direction, and wave period. This study uses both the values of longshore sediment transport from U. S. Army Corps of Engineers, and values obtained by the energy flux method using Wave Information Study (WIS) data from the Waterways Experiment Station of the U. S. Army Corps of Engineers. These results can then be employed in Eq. 1-12 to infer gross-shore sediment transport. A second method of calculating cross-shore transport utilizes a comparison of the wave energy-dissipation rate of the actual beach profile to that for the calculated equilibrium beach profile. This method is usually reasonable for predicting the direction of cross-shore transport; however the magnitude of transport may be questionable. The wave energy-dissipation rate on the profiles is dependent upon the slope of the profiles. In general, if the measured beach profile lies above the equilibrium beach profile, onshore transport exists, and the opposite is true if the measured profile lies below the calculated equilibrium beach profile. This is demonstrated for Little Talbot Island, which was surveyed in January, 1999 by the Florida Department of Environmental Protection (DEP), and January, 2002 by Jason Engle of The University of Florida Civil and Coastal Engineering Department. Sediment samples were collected at the same time as the survey taken in 2002 for a concurrent equilibrium beach profile analysis. CHAPTER 2 LONGSHORE TRANSPORT Sand transport is usually represented as a function of the wave energy available to the surf zone system. Longshore transport can be predicted using an energy model, or determined empirically, within an additive constant, using a historic shoreline database. The energy flux model relates the longshore transport to the amount of wave energy in the longshore direction. The energy flux model is expressed as follows: Q ( os) sin Ob (2-1) Where, subscript 'b' denotes breaking conditions Q = Longshore transport K = Dimensionless Parameter, 0.33 expressed in terms of significant wave height K 0.77 for periodic waves. E = Wave energy Cg = Group velocity 0 = Wave angle relative to the local contours C = Wave velocity p = mass density of medium (e.g. sea water) g = Acceleration of gravity s Specific gravity of sand 2.65 p = Porosity 0.3 For bathymetry characterized by straight and parallel bottom contours, Eq. 2-1 can be transferred to any point from which data are available using conservation of energy flux (2-2), and Snell's Law (2-3) (ECg cos O)b = (ECg cos (2-2) (sin 0J (sin90) (2-3) This conversion results in, Q K K(E'Cg'cos,8 a'))' 2 8*4 )02 (f a)cs8ah (24 pg: .,,-) / C .,og- co (, , In Eq. (2-4) denotes the location of the measurement, 13 = azimuth of the outward normal to the shoreline, at = wave angle relative to North ((13 ) = 0), and K = 0.78 (breaking wave criterion). Assuming that the waves break approximately perpendicular to the shoreline, cos (3-cab) 1. Positive transport represents transport from left to right for an observer looking in the offshore direction. In this study, the wave data used in the energy flux equation is from the Wave Information Study (WIS) database developed by the U. S. Army Corps of Engineers (USACE) Waterways Experiment Station. WIS data is produced from a hindcast computer model with "stations" represented as points in the model taken at particular offshore lacations. WIS data are available for the Pacific, Gulf of Mexico, Great Lakes, and Atlantic Coasts of the United States. This study uses the WIS data from the South Atlantic Coast, which includes the area of interest. The WIS Phase II data set covering 1976-1995, which includes hurricanes and tropical storms, is used for this study. The WIS data set includes significant wave height, peak period and direction; mean period and direction, a primary and secondary component of the spectrum, and wind speed and direction, all presented at three-hour intervals. The significant wave height and mean period and direction were used in the energy flux model. The shoreline has been characterized using the latest shoreline positions from the Florida Department of Environmental Protection Historic Shoreline Database, which is obtained from their website (www.dep.state.fl.us/beaches/data/his-shore.htm). The coordinates of the shoreline position were given in the State Plane, NAD 27 horizontal datum. This allows a simple trigonometric analysis to find the shoreline angle azimuth (03) between monuments, as the azimuth of the perpendicular of the line connecting the mean high water (MHW) shorelines between adjacent monuments. Considering the longshore transport component only, a decrease in longshore transport (negative gradient in Q) with distance results in a deposition of sand and a corresponding advancement of the shoreline, whereas an increase in longshore transport (positive gradient in Q) with distance is associated with erosion. This is based on the equation of sediment continuity. a3Q 3 a(2-5) ax at Where S = Volume rate of beach nourishment per unit shoreline length, and V = Total volume of sand, per unit beach length The predicted longshore transport using WIS data was converted to a change in shoreline position by considering the profile to move landward or seaward without change in form, ie aQ s- av (h. I B) d ax at dt faQ- fSax = -(h. + B)dYax t (2-6) AQ -SAx = -(h. + )dtA dt dy AQ SAx dt +x(h.+B) These calculated shoreline change rates were compared to values obtained from the historic shoreline position database, which were averaged over the same time period. The historic shoreline position database includes any beach nourishment since the database reports a direct measurement of MHW shoreline. Because of this, the contribution of the nourishment quantities (obtained by Rosati from Valverde, Trembanis, and Pilkey (1999), Bodge (2000)) were subtracted from the historic shoreline change rate in an attempt to quantify the values of shoreline change caused only by longshore transport. The plots of shoreline change differ from the measured in the vicinity of the nourishment areas because nourishment spreading was not taken into account by the calculation procedure; however, this should not affect the overall results in the nourishment/spreading regions. Table 2-1 presents the correlation between the measured and calculated change rates. As seen from this table, two counties correlated well (max of 0.542), while others did not. The shoreline change rates obtained from the gradient of the longshore transport calculated from WIS data were smoothed by taking a moving five point average (2 points north and 2 points south of point in question), 10 (4 points north and 5 points south), and 15 (7 points north and 7 points south). The results of this correlation can be seen in Table 2-1 with the values for the optimum moving average displayed. The correlation is noted in the last column of the table with the level of significance taken from Emery and Thompson, 1997. Table 2-1 Correlation of shoreline change rates from gradient of longshore transport calculated from WIS data, to shoreline change rates from historical shoreline position database. County Optimum Correlation Coefficient of Degrees of Significance Filter (r) Determination Freedom (Yes/No)* (r 2) Nassau x5 0.224 0.05 77 Y(5%) Duval xl0 0.300 0.09 77 Y(l%) St. Johns x15 0.179 0.03 205 Y(l%) Flagler x15 0.083 0.01 97 N Volusia x15 -0.202 0.04 232 Y(l%) Brevard x15 0.530 0.28 216 Y(l%) Indian x15 0.542 0.29 116 Y(1%) River St. Lucie xl0 0.210 0.04 112 Y(5%) Martin x5 -0.312 0.10 124 Y(l%) Palm Beach x15 -0.119 0.01 224 N Broward xl0 -0.150 0.02 124 N Dade x15 0.143 0.02 102 N *Emery and Thompson (1997), The equation for the correlation coefficient is: p(Xi xXYi YA r- ii (2-7) I ( = xi -- 50 2 1 ( i -- f)2 Where x and y denote the two different datasets, and the bar over the x and y represent the associated mean values. Correlation is a measure of the strength of the relationship between the two variables, showing whether large values of one variable are related to large values of another. The correlation coefficient can range from -i to +1. Values of-I and +1 show a perfect linear relationship between the two data sets. Negative values of the correlation coefficient represent a linear relationship with a negative slope, meaning that the two datasets are perfectly inversely correlated. To test the correlation, a level of significance is determined. The level of significance is dependent on the sample size, and the correlation. For example, if the level of significance were found to be 5%, it can be assumed that there is a 95% probability that the correlation between the two variables is not zero. This does not mean that there is a 95% chance that the two variables are related, it Just means that there exists a 95% chance that the correlation is not zero. The square of the correlation, r 2, represents the sample coefficient of determination (Table 21). The sample coefficient of determination represents the proportion of variation of one variable that can be accounted for by a linear relationship with the other. Comparison of Qualitative Results for Longshore Transport (WIS Data) Nassau County Results for this county are presented in Figures 2-1 and 2-2 for calculated longshore sediment transport and shoreline change rates respectively. Nassau County is the northern county on the east coast of Florida. Monuments 1 through 10 of Nassau County are located inside St. Mary's Entrance and are not included in this analysis (Figure 2-1 includes these monuments). The longshore transport calculated from the WIS data increases sharply from Monument 10 to Monument 11. Rapid changes in calculated longshore transport occur in the immediate vicinity of many of the inlets along the east coast, and are due to the local changes in shoreline orientation. South of this monument, from Monument 40 to 74, a steady decrease can be seen. This reduction signifies a negative gradient, which should cause a shoreline accretion (Eq. 25). This accretion can also be seen in the historical shoreline data, where a positive value of dy/dt is present of approximately 7 ft/yr. The shoreline of Nassau County has been nourished throughout, but the largest nourishments occurred from Monument 14 through Monument 34 with volumes ranging from 110 yd3/ft to 210 yd3/ft. A large amount of nourishment also occurred between Monuments 55 and 77 with volumes ranging from 180 yd3/ft to almost 340 yd3/ft. Even though the longshore transport gradient suggests the measured accretion, when the nourishment is subtracted from the shoreline change, the data indicate that the shoreline would erode without the nourishment. Another large increase can be seen from Monument 74 to Monument 79, where a large increase in shoreline angle exists, followed by a decrease at Nassau Sound, located at Monument 82, where the tidal currents and shoals certainly play a significant role, which is not taken into account in this analysis. The positive gradient from Monuments 74 to 77 is reflected in the shoreline data, both with and without nourishment. For the shoreline change rate plot of Nassau and all subsequent counties if the method were exact, the curve of shoreline change rate minus nourishment would match the curve of the shoreline change rate calculated from the gradient of the longshore transport. Duval County Results for this county are presented in Figures 2-3 and 2-4 for calculated longshore sediment transport and shoreline change rates respectively. A rapid increase in longshore transport from WIS data is evident at the north end of Duval County, at Nassau Sound. From Monuments 3 to 16, the trend of the longshore transport is relatively constant, south of which a negative gradient exists. This negative gradient is also evident in the historical shoreline data, which shows an accretion from Monument 16 until it approaches the inlet at Monument 22. The longshore transport is extremely dynamic due to the presence of Ft. George Inlet, and the St. Johns River entrance, which are located at the south end of Little Talbot Island from Monuments 25 through 31. Another negative trend in the gradient in longshore transport can be seen from Monument 32 to the south end of the Duval County shoreline. This is also supported by the positive value of dy/dt from the historical shoreline data with nourishment included, but when the nourishment was taken into consideration, the shoreline change based on longshore transport was negative at the locations of the nourishment. Duval County was nourished with over 160 yd3/ft from Monument 31 to Monument 50, and over 190 yd3/ft from Monument 60 though Monument 80. St. Johns County Results for this county are presented in Figures 2-5 and 2-6 for calculated longshore sediment transport and shoreline change rates respectively. The calculated longshore transport rates are relatively uniform to Monument 73, south of which the longshore transport steadily decreases to the St. Augustine Inlet at Monument 122. The shoreline changes based on historical data do not reflect this negative gradient, i.e. an accretion. St. Augustine Inlet, a jettied inlet located at Monument 122, is evident in the calculated longshore transport with the signature change in direction of transport. The fact that the shoreline advances on the updrift side, and erodes on the downdrift side is caused by the blockage of longshore transport by the jetties. The shoreline shape between St. Augustine Inlet and St. Augustine Pier can explain the calculated longshore transport changes seen between Monuments 122 and 142. The St. Augustine Pier is located at Monument 142, and the shoreline is heavily armored from Monument 142 to 145. After the initial drop in longshore transport at the pier, the trend is relatively constant to Monument 156, south of which a negative gradient can be seen towards Matanzas Inlet at Monument 196/197. This negative gradient is supported by the positive shoreline changes shown in the historical shoreline data. St. Johns County has been nourished just south of St. Augustine inlet, but the nourishment occurred in 1996, which is not within the time frame for this study. Flagler County Results for this county are presented in Figures 2-7 and 2-8 for calculated longshore sediment transport and shoreline change rates respectively. No inlets exist in Flagler County, because of this; the calculated longshore transport is relatively constant with the only minor variation caused by differences in shoreline angle. The shoreline change rates support this with relatively low values close to zero, which vary randomly along the shoreline, with an average value of approximately zero for Flagler County. The calculated longshore transport using WIS data is shown to be to the north throughout Flagler County, which is opposite to the accepted southerly direction. Volusia County Results for this county are presented in Figures 2-9 and 2-10 for calculated longshore sediment transport and shoreline change rates respectively. The calculated longshore transport using WIS data is shown to be to the north throughout Volusia County, i.e. opposite to the southward longshore transport which is the generally accepted direction of longshore transport for the east coast of Florida. The calculated longshore transport rates for the northern part of Volusia County are quite variable; however the trend is relatively constant to Monument 84 where a large change in magnitude occurs. This is likely due to the pier located between Monuments 83 and 84. South of the pier the transport decreases, predicting an accretion of the shoreline. Once again, the historic shoreline data support this with an accretion of the shoreline from the pier at Monuments 84 and 85 to Ponce de Leon Inlet between Monuments 148 and 149, which is jettied. The shoreline was heavily nourished with over 190 yd3/ft just north of this inlet, from Monument 142 to Monument 148 in 1985 and 1989. This can be seen on the plot of shoreline change minus the nourishment (Figure 2-10), which does not agree with the gradient in longshore transport obtained based on the WIS database. Immediately south of this inlet the gradient is once again negative which predicts accretion on the south side of the inlet, which is consistent with results from the shoreline data. Brevard County Results for this county are presented in Figures 2-1 la, b and 2-12 for calculated longshore sediment transport and shoreline change rates respectively. Cape Canaveral is located south of the Volusia/Brevard County border; however, historic shoreline data do not exist after 1970 for this segment of the shoreline. A combination of the change in shoreline shape and the wave angle causes the longshore transport to shift from relatively constant to abruptly changing direction at Monument 90 of Cape Canaveral, after which the transport reaches a peak, then decreases to change direction at Monument 118. At the most seaward extent of Cape Canaveral, the transport once again changes direction, drops off, then increases to the inlet at Monument 167 of the Cape Canaveral data set, and the first regular monument of Brevard County, i.e. south jetty of Port Canaveral Entrance. Based on shoreline orientation, the calculated longshore transport (based on WIS data) initially increases southward then becomes approximately constant at slightly less than 1,000,000 m3/yr to approximately Monument 40. However, the shoreline advances from Monument 12 through 35 because of beach nourishment from Monument 1 to Monument 82. With the nourishment removed from the shoreline change, the data still show positive shoreline change rates. South of Monument 40, the transport shows a slight negative gradient. The historical shoreline data show very little shoreline change, which is consistent with the relatively low gradient in the transport calculations, and nourishment. The beach has also been nourished relatively lightly from Monument 1 through 52 with 16 yd 3/ft, from Monument 55 through Monument 82 with 6.5 yd 3/fi, and from Monument 106 through Monument 137 with 23 yd 3/ft. Indian River County Results for this county are presented in Figures 2-13 and 2-14 for calculated longshore sediment transport and shoreline change rates respectively. Sebastian Inlet is the only inlet in Indian River County and is located at the northern county boundary. The effect of Sebastian Inlet, which has sediment bypassing, can be seen in both the calculated longshore transport, and the shoreline change data. The shoreline change data do not show erosion south of the inlet; however when the contribution of the nourishment of 44 yd 3/ft was subtracted from the shoreline change results, the effects of the inlet are evident as erosion south of Sebastian Inlet. Two large decreases in transport are predicted. The first occurs at Monument 42, which is an area where the shoreline angle decreases rapidly from 60 and 63 degrees to 56 degrees on either side at the monument. The second drop occurs between Monuments 88 and 98, also due to a change is shoreline angle. The decrease in longshore sediment transport coincides with a predicted accretion of the shoreline, shown in the historical shoreline data, as expected. The accretion ranges from Monument 88 to 101, then the shoreline erodes from Monument 10 1 to 108. This is a good example of the correlation between the historical shoreline data, and the longshore transport calculations. St. Lucie County Results for this county are presented in Figures 2-15 and 2-16 for calculated longshore sediment transport and shoreline change rates respectively. Fort Pierce Inlet, located between Monuments 33 and 34, is evident with the signature reduction of longshore transport north of the inlet, then a rapid increase in longshore transport south of the inlet. This can also be seen in the shoreline change data with an accretion on the updrift side and erosion on the downdrift side caused by the lack of bypassing sand at this jetted inlet. The shoreline just south of this inlet was nourished, but with inadequate quantities to compensate for the transport deficit. The nourishment of 87 yd3/ft of sand from 1971 to 1990 has resulted in approximately 5 feet of shoreline advancement per year. The downdrift side of this inlet has a relatively small amount of erosion because of the nourishment between Monuments 34 and 46. Other than in the vicinity of this inlet, the longshore transport and the shoreline are relatively stable. Martin County Results for this county are presented in Figures 2-17 and 2-18 for calculated longshore sediment transport and shoreline change rates respectively. The effect of St. Lucie Inlet, which is located between Monuments 42 and 43, is not immediately evident in the calculated longshore transport. The historic shoreline data show the effect of St. Lucie Inlet more clearly with accretion on the updrift side of the inlet, and extreme erosion immediately downdrift of the inlet. The calculated longshore transport rates do not show a negative trend in the gradient north of Monument 60; however, the shoreline data show a deposition of sand from Monuments 45 through 60 and erosion from Monument 60 to 112. According to the nourishment data, the beach has only been nourished from Monument 60 to Monument 111. This causes the negative correlation shown in Table 2-1. This odd correlation can be caused by the heavy amount of nourishment from Monument 60 to 111 and also the inlet itself. The effect of the nourishment of 100 yd3/ft of sand from Monument 60 through Monument 111 can be seen in Figure 2-18. Palm Beach County Results for this county are presented in Figures 2-19 and 2-20 for calculated longshore sediment transport and shoreline change rates respectively. There is a general trend of decreasing calculated longshore sediment transport in Palm Beach County, from the WIS database. This general negative gradient should be associated with positive shoreline advancement, which is also evident in the historical data prior to the subtraction of the nourishment contributions from the shoreline data. With nourishment taken into account, the shoreline change rate is negative. The effect of Jupiter Inlet can be seen in the calculated longshore transport at Monuments 12 and 13; however the shoreline is eroded on the updrift side, and advances on the downdrift side. This is the opposite of what is expected from the longshore transport gradient calculated from the WIS data. The accretion on the downdrift side is attributed to the large nourishment volume of approximately 70 yd3/ft in 1995. When the effects of the nourishment are removed from the shoreline data, the erosion on the south side of Jupiter Inlet is evident even though sediment is bypassed across this inlet. The effect of the Lake Worth Inlet at Monument 75, which also has sediment bypassed across it, is evident in the gradient of the longshore transport, and is also evident in the shoreline change data after the nourishment of approximately 60 yd3/ft is subtracted. These anomalies can be seen in the negative correlation coefficient in Table 2-1. Additionally, the data do not pass the significance requirements of the correlation test. The effects of the South Lake Worth Inlet at Monuments 150 and 151 can be seen in the calculated longshore transport, but are reasonably small in the shoreline change rate data because sediment is bypassed across this inlet. The effects of Boca Raton Inlet at Monuments 222 and 223, which also has sediment bypassed across it, are evident in both the calculated longshore transport, and the shoreline change data. The effects of the jetties at Boca Raton Inlet can be seen in the fact that the shoreline is accreting on the updrift side and eroding on the downdrift side of the inlet. The Palm Beach County shoreline was also nourished from Monument 177 to Monument 189 with approximately 180 yd3/ft, and from Monument 204 through Monument 213 with approximately 90 yd3/ft. Broward County Results for this county are presented in Figures 2-21 and 2-22 for calculated longshore sediment transport and shoreline change rates respectively. The effects of Hillsboro Inlet between Monuments 24 and 25, and Port Everglades Entrance between Monument 84 and 85 are evident in the calculated longshore sediment transport. Similar to Palm Beach County, the shoreline change is the opposite of that expected at Hillsboro Inlet which has sediment bypassing. This is reflected in the negative correlation coefficient. The shoreline change responds in the expected way at the Port Everglades Entrance, i.e. the shoreline advances on the updrift side of the inlet, and erodes on the immediate downdrift side based on both the historical shoreline data, and on the gradient of longshore sediment transport obtained from the WIS database. The longshore transport gradients for the rest of Broward County are relatively small. The shoreline data however show erosion for most of the county's shoreline. This net erosion is apparent after accounting for the large amount of nourishment from Monuments 40 through 60 (90 yd3/ft), and from Monument 85 through 128 (100 yd3/ft). Thus, assuming that the nourished areas were eroding, since it is perceived from the calculated longshore transport that there is no erosion, or accretion, the nourishment has stabilized the shoreline. Thus, the beach nourishment has spread out, and evolved the shoreline such that the longshore transport gradients are minimal. Dade County Results for this county are presented in Figures 2-23 and 2-24 for calculated longshore sediment transport and shoreline change rates respectively. Other than near the north end of the Dade County, the calculated longshore transport is relatively uniform north of Monument 40. The shoreline data show considerable erosion. The nourishment of 250 yd3/ft near the north end of Dade County from Monument 5 through Monument 10, and 77 yd3/ft north of Baker's Haulover Inlet account for this. The effect of Bakers Haulover Inlet, at Monuments 26 and 27, is evident in the longshore transport calculations. A large number of inlets are present at the south end of the Dade County shoreline, which account for the large variability of longshore transport. Government Cut at Monuments 74 and 75 is evident in the shoreline data, which is then followed southward by a decrease of shoreline advancement on the south side of the inlet. This is likely due to the small amounts of beach nourishment of approximately 16 yd3/ft placed in this region, which is subtracted from the historic shoreline data, but still causes an anomaly in the data. South of Bear Cut at Monuments 89 and 90 the shoreline shows a net advancement, again due to the large amount of beach nourishment. Nassau County Longshore Transport from WIS Data 2.00E+06 1.50E+06 ... St. I ary's Entrance 1.00E+06 Entance 5.00E+05 I O.OOE+OO- 7 a 1 20 3 4 5 .... 7 -5.00E+05 -1.00E+06 -1.50E+06 -2.00E+06 Monument Figure 2-1 Longshore sediment transport calculated from WIS data using the energy flux equation for Nassau County Nassau County Shoreline Change Rate - -- - Measured dy/dt I dy/dt-Nourishment - WIS Average (X5) Monument Figure 2-2 Measured and calculated shoreline change rates for Nassau County Duval County Longshore Transport from WIS Data 2.00E+06 1.50E+06Ft. George Nassau Inlet 1.OOE+06 ound 5.00E+05 SO.OOE+O0 a 10 20 30 40 50 60 70 80 -5.00E+05 -1.E+06 St. Johns -1 .00E+06 iver -1.50E+06 .... -2.00E+06 -- -- - Monument Figure 2-3 Longshore sediment transport calculated from WIS data using the energy flux equation for Duval County Duval County Shoreline Change Rate ----- Measured dy/dt -dy/dt-Nourishment WIS Average (X1O) Monument Figure 2-4 Measured and calculated shoreline change rates for Duval County St. Johns County Longshore Transport from WIS Data 2.00E+06 1.50E+06 St. A gustine M tana as 1.00E+06 I let Inlet 5.00E+05 4 O.OOE+OO00 8O O) 13 20 30 4r 63 70 80 9 100,,,,l 0 1 0' 0 14 150 160 170 1.8 )0 !,2 0 0 -5.00E+05 1 -1.00E+06 --1.50E+06 T -2.00E+06 -- --. Monument Figure 2-5 Longshore sediment transport calculated from WIS data using the energy flux equation for St. Johns County St. Johns County Shoreline Change Rate (St. Johns County was not nourished between 1976 and 1995) m Measured dy/dt - WIS Average (X15) Monument Figure 2-6 Measured and calculated shoreline change rates for St. Johns County Flagler County Longshore Transport from WIS Data 2.00E+06 1.50E+06 1.00E+06 5.00E+05 3.OOE+0 40 56 -5.00E+05 ar -1.00E+06 -1.50E+06 -2.00E+06 Monument Figure 2-7 Longshore sediment transport calculated from WIS data using the energy flux equation for Flagler County -- -I Flagler County Shoreline Change Rate (Flagler County was not nourished from 1976-1995) -Measured dy/dt - WIS Average (X15) Monument Figure 2-8 Measured and calculated shoreline change rates for Flagler County 6 4 2 e=0 -2 -4 -6 -8 Volusia County Longshore Transport from WIS Data 2.00E+06 1.50E+06 1.00E+06 Pon e de eon Inlet 5.00E+05 40 10 2008040 A50,, 0 800 10 1 0 10 1 0 1 0 1 010 10 20 20 -5.00E+05 _-"-_r-1.00E+06 --1.50E+06 1 -2.00E+06 - -. -. -. -- Monument Figure 2-9 Longshore sediment transport calculated from WIS data using the energy flux equation for Volusia County 30 25 20 15 ,. 10 5 0 -5 -10 Monument Figure 2-10 Measured and calculated shoreline change rates for Volusia County Volusia County Shoreline Change Rate ----- Measured dy/dt dy/dt-Nourishment WIS Average (X15) -i 240 Cape Canaveral Longshore Transport from WIS Data 2.00E+06 1.50E+06 1.00E+06 5.00E+05 -.. ...-- __' 10 20 30 40 50 60 70 80 9 110 110 1 0" 1 0 1 0 ;0 160 170 -5.00E+05 -1.00E+06 --- -.---1.50E+06 -2.00E+06 .. Monument Figure 2-11 a Longshore sediment transport calculated from WIS data using the energy flux equation for Cape Canaveral Brevard County Longshore Transport from WIS Data 2.OOE+06 1.50E+06 1.00E+06 5.00E+05 S 10 0 405 60 7 90 100 10 10 130 140 1 10 10 0 1 0 -5.OOE+05 -1.00E+06 -1.50E+06 -2.00E+06 ...- --L.-.Monument Figure 2-1 lb Longshore sediment transport calculated from WIS data using the energy flux equation for Brevard County astian istian let 1 20 ----- Measured dy/dt -dy/dt-Nourishment -WIS Average (X15) Monument Figure 2-12 Measured and calculated shoreline change rates for Brevard County Brevard County Shoreline Change Rate Indian River County Longshore Transport from WIS Data 2.00E+06 Set 1.50E+06 1.00E+06 5.00E+05 0.00E+00 -5.00E+05 -1.00E+06 -1.50E+06 -2.00E+06 - astian nlet 1 2 -K - 50 6 0 80 90 1 () 1 - 120 Monument Figure 2-13 Longshore sediment transport calculated from WIS data using the energy flux equation for Indian River County Indian River County Shoreline Change Rate . .---- ----- Measured dy/dt 120 -dy/dt-Nourishment WIS Average (X1 5) Monuments Figure 2-14 Measured and calculated shoreline change rates for Indian River County St. Lucie County Longshore Transport from WIS Data 2.00E+06 1.50E+06 1.00E+06 5.oo00E+05 -_ _ _ _""_.....__ _ ' O .OOE+00 I C 1 20 3 40 50 60 70 8 9 1 0 110 120 Ft. Pierce -5.00E+05 Inlet -1.00E+06 -1.50E+06 -2.00E+06 Monument Figure 2-15 Longshore sediment transport calculated from WIS data using the energy flux equation for St. Lucie County St. Lucie County Shoreline Change Rate ----- .....Measured dy/dt -, dy/dt-Nourishment 120 WIS Average (X10) Monument Figure 2-16 Measured and calculated shoreline change rates for St. Lucie County Martin County Longshore Transport from WIS Data 2.00E+06 1.50E+06 1.00E+06 5.00E+05 0.00E+00 -5.00E+05 -1.00E+06 -1.50E+06 S Lucie Inlet - 1; 2 4 0 3 ) 5 * *~h _____________ 0I 0 1,1 0 130 -7 -2.00E+06 -L ---- -.-- Monument Figure 2-17 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Martin County -v- Martin County Shoreline Change Rate ------- Measured dy/dt dy/dt-Nourishment WIS Average (X5) Moument Figure 2-18 Measured and calculated shoreline change rates for Martin County Palm Beach County Longshore Transport from WIS Data - - 2.00E+06 1.50E+06 1.00E+06 5.00E+05 0.00E+00 -5.00E+05 -1.00E+06 -1 50E1=+06R -2.00E+06 . Monument Figure 2-19 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Palm Beach County Palm Beach County Shoreline Change Rate - ------Measured dy/dt -dy/dt-Nourishment WIS Average (X15) Monument Figure 2-20 Measured and calculated shoreline change rates for Palm Beach County 20 10 0 -10 -20 -30 -40 -50 Broward County Longshore Transport from WIS Data 2.00E+06 1.50E+06 1.00E+06 HIsboro Port Inlet Everglad s 5.00E+05 O O.OOE+O0 ___ ' 1 20 30 4 0 60 0 8 90 100 1 0 1 0 -5.00E+05 -1.00E+06 -1.50E+06 --_-2.00E+06 L - -- - Monument Figure 2-21 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Broward County 130 30 ----- Measured dy/dt - dy/dt-Nourishment (ft/yr) - WIS Average (X1O) ftlyear Monument Figure 2-22 Measured and calculated shoreline change rates for Broward County Broward County Shoreline Change Rate Dade County Longshore Transport from WIS Data 2.00E+06 1.50E+06 -1.00E+06 Baker's Government Haulover Cut Bear Cui 5.OOE+05 -I---' O .OOE+002 30 41 4 0 70 0 0 1 0 1 -5.00E+05 Nonris Cut -1.00E+06 -1.50E+06 -2.00E+06 Monument Figure 2-23 Longshore sediment transport rates calculated from WIS data using the energy flux equation for Dade County Dade County Shoreline Change Rate -- ------ Measured dy/dt -dy/dt-Nourishment (ftlyr) WIS Average (X15) ft/year Monument Figure 2-24 Measured and calculated shoreline change rates for Dade County Comparison of Longshore Transport at East Coast Inlets The longshore transport values calculated by Walton (1973) were compared to the longshore transport calculated from WIS data. This will provide a more direct comparison of two different methods of calculation. Walton used a longshore energy flux model which was very similar to the one used in this study, except the waves were based on SSMO observations, i.e. ship board observations of wave height, period and direction, and the waves were transformed to shore accounting for friction and percolation with the "friction-percolation coefficient," Kfp. Walton's calculations were based on Q = 125E, 24(3600) (2-9) S(EoCgo coSao)Kp sinh 106 Where, Q = Longshore transport in cubic years per day Ea= Longshore energy flux in millions of ft. lbs. per day per foot of beach Eo = yHo2/8 = the deep water surface energy density y = specific weight of seawater = 64 lbs/ft3 Ho = deep water wave height in feet Cgo = deep water wave group velocity in ft/sec ao = deep water angle of wave approach to coastline Ctb = breaking angle of wave approach to coastline Kfp = friction-percolation coefficient, Bretschneider and Reid (1954) In 1973, when Walton conducted his studies, there were only 5 wave gages along the Florida coast. None of those wave gages measured wave direction, which is a critical 47 parameter for calculating the longshore transport. The only wave data that existed which included wave direction was data taken by ships at sea, and assembled by NOAA. The longshore sediment transport model applied in this report uses the dimensionless parameter K = 0.77 for breaking wave height found by Komar and Inman (1970), which was converted to 0.33 since significant wave heights are presented in the WIS data. Komar and Inman found their coefficient by plotting the immersed weight sediment transport rate to the longshore component of the energy flux. The dimensionless coefficient of 0.77 was the value that fit the data best. 10' I I ' 0 El Moreno Beach a Silver Strand Beach LU 107 0 i; 100 3 0 0 S ,I1, I lp I to'I0 10' i0' 10' (ECn)b cos 0ab erg/sec-cm Figure 2-25 Relationship between the immersed weight longshore sand transport rate and the energy flux. (Komar and Inman, 1970) Table 2-2 presents the values of longshore sediment transport obtained by Walton (1973), the USACE, and values obtained in this study using WIS data. Even though both Walton's values, and the values calculated from the WIS data are based on the energy Table 2-2 Comparison of longshore transport values at the inlets of the east coast of Florida obtained from Walton (1973) and values obtained from WIS data from this study. (x 15 filtered from WIS data by averaging 7 points on either side of the monument in question) Inlet Qnet from Walton Qnet from USACE Q from WIS Data (yd3/yr) (yd3/yr) (yd3/yr) (x 15) St. Mary's Entrance 200,000 550,000 N/A St. John's River 250,000 480,000 123,000 St. Augustine Inlet 380,000 440,000 -265,000 Matanzas Inlet 290,000 440,000 -326,000 Ponce De Leon Inlet 180,000 500,000 -616,000 Port Canaveral Inlet 250,000 360,000 153,000 Sebastian Inlet 160,000 300,000 -5,000 Ft. Pierce Inlet 140,000 225,000 553,000 St. Lucie Inlet 200,000 230,000 623,000 Jupiter Inlet 240,000 230,000 739,000 Lake Worth Inlet 380,000 230,000 293,000 S. Lake Worth Inlet 280,000 230,000 151,000 Boca Raton Inlet 280,000 150,000 176,000 Hillsboro Inlet 280,000 100,000 167,000 Port Everglades Inlet 270,000 50,000 179,000 Baker's Haulover 270,000 20,000 178,000 Inlet Government Cut 270,000 20,000 91,000 flux model, the two sets of results do not correlate well, especially for the northern inlets of Florida. The discrepancy is most likely due to the two different sources of wave data for the studies. When compared to actual measured wave heights from the National Data Buoy Center, at similar points in space, the WIS hindcasts correlate relatively well (r = 0.509, for 2759 degrees of freedom); however predictions of longshore sediment transport also require wave direction, and wave period. The results obtained by Walton are much less variable along the coast. Walton stated that it has been shown that the wave observers are biased to characterizing the wave direction as N, E, S, W, NE, SE, SW, and NW. This bias as well as the incompleteness of this dataset is probably the major reason for the lack of variability. WIS hindcast data include wave direction every 49 three hours reported to the degree compared to the 45 degree segments of the observed wave data used by Walton. The values of longshore transport provided by the USACE are the most direct measurement of longshore transport of the three, and are based on the rate of updrift sediment accumulation at the jetties of the inlets (Dean and O'Brien, 1987). CHAPTER 3 CROSS-SHORE TRANSPORT Sediment Budget As discussed previously, using the historical shoreline position data, a value for dy/dt was determined for approximately the same 20-year period of the WIS data. In this chapter the sediment transport is calculated from the shoreline change rate using the continuity equation, and assuming an equilibrium beach profile. 8Q av (h. + B)d (3-1) ax at dt where h.= Depth of closure B Berm height dy- Average shoreline change rate between xo and x dt The value calculated from the shoreline change data are considered to be the total volume change rate into the system, which includes the longshore transport, the crossshore transport, and the beach nourishment. With the assumed amount of volume change rate, the accepted values for longshore transport, and the beach nourishment volumes, the cross-shore transport can then be calculated, using the sediment budget equations from Chapter 1 (Equation 1- 12), where the total volume change rate is equal to AV/At. - -AV 1, -+ -(Q, -Q, )S (1-12) At Ax"- Results The values of longshore transport from the USACE were used to obtain the qy, out values presented in Figure 3-1. It can be seen in Figure 3-1, that when the USACE values for longshore transport are used to solve for values of cross-shore transport, the general result is onshore transport for the section of the Florida coastline north and south of Cape Canaveral. A gap in the results occurs at Cape Canaveral because the historical shoreline database does not include surveys after 1975. The average cross-shore transport value for the entire east coast of Florida is in the onshore direction at approximately 2.8 yd3/year per foot of shoreline. An onshore transport of 2.8 yd3/year per foot of shoreline translates to approximately 3 feet/year of shoreline accretion, considering (h,+B) = 25 feet. It is emphasized that this value accounts for the effect of beach nourishment. The values of cross-shore transport using longshore transport values calculated from WIS data can be seen in Figure 3-2. The average resulting cross-shore transport using longshore transport values derived from WIS data is just over 1.7 yd3/year per foot of shoreline in the onshore direction. An average onshore transport of 1.7 yd3/year per unit length of shoreline translates to approximately 1.8 feet of shoreline accretion, considering (h,+B) = 25 feet. Since both of the representations of cross-shore transport result in onshore transport, the shoreline should accrete, on average, over time without any disturbances. Large values of calculated onshore and offshore transport occur at the inlets along the east coast of Florida. This is caused by the large shoreline change rates that occur at these inlets which cause large values for AV/At which in turn cause large values of cross- shore transport when calculated from Eq. 1-12. These variations at the inlets cancel when considering the large scale of the entire east coast of Florida. The trend line for the values calculated using USACE results for longshore transport shows a decrease of onshore transport from Nassau County toward Cape Canaveral. South of Cape Canaveral to Dade County, the trend line shows an increase of onshore transport. The cross-shore transport calculated using the longshore transport values obtained from WIS data have a constant trend which is dominated by the average onshore transport of approximately 1.8 yd3/year per foot of shoreline. Table 3-1 Average values of cross-shore transport using accepted longshore transport values from the USACE, and calculated from WIS data. Qy, USACE Qy, WIS Nassau -9.6 yd3/ft/yr -2.0 yd3/ft/yr Duval -7.9 yd3/ft/yr -10.5 yd3 /ft/yr St. Johns -0.85 yd3/ft/yr -2.2 yd3/ft/yr Flagler 0.25 yd 3/ft/yr 2.6 yd3/ft/yr Volusia -3.1 yd3/ft/yr -5.7 yd 3/ft/yr Brevard 0.048 yd3/ft/yr 4.2 yd 3/ft/yr Indian River -0.47 yd3/ft/yr -2.7 yd3/ft/yr St. Lucie -0.82 yd3/ft/yr 3.5 yd3/ft/yr Martin -2.9 yd 3/ft/yr -2.5 yd3/ft/yr Palm Beach -1.7 yd 3/ft/yr -0.20 yd3/ft/yr Broward -3.6 yd3/ft/yr -4.2 yd3/ft/yr Duval -6.0 yd3/ft/yr -5.0 yd 3/ft/yr Total -2.8 yd3/ft/yr -1.7 yd3/ft/yr Cross-Shore Transport qy=(-AVAt(from dyldt))+(AQx, USACE/AX)+(SIAx) Distance Along the FL Coastline (miles) Figure 3-1 Cross-shore sediment transport rates from sediment budget equation with accepted longshore transport values from the USACE. Cross-Shore Transport qy=(-AV/At(from dyldt))+(AQx, wis/Ax)+(S/Ax) 2500 2000 1500 1000 -500 -1000 -1500 -2000 Distance Along the FL Coastline (miles) Figure 3-2 Cross-shore sediment transport rates from sediment budget equation with accepted longshore transport values from energy flux equation using WIS data Beach Profiles Cross-shore transport can also be implied from a comparison of beach profiles. Moore (1982) was the first to develop this hypothesis, followed by Kriebel (1982), and Kriebel and Dean (1985). The theory is based upon the concept that for a uniform sand size across a profile, the wave energy-dissipation rate per unit water volume is uniform. This is the same basis used to develop the equilibrium beach profile, which is represented by; h(y)= Ay2/3 (3-2) where h = water depth y = distance from mean water line (MWL) in the offshore direction A = profile scale parameter, which is a function of energy-dissipation rate (D), and indirectly sediment size (d). (Figure 3-3, and Table 3-2) For the case of nonuniform sediment sizes, the following is valid: h(y)= (h 3/2 + A 3/2(y 1))3 (3-3) where yn difference in the energy-dissipation rate for the particular profile and the dissipation rate for the equilibrium beach profile. q, = K(D D, ) (3-4) where qy = volumetric cross-shore transport in the offshore direction Sediment Fall Velocity. w (cn/s) 1 0.1 1 Suggested Empiricar Relationship A vs. D (Moore) From Hughes' From Individual Field Field Results Profiles where a Range of Sand Sizes was Given\\ __ AA A .m Swarrs Laboratory Result., 1.0 10.0 100.0 '1% Based on Transforming A vs. D Curve using Fall Velocity Relationship Sediment Size, D (mm) Figure 3-3 Profile scale parameter, A, versus sediment diameter, d, and fall velocity, w (Dean, 1987; adapted in part from Moore, 1982) Table 3-2 Summary of recommended A values (mi13) for diameters from 0.10 to 1.09 mm. (Dean and Dalrymple, 2001) d(mm) 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.063 0.0672 0.0714 0.0756 0.0798 0.084 0.0872 0.0904 0.0936 0.0968 0.2 0.100 0.103 0.106 0.109 0.112 0.115 0.117 0.119 0.121 0.123 0.3 0.125 0.127 0.129 0.131 0.133 0.135 0.137 0.139 0.141 0.143 0.4 0.145 0.1466 0.1482 0.1498 0.1514 0.153 0.1546 0.1562 0.1578 0.1594 0.5 0.161 0.1622 0.1634 0.1646 0.1658 0.167 0.1682 0.1694 0.1706 0.1718 0.6 0.173 0.1742 0.1754 0.1766 0.1778 0.179 0.1802 0.1814 0.1826 0.1838 0.7 0.185 0.1859 0.1868 0.1877 0.1886 0.1895 0.1904 0.1913 0.1922 0.1931 0.8 0.194 0.1948 0.1956 0.1964 0.1972 0.198 0.1988 0.1996 0.2004 0.2012 0.9 0.202 0.2028 0.2036 0.2044 0.2052 0.203 0.2068 0.2076 0.2084 0.2092 1.0 0.210 0.2108 0.2116 0.2124 0.2132 0.2140 0.2148 0.2156 0.2164 0.2172 K = dimensional constant (different from K in longshore transport equation) = 2.2x10-6 m4/N (Moore, 1982), or 1.13x10-3 ft4/lb D = energy-dissipation rate for the profile, and the subscript "" represents the equilibrium beach profile When D is greater than D., the turbulence will be greater than when D is equal to D*, and will cause offshore sediment transport. When D is less than D., the opposite is true, and onshore sediment transport is implied. .0 1.01 A(mt13) 0.10 0.01 0.0 A-0.067 w.44 01 0 ZZ The energy-dissipation per unit water volume can be expressed as a function of grain size: IldF - D(d) = _d h dy' - hD(d)- = pgKh(3-5) D(d) = 56OgIC 2 h dh 16 dy where F = wave energy flux y' = shore normal directed onshore For equilibrium beach profiles, the energy-dissipation rate can be determined directly from the profile scale parameter using the following equation. 2/3 24D 2 (3-6) A= 5,ogIC2 /g-) It can be seen from Eq. 3-5 that the energy-dissipation is dependent upon beach slope consistent with the Moore, Kriebel, and Dean concepts. The energy-dissipation is also dependent upon water depth, but to a lesser degree due to the square root. Results This study concentrates on Little Talbot Island, which is located just north of Jacksonville, FL, in Duval County. Little Talbot Island is bounded by Nassau Sound on the north, and Fort George Inlet on the south and encompasses Monument 1 through 25 in Duval County. The last shoreline survey of Little Talbot Island conducted by the Florida Department of Environmental Protection (DEP) was in January, 1999 and includes profiles at each of the 25 monuments on Little Talbot Island. Jason Engle of the University of Florida Department of Civil and Coastal Engineering also surveyed profiles on January 20, 2002 in conjunction with the present study. This survey was conducted using the Department's wave runner, which was equipped with an echo sounder and a Global Positioning System (GPS). The data logger onboard the wave runner coordinates the depth from the echo sounder with the GPS position to generate the data file for the profile. This is relatively automated and provides a much more precise survey with more data points that is accurate to within approximately plus or minus 5 cm vertically (MacMahan, 199 1). To provide the basis for calculating equilibrium profiles, surface sediment samples were taken every third monument, starting with Monument 7, by dragging a bucket at approximate 1000 ft intervals cross-shore, along with grab samples taken from the beach face. The sediment samples were analyzed for sediment size using two methods as described below. The first method of sediment characteristic measurement and analysis was through the use of sieves, a common method among geotechnical engineers, and involves the uses of screens with different size openings to segregate different sediment sized particles. Since sieve analysis is impractical for sediment sizes less than 0.075 mmn the sediment is first washed through the number 200 sieve to remove any sediment less than 0.075 mm in diameter. Sediments smaller than 0.075 mm are considered silts and clays, which are relatively easily suspended in the surf zone. Because silts and clays remain suspended they tend to be transported out of the surf zone, and do not contribute to the profile stability. After the sediment is washed, and dried in an oven, it is sorted through the sieves using a RoTap. The sizes of sieves that were used for this analysis were number 10 (2 mm), 20 (0.841 mm), 30 (0.595 mm), 50 (0.297 mm), 60 (0.25 mm), 70 (0.212 mm), 80 (0.177 mm), 100 (0. 149 mm), 120 (0.125 mm), 140 (0.106 mm), 170 (0.09 mm), and 200 (0.075 mm). The sieves are then weighed to measure the amounts of the various sized sediments remaining on the sieves. This distribution is then used to obtain the median sediment size, on which the profile scale parameter (A) is dependent (Figure 3-3, and Table 3-1). The second method used to analyze the sediment is based on fall velocity. This should provide a more direct link to the equilibrium beach profile since for the equilibrium beach profile theory, the profile scale parameter is linearly related to the fall velocity (on a loglog plot), as can be seen in Figure 3-3 (Dean 1987). The rapid sediment analyzer (RSA) was used for this analysis. The RSA functions by dropping a sample of sediment from a specified height through a column of water. A pan at the bottom of the water column collects the sediment, which is weighed by a load cell at certain intervals of time. The distance the sediment travels through the water column (246 cm for our apparatus) is divided by the time required for the sediment to reach the pan to find the fall velocity through water. The approximate sediment sizes can then be determined from this distribution of fall velocities using the following formula by Gibbs (197 1). = O 3v + v~9v2 + gd2 (s 1XO.003869 + 0.02480d) (3-7) 0.011607 + 0.07440d where wo= settling velocity (cm/sJ d = sediment grain size diameter (cm) v = fluid viscosity (CM2/S) Just as was done with the distribution obtained by sieve analysis, the median grain size is extracted from the distribution obtained from the RSA. These sediment sizes were used to calculate equilibrium beach profiles using Eq. 3-3. These profiles were then compared, using Eq. 3-4, to the profiles measured by the DEP in 1999, and to the profiles surveyed in January 2002. The energy-dissipation rates for the measured profiles were calculated at each measurement of elevation using the individual slopes at those points. The energy-dissipation rates for the equilibrium beach profiles were calculated using the profile scale parameter, and Eq. 3-6. The cross-shore transport was then calculated for each measurement of elevation using Eq. 3-4. A weighted average of the cross-shore transport was taken from the MWL to the point corresponding to 15 ft of depth. The average was only taken to 15 ft of depth due to the fact that equilibrium beach profiles have been found to be representative to only 13 to 16.5 feet of depth. (Charles, 1994) The weighted average is found by multiplying the individual cross-shore transport rates by the Ay values separating the sample points and normalizing as 97 q. y (3-8) where q,, the individual cross-shore transport calculation Ayj distance separating the individual cross-shore transport rates in the y-direction qs, Total = the weighted average for the section of interest The average cross-shore transport values calculated from profiles and sediment sampled from January, 2002 was 1,841 yd 3/ft/yr onshore from the sieve data, and 1,451 Table 3-3 Cross-shore transport calculated from Eq. 3-4 and 3-8 for Little Talbot Island. January, 2002 January, 1999 (DEP) Profile Sieve RSA Sieve RSA R-07 -1314 yd3/ft/yr -1316 yd3/ft/yr -1143 yd3/ft/yr -1302 yd3/ft/yr R-10 -2427 yd3/ft/yr -1190 yd3/ft/yr -2039 yd3/ft/yr -1185 yd3/ft/yr R-13 -1594 yd3/ft/yr -1659 yd3/ft/yr -13258 yd3/ft/yr -13298 yd3/ft/yr R- 16 -2030 yd3/ft/yr -1637 yd3/ft/yr -2288 yd3/ft/yr -1715 yd3/ft/yr Average -1841 yd3/ft/yr -1451 yd3/ft/yr -4682 yd3/ft/yr -4375 yd3/ft/yr yd3/ft/yr onshore from the fall velocity data. This can be compared to the values calculated using the DEP's profiles taken in January of 1999. The cross-shore transport values calculated from the DEP profile are both onshore with quantities of 4,682 yd3/ft/yr using the sieve data, and 4,375 yd3/ft/yr using the RSA data. This large difference between the 2002 and 1999 surveys can be attributed to Monument 13. The sediment used to determine the equilibrium beach profile at the beach face was coarse relative to the other profiles. The reason this anomaly does not show up in the calculations using the 2002 profile is the fact that the 2002 profile was not defined in as shallow water as the DEP profiles. This means that the section of the equilibrium beach profile represented by this large sediment size was not taken into account with the analysis for the 2002 profile. The profile at Monument 19 was excluded because of the close proximity to the Ft. George Inlet. The values calculated for cross-shore transport are too large to be considered realistic. A cross-shore transport value on the order of magnitude of 4,000 yd3/ft/yr would translate into an annual accretion of 4,000 feet of shoreline with an (h,+B) value of 25 feet. Thus direction of the cross-shore sediment transport is the most significant finding from this analysis. The energy-dissipation theory of cross-shore sediment transport is not considered to be sufficiently accurate to yield valid transport magnitudes; however, the basic concept of the theory can be accepted to provide good approximations for the direction of cross-shore transport. The profiles surveyed by the wave runner are more precise with measurements at one to two foot intervals, while the DEP profiles are reported at an average of 50-foot intervals in the cross-shore direction. The irregularities associated with the closely spaced data can result in undesirable interpretation effects. For this purpose a "best fit" profile scale parameter was determined using the method of least squares. hi =Ay 2/3 S 2 Y[hi _Ay 72 3]2 aC2 2/3-A/] (3-9) _ => "[hiyi yi/ 39 jh Yi 2/3 A BestFit 4/3 Table 3-4 List of best-fit profile scale parameters from January, 2002 survey data. Monument Best fit profile scale parameter (m/3) 7 0.098715 10 0.116039 13 0.115551 16 0.078604 This representative profile scale parameter determined by the least squares method is then used to find an associated energy-dissipation rate using the same equation as for the individual profile scale parameters. This smoothing removes profile irregularities such as bars, and any other features that could cause slope anomalies. It can be seen from Table 3-5 that the smoothed data shows, on average, onshore transport. At Monument 10, even though the representative equilibrium profile is above the equilibrium profile based on the sediment samples analyzed with the RSA, the data show offshore transport because the representative profile has a steeper slope. The same is true for the profile at Monument 13 when comparing the profile from the sieve data. This is due to the fact that the energy-dissipation is directly related to the slope, compared to the square root of the water depth. All of the other smoothed representations of cross-shore transport show onshore transport, which agrees with the values, obtained using the DEP profiles. Table 3-5 Cross-shore transport calculated from Eq. 3-4 using smoothed profile for January, 2002 survey. Based on UF profiles. January, 2002 Profile Sieve RSA R-07 -611 yd3/ft/yr -613 yd3/ft/yr R-10 -1567 yd3/ft/yr -239 yd3/ft/yr R-13 -592 yd3/ft/yr -657 yd3/ft/yr R- 16 -924 yd3/ft/yr -530 yd3/ft/yr Average -924 yd3/ft/yr -510 yd3/ft/yr R-07 1000 1500 2000 2500 3000 3500 --1 4000 Waverunner (2002) ____ DEP (1999) - - Equilibrium (Sieve) -Equilibrium (RSA) Best Fit (2002) Distance from DEP Monument (ft) Figure 3-4 Profiles for Monument 7 of Duval County. R-1O 1000 1500 2000 2500 3000 3500 -Waverunner (2002) ___ DEP (1999) - - Equilibrium (Sieve) ----- Equilibrium (RSA) - Best Fit (2002) Distance from DEP Monument (ft) Figure 3-5 Profiles for Monument 10 of Duval County. R-13 20 15 10 5 ' 0 -_--- -' ..... W a v e ru n n e r (2 0 0 2 ) > 1000 1500 2000 2500 3000 3500 4000 5 DEP (1999) z -5 - Equilibrium (Sieve) "- -"- - - - -Equilibrium (RSA) 0 -10 Best Fit (2002) * -10... .. .. . . > w -15 . -20 "" -..-".-. -25 Distance from DEP Monument (ft) Figure 3-6 Profiles for Monument 13 of Duval County. R-16 1500 2000 2500 0 0Waverunner (2002) 3000_ DEP (1999) - -- Equilibrium (Sieve) -----Equilibrium (RSA) Best Fit (2002) Distance from DEP Monument (ft) Figure 3-7 Profiles for Monument 16 of Duval County. 1000 CHAPTER 4 SUMMARY AND CONCLUSIONS Summary A sediment budget is based on a conservation of mass analysis, incorporating the longshore and cross-shore sediment transport components, beach nourishment, and change with a defined control volume. This thesis accounts for all four of these components. Two representations of longshore transport are employed. The first is based on the energy flux equation using WIS data to calculate the longshore transport, Eq. 2-4, which is a representation of Eq. 2-1 transferred to the point at which the WIS data are provided, by using the conservation of energy flux and Snell's law. The second is a published distribution of the net longshore sediment transport along the Florida east coast. This sediment budget methodology was applied to the twelve sandy beach counties on the east coast of Florida. Shoreline changes were calculated from gradients in the longshore sediment transport and correlated with values obtained from the State of Florida shoreline position database. This analysis shows that for eight of the twelve counties the correlation is statistically significant; however, the small correlation values represent a small proportion of the variation in shoreline change rates accounted for by a linear relationship with the gradient in calculated longshore sediment transport rates. Additionally, for two of the counties with significant correlation, the correlation is negative. Cross-shore transport was calculated from the sediment budget equation using the same two different sets of accepted values of longshore transport. The net sediment transport was found to be in the onshore direction using both sets of longshore sediment transport. A more local analysis of cross-shore transport was performed for Little Talbot Island of Duval County using concepts of equilibrium beach profiles based on wave energy-dissipation rate. This approach also results in sediment transport in the onshore direction but of an unrealistically large magnitude. These unrealistically large onshore transport rates can be attributed to the fact that the wave energy-dissipation rate theory is based on breaking across the entire profile; however, for the measured profiles, waves are only breaking a small fraction of the time for larger depths. Conclusions *Although the correlation between gradients of longshore sediment transport calculated from WIS data using the energy flux equation, and measured shoreline change rates may have a level of significance of 5% for eight of the twelve counties on the east coast of Florida, the correlation values of ten of these counties are low and/or negative. This means that while the correlations are of a level of significance of 5%, only a small proportion of the total variation of measured shoreline change rates can be explained by a linear relationship with the longshore sediment transport values from WIS data. For example, if the level of significance is 5%, there is a 95% chance that the correlation is not zero. This does not mean that the calculated longshore sediment transport gradients provide a good representation of the measured shoreline change rates, thus the longshore sediment transport values calculated from WIS data using the energy flux equation cannot be considered applicable to engineering projects. * Because the USACE values for longshore sediment transport are based on a direct measurement of sediment accumulation on the updrift sides of inlets, they are besed on estimates only at several locations along the Florida east coast. In an attempt to include analysis of longshore sediment transport for the coastline between inlets, the energy flux equation was used with WIS data, but yielded poor results. When gradients were compared to the measured shoreline change rate, a low correlation was found. (Previous conclusion) Walton's data is based on an energy flux equation similar to the one used in this report, but is based on ship observations which are subject to several Imitations. However, they agree better with the USACE representation than the WIS based transport values. * The average yearly cross-shore sediment transport was found to be primarily in the onshore direction using the sediment budget methodology with accepted values of longshore sediment transport from the USACE and the energy flux equation using WIS data. * The cross-shore transport calculated using the wave energy-dissipation model proposed by Kriebel (1982), Moore (1982), and Kriebel and Dean (1985) also estimates onshore cross-shore transport, but clearly overestimates transport magnitudes. The overestimation of magnitudes can be attributed to the infrequency of breaking waves in the deeper portions of the surf zone APPENDIX BEACH NOURISHMENT Beach nourishment, or beach fill, is becoming the accepted solution to many coastal erosion problems; however, there is still some controversy over the use and performance of beach nourishment. It can be seen that when a beach is nourished with sediments of a compatible size, at an appropriate interval, nourishment can be extremely effective at stabilizing an otherwise eroding shoreline, while still maintaining a relatively natural appearance. Hard structures such as groins and jetties have been found to stabilize shorelines, but sometimes at an extreme cost to shorelines downdrift of the project. Additionally, hard structures can be obtrusive to the eye, and cause public safety concerns. A sediment budget can be useful to determine the need for beach nourishment, and it can show whether a beach nourishment project has been effective in stabilizing a shoreline. Dade County beaches used to be practically non-existent with seawalls lining the shoreline, rather than sandy beaches. Due to the lack of sandy beaches in Dade County, tourism plummeted causing the county, state and federal agencies to commence a large-scale nourishment project in 1976. The project has been considered a success with tourism up, and the beaches stabilized. This stabilization can be seen in Figure 2-23, which shows that in the northern half of the county, the longshore sediment transport is relatively constant. This lack of gradient of longshore transport along the coast of Dade County signifies a lack of erosional trends, which can infer a stabilization of the coastline due to the large beach nourishment project. This can also be seen in Broward County in Figure 2-21. Broward County has also placed large volumes of sand to nourish its shorelines, which results a relatively constant trend for the distribution of longshore sediment transport throughout the county. Similar to Dade County, this constant trend results in small gradients, which result in little variation in shoreline change. Figure A- 1 presents the beach nourishment volumes for the period of this study, which covers 1976 through 1995. Julie Rosati compiled the values in Figure A- I from data obtained by Valverde, Trembanis, and Pilkey (1999), and Kevin Bodge (2000). These data encompass the entire period from 1944 through 2000; however, the values for 19761995 were utilized since the purpose of this study was to compile a sediment budget for the same period of the WIS data. The values were presented as yearly totals for each monument along the east coast of Florida. Figure A- I represents the total for the 20 year period covering 1976 to 1995 divided by the distance between monuments to give a representation of the total nourishment density in yd 3/ft during this 20 year period. It can be seen in Figure A- I that Nassau County, the southern part of Martin County, the southern part of Palm Beach County, Broward County, and Dade County have all been nourished heavily during this 20 year period. Beach Nourishment for 1976-1995 300 . 0 - 250 E 200 Jn 0 z . 150 I *.. 100 0 CU0 EDC ~ 05 D CU j C a CU M CU 0 2U0 LL >oC 150 200 250 Distance Along the FL Coastline (miles) a ~C~r Figure A- I Beach nourishment volumes for the entire east coast of Florida for the period of this study (1976-1995). Compiled by Julie Rosati from data obtained from Valverde, Trembanis, and Pilkey (1999), and Kevin Bodge (2000) LIST OF REFERENCES Bretschneider, C. L. and R. 0. Reid, "Modification of Wave Height Due to Bottom Friction, Percolation, and Refraction," Beach Erosion Board (CERC), U. S. Army Corps of Engineers, Technical Memorandum No. 45, 1954. Charles, L. L., "Applications of Equilibrium Beach Profile Concepts to Florida's East Coast," Master's Thesis, University of Florida Department of Coastal and Oceanographic Engineering, 1994. Dean, R. G., "Sediment Budget Principles and Applications," University of Florida Department of Coastal and Oceanographic Engineering, Technical Report 86/019, 1986. De Beaumont, L. E. "Leqons de Geologie Pratique," 7me Leqon-Levees de Sables et Galets, Paris, 1845. Dean, R. G. and L. Charles, "Equilibrium Beach Profiles: Concepts and Evaluation," University of Florida Coastal and Oceanographic Engineering Department, Technical Report 94/013, 1994. Dean, R. G. and R. A. Dalrymple, "Coastal Processes with Engineering Applications," Cambridge University Press, 2001. Dean, R. G. and J. Grant, "Development of Methodology for Thirty-Year Shoreline Projections in the Vicinity of Beach Nourishment Projects," University of Florida Coastal and Oceanographic Engineering Department, Technical Report 89/026, 1989. Dean, R. G. and M. P. O'Brien, "Florida's East Coast Inlets: Shoreline Effects and Recommended Action," University of Florida Department of Coastal and Oceanographic Engineering, Technical Report 87/017, 1987. Emery, W. J. and R. E. Thompson, "Data Analysis Methods in Physical Oceanography,"Gray Publishing, 1997. Komar, P.1 D. and D. L. Inman, "Longshore Sand Transport on Beaches," Journal of Geophysical. Research, 75, 30, 5914-5927, 1970. Kriebel, D. L., "Beach and Dune Response to Hurricanes," M.Sc. Thesis, University of Delaware, 1982. Kreibel, D. L. and Robert G. Dean, "Numerical Simulation of Time-Dependant Beach and Dune Erosion," Coastal Engineering, 9, 3, 1985. Moore, B. D., "Beach Profile Evolution n Response to Changes in Water Level and Wave Height," MCE Thesis, Department of Civil Engineering, University of Delaware, 1982. Nicholls, R. J., W. A. Birkemeier, and R. J. Hallermeier, "Application of the Depth of Closure Concept," Proceedings of the 25 International Conference of Coastal Engineering, ASCE, Orlando, 1996. Thornton, E. B., "Distribution of Sediment Transport Across the Surf Zone," Proceedings of the 13th International Conference of Coastal Engineering, ASCE, Vancouver, 1972. Trembanis, A. C., Pilkey, 0. H., and Valverde, H. R., "Comparison of Beach Nourishment Along the U. S. Atlantic, Great Lakes, Gulf of Mexico, and New England Shorelines," Coastal Management, v 27, n 4, 1999. Walpol, R. E. and R. H. Meyers, "Probability and Statistics for Engineers and Scientists," MacMillan Publishing Company, 1985. Walton, T. L., "Littoral Drift Computations Along the Coast of Florida by Means of Ship Wave Observations," Florida Sea Grant Program Report No. 15, 1973. Walton, T. L., "Littoral Drift Estimates Along the Coastline of Florida," Florida Sea Grant Program Report No. 13, 1976. BIOGRAPHICAL SKETCH 1h I was born on August 15 1977 in Richmond, VA. When I was 10 years old, my parents bought a house on Topsail Island, in North Carolina. Being a barrier island, Topsail Island is exposed to many dynamic features along its coastlines, especially adjacent to the inlets on either end. During my freshman year of high school, also in Richmond, I participated in a weekend trip to the Tangier Islands in the Chesapeake Bay. The main purpose of the trip was to learn about the features of the wetlands, and coastlines of a unique island just north of the fishing town of Tangier. This combined with my exposures at Topsail Island increased my interest in the shorelines, and the processes associated with them. In the fall of 1995, 1 began my studies at Rensselaer Polytechnic Institute in Troy, NY. After many rough years in the cold of Upstate New York, and an internship in Connecticut, I graduated in May of 2000 with a Bachelor of Science degree in Civil Engineering from Rensselaer Polytechnic Institute, after which I enrolled at the University of Florida to pursue a Master of Science degree in Civil and Coastal Engineering. After receiving my Masters degree from the University of Florida, I plan to pursue a Ph.D. in Geotechnical Engineering at Virginia Polytechnic Institute and State University. |