St. Lucie Shoal Complex: Regional Sediment Resource or Submerged Storm Breakwater. Leaf Erickson, M.E., E.I.T.

Transcription

1 St. Lucie Shoal Complex: Regional Sediment Resource or Submerged Storm Breakwater by Leaf Erickson, M.E., E.I.T. A dissertation submitted to the College of Engineering at Florida Institute of Technology in partial fulfillment of the requirements for the degree of Doctorate of Philosophy in Ocean Engineering Melbourne, Florida December, 2017

2 We the undersigned committee hereby approve the attached thesis, St. Lucie Shoal Complex: Regional Sediment Resource or Submerged Storm Breakwater, by Leaf Erickson, M.E., E.I.T. Gary A. Zarillo, Ph.D Professor, Department of Ocean Engineering and Science College of Engineering Stephen L. Wood, Ph.D Department Head, Department of Ocean Engineering and Science College of Engineering Edward H. Kalajian, Ph.D Professor and Associate Dean, Department of Civil Engineering College of Engineering George A. Maul, Ph.D Professor, Department of Ocean Engineering and Science College of Engineering ii

3 ABSTRACT St. Lucie Shoal Complex: Regional Sediment Resource or Submerged Storm Breakwater Author: Leaf Erickson, M.E., E.I.T. Advisor: Gary Zarillo, Ph. D. Nearshore sand shoals have become the predominant sediment resource for beach nourishment projects on the east coast of Florida. Along this coast, the St. Lucie Shoal Complex (SLSC) is comprised of several shoals designated as sediment resources for beach nourishment, many having depths less than 7 meters, at their crests. This group of shoals represents the largest high-quality beach nourishment sediment resource in southeast Florida. Among these shoals, the St. Lucie shoal is the largest and shallowest at the crest. This project explores the current best practice methodologies to explore impacts of excavating sand resources from shallow-crested shoal systems like the SLSC in comparison to those used to previously to demonstrate that assumptions used previously are still viable through a pragmatic use of increased model capabilities and improved datasets. At times, limited modeling capabilities were the problem but, increasingly the sparse data density, both spatially and temporally of regional scale oceanographic datasets, was found as the limiting factor in model accuracy. iii

4 A brief review of the Wave Information Studies (WIS) hind cast of wave data from the U.S. Army Corps of Engineers (USACE) Coastal and Hydraulics Lab (CHL) indicates that significantly larger wave heights, 13.6 meters at a 14.9 second period, offshore of this area exceed those previously modeled, a 1.4-meter wave at a period of 15 seconds. To examine the potential of sand excavation from the SLSC to alter the local wave regime, the year of 2004, including Hurricanes Frances and Jeanne, was modeled as a worst-case scenario. Shallow crested, relative to their local wave climates, shoals must be evaluated for their wave energy dissipation effects during major storm events. Wave attenuation from the shallowest shoal permitted for use during the strongest conditions (Hurricane Frances), showed a marginal wave reduction of 4%. As the largest high-quality sediment resource in southeast Florida, the SLSC is targeted by several Florida coastal counties for sand excavation. Pragmatic management strategies can help provide a greater benefit for all by reincorporating more of the highest quality beach compatible sediment back into the longshore sediment movement from north to south along the southeast Florida coast. Counties who have downdrift beaches should consider cost sharing as well as mutually beneficial policy changes to encourage the implementation of regional sediment management plans. iv

5 TABLE OF CONTENTS Abstract... iii Table of Contents... v List of Figures... vii List of Tables... ix Acknowledgement... x Dedication... xi Chapter 1 Introduction... 1 Objectives... 1 Significance... 1 Location... 2 Origins of Southeast Florida Shoals... 3 Geology... 6 Survey Data... 7 Wave Climate... 8 Local Hurricane Impacts Tidal Range Sea Level Rise Local Observations Chapter 2 Methods Introduction Model Type Previous Studies Model Justification Model Setup Model Grid development Boundary Condition Inputs Water level time series inputs Wind inputs Wave input Model Calibration v

6 Chapter 3 Results Modeled Conditions Model Limitations Chapter 4 Discussion Engineering Design and Utilization References Appendix A1: Model Calibration Appendix A2: Model Results Definition of Terms vi

7 LIST OF FIGURES Figure 1. Florida showing the location of the SLSC... 3 Figure 2. Representation of bathymetric data acquired in the 1930s by the U.S. Coast and Geodetic Survey. Location of the SLSC is shown... 5 Figure 3. Representation bathymetric data in meters from 1930s and 1960s in the vicinity of the SLSC. Data are available from the NOAA Coastal Relief Model ( 8 Figure WIS wave height and period [WIS, 2017]... 9 Figure 5. WIS wave rose [WIS, 2017] Figure 6. WIS storm return period analysis [WIS, 2017] Figure 7. Seasonal variation of sea level surrounding the study area Figure 8. Sea Level Trends at Lake Worth Pier in meters. [NOAA, 2017] Figure 9. Storm wave interacting with the St. Lucie shoal [Erdman,2012] Figure 10. Typical elevation data density relationship with 100m grid spacing showing data density limitation to grid resolution Figure 11. Wave model grid extent and depths in meters available from historical hydrographic survey H-sheets available in digital format from the NOAA Coastal Relief Model ( 25 Figure 12. SLSC modeled water level time series Figure 13. SLSC modeled wind speed time series Figure 14. WW3 modeled wave height time series Figure 15. Example of the spectral energy file utilized for analysis Figure AWAC recorded wave heights in meters Figure 17. Modeled surface roughness and wave height root mean squared error.. 32 Figure 18. Graphical comparison of measured (2007AWAC) and model wave heights Figure 19. CMS-Wave modeled vs. AWAC measured wave heights for 2007 calibration Figure 20. Complete inshore observational transect transformed wave data Figure 21. Model results for St. Lucie shoal extents during hurricane Frances peak wave conditions Figure 22. Pre-sediment extraction Hurricane Frances peak wave heights in meters Figure 23. Yearlong CMS-Wave Model Calibration of both high and low frequency wave events in meters Figure 24. Yearlong Comparison of CMS-Wave Model outputs for various bottom roughness coefficients vii

8 Figure 25. CMS-Wave Model Control Parameters applied to all model variations Figure 26. Pre-sediment extraction Hurricane Frances peak wave heights in meters Figure 27. CMS-Wave Modeled Results for Wave Height in meters for the Inshore Observation Transect Figure 28. CMS-Wave Modeled Results for Wave Height in meters for the Inshore Observation Transect viii

9 LIST OF TABLES Table 1. Local storm return period analysis [WIS, 2012] Table 2. Survey data utilized [NOAA, 2012] Table 3. CMS-Wave Modeled Results for Wave Height in meters for the Inshore Observation Transect ix

10 ACKNOWLEDGEMENT I would like to acknowledge the late Dr. Lee Harris, Professor of Ocean Engineering, who helped me begin and guided me through the start of my doctoral endeavors at Florida Institute of Technology. I also acknowledge Dr. Gary Zarillo, who gave me the opportunity to fulfill my doctoral pursuit. Due to their energy, support, and guidance, I have achieved my goals. x

11 DEDICATION I dedicate this paper to my family. Who supported my doctoral endeavors even before I did and regardless of where it would take me. With their love and understanding, my life s journey is and has been that much brighter. xi

12 CHAPTER 1 INTRODUCTION Objectives Beach nourishment projects all begin with a need for sediment and must be specifically designed for a particular sediment source, the quality of which is increasingly difficult to locate in quantities sufficient for beach nourishment activities. Nearshore sand shoals are commonly the best match for adjacent shorelines as they are, in many cases, their geologic source. Although largely isolated from the shoreline sediment transport system, their impact on the local wave climate needs to be understood for effective coastal management. This paper explores the potential impacts from the utilization of these nearshore sand shoals and discusses the most effective use of this limited resource. Significance Several alternative sediment resources have been attempted in the past, with only limited success: Bypassed sediment, upland sources, and nearshore sand flats. Bypassed sediment is helpful along shorelines near inlets but, inevitably is not sufficient to fulfill the overall sediment demands for the downdrift shoreline. Upland alternatives have additional handling and transportation costs and have proven, in many cases, insufficient in both quality and quantity. Finally, nearshore sand flats have insufficient sediment quality regardless of overwhelming quantity [NOAA, 2010]. Transportation costs for moving the sediment from the borrow site to the beach site is central to the financial cost associated with beach nourishment 1

13 projects. The minimization in travel distance between borrow and fill locations has always helped lead coastal planners to the closest sediment resources with sufficient sediment quality, commonly nearshore sand shoals. Larger waves than modeled previously occur locally and may experience energy dissipation through breaking over these shoals. It remains to be proven if storm waves large enough to experience significant energy dissipation can be achieved by the local wave climate, with any considerable frequency. However, with the possibility of increased wave energy reaching the adjacent shoreline storm wave conditions, this must be explored for their interaction with shoals prior to sediment extraction. Location As seen in Figure 1, Florida s east central coast lies just north of the south eastern most Florida counties. Offshore of this area several shoals exist, these shoals have persisted through many tropical cyclones since first being noted on nautical charts of the area over a century ago. The majority of Florida s central east coast s proven sediment resources are within these nearshore sand shoals [NOAA, 2010]. Among these shoals, the St. Lucie Shoal Complex (SLSC), offshore of Hutchinson Island between Ft. Pierce and St. Lucie Inlets, sits in approximately meters of water and has crests with depths of 7 meters or less. 2

14 Figure 1. Florida showing the location of the SLSC Origins of Southeast Florida Shoals Many of these features are reworked ebb shoals, detached from existing or relic barrier island inlet features during a period of relatively rapid sea level rise [McBride and Moslow. 1991: CP&E and URS, 2007]. Although nearshore shoal systems can have many origins, the most likely origin along the southeast Florida inner continental shelf (Figure 2) involves inlet migration, common for retreating barrier island systems during a period of sea level. This can cause the elongation of the curved ebb shoal into a linear nearshore shoal feature we recognize today. These shoals eventually detach from the retreating shoreface and usually form a 3

15 small, 35 o or less, angle with the shoreline, which likely occurred during the most recent sea level rise. These relic ebb shoals, comprised of relict barrier island sediments, constitute the closest, largest and most compatible sediment for beach nourishment along Florida s central east coast [CP&E and URS, 2007]. 4

16 Cape Canaveral Melbourne Depth [m] Sebastian Vero Ft. Pierce St. Lucie Shoal Complex St. Lucie Jupiter Figure 2. Representation of bathymetric data acquired in the 1930s by the U.S. Coast and Geodetic Survey. Location of the SLSC is shown 5

17 The opening, closing, and frequent migration of these inlets, occurs along the length of any barrier island system, creating a cycle of formation and subsequent abandonment of their ebb shoal features (McBride and Moslow, 1991). If sea levels rise too quickly, these ebb shoals are unable to be significantly reworked back into the retreating beachface and are effectively abandoned by sediment transport occurring at the shoreline. As many of these features originate from reworked relic ebb shoal sediment, they contain relatively uniform beachface compatible material with sufficient stability, persisting without the continued longshore sediment transport from updrift beaches that initially provided the sediment source that allowed them to form. Geology The geologic origin for these sand shoal features began largely during the Pleistocene Epoch when sea level fluctuations allowed for sedimentation and subaerial erosion of the barrier island system. These sand shoals experienced continued sedimentation and reworking during and since the sustained sea level rise of the Holocene era, creating the complex formations of sand shoals we are familiar with today. Pleistocene and Holocene sediments in this area are primarily quartz with median grain size of approximately 0.24 mm and whose carbonate content increases towards the south [Hammer et. al., 2005]. 6

18 Survey Data While active in the local wave climate, the SLSC has endured several tropical cyclonic events since the 1930s. Despite being an essentially isolated sediment resource, it has remained stable, allowing the component shoals to behave as submerged offshore breakwaters. This endurance is found in the minimal change in the SLSC by only limited accretion or erosion of sediment over this time period. The two surveys having complete coverage of the SLSC, during the 1930s and 1960s, are presented in Figure 3. Additional surveys have been conducted recently but, due to their limited coverage area, are not included in this elevation change analysis. The overall structure of this shoal complex has changed little over the thirty-year period between surveys. The largest and shallowest crested shoal, St. Lucie, will be investigated as it presents the most likely portion of the SLSC to experience energy dissipation during storm events. 7

19 1930 s Ft. Pierce Inlet 1960 s Ft. Pierce Capron SLSC Pierce St. Lucie Depth [m] Dredge Area Gilbert o AWAC Gauge St. Lucie Figure 3. Representation bathymetric data in meters from 1930s and 1960s in the vicinity of the SLSC. Data are available from the NOAA Coastal Relief Model ( St. Lucie Inlet Wave Climate Given frequent tropical cyclones, there are several years for which major storm wave events occur, including the 2004 hurricane season when two hurricanes directly impacted the study area. The United States Army Corp of Engineers (USACE) Wave Information Studies (WIS) analysis shows wave heights in excess of those used in previous studies occur regularly across the SLSC. WIS station 63523, immediately offshore of the study area, shows an average wave height of 1.4 meters and average period of 8.8 sec, as seen in Figure 4. 8

20 Figure WIS wave height and period [WIS, 2017] 9

21 To provide directionality to the wave data, the 2004 wave rose for WIS station 63523, centrally located offshore of the study area, is presented in Figure 5, and shows waves primarily arrive from the east to northeast sectors. Figure 5. WIS wave rose [WIS, 2017] 10

22 The largest storm conditions for 2004 were estimated by WIS to have a maximum wave height of meters with a period of 14.9 sec and occurred on September 26 th, Given the limited long term data available for wave conditions, storm events are commonly under predicted. The WIS Storm Event Return Period analysis ranked the top ten events between 1980 and 2012, as shown in Table 1. Table 1. Local storm return period analysis [WIS, 2012] Event Time Wave Height [m] Wave Period [s] 1 9/26/ /5/ /24/ /16/ /15/ /26/ /2/ /12/ /5/ /14/ After a careful search of the WIS historical data for years having tropical cyclones, the year of 2004, included two major storm events passing directly over the SLSC, hurricanes Frances and Jeanne, stood out as the strongest two storm events of the WIS analysis where Frances was just under 40 years and for Jeanne was just under 20 years as seen below in Figure 6 (WIS, 2012). Based only on the 33 years of data used, , it would be difficult to assess the accuracy of a storm return period beyond those that occurred within the study area. However, this represents the best site specific data for storm return period. 11

23 Figure 6. WIS storm return period analysis [WIS, 2017] The year of 2007, which overlaps with previously recorded directional wave data offshore of Jensen Beach, was chosen to calibrate model runs. Storms in these years present conditions sufficient to explore storm wave interaction on the SLSC. Local Hurricane Impacts Coastal storm impacts from hurricanes Frances and Jeanne were significant between Ft. Pierce and St. Lucie inlets with Frances the most intense storm conditions of the two tropical cyclones. Dune retreat of meters formed scarps of 3-4 meters, measured wrack lines showed a storm surge of 4 meters, and several overwash events on the order of 100 meters or more occurred along the study area coastline [FDEP, 2004]. 12

24 Long term shore protection provided by natural nearshore sand shoals can provide greater endurance when exposed to such storm events. For example, within the study area, an engineered sediment feature designated as the Texas Reef, similar in elevation to the adjacent SLSC, exhibited significant impacts during the 2004 hurricane season. Improvements to the navigable depths and sediment containment basin for St. Lucie Inlet produced significant quantities of sand and limestone cobble, ranging from 6.3 to 51 cm in diameter. This sediment was placed 13 km south of the SLSC, creating a large mound of material in 15 meters of water as an artificial reef feature with several concrete and metal fish attracting structures. Initial surveys indicated a minimum depth at 5.5 meters below the water surface. After construction ended in 2002, the material settled for approximately a year before the first baseline surveys were completed in August Annual surveys, as well as after major storm events, were performed. After experiencing the tropical cyclones of 2004, a storm event survey was completed in February 2005 and showed a loss of around 5.2 meters of material. After the next annual monitoring survey, accretion of approximately 1 meter was found to occur, with a minimum depth of approximately 9 meters [CSA Int, 2007]. Storm wave energy was able to significantly redistribute the relatively large limestone cobble structure to around half of its original relief above the surrounding seafloor. This suggests the interaction with storm wave conditions was able to move material on the order of 6.3 to 51 cm in diameter, at a depth of around 9 meters. Despite the two years between construction and two direct 13

25 tropical cyclone impacts, Frances and Jeanne, the erosion of material would imply that the overall stability of this structure is far less than that of the naturally occurring nearshore shoals of the SLSC. Tidal Range Mean tidal ranges for the area vary from 1.06 meters to the north at Port Canaveral (Trident Pier) and 0.79 meters to the south in Palm Beach, FL. A seasonal high stand of sea level occurs during the month of October. Monthly Mean Sea Level (MSL) data for Daytona Beach, to the north, and Miami Beach, to the south, shows the seasonal variation of the MSL as m and m respectively, as shown in Figure7 [NOAA, 2009]. 14

26 Figure 7. Seasonal variations of sea level surrounding the study area Sea Level Rise Rising sea levels, over the long term, likely will have only a minimal impact upon storm wave-shoal interaction, given the increase in sea level for Florida s east 15

27 central coast, as shown at Lake Worth Pier in Figure 8, which has a value of 3.56 mm/yr. [NOAA, 2017]. These shoals are isolated from their initial sediment source, the longshore sediment transport regime, and as water level rises the distance between waves and shoals will increase. This will limit the dissipative effect of wave breaking and the energy allowed to pass over to the adjacent shoreline. The larger impact of sea level rise on the utilization on the SLSC is more indirect, because as sea levels rise and the related beach retreat occurs, significant sediment inputs through beach nourishment will be necessary to keep up with rising seas in order to prevent shoreline regression and to protect upland structures. Figure 8. Sea Level Trends at Lake Worth Pier in meters. [NOAA, 2017] Local Observations Shoals that remain active in the local wave climate have a limited impact on beach sediment transport if no longer shoreline connected. Given that longshore sediment transport is directly associated with the wave energy reaching the shoreline, 16

28 anything that may impact these waves must be understood to adequately design and manage beach nourishment projects. The highest sediment transport rates occur during high energy storms and these events must be explored to understand to what degree nearshore sand shoals actively participate during these events. Breaking waves are easily visible from shore along the SLSC during large wave events, such as the 2.4-meter-high 14 second wave seen in the photograph presented in Figure 9. This indicates that strong wave-shoal interaction could be possible during storm conditions. St. Lucie Figure 9. Storm wave interacting with the St. Lucie shoal [Erdman,2012] Storm events were explored to determine what sheltering effect, if any, they may have on adjacent shorelines during these temporally brief but, highly energetic wave events. Previous studies in the area only considered average wave conditions 17

29 when evaluating the interaction between sand shoals and wave climate (Hammer et al., 2005). Thereby utilizing these shoals for beach nourishment has begun without a full understanding of their role in dissipating the energy transmitted to the adjacent nearshore wave environment. If the modification of the local wave regime is significant enough, these benefits may be jeopardized, resulting in higher longshore sediment transport. It is the potential for this erosion that requires greater understanding of wave-shoal interaction during large storm events and therefore, this was explored to ensure the sustainable management of limited sediment resources. Since these shoals are somewhat isolated from the currently active beach sediment transport system, many coastal planners are inclined to utilize them for beach nourishment and might assume they no longer play an active role in nearshore sediment transport, assisting approval to utilize these features. A shoal s ability to shelter or focus wave energy and, during storm events, actively dissipate wave energy, must be taken into consideration, in order to determine exactly what function, they have in the nearshore sediment transport regime at the shoreline during storm events. 18

30 CHAPTER 2 METHODS Introduction In order to determine the storm wave energy dissipation across the SLSC nearshore shallow crested shoal, a numerical model was employed to predict the wave attenuation. The larger the wave height, and the longer the wave period, the more likely it is to break over shallow crested shoals. Thus, the model was run for the year of 2004, which included hurricanes Frances and Jeanne, to determine if, during storm conditions, these shoals dissipate wave energy. The focus of the analysis will be on the shallowest of all the SLSC shoals, the St. Lucie shoal. This shoal consists of two primary crests, one to the north and one to the south. The northern region has been permitted for utilization and the southern reach has not and thus the northern reach was chosen as the primary region of interest with the southern reach utilization modeled as an expected continuation of current coastal zone management policies. Based on the degree of wave dissipation over the St. Lucie shoal predicted during these storm events, effective management strategies will be discussed to support the utilization of these limited resources. Model Type The SLSC was modeled with the Coastal Modeling System for Waves (CMS- Wave) using the Aquaveo Surface Water Modeling System (SMS) 11.0 in order to develop the model grid. SMS is a model interface that allows the user to 19

31 construct computational grids and apply model boundary conditions for a range of coastal engineering models [Lin, 2008]. Within the SMS software platform, the U.S. Army Corps of Engineers (USACE) Coastal Modeling System Wave model (CMS-Wave) was then used to propagate and transform waves from offshore to, as well as within, the study area. Previous Studies Previously an U.S. Minerals Management Service (MMS) study used the Steady- State Spectral Wave Model (STWAVE) (Smith et al., 1999) and WIS predicted wave data to model the pre- and post-dredge conditions for these shoals. STWAVE is similar in overall theory and numerical formulation to CMS-Wave. Average wave conditions, having a wave height of 1.4 meters and a period of 15 seconds, were used for static STWAVE runs and showed only refraction and diffraction landward of the shoal. Due to the use of relatively small wave conditions, no energy dissipation occurred when passing over these nearshore shallow crested shoal features, despite significantly larger waves, 8.5 meters at 14 seconds predicted by WIS, occurring within the study area. Additionally, studies by the Florida Department of Environmental Protection (FDEP) and the USACE, in 2011, have investigated the sediment resource potential of the SLSC. Sub-bottom profiling was used to determine the internal structure of these shoals so as to help estimate their likely sediment yield. Vibracores were performed to verify their internal structure and to further refine the estimated beach quality sediment 20

32 available. The internal structure is slightly stratified but the majority of the entire shoal feature, down to the level of the adjacent sand flats, is likely usable for nourishment activities. Model Justification CMS-Wave was chosen as it has been proven to accurately represent wave transformation by coastal systems in the nearshore environment [ERDC, 2008]. Previous studies of wave-shoal interaction by FDEP used the STWAVE model and were limited by using only static average wave conditions. In this investigation, CMS-Wave was used to model yearlong runs of hind cast data for a more complete estimation of wave transformation and dissipation over these shallow crested shoal features when exposed to a realistic wave climate. CMS-Wave is a component of the Coastal Modeling System developed by the USACE Coastal and Hydraulics Laboratory (CHL) (Lin et al., 2008) CMS-Wave is a two-dimensional wave spectral transformation model that employs a forward-marching, finite-difference method to solve the wave action conservation equation. CMS-Wave contains theoretically developed approximations for both wave diffraction and reflection and, therefore, is suitable for conducting wave simulations in shallow marine environments The CMS-Wave model grid spacing was refined beyond that which was utilized by the previous MMS study. By using the newer CMS-Wave model with WW3 predicted wave data (Tolman, 2002) a more complete analysis of the nearshore 21

33 wave climate was predicted. The time series of wave data used provided a more robust estimation of storm wave-shoal interaction by allowing for a clearer assessment of how these low frequency, highly energetic storm waves interact with shallow crested shoals. Model Setup Model Grid development Elevation data for the last regional scale survey from the 1960s was used with hind cast WW3 wave data, for several separate yearlong models runs. The first model runs calibrated the transformation of the WW3 data from offshore of Jensen beach to the location of the Acoustic Wave and Current (AWAC) gauge for Next, model runs for 2004 were able to estimate the extent of the local storm waveshallow crested shoal interaction during the direct impacts of hurricanes Frances and Jeanne. Finally, sediment extraction was explored focusing on changes in wave energy for 2004 to explore the impact of shallow crested shoal utilization. A complete listing of the survey data set utilized in this analysis is shown in Table 2, which lists the specific hydrographic survey sheet (H-Sheets) used to compile the bathymetric data available in the NOAA integrated topographic relief model ( 22

34 Table 2. Hydrographic Survey data utilized [NOAA, 2012] 1930's 1960's H05032 H05057 H08959 H08958 H05023 H05047 H08956 H08839 H05025 H05031 H08957 H08713 H05027 H05040 H08783 H08954 WW3 data were propagated from offshore, through the study area, using a grid spacing of 100 meters as seen in Figure 10. The relative relationship between elevation data density and grid size made the improvement to model accuracy through a further reduction in grid size minimal to non-existent. The wave model used time series of water level, wind speed, wind direction, wave height, period, and direction in conjunction with spreading parameters, from the WW3 hind cast data model developed by the National Oceanic and Atmospheric Administration (NOAA) and was applied to the outer boundary of the CMS-Wave grid in water depths of around 40 meters as seen in Figure

35 Figure 10. Typical elevation data density relationship with 100m grid spacing showing data density limitation to grid resolution 24

36 Ft. Pierce Depth [m] 10km St. Lucie Figure 11. Wave model grid extent and depths in meters available from historical hydrographic survey H-sheets available in digital format from the NOAA Coastal Relief Model ( 25

37 Boundary Condition Inputs Water level time series inputs Lateral boundary conditions were established from the averaged long term tidal constituents, as found from using a 25 hour Butterworth low pass filter to reveal the seasonal water level variations. This was accomplished by utilizing the nearest tidal stations, Trident Pier and Lake Worth Pier, averaging and applying the low pass filter. Tidal currents minimal to non-existent given the distal nature of the two closest inlets and open ocean tidal ranges are small, on the order of a meter or less. The Monthly Mean Sea Level (MSL) data for Daytona Beach, to the north, and Miami Beach, to the south, is presented in Figure 12, and shows the seasonal variation of the MSL [NOAA, 2009]. Figure 12. SLSC modeled water level time series 26

38 Wind inputs Wind data consists of a time series for hourly wind speed and direction generated by hind cast data from the WW3 model (Tolman, 2002), as seen below in Figure 13. Wind data time series was applied as a spatially constant value across the entire model grid. Figure 13. SLSC modeled wind speed time series Wave input WW3 hindcast wave data was applied uniformly across the offshore boundary. These wave heights are significantly lower than those predicted by WIS but, represent the best data set available for analysis is presented in Figure 14. An example of the spectral energy file utilized for analysis is presented below in Figure

39 Figure 14. WW3 modeled wave height time series 28

40 Figure 15. Example of the spectral energy file utilized for analysis Model Calibration CMS-Wave allows for manual input of wave spreading parameters, the type of spectrum, and location of observation cell/data outputs. Input wave data used along the offshore boundary, was collected from the end of 2006 through the beginning of 2008, offshore of Jensen Beach with a 1,200 MHz Norteck AWAC Acoustic wave and current profiler is presented below in Figure

41 Figure AWAC recorded wave heights in meters For the 2007 model run, seasonal events, like tropical cyclones and distant nor easters, were specifically explored for their correlation between the modeled and measured data sets. This model correlation was achieved through comparing several models runs at an observation cell coinciding with the location of the nearshore AWAC gauge previously deployed offshore of Jensen Beach, while varying the friction coefficient (Cf). Additionally, wave breaking formulas are adjustable within CMS-Wave and were also used in this calibration adjustment. It was found that the Battjes and Janssen (1978) wave breaking formulation provided 30

42 slightly better calibration. The modeled calibration run conditions are presented below in Table 3. Table 3. Modeled calibration conditions Dredge Depth Boundary Conditions Friction Coefficient None None None None These modeled conditions were analyzed to determine their accuracy through a comparison of the transformed wave conditions by the model at an observation cell coincident with the location of the previously deployed AWAC gauge. During analysis, a point was found where the friction coefficient increase would improve the overall model accuracy but, low frequency storm events were significantly under predicted. In order for the bottom friction to be representative of real world conditions, a root mean squared error was used to determine how the increase in bottom friction and model accuracy improvement was related, as seen in Figure 17. As the friction coefficient (Cf) increased the improvement in the root mean squared error leveled off significantly. Additionally, the root mean squared error between the three dredge cut depths had an average standard deviation of and a standard deviation of

43 Figure 17. Modeled surface roughness and wave height root mean squared error The modeled wave heights utilized 1960 s water depths, WW3 hind cast wind and wave data, and water level changes based on tidal constituents averaged between constituents calculated from observations at NOAA Stations (Trident Pier, Cape Canaveral) and (Virginia Key, FL) were compared to the 2007 measured data. The model data reasonably represented both low and high frequency wave events as seen in Figure 18. Thus, output wave data for the 2007 model runs best correlated with those recorded by the AWAC unit utilizing Battjes and Janssen (1978) as the wave breaking model and a Cf=0.045 for bottom friction. 32

44 Additional information on the model setup procedure for model calibration and calibration results are given in Appendix A1. Figure 18. Graphical comparison of measured (2007AWAC) and model wave heights Adjusting the friction coefficient over the model grid to improve the correlation between observes and modeled wave heights is a primary calibration process. The modeled vs. measured values, shown in Figure 17, correlate well for the friction coefficient (Cf) of and further shows agreement between the two data sets. 33

45 CMS Wave 2007 (C f =0.045) Modeled vs. Measured CMS Wave Hs [m] y = x R² = AWAC Gauge Hs [m] Figure 19. CMS-Wave modeled vs. AWAC measured wave heights for 2007 calibration 34

46 CHAPTER 3 RESULTS Modeled Conditions Model runs for the year of 2004 consisted of both pre-sediment extraction and postsediment extraction conditions for the utilization of the shallowest component of the SLSC, the St. Lucie shoal, with three alternative dredge cut depths chosen as shown below in Table 4. The results of these analysis are shown by an observational transect inshore of the SLSC presented in Figure 20. Table 4. Modeled analysis conditions Dredge Depth Utilization Strategy Boundary Conditions Friction Coefficient 11 m Minimum m Moderate m Complete

47 Indian River Pierce Capron St. Lucie Gilbert Figure 20. Complete inshore observational transect transformed wave data Considering the average depth of the St. Lucie shoal crest is approximately 10 meters (MSL) and surrounding ambient depths are approximately 14 meters (MSL), dredge cut depths for borrow area utilization are presented as the minimal, median, and maximum. The relative differences among the three borrow area utilization strategies are negligible to nonexistent, as seen in Figure

48 Figure 21. Model results for St. Lucie shoal extents during hurricane Frances peak wave conditions. A maximum reduction in wave height for the St. Lucie shoal during hurricane Frances was approximately 0.2 meters. However, to the south, shallower sections of the St. Lucie shoal, not currently approved for sediment extraction, show significant wave attenuation and thus would be a logical expansion of the existing utilization areas, as seen in the pre sediment extraction condition presented in Figure

49 Wave Height [m] Inshore Observation Transect Start Ft. Pierce Inlet Indian River Shoal Capron Shoal Pierce Shoal St. Lucie Shoal 10km Gilbert Shoal St. Lucie Inlet Inshore Observation Transect End Figure 22. Pre-sediment extraction Hurricane Frances peak wave heights in meters. 38

50 Hurricane Frances represents the largest wave event in the WW3 hind cast dataset for this area and for tropical cyclone impacts is representative of a 100 year return period storm event. Given the marginal nature of the shoal protection of the adjacent beachface, sustainable sediment utilization strategies could be implemented with only minimal impacts to the regional shoreline wave climate. These areas are currently proposed for utilization but, are more active in the dissipation of energy during these strong storm events as indicated by the increased wave energy between the sediment extraction strategies shown above in Figures 19 and 20. Further model simulations should be performed for the southern extent of the St. Lucie shoal complex to examine its interaction with the local wave regime due to both its size and closer proximity to shore which would likely have a greater influence on the adjacent shoreline before sediment extraction is approved. Additional details of wave attenuation across the SLSC is provided in Appendix A2. This includes a tabular listing of wave height along the inshore model observation transects shown in Figures 20 and 21. Model Limitations The primary limitation of this model is grid size, which is a primary factor in any model of wave energy propagation. Resolution of physical features with a minimum of at least three grid squares is necessary to begin to represent a feature within the SMS modeling grid. The surveyed depth data averaging over each hundred (100) meter square does not reflect the overall reality of the actual crest 39

51 heights, as it uses an average depth of the bottom within the cell dimensions. It is this limitation that may controls the resolution of wave energy dissipation over the crest of the shoals. However, the limitation of spatial resolution set by the model grid cell size was, due to the restricted spatial resolution of the historical hydrographic survey data available in the study area. 40

52 Engineering Design and Utilization CHAPTER 4 DISCUSSION The single most important material element in the engineered design of beach nourishment is the sediment resource utilized for beachfill material. The quality, proximity and quantity of any sediment resource are the primary concerns for coastal engineers in the design and development of beach nourishment projects. The utilization of isolated sediment resources no longer within the longshore sediment transport regime is an essential part of sediment management within the coastal zone. Without a strong biologic or physical impediment to utilization of nearshore sand shoals, their reincorporation into the nearshore sediment transport system through engineered best practices, is the best use for this beach quality sediment resource. The alteration of the wave regime when propagating across shallow crested nearshore shoals, must not result in any significant adverse effects for the adjacent shoreline. Examining high-energy and low-frequency storm events should be one of the first steps when determining the dissipative effect of these shoals. Dissipation of wave energy must be considered as the primary concern when evaluating shallow crested shoals as a sediment resource. Nearshore shoals that do not actively dissipate wave energy during storm events should be considered as a sediment resource for utilization. Through extreme storm events, much of the 41

53 change in the nearshore environment occur during these short periods of time and, through natural selection, have prepared the biologic systems for the ephemeral nature of this ecosystem. Through this biologic resiliency, changes can be made to the nearshore environment with less impact than might otherwise be expected but, the frequency and temporal spacing of these events must remain consistent within this framework to help ensure the biologic system is able to keep pace with both natural and anthropogenic changes. Nearshore sand shoals that do not dissipate significant amounts of wave energy generally tend to actively focus and dissipate wave energy through diffraction and refraction to varying degrees depending on the relationship between wave magnitude and water depth. In many cases these interactions negatively manifest themselves in erosional hotspots along the adjacent shoreline. Thus, when these shallow crested shoals are removed, wave energy is more evenly distributed and thereby their related erosional hot spots are eliminated. The wave energy dissipated at the proposed borrow areas along the shallowest portion of St. Lucie shoal does not show significant wave attenuation given the frequency of these storm events. The max wave height was raised to 4.2 from 4 meters, during hurricane Frances a 100 year storm event. Such a limited, approximately 4%, increase in wave heights during such a strong storm event, the benefits for keeping the resource in place, are heavily outweighed by the value of this high quality sediment resource. SLSC has limited impact in this case, possibly because the distance these shoals are from shore, the subsequent reformation of the 42

54 wave train behind these shoal features, limits the overall influence of these shoals at the adjacent shoreface but, in other cases nearshore shore shoal wave attenuation may play a larger role. Based on this analysis, the increase in local wave heights at the shoreline adjacent to the St. Lucie shoal appears to be relatively minimal when considering the return period for storms of these magnitudes which supports their use for sediment extraction. As for those counties to the south with more limited sediment resources, the physical limitations of unequally distributed resources can always be overcome at a cost but, the policies related to their access do more to control their utilization and must be addressed to change the current management norms that allow for the use of old, out of date, data analysis. Regional Sediment Management Disparate resources require that sediment be managed regionally, with consideration to the political accessibility, when developing policies to encourage the overall equitable use and common good. This is not to say that beachfill material should be transported long distances to nourish distant beaches relative to the resource, but the local management of these resources should consider their impact upon the downdrift beaches, however distant. These resources must, whenever possible, utilize the natural system in which they exist while remaining 43

55 sensitive to the biologic systems that are reliant upon these sediment features during their lifecycle. Locally, the primary concerns to using these resources are generally limited to physical and biologic impacts. When these resources are inequitably distributed on regionally scale, a broader multifaceted approach to sediment management is necessary to provide the greatest benefit to public and private property. Adjusting public policies that shape the regulatory and political environment, providing for the sustainable use of existing sediment resources, thereby is essential to the management of these valuable resources. Due to the overall southern sediment transport in Florida, all counties rely, to some extent, on the southern sediment bypassing of inlets, none more so than those with limited to no nearshore sediment resources like southeast Florida. Although nearshore sand shoals will need to be accessed, best management practices should continue be employed. All sediment viable for beach nourishment should be placed into the nearshore sediment transport system. Reflective of the natural background transport regime, a downdrift only policy for dredging and nourishment projects with cost sharing to help provide a funding resource should be considered as a component of any sustainable coastal management plan. Recognizing their indirect benefit and stake in any sediment bypassing project, downdrift counties should shoulder more of the cost associated with these projects. 44

56 Although in the end, these counties needs will require significantly more sediment than these projects can provide. A multi prong approach to coastal protection and, more specifically, beach nourishment is essential to provide for the demands of coastal communities given the undeniable rise in sea levels over time. Downdrift counties are dependent on the nourishment policies of updrift counties. Also, the ability of and how each county is able to implement their nourishment policies. This, combined with several other factors, has caused the frequency of both beach nourishment and inlet sediment bypassing projects has diminished. Eminent domain upon nearshore sediment resources is an unlikely, but not impossible, outcome to restrictive policies of local county governments. The unified power of the tourism industry and beachfront property owners will likely become more and more creative in accessing sediment on a more regional basis the longer they are denied a viable sediment resource. The economic value of a recreational beachfront in southeast Florida may eventually change the process by which these resources are accessed, opening up the SLSC to greater utilization. The longer southeast counties are denied a sediment resource, the more likely creative methods are likely to be used. Sea level rise is conservatively approximated at meter by the end of the century. The proximity of the shoal s crest to the water s surface, relative to the local wave climate, is the primary factor in energy dissipation through wave breaking. Wave-shoal interaction will be reduced over the long term by sea level rise through increasing water depths over these shoal systems. Although this a 45

57 slow process, a staged utilization strategy of accessing deeper shoals first, would allow for this trend to work, albeit over the longer term, in the coastal zone manager s benefit. A best practices approach needs to be implemented to continuously incorporate any new data, capability, or accuracy into models used by engineers to enhance the ability for a clearer understanding of modeled results. 46

58 REFERENCES Battjes, J.A., Janssen, J.P.F.M., Energy loss and set-up due to breaking of random waves. In: Proceedings of the 16th Conference on Coastal Engineering, ASCE, Hamburg, Germany, vol. 1, pp Coastal Planning & Eng., URS. (2007) Florida Central Atlantic Coast Reconnaissance Offshore Sand Search. 280 pp. Florida Dept. of Env. Prot., Bur. Of Beach. and Coast. Syst., Tallahassee, Florida. United States Army Corps of Engineers (USACE) (2010), Coastal Inlets Research Program (CIRP), Vicksburg, MS. Texas Reef Monitoring Program: Year 4 Survey Final Monitoring Report, CSA International, Inc., September 2007 Dean, R. G. and R. A. Dalrymple. (2004), Coastal Processes with Engineering Applications. 475 pp. Cambridge University Press, New York. Dean, R. G., R. A. Dalrymple, and L. Philip (Eds). (1991), Water Wave Mechanics for Engineers and Scientists, Advanced Series on Ocean Engieering., Vol. 2, 353 pp. World Scientific, New Jersey. Engineer Research Development Center (2008), Coastal Hydraulics Lab (ERDC/CHL TR-08-13), Coastal Inlets Research Program, CMS-Wave: A Nearshore Spectral Wave Processes Model for Coastal Inlets and Navigation Projects, Vicksburg, MS. Erdman Video Systems, Inc.,8895 SW 129th Street, Miami, FL 33176; Tel ; 2012 Florida Department of Environmental Protection (FDEP), Division of Water Resource Management, Bureau of Beaches and Coastal Systems, Hurricane Frances and Jeanne Post-storm Beach Conditions and Coastal Impact Report with Recommendations for Recovery and Modifications of Beach Management Strategies, October

59 Hammer, R.M., et. al. (2005), Environmental Surveys of Potential Borrow Areas on the Central East Florida Shelf and the Environmental Implications of Sand Removal for Coastal and Beach Restoration. OCS Study MMS , 306 pp. Continental Shelf Assoc., Applied Coast. Res. and Eng., B. A. Vittor & Assoc., FL Geo. Surv., U.S. Dept. of the Int., Miner. Mgt. Serv., Leasing Div., Marine Miner. Bur., Herndon, Virginia. Kennett, James P. (1982) Marine Geology. 813 pp. Prentice Hall, New Jersey. Knauss, John A., (2000) Introduction to Physical Oceanography. 309 pp. Prentice Hall, New Jersey. Lin, L., et al. (2008) CMS-Wave: A Nearshore Spectral Wave Processes Model for Coastal Inlets and Navigation Projects. United States Army Corps of Engineers Coastal Inlets Research Program., Washington, D.C. McBride, R.A. and T.F. Moslow Origin, evolution, and distribution of shoreface sand ridges, Atlantic inner shelf, U.S.A. Mar. Geol. 97: National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) Oceanographic Survey Data is available through: National Data Buoy Center (NDBC) data is available at through the National Oceanic and Atmospheric Administration: Shore protection manual. (1984). 4th ed., 2 Vol, U.S. Army Engineer Waterways Experiment Station, U.S.,Government Printing Office, Washington, DC. Smith, J. M., Resio, D. T. and Zundel, A. K. (1999). STWAVE: Steady-State Spectral Wave Model; Report 1: User s manual for STWAVE version 2.0, Instructional Report CHL-99-1, U.S. Army Engineer Research and Development Center, Vicksburg, MS Tides, Current, Sea Level Rise data available through the National Oceanic and Atmospheric Administration s (NOAA) Center for Operational Oceanographic Products and Services: Tolman, H.L User manual and system documentation of WAVEWATCH-III version NOAA / NWS / NCEP / MMAB Technical Note 222, 133 pp. U.S Army Corps of Engineers, St. Lucie County South Beach and Dune Restoration Project, Draft Environmental Impact Statement, 206 p. 48

60 Wang, P., et. al. (2002), Longshore Sand Transport Initial Results from Large- Scale Sediment Transport Facility, Engineer Research Development Center, Coastal Hydraulics Lab (ERDC/CHL CHETN-II-46). Wave Information Studies (WIS), (2012) is available through the United States Army Corps of Engineers Coastal and Hydraulics Laboratory: 49

61 APPENDIX A1: MODEL CALIBRATION Figure 23. Yearlong CMS-Wave Model Calibration of both high and low frequency wave events in meters. 50

62 CMS Wave 2007 (C f =0.045) Modeled vs. Measured CMS Wave Hs [m] y = x R² = AWAC Gauge Hs [m] Figure 17. CMS-Wave modeled vs. AWAC measured wave heights for 2007 calibration 51

63 Figure 24. Yearlong Comparison of CMS-Wave Model outputs for various bottom roughness coefficients. 52

64 Figure 25. CMS-Wave Model Control Parameters applied to all model variations. 53

65 APPENDIX A2: MODEL RESULTS Wave Height [m] Inshore Observation Transect Start Ft. Pierce Inlet Indian River Shoal Capron Shoal Pierce Shoal St. Lucie Shoal 10km Gilbert Shoal St. Lucie Inlet Inshore Observation Transect End Figure 26. Pre-sediment extraction Hurricane Frances peak wave heights in meters. 54