University of Floridaufdcimages.uflib.ufl.edu/UF/00/09/40/44/00001/Binder7.pdfTitle Unknown Author...

"

State of RoridaDepartment of Environmental Protection

David B. Struhs, Secretary

Division of Administrative and Technical Services

Rorida Geological SurveyWalter Schmidt, State Geologist and Chief

Published for theRorida Geological Survey

TaUahassee, Rorida1999

LETTER OF TRANSMITTAL

Florida Geological SurveyTallahassee

Governor Jeb BushFlorida Department of Environmental ProtectionTallahassee, Florida 32304·7700

Dear Governor Bush:

The Florida Geological Survey, Division of Administrative and Technical Services,Department of Environmental Protection is publishing two papers: "Seasonal variation insandy beach shoreline position and beach width" and "Open-ocean water level datum planes:Use and misuse in coastal applications".

The first paper identifies a methodology for predicting seasonal shifts in Florida'sshorelines. A number of practical uses emerge from the research, two of which are theanalytical assessment of long-term shoreline erosion data, and determination of the seawardboundary of public versus private ownership.

The second paper is a companion paper to "Open-ocean water datum planes formonumented coasts of Florida" published by the Florida Geological Survey as a separatework. It identifies erroneous applications made when considering mean sea level (MSL),mean high water (MHW), mean low water (MLW), etc., tidal datum planes, illustrating whythey are erroneous using practical examples, and details how proper applications should bedetermined.

2j:;;:'~~Walter Schmidt, Ph.D., P.G.State Geologist and ChiefFlorida Geological Survey

iii

CONTENTS

PageSEASONAL VARIATION IN SANDY BEACHSHORELINE POSITION AND BEACH WIDTH

ABSTRACT 1INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 1SEASONAL VARIABILITY 2DATA AND RESULTS 3

Data 3Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 7

DISCUSSION 9The Single Extreme Event and the Combined Storm Season 9Beach Sediments 11Astronomical ndes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 14

APPLICATION OF RESULTS 15General Knowledge 16Seaward Boundary of Public versus Private Ownership . . . . . . . . . . . . . . . . . . , 6Long-Term Shoreline Changes . . . . . • . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Project Design and Performance Assessment 19

CONCLUDING REMARKS ..•......................................... 20ACKNOWLEDGEMENTS 20REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

LIST OF FIGURES

Figure 1. Relationship between seasonal shoreline variability, V$' and mean rangeof tide, hINt. . 4

Figure 2. Monthly time series for Torrey Pines Beach, California, for shorelinevariability, V; breaker height, HIl, and wave period, T. 5

Figure 3. Monthly time series for Stinson Beach, California, for shoreline variability,V; breaker height, H

Il, and wave period, T 5

Figure 4. Monthly time series for Jupiter Beach, Rorida, for shoreline variability, V;breaker height, H

Il, and wave period, T. 6

Figure 5. Monthly time series for Gleneden Beach, Oregon, for shoreline variability,V; breaker height, H

Il, and wave period, T. . 6

Figure 6. Illustration of mathematical fit for equation (1). . 9Figure 7. Illustration of mathematical fit for equation (2). . 9Figure 8. Example of the quick response and recovery of the beach to storm wave

activity, Pensacola Beach, Rorida, December 1974. . '0Figure 9. Monthly average occurrences of extreme event wave events for the Outer

Banks of North Carolina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , 1

v

Figure 10. Typical examples of time series relation of monthly data for breakerheight, wave period, and foreshore slope grain size for California andnorthwestern Florida panhandle. . '3

Figure 11. Monthly variation in sea level for the contiguous United States. . 16Figure 12. Example of long-term shoreline change rate temporal analysis using

seasonal shoreline shift data. . '8

LIST OF TABLES

Table 1. Force, response, and property elements for seasonal shoreline shift analysis... 4Table 2. Assessment of the wave steepness ratio for a selection of expressions

related to VS. 8Table 3. Mean annual beach grain size (foreshore slope samples) from monthly

data, and range in size. 12Table 4. Two cases of sedimentologic response of moment measures to wave

energy levels. 12Table 5. Seasonal range in monthly average water levels 15

APPENDIX

APPENDIX: PROPAGATION OF ERRORS IN COMPUTING 28

OPEN-OCEAN WATER LEVEL DATUM PLANES:USE AND MISUSE IN COASTAL APPLICATIONS

ABSTRACT 29INTRODUCTION 29INLETS/OUTLETS AND THE ASTRONOMICAL TIDE ~ 33WATER LEVEL DATUM PLANES 33SYNERGISTIC TIDAL DATUM PLANE APPLICATIONS 36

EXTREME EVENT IMPACT 36LONGER-TERM BEACH RESPONSES 37

Seasonal Beach Changes 41Long-Term Beach Changes 42

THE SURF BASE 43SEA LEVEL RISE 47

MONERGISTIC TIDAL DATUM PLANE APPLICATIONS 48DESIGN SOFFIT ELEVATION CALCULATIONS 48EROSION DEPTH/SCOUR CALCULATIONS 49SEASONAL HIGH WATER CALCULATIONS 49BEACH·COAST NICKPOINT ELEVATION 50BOUNDARY OF PUBLIC VERSUS PRIVATE PROPERTY OWNERSHIP 50

INLETS AND ASSOCIATED ASTRONOMICAL TIDES 52CONCLUSIONS 54ACKNOWLEDGEMENTS 54REFERENCES 54

vi

LIST OF FIGURES

Figure 1. Relationship between open coast tidal datums and National GeodeticVertical Datum for the Florida East Coast. . . . . . . . . . . . . . . . . . . . . . . . . . . .. 31

Figure 2. Relationship between open coast tidal datums and National GeodeticVertical Datum for the Florida Lower Gulf Coast. . . . . . . . . . . . . . . . . . . . . . .. 32

Figure 3. Relationship between open coast tidal datums and National GeodeticVertical Datum for the Northwest Panhandle Gulf Coast of Florida. . . . . . . . .. 32

Figure 4. Erosion volumes, Qe' above MHW for identical profiles impacted byidentical storm events, but with different local MHW planes. . . . . . . . . . . . . .. 37

Figure 5. Beach profile-related terms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 39Figure 6. Seasonal horizontal shoreline shift analysis 41Figure 7. Long·term shoreline shift analysis 43Figure 8. Semidiurnal tide curves for 6 tidal days 46Figure 9. Actual damage to the Flagler Beach Pier from the Thanksgiving Holiday

Storm of 1984 (Balsillie, 1985c) used to test the MUltiple Shore·BreakingWave Transformation Computer Model for predicting wave behavior,longshore bar formation, and beach/coast erosion . . . . . . . . . . . . . . . . . . . . .. 49

Figure 10. Beach/Coast nickpoint elevations for Florida . . . . . . . . . . . . . . . . . . . . . .. 50Figure 11. Comparison of Seasonal High Water (SHW) and Median Beach/Coast

Nickpoint Elevation (NJ for the Florida East Coast 51Figure 12. Comparison of Seasonal High Water (SHW) and Median Beach/Coast

Nickpoint Elevation (Ne) for the Florida Lower Gulf Coast 51Figure 13. Comparison of Seasonal High Water (SHW) and Median Beach/Coast

Nickpoint Elevation (Ne>for the Florida Panhandle Gulf Coast. . . . . . . . . . . .. 51Figure 14. Departure of Florida inlet tide data and open coast tide data. . . . . . . . . .. 53Figure 15. Open ocean and inside astronomical tides for Ft. Pierce and St. Lucie

Inlets 54

LIST OF TABLES

Table 1. Tidal Datums and Ranges for Open Coast Gauges of Coastal Florida. . . . .. 30Table 2. Selected North American Datums and Ranges Referenced to MSL . . . . . . .. 38Table 3. Florida Foreshore Slope Statistics by County and Survey 40Table 4. Moment Wave Height Statistical Relationships 45

vii

SPECIAL PUBLICAliON NO. 43

SEASONAL VARIATION IN SANDY BEACHSHORELINE POSITION AND BEACH WIDTH

by

James H. Balsillie, P. G. No. 167

ABSTRACT

Annual cyclic fluctuations in beach width due to seasonal variability of forcing elements(e.g., wave energy) have been a subject of concerted interest for decades. Seasonal variabilitycan be used to 1) identify and evaluate the accuracy of historical, long-term shoreline datainterpretations, 2) aid in the identification of the boundary of sovereign versus private landownership, and 3) predict expected seasonal behavior of beach nourishment projects, whichshould be a stated up-front design anticipation.

In this paper, data representing monthly averages are used to compare ·winter· and·summer· wave height and wave steepness as they relate to seasonal shoreline shifts. Coupledwith astronomical tide conditions and beach sediment size, two quantifying relationships areproposed for predicting seasonal shift of shoreline position (i.e., beach width).

INTRODucnON

The configuration of the beach inprofile view is primarily due to tidalfluctuations which cause periodic changes insea level, and shore-breaking wave activity.Any change in wave characteristics anddirection of approach will, depending on tidalstage, result in a change in the sandy beachconfiguration.

Systematic beach changes through asingle astronomical tidal cycle are well noted(Strahler, 1964; Otvos, 1965; Sonu andRussell, 1966; Schwartz, 1967). Cyclic cutand fill associated with spring and neap tides(Shepard and LaFond, 1940; Inman andFilloux, 1960), and the effect of suchphenomena as sea breeze (Inman and Filloux,1960; Pritchett, 1976), can contributeadditional modifying influences.

Beach changes are noted to occur attime intervals longer than a tidal cycle (e.g.,Dolan and others, 1974), Smaller beachcusps. for example, may range from 10 to50 meters apart, while sinuous forms may

1

span distances of from 450 to 700 meters,and such features often migrate alongshoreat time scales on the order of days or weeks(Morisawa and King, 1974). As the baybetween cusp horns passes a profile line, thebeach becomes narrower, and as a hornpasses, the beach widens. A predictionmodel for daily shoreline change has beensuggested by Katoh and Yanagishima(1988).

Of the possible cyclic changes,perhaps the most pronounced is thatoccurring on the seasonal scale. During the·winter" season, when incident storm waveactivity is most active, high, steep wavesresult in shoreline recession. Generally, theberm is heightened with a gentle foreshoreslope, although erosion scarps may form.Sand removed from the beach is depositedoffshore in one or more submergedlongshore bars. During the ·summer"season lower waves with smaller wavesteepness values transport sand storedoffshore back onshore, resulting in a widerbeach. It should be noted that along somecoasts such as the approximately east-west

FLORIDA GEOLOGICAL SURVEY

trending coastline of Long Island, New York(Bokuniewicz, 1981; Zimmerman andBokuniewicz, 1987; Bokuniewicz andSchubel, 1987), no seasonal variability canbe detected (H. J. Bokuniewicz, J. R. Allen,personal communications). Such lack ofseasonal variability may be symptomatic ofsub-seasonal storm wave groups combinedwith an almost imperceptible climatic change(J. R. Allen, personal communications),possibly exacerbated by changes in oceanicstorm front azimuths relative to shorelineazimuths (Dolan and others, 1988).Similarly, the east·west trending shoreline ofthe northwestern panhandle coast of Florida,while having annual net longshore transportto the west, appears to be characterized bydaily to weekly rather than seasonalreversals in longshore current direction(Balsillie, 1975). It appears, therefore, thateast-west trending shorelines poseconsiderations deserving further attention.However, for much of the Earth's open,ocean-fronting shoreline seasonal changesare clear, which constitutes the subject ofthis paper.

SEASONAL VARIABIUTY

Classically, seasonal variability isassociated with California beaches wheretheir geometric character changes noticeablyfrom "summer· to "winter" (e.g., Shepardand LaFond, 1940; Shepard, 1950; Bascom,1951, 1980; Trask, 1956, 1959; Trask andJohnson, 1955; Trask and Snow, 1961;Johnson, 1971; Nordstrom and Inman,1975; Aubrey, 1979; O'Brien, 1982;Thompson, 1987; Patterson, 1988; Collinsand McGrath, 1989). A considerablenumber of such studies have also beenconducted along the U. S. east coast (e.g.,Darling, 1964; Dolan, 1965; Urban andGalvin, 1969; DeWall and Richter, 1977;DeWall, 1977; Everts and others, 1980;Bokuniewicz, 1981; Miller, 1983;Zimmerman and Bokuniewicz, 1987).

Geometric characteristics of seasonal

2

change have been described in terms of sandvolume changes (Ziegler and Tuttle, 1961;Dolan 1965; Eliot and Clarke, 1982; Aubreyand others, 1976; Davis, 1976; DeWall andRichter, 1977; DeWall 1977; Thorn andBowman, 1980; Everts and others, 1980;Bokuniewicz, 1981; Miller, 1983;Zimmerman and Bokuniewicz, 1987;Samsuddin and Suchindan, 1987), bycontour elevlltion changes (Shepard andLaFond, 1940; Ziegler and Tuttle, 1961;Gorsline, 1966; Urban and Galvin, 1969;Nordstrom and Inman, 1975; Aubrey, 1979;Felder and Fisher, 1980; Clarke and Eliot,1983; Berrigan, 1985; Brampton and Beven,1989), and in terms of botizontal shoTelineshilts or beach width changes (Darling,1964; Johnson, 1971; DeWall and Richter,1977; DeWall, 1977; Aguilar-Tunan andKomar, 1978; Everts and others, 1980;Clarke and Eliot, 1983; Miller, 1983;Garrow, 1984; Berrigan and Johnson, 1985;Patterson, 1988; Kadib and Ryan, 1989).

Potential legal ramifications ofseasonal shoreline changes as they relate tothe jurisdictional shoreline boundary positionhave been addressed by Johnson (1971),Hull (1978), O'Brien (1982), and Collins andMcGrath (1989). While there are otherseasonal shoreline change applications(discussed in the section on Application ofResults), the motivation for this work centersabout derivation of a least equivocalmethodology for identifying probable realshifts in historical long-term shorelinechange.

In addition to wave height and wavesteepness, wave direction and beachsediment characteristics can influence thedegree of seasonal beach change. Wavedirection is particularly influential for pocketbeaches found along the U. S. west coast.Along some beaches (e.g., Oceanside Beachjust north of Cape Meares, Oregon) a sandy"summer" beach is removed during the"winter" season exposing a cobble beach.In such cases, "summer" to "winter" grain

SPECIAL PUBLICATION NO. 43

size differences are significant. In this study,however, we shall deal with relativelystraight, ocean-fronting beaches composedentirely of sand~sized material.

DATA AND RESULTS

In an investigation of seasonal beachchanges at Torrey Pines Beach, California,Aubrey and others (1976) state: NNo fieldstudies to date have been able to adequatelyquantify these wave-related sedimentredistributions.· In approaching aquantitative solution(s) to the problem, itbecomes prudent to identify the force andresponse elements involved. Basic forceelements are identified to be: 1) astronomical tides, 2) wave height, and 3) wavesteepness. Response elements are: 1) volume change, 2) change in beach elevation,or 3) horizontal shoreline shift. While thebeach sediment might be viewed as aresponse element, given the paucity ofinformation about temporal/spatial sedimentvariation as it impacts this problem, it maybe prudent to treat sediment characteristics(within the sand-sized range) as a propertyelement (see section on Beach Sediments forfurther discussion).

The response element used here isthe horizontal shoreline shift. Fortunately,we are dealing with a measure which,compared to the others, has the largestrange in possible values. For example,vertical contour changes are less than 1-1/2to 2 meters, and volumetric changes wouldbe 3 to 4 times less than horizontal shift(" rule-of-thumb" guidance suggested by U.S. Army (1984) and Everts and others(1980)). while horizontal shift may range upto tens of meters.

Data

While the amount of data available toquantify seasonal variation in shorelineposition is not large, 14 data sets for whichsufficient information appears to exist were

3

located to search for a solution (Table 1).

First. it might be reasonable toinspect the relationship betweenastronomical tidal conditions and horizontalseasonal shoreline shift, V5' since the tidalcondition essentially constitutes a signaturecharacteristic for each site (i.e., it can varyconsiderably depending on the coast understudy). Horizontal seasonal shoreline shift isdefined as V5 = Vmax -Vmin , where Vmax isthe largest measurement representing thewidest seasonal beach, and Vmin is smallestmeasurement representing the narrowestbeach (in this paper V is the distance froman arbitrary permanent coastal monument tothe shoreline at anyone time). The meanrange of tide, hmn, (i.e., the differencebetween mean low water and mean highwater), is plotted against Vs in Figure 1.While there is scatter in the plot, a generaltrend is apparent.

In addition to astronomical tideconditions, we know that wave climate mustbe considered and that it, like tidalconditions, varies widely from coast tocoast. Selection of values for variablesgiven in Table 1 can be illustrated using timeseries plots of monthly averages forshoreline shift and wave data. An examplefor Torrey Pines Beach, California, is plottedin Figure 2, which represents two years ofconcurrently observed monthly averages forshoreline position, wave height, wave period,and sediment data (Nordstrom and Inman,1975; Pawka and others, 1976). Further,the data have been smoothed by a threepoint moving averaging sequence.Comparison of horizontal shoreline shifts andwave heights suggests that for the monthsfrom about December through April stormwave activity prevailed, resulting in anarrower beach, with lull conditions fromabout May through October coinciding withbeach widening. Hence. the average stormwave height, Hs, is that occurring fromDecember through April, and the average lullwave height, HL, is that occurring from May


Table 1. Force, response, and property elements for seasonal shoreline shift analysis.

SiteVs Hs Hl Ts TL hm.. 0 CO/COs(m) (m) (m) (5) (5) m (mm)

Gleneden, OR 46.9 1.14 0.72 9.2 8.1 1.91 0.35 0.815

Stinson Beach, CA 42.7 1.28 0.99 16.1 12.1 1.21 0.30 1.370

Atlantic City. NJ 32.0 1.04 0.77 7.4 7.0 1.40 0.30 0.820

Torrey Pines, CA 29.0 1.34 0.99 11.8 11.4 1.28 0.28 0.794

Goleta Point. CA 22.9 1.07 0.73 12.5 14.0 1.28 0.21 0.547

Duck., NC (1982) 18.6 1.10 0.75 8.8 8.1 1.00 0.40 0.808(1983) 20.4 1.26 0.73 9.2 8.1 0.98 0.40 0.749(1984) 17.4 1.15 0.70 8.7 8.4 0.96 0.40 0.654

Surfside-Sunset, CA 20.1 1.10 0.73 10.2 13.2 1.07 0.26 0.398

Huntington Beach, CA 18.3 1.14 0.99 11.6 10.4 1.15 0.21 1.078

Holden Beach, NC 15.2 0.70 0.50 6.5 7.0 1.30 0.30 0.614

Jupiter Beach. FL 10.7 1.00 0.63 5.4 5.5 0.92 0.42 0.614

Boca Raton. FL 2.4 0.64 0.51 4.9 4.5 0.84 0.90 0.933

Hollywood, FL 2.1 0.49 0.47 4.7 4.5 0.79 0.60 1.037

Vs = Seasonal range in shoreline position or beach width; Hs = Storm season average wave height;HL = Lull season average wave height; Ts = Storm season average wave period; T l = Lull season average waveperiod; hmn = Mean range of tide; D = Swash zone mean grain size; ¢l l = Lull season wave steepness; ¢Is =Storm season wave steepness; CA = California. FL = Florida, NC = North Carolina. NJ = New Jersey, OR =Oregon. Sources of data are given by beach in the text.

4

shoreline

inclusive) consistently result in the 43-meterseasonal shoreline shift reported by Johnson(1971) and O'Brien (1982).

Concurrently observed data for fouryears at Jupiter Beach, Florida (DeWall,1977; DeWall and Richter, 1977) are plottedin Figure 4. It is apparent from Figure 4 thatlull wave heights occur from about Maythrough September resulting in a widerbeach, with storm waves occurring fromabout October through at least January

Vs =21.9 + 37.6 limn

r =0.1302

6O_,.....,,.............-.,........""'T"""T"""'T"'""T"""".,..-_,.....,,....,.......-.,.....,....,..""'1

(m) 20

hmrt (m)

Figure 1. Relationship between seasonalvariability, Vs, and mean range of tide, hmrt.

through October. Note thatwave period varies littlethroughout the year for thissite.

The classic example ofseasonal shoreline shift(Johnson, 1971; O'Brien, 1982)for Stinson Beach, California.represents a 22-year period(1948-1970), suggesting anaverage shoreline shift of about43 meters annually. These data are plottedagainst six years of wave data for the period1968 to 1973 (Schnieder and Weggel,1982) in Figure 3. Sediment data are from aseparate source (Szuwalski, 1970). Notethat unlike the data plotted in Figure 2, waveperiod shows a concerted seasonal trend.The inference may be made. therefore, thatspecial attention should be given to seasonalwave steepness values. More recentshoreline surveys published by Collins andMcGrath (1989) for three years (1984-1986


11

T

I 0 _~""""-I-.....I.---I_"'--"""""""--L.......&.......I'---I

JFMAMJJASONOJ

MOfttll

Figure 3. Monthly time series for StinsonBeach, California, for shoreline variability, V;breaker height, Hb; and wave period, T.

wave height and period are given by HL, andTlI respectively; similarly, storm seasonvariables are given by Hs, and Ts. Waveheights and periods were selected torepresent conditions for the lead flanks ofseasonal accretion/recession trends, since itis under these force element conditions thatresponses are produced.

Similar analyses were conducted forBoca Raton and Hollywood Beaches inFlorida (DeWall, 1977; DeWall and Richter,1977) for four years of monthly data for V,wave height and period, with mean grainsizes for swash zone sediment.

Data published for Holden Beach,North Carolina (Miller, 1983) were plotted bythe original author so that seasonal changes

5

IS 90

10 85 •V 10 ",.;........

"' "75 , .' ,, ,.(m) V ,

70 , .\.,' \

tiS-,, ., \ .

60 • , ,(m) ,.

I• , ,55 ,. I•50 "' \

/. •- • '\I

Hb.5 • /' .

---• 0 --~..-.35 •

(m)I..

I.JHb 1.2

(m) 1.l

1.0

0.9

IO~...A:-~~~I.o-~""'''''''''--''''''''I.-.l....'''''...,jMJJASONOJFMAM

tlcMllII

Rgure 2. Monthly time series for TorreyPines Beach, California, for shorelinevariability, V; breaker height, Hb, and waveperiod, T.

producing a narrower beach. Monthlyaverages for wave heights and periods wereconcurrently measured, with a reportedrepresentative grain size.

T

A single year of monthly wave datawere collected (Aguilar-Tunan and Komar,1978) at Gleneden Beach, Oregon, fromwhich a seasonal shoreline shift of about 47meters is evident. Because wave datareported by the authors are probablyinappropriate (i.e., they strongly appear torepresent the initial offshore breaking waveheight), the multi-year data reported by theU. S. Army (1984) are used. A single swashzone sediment size was reported by AguilarTunan and Komar (1978). Shoreline shiftand wave data are plotted in Figure 5.

These four examples illustrate howwave data values were determined torepresent each season, where the lull season

v

(m)

(m)

T

(I)

with simultaneously measured seasonalwave data. Sediment data are from the U.S. Army (1984).

Perhaps the most complete data setsare for Duck, North Carolina, at the CoastalEngineering Research Center's FieldResearch Facility. All information necessaryfor this study was collected simultaneouslyto result in data for three years (Miller, 1984;Miller and others, 1986a, 1986b, 1986c).

J F M A M J J A SON 0 J

IIoIItll

Figure 5. Monthly time series for GlenedenBeach, Oregon, for shoreline variability, V;breaker height, Hb; and wave period, T.

Where the specific studies discussedabove did not provide the necessaryastronomical tide information, these datawere obtained from other sources (Harris,

For a 4-1/2 year period, Patterson(1988) reports a Vs of 20.1 meters forSurfside-Sunset Beach, Orange County,California, along with seasonal waveinformation. Sediment grain size informationis from Szuwalski (1970).

6

T

Results for Goleta and HuntingtonBeaches, California (Ingle, 1966) includeapproximately monthly surveys for a oneyear period, including beach profiles, wave,and sediment data. Unfortunately, waveinformation for these sites representsonly those conditions for the day profileswere surveyed. While information for thesesites generally was consistent, wave perioddata from Schneider and Weggel (1982)were used for Goleta Beach due tounresolvable dispersion in the few daily data.

(I)

• JL-~F--J.M~A~...L.M--J.J-.Jl:-...L.A~S---JO'-N..I...-~O~J

Month

Figure 4. Monthly time series for JupiterBeach, Florida, for shore variability, V;breaker height, Hb; and wave period, T.

v

could be directly assessed by measuringpeaks of change. The data represent fouryears of approximately monthly profiles for16 alongshore profiles, with concurrentlymeasured wave data. Sediment data arefrom the U. S. Army (1984).

(m)

(m)


Seasonal shoreline shift data forAtlantic City, New Jersey (Darling, 1964)were measured for a two-year period along


1981; U. S. Department of Commerce,1987a, 1987b).

It is worthwhile to note that Berriganand Johnson (1985) compared wave powercomputations to shoreline position for sevenyears of data at four localities along OceanBeach, San Francisco, California. Deepwater wave data were measured at sitesranging from 3.9 to 26.7 kilometers offshore(Berrigan, 1985). While some refractioneffects may have occurred due to the SanFrancisco entrance bar, there appears to bea correlation between an increase in wavepower and decrease in beach width.

Results

There is, from Figure 1, an indicationthat astronomical tides play a role inseasonal variability. The mean range of tide,hmrt and seasonal wave height difference,~H ,;" Hs - HL, might be expressed as a sum,i.e., hmrt + ~H, or as a product, i.e., hmrt

(~H). Since energy according to classicalwave theory is proportional. to the heightsquared, the product, i.e., hmrt (~H), mightbe more appropriate. On the other hand, thesum has merit because laboratory data, ifavailable, could be used (i.e., since tides arealmost never modelled in laboratory studies,a product would be meaningless because theresult would always be zero). In eitherevent, many combinations of parameterswere investigated (Balsillie, 1987b; see alsoTable 2 for some of the equations), and itwas found that the sum was not nearly assuccessful as the product; either scatter wasexcessive as indicated by a low correlationcoefficient, r, and/or the fitted regression linedid not pass through the origin of the plot.

Many researchers have emphasizedthe importance of wave steepness ininfluencing the shore-normal direction ofsand transport (e.g., Johnson, 1949; Ippenand Eagleson, 1955; Saville, 1957; Dean,1973; Sunamura and Horikawa, 1974;Hattori and Kawamata, 1980; Sawaragi and

7

Deguchi, 1980; Watanabe and others, 1980;Quick and Har, 1985; Kinose and others,1988; Larson and Kraus, 1988; andSeymour and Castel, 1988). In this paper,the "summer" or lull season wave steepnessis expressed as ¢>L = H/(g TL2), and the"winter" or storm season steepness as CPs =HJ(g Ts2), It became apparent thatincorporation of the wave steepness ratioinduced numerical consistency inquantitative prediction. Whether the ratio isevaluated as ¢>/¢>s or ¢>JCPL becomesimportant. The form of the ratio for variousarrangements of relating expressions forassessment purposes is given in Table 2.Hence, if (¢>/¢>s) < 1.0 then wave heightduring the storm season must be moreimportant; if (¢>/¢>s) > 1.0 then wavesteepness plays a stronger role. In fact, itwould be expected that ¢>L/¢>S results inbetter correlation, since beaches are erodedby steeper waves, with lower steepnesswaves resulting in accretion.

In addition, beach sedimentcharacteristics have been touted to play asignificant role. The general view is that,holding force elements constant, a beachcomposed of coarser sediment is more stablethan a beach composed of finer material(e.g., Krumbein and James, 1965; James,1974, 1975; Hobson, 1977), i.e., a beachcomprised of coarser sediment should exhibitless seasonal variability than a beachcomposed of finer sediment (note that thisexplanation is not so straightforward, andwill be addressed in greater detail in thefollowing section). Since a number ofinvestigators have published generalquantifying relationships which in addition towave height and steepness, incorporate sandsize (e.g., Dean, 1973; Hattori andKawamata, 1980; Sawaragi and Deguchi,1980; Watanabe and others, 1980), it wouldbe prudent to consider granulometry in thisstudy.

Again, it is to be noted that manyforms of possible relating parameters were


'~.

Expressions Using CPL/CPS r Expressions Using CPS/CPL r

h"", + [~H) 41 L {4Isl0.9339

hmrt + [~H) 4Is /4IJ0.7445

[hmrt + (AH)1 4l L /4l S0.8843

[hmrt + (AH)] 4IS~L0.4071

h"", (AH) 4lL f4l s0.9047

hmlf (AH) 4lS~L0.5498

h"", + [~H) 4l L /4ls1 hIM + [~H) 4ls /4l,J

D 0.8567 D 0.3837

hIM (11H) 4l L /4lS hIM (liH) ~S~LD

0.9672D

0.5478

r = Pearson product-moment correlation coefficient between each expression evaluatedusing measured force and property element data of Table 1, and measured Vs response

data of Table 1.

Table 2. Assessment of the wave steepness ratio for a selection of expressionsrelated to V

considered in an earlier study, but that onlythe most successful are presented here.Incorporating the preceding considerations,two equations are presented, the first whichincludes force elements only, which posits:

(1)

and is plotted in Figure 6. The cubic leastsquares regression coefficient (forcedthrough the origin) of 78.5 is in units of m·l

where the mean range of tide, hmn, andseasonal wave height difference, ~H, are inmeters. The standard deviation of the datafrom the equation (1) regression line in thevertical direction (Ricker, 1973) is 11.4 m.The second equation includes the meanswash zone grain size, 0, to yield:

(2)

plotted in Figure 7, wherein all variables areexpressed in consistent units. In terms ofdimensions, one will note that when alldimensional cancellations are made inequations (1) and (2), length only remains.The coefficient of 0.025 was determinedusing the same fitting procedure as forequation (1). It is apparent from the figuresthat equation (2) reduces some of the scatterof equation (1). The standard error (Ricker,1973) of equation (2) in the vertical directionis 6.8 m. It may also be of interest to notethat the coefficient of equation (1) whenexpressed relative to the coefficient of

8

--~~_.__._-_ ..

9

The Single Extreme Event andthe Combined Stonn Season

become available to further test and/orenhance the prediction relationships.Nevertheless, the results presented here arestatistically valid; one should not be timid inapplying resulting computational valuespending future refinement in predictionmethodology. One purpose of this paper isto act as a plea for more data. Following arediscussions of a few concerns related toseasonal shoreline variation predictions.

The sandy littoral zone is comprised,from offshore·to-onshore, of the nearshore,the beach, and the coast. Each of thesethree subzones is created and maintained bysets of force elements normally differentfrom each other within the long-termtemporal framework. When a storm orhurricane impacts the littoral zone, thefollowing scenarios are possible: 1) theextreme event produces a combined totalstorm tide which rises above the beach-coastinterface elevation to affect all threesubzones, 2) the combined total storm tidedoes not rise above the beach-coast

"mrl (6N) 41L/4'sVs =0.025 D

r.s 0.'.72

oo·

°o:F--;tI-*---::~--;;L::---*---::~-...;J1I~0.2 0.3 0." 0.5 0.6 0 7

"mrl (6H) 41L/41s (m2)figure 6. Illustration of mathematical fit for equation (1).

1000

""'r. (AN) 41L/4ls (m )D

Figure 7. Illustration of mathematical fit for equation (2).

DISCUSSION

A favorable result frommany of the prediction equationstested during the course of thisinvestigation is that most showed Vs

a trend between Vsand the relating'lit)

parameters (e.g., column 1 ofTable 2). Ostensibly, suchconsistency should not besurprising since the major factorsknown to cause seasonalvariability were considered, andthe remainder of the workinvolved rearranging the variables to reducescatter. Further, the goal to delineateseasonality was a simplified approach(compared to relating the entire time seriesof monthly values which becomesincreasingly complex).


equation (2) results in a mean 60r--..,.---r--,.----r--.---,.- __

grain size of 0.318 mm which.u sin 9 the Wen two r t h Vs'-O

classification scheme. is amedium-sized sand (Wentworth, ("'I 20

'922).

Equations (1) and (2) engender someheterogeneity that needs discussion. Both~H and t/Jl/t/JS are seasonal parameters.Granulometry as it appears in equation (2) isa property element application, although aseasonal response element application ispossible and is discussed in a later section.The quantity, hmrt, however, is not aseasonal measure. It is, rather, an averageapproximate hourly measure where one tide(diurnal) or two tides (semi-diurnal) occur inone tidal day of 24 5/6 hours. Hence, hmrtis also a property element that is a signaturevalue for each site, noting that it can varysignificantly depending upon the locale.Seasonal mean sea level change for whichthere are no site-specific data for Table 1localities, is discussed in a following section.

The results of this work might be bestviewed as a first appraisal until more data


1

60

2

1986; Savage and Birkemeier, 1987), forevents described by scenarios 1, 2 and 3above. Beach recovery following the effectsof a storm wave event (i.e., scenario 4) wasrecorded by James P. Morgan at hisPensacola Beach, Florida, home (Figure 8);within a day following storm waveabatement, the beach had recovered to itspre-storm width.

1 2 3 • 5 6 1 8 9 101112Day

Figure 8. Example of the quick response andrecovery of the beach to storm waveactivity, Pensacola Beach, Florida, December1974;the storm peak occurred on December7 (data courtesy of James P. Morgan,personal communications).

(m) 50

(m) 0

The magnitude of seasonal shorelinechange may vary from year-to·year, since forany site some years may have more frequentand intense storm tide and wave activitythan other years. Horizontal shoreline shiftsdue to direct storm and hurricane impactsare now usually recorded. However, forstorms that do not directly impact the shore(i.e., are far out at sea, for example TropicalStorm Juan (Clark, 1986) which affectedFlorida) but generate storm waves that do

interface elevation but does persist longenough for the beach to be eroded and thecoast is attacked by storm waves, 3) thecombined storm tide does not rise above thebeach-coast interface elevation and is shortenough in duration so that only thenearshore and beach are affected, and 4) theextreme event remains out at sea so thatimpact is indirect (i.e., a combined totalstorm tide does not or only fractionallyreaches the shore) and storm wavesprimarily affect the nearshore and beach.The combined total storm tide used here isdefined by Dean and others (1989) as thestorm surge due to astronomical tide, windstress, barometric pressure, and breakerzone dynamic setup, which defines theactive phenomena for scenarios 1, 2, and 3(i.e., the stonn tide event). Scenario 4includes only the effects of breaking waveactivity, including dynamic wave setup, andis termed the stonn w.ve event. Scenarios1 and 2 are those which, depending onstorm strength, duration, continental slope,and approach angle, usually produce thedesign erosion event (Balsillie, 1984, 1985a,1985b, 1986). Probabilistically, thefrequency of occurrence increases fromscenario 1 to 4.

Under certain circumstances of eventlongevity, astronomical tides, and nearshoreslopes, exceptions can occur. One suchexception occurred when Hurricane Gilbertstruck Cancun, Mexico in 1988. Becausethere is essentially no continental shelf andnearshore slopes are steep, all eroded sandfrom Cancun's beaches was removed andnatural beach recovery was not possible.Potentially, other exceptions can occurwhere, for instance, submarine canyonsmight act as a sediment transport conduitand sand is irremeably lost from the littoralsystem. For most shores, however,continental shelves are wide and nearshoreslopes gentle enough that beach recovery topre-storm dimensions following single stormimpact occurs in a period of one to severaldays (Birkemeier, 1979; Bodge and Kriebel,

10


cause shoreline erosion, sucherosion is usually not measured.

Month

Figure 9. Monthly average occurrences of extreme eventwave events for the Outer Banks of North Carolina.

PI

JI

IJ

o,J

J

/I

JaJ

JI

II

JD

\ '\ ',

Q

Beach Sediments

a

EXTREME EVENT TYPE

o Extretroplcel (Dolan. Llna, andHayden, 1981) "42-1184

o Tropica' I (Neumann et al.• Hurricane 1981) 1940-1980

Beach sediments engender someinteresting concerns. How we considersediments depends upon whethergranulometry is applied as a propertyelement or a response element, which in turnhas an effect on the dimensionalconfiguration of a numerical representation.As an example, equation (1) requires anadditional parameter with units of L·1 for theequation to be unit consistent. Equation (2)was rendered unit consistent by dividing bya granulometric parameter with a lengthdimension. If this is to be the applied case,it is useful to note that when sedimentologicgrain size is specified in S. I. units, the meangrain size and standard deviation momentmeasures have units of mm, while

5

1

'5c:o

2 "..•~•-c:•&io 3...•~E~z& 2•...•.I

Dolan and others (1988)conducted an extensive study onextratropical storm activity,assessed also in terms of stormwave hours, for 41 years of data(1942 to 1984) along the OuterBanks of North Carolina. Thesedata (Figure 9) show a concertedseasonal trend. In addition, theauthor extracted from Neumannand others (1981) tropical stormsand hurricanes whose trackscame within about 250 miles ofthe Outer Banks for the period1940 to 1980. These latter data,also plotted in Figure 9, are addedto the extratropical data (plottedas a bold, solid line). Hence, thetotal storm record is nearlyrepresented and, except for onlya few direct impacts, representstorm wave events (i.e., scenario'4 above). For the mid-Atlantic,about 35 storms occur per yearon the average (about 26 winterevents and 9 summer events),93% of which are extratropicalevents. In terms of storm wave duration,Dolan and others (1988), determined usinghindcast techniques that on the average,storm waves occur for about 571 hours peryear (i.e., 24 days per year) for extratropicalstorms off of the Outer Banks; winter stormwaves persist for an average of 433 hours(i.e., 18 days), and summer storm wavesabout 156 hours (i.e., 6.5 days). These datastrongly correlate with the expectation ofwider mid-Atlantic east coast summerbeaches and narrower winter beaches, andillustrate the important fact that a largenumber ... not a few ... winter stonn eventsaTe required to maintain a nanuwer winterbeach relative to a wider summer beach.

11


Table 3. Mean annual beach grain size (foreshoreslope samples) from monthly data, and range in size.

Annual RangeSite D(mm) of D Source

(mm)

FLORIDA

S1. Andrews St. Pk. 0.29 0.04 Balsillie, 1975Grayton Beach 0.37 0.13 " "Crystal Beach 0.37 0.15 " "J. C. Beasley St. Pk. 0.40 0.11 .. "Navarre Beach 0.41 0.14 .. "Fort Pickens Beach 0.43 0.27 " "

NORTH CAROLINA

Duck 0.40 0.19 Miller. 1984

CALIFORNIA

Goleta Pt. Beach 0.21 0.16 Ingle, 1966Trancas Beach 0.22 0.18 ,

"Santa Monica Beach 0.26 0.29 .. "Huntington Beach 0.21 0.14 " .La Jolla Beach 0.17 0.04 " "

skewness and kurtosis aredimensionless. Otherwise, thegranulometric moment measures canbe specified all in dimensionless phiunits.

Beach sands characteristicallyhave a range in size from 0.1 mm to1.0 mm (U. S. Army, 1984) whichoccupies about 46% of the sandsized range of Wentworth (1922;i.e., 0.0625 to 2.0 mm). From Table3, it is apparent that the range inmean grain sizes occurring over anannual period is less than 1/3 of thecommonly found range in beach sandsize (i.e., 0.9 mm). Therefore, thetypical annual mean grain size, 0, forany beach might be an appropriatemeasure to consider as a propertyelement provided that sufficientsamples are available annually toobtain a reliable measure (e.g., a suite ofmonthly samples). This implies that thereneeds to be a real difference in mean grainsizes from site-to-site for the application tohave meaning. Even so, the use of meangrain size alone without consideration ofstandard deviation, skewness and kurtosisremains somewhat of a curiosity other than:1. its use results in a good fit for equation(2), 2. is properly applied in equation (2)(i.e., the larger the value of D, the smallerbecomes V s)' 3. produces the proper unitdimensions for the equation, and 4. hasbeen a considered variable in other researchresults.

It is generally the case (CASE 1 ofTable 4) that the coarsest beach sand isfound in the swash zone, and which is theonly type of sample considered here since itdirectly represents energy expenditures ofthe littoral hydraulic environment. Onemight suspect that swash samples arecoarser during the storm than the lullseason. However, the range in sedimentsize within the sand-sized range is limited forany beach to the coarsest available material

Table 4. Two cases of sedimentologicresponse of moment measures to waveenergy levels.

CASE' CASE 2Enetgy UveIs Ale Enetgy lewis Ale

&.cessive 10 Nat fJcc:essive 10Se__1dDkigic Se6nentulagic

RespawlSe Respmi5e

MEAN GRAIN SIZE

Ds - DL I Os > DL

SKEWNESS

SkS - SkL I Sks < SkL

KURTOSIS

Ks < KL I Ks < KL

NOTES: Subscripts 5 and L refer to the stonn seasonand lUll season, respectively. The corresponds tosymbol, ~, is meant to signify that the measure didnot change due any recognizable response to energyleve.1 force element changes.

commensurate with bulk properties meetingconservation of mass and energeticsconstraints (Passega, 1957, 1964). In fact,

12


13

the negligible effect of sand-sized material onrunup for larger waves has been noted bySavage (1958). His results strongly implythat relative to sand size, as the wave heightincreases there is reached a point beyondwhich sediment size within the sand-sizedrange no longer discriminately responds.That is, the level of wave energy isoverpowering even to the coarsest fractionof sediment available within the sand-sizerange.

Hence, unless the wave climate isclosely in equilibrium with sedimentcomprising the beach, one would notnecessarily expect to find significantlycorrelative seasonal changes in mean grainsize (or for that matter skewness, althoughit might be somewhat less sensitive toenergy) within the sand-size range. Theauthor located data where at least monthlysand samples were collected with concurrentwave data for sites along the U. S. west,east, and Gulf coasts. There was nodiscernible seasonal correlation betweenwaves and mean sediment grain size.Several typical examples are illustrated inFigure 10.

Samsuddin (1989), however, reportsto have found correlation between seasonalchanges in wave conditions, foreshore slope,and sand-sized textural changes along thesouthwest Kerala coast of India, whereinmean grain size increased and kurtosisdecreased during higher seasonal waveenergy conditions (CASE 2, example 1).Samsuddin's one-year investigation, in whichbeach foreshore sand was seasonallysampled, may have been a fortuitous year inwhich equilibrium conditions were morenearly manifest. Kerala sand samples arealso characterized by a consistently largestandard deviation which allows for greaterleeway in sorting potential (0.6 to 0.7 phicompared to 0.2 to 0.55 phi commonlyfound for U. S. beach sands). Unfortunately,Samsuddin did not describe the mineralogyor shape characteristics of the samples

T

e-I o.so

CUI

1,---...... __....T I..

e-) 3z St. ... . ""...

D U h>-"'........__- '""--

e_1 It.Z'.1 ~~L-J..~u..~..J...&...J....&....L.""I,...c...L...I. ..&.....I.""""J...J

.. " SO.DJF SO.D_Illfigure 10. Typical examples of time series relationof monthly data for breaker height. wave period,and foreshore slope grain size for California (datafrom Ingle, 1966) and northwestern Roridapanhandle (data from Salsillie. 1975) sites.

which mayor may not differ from thecharacteristically rounded. quartzosefeldspathic U. S. beach sands considered inthis work.

There also occurs the case (CASE 2,example 2) where a beach is comprised ofsediments exceeding the sand-sized range.An example is Oceanside Beach, Oregon,mentioned earlier, in which all the sand-sizedsummer beach material is removed to exposea winter cobble beach. Under suchconditions, one would expect that sedimentcoarsening, as reflected by the mean grainsize and skewness, would result from higherwave energy levels because of the excessivesize of coarser sediments.

When singularly considered, the 1stmoment measure (mean grain size) tells usnothing about the nature of the distribution.


From the preceding discussion, it isapparent that two general cases can beidentified where wave energy levels eitherexceed stability constraints of the coarsestfraction of the sedimentologic distribution, orthey do not. For three moment measuresconsidered to best represent sedimentologicresponse to the wave energy force element,storm and lull season responses are listed inTable 4. For the two cases (Table 4) onlythe kurtosis persists in providing a response,because the 4th moment measure is notrendered ineffective to register a change byexcessive wave energy levels. Therefore, aparameter for consideration that more nearlyquantifies sedimentologic response might begiven by:

The 2nd moment measure (standarddeviation) tells us about the dispersion aboutthe 1st moment measure, but leaves noinsight as to how the distribution departseither symmetrically or asymmetrical fromthe normal bell-shaped frequency curve (orfrom the straight line for the cumulativecurve plotted on standard probablity paper).Such departure is a characteristic of the tailsof the distribution about which knowledge isprogressively imparted to us by consideringthe 3rd moment measure (skewness), 4thmoment measure, (kurtosis), and highermoment measures (Tanner, personalcommunication; Balsillie, 1995). It is, infact, the tails of the distribution which canprovide a great deal of environmentalinformation. It has been demonstrated, forinstance, that there is an inverse relationshipbetween the kurtosis and the level of surfwave energy expenditure (Silberman, 1979;Rizk, 1985; Rizk and Demirpolat, 1986;Tanner, 1991,1992). Tanner (1992) hasreported a correlation between sea level riseand kurtosis, because the rise component isattended by an increase in surf wave energyexpenditure.

e = (20 + Sk) KD

(3)

14

where the moment measures are defined inTable 4. The 3rd moment measure(skewness) of equation (3) has a value of 20added to it in order to assure that positivevalues will result. The parameter () whenevaluated using S. I. units has units of V'(dimensionless units result whengranulometric measures are evaluated in phiunits). By using seasonal values of 8, thatis, 8s for the storm season and 8L for the lullseason, it may be possible to compile asedimentologic response element parameterthat can be incorporated into equation (1).The proper form of the parameter, includingequation (3), however, requires additionaldata, research, and testing.

AstrDllomical Titles

That mean astronomical tideelevations exhibit cyclic seasonal variabilityhas long been established (Marmer, 1951;Swanson, 1974; Harris, 1981) and isincluded in tide predictions. The U. S.Department of Commerce (1987a, 1987b)states, however, that at .... ocean stationsthe seasonal variation is usually less thanhalf a foot.· Marmer (1951) notes thatseasonal variation in terms of monthly meansea level for the U. S. can be as much as0.305 m (1 foot; Table 5); some examplesfor the U. S. east, Gulf, and west coasts areillustrated in Figure 11. Based on the manyyears of monthly data, researchers (Marmer,1951; Harris, 1981) note slight variations inthe seasonal cycle from year-to-year, butalso recognize the periodicity in peaks andtroughs over the years. For much of ourcoast, lower mean sea levels occur duringthe winter months and higher mean sealevels during the fall. Harris (1981 )inspected the record to determine if stormand hurricane occurrence was in any wayresponsible for the seasonal change, butfound .... no systematic variability·. Galvin(1988) reports that seasonal mean sea levelchanges are not completely understood, butsuggests that there appears to be twoprimary causes for lower winter mean tide


levels for the U. S. east coast: 1. strongnorthwest winter winds blow the wateraway from shore, and 2. water contracts asit cools. He notes that winds are moreimportant in shallow water where tidegauges are located, but that contractionbecomes important in deeper waters.Swanson (1974) also notes .... seasonalchanges resulting from changes in directbarometric pressure, steric levels, riverdischarge, and wind affect the monthlyvariability. "

Seasonal variation in tides is usuallyattributed to two harmonic constitutents:one with a period of one year termed thesolar annual tidal constituent, and the otherwith a period of six months termed the solarsemiannual constituent (Cole, 1997). Someconsider these to be meteoroligical in nature,rather than astronomic. However, becausethe root cause of cyclic seasonal weather isthe changing declination of the sun, theyshould more nearly be astronomical in origin.Harmonic analysis of the annual tidal recordcan easily determine the amplitude andphase of each of these constituents, thereby

.providing a mathematical definition of theseasonal variation. (George M. Cole,personal communications.)

Comparing the closest appropriatecurve from Figure 11 to Figures 2 through 5,it is apparent that the lowest seasonal standof mean sea level and, therefore, averageastronomical tide effects occurs when thebeach is narrowest for Stinson Beach andTorrey Pines Beach, California, and JupiterBeach, Florida. For Gleneden Beach,Oregon, narrow beach widths and monthlyaverage tidal highs seem to be more nearly inphase. Therefore, it is not clear thatseasonal changes in astronomical tidessignificantly affect seasonal shorelinevariability, at least not in terms of averagemonthly measures. Quite clearly, however,such data needs to be procured for each siteto confirm a correlation or lack thereof.Should the proper correlation consistently

Table 5. Seasonal range in monthlyaverage water levels.

I SiIe Iv:" Ih

I I- I(m) Law

U. S. fast Coast

New York. 19 0.177 Feb SepAtlantic City 19 0.165 Feb SepBaltimore 19 0.238 Feb SepNorfolk 19 0.177 Feb SepCharleston 19 0.253 Mar OctMayport 19 0.314 Mar OctMiami Beach 17 0.259 Mar Oct

U. S. a. Coast

Key West 19 0.216 Mar OctCedar Key 10 0.244 Feb SepPensacola 19 0.232 Feb SepGalveston 19 0.247 Jan SepPort Isabel 4 0.262 Feb Oct

U. S. West Coast

Seattle 19 0.159 Aug DecAstoria 19 0.219 Aug DecCresent City 14 0.180 Apr DecSan Francisco 19 0.104 Apr SepLos Angeles 19 0.152 Apr SepLa Jolla 19 0.143 Apr SepSan Diego 19 0.152 Apr Sep

Notes: 1. h = seasonal range based on average of nyears of monthly means where monthly means areaverage of hourly heights; 2. San Diego gauge islocated in San Diego Bay; 3. Astoria gauge is located 15miles upstream from the mouth of the Columbia River.

occur (e.g., low monthly average mean sealevel - wider beaches, and high monthlyaverage mean sea level - narrower beaches)then a relating parameter needs to beincorporated in the quantifying predictiverelationship(s). It is of consequence to note,for the data of Tables 1 and 4, that theseasonal range of monthly average mean sealevel is from 9 to 33% of the mean range oftide (hmrt).

APPUCAnON OF RESULTS

While horizontal shoreline shift (orbeach width change) addresses only one

15


III

u. S. GULF coasT

~'MAM~~ASO"D

MONTH

u. s. weST COAST

~ , M A M ~ ~ A • 0 " D

Rgure 11. Monthly variation in sea level for the contiguous United States (afterManner, 1951).

dimension of a measure of beach change, itdoes serve to straightforwardly punctuatethe nature of the phenomenon. The mannerof approaching quantification of thephenomenon here, allows for a simplyapplied methodology that is useful foreducational, technical, and planningpurposes.

General Knowledge

Seasonal beach shifts are notgenerally known by the layman. In Florida,with 35,000 new residents arriving monthly(Shoemyen and others, 1988), new coastalproperty owners have been alarmed afterpurchasing ocean-fronting property duringthe "summer" when their beach is wide, tofind or return to find a narrow ·winter"beach, believing that they have unwittinglypurchased eroding property. OstensiblY, thismight result in an application for a permit toconstruct a coastal hardening structure suchas a bulkhead or seawall withoutinvestigating seasonal beach width variationon the part of the applicant, the applicant'sdesign professional, or the permitting

16

agency. The results of this paper provide aquantitative basis upon which to inform thepublic, and a method to assess a permitapplication.

SeawanlllDundary of Publicversus

Private Ownership

The boundary between private (i.e.,upland) and public (i.e., seaward) beachownership is fixed by some commonlyapplied tidal datum. For most of the U. S.this is the plane of mean high water (MHW)which, when it intersects the beach or coastforms, the mean high water line. However,unlike other riparian ownershipdeterminations (i.e., fluvial, lacustrine andestuarine), littoral properties must, inaddition, contend with significant waveactivity that seasonally varies. Hence,ocean-fronting beaches all-too-oftenexperience cyclic seasonal width changes ofa magnitude long recognized as problematicin affixing an equitable boundary (Nunez,1966; Johnson, 1971; Hull, 1978; O'Brien,


1982; Graber and Thompson. 1985; Collinsand McGrath. 19891.

Many investigators have suggestedthat the legal boundary for ocean·frontingbeaches should not be continuously movingwith the seasonal changes. but should bethe most landward or "winter" line of meanhigh water INunez. 1966). Selection of the"winter" MHW line would be the mostpractical to locate and would be the mostprotective of public interest by maintainingmaximum public access to the shoreline(Collins and McGrath, 1989).

In Florida, the ocean-fronting legalboundary • seasonal fluctuation issue wasdeliberated upon in State of Florida,Department of Natural Resources vs OceanHotels, Inc. (State of Florida, 1974) as itrelated to locating the MHW line from whicha 50-foot setback was to be determined.Judge J. R. Knott, upon consideration of allthe options. rendered the following decision:

This eDUlt u,.,.fotw eoncludes th« the winterand most 1MHIwan/ mean high w.r.r linemust be selected as the boundary Iwtweenthe stat. and the upland owner. In so doingthe eourt has had to balanee the public poDeyfavoring private littoral ownership against thepublie poOey of holding the tideland in trustfor the people, whetw the preseNation of avitalpubHe right is seeured with but minimal.ffectupon the inte,.sts ofthe upland owner.

A 1966 California Court of Appealdecision rejected the application of acontinuously moving boundary in People vsKent Estate (State of California, 1966).However. no decision has been rendered asto what line to use (Collins and McGrath,1989). More recently, however. Collins andMcGrath (1989) report:

The Attomey General's Offiee in Califomialuis offetwd its informal opinion thilt, ifsquarely faeed with the issue, Califomiaeourts would follow the twasoning in theRorida ease and adopt the "winter and mostlandward line of mean high tide" as the legal

17

boundary between publie tidelands andprivate uplands ... (it should be undemoodthat such a boundary, while relatively stable,would not be permanently fixed but would b.ambulatory to the extent th.re occurs longterm aecretion or erosion).

Collins and McGrath also discussspecial issues such as shore and coastalhardening structures, artificially inducedaccretion of sand. etc., and their work ishighly recommended for further reading.

However, no formal legal adoption ofthe littoral MHW boundary has found nationwide acceptance. This is symptomatic ofmankind's tendency to give credence tocodes of anthropic conduct through thet.ws.fMan (published in local codes, statestatutes, and federal regulations, etc.) but toessentially ignore the environment and howit works through the LrNs .f NIItuIe(published in scientific papers and journals).Until a balance is more nearly achieved, weshall continue to exacerbate theenvironmental crisis that has befallen us all.The results of this paper provide for onesmall aspect of the behavior of nature anopportunity to achieve a balance betweenthe two sets of laws.

Long-Term Shoreline Changes

The initial motivation to investigatethis subject was the development of amethodology to analyze and assess longterm shoreline changes.· Quantitativebehavior of long·term shoreline change toassess coastal stability is best accomplishedusing actual historical surveys. In Florida, asmany surveys as possible are located for theperiod from about 1850 to present (aerialphotography is used where an historicalhiatus occurs), usually resulting in from 8 to14 points to represent the historical shorelineposition (Balsillie. 1985a, 1985b; Balsillieand Moore. 1985; Balsillie and others,1986). These data are assessed alongshoreat a spacing of approximately 300 m.Hence. historical change rate analysis


V••F

Rgure 12. Example of long-term shoreline change rate(solid lines) temporal analysis using seasonal shorelineshift data (dashed lines); see text for explanation.

Of the numerical methods available toanalyze such data, many can actuallymagnify the uncertainty and/or errorassociated with the final results of aninvolved computational approach. Cautionwith respect to this aspect of analysiscannot be over emphasized. In fact, thetopic is so important that a series ofstandard equations for assessing thepropagation of error in computing have beenprovided in the Appendix.

20001950

a: -6.25 m/YF c: -0.45 m/YFb: +110 m/YF d: +1.64 m/yr

magnitude that we must keep the number ofcomputational steps to a minimum in orderto minimize the propagation of error incomputing (bear in mind that in addition tothe tempol'lll analytical component a spatialcomponent remains, which further increasesanalytical computation).

The •bottom line" is that we need touse the most appropriate andcomputationally simple analyticalmethodology available. The mostappropriate statistical analytical tool isundoubtedly tIend analysis which alreadyincludes measures of determining theassociated error or variability. In addition,what we might learn and quantify aboutnature's own systematic variability can beused to our advantage both in terms ofassessing the acceptability of data, and asan analytical tool. Such is the usefulness ofhorizontal seasonal shoreline change.

An example of temporal analysis isillustrated in Figure 12 for a locality about2.7 kilometers south of a major inlet on theeast coast of Florida. Equation (1) wasevaluated using the appropriate wave data of

1900

Art""lal Nou.Is_•• 80".1Jetty Construction aeg_n~ ," ...

I ...Inlet Artlflcl_lIy Cut1 I ....

," a.b ' ...., ..... ---_-.I, ...

_ .. ," C ...... '... _- '!. I

~;#; • ~~_#- --- ...... d. .. -,--' ---- ,#

200

100

400

300

v

(m)

analyticalanalytical

tempol'llla spatial

requires both acomponent andcomponent.

The nature of historical shorelinelocation data is such that there is associatederror and variability. Surveying errorincludes inherent closure errors, error due toolder technologies, and non-adjustment errorfor more recent vertical and horizontal epochreadjustments. Survey nets established forcounty surveys may not precisely relate toadjacent county nets as they would in astate-wide net. Long-term sea levelchanges, though slight, affect long-termshoreline changes. These sources of errormay be called map-source errorsafter Demirpolat and others(1989), for which a magnitude of± 9 to 15 m may be appropriate(Demirpolat and others, 1989).Interpretive plotting of errors ofshoreline location (depending ondata concentration) on originalsurvey maps must be assumed,especially for older maps.Present digitizing technologyresults in an error of ± 3 to 4 m(Demirpolat and others, 1989).

Except for recenttechnologies, magnitudes oferrors for examples suggestedabove are not known withcertainty in the majority of cases.Even so, it can be envisioned thatthey are of sufficiently large

18

-- -- ~ SPECIAL PUBLICATION NO. 43

Thompson ('977) and tidal data fromBalsillie (' 987a). To the result. one standarddeviation was added to yield a predictedseasonal variability measure of 50.5 m.Starting with the most recent data andmoving back in time, regression techniquesare used to determine a trend line (solid linein Figure 12) about which plus and minusone-half the seasonal variability measure isaffixed in the vertical direction (dashed linesin Figure 12). The slope of the trend line ofthe time series is the rate of erosion oraccretion (a zero slope or horizontal linerepresents stability). Now the seasonalvariability measure becomes a valuable assettowards identifying spurious data or longterm change segments in shoreline behavior.For instance, if a point lies outside theseasonal variability envelop in the middle ofsegment d, one would conclude that eitherseasonal variability was extreme for thatyear (for which there are undoubtedly norecords) or the survey was madeimmediately following extreme event impact(either storm tide or wave event for whichthere are probably no records). In eithercase, we have reason to not include the datapoint in our analysis, since there aresufficient data points for the segment tosuggest a strong trend. Interactively, trendsin segment d at localities up- and downcoast can be used to verify such a trend inthe spatial component of the change rateanalysis.

We also can use historical informationabout the area to assist in analysis. Forinstance, we know that the inlet wasartificially constructed in 1951, and jettyconstruction began in 1953. Furthermore,artificial nourishment south of the inlet beganin 1974. Each of these events is coincidentwith a new episode in shoreline behavior,and may be verified with similar analyses atnearby up- and down-coast sites. Note thatthere are too few data points to quantify theshoreline change trend for segment c; eitheradditional data points are required orverification/readjustment from analyses at

19

nearby adjacent sites are required to assurequantification of representative shorelinechange.

Project Design andPedonnance Assessment

Both Iong-tenn changes and eJtt1'emeevent impacts have long been considered inassessing coastal development design.activities (until recently the former has byand-large been qualitative). In proper order,long-term changes should first bedetermined, followed by the design extremeevent impact. The first determination allowsfor prudent siting of the developmentactivity, and the second for responsiblestructural design solutions to withstandstorm tide, wave, and erosion event impacts.However, without knowledge of BellSOIIII1shoteIine shifts for a particular locality,uncertainty will be introduced into suchassessment. Following long-termdetermination of where the shore will be(e.g., say, a standard 30-year mortgageperiod) it would, for instance, be prudent toadjust the beach width of a giventopographic survey to its narrowest expectedseasonal dimension, then to apply extremeevent analyses. Considering the significantoutlay of resources for beach nourishmentprojects, it would seem appropriate toconsider seasonal shoreline variability both inproject design and in assessing performance.

The controversial issue of whethercoastal hardening structures (e.g., seawalls,bulkheads, revetments) promote the erosionof beaches fronting them, is one of complexproportions. Without being long-winded, theissue might finally be resolved by inspectinglong-term shoreline location data. Again,however, seasonal shoreline shifts wouldrequire quantification and application in theanalysis. At the very least, methodologydeveloped here would allow one todetermine if seasonal shoreline change wasof significant proportions that it should beconsidered in design applications. Using


known wave. tidal. and sedimentologicaldata it would be a straightforward task tocompile such results. particularly in Floridawhere the coast has been monumented.

CONCLUDING REMARKS

For much of our shoreline, seasonalshifts in shoreline position occur. While thephenomenon has been the subject ofconsiderable concern, no specificquantification has. until now, surfaced.

It has been noted earlier that someshorelines (e.g., east-west trending shores)apparently do not exhibit seasonal shifts.This may be due to storm wave impactsoccurring in groups for periods of less thanmonthly and/or due to climatic changeaffecting storm front azimuths relative toshoreline azimuths. Correlation might beattained by selecting most and least activemonthly averages, or by applying momentstatistics.

An historical study of Gulf of Mexicostorm wave and direct coastal impacts, asDolan and others (1988) conducted for theAtlantic Ocean off North Carolina, is needed.Results of such a study would shed light onthe regional behavior of east-west trendingshores of the central Gulf, and would also beapplicable to the more nearly north-southtrending shores of the lower Gulf coasts ofFlorida and Texas.

While the methodology for assessingaverage seasonal shoreline and beach widthvariability can be used for a variety ofimportant applications, the developmentspresented here are a first appraisal. Theintent of this work is to invoke interest in thesubject and to act as a plea for additionaldata on which to test existing predictivemethodology and/or develop more exactingtechnology. For instance, while this worktreats straight ocean-:fronting beachescomposed of sand, seasonal changes ofpocket beaches might be treated by

20

including seasonal wave approach anglechanges, and data for beaches composed ofsand and pebbles (i.e .• a very large standarddeviation) would help in understanding therole of the sedimentologic property element.

ACKNOWI.£DGEMENTS

Review of an earlier manuscriptleading to this paper provided significantguidance, and those comments andsuggestions from Paul T. O'Hargan, Joe W.Johnson, George M. Cole, Alan W.Niedoroda, and Gerald M. Ward are gratefullyacknowledged. James R. Allen and Ralph R.Clark, and William F. Tanner reviewed thepresent form of the paper and made severalvaluable suggestions. Special thanks arealso extended to Kenneth Campbell, EdLane,Jacqueline M. Lloyd, Frank Rupert, andThomas M. Scott of the Florida GeologicalSurvey for the many useful editorialcomments.

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APPENDIX: PROPAGA710N OFERRORS IN COMPunNG

(compiled from formulations in Barry, 1978)

Where R is the result of some numericaloperation (e.g., addition, subtraction,multiplication, division, power function,average, etc.) for measured quantities N

"N2

, N3

, ... ,Nn

, each with associatedmeasurement errors E1, E2, E3, .. ·,En,

respectively, then the total error Eror isapplied as:

where Etor is determined according to:

ADDITION OR SUBTRACTION

EIr1I

=0 Je: + E; + ~ + ... + E;

PRODUCT OR QUOTIENT

E.. =R (~r(~)·(~r ..... (;.)

28

AVERAGE

_ {~ + ~ + E; + ... + E;EItJt - ...!...-..:...-..---=:......---=..--_:,:,-,-

n

CONSTANT ERROR

where E = E, = E2 = E3 =... = En

EIrJI '" E {n

POWER

where (R + E,}m = (N1 + E1)m

EhJI '" E., 11,"""

ROOT

where (R + E,}'/m = (N, + E,)1/m

E - -1 E a.tl/~-lItJt - m 1 N;


OPEN-OCEAN WATER LEVEL DATUM PLANES:USE AND MISUSE IN COASTAL APPLICATIONS

by

James H" Balsillie, P. G. No. 167

ABSTRACT

Swanson (1974) notes that tidal datum planes".. , are planes of reference derived from the riseand fall of the oceanic tide", There are numerous tidal datum planes. Commonty used datumsin the United States include the planes of mean high., high w.", (MHHW), mean high WMer(MHW),""" tide__ (MTl),""""1wrJI (MSl).,.." low... (MlW), and",." /owei'low WI•• (MllW). Each datum is defined for a specific purpose or to help describe some tidalphenomenon. For instance, MHW high water datums have been specified by cartographers insome states (e.g., Florida) as a boundary of property ownership. low water datum planeshave been used as a chart datum because it is a conservative measure of water depth and,hence, provides a factor of safety in navigation. High water tidal stages have historically beenof importance because they identified when sailors should report for duty when "flood tide"conditions were favorable for ocean-going craft to leave port, safely navigate treacherous ebbtidal shoals, and put to sea. Not only do tidal datum specifications vary geographically basedon local to regional conditions for purposes of boundary delineation, cartographic planes, designof coastal structures, and land use designations, etc., but they have changed historically aswell. Moreover, given ongoing technological advancements (e.g., computer-related capabilitiesincluding the advent of the personal computer), how we approach these data numerically ishighly importan't from a data management viewpoint.

INTRODUC710N

Tide gauges are usually located in waterbodies connected to the oceans, such asestuaries and rivers, and may even be used torecord seiches such as those occurring in theGreat Lakes. Here, however, the concern iswith open ocean tides. Open ocean tidegauges are defined " ... as those gauges siteddirectly upon the open ocean nearshorewaters and SUbject to the influence of oceanprocesses, excluding those under theinfluence of inlet hydrodynamics .... (Balsillieand others, 1987a, 1987b, 1987c). Thelatter constraint in the definition is includedeven though it is difficult to determine theextent of influence from inlet to inlet.

Open ocean tidal datum applications in

29

Florida are problematic because there are alimited number of gauging stations torepresent astronomical tidal phenomena.While it has been standard practice tolinearly interpolate open ocean tidal datumsbetween gauges, such an approach is notrecommended should the gauges be spacedfurther apart than about 6.2 miles (Balsillieand others, 1987a). Of the 33 currentlyavailable open ocean gauges in Florida (Table1), only three pairs of stations meet thisconstraint. In fact, the average distancebetween Florida open ocean tide gauges is27.4 miles. Ostensibly, the 6.2-mileconstraint is recommended sinceconcurrently similar tidal stage datumelevations can vary significantly oversegments of the coastline when this distance


Table .1. Tidal Datums and Ranges for Open Coast Gauges of Coastal Rorida(Updated in 1992 after Balsilie. Carlen and Watters. 1987a, 1987b, 1987c).

OpenSt.t~ Plane MHHW MHW M1l. MLW MLLWCoordinates

station NameCoast MTR XGauge

Easting Northing(Feet) (Miles)

I. D.(Feet) (F..t)

(Ft. NOVO)

FLORIDA EAST COAST

Femanclina Beach 0061 362649.81 2287406.62 3.52 3.11 0.25 -2.61 -- 5]2 5.831little Tabot Island 0194 372355.76 2216450.20 3.60 3.30 0.55 -2.19 -2.35 5.49 19.753

JacksonviUe Beach 0291 377952.02 2163090.54 3.25 2.94 0.39 -2.17 -2.33 5.11 30.150

St. Augustine Beach 0587 417053.67 2008422.56 2.73 2.48 0.15 -2.17 -2.33 4.62 60.491

Daytona Beach 1020 498405.18 1779242.33 2.52 2.27 0.19 -1.88 -2.06 4.15 106.820Daytona Beach Shores 1120 511704.59 1749549.40 2.44 2.06 0.07 -1.89 -2.06 3.98 112.990Patrick Air Force Base 1727 628785.91 1421930.52 2.27 2.09 0.32 -1.45 -1.61 3.54 185.030

Eau Gallie Beach 1804 619782.34 1383121.82 2.25 2.07 0.33 -1.33 -1.49 3.40 191.810

Vera Beach 2105 707153.65 1213218.30 2.01 1.89 0.19 -1.51 -1.67 3.40 227.560

Lake Worth Pier 2670 815854.41 829171.49 1.93 1.87 0.47 .0.93 -1.10 2.80 304.910

HUlsboro Inlet 2862 800981.65 700015.89 1.79 1.73 0.43 .0.87 -1.03 2.60 329.700

Lauderdale-by-the-Sea 2899 797331.41 675151.18 1.99 1.93 0.63 .0.67 .0.83 2.60 334.580

North Miami Beach 3050 789219.52 581194.67 1.77 1.71 0.46 .0.79 .0.96 2.50 352.520Miami Beach (City Pier) 3170 785173.29 522409.95 1.76 1.67 0.42 .0.84 -1.00 2.51 363.780

NoTE; X is the shoreMne distance in miles south ot the center tine of St. MillY's EntranceChannel (origin: northing = 2317969.50 teel: easting = 366516.31 teet).

FLORIDA LOWER GULF COAST

Bay Port 7151 291286.83 1527111.33 2.31 1.88 0]0 .0.48 -0.97 2.36 4.472

Howard Pm 6904 241667.70 1389244.60 1.87 1.50 0.43 .0.64 -1.19 2.14 33.555

Clearwater 6724 231561.35 1325079.09 1.62 1.29 0.33 .0.64 -1.17 1.88 46.634

Indian Rocks Beach Pier 6623 224898.87 1295432.55 1.50 1.13 0.25 .0.63 -1.15 1.76 52.650

St. Petersburg Beach 6430 261046.14 1218243.36 1.52 1.16 0.42 .0.32 -0.83 1.48 69.560

Anna Maria 6243 268746.05 1150335.15 1.52 1.20 0.45 .0.29 -0.76 1.49 83.284

Venice Airport 5858 352475.83 995445.81 1.35 1.07 0.36 .0.35 -0.84 1.42 117.918

Captiva Island. South 5383 351707.10 179m.OO 1.52 1.27 0.42 .0.42 .0.94 1.69 163.464

Naples 5110 563431.54 652958.84 1.81 1.55 0.50 .0.54 -1.17 2.09 205.226

Marco Island 4967 589299.92 572441.43 1.96 1.71 0.56 -0.59 -1.20 2.30 222.015

NoTES: 1. X is Ihe shoretine distance in miles south of an arbitrary location in Hernando County, FL.(origin: northing = 1551271.53 leet; easting = 287952.53 leet).

2. State Plane Coordinates and distances are based on Zone 3 lranstonnalions Where necessalY.

flORIDA NORTHWEST PANHANDLE COAST

Dauphin Island 5180 472269.39 871380.81 0.87 0.82 0.26 .0.29 -0.34 1.11 -33.347

Gulf Shores 1269 467866.88 999712.52 1.20 1.13 0.50 {l.12 -0.18 1.25 -9.228

NaVlllTe Beach 9678 508373.97 1254261.65 1.20 1.13 0.50 -0.14 .0.21 1.27 39.737

Panama City Beach 9189 434604.55 1579274.67 1.25 1.18 0.54 -0.09 {l.14 1.27 104.489

st. Andrews Park 9141 414248.96 1610651.22 1.16 1.06 0.47 .0.12 {l.23 1.18 "1.489

Mexico Beach 8995 346061.53 1706517.15 1.06 1.00 0.41 .0.17 {l.22 1.17 134.479

Cape San Bias 8942 244076.07 1726862.58 1.01 0.99 0.30 -0.38 -0.38 1.37 162.615

Alligato r Point 8261 325491.24 2035385.12 1.73 1.49 0.53 -0.44 -1.02 1.93 232.302

Bald Point 8237 344903.70 2050145.99 2.09 1.76 0.62 .0.52 {l.98 2.28 238.633

NOTE: X is the shoreline distance in miles east 01 the AJabamalFlorida border(oligin: northing", 478050.00 feet; easting .. 1047360.00 feet).

QENERAL NOTES:1. Tidal datums are referenoed to NGVD of 1929.

2. Source of inlormation - Bureau 01 Survey and Mapping. Division 01 State Lands,Florida Department 01 EnVironmental Protection. lor the National Tidal Dalum Epoch 01 1960-1978.

3. MLLW =mean lower low water. MLW = mean low water. MTL .. mean tide level, Which along the open coast = MSl = mean sea level:MHW = mean high water: MHHW = mean higher high water: MTR = mean range of tide V·e.. MTR = MHW - MLW).

30


is exceeded. In addition, it was found thatlinear interpolation led to results that simplydo not reflect the natural behavior of coastalprocesses. Hence. in 1987, a non-linear nthorder polynomial numerical methodologywas introduced and utilized to determinequantitatively open ocean tidal datums for asignificant portion of Florida's ocean-frontingcoasts (Balsillie and others, 1987a, 1987b,1987c). Updated results (Balsillie andothers, 1998) are plotted in Figures 1, 2, and3.

This work is a companion paper to tidaldatums listings for Florida originallypublished by Balsillie and others (1987a,1987b, and 1987c) and updated by Balsillieand others (1998). It was determinednecessary to undertake the presentcompilation because of an increasing numberof misapplications of tidal datums appearingin the coastal engineering literature. Forexample, Foster (1989,1991), Foster and

Savage (1989a, 1989bl, and Schmidt andothers (19931 consistently used MHW astheir vertical reference from whichvolumetric beach changes were measured.Komar (1998) used NGVD (it is assumedthat this is NGVD of 1929, although such isnot stated) but stated that for his site NGVD.... is approximately equal to mean sea level'" •. Lee and others (1998) used NGVD at aNorth Carolina coastal location; they did notstate, however, how NGVD departs fromMSL at their site. These exemplifyinstances in which tidal datums referencingcan introduce significantly compoundederror. One illustrates other cases where noexplanation detailing how tidal datums areapplied is given, and one cannot be sure ifhe or she can have confidence in finalresults.

To one extent or another, misapplicationof tidal datums may be due to 8 lack ofunderstanding as to how they have been

North South

40050 100 150 200 250 300 350

Alongshore Distance (statute miles)

/..... I i I i I"I i I,i

i ~~ 1 .. j i! ~---. ,,,. " '"

I )

i I I i ~HW : i.--.;;

! Iii I i I ,

I I

i---- 'M:::iL ,:

I

I i I IT ~

i IIIIL.VVI iI I

! I MILW I !:

ir I I :I I

, I I , i !i i, I I I I

co~ 0.5

> 0com -0.5

E -1

.3 -1.5etlCl -2

-2.5

-3 o

4

_ 3.5

o 3>c.!) 2.5

Z 2

S 1.5

Figure 1. Relationship between open coast dial datums and National Geodetic Vertical Datumof 1929 for the Florida East Coast. Alongshore distance is measured from the center line ofSt. Mary's Entrance Channel proceeding south to Cape Rorida. (Updated in 1992 afterBalsillie and others, 1987a).

31


North South

200o 50 100 150


---,

I ! I!

... I MLVV'1

I ,I -...... i - lAI- ._-,, , -

! I! I I

! II

o

-1

-1.5

-2

-2.5

-3-50

4 -,-,-------,--------------

3.5 +-i------"----r--------~---~,0- 3 +1--------~----------------i> 2.5 -.-1-----.,__----' """--- _

! ':1.=~=~:EI,i::;;;;;~=~===::;e;:::=:==C1~11-~ MH:~

I ~V.g 0.51 , MSli

as>Q)W -0.5

E~.....aso

Figure 2. Relationship between open coast tidal datums and National Geodetic Vertical Datumof 1929 for the Florida Lower Gulf Coast. Alongshore distance is measured from north tosouth with the origin located at the north end of Pinellas County (i.e., north end of HoneymoonIsland) and terminating to the south at Caxambas Pass. (Updated in 1992 after Balsillie andothers, 1987b).

West East

250o 50 100 150 200


iI

I I

II

~

i h• W' , .. i ~

I~ I\fHVV I

,......., ......",.,. MdN IV''''~ -I

I- PtA I I W! ...............

"""'-iI

; II,

-0.5

-1

-1.5

-2

-2.5

-3-50

3.5-Cl 3>c.!J 2.5

Z 2

E.. 1.5

1

4

co~ 0.5

> 0Q)

wE~.....co

Cl

Figure 3. Relationship between open coast tidal datums and National Geodetic Vertical Datumof 1929 for the Northwest Panhandle Gulf Coast of Florida. Alongshore distance is measuredfrom the Florida-Alabama border east to Ochlockonee River Entrance. (Updated after Balsillieand others, 1987c).

32


established, and what they represent. Thefirst part of this work, therefore, discussesthe history of tidal datums determination anddefinition in U. S. coastal waters.

Guidance illustrating proper tidal datumsapplications for coastal scientists andengineers is available for important basictidal datums applications (e.g., Cole, 1983,1991, 1997; Pugh, 1987; Lyles and others,1988; Brown and others, 1995; Gorman andothers, 1998; Stumpf and Haines, 1998).For other specific cases it is absent. Verbalcommunications by a few professionalsreach only a small audience. Even then, thelatter often results in a blank stare, leavingthe instructor with the message that theexplanation was not comprehended by theinformant, that he or she has predeterminedthat it is not important, or that the informanthas already predetermined just what isproper. The author has, therefore, in thelatter portion of this work presented a seriesof selected examples and discussion abouttidal datums applications. At the outset, oneneeds to understand that the surveyingprofession, in large part, is concerned withthe management of error and variabilityassociated with horizontal and verticalcontrol. It is often the case that one is notconvinced by simple directive that there is aproper methodology, so evidenced by recentimproper uses of datum applications incoastal engineering works cited above. Thisoccurs because there isnothing to convinceone that the methodology is better or best atreducing error or variability. Therefore, theauthor has opted to present a series ofcommon improper tidal datums applicationsand to demonstrate, relative to the properapplication, just why, numerically, they areinappropriate.

INlETS/OUTlETS ANDTHE ASTRONOMICAL TIDE

The preceding definition of open oceantides excludes the influence of inlets (perhapsmore appropriately termed outlets after Carter,

33

1988. p. 470). Hence, exclusion of inletsmight be an oversight, particularly in view ofthe current inlet management effortundertaken by the State. At a most basiclevel, the classification of inlets is wellknown depending upon the effect ofastronomical tides relative to volume offluvial discharge (e.g., van de Kreeke, 1992).In fact, for many inlets, selection of theproper datum plane assists in providing aleast equivocal representative design waterreference level. Hence, a section on inletsas they relate to astronomical tides in Floridais herein developed.

WATER LEVEL DATUM PLANES

In endeavors concerning hydraulicphenomena with a free fluid surface, manypractitioners have lost perspective in selectionof the reference fluid plane across which forceelements propagate, in both the prototypicalsetting and the natural environment. Giventhis assertion, pemaps it would be appropriateto review the basics of historical developmentof tidal datum plane quantification that haswithstood the practicable tests of time.

The first recorded effort of geodeticleveling in the United States began in 1856p

57. During ensuing years surveying controlbecome better. As chronicled by Schomaker(1981), by the first quarter of this century:

Aher the previous period ofcom".rative/y short intetVlI1s betweenadjustments, 17 yean elapsed beforethe network was adjusted IIgain. In themeantime, it had become moreextensive and complex, and includedmany more SeHevei connections. TheGenersl Adjustment of 1929incorporllted 75, 159 /em of leveling inthe United Stlltes end, for the first time,31,565 km of leveling in Canadll. TheU. S. snd Canadian networks wereconnected by 24 ties between Calais,Me./Brunswick, New Brunswick; lindBlaine Wash.! Colebrook, BritishColumbill. A fixed elevation of zero


WIIS IIssigned to the points on melln selllevel determined lit the following 26 tidestlltions.

Father Point, Ouebec St. Augustine, Ra.Halifax, Nova Scotia Cedar Keys, Ra.Yarmouth, Nova Scotia Ptlns8cola, Ra.Portland, Me. Biloxi, Miss.Boston, Mass. Galveston, Tex.Perth Amboy, N.J.' San Diego, Calif.Atlantic City, N.J. San Pedro, Calif.Baltimore, Md. San Francisco, Calif.Annapolis, Md. Fort Stevens, Drs.Old Point Comfort, Va. Seattle, Wash.Norfolk, Va. Anacortes, Wash.Brunswick, Ga. Vancouver,

British ColumbiaFernandina, Ra. Prince Rupert,

British Columbia

'Thers was no tide station at PerthAmboy, but the elevation ofa bench marie atPelth Amboy was established by levelingfTom the tide station at Sandy Hook.

The 7929 adjustment provided thebasis for the definition of elevationsthroughout the nationalntItWork..itexistedin 7929, and the resulting datum is stillusedtoday.

The elevation adjustment of 1929 wasreferred to as the "Sea Level Datum of 1929",although it commonly became known as the"Mean Sea Level". In coastal work, however,there are two standard Design Water Levels(OWls) that are applied. These and theirdefinitions (GalVin, 1969) are:

Mean Water Level (MWL) - the time-averagedwater level in the presence of waves, and

Still Water Level (SWL) - the time-averagedwater level that would exist if the waves arestopped but the astronomical tide and stormsurge are maintained.

These water levels (i.e., MWL and SWL)apply for any length of time over which afield study or experiment is conducted, whileMean Sea Level and other tidal datums aredetermined as an average of measurementsmade over the 19-year National Tidal Datum

34

Epoch (i.e.. the Metonic cycle; shorter seriesare appropriately named, e.g., Monthly MeanSea Level, etc.). It was not until 1973 thatthe confusion over the Sea Level Datum or"Mean Sea Level" as it popularly came to beknown and Mean Water Level was resolvedby assigning the more appropriate name of•National Geodetic Vertical Datum of 1929·(NGVD) to replace ·Sea Level Datum of1929· . NGVD of 1929 is additionallydefined (Harris, 1981) as a fixed referenceadopted as a standard geodetic datum forelevations determined by leveling. It doesnot take into account the changing stands ofsea level. Because there are many variablesaffecting sea level, and because the geodeticdatum represents a best fit over a broadarea, the relationship between the geodeticdatum and local mean sea level is notconsistent from one location to another ineither time or space. For this reason NGVDshould not be confused with mean sea level,even though it has always been defined by amean sea level (Schomaker, 1981).

The various North American tidal datumplanes are defined (e.g., Marmer, 1951;Swanson, 1974; U. S. Department ofCommerce, 1976; Anonymous, 1978;Harris, 1981; Hicks, 1984) as follows:

National Tidal Datum Epoch - the specific 19year period adopted by the National OceanService as the official time segment overwhich tide observations are taken and reducedto obtain mean values for tidal datums. It isnecessary for standardization because ofperiodic and apparent secular trends in sealevel. It is reviewed annually for possiblerevision and must be actively considered forrevision every 25 years.

Mean Higher High Water (MHHW) - theaverage of the higher high water heights ofeach tidal day observed over the NationalTidal Datum Epoch.

Mean High Water (MHW) - the average of allthe high water heights observed over the


National Tidal Datum Epoch.

Mean Sea Level (MSL) - the arithmetic meanof hourly heights observed over the NationalTidal Datum Epoch. Shorter series arespecified in the name: e.g., monthly meansea level and yearly mean sea level.

Mean Tide Level (MTL) 4 a plane midwaybetween Mean High Water and Mean LowWater that may also be calculated as thearithmetic mean of Mean High Water andMean Low Water. MTL and MSL planesapproximate each other along the open coast(Swanson, 1974, p. 4).

Mean Low Water (MWL) - the average of allthe low water heights observed over theNational Tidal Datum Epoch.

Mean Lower Low Water (MLLW) - theaverage of the lower low water heights ofeach tidal day observed over the NationalTidal Datum Epoch.

Mean astronomical tide elevations exhibitcyclic seasonal variability (Marmer, 1951;Swanson, 1974; Harris, 1981) and areincluded in tide predictions. Marmer (1951)notes that seasonal variation in terms ofmonthly mean sea level for the U. S. can beas much as one foot. Based on the manyyears of monthly data, researchers (Marmer,1951; Harris, 1981) note slight variations inthe seasonal cycle from year4 to-year, butalso recognize the periodicity in peaks andtroughs over the years. For much of ourcoast, lower mean sea levels occur duringthe .winter months and higher mean sealevels during the fall. Harris (1981 )inspected the record to determine if stormand hurricane occurrence was in any wayresponsible for the seasonal change, butfound •... no systematic variability·. Galvin(1988) reports that seasonal mean sea levelchanges are not completely understood, butsuggests that there appears to be twoprimary causes for lower winter mean tidelevels for the U. S. east coast: 1) strong

35

northwest winter winds blow the wateraway from shore, and 2) water contracts asit cools. He notes that winds are moreimportant in shallow water where tidegauges are located, but that contractionbecomes important in deeper waters.Swanson (1974) also notes •... seasonalchanges resulting from changes in directbarometric pressure, steric levels, riverdischarge, and wind affect the monthlyvariability.· Cole (1997) notes that seasonalvariation in tides is usually attributed to twoharmonic constitutents: one with a period ofone year termed the solar annual tidalconstituent, and the other with a period ofsix months termed the solar semiannualconstituent. Some consider these to bemeteoroligical in nature, rather thanastronomic. However, because the rootcause of cyclic seasonal weather is thechanging declination of the sun, they shouldmore nearly be astronomical in origin.Harmonic analysis of the annual tidal recordcan easily determine the amplitude andphase of each of these constituents, therebyproviding a mathematical definition of theseasonal variation. (George M. Cole, personalcommunications.) Shorter-term changesoccur bi-weekly and monthly; longer-termchanges occur in the relative levels of landand sea that are of eustatic or isostaticorigins (e.g., Embleton, 1982). It isapparent, therefore, that there is naturalvariability associated with any averagerepresentation of tidal datums. Given thesenatural insensitivities associated withaverages, it is important that we do notexacerbate them through impropermanifestations of our own making whenapplying tidal datums as references.

At this point it is necessary to definecertain terms. If one is interested in merelyreferencing a vertical distance without arequirement of spatial comparability, theresult is termed a monergistie spp/icBtion.That is, the result of the application is goodonly for that particular location. If, however,in addition to a vertical datum, one has a


need that the. resulting application will havespatial comparability (i.e., it can becompared to the same application at anyother site), the result is a synetgisticapp/iclltion. We shall discuss this latter classof application first.

SYNERGISTIC TIDALDAroM PlANE APPUCATlONS

It has been widely recognized, asdemonstrated in the introduction to this paper,that selection of the proper tidal datumdepends upon the purpose to which it is to beapplied. The main purpose of this worK is todetennine the proper tidal datum for use incoastal science and engineering forreferencing littoral force and responseelements. Force elements includeastronomical tides, storm tides, nearshorecurrents, waves, etc. Response elementsinclude extreme event beach and coasterosion, foreshore slope changes, long-termshoreline changes, seasonal shorelinechanges, etc. It became apparent during thecourse of preparation of this paper thatdetermination of the proper datum plane isprobably best accomplished by discussingapplication/use examples.

EXTREME EVENT IMPACT

From the preceding description of tidaldatum planes we must, from the scientificperspective, be quite careful in selecting areference water level from which we definesuch response elements as beach and coasterosion due to extreme event impact, andsuch force elements as the peak combinedstonn tide accompanying extreme events that,in part, induces such erosion. As notedpreviously, water level datum planes includecertain insensitivities regardless of therigorous nature of statistical methods applied.It is necessary that we do not furtherexacerbate these insensitivities, creatingadditional variability and error throughselection of improper reference datums.

36

As an example, suppose that we areanalyzing and interpreting profile data todetermine volumetric erosion of sandybeaches and coasts due to extreme eventimpact. Further, let us select as our referencewater level datum Mean High Water, MHW.That is, we shall assess erosion volumesabove MHW to an upland point that must becarefully deliberated depending upon whetherthe coast was non-flooded (interpretations arenormally straightforward) or flooded and/orbreached (interpretations can be problematic)as discussed by Balsillie (1985b, 1986). Itmust be recognized that MHW can beassigned the status of a signature value for aparticular locality, representing its NationalTidal Datum Epoch. This assessment can belevied because MHW can change significantlyfrom locality-to-Iocality. For instance, inFlorida MHW varies from +3.12 feet MSL (or+3.36 feet NGVD; Balsillie and others, 1987a)along the northem portion of Nassau Countyon the Atlantic east coast, to +0.66 feet MSL(or +0.90 feet NGVD; Balsillie and others,1987c) along the westem portion?of FranklinCounty on the northwestem panhandle Gulf ofMexico coast of Florida. This embodies apotential maximum difference of almost 2.5feet in MHW elevation about the State ofFlorida. Suppose that for the above twoareas, profile conditions are comparable.Furthermore, suppose that extreme eventsembodying precisely the same magnitudesand characteristics producing identical forceelements impacted the two areas, resulting inidentical response elements, that is, the sameerosion volumes (i.e., the area above thedashed lines and below the solid lines ofFigure 4). If, however, we reference theerosion volumes to MHW (shaded areas) asillustrated in Figure 4, 8.12 cubic yards ofsand per foot are eroded above MHW alongthe northern portion of Amelia Island, 33 percent less than the 12.05cubic yards of sandper foot eroded above MHW along westernSt. George Island. It becomes quite clear,therefore, that erosion volumes around thestate cannot be compared using MHW, sincethe MHW base elevation is not only


LONGER-TERM BEACHRESPONSES

MHW is not the proper referencewater level datum to apply forerosion volumes. It also becomesapparent that it is not proper touse the datum for reference forsuch a force element as the peakcombined storm tide. Similarlogic results in the conclusionthat use of the MHHW, MLWi

and MLLW datum planes wouldalso be improper. It should, infact. be clear that MSL (or MTL)is the only tidal datum that is tobe used for reference.

--

eas. Ie Not1Mm AIMIIe I.-rd,......, County,lIIiW '" +3.12 rt MSL

Q. '" ~.12 yct3/M

••••,.II

'.... ~ ,,;:.,~ .

--i::~;';"';':"~"""::===-.,.....---"W----·~

•6

..

12

:; 2o -~-~

2 0t-----------.,;:.~=-~-- IISl -.-:.. 10 ~---,....-..,....,......j \;:/:.

! ~ \l~lj31W~~~~;:::;:;-~O~--------...:..::~i::::;~~!=-:-==~

·2

-:\20~....--=100~~-IO=- ........_eo*-......~~......-~ZO~~O~~ZOI..=-~40~~1ODimnCe tram 1M IISlInten:ePt ("'1)

Agare 4. &osion volumes. 0.. above MHW for identicalproIIes impacted by identical storm events. but withclfferent Ioc* MHW plaDes.

geographically variable, but significantly so.One will note further that, for other NorthAmerican MHW datums (see Table 2), theproblem can become even furtherexaggerated. In fact. it has beendemonstrated that MSL is the best datumfrom which to reference erosion volumes;"... at the seaward extremity of the poststorm profile, some material of the seawardsink (also including some degree of poststorm beach recovery) may reside aboveMSL (determined to be about 6% of theseaward sink volume from 245 analyzedprofile pairs), the analytical method is fairlyunbiased since it is applied equally to allprofiles investigated" (Balsillie, 1986).Seaward datums or depth of profile closureare not suitable references, if only becausesurvey response is slow compared to theresponse of subaqueous sand·sizedsediments in the energetic force element surfenvironment (e.g., Pugh, 1987; Lyles andothers, 1988).

It becomes apparent, therefore, that

It is clear why the MSL datumis the desired convention to applyfor extreme event impacts to whichforce and response elements areto be referenced. MSL datumshould also be applied to longer

term force and beach responses.Notwithstanding the need for a standardizedconvention already required for extreme eventimpact, there is sound reasoning that it appliesto longer·term scenarios, although, suchapplication is more subtle than for the extremeevent impact case. The preceding extremeevent impact scenario has dealt with physicalbeach and coast conditions of a sort whichtranscend certain physiographic limitations.That is, the energetics associated with stormsand hurricanes so exceed physical stabilityconstraints that individual gradients comprisingthe beach and coast (e.g., shoreface,foreshore slope, berm(s), dune or bluff stossslope; see Figure 5) do not, in themselves,impose limiting conditions. Under normallittoral force conditions, however,physiographic slope characteristics becomemore nearly a limiting condition. Perhaps themost important of these gradients is theforeshore slope, a subject that needs somediscussion prior to addressing two additionalsynergistic application/use examples,namely, seasonal beach changes and long·

37


Table 2. Selected North American Datums and Ranges Referenced to MSL (after Harris,1981 ).

I St.tion I MHHW I MHW I NGVD I MTL I MLW I MLLW I MTR IEastport, ME 9.32 8.88 -0.20 -0.10 ·9.01 -9.41 18.20

Portland, ME 4.87 4.45 -0.22 0.00 -4.46 -4.80 8.91

Boston, MA 5.16 4.72 -0.31 -0.15 -4.86 -5.19 9.58

Newport, AI 2.18 1.93 -0.23 +0.15 -1.69 -1.75 3.62

New London, CN 1.48 1.22 -0.43 -0.10 -1.34 -1.45 2.60

Bridgeport, CN 3.61 3.31 -0.54 -0.05 ·3.36 -3.52 6.70

Willets Point, NY 3.85 3.59 -0.58 -0.05 ·3.58 -3.78 7.10

New York, NY 2.51 2.19 -0.49 +0.05 -2.29 -2.42 4.50

Sandy Hook, NJ 2.66 2.33 -0.51 0.00 -2.34 -2.47 4.60

Breakwater Harbor, DE 2.46 2.04 -0.41 -0.05 ·2.08 -2.15 4.10

Reedy Point, DE 3.07 2.73 -0.35 -0.10 -2.77 -2.85 5.51

Baltimore, MD 0.74 0.51 -0.43 -0.03 -0.52 -0.64 1.03

Washington, DC 1.54 1.39 -0.54 0.00 -1.37 -1.42 2.76

Hampton Aoads, VA 1.41 1.22 -0.02 +0.03 -1.22 -1.26 2.44

Wilmington, NC 2.26 2.02 -0.38 +0.02 -2.24 -2.33 4.26

Charleston, SC 1.88 2.87 -0.05 +0.21 -2.67 -2.81 5.17

Savannah Aiver Entr. 3.77 3.38 -0.28 -0.15 -3.56 -3.70 6.94

FLORIDA Listed it T.bIe 1.

Mobile, AL 0.73 0.65 -0.05 -0.05 -0.62 -0.70 1.27

Galveston, TX 0.57 0.47 -0.10 -0.05 -0.44 -0.85 0.91

San Diego, CA 2.90 2.11 -0.21 -0.05 -2.09 -3.06 4.'-0

Los Angeles, CA 2.63 1.91 -0.08 0.00 -1.87 -2.82 3.80

San Francisco, CA 2.59 2.04 +0.06 +0.30 -1.93 -3.14 4.00

Cresent City, CA 3.22 2.56 -0.12 0.00 -2.49 -3.75 5.10

South Beach, OA 3.22 2.56 -0.49 +0.02 -3.09 -4.48 6.30

Seatle, WA 4.83 3.94 -0.35 0.00 -3.75 -6.48 7.60

NOTES:MfA = Mean range of tide; averege value of MfL is -0.01 feet MSL; average value of NGVD (1929) is -0.29 feet MSL;

these stations do not necessarily represent open coast gauging sites.

term beach changes.

The foreshore slope or beach face slope(Figure 5) is defined by the Shote ProtectionManual (U. S. Army, 1984) as "... that partof the shore lying between the crest of theseaward berm (or upper limit of wave washat high tide) and ordinary low water mark,that is ordinarily traversed by the uprush andbackwash of waves as tides rise and fall. "Komar (1976)elaborates further, stating thatthe foreshore slope "... is often nearly

38

synonymous with beach face but iscommonly more inclusive, containing alsosome of the beach profile below the bermwhich is normally exposed to the action ofthe wave swash.· The berm or beach bermis the "... nearly horizontal part of the beachor backshore formed by the deposit ofmaterial by wave action ... some beacheshave no berms, others have one or severa'"(U. S. Army, 1984). The berm andforeshore (or beach face) are separated atthe berm crest or berm edge.

CHUol ore

't~e

Botro'"

Neon'If,.e ~Q"e

Inshore or Shore foee

The slope of the foreshore tends toincrease with an increase in the grain size ofthe sediment ( U. S. Army, 1933; Bascom,1951; King, 1972). Dubois (1972) found aninverse relationship between grain size andforeshore slope where the foreshoresediments contain appreciable quantities ofheavy minerals. Sediment porosity andpermeability effects on the foreshore arediscussed by Savage (1958).

GeneraJly, foreshore slope increases withan increase in nearshore wave energy (allother factors held constant), and an inverserelationship is found when wave steepness isapplied (e.g., Bascom, 1951; Rector, 1954;King, 1972). For instance, steeper erodingwaves such as winter waves will result inflatter foreshore slopes, while longer (lesssteep) accretionaIY waves such as poststorm or summer waves produce steeperslopes. Average foreshore slope statisticsfor Florida are listed in Table 3. While thistreatment of foreshore slopes is general, it

39

Figure 5. Beach plCllfiIe related terms (from U. S. Amy, 1984).

"wffor

... th6t portion of the beach or coastthllt is, on a daily basis, subject to thecombined influence of high lind lowtides, lind Wave activity including waveupl1Jsh Of backwash. For purposes ofthis Chllpter, it includes thllt patt of thebeach between mean higher high wsfer(MHHW) and mean lower low wllter(MUW).


In Florida, the foreshore slope is defined(Chapter 168-33, Florida AdministrativeCode, State of Florida) as:

The slope of the foreshore, the steepestportion of the beach profile, is a useful designparameter since along with the berm elevationit determines beach width (U. S. Army, 1984,p. 4-86). As a response, element theforeshore is a function of force elements suchas astronomical tides, waves, currents, andproperty elements such as grain size.sediment porosity, and sediment massdensity.


Table 3_ Aorida Foreshore Slope Statistics by County and Survey.

County Survey Type Survey Date nAverage Standard

Slope Deviation

FLORIDA EAST COAST

Nassau Control Line Feb 1974 81 0.0359 0.0235Nassau Control Line Sep-Oct 1981 85 0.0474 0.0344Duval Control Line Mar 1974 68 0.0199 0.0178St. Johns Control Line Aug-Sep 1972 203 0.0523 0.0322St. Johns Control Line Feb-May 1984 210 0.0339 0.0384Flagler Control Line Jul-Aug 1972 99 0.1077 0.0273Volusia Control Line Apr-Jun 1972 227 0.0348 0.0306Brevard Control Line Sap-Nov 1972 217 0.0798 0.0413Brevard Control Line Aug 1985-Mar 1986 219 0.0719 0.0347Indian River Control Line Nov 1972 116 0.1163 0.0335Indian River Control Line 1986 119 0.1201 0.0793St. Lucie Control Line Jun 1972 115 0.1012 0.0358St. Lucie Condition Jan-Feb 1983 36 0.0919 0.0248Martin Control Line Oct-Nov 1971 115 0.0939 0.0378Martin Control Line Jan-Feb 1976 96 0.0867 0.0287Martin Control Line Feb-Apr 1982 104 0.0845 0.0301Palm Beach Control Line Nov 1974-Jan 1975 226 0.1011 0.0347Palm Beach Condition Aug 1978 24 0.1113 0.0334Broward Control Line 1976-1976 127 0.1099 0.0423Dade Condition Nov 1985-Feb 1986 28 0.1243 0.0328

Total n and Weighted Averages 2,515 0.0760 0.0359

FLORIDA LOWER GULF COAST

Pinellas Control Line Sep-Oct 1974 185 0.0747 0.0447Manatee Control Line Aug 1974 67 0.1009 0.0419

Manatee Control Line Aug 1986 67 0.0942 0.0377

Sarasota Control Line Jun-Aug 1974 181 0.0983 0.0375

Sarasota Condition Apr 1985 62 0.1051 0.0469

Charlotte Control Line May 1974 67 0.0757 0.0343

Charlotte Control Line Dec 1982 68 0.1127 0.0363

Lee Control Line Feb 1974 238 0.0843 0.0415

Lee Control Line May-Sep 1982 236 0.0980 0.0419

Collier Control Line Mar-Apr 1973 144 0.0796 0.0265

Collier Condition Sep 1984 40 0.0927 0.0277


FLORIDA NORTHWEST PANHANDLE COAST

Franklin Control Line May-Jul 1973 147 0.0933 0.0349

Franklin Control Line Jun-Sep 1981 244 0.1155 0.0472

Franklin Condition Oct 1982 31 0.0769 0.0322

Gulf Control Line Jul-Sep 1973 ~ 61 0.1032 0.0540

Gulf Condition Jan 1983 45 0.0785 0.0327

Bay Control Line Feb 1971-Feb 1973 141 0.0707 0.0255

Walton Control Line Oct 1973 130 0.0991 0.0699

Walton Control Line May 1981 130 0.1060 0.0578

Okaloosa Control Line Nov-Dec 1973 49 0.0650 0.0406

Escambia Control Line Jan-Feb 1974 213 0.0988 0.0429


Grand Total n and Weighted Average 5,089 0.0848 0.0391

I NOTE: n =0 number of profiles per survey.,

40

-- _.:.


-10-40-20

"'10:---- MSL

51.' tt.

Like Figure 4, Figure 6 is a simplification,

I

IIII

II

--...."""""""-----...'.!.'-------3,--,.0::;:----.;-' MSL.-------.l,,,

40 tt. -I

Balsillie, 1998). Here, however, beach widthis used since, compared to the others, itoffers the largest range in magnitudes.

Let us investigate such seasonal changesfor two localities with identical profileconditions and average seasonal MSLshoreline variations, but different MHWdatums. First, however, we need somerepresentative foreshore slope data. FromTable 3, let us select the average foreshoreslope of tan afs = 0.085 to represent awinter foreshore slope and a maximum oftan afs = 0.2 (i.e., 0.085 + 3 standarddeviations) to represent a summer foreshoreslope. The two cases, each with a summerand winter profile are illustrated in Figure 6.

.......--17.1 fL --""1

100 10 10

WINTER-.nil" = 0.085

CASE IIMHW =+4.0 fl. MSL

WINTERa. II.. '" 0.085

CASE IMHW =+2.5 ft. MSL

120

41

o-2

...-I

+2

+I+4~----~==.lllL-_-----....

+2 ' "'Il:""'""---MHW---l

"""---MIL

g +I~---_-~IIerm=!..-_--......= +4 ~---•: +2iii 0

·2..... ,,-+4

+2_ 0

""" ·2en::E ...i of•--

40 20 0Distance (feet)

Figure 6. Seasonal horizontal shorelne shift analysis.

will suffice for the following use/applicationexamples.

Seasonal Beach Changes

Beach changes due to extreme impactsfrom storms and hurricanes are considered tomore nearly represent isolated events. Thereare, however, beach changes that are morenearly episodic or cyclic. For instance,systematic beach changes through anastronomical tidal cycle (e.g., Strahler, 1964;Sonu and Russell, 1966; Schwartz, 1967),cut and fill associated with spring and neaptides (e.g., Shepard and LaFond, 1940;Inman and Fil/oux, 1960), and effects of seabreeze (e.g., Inman and Filloux, 1960;Pritchett, 1976), are well known. Of thepossible cyclic occurrences, however,perhaps the most pronouncedis that occurring on theseasonal scale. Using theabove prescribed rules, thefollowing scenarios can besuggested. During the winterseason, when incident stormwave activity is most active,high, steep waves result inshoreline recession. Normally,the berm is eroded and agentle foreshore slope isproduced. Sand removedfrom the beach is storedoffshore in one or morelongshore bars. During thesummerseason smallerwaveswith smaller wave steepnessvalues transport the sandstored in longshore bars backonshore, resulting in a widerbeach berm and steeperforeshore.

Seasonal beach changeshave been described in termsof sand volume changes,contour elevation changes,and horizontal shoreline shiftor beach width changes (see


albeit representative since the slopes anddistances presented are precise. First, let usfocus our attention on the CASE I localitywhere MHW = + 2.5 feet MSL. One willsee that if we utilize MSl as the referencedatum, the seasonal variability in beachwidth shifts by 40 feet. If, however, oneuses MHW as the reference datum, the shiftis 56.9 feet. The two values depart from.each other by 30 per cent. If, on one hand,the CASE I locality were to be singularlyassessed using the MHW reference planeshoreline, consistent results would emerge.If, on the other hand, one would wish torelate force elements (e.g., wave and tidecharacteristics) to the shoreline response,the use of MHW would pose problems (moreabout this later).

Similar assessment for the CASE /Ilocality (MHW = +4.0 feet MSl) results ina departure of the MHW - MSl shorelinechange of 40 per cent. As for CASE I,application results similarly apply.

Now let us compare the results ofshoreline shift at the two localities. MSlshoreline shifts would remain comparablefrom locale to locale, since they directlyrepresent both the tide base and surf base.MHW shoreline shifts, however, depart fromeach other by 15 per cent. Again, as withextreme event impact, MHW shoreline shiftscan not be compared from locality to locality(the same would hold true for other datumssuch as MHHW, MlW, MllW, etc.). In fact,if we evaluated seasonal beach changesvolumetrically, MHW or any of the other sitespecific variable datums would result inprecisely the same non-comparabilityproblems of the extreme event examplepreviously given.

Long-Tenn Beach Changes

long-term beach changes pose somehighly important concerns. Profile typesurveys provide a source of detailed coast.beach, and nearshore conditions. Such data

42

offer the opportunity for calculation ofvolumetric changes which, if sufficientalongshore profiles are surveyed, allows forsediment budget detenninations.

Profile surveying for temporal beachchanges, however, requires a monumentsystem maintained over many years. Forinstance, Florida's coastal monument systemhas been in place for some 26 years. Othersuch efforts occur on a site-specific basis. Formost of our coasts there is insufficientmonumentation, or it has not been in place forenough time to assure long-term records.Even the 26 years for the Florida program isnot lengthy. Moreover, early surveysmeasured shoreline positions. In order toobtain volumetrics from shoreline positiondata, horizontal shoreline change (.boX) andvolumetric change (.boV) have been related inthe ShIIte PtrIteetion MaIlUlll (U. S. Army,1984) according to:

where c is a relating coefficient. If not verycarefully applied, such an approach canproduce highly misleading results (Balsillie,1993a).

long-term shoreline change rate data forFlorida (Balsillie and Moore, 1985; Balsillie,1985f, 1985g; Balsillie, and others, 1986)are determined from shoreline position datafor the period from about 1850 to present.Commonly up to about a dozen data pointsare available from which to conduct temporalanalyses.

By way of example, let us inspect theapplication of MHW as the reference datumplane for determination of horizontalshoreline change. let us select an averageMHW value of + 1.7 feet MSl and amaximum value for MHW of + 3.0 feet MSl,both of which are representative of Floridaconditions (from Table 1). Using these data,three cases of combinations of MHW andforeshore slope values are illustrated in

-- .... --SPECIAL PUBLICATION NO. 43

5040302010o

- .......::----MSl (SURF BASE) -----4

-10

,,III I

:.. 10.2 ft.:

processes.

THE SURF BASE

The preceding application/use examples,while rigorously identifying inconsistenciesresulting from the use of extreme datumplanes for coastal science and engineeringpurposes, have not specifically addressedcoastal processes in terms of the forces thatcause beach responses.

In order to understand how the sillbaseapplies, one needs a basic understanding ofhow wave statistics are derived and applied.At a given water depth a wore train is anear-periodic set of waves with acharacteristic average wave crest height H,wave length L. period T, and having a

·20

CASE 3,-"ala so 0.016

·30

4 r ---------r-------------.3

o

CASE 1

Berm 'a"a,. '" 0.0852 r--.:;,;;,;,;,;,;"..--.....~---~ WfW .. ~1.7 " ---------1

2 ~---..:::;...:;"".;,,;;~"!_-~-_4_I , MHW = +1.1 It-------.j

I I CASE 2I ,

:--'''' ft~ lana,. = 0.2; 0 "~l:----MSL (StR: BASE) ----i,~!.--2S.6"_• I

IIII

.....I~_- .... "" +3.0 It _+- ~

o

·1

2

3

1

... HI

·2

·1

·2

Figure 7. Lon~tenn shorelne shift analysis.

Figure 7. Additional datacould have been selectedas well as additionalcombinations; however.the three illustratedcases will more thansuffice for our purposes.The profiles of the threeexamples are plotted sothat the MSL (Surf Base)intercepts define theorigins of the plots thatthey may be compared.Horizontal differences ofMHW intercept locationsare identified by verticaldashed lines. Deviationsrange from 10.2 to 25.6feet, all of which aresignificant illustrating theinappropriate nature ofusing MHW for such apurpose. Again, as withextreme event impactand seasonal shorelinechange, MHW shorelineshifts are not comparablefrom locality to locality(the same would holdtrue for other datumssuch as MHHW, MLW, MLLW, etc.). In fact,if we evaluated long-term beach changesvolumetrically, MHW or any of the other sitespecific extremal variable datums wouldresult in precisely the same noncomparability problems of the extreme eventand seasonal shoreline shift examplespreviously given.

We can approach the subject from adifferent perspective. If MSL is not used asa reference Surf Base plane, then whatshould be used? If one selects an extremetidal datum plane such as MHW, does itrepresent a base to which aktological forceand response elements can be based? Doesit have spatial continuity? Is it applied in aconceptually correct sense? All of thesequestions need be directed toward coastal

43

-- _..FLORIDA GEOLOGICAL SURVEY

specific direction of propagation. Wherewater depths are such that waves remainrelatively stable, the wave record (such asthat measured by a wave gauge) willrepresent all wave trains (i.e., multiple trains)passing the gauge. Multiple wave trainheight and period measurements are termedthe speetTal wave reconl or wave field.Shote-brea/dng waves, however, do notconform to spectral wave statistics. Thisoccurs because in nearshore waters, wavesare ultimately limited by water depthaccording to db =' , .28 Hb (McCowan,1894; Balsillie, 1983a; Balsillie, 1999b;Balsillie and Tanner, 1999) where Hb is thewave crest height at shore-breaking and dbis the water depth where the wave breaks.Hence, shore-breaking waves engendermoment wave statistics for single w~e

trains since a wave train with larger waveswill break further offshore than one withsmaller waves.

It follows, then, that moment wavestatistics vary depending upon whether theyrepresent the spectral wave record or singleshore-breaking wave trains. The mostcommonly applied nearshore wave heightstatistics are the average wave height H,root-mean-square wave height Hrms'significant wave height Hs (average of thehighest 30 per cent waves of record). H10(average of the highest 10 per cent wavesofrecord) , and H1 (average of the highest 1per cent waves). Each of these momentmeasures is applied in the design of coastalengineering solutions by defined prescription.Relating moment measures for spectral andshore-breaking wave cases are listed in Table4 to illustrate the variability of relatingcoeffic ients.

Let us look at an example of tideconditions to which we might superimposecertain wave conditions. Figure 8 illustrates6 days of an astronomical tide record.Suppose one inspects the case where MHWand Hs are, for whatever reason(s). selectedfor use. From the plots, each peak of the

44

tide might be considered to be maintained,say. for 1/2 to 1 hour. Doubling this value,since two highs occur in each tidal day forthe semidurnal tide, then MHW is actuallymaintained for about 4 to 8 per cent of thetime (e.g., 14 and 28 days a year).Superimposed upon MHW is the significantwave height which, by definition, neglects70 per cent of the wave record (assumingthat Hs adequately includes any significantzero wave energy component; Balsillie,, 993b). Clearly, such an application wouldbe inappropriate for one applying such forceelements to annual or long-term conditions.Unfortunately, however, such misapplications, of which this is just one example, arecommonplace. On the other hand, such anapplication might have more viableapplication if it included a storm surge (i.e.,peak combined storm tide minus theastronomical tide) to represent the peakcombined storm tide and attendant waveactivity which occurred coincident with thepeak astronomical tide. This latter case,however, has application only to identify aconservative design elevation for a structure(e.g., perhaps a pier) which is a monergistictidal datums application, but certainly not toprofile response which constitutes asynergistic application.

Previously discussed use/applicationexamples have already led to the eliminationof extreme datum planes (i.e., MHHW,MWH, MLW, MLLW) as has the precedingexample, and MSL and NGVD remain forconsideration. The NGVD reference is not,of course, a tidal datum. It is rather, for allpractical purposes a geodetic datum forcomputational reference, that although foropen-coast gauges has a departure generallyless than 0.5 of a foot from MSL for Florida,the long·term primary departure of MSL andNGVD is subject to influences of sea levelrise or fall (shorteHerm natural deviationshave been discussed above). Hence, itshould not be utilized as a datum,particularly where global data are involved(i.e., where the non-tidal vertical reference


Table 4. Moment Wave Height Statistical Relationships (after Balsllie and Carter. 19848.1984b).

Portion of Wave Record Spectral Relationships Shore.Breaking RelationshipsConsidered

All Waves Average Wave Average BreakerHeight "H Height = It

All Waves H= 0.885 Hrms It = 0.98 ft-

Highest 30% H= O. 625 ~ It = O. 813 Hbs

Highest 10% H =- O. 493 f(o ~ = O. 73 ~'O

Highest 1% H=- 0.375 f( ~ = O. 637 ,""

Definitions:

Average Wave Root-M~Square WaveN W ~ '= significant

Height = H= 1 ~ ~ Height =-Hrms " -~f1 wsve heightN. N .,

NOTE: Formulas apply to both H and H~ H•• H,o. and H, are calculatedusing the form of the equation as for the average wave height.

represents a conceptual plane not locatedand/or not calculated such that it is notnecessarily comparable to NGVD). Theremaining tidal datum is, then, MSL. Otherthan its identification by elimination of otherdatums, there are strong motivating reasonswhy MSL is the proper tidal datum referenceto use when dealing with coastal processes(i.e., force and response elements). As wehave already learned, principal forceelements include astronomical tides, stormtides, and waves. Astronomical tides are, bydefinition, already accounted for when usingMSL, and storm tides are extreme eventsthough accounted for as described in thepreceding section. Waves. however,constitute an ubiquitous phenomenon nearconstant in nearshore coastal waters (exceptfor coasts with a substantial zero waveenergy component).

45

Therefore, by the process ofelimination MSL is defined as the sud base(it is also the tide base, not to be confusedwith the concept of the wave base). Uponinspection of Figures 1, 2, and 3, it is readilyapparent that MSL, like the other datums,has variability. Why, then, would we selectit as a convention for reference? Waterlevels are not globally coincident in thevertical sense for very real reasons.However, MSL is a measure representativeof the entire distribution of the metonicastronomical tide, and is the only one of thetidal datums that has statistical continuityand comparability of results from place toplace. Noting that for open coastal watersMSL is equivalent to MTL (Swanson, 1974,p.4), then the MTL measure remains torepresent the central tendency of the tidedistribution since metonic measures of highsand lows are used in its determination. The


one should view it in thestatistical sense where we knowmore about its central tendencythan we do about the behavior ofthe lower foreshore (corresponding to MLW or MLLW) orhigher foreshore (correspondingto MHW or MHHW). When weapproach the extremes of theslope, exceptions due tophysiographic irregularities canoccur. Hence, one needs to viewthe surf base - foreshore slopeintersection as a focal point aboutwhich the foreshore rotates. Inthis context, the focal point isdirectly related to incoming forceelements. Furthermore, it isconceptually not subject tovariations to which the upper andlower parts of the foreshore aresubject, since it is an origin bothcommon and comparable to thefocal point at other localities.

From a slightly differentviewpoint, one argument

Figure 8. SelDiciumai tide CUlVes for 6 tidal _ys (froID proffered by a colleague whoManner, 1951). took the "devit's advocate"

position, is that the MHWintercept represents the most

stable portion of the foreshore slope. Whilethis may appear appropriate to the layman,from the geological perspective it is not. Itis, in fact, the least stable in terms ofrepresenting a normal slope. The moststable position of the foreshore is probably atthe MSL intercept (Le., relative to othersubmerged portions of the profile) since it isreflective of average, ongoing force elementsto which it is modified as a responseelement. By comparison, the foreshore inthe vicinity of the MHW or MHHW interceptsis affected only during high tide stages andcan be reflective of extremal impacts (e.g.,storm wave events). Extreme impactsaffecting the MHW foreshore are likely toresult in relict features which persist untilcontinual average force conditions finally

issue becomes particularly poignant frominspection of Figure 1 where the behavior oflow waters (i.e., MLW and MLLW) and highwaters (i.e., MHW and MHHW) are anythingbut symmetrical in their relationship to MSL(or MTL), signifying a need for an averagesurf base measure. Statistically extremeaverage point measures providing numericalvalues of upper (i.e., MHW and MHHW) andlower (i.e., MLW and MLLW) tidal datumsare robustly founded. Correspondingextremes of such physiographic features asthe foreshore may not be so robustlyfounded, since its formation andmaintenance has not been rigorously definedin terms of forces and responses (e.g., Krausand others, 1991, p. 3). Given the mannerin which we currently define the foreshore,

46


return the upper portions of the slope tonormal slope status.

What point estimator of waveparameters, representing the appropriateforce element, does one subscribe for anextreme average measure of theastronomical tide, say for MHW? One doesnot apply such point estimators for wavetransformation synergistic applications,because none would be appropriate. Hence,unless an average sea level (MSl or MTL) iscombined with an average wave height, oneis mixing •apples and oranges·. It isimperative when undertaking such a task,we render the task to simplest terms. Forinstance, when transforming waves to thepoint of shore-breaking, including any wavereformation and rebreaking, the wavesshould be expressed as an average waveheight or, perhaps, root-mean-square waveheight since these measures include allwaves of record. Do not use the significantwave height, average of the highest 10 percent of heights, average of the highest 1 percent of wave heights, etc. Whether or not asignificant zero wave energy component isincluded depends on the purpose of the work(Balsillie, 1993b). Any conversion of theaverage wave height to extreme wave heightmeasures of Table 4, say for designpurposes, is accomplished by converting theaverage measure, but only after wavetransformation as an average height hasoccurred. Kraus and others (1991) note theimportance of the average wave height andtout its use to be the •... •Rosetta stone·for conversion .... , no less important is theproper application of the surf base (MSL)which becomes the Rosetta Stone forreferencing tide and wave phenomena.Another good reason for using averagesthroughout any numerical transformationprocess is because one is often unable todetermine from published results if thetransformation methodology is trulycommutative.

MSL is, therefore, the only datum

47

plane that is relevant to the surf base. For arelatively short experiment or field study,MWL or SWL references are suitable torepresent the time frame of the experimentor study. Such referenced results, however,may not be comparable to results referencedto MSL at other localities. For this reason,all applicable datums ... MSL, MWl, andSWL, where known ... collectively termedDesign Water Levels (OWLs), should beprovided in documentation of results.

SEA LEVB. RISE

So far, we have but in passingmentioned the effects of sea level rise,recalling that the primary difference betweenNGVD and MSL (or MTL) is sea level rise. Inan historical context, the effect of sea levelrise on the current metonic period has. thusfar, been insignificant from a surveyingperspective. Its future effect. however.remains controversial (e.g., Titus and Barth(1984) and Titus (1987) versus Michaels(1992), to mention but only severalpublished works among a vast number onthe subject). Other work indicates details ofsea level reversals or pulses (Tanner, 1992,1993), also characterized as crescendos(Fairbridge, 1989).

There are certain applications wheretemporal specifications of sea level rise areof potential consequence. Hence, from adata management and processing viewpoint,it becomes in certain cases necessary tostart with NGVD and calculate the relativedate-certain sea level rise component. Theresult, of course, becomes the date-certainMSl (or MTL). For the 1960·1978 NationalTidal Datum Epoch, the following relationshipassessed in British Imperial units is posited:

MSLD ~ NGVO + c (D - 1969.5)

where MSLo is the date-certain value forMSl (or MTL), C = 0.0060for Florida's eastCoast), c = 0.0064 for Florida's Lower GulfCoast, and c = 0.0069 for the Florida


Panhandle Gulf Coast (Balsillie and others,1987a, 1987b, and 1987c, respectively),and 0 is the survey date. Please note thatthe value of c changes with time andlocation; the current value of c for aparticular coast is a representative regressionvalue.

MONERGISnc TIDAL DA TUMPLANE APPUCAnONS

Thus far, the above application/useexamples have been described as synergistic. That is, horizontal shoreline shift andvolumetric change results are referenced toa datum so that they can be comparedspatially within a North American or globalcontext. The scientific need to do so hasbeen robustly demonstrated. Even more,considerable analytical work is required todetermine such synergistic results whichcannot be simply recalculated to anotherdatum.

As described in the introduction thereare, however, other quite different conceptual applications of astronomical tidal datumplanes. Some of these are not necessarilybound by the need for a spatial tidal datumconvention. These are described asmonergistic applications. The purpose, here,is to demonstrate several such examples.

DESIGN SOFFIT ELEVATIONCALCULATIONS

"Soffit elevation" is a generic termmeaning the elevation to the underside of thelowest supporting structural member excluding the piling foundation, say, for a pier orsingle- or muti-family dwelling. Suchelevations are calculated for extremeelevations associated with the impact ofextreme events (i. e., storms and hurricanes).The goal is to raise the structure to anelevation so that it is above the destructivehydraulic force elements which will passbelow the soffit and through the pilingfoundation. For a pier, for instance, a peak

48

combined storm tide (super-elevated waterlevel including contributions of wind stress,barometric pressure decrease, dynamic wavesetup and astronomical tides) correspondingto a 50-year return period elevation isnormally used for design calculations.Superimposed upon the storm tide still waterlevel is a design wave height, normally abreaking wave height corresponding to Hb1 0or Hb1 . As previously noted, where a waveshore-breaks is dependent on the waterdepth which, in turn, is dependent on patterns of sediment redistribution occurringduring event impact. Sediment redistributionis largely a function of offshore sedimenttransport and longshore bar formation(Balsillie, 1982a, 1982b, 1983a, 1983b,1983c, 1984a, 1984b, 1984c, 1985a,1985b, 1985c, 1985d, 1985e, 1986;Balsillie and Carter, 1984a, 1984b, etc.). Anexample is illustrated in Figure 9.

Such design work calculations aresite-specific because results will beinfluenced by the pre-impact site-specificprofile configuration. There is no intention,nor at this time a need to compare suchresults to other localities. Should such anapplication need arise (e.g., a generalizedmodeling effort or an accounting need toassure consistency in design application(s)),then the reference base should be MSL.However, such transformations to otherdatums can be easily accomplished,compared to much more involved recalculation of synergistic data (Le., volumesor horizontal distances).

EROSION DEPTH/SCOUR CALCULATIONS

Site-specific design work such asminimum pile embedment requiresknowledge of the design surface elevation.This elevation necessarily includes erosiondepth (e.g., longshore bar trough elevation orbeach erosion elevation), additional scourcaused by the pile, and sedimentliquefaction. In essence these designelevation calculations are treated in the samemanner as design soffit elevation


DamagedSection --t-- Destroyed Section --o-i

40

·10

~

.2 10

iiii

Q 30>

~ 20 ~~......;..F,;;;,LA;.,;,G~LE;;.;R~B.;;;E-..;A~C..;.;;H...;,P..;IE;;;.;R;.;..........L.__~~~~_~~~__--.L

t _.-' -' - .=~-:.:'=.-=~.:-:~;:. :::.::.:'" ._ ::-.::::::::::: ::.::-.:'.::' :.:-:.:.:::::.l 1I:__ ~"":;i.;;:~_-:--':":::'::":'" -... ST SWL,....---------...,,!

r---::::'-'- '-'-'- .-.o Po t Storm -=-;;.-~.-::-:-.-r-:-::_-=.-~.'-"_.....-_-.-"'''''.''=--.--.---.---.--.--.-_-.-_-.-_-._----.---~B8-r-C=-r-e-.tcEn:::--v-.Iope~--Is- -'- .-.-.~-Prof" .-._._.-._._-_. - ._._.- '-'-'_. - '-'-'-'

Pre-Storm Profle ._. -. -- _. -".,7' _.-. ._.

Bar 'D'ough EnveIope---"'" - .-.

·20 L...--:.2~0~O:--...L...-."':'1::00;O-........--:!:0--"--':":100b;----'--::2:*OO:;:-~-300=.---..L...---:400;.-L...--:500=~.L-.......:600lur--'

Distance from NGVD Shotelne (feet)

Agure 9. Actual damage to the Ragler Beach Pier from the Thanksgiving Holiday Storm of1984 (Balsilf.e. 1985c) used to test the Multiple Shore-Breaking Wave TransformationComputer Model for predicting wave behavior. longshore bar formation. and beachlcoasterosion (after Balsillie. 1985b).

calculations.

SEASONAL HIGH WATEA CALCULAnONS

In addtion to short-term erosiveimpacts due to extreme events, our coastsare subject to long-term changes. In 1972,the State of Florida incorporatedconsideration of stormlhurricane erosion inaffixing the location of Coastal ConstructionSetback Lines. In 1978, it adopted a posturein which quantitative extreme event erosionbecame the primary means by which CoastalConstruction Control Lines were located. Itwas not until 1984, however, that long-termerosion was officially recognized by theState of Florida (Balsillie and Moore, 1985;Balsillie, State of Florida (Balsillie and Moore,1985; Balsillie,1985f; 1985g; Balsillie andothers, 1986; etc.,). In 1985, the GrowthManagement Amendment requiredassessment of erosion at any coastal site forwhich a permit application was tendered tobe assessed for a 30-year period.Associated with 30-year long-term erosionprojections is the local Seasonal High Water(SHW) defined as ... the line formed by the

intersection of the rising shore and theelevation of 150 percent of the local meantidal range above local mean high water ...(para. 161.053(6)(a) 1, F. S.). That is:

SHW = (1.5 MRT) + MHW

in which MRT is the mean range of tide(commonly referred to as the mean tiderange). One might assume that the 30-yearerosion projection is to be assessed at theSHW elevation. This is simply not true and,in fact, as we have seen earlier would be amisapplication leading to spatial discontinuityintroducing computational error (Balsillie andMoore, 1985). Rather, the erosionprojection needs to be assessed at MSL.The, required methodology specified by rule(para. 16B-33.024(3Hhl, F. A. C.,republished as State of Florida, 1992, 62B33.024(3)(h)1., F. A. C.) specifies NGVD asthe assessment elevation. The original rule,however, was written before compilation ofdatum elevations, foreshore slope, and sealevel rise information for the State.Subsequent work IBalsillie, Carlen, and

49


Watters. 1987a. 1987b, 1987c) has remediedthe situation, and the rule needs to bereassessed. Following is an alternative forconsideration.

from the figures that only the upper eastcoast is significantly affected by the SHW,attesting to the low impact figure of Curtisand others (, 985).

BEACH-COAST NICKPOINT aEVAnON BOUNDARY OF PUBUC VERSUS PRIVATEPROPERTY OWNERSHIP

~--- IISL---

--I- BNdI .....,..-+-1.._-

The boundary between private (i.e.,upland) and public (i.e., seaward) beachownership is normally fixed by somecommonly applied tidal datum. For most ofthe U. S. this boundary is determined by theplane of MHW which when it intersects thebeach or cOast forms the line of mean highwater. However, unlike other riparianownership determinations (i. e., fluvial,lacustrine and estuarine), littoral propertiesmust, in addition, contend with significantwave activity that seasonally varies. Hence,ocean-fronting beaches all too oftenexperience cyclic seasonal width changes ofa magnitUde long recognized as problematicin affixing an equitable boundary (Nunez,1966; Johnson, 1971; O'Brien, 1982;Graber and Thompson, 1985; Collins andMcGrath, 1989).

••

---------JI:

)"

-"-_ .. - ----DI.ne or IIIuff

......---Coat

z·f 10 EAST COAS~

j .. .

i 1: LOWER GULF COAST

I

00 0.1 0.2 0.3 0.4 0.5 0.8 0.7 0.8 0.9EJrc....1Ce~.P

Figure 10. Beach/coast niekpoint elevations for Aorida.

In reality, Seasonal High Water is amisnomer. First, the components necessaryfor computation are metonically derived (i.e.,19-year averages). Second, the results havenot been demonstrated to represent seasonalvariation in astronomical tide behavior.Third, it has been demonstrated that uponapplication, only about 13% to 15% ofundeveloped beach property in Florida wouldbe affected by the SHW application (Curtisand others, 1985).

An alternative consideration for suchan application, and others, is thebeach/coast nickpoint elevation. Thenickpoint represents the point where thebeach intersects the coast, normallyidentified as the base of a dune or bluff.Generation and maintenance of the nickpointis primarily a function of direct extremeevent impact. Theseelevations for Florida areprobabilisticallyinvestigated; the resultsare plotted in Figure 10.Median (i.e., 50thpercentile) nickpoint felevations, Ne, for Florida ~

are as follows: 1) East :.Coast: +7.15 feet NGVD(1929), 2) Lower GulfCoast: + 5.65 feet NGVD(1929), and 3) PanhandleGulf Coast: +6.45 feetNGVD (1929).

The relationshipbetween nickpointelevations and SHWelevations for Florida isillustrated in Figures 11,12. and 13. It is apparent

50


PALMBEACH

BREVARD

SHW

---------~ -- ----- ------------ -----

MedlIn Ne

ij 5w

----

00 100 . 200 300 400~.(......)

Figure 11. eom,.rison of Season... High Wmer (SHW) and MecillnBeach/Coast Nickpoint Bevatioa (NJ for the RoridII East eo.st.

~u.

iI

I~ 0 I ld ~ EI, ~ i~:l~LRE

e. ill r J I 5~10"" .

~ ..,.,.- ....... N.

S "- _i 5 ---------------------------

iii

SHWo'-'-l_1_~~'-'-L...L...L...L...~l-1-L...L...L...L...............L.J

o 100 200

DIst8nce (min)

Figure 12. eom,.rison of Seasoal High Wider(SHW) and MecIiIn Beach/Coast Nickpoint Bevnon(N.) for the RoridII Lower Gulf CoIIst.

51

200o

IoNIc c I~! ~2 I!

c

i BAY GU.F FRAt«LJNC1 ;en

~III

- -L .... Ne

------------------ -----------_ .. _-------- SHW~ .--/--- I

.Io

j 5

I100

D6stIInce ("...)

Figure 13. eom,.rison of Seasonal High Water (SHW) andMecian Beach/Coast Nickpoint 8evation (Ne) for the AoridaPanhancle Gulf COiIst.


Many investigators have suggestedthat the legal boundary for ocean.frontingbeaches should not be continuously movingwith the seasonal changes, but should bethe most landward or "winter" line of meanhigh water (Nunez. 1966). Selection of the"winter" MHW line would be the mostpractical to locate and would be the mostprotective of public interest by maintainingmaximum public access to the shore (Collinsand McGrath. 1989),

In Florida, the ocean.fronting legalboundary - seasonal fluctuation issue wasdeliberated upon in State of Florida,Department of Natural Resources vs OceanHotel, Inc. (State of Florida, 1974) as it relatedto locating the MHW line from which a 50-footsetback was to be required. Judge J. R. Knottrendered the following decision:

This couff therefore concludesthllt the winter lind mostIlIndwllrd mean high wllter linemust be selected liS theboundllry between the stllte lUJdthe up/lind owner. In so doingthe couff hilS hlld to bMlInce thepublic policy fllvoring prlvlltelittorlll ownership IIgainst thepublic policy of holding thetidelllnd in trust for the people,where the preservation of II vitalpublic right is secured with butminimM effect upon the interestsof the uplllnd owner.

A 1966 California Court of Appealsdecision rejected the application at acontinuously moving boundary in People vsKent Estate. However, no decision has beenrendered as to what line to use (Collins andMcGrath, 1989). More recently, Collins andMcGrath (1989) report:

The Attomey Generlll's Office inClllifomill hilS offered its informlllopinion thllt, if squllrely fllcedwith the issue, ClIlifomill courtswould follow the rellsoning in the

52

Floridll ClIse lind IIdopt the"winter lind most Ilmdwllrd lineof melln high tide" liS the leglllboundllry between publictideJlInds lind privllte uplllnds ...(it should be understood thlltsuch 1I boundllry, which reilltive/ystllble, would not be permllnentlyfixed but would be IImbullltory tothe extent there occurs long-termIIccretion or erosion).

The use of the MHW datum plane forthe determination of a boundary isstraightforwardly a monergistic application;one must be careful, however, to note thatdetermination of the seasonal shoreline shift(or beach width) is not. This will require asynergistic application using MSL. Similarly,any periodic review and boundary relocationdue to long-term shoreline changes willrequire the synergistic approach.

INLETS AND ASSOCIATEDASTRONOMICAL nOES

It has been speCUlated that tidal inletscan significantly affect the character of opencoast tide behavior. There are, however,insufficient alongshore data crossing inlets,both upcoast and downcoast, upon which toassess the effect of inlets (termed the"shadow effeer). In addition, flowcharacteristics vary from inlet to inlet and amultitude of such investigations would bereqUired to investigate the alongshoreinfluence of inlets. There are, however, someisolated open coast tide data near inlets orwithin inlet throats close to the shoreline.There are more data interior to inlets. Suchinformation for 24 Florida tidal inlets andpasses are plotted in Figure 14 from whichsome significant elucidating conclusions maybe gleaned.

The data of Figure 14 are displayed intenns of the measured inlet tide data minusthe open coast tide data of Balsillie and others(1987a, 1987b, 1987C). In this way the


0.4~---r----~--~--...,.....--....,

53

reference plane for a synergisticapplication (e.g., storm impact,seasonal, or long-term beachchanges), the amount of errorintroduced is potentially highlysignificant. It would, in addition,occur over a quite short segment ofshoreline. For MHW,39% of the data are acceptable (i.e.,lie with :t 0.1 ft. of the open coastdata) with 61 % of the data beingunacceptable. For MLW 76% of thedata are unacceptable. However, forMTL almost 70% of the data areacceptable. This shift in dataacceptability for MTL is not aberrant.Rather, it is to be a moderatingexpectation since MTL is the planelying halfway between MHW andMLW and should, therefore muchmore closely approach open coastMTL values than any of the otherextremal tidal datum planes .Therefore, depending on theapplication, the locally measuredMSL (MTL) datum plane or the opencoast MSL (MTL) datum plane shouldbe used for synergistic applications inthe vicinity of inlets (which is usedshould be clearly specified). Hence,MTL (or the MSL surf base) is, onceagain, the proper datum plane to usefor inlets. In fact, O'Brien (1931)intentionally included in hisdefinitions for tidal characteristics

(e.g., flow area, tidal prism) that they bereferenced specifically to MSL.

Ideally, the alongshore "shadoweffect" of inlets on astronomical tides shouldbe quantitatively assessed. Such work is,however, expensive and time consuming andis not expected to be forthcoming any timesoon.

It is also of significance to note thatCole (1997, p. 38) has found that nth orderpolynomial equations precisely determinetidal datums within estuaries. The order ofthe best fit polynomial for an estuary was

••

•

• ••

•

• ••

• ••

MHW

•I

•

••

•

•

MLW

•

f-------- -----_----- ----- -----..0.2 ..~.4 •..-0.6 ........, __-'-__--.I",__--L1 'L....-_..:.HI:.:.lI

o 0.5 1.0 1.5 2.0 2.5

... from SftoreIIne

0.2f-i---- -------- --------------

o • • •• .' •... _1 .1. .. _

~.2 • •• •.....: -0.4 ••-i -0.8

l. -0.1

; ·1.0ii fe ·1.2

•• •• •:I O.2f->, •• • • • •.Ii -,.... --------------------------

O' • •• •

i 0.4,.....---..L..---'---........--"'-----4oU 0.2 MTlc • •• .M_ -, - - - - -.- r , - - - ~ - - - - - - - - - - - - -Q, O. I •• • . •c. ••• ••i ::~ ~~~----.:-----~.--------.----

! 0.1 t~5 0.6"

! 0.4

Aggre 14. Oep8rture of Rorida Mt tide data andopen coast tide Uta (measured tide data from DNR,Bureau of Survey and Mapping). See text forclscussion.

acceptability of the data within the dashedlines (i.e., plus and minus 0.1 ft.) can beeasily assessed. Data for MHHW and MLLWplot similar to MHW and MLW data withsomewhat greater variability, and are notshown.

The first conclusion to be drawn fromFigure 14, is that the amplitude of the tide isattenuated by the inlet (i.e., MHW becomeslower in elevation and MLW gains elevation);this is illustrated in a different manner fortwo Florida inlets in Figure 1S. Hence, if onewere (as before) to use MHW as the


~1-"5~-roe,-__ _'~~_N~~~~_ _~~~~~~T.~~~2.00 .

I I I I I I

: : r~: :I I , ,

. I ~ I 6" I 1,,.-.... 1.00 - -!- - - -,- - -.. - - i - - - r - - - - - r

: "'" I t l I I '-"'ti' 'i I il

,.~ I ~'I J I 10 I

g 0.00 i '" _:_ '_ - ~ \- - -a ~\ I I \\

> ~\' I~\Q) '....,..1 i 1.".J. , '

W \, '-I 'to L_ -1.00 "\' - - - - -", - - - I

o . I I

"D I

t- :I I I I I

-200 ., .1'. ".,1." ".1 •• 1.""'" ,I •••• " ••• 1" ""·.,1",,·,, "1"",,,,·(. 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00

Time (Hours)

Rgure 15. Open ocean and inside astronomical tides for Ft. Pierceand St. Lucie Inlets, Aorida (from Anonymous, 1992).

found to be predictable based on the lengthof the estuary and the travel speed of thetidal wave within the estuary.

CONCLUSIONS

A considerable amount of information,hopefully simplified as much as possible, hasbeen presented in the above application/useexamples. It would not serve further purposeto restate conclusions here that could be moresuccinctly touted, other than to state that MSL(or open-coast MTL) is the proper datum toemploy for synergistic coastal engineeringapplications. It is hoped that this work hasrendered it apparent that how we perceive andtreat such subject matter in a scientific contextis sensitively critical. The considerationspresented herein embody not just philosophy,but engender intellectual contemplation anddeliberation necessary to arrive at a deductive,reasonable, and robustly correct conventionfor application. In this day and age, it isunfortunate that while we are finally realizingsuch enhanced data processing capabilities,we are fraught with misapplication that all-toooften render good data to inaccurate results.

ACKNOWLEDGEMENTS

Review of this work by selected staffof the Florida Geological Survey is gratefullyacknowledged, in particular those editorialcontributions of Jacqueline M. Lloyd,Thomas M. Scott, Kenneth M. Campbell, JonArthur and Walter Schmidt. Review by theBureau of Beaches and Coastal Systems isalso acknowledged with special thanks toRalph R. Clark and Thomas M. Watters fortheir interest in the subject and/or editorialcomments. Special thanks are extended toGeorge M. Cole who reviewed themanuscript and encouraged its pUblication.

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