lIfo.-- -

State of RoridaDepartment of Environmental Protection

David B. Struhs, Secretary

Division of Administrative and Technical Services

Rorida Geological SurveyTallahassee, Rorida

1999

ISSN 1058..1391

-- ..-

CONTENTS

PageABSTRACT 1INTRODUCTION 1EXTREME EVENT EROSION AND ITS RELATION TO THE TYPE OF PRE-IMPACT

COASTAL PHYSIOGRAPHY 2DATA , 3ANALYTICAL RESULTS 4

The Event Longevity Parameter (ELP) . . . . . . . . 7Average Erosion Quantity Above Mean Sea Level and ProbabilityDensity Function (PDF) . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Average Erosion Quantity Above the Peak Storm Tide Level andProbability Density Function (PDF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Design Erosion Quantities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13The Offshore Sink Efficiency Parameter (OSEP) . . . . . . . . . . . . . . . . . . . . . . . . 14Return Period Volumetric Erosion Events 18Post-Storm Recovery .......................•.................. 20

APPLICATIONS .. . . . . . . . . • . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Post-5torm Beach and Coast Physiography . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Encounter Period and Probability ....................•............. 23An Erosion Damage Potential Scale 24

CONCLUSIONS 25ACKNOWLEDGEMENTS 27REFERENCES 27APPENDIX 35

TABLES

Table 1. Characteristics of storms and hurricanes used in this study. . 5Table 2. TYPE I erosion volume above mean sea level. 9Table 3. TYPE I erosion volume above the combined peak stonn tide 15Table 4. Amended Saffir/Simpson Hurricane Damage Potential Scale 25

FIGURES

Figure 1. Idealized pre-storm (solid lines) and eroded (dashed lines) profile scenariosfor the three basic types of coastal physiography 2

Figure 2. Relationship between the measured TYPE I average erosion volume above meansea level and the event longevity parameter 8

Figure 3. Example of water surface hydrograph through an idealized storm tide, anddefinition of storm tide rise time measure (after Balsillie, 1986) 11

Figure 4. Relationship between the storm tide rise time and event forward speed,where the relating coefficient, 0.00175 is in units of hours squared (afterBalsillie, 1986) 11

Figure 5. Typical examples of density distributions for determination of the slope q:»relating Qe and e3P (event I. D.s refer to Table 2). . 12

Figure 6. Relationship between the event longevity parameter and distributioncoefficients for TYPE I average volumetric erosion above MSL. . . . . . . . . . . . . . 13

Figure 7. Relationship between the measured TYPE I average net erosion quantity abovepeak combined storm tide and the event longevity parameter. . 13

Figure 8. Relationship between the event longevity parameter and distributioncoefficients for the TYPE I average erosion volume above the peak combinedstorm tide. . 14

Figure 9. Tesselated relationship relating nearshore bed slope to the ELPcoefficient, f. 16

Figure 10. Comparison between a typical Florida nearshore profile and typical Cancun,Mexico nearshore profile. . 17

Figure 11. Relationship between the initial nearshore bed slope, tan ai' and thepower curve fit shape coefficient, as. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Figure 12. Relationship between exceedence probability, P, return period, Te, andaverage TYPE I erosion volume above MSL. 19

Figure 13. Example of application for determining two-dimensional post-stonnphysiography using volumetric data, and design wave conditions 23

Figure 14. Nomograph for relating event return period, encounter period, andencounter probability 24

Figure 15. Beach and coast erosion damage potential scale as a function of eventforward speed at landfall and peak stonn tide elevation. Erosion volumes arebased on peak storm tide elevation classes of Table 4; even so, results applyto storm events as well as hurricanes.. . 26

ii

VOLUMETRIC BEACH AND COAST EROSION DUETO STORM AND HURRICANE IMPACT

by

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

ABSTRACT

Prior to the initial work of the author during the early 1980s, methods to predict nearshore,beach, and coastal erosion due to storm and hurricane impact were based on theoretical applications andestimation. However, with the acquisition of actual field data quantifying storm and hurricane erosiveimpacts, it became clear that, in addition to the combined storm tide (commonly termed the storm surge),the length of time that an event has to erode the beach and coast is a highly significant factor that couldbe quantified (i.e., given two events each producing identical storm tide hydrographs, the slower movingevent will result in greater beach and coast erosion). Hence, based on actual field data, the .".",IDntIevitr"...".,..(B.P} was introduced (Balsil\ie. 1985c. 1986) which incorporates both the combinedstorm tide and its rise time, the latter of which can be computed from the event forward speed.

Since the published work of the mid·1980s, additional field data (a three-fold increase) havebecome available to further verify the ElP approach, and to introduce new developments. It has, forinstance, become apparent that in addition to the design peak storm tide elevation, the design erosionevent requires attention in many coastal engineering design applications if they are to be successful. Infact, aside from design soffit elevations which are determined from the peak combined storm tideelevation and superimposed storm waves propagating upon the storm tide surface, it is the design erosionevent that quantifies the final expression of all other impacts. Hence, probability density functions aredefined for both erosion above mean sea level and peak storm tide level. In addition, it has been foundthat the pre-impact offshore bed slope can be used to indicate the "efficiency· or "receptiveness" of theoffshore sediment sink to accept sand eroded from the beach and/or coast (termed the off6hote .mkefIicieney "..".,., {OSEP}. Incorporation of the new data, and quantification of the two additionaldevelopments and an amended Saffk/Simpson hurricane damage potential scale constitute the subjectmatter of this paper.

INTRODucnON

Although, in the seasonal andlong-term sense, beaches are constantlybeing remolded by waVes, tides and winds,the most dramatic changes occur as theresult of extreme event (i.e., short-termimpacts from storms and hurricanes). Theconsideration of short-term, seasonal, andlong-term impacts (i.e., force elements suchas astronomical tides, storm tides, waves,etc.) and the resulting outcomes (i.e.,response elements such as beach and coasterosion, longshore bar formation, andstructural damage) are matters of standard

1

coastal engineering practice. In this paper,short-term impacts define the subject ofinterest.

For many years, only the peakcombined storm tide (also commonly termedthe storm surge) was employed indetermining and assessing nearshore, beach,and coastal engineering design solutions.Consideration of the storm tide alone,however, does not provide a realisticmeasure of impact potential. For instance,given two extreme events with identicalstorm tides, the slower moving event willresult in greater beach and coast erosion.

------

-------~--- ....----

_ A

..-- ~--- ....----------~------- --.....::::.:::::=.=:.::

recession is important in determining siting ofcoastal development activities. It is,however, the maximum vertical recessionproduced during event impact (Balsillie,1984c, in manuscriptl which is needed toassess structural design constraints (e.g.,piling tip penetration, "first floor" soffitelevations, etc.) based on hydraulic forcessuch as shore.breaking wave impactpressures (Balsillie, 1985b). Verticalrecession should include effects due to bothscour, and sediment liquefaction (Zeevaert,1983, 1984).

It is also important to bear in mind thedifferences between the nearshore, beach (orshore), and coastal subzones of the littoralenvironment (Figure 1). Under normalhydraulic littoral conditions, processes areclearly different within each subzone(discussed in detail in later sections).Whether or not the storm rises above thebeach, or if not, has the longevity to erode

-------------"..-FLOODED

----t--.....,'""="~-------n ..--

The peak storm tide elevation plussuperimposed storm wave activitypropagating upon the storm tide surface isuseful in determining deck, floor, etc. (termedII soffit") elevations, provided that any shift orerosion of the bed is known, since increasedwater depth results in higher waves. Allother design solutions are more nearly relatedto erosion responses, such as pile tippenetration, seawall and bulkhead panelembedment elevations, etc. In addition,since storms cause nearshore erosion andbed shifts in response to longshore barformation accompanying beach and coasterosion, resulting increased water depths cansignificantly affect both horizontal andvertical wave impact potentials which requireconsideration in design solutions andassessments.

The need for methodology to predictbeach and coast erosion due to the impact ofstorms and hurricanes has been an issue ofongoing and increasing concern. Moreover,it is one which, for the majority of the historyof the discipline of coastal science, haseluded satisfactory quantifying solutions.The lack of methodology is not surprisingconsidering the complexities involved inquantifying littoral processes. Ultimately,however, only through the acquisition of fielddata will confident successful solutions berealized. This paper provides a significantupdate (in terms of the number of hurricaneand storm events) to previous work by theauthor (Balsillie, 1985c, 1986).

Figure 1. Idealized pre-storm (solid lines) anderoded (dashed lines) profile scenarios for thethree basic types of coastal physiography(STL = peak storm tide level, MSL = meansea level).

NON-FLOODED

\ C\,":'"..--~c--------" ..-­.....­.....

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

EXTREME EVENT EROSION ANDns RELAnON TO THE TYPE OF

PRE-IMPACT COASTALPHYSIOGRAPHY

In this paper erosion is considered tobe the overall term encompassing horizontaland vertical recession components of beachand coast response due to storm and/orhurricane impact. Depending on the type ofcoastal physiography, these components canresult in quite different outcomes. Horizontal

2

_. ....

the beach and begin to erode the coast, andpost-storm beach recovery, are importantissues which shall be addressed later.

Considering initial coastalphysiography and responses due to extremeevent impact, three general types ofgeomorphic scenarios are suggested:non-flooded, flooded, and breached profiles(Figure 1). In assessing these profile types,several assumptions are made: 1) the beachand coast are composed of relativelyunconsolidated sand-sized sediment, 2)onshore-offshore sediment transportprocesses prevail and alongshore processesare assumed static, and 3) ·shallow water"hydraulic processes are approximatelyconstant for a given water depth, noting thata change in wave conditions (principallyshore-breaking and broken waves) will causea shift in bathymetry which, in turn, willaffect the waves.

Where the coast is higher than thepeak storm tide and is wide enough not to bebreached (i.e., the non-flooded' condition),only the offshore •sink" is available fordeposition of sand eroded from the beachand coast. A major contributing erosionalmechanism is gravitational mass wasting,because only a relatively few waves arerequired to cause an unstable, steep sandface to collapse. As the sedimentescarpment increases in height, increasinglymore sediment is potentially available forintroduction to the prevailing littoral hydraulicenvironment for redistribution.

The barrier islands of the lower FloridaGulf Coast may in many places be inundatedby 1 to 2 meters of water due to impact of a1OO-year return period peak combined stormtide event (see Table 1 for definition). Thisdoes not include the added hydraulicelevation due to shore-breaking wave activitywhich propagates upon the storm tidesurface. Therefore, the contribution ofgravitational mass wasting, important to thenon-flooded scenario, may not be of special

3

consequence for relatively low-lying barriers.It does, however, introduce the aspect of anadditional "sink" for eroded sand due tooverwash processes (Leatherman, 1976,1977, 1979, 1981; Leatherman and others,1977; Schwartz, 1975). Combination of thepreceding two physiographic-hydrographicscenarios leads to the breached profilecondition illustrated in inset B of Figure 1 inwhich the overwash sink again occurs.

It is also apparent from the literaturethat the success of grain-by-grainonshore-offshore sediment transportmechanics under littoral wave activity as yetremains to reach the status of satisfactoryquantification (Balsillie, 1984c, 1986). Thatexisting attempts at quantification may befraught with insensitivities is furtherexaggerated when dealing with a rising andfalling storm tide and with storm-generatedlittoral wave activity. Hence, pursuit ofalternative approaches is desirable. Onesuch approach is investigation of field dataquantifying actual storm and hurricaneimpact upon our shores.

DATA

This subject has received muchattention in previous work, dating back forabout 3 decades. Perhaps the mostcompelling work is that of Caldwell (1959)just preceding the infamous U. S. east coastAsh Wednesday storm of 1962(Bretschneider, 1964; Harrison and Wagner,1964; and O'Brien and Johnson, 1963), witha resurgence of interest occurring with theworks of Edelman (1968, 1972). Therehave, in addition, been many studies reportedin the literature providing descriptiveaccounts of the erosive power of extremeoccurrences. However, until this work wasoriginally published (Balsillie, 1985c, 1986),there were insufficient types and quantitiesof field data on which to quantify beach andcoast erosion due to storm and hurricaneimpacts. This work has increased the size ofthe field data base by a factor of three.

Fourteen erosion events for 11hurricanes, and 22 erosion events for 20storms (Table 1) provides the largest fielddata compilation amassed to date for thepurpose of quantifying beach and coasterosion due to extreme event impact. 5evenevents (H4, 517,518, H7,H8, H9 and H10)were assessed through field data collectionof the 5tate of Florida, Department of NaturalResources (DNR, now the Department ofEnvironmental Protection, DEP), Division ofBeaches and Shores (now the Bureau ofBeaches and Coastal Systems); field datacollection techniques have been discussedelsewhere (Sensabaugh and others, 1977;Balsillie, 1985a, 1985c, 1985e, 1986,1988). Thirteen events (S2 through S11,514, 515 and S16) are the direct results ofthe efforts of the Coastal EngineeringResearch Center (CERC); field data collectiontechniques are discussed by Birkemeier(1979); Birkemeier and others (1988). Amore recent event has been reported by Kanaand Jones (1988) and Jones and Kana(1988). Hurricane Hugo (H11) information ispresented by Birkemeier and others (1991)and 5tauble and others (1991). A tropicalstorm (520) was reported by Beumel andCampbell (1990). Ferriero (1994) reportederosion from a Portuguese storm event thatoccurred in 1989. Remaining events arefrom independent studies (references arelisted in Table 1) that were previouslyanalyzed by the author (Balsillie, 1985c,1986).

Of the aspects concerning the data, itis important to note for managementpurposes that there are two types of erosion(Balsillie, 1985a, 1985e). One is themeasure which represents those sampledprofiles where erosion only occurred (TYPE Ierosion measure). The other (TYPE II) is thatwhich includes all profiles regardless of gainor loss. TYPE II erosion is important inassessing actual beach and coast economiclosses. For design applications, TYPE Ierosion is the better measure, since fordesign work we are interested in locations

4

only where erosion has occurred. Hence, inthis paper, TYPE I erosion volumes are used.Using the data from events H4, H5, 517,518, H7, and H8, Balsillie (1985e, p. 33-34)found that, on the average, TYPE II erosion is73% of TYPE I erosion (n = 13, sampled forover 200 profile pairs, r = 0.9515),

Where possible, profiles were selectedto represent known extreme event impactmagnitudes. For instance, only DNR (nowDEP) ranges R-33 through R-125 in WaltonCounty, Florida were selected for HurricaneEloise, since it was this area that coincidedwith the first quadrant of Eloise in terms ofthe combined storm tide height (see Balsillie,1983a). In other cases, one could onlyconsider what pre- and post-storm profiledata were available; an example is the AshWednesday storm of 1962.

ANALYTleAL RESUL7S

Two reference water levels havecommonly been used, above whichvolumetric erosion is determined: 1. thepeak storm tide still water level (5TL), and 2.mean sea level (MSL).

The first water level (STL) isconsidered here because it has been used inother work. It is particularly accurate fornon-flooded profiles since erosion volumesrepresent single process losses above thereference water level due to gravitationalmass wasting, and include none of thecomplexities occurring below the referencelevel due to interactive hydraulic andsediment transport processes. It should beclear, however, that this reference waterlevel has no applicability in determiningvolumetric erosion for breached or floodedprofiles and, therefore, its use results in onlypartial success in volumetric erosiondetermination.

The mean sea level reference will, onthe other hand, provide for volumetricerosion determination for all three

Table 1. Characteristics of storms and hurricanes used in this study.

Peak Event Stonn

Stonn ForwardTide

Event and LocationTide 1m Speed Rise Infonnation Sources

I. D.MSL) (krnlhr)

Timelhr$)

HlHurricane AUdrey, June

3.66 19.0 11.7 Morgan and others, 19581957, Louisiana Gulf Coast

Hurricane Carla, Sep.Reid and others. 977; Neumann

H2 2.30 6.3 S1.0· and others, 1981; Schwerdt and1961, Texas Gulf Coastothers. 1979; U. S. Army. 1962

Ash Wednesday Storm, Bretschneider, 1964; Harrison andS1 Mar. 1972, U. S. East 3.0S --- 28.0' Wagner, 1964; O'Brien and

Coast Johnson, 1963

S2Nov. 1962 Storm, U. S.

1.50 --- 7.S'East Coast

S36 Nov. 1973 Storm, U. S.

1.40 --- 18.S· Birt.emeier and others, 1988East Coast

S413 Jan. 1964 Storm, U. S.

1.S0 --- 12.4'East Coast

Hurricane Betsy, Sep. Wanstrath, 1978; Neumann andH3 1965, Mississippi Gulf 2.26 16.0 18.0' others, 1981; Schwerdt and

Coast others, 1979; U. S. Army 1979

SS 16 Sep. 1967 Storm, U. S.1.40 ". 12.4'

East Coast

S6 12 Mar. 1968 Storm, U. S..1.20 --- 6'"East Coast

S712 Nov. 1968 Storm, U. S.

1.60 --- 15.0'East Coast

58 2 Feb. 1970 Storm, U. S.1.10 --- 6'"East Coast

5917 Dec. 1970 Storm, U. S.

1.60 12.4' Birkemeier and others, 1988._-East Coast

S10 19 Feb. 1972 Storm, U. S.East Coast

S10a New Jersey 1.80 --- 6.1'SlOb New York 2.00 --- 6. ,.

511 17-22 Mar. 1973 Storm.U. S. East Coast

S1 1a New Yort. 1.40 ... 12.2'S11b New Jersey 1.30 --- 12.2'

S12Nov·Dec. 1973 Events, 3.S7 --- --- Erchinger, 1974German North Sea Coast

51323 Sep. 1974 Storm, U. S.

1.45 --- 9.0 Kana, 1977East Coast

Hurricane Eloise, Sep. BalsilJie. 1983a; Burdin, 1977;H4 1975, N.W. Florida Gulf 3.15 42.6 5.0'

Chiu, 1977; U. S. Army, 1976Coast

5

Table 1. Characteristics of storms and hurricanes used in this study (cont ), ,

Peak Event Storm

Storm ForwardTide

Event and Loc:ationTide(m Speed

Rise Infonnation SourcesI. D.

MSLI (kmlhr)Time(hrs)

51414 Oct. 1977 Storm, U. S.

1.80 17.0·East Coast ---

51519 Dec. 1977 Storm, U. S.

1.40 35.0.

Birkemeier and others, 1988East Coast

---

5166 Feb. 1978 Storm, U. S.

1.70 _.. 19.9'East Coast

Balsillie and Clark, 1979; Parker

H5 Hurricane Frederic, Sep.3.66 24.1 11.0' and others, 1981; Penland and

1979 Alabama Gulf Coast others, 1980; Schramm andothers, 1980

H6Hurricane Allen, Aug.

2.74 32.2 6.0' Dahl and others, 1983; U. S.1980, Texas Gulf Coast Army,1980

No Name Storm, 17·18517 June 1982, Lower Florida 1.68 40.2 8.0' Galvin, 1983; Trescott, 1983

Gulf Coast

H7 Hurricane Alicia, Aug.3.86 12.0 18.0' Dupre, 1985; Garcia and Flor,

1983, Texas Gulf Coast 1984

Thanksgiving Holiday518 Storm, 21-24 Nov. 1984, 1.83 ... 21.0' Balsillie, 1985a

Florida East Coast

H8 Hurricane Elena, Sep.1985, Florida Gulf Coast

H8a Pinellas County 1.37 14.5 20.0'Balsillie, 1985e

H8b Franklin County 2.32 16.1 13.4H8c Gulf County 2.10 16.1 13.4Had Escambia County 2.29 25.7 8.0'

H9 Hurricane Kate, Nov. 1985,2.60 9.2 Balsillie, 1986

N. W. Florida Gulf Coast...

S191 Jan. 1987 Storm, U. S.

1.50 ... 12.0Kana and Jones, 1988; Jones and

East Coast Kana, 1988

H10Hurricane Gilbert, Sep.

3.81 .-- 9.5Unpublished Florida Department of

1988, Cancun, Mexico Natural Resources data.

S20Feb. 1989 Storm,

3.53 45.0 Ferreira, 1994Portuguese Atlantic Coast

..-

Hurricane Hugo, Sep.Birkemeier and others, 1991;

Hll 3.80 32.2 5.0 Nelson, 1991; Stauble and others,1989. U. S. East Coast 1991

Tropical Storm Marco. Oct521 10-11,1990. Lower 1.13 16.1 9.0 Beumel and Campbell, 1990

Florida Gulf Coast

Notes: Peak storm tide is the combined peak storm tide level above NGVD including the astronomical tide anddynamic wave setup; Peak storm tide for event S12 was measured from the local datum; • indicates the measurestorm tide rise time, all other are predicted using equation (21.

6

physiographic scenarios of Figure 1 (except,perhaps, for extreme cases such as inletformation where erosion occurs below MSL).For breached or flooded profiles, overwash iseliminated from erosion volumes, so thatvolumetric erosion for non-flooded profiles(where only the seaward sink is available fordeposition) and for flooded and breached(where the seaward and upland sinks areavailable, but eliminated) profiles arecomparable. Elimination of upland andseaward sinks is desirable since, on theaverage, the sum should be equivalent to theamount eroded. While at the seawardextremity of the post-storm profile, somematerial of the seaward sink (also includingsome degree of post-storm beach recovery)may reside above MSL (determined to be about6% of the seaward sink volume from 245analyzed profile pairs from Balsillie, 1985c),the analytical method is fairly unbiased sinceit is applied equally to all profiles investigated.

For erosion volume determinations andapplications, any datum other than MSL (i.e.,mean lower low water (MLLW), mean lowwater (MLW), mean high water (MHW), andmean higher high water (MHHL)) is not to beemployed. Their departure from MSL is notconstant from locality to locality (Balsillie andothers, 1998). Hence, volumes will not becomparable.

It should be noted that volumetricchanges were investigated which includedoffshore profile data. The results, however,introduced significant scatter. It is to beunderstood that offshore profiling requiresconsiderable time and resources (Sensabaughand others, 1977; Balsillie, 1985a, 1985e).Post-storm field measurements are most usefulwhen the response time is swift, since anydelay increases the possibility of post-stormbeach recovery which can be faster thanpreviously thought. Based on the preliminaryanalysis alluded to above, the inclusion ofoffshore profile bathymetry does not yetappear to be justifiable.

7

There have been a number of extremeevent erosion studies in which volumetricerosion calculations are based on singleaveraged or composite pre-storm andpost-storm profiles, even though multipleprofiles were measured. In this study,however, pre- and post-storm profiles aresurveyed from precisely located coastalmonuments, along azimuths established foreach monument. Hence, volumetric changeshave been calculated for each profile pair, andresulting data have been then statisticallytreated to obtain point estimators andprobability density functions (PDFs).

The Event LongevityParameter (EU')

AverageErosion QuantityAboveMean SeaLevel and Probablity Density Funt:lion(PDF)

The most complete set of field dataamassed to date is now available to quantifybeach and coast response due to extremeevent impact. However, such data have littlevalue if there does not exist a methodology forpredicting future occurrences of erosion. Infact, until recently, there has been noconsolidated methodology by which to realizesuch prognostication. Recognizing that theamount of erosion is significantly dependentupon the length of time that an extreme eventaffects the beach and coast (Hayes, 1967;Hayes and Boothroyd, 1969), the author(Balsillie, 1985c, 1986) developed the eventlongevity parameter (ELP). In terms of theaverage TYPE I erosion quantity above MSL,Q e avg' the relationship is given by:

Q. IIIf!1 = 1622-1 (g1/2 I, S2t/5 (1 )

where g is the acceleration of gravity, S is thecombined peak storm tide elevation (see noteof Table 1 for definition), and t r is the stormtide rise time. The relationship and data onwhich equation (1) is based are plotted inFigure 2 and listed in Table 2. The data

I/?b

300000250000

(g 4/5Q =1622-1 1/2 t 52)e avg r

0.9857

r0.98670.9833

n142236

50000

• Hurricanes• Storms

Total

180160140120100806040200 ......._ ......-.........-.........._--.........__.....................-...................-----'

o

Qeavg

(m3 /m)

The role of pre-storm setup as an

where g is in units of km/hrl (i.e., g = 9.8m/s2 = 127008 km/hrl), vf is in units ofkrn/hr, and the coefficient 0.00175 is in unitsof hrl.

introduced, when trying to interpret when thestorm tide ends. The total value of tr for astorm produced tide, maintained overmultiple astronomical tides, is determined byadding the rise time components of eachadditional cycle.

For analytical purposes, t r is anexcellent quantitative measure of eventlongevity. However, for applied predictivepurposes, for an approaching event, themeasure is not useful because it is availableonly after event impact. However, it wasfound (Balsillie, 1985c) that the storm tiderise time and event forward speed, vf(measured at the point when the radius ofmaximum winds, or a facsimile thereof forextratropical storms, makes landfall), arerelated (Figure 4) according to:

(2)Ir = 0.00175 gv,

The storm tide rise time, t r, is the finalcontinuous surge of the storm tiderepresenting impact of the event at landfall.In some cases, pre-storm setdown (e.g.,particularly for alongshore hurricanes notconsidered here) and pre-storm setup canoccur. These should be eliminated indetermining the value of t r, whose graphicaldetermination is illustrated in Figure 3.

sample on which equation (1) is founded isthree times larger than that available toBalsillie (1985c, 1986) in the originaldevelopment of the relationship, whichallowed for refinement of the dimensionlessconstant. The coefficient of equation (1) is,however, but 2.5% smaller than thatreported in the earlier work.

Values of the storm tide rise time arefrom measured storm tide hydrographs(references are given in Table 1). Suchrecords are not always simple to interpret,depending on gauge siting, distance ofgauges from event landfall, and relationshipof the storm generated tide and theastronomical tidal cycle. Consideration of thecombined storm tide rise time rather thanthe total tide history does, however,eliminate uncertainty, which may be

8

Table 2. TYPE I erosion volume above mean sea level

Av....ge Maximum eventerosion &oslon Longevity Elapsed

ProfileJ.D. Event and Location Volume Volume Parameter cp Timen r. Type(m3/m) (m3/m) (m3/ml (months)

Hunicane Audrey,H1 Jun. 1957, Louisiana 51.7 89.0 6 99,461 5.55 0.8449 29-48 F

Gulf Coast

Hurricane Carla, Sep.H2 1961, Texas Gulf 89.8 --- 8 153,710 --- ... 5.3 NF,F

Coast

Ash WednesdayS1 Stonn, Mr. 1962, U. 93.0 ..- 5 149,327 .-- ..- 60-96 NF

S. East Coast

S2Nov. 1962 Storm, U.

12.9 28.9 31 16,724 1.80 0.9721 0.36 NFS. East Coast

S36 Nov. 1963 Storm.

20.5 47.3 28 30,970 2.95 0.9634 0.60 NFU. S. East Coast

S412 Jan. 1964 Storm,

25.0 56.9 21 25.037 3.55 0.9703 0.50NF,

U. S. East Coast MS

Hurricane Betsy, Sap.H3 1965, Mississippi Gulf 46.5 99.0 9 64,912 6.17 0.9939 4 F,B

Coast

S516 Sap. 1967 Storm, 16.6 43.6 18 22.420 2.72 0.9637 0.16 NFU. S. East Coast

S612 Mar. 1968 Storm, 9.7 24.9 18 9,919 1.55 0.9787 0.16 NFU. S. East Coast

S712 Nov. 1968 Storm,

26.2 55.8 41 32,285 3.48 0.9610 0.72NF,

U. S. East Coast MS

S82 Feb. 1970 Storm, U. 11.1 19.1 29 8,630 1.19 0.9404 0.52 NFS. East Coast

S917 Dec. 1970 Storm,

17.7 43.5 37 27,724 2.71 0.9906 0.41 NFU. S. East Coast

S10 19 Feb. 1972 Storm,U. S. East Coast

S10a New Jersey 9.5 18.8 34 18,977 1.17 0.9572 0.76 NF

SlOb New York. 20.2 41.7 23 22,462 2.60 0.9630 0.82 NF

S11 17·22 Mar. 1973Storm, U. S. EastCoast

S11a New York. 23.6 52.9 16 22,102 3.30 0.8923 0.69 NF,MS

S11b New Jersey 10.3 25.3 17 19.630 1.58 0.9768 0.66 NF,MS

Nov.·Dec. 1973 Event,S12 German North Sea 200.0 ... ... --- _.. ..- --- NF

Coast

S1323 Sep. 1974 Storm, 12.0 ... 10 18,328 ... --- 0.07 NFU. S. East Coast

Hurricane Eloise, Sep.H4 1975, N.W. Florida 20.0 50.7 62 39,628 3.16 0.9735 24 NF

Gulf Coast

9

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

Table 2. TYPE I erosion volume above mean sea level (cont ). .Ave,.ge Maximum Event

1.0. Event and LocationErosion &O.ion Longevity Elapsed

Profilen TimeVolume Volume Parameter Q) r. Type(m3/m) (m3/m) (m3/m) (months)

S1414 Oct. 1977 Storm, 18.5 34.8 22 43,085 2.17 0.9710U. S. East Coast

0.23 NF

S1519 Dec. 1978 Storm, 11.6 37.9 17 42,979 2.36 0.9800U. S. East Coast

3.25 NF

S166 Feb. 1978 Storm, U. 11.6 37.9 17 42,979 2.36 0.9800 3.25 NFS. East Coast

Hurricane Frederic, Sep.H5 1979, Alabama Gulf 52.0 121.1 32 94,671 7.55 0.9738 6 F,B

Coast

H6Hurricane Allen, Aug. 28.0 ... 3 36,682 --- 30 NF,B1980, Texas Gulf Coast

-..

No Name Storm, 17-18S17 Jun. 1982, Lower 14.0 25.8 24 21.111 1.61 0.9917 3 NF

Florida Gulf Coast

H7Hurricane Alicia, Aug.

92.4 ... 1 152,259 36 NF1983, Texas Gulf Coast

.,. ...

Thanksgiving Holiday

S18Storm, 21·24 Nov. 27.0 70.0 127 52,388 4.30 0.9077 3-20 NF1984, Florida EastCoast

H8 Hurricane Elena, Sep.1985, Florida GulfCoast .-

H8a Pinellas County 21.0 48.3 44 31,704 3.01 0.9622 130 NF

H8b Franklin County 40.0 75.4 35 54,456 4.70 0.9585 49 NF

H8c Gulf County 24.0 44.1 54 45,579 2.75 0.9753 13-21 NF

H8d Escambia County 19.0 38.3 112 34,653 2.39 0.9875 10 NF

Hurricane Kate, Nov.H9 1985, N. W. Florida 22.0 51.2 18 47,481 3.19 0.9617 2 F,NF

Gulf Coast

S191 Jan. 1987 Storm, U. 19.4 --- 4 25,669 ... 0.3 NFS. East Coast

---

Feb. 1989 Storm,S20 Portuguese Atlantic 164.0 341.0 4 276,390 .,. --- -.- .,.

Coast

Hl0Hurricane Gilbert, Sep. 144.7 297.0 8

89,78218.52 0.9842 60 NF

1986, Cancun, Mexico 231,462-

HllHurricane Hugo, Sep. 28.0 52.5 19 53,501 3.98 0.9691 4 NF1989, U. S. East Coast

Tropical Storm Marco,

S21Oct. 10-11, 1990, 3.9 11.4 28 9,317 0.57 0.9755 1 NFLower Florida GulfCoast

Notes: Elapsed time is the time between pre- and post-storm surveys; Profile types are: F :: Flooded, B :: Breached,

NF :: Non·f1ooded, MS :: Multiple Storms; adjusted value to account for increased offshore sediment sink efficiency,

see text for discussion; data sources are listed in Table 1.

10

60

,.

II I

_1,-':I I____ ....J. ... _

~-Storm

... Setup.,

t r • 0.00175 !f

that pre-storm setup is an anomalous feature,the above further substantiates that it shouldbe deleted from consideration in erosionprediction.

It is to be noted that the ELP containsboth the peak storm tide, S, and the stormtide rise time, t r. It is the introduction of thelatter which prompted the name eventlongevity parsmeter. Utilizing stepwiseregression (Krumbein and Graybill, 1965;Balsillie, in press; Balsillie and Tanner, inpress), it has been determined that 5 resultsin a relative net contribution in predicting0e av.g of 76%, and tr provides a net relativecontribution of 24%. Even so, both arerequired in order to obtain the success of

n =17r = 0.9278

Normal P,••StormTidal Conditions

7 JoB

2

o

20

80

100 ,...,.--.-.,.--.--..,....-,.--r---.----r--r-~-..,.___.

ElellaUonAbow MSL 3

(mJ

o ~~~:!=J~=f:::!:::j~:::z:::!Io 10 20 30 040 50

Vf (kmlhr)

Figure 4. Relationship between the storm tide rise time and eventforward speed, where the relating coefficient, 0.00175 is in unitsof hours squared (after Balsillie, 1986).

-1 O~-.J.---::2:1;:O-..-.I-~"o~- .......-'"*~-J'-~80~-..J

Time (houu)

Aigure 3. Example of water surface hydrograph through anidealized storm tide, and definition of storm tide rise timemeasure (after Balsillie, 1986).

erosive agent deservesadditional comment. Ifthe general onshorephysiographic scenariocan be described as abeach that is backed bya coast comprised of adune or bluff (see Figure1 for graphicaldefinition), then theelevation relative to MSLwhich identifies wherethe coast begins (i.e.,the beach-coastinflection point, ornickpoint), becomes animportant measure.That is, if the storm tideis less than thebeach-coast nickpointelevation, then moretime will be required toerode the beach beforethe coast is affected,relative to the case (hrs) 40where the storm tide ishigher than thebeach-coast nickpointelevation, so that boththe beach and coast willbe affected within timeconstraints of the event.Experience withidentification of thebeach-coast intersection for Florida beaches(i.e., those for beaches preceding eventslisted in Table 1), tells us that it is the latterscenario which usually defines the designerosion condition. Current examples ofaverage nickpoint elevations are + 2. 19mMSL for Florida's upper East Coast (St.Johns County), + 2.25 m MSL for the lowerGulf Coast (Charlotte County), and + 2.1 mMSL for the northwestern panhandle GulfCoast (Walton County). It is significant thatof the events of Table 1 and thosegraphically reported by Harris (1963), noneresulted in a pre-storm setup in excess ofabout + 1.5 m MSL, well below thebeach-coast nickpoint elevation for Florida.Hence, in combination with the observation

11

equation (1) evident in Figure 2.

•

•

0.5 0.7

Event

50

150 0.1JoB

100

Qe

(m,",)59

2.71

$1 2.36

0 2.15$15

••• • •0

S6 1.55

0

SlOa 1.17

There are 29 events thatprovide information on which toinvestigate an erosional probabilitydensity function (PDF). From 6 to127 profiles represent each of theevents (Table 2), and result in thefollowing equation:

in which 0e is the volumetriccoastal erosion quantity occurringabove mean sea levelcorresponding to the erosionprobability, P, which is theprobability of erosion less than orequal to that stated, and f is arelating coefficient, Values of ¢I(examples are plotted in Figure 5,results and correlationcoefficients are listed in Table 2)are plotted against the ELP inFigure 6, showing remarkableagreement. The relatingcoefficient f becomes 12344-1

,

Correlation coefficientsassociated with ¢I are allsignificantly large. Note that if wewere to consider, say, median andlarger erosion values in the PDFs(see Figure 5), rather than allvalues available, correlationcoefficients would be even larger.

Average Erosion Ouantity Above the Figure 7, surfaces:Peak Storm Tide Level and ProbabBityDensity Function (PDF) Q:.~ = 3299-

1 (g1(2 IT $2)4/5 (4)

The preceding has dealt withvolumetric erosion occurring above mean sealevel. While it has been noted thatconsideration of erosion above the peakstorm tide elevation has no applicability forflooded or breached profiles, such aconsideration does have validity fornon-flooded profiles. Based on availabledata listed in Table 3, the followingrelationship based on 24events, illustrated in

where A'e avg is the TYPE I average erosionquantity occurring above the peak storm tidelevel.

Using data from 22 events (Table 3) aPDF may be proposed according to:

(5)

12

25 r-----------------------,20

15

10

5

• Hurricanes.Stonns

Total

11 0.980318 0.593529 0.9603

O~..... ...... ......................_......I. _...Io.....__-...I

o 50000 100000 150000 200000 250000

415(g1/2 t r 52)

Figure 6. Relationship between the event longevity ,.rameter anddistribution coefficients for TYPE I average volumetric erosion aboveMSL.

150000

415Q' = 3105.1 (g1/2 t 52) - __

eavg r

r= 0.8965

n=24

100 ,...--------------------......

80

60Qeavg

40• Hurricanes2: L!t:-:t.tI'-~.!l.~~...~~ ~.~5~t:onna:~_.J

o 50000 100000415

(g1/2 t r 52)

Figure 7. ReI8tionship between the measuNd TYPE I average neterosion quantity above peak combined storm tide level and the eventlongevity parameter.

where the relating coefficient f from Figureis 23630".

It is evident from results presented inFigure 8, that the correlation betweenvariables is significantly less than thosestatistical assessments for analysespresented in Figures 2, 6, and 7. Even so,the probability that a random sample of thissize could result in sample correlations solarge, is very small.

relative to MSL and the peak storm tideelevations, we can broaden our quantitativeexpectations. We know that for engineeringdesign purposes, using TYPE I erosionvolumes, an average measure is notresponsible. For engineering design purposesit is always prudent to consider some uppermeasure of a destructive force, or responseelement. A highly useful measure fromsubstitution of equations (1), (3), (4), and(5), where PDF linearity prevails, is given by:

in which 0e and 0'e are erosion volumes for

Design Erosion Ouantities

Now that we have establishedsuccessful relationships that quantitativelypredict average erosion volumes for events

0'=--'- = 0.1314 e3 P,

o••~(6)

13

for the TYPE I erosion volume above MSL,and:

for the TYPE I erosion volume above thecombined peak storm tide level. Bothequations result in erosion volumes close to

a specified exceedence probability P aboveMSL and peak storm tide, respectively.Hence, the TYPE I median erosion volume(i.e., P = 0.5) is about 61 % less than theTYPE I average erosion volume (for theaverage erosion volume P = 2/3), the thirdquartile TYPE I erosion volume (i.e., P =0.75) is 130% greater than the averageTYPE I erosion volume, etc.

It is to be noted that coefficients ofequations (7) and (8) precisely agree withfitted coefficients describing the graphicallyestimated maximum erosion quantities ofTables 2 and 3.

The 0IIsh0Te Sink EfficiencyParameter (OSEP)

The form of the event longevityparameter has invoked some controversy.While the combined peak storm tide heightand storm tide rise time components havegenerally been well received, the appearanceof the acceleration of gravity and thedimensionless proportionality constant havenot.

twice (i.e., 2.1) the average erosion volume.

If one compares erosion quantitiesabove the combined storm tide to thoseabove mean sea level, it is apparent thatabout half the eroded sand volume originatesfrom above the peak storm tide level (50% ifone compares coefficients from equations (1 )and(4), and (3) and (5), and 55% from thedata). This should not be surprising from ageomorphic viewpoint, considering that ourbeaches and coasts have certain constrainingdimensions physiographically. It isrecognized that the efficiency of gravitationalacceleration is not only greater for steeperslopes when dealing with sand transport, but

(7)

(8)

Noting that pre4 storm profiles areseldom measured just prior to storm orhurricane impact, some physiographicdeviation might be reasonable to levy on aPDF in assessing a design maximum erosionvolume. This and purely random,anomalously high erosion volumes suggestthat, perhaps, a probability P of between 0.9and 0.95 would not seem inordinate toapply. Using a value of 0.925 andcoefficients from equations (1) and (4), theapplication of equation (6) yields thefollowing design relationships:

14

Table 3. TYPE I erosion volume above combined peak storm tide

Average Muimum Event

I. D. Event and Location&osion &osion LongevitynVolume Volume Parameter ¢> r.(m3/m) (m3/ml (m:l/ml

Sl Ash Wednesday Stonn, Mar. 1962,53.0 --- 4 149,327U. S. East Coast ..- ._-

S2 Nov. 1962 Stonn, U. S. East Coast 6.3 18.6 32 16,724 1.16 0.9953

S3 6 Nov. 1963 Stonn, U. S. East Coast 6.9 24.2 26 30,970 1.51 0.9552

S4 13 Jan. 1964 Stonn, U. S. East Coast 11.7 26.1 37 25,037 1.63 0.9841

S5 16 Sep. 1967 Stonn, U. S. East Coast 3.9 7.1 19 22,420 0.44 0.8918

5612 Mar. 1968 Stonn, U. S. East

5.8 18.6 37 9,919 1.16 0.9590Coast

57 12 Nov. 1968 Storm, U. S. East14.8 28.7 43 32,285 1.79 0.9879Coast

58 2 Feb. 1970 Stonn, U. S. East Coast 6.9 15.6 31 8,630 0.97 0.9559

S917 Dec. 1970 Stonn, U. S. East

5.8 15.1 42 27,724 0.94 0.9316Coast

S10 19 Feb. 1972 Storm, U. S. East CoastS10a New Jersey 12.0 22.8 23 18,977 1.42 0.9815Slab New York 7.6 15.7 38 22,462 0.98 0.9831

S11 17-22 Mar. 1973 Storm, U. S. EastCoast

S11a New Yo",- 7.5 16.4 17 22,102 1.02 0.9758Sl1b New Jersey 5.3 12.5 16 19,630 0.78 0.9909

S12Nov.-Dec. 1973 Events, Gennan

31.0 ._- ._- 92,944 .,. ...North Sea Coast

H4Hurricane Eloise, Sep. 1975, N. W.

16.0 29.8 72 39,628 1.86 0.9557Florida Gulf Coast

S14 14 Oct. 1977 Stonn, U. S. East Coast 15.5 31.6 22 43,085 1.97 0.9890

S1519 Dec. 1977 Storm, U. S. East

11.8 23.4 20 51,356 1.46 0.9890Coast

S16 6 Feb. 1978 Stonn, U. S. East Coast 12.3 30.5 17 42,979 1.90 0.9940

S17 No Name Stonn, 17-18 Jun. 1982, 14.0 25.8 24 21,111 1.61 0.9917Lower Florida Gulf Coast

S18Thanksgiving Holiday Storm, 21·24 14.6 32.4 128 52,388 2.02 0.9807Nov. 1984, Florida East Coast

H8 Hurricane Elena, Sep. 1985, FloridaGulf Coast

H8b Franklin County 10.3 31.6 34 54,456 1.97 0.9661Hac Gulf County 7.1 18.9 30 45,579 1.18 0.9958H8d Escambia County 4.2 11.4 58 34,653 0.71 0.9459

H9Hurricane Kate, Nov. 1985, N. W. 8.7 22.0 13 47,481 1.37 0.9247Florida Gulf Coast

Note: The time between pre-stonn and post·stonn surveys, and comments are given in Table 2; data sourcesare listed in Table 1.

15

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

0l-_-..I._--'---'-.................."'""""'"-li..L.-__..L..--..I._~

0.01 OJ» 0.1 0.5

tan ai

Figure 9. Tesselated relationship relating nearshore bedslope (tanai which occurs from 300 to 800 m offshore ofthe MSL shoreline) to the ELP coefficient f.

according to:

(9)

(10)4> = 2.07 + 13.2 tan "j .

The validity of 4J can be tested usingdata obtained from Hurricane Gilbert whichstruck Cancun, Mexico in September, 1986.While the accuracy of data for HurricaneGilbert is not touted to be of the standard forthe remainder of the data base presentedhere (and in particular for the Florida data),the magnitude of the event was sooverwhelming that it cannot be neglected;best known data are listed in Tables 1 and 2.A significantly important factor associatedwith the Gilbert data are the very steep

Data and fitted relationship leading toequations (9) and (19) are plotted in Figure 9.Results from equation (9) apply only wherethe initial or pre~impact nearshore bed slopeis greater than 0.01638; where the initial bedslope is less than 0.01638 the value of 4J isunity (i.e., 1.0). The final form of equation(3) now becomes:

where tan aj is the initial or pre~impact

nearshore bed slope, and:

6J8

,05 • Saville (1957) ,,/

a De11e and Uliczka (1987) /' '.. • Present study ",,'.

«1»3 p_ -o-pt/' ,___------- '" 'I' = (lanai) where

2 ~ 4» =2.07 + 13.2 tanai for tanai> 0.016

1 '" =12344""1 fortanaj> 0.016

due to inertial effects is lessresponse oriented under lower slopesubaqueous than steeper slope subaeriallittoral conditions. The result is a partitioningof sediment transport between kinetic energy(i.e., by virtue of low-slope, near horizontalmotion due to shore-normal subaqueoussediment transport mechanics) and potentialenergy (i.e., by virtue of subaerial elevationof dunes and bluffs and potentialgravitational mass wasting due to waveimpacts propagating upon an elevated waterlevel). Based upon this logic, it would appearthat the diminished effect of the accelerationof gravity is not unwarranted, because itprobably relates more to spreading ratesacross the nearshore than to dune or bluffmass wasting. The latter is essentiallyinstantaneous, while the former is time­consuming. In fact, the prototype wave tankresults of Dette and Uliczka (1987) appear toprovide some elucidating information. First,their results show that the pre-impactnearshore bed slope correlates with themagnitude of beach and c()ast erosionvolumes and the rate of erosion.Specifically, the steeper the pre~storm

nearshore bed slope, both the greater theerosion volume above SWL, and the fasterthe removal rate. Second, regular andirregular waves appear to erode the beachand coast at different rates.

Dette and Uliczka (1987)report prototype results for initialnearshore bed slopes of 0.25 and0.05, and Saville (1957) for aslope of 0.0667. U. S. East andGulf Coast natural nearshoreslopes (i.e., 300 to 800 moffshore) are, however,characteristically less than 0.02,averaging about 0.016 forFlorida. Application of these datarelative to f the PDF coefficientof equation (3), yields adimensionless proportionalityconstant 4J termed the offshoresinkefficiencyparameter(OSEP),

16

nearshore slopes off of Cancun as illustratedin Figure 10. In fact, the nearshore slope isover twice (i.e., 222%) as steep as slopescommonly found off U. S. East and GulfCoast nearshores. Such a slope ;s steepenough that sand is not able to betransported back onshore during post-stormconditions. Hence, the steep offshore slopebecomes, for all practical purposes, asediment sink. Given the following data forHurricane Gilbert:

tan Uj = 0.0363,

t, = 9.5 hours,S = 3.81 m,

P = 0.68 (average erosion volume),P = 0.925 (maximum erosion volume),

steeper nearshore and increased value of theoffshore sink efficiency pa/'Bmeter is theproduct of the ELP and OSEP, resulting in avalue of 231,462 m3/m. The goodness of fitof this result is illustrated in Figure 2.Moreover, equation (1 1) results in an averageerosion volume (i.e., P = 213) of 144.5 m3/mwhich is very close to the measured amountof 144.7 m

3/m, and a maximum erosion

volume (/:e., P = 0.925) of 313.6 m3/mWhich is within 5.6% of the measured valueof 297 m3/m.

The final form of equation (5) forvolumetric erosion above the peak storm tidelevel becomes:

(12)

then:

and:

ELP = 89,782 m3/m,OSEP = 2.578,

e3P = e3

(2/3) = 7.3891,

and,

e3P = e3(0_925) = 16.0386.

where by similitude, it is assumed that theOSEP applies straightforwardly as in equation(11) (field data are needed, however, forconfirmation) .

,Nearshore geometry is now commonly

quantified by a power curve (Dean, 1977;Hughes, 1978; Balsillie, 1982a, 1987) givenby:

The adjusted ELP due to the effect of the(13)

in which d is the water depth, andx is the distance offshore. Usingthe data of Saville (1957), Detteand Uliczka (1987), and averagedata for Florida, tan Uj may beapproximately related to the shapecoefficient (Dean, 1977), as'according to:

- ,.,,1.,.1 CMlCUlI 'rolUe---- Fit.." c__ ._ c.ww. "0111.-_•. - typic.' FI....'. '-r Curw. "0'10

_._-----.._-------------. -._------- -'-- _.---- tana, ::0 0.5 8.3(2 (14)

-200~L--l--20,-LO---'--~_-:---..J...-~60::-0_..i.--::lIOO=---L_-;;,oooDI.,...c. (Ill'

Figure 10. Comparison between a typical Roridanearshore profile and a typical Cancun, Mexico nearshoreprofile. -

17

illustrated in Figure 11 (as inequations (1 1) and (12) has unitsOf m'/3. if a is in units of ft l /3, smultiply the value by 0.673 toobtain consistent S. I. units).

II!?C!-,

Using equations (15) and (16), the

Return Pedod VolumetricErosion Events

where m is the ranked value. If the theorydoes hold, the points should plot as astraight line on probability paper. The returnperiod Te is then given by:

• Saville (1957)oDette and Uliczka (1987)• Present Study

0.1

all/

//

//

//

//

I

~/\I "'" 3/201 0 tanaj " 0.5 as

II

II///I,

III0.01 ~~-..L--J.-..L..---JL....-....L.._L-...J

o ~ ~ ~ ~ ~ ~ v ~

tan a j nos

as cm'/3 ,

Figure 11. Relationship between the initialnearshore bed slope (tan aj occurring 300 to800 m offshore of the MSL shoreline) andthe power CUNe fit shape coefficient, as'

plot of Figure 12 is constructed using datafrom Table 2. Only Atlantic Ocean eventsare considered in this analysis. There are 35events listed in Table 2 which apply. Theseevents occupy a 34·year period from 1957through 1990. During this period some 324tropical storms and hurricanes formed in theAtlantic. Of these, about 104 (or 32% of thetotal) landfalling or exiting events affectedthe Americas along the U. S. East Coast, andGulf of Mexico coasts of the U. S. andMexico. It is assumed that the applicable 35events of Table 2 represent a random sampleof erosion conditions. The 35 events,however, represent only one-third of theactual number of events that affectedcoastal reaches. Therefore, for analyticalpurposes, the 35·event sample is"triplicated" to yield 105 events (i.e., tripledin size· to more nearly represent the 104events that actually occurred); only the mid­point of each "triplicate" is plotted to

(15)

(16)T~=_..:.....l_1 - p.

The frequency Pe used in plotting thedistribution is found (Gumbel, 1954) byranking the erosion volumes from smallest tolargest and then dividing the rank of each ofthe sample size plus one, i.e.:

P = m 1~ n + 1

The incidence of extreme phenomenamay require site-specific treatment. Such isthe case with the determination of the returnperiod storm tide which is dependent notonly on historical storm/hurricanecharacteristics and water levels, but also,importantly, on local conditions such asoffshore and nearshore bathymetries. Amajor problem in following such an approachfor erosion responses is that site-specificquantitative erosion data are historicallydeficient. However, since uncertaintiesabout erosion make simplified considerationsthe most appropriate (Hallermeier andRhodes, 1986), and because of the apparentsuccess of foregoing quantitative results, it isassumed that physiographic responses tostorm attack need not be held to asite·specific treatment.

Further, it has been a major tenet ofthis and other works (Balsillie, 1985c, 1986)that the storm tide return period event andthe storm erosion return period event areseldom coincident. Until now there has beeninsufficient information on which to specifythe probabilistic erosion event.

18

0.9990.9980.9950.990.98

0.95

0.9

0.8P

0.70.60.50.40.30.2

S.gm.nt C:

-g 6.858.5 x 10 Q ••vg

T. ,..If - 0.982')

• T,.. ...... M_ Ud. ro.. _. _ ....en,.,o••• nIc:..........- - - - -\ ".".'ID.. __ P.olll•••••,,__"'-d o.

\~~~ ......tIng~~..=h~..:.oa,:,~.:=,a:.... _II

Til IO.ID did lID••1.. __ II .,..'.,0••' _p......•••" bul p.......d '0 10 "oth "" _ "D•••••0 Dr .,.. p.o." ••• ftoOll ...

T..........'arm ..... _ IIOt ,_ ......... _ ,Goa., _poIItt......tloa and tlltIllO' p.,,,.,, '.-uncI III .,...., onlY.

----- ------------- --------

S.....nl A:

1.251 + 0.006 O. evg

T.....

S.gm.nt B:2.49

0.00033 O. avgT. ,..

1000500200100SO

20

Te10

5(years)

3

2

1.25

0.1

0.05~-..l.L----l-----'-.....l.-.....L.:-....L.-...J..-...L...-..L...-~-.L....-L...........I-.....L__.:.JoB:::J0.02o 50 100 150

Q e avg (m 3/m)

Figure 12. Relationship between exceedence probability P, return period T., and averageTYPE I erosion volume above MSL.

By incorporating results from equation (6),the design maximum erosion volume (i.e., forP = 0.925) results in a factor of 2.1 and:

(21 )

(19)

(20)

Q. IIfIg = 60 ((In T.) - 1] 0.8

Q._ = 126 [(In T:) _1]°·8

For segment B of Figure 12, whichdescribes events between about 1.25- and 4~

year return occurrences, the return period isgiven by:

0.00033 Q~'~T. = e

for which equations corresponding to (18),(19), and (20), become:

represent the associated probability andreturn period. It is noted ~at threestraight-line segments are apparent for whichpossible explanations have been suggested(see Figure 12). Equations of immediateinterest for coastal construction designpurposes are:

1 + 0.006 Q 1.25"-tJ (17)

T" = efor segment A which describes extremeevents with a frequency less than about a 4­year return period, where Q e 8Vg is specifiedin cubic meters per alongshore meter ofbeach or coast (note: m3/m = 2.508(yd3/ft)). Utilizing, by substitution, equation(6) the corresponding probability of equation(17) is given by:

(1.25 )-1Pili = 1 - e1

+ 0.006 Q,.", (18)(22)

Further, by rearranging equation (17), thereturn period erosion quantity in mJ/m maybe determined according to:

Q••vg = 25 ((In T.) - 1] 0.4016

and:

(23)

19

06 max = 53.5 [( In T6) - 1] 0.4016 (24)

Following this methodology, similarequations may be developed for segment Cthat represent events occurring more oftenthan the 1.25-year return period (see Figure12).

There is simply not yet sufficient fielddata to reliably determine return periodvolumetric erosion events for erosion abovethe peak combined storm tide level (inparticular for that portion corresponding tosegment A of Figure 12). However,statistics indicate that erosion volumes abovethe peak storm tide level, on the average areabout one-half those above MSL. Hence, inthe interim, a reasonable estimation may bedetermined by doubling the value ofQ'e avg and using equations (17) through(24).

The quantifying equations developedin this section are of special consequence.Past return period damage elements havebeen assessed in terms of forces, specificallythe combined storm tide elevation and waveheights. Now, for the first time, a returnperiod response element in terms of erosionis provided which accounts for all the forceelements, inclUding longevity of the event. Itis envisioned that these equations will behighly valuable in design and coastalmanagement activities.

One might be inclined to believe thatthe developed approach is based upon broadassumptions (e.g., global continuity in littoralphysiography) and a limited sample size.Recognize, however, that errors creep intodesign computations due to assumptionsabout convoluted littoral processes. Atpresent, and at a minimum, equations (17)through (24) would seem to provideinformation as a valuable check for the moreinvolved design computations (methodologyfor application of volumetric erosion volumesis discussed in the conclusions).

20

It is, however, notable that Figures 11and 12 support the significance ofphysiographic zonation between the beachand coast.

Post-Storm Recovery

There seems to be considerableinterest among coastal scientists andengineers in post-storm littoral recovery,even though we are just now quantifyingdetails about magnitudes of physiographicresponses during the "height" of extremeevent impact. While there exists somequantifiable representation of such recovery(Balsillie, 1985d, in manuscript), additionalwork remains. Generally, based on what isknown about littoral processes, we canendeavor to find discernible and logicalconclusions about such recovery. Again, itbecomes of importance to delineate littoralsubzones (see Figure 1), namely, ... 1. thenearshore, 2. the beach, and 3. the coast. Itis these three subzones which interactivelydefine the extent of both extreme eventimpacts and what are discernibly "norma'" or"day-to-day· littoral processes.

The nearshore, which is alwayssubject to the effects of astronomical tidesand waves, is expanded when a rising stormtide encompasses the beach, and, underdesign conditions, the coast. That longshorebars are formed during extreme event impacthas been a controversial issue. The problemis, of course, that nearshore subaqueousbehavior has not been adequately monitoredto yield confident quantification duringextreme event impact. However, based onadditional considerations and tested data(Balsillie, 1984c, 1985d), and fieldobservations (Dette, 1980; Birkemeier, 1984;Sallenger and others, 1985), the formation oflongshore bars during extreme event impactseems more nearly to be the case.Ramifications of the concept are not onlyessential towards a new understanding ofcoastal engineering design constraints thatmight be required, but of interactive littoral

21

forces and responses that could occur duringextreme event impact (bearing in mind thatextreme prospects are probabilistic).

Further, longshore bars are nature'sown protective device. During storm actionthey not only are formed but move offshore(Short, 1979; Birkemeier, 1984; Mason andothers, 1984, Sallenger and others, 1985),causing storm waves to break furtheroffshore than would normally occur. Byinducing breaking they cause the greatestamount of energy dissipation that waterwaves can experience and, should wavereformation occur, significantly reduce theelevation of destructive wave energy V.e.,reformed wave heights are attenuated; Carterand Balsillie, 1983; Balsil/ie 1984b, 1985b}.

During storm impact, the width of thesurf zone dramatically increases. When,following impact, surf width again attains"normal" width the bar(s) within the•normal" surf zone move onshore in a fewdays. Outer bars either remain as relictfeatures or disappear, although the latterrequires months to occur (Birkemeier, 1984;Mason and others, - 1984; Sallenger andothers, 1985).

Beach (or shore) recovery appears tobe considerably more rapid than has beenpresupposed by many coastal engineers.Although complexities occur (e.g., longshoretransport) which can produce a large range invalues, it is now quite clear that beachrecovery often occurs within days.Birkemeier(1979)found for the 19 December1977 U. S. east coast storm (event S15) thatfrom 38% to 100% beach recovery occurredwithin one or two days following eventimpact. Bodge and Kriebel (1985) also reportrapid recovery for beaches following impactof Hurricane Elena in Pinellas County, Florida(event H7a). Such rapid beach recoveryagrees with response time scales ofpost-storm nearshore profile changes.

The coast is of special interest

because it is detrimentally affected onlyduring extreme event impact (or man'sactivity). Where high sandy dunes or bluffsexist, the coast affords substantiveprotection to the upland. It is nature'sphysiographic reserve of particulate mass,drawn upon to replenish the more activebeach subzone, when beach subzonedimensions are diminished.

Of the three sub-zones, the coast inits natural state can be expected toexperience no immediate recovery. Anexample is Dauphin Island, Alabama struckby Hurricane Frederic in 1979, destroyingdunes which attained heights of up to + 10m MSL. Average volumetric dune losseswere about 50 m3/m. Assuming the sandsupply is available and that vegetation isinstrumental in natural dune reconstruction,then based on the data of the U. S. Army(1984) and Dahl and others (1975), naturaldune reconstruction would require 70 to 75years for American Beach Grass and SeaOats, respectively, and 180 years forPanicum (Balsillie, 1979a).

APPUCAnONS

The results of this work deal withvolumetric erosion of the beach and coastdue to extreme event impact. Thiscomprises, however, but one aspect ofinterrelated natural processes in terms offorce and response elements that occur

. within nearshore, beach, and coastsubenvironments of the littoral zone. Otheraspects include storm wave activity which isinstrumental in causing the erosion,producing dynamic and impact loads onexposed structural members, and forminglongshore bars that house sand eroded fromthe beach and coast. These various aspectsare quantified and discussed in a series ofpapers, the sum total of which actuallydescribe the entire Multiple Shore-BreakingWave Transformation Erosion computermodel (Balsillie, 1984c. 1985d). Thisapproach allows one to more succinctly

manage research by dealing with discrete orsets of discrete natural process units, andalso facilitates updating of each manageableunit as new developments are made. Evenso, it is recognized that some guidancewould be helpful to describe how thepredicted volumetric erosion can bepractically applied.

Post-Storm Beach and CoastPhysiography

The problem in applying volumetricerosion quantities, is the determination of theresulting physiography of the profile. For thetwo~dimensional case, the followingsimplified methodology is suggested asillustrated in Figure 13 (discussed by Balsillie1984c, 1985d). Following determination ofthe design erosion volume, plot the pre­impact coast, beach, and nearshore profile.The nearshore profile shape in Florida can bedetermined using the power curve formaccording to Balsillie (1982a, 1982b, 1987).Plot the bar crest envelope, dbci'V.e., the lineconnecting the crests of longshore barsformed during the event) and thecorresponding bar trough envelope, dbt V.e.,the line connecting the bar troughs,according to:

AB lying above the nickpoint of Figure 13)has a 1 on 1 slope. The segment Be is aslightly curved line smoothly continuing thebar trough envelope to the nickpoint (wherethe coast is flooded only segment BCapplies). Starting at the pre-impact shoreline,segment ABC (or segment BC where thecoast is flooded) is iteratively movedlandward until the erosion volume is attained(shaded area of Figure 13).

Nearshore wave heights aredetermined using the bar crest envelope torepresent the water depth at breaking, db(Balsillie, 1983b, 1984b, in press). Theamount of the breaking wave height lyingabove the peak storm tide still water level,Hb', has been determined from field data(Balsillie, 1983d, 1985b, in press) to begiven by:

(27)

in which Hbx is the average height of thedesired moment measure. The breakerheight envelope illustrated in Figure 13,represents the significant height. Relatingequations developed by Balsillie and Carter,1984a, 1984b) for other moment measurescommonly used in design work are:

where S is the peak combined storm tide, asis the shape coefficient given by Balsillie(1982b) for Florida, and Xbc is the distanceoffshore measured from the pre-storm MSLshoreline, and:

where Hb rms is root-mean-square breakerheight, and Hb is the average breaker height;

(28)

(29)

in which Hbs is the significant breaker height(i.e., average of the highest two-thirds of theheight record);

(25)

(26)

where Xbt is the distance offshore measuredfrom the pre-storm MSL shoreline.

(30)

Inspection of post-storm profilesindicates that the portion of the erodedprofile above the peak storm tide (segment

where Hb10 is the average of the highest10% of the wave record; and:

22

10

Me••ured De.ePre-Storm Profile

- - - - Post-Storm

-----

~"iCi±"ffi+:±+~"""IO;:::-------------- PST SWL-----t

MSL = M_n Sea LevelPST SWL =: Peak Storm Tide Still Wate, Level

[ITJ Eroded Volume above MSt.

Predicted Data-._._._ Post-Storm Erosion Profile---- Ber lrough Profile_ ..__.- - ear Cr••t Profl'•.......-.......... Significant Br••ker Height Envelope

- 5~CI)

:..!.I:.2­•>.!! 0w

-60 -50 20 2$

Dlatance from Pre-Stonn ShCM'eUne (m)

Figure 13. Example of application for determining two-dimensional post-storm physiographyusing volumetric data, and design wave conditions.

(31 )

in which Hb1 is the average of the highest1% waves of record.

statistics to the design life of a project.What we really wish to do is transform thereturn period statistic to one of encounterprobability, based upon a specified encounterperiod.

Encounter Period and Probablity

A return period statistic is oneproviding a measure of the probability ofannual occurrence. For instance, an eventwith a 100-year return period has aprobability of 0.01 or a chance of 1%occurrence in any given year, an event witha 5-year return period has a probability of0.20 or a 20% chance of occurrence in anygiven year, etc. Even if the return periodoccurrence occurs during an annual period,its probability of recurrence remains the samewithin the current annual framework.

The solution is the use of Figure 14.The abscissa of Figure 14 gives theEncotmteTPeliod which is the period of timefor which a project is to last (i.e., its designlife). In the case of single-family dwellingdesign, the encounter period might be 50years representing a depreciation period fortax purposes, etc. The ordinate of Figure 14gives the Ent:ountet' Probability whichrepresents the assigned return period equaledor exceeded during the selected EncounterPBIitHI. Curves internal to the graph are forvarious Retum Pe/iods associated with thedesign event.

The above often leads to confusion,particularly when one tries to relate such

Following is an example of how to usethe figure. Suppose that you would like to

23

I 1 I 1 / V ~Ioo' /I""'" V I""'"

~~~Lr_Return Period /" I.-' /

(Years) ~ / / II V/

v )"/ I'"

" 1I / / IIii' / I V IIl"'iI. 1I

1/' or7 V )1 V V V ~... "1/ 1/ ;tr 1/ V / / V~ r-,,§! j

/ f7 V~,,' ~J V- II ~ 1/"" ~~r! J

/ ./V ~v V )~ v

ll!/ .,~O'~ lJ'

V L/ L,.- / ./v 1,.;1'

1,.01.0"..-/~ ~

~ l...,...-' V L-L.- 7 -',,/ I.---' I.-'

"" ..L..ol,..o ~ loo"

~ 1..---'1-"".....1,..o~~--

1.0

>- 0.8=:aIID

0.60...a....I)- 0.4~:I0U~

W 0.2

o1 5 10 50 100 500 1000

Encounter Period (Years)

Figure 14. Nomograph for relating event return period, encounter period, andencounter probability.

build your single~family beach~fronting

dwelling so that it is relatively safe from the1DO-year return period erosion-event. Theprobability of a 1DO-year return periodoccurrence being equaled or exceeded duringthe above assigned 50~year period (i.e.,Encounter Period) is 0.4, as illustrated inFigure 14. Hence, there is a 40% chancethat the 1OO-year return period erosion eventwill occur in the planned life time of thehome. Had the dwelling been designed fora SOO-year return period erosion event, thestructure would have a much better chanceof surviving the critical event ... then only a10% chance of occurrence during its plannedlife.

Using the figure in another manner, ifa homeowner or prospective home owner iswilling to take a 20% chance that the designerosion event will occur during the 50-yeardesign life of the structure, then the RetumPetiod of the erosion event that should bedesigned for is 250 years.

The above example uses the returnperiod erosion event. However, Figure 14

24

can also be used for any other measure (e.g.,peak combined storm tide, wave event,event forward speed, etc.) provided thatreturn period statistics are quantified.

An Erosion Damage Potential Scale

A beach/coast erosion damage scalefor extreme events has not, here-to·fore,been proposed. Perhaps the best way inwhich to assess an erosion damage potentialscale is to build upon the existingSaffir/Simpson hurricane damage potentialscale (Table 4). Volumetric erosion isassessed using equation (1) for averageerosion quantities and equation (7) formaximum erosion' quantities. Theassessment of Table 4 is, therefore,applicable to the U. S. Atlantic East Coastand the U. S. Gulf of Mexico Coast whichhave relatively low nearshore slopes (i.e.,where tan Qj is characteristically less than0.02). Equations (1) and (7) were evaluatedusing the Saffir/Simpson peak storm tide(commonly termed the ·storm surge·)classes of values. Event forward speedclasses were determined using the historical

Table 4. Amended Saffir/Simpson Hurricane Damage Potential Scale

PeakEvent

StormAvera"e MaximumCentrel Wmd Storm Tide Tide

Category Pressure Speed ElevetionForward

RiseErosion Erosion Damage

Speed Volume Volume Potential(mb) (kmlhr) above (kmlhr) Time(m3/m) (m3/m)MSL(m) (hr)

1 >980 46-59 1.22-1.68 50·90 2.5-4.5 3-8 6.5·17 Minimal

2 965-979 60-68 1.68-2.60 30·50 4.5-7.5 8-25 17-53 Moderate

3 945·964 69-81 2.60·3.81 20·30 7.5·11 25·63 53-132 Extensive

4 920-944 82-96 3.81·5.49 10·20 11·22 63-188 132-395 Extreme

5 <920 >96 >5.49 <10 >22 >188 >395 Catastrophic

data of Schwerdt and others (1979). Stormtide rise time was then determined usingequation (2).

The Saffir/Simpsonscale assessed thedamage potential in terms of the wind speedand peak. storm tide. There is, in fact, soundreasoning for doing so, since both are largelydependent on event central pressure.

The same is not true of the eventforward speed because the three·dimensionalgeometry of surrounding weather systemsand conditions affect steering currents.Hence, factors other than central pressurehave significant effect on the propagation ofa hurricane.

There are two additional issues to beconsidered.

One is that it may be difficult toenvision just what a volumetric erosion valuemeans in terms of erosion damage for aspecific coastal locality, unless cross­sections representing pre-storm and post­storm profiles are assembled. A horizontalrecession value rather than a volumetricerosion value is an alternative, but this wasfound to result in many more problematiccomplexities than the volumetric approach(Balsillie, 1985c, 1986). Hence, whilevolumetric erosion values may not obviouslyidentify the damage potential, they can becorrelated to the SaffirlSimpson hurricane

25

category and damage potential scale toprovide a pragmatically useful addition to thescale.

The other issue centers about the factthat extreme events with much lowerintensities than hurricanes (e.g., tropicalstorms, which are here identified under thecollective term ·storms") can potentiallyresult in as much or more erosion than manyhurricanes (see Table 2). An example is astorm which essentially stalls just offshorefor days. Hence, Figure 15 has beencompiled which, based on event forwardspeed and peak. storm tide elevation, can beused to assess erosion damage potentialwhether the event is a hurricane or a storm.

Table 4 and Figure 15 are transformedto British Imperial Units and given in theAppendix.

CONCLUSIONS

Analyzed information for storms (e.g.,Birkemeier and others, 1988; Kana andJones, 1988; Jones and Kana, 1988; Beumeland Campbell, 1990; Ferriera, 1994) andmore recent hurricanes (e.g., Birkemeier andothers, 1991; Stauble and others, 1991 ;Nelson, 1991) has increased the existingsample size of Balsillie (1985c, 1986) forfield data quantifying beach and coasterosion due to extreme event impact. Thisadditiona I data allows for testing of a

· Peak Storm Tide Elevatlo.n (m MSL)

0.5 1 1.0 j 1.5 ~ 2.0 j 2.6 ~ 3.0 i 3.5 1 4.0 : 4.5 ; 5.0 ; 5.5

Figure 1.5. Beach and COIIst erosion damage potential scale as afunction of event forward speed at lanclfal and peak storm tideelevation. &osion volumes are based on peak storm tideelevation classes of Table 4; even so, results apply to stormevents as wei as hunicanes.

refinement of quantifying relationships.

A most important aspect of being ableto predict beach and coast erosion due tostorm and hurricane impact is the capabilityto assess profile geometry during and as aresult of impact. By so doing, coexistingstorm-generated wave activity propagatingupon the storm tide surface can be assessedfor management and design purposes. Thefact remains, regarding waves and theirmodifying influence on a mobile bathymetry,that any change in wave characteristicsinduces an alteration in bathymetry but at a

26

lag-time behind a change in wavecharacteristics. Because of the bathymetriclag-time, bathymetry can in turn imposesignificant influential effects on the characterof littoral wave activity. Hence, in additionto erosive outcomes, it is the destructivepotential of storm-generated wave impactsthat also must be considered if a successfulassessment methodology is to exist.Determination of profile geometry is then amatter of modeling interactive littoralprocesses, that is, both force (e.g., waterlevel rise and waves) and response (e.g.,profile modification) elements. A computer

model exists (Balsillie. 1984c. 1985c.1985d. 1986) in which a bulkonshore~offshore sediment transportmechanism, in terms of bedform movementhas been developed (Balsillie, 1982a, 1982b,1984b, 1984c), which is dependent onlittoral wave activity (Balsillie, 1983a.1983b, 1983c, 1983d, 19848, 1984b.1984c, 1985b; Balsillie and Carter, 1984a,1984b). It is the volumetric erosionmethodology contained herein which allowsfor the real~time calibration of the combinedassessment of combined storm tide, stormwave impact, horizontal and verticalphysiographic recession force and responseelements due to extreme event impact. Inaddition, there now appears to be enoughinformation to make a statement about thereturn period erosion event. Least equivocalresults given by equations (17) through (24)will, hopefully, be refined by future work. Inthe meantime, however, they are valuable asa check in design applications.

In addition, applications of thevolumetric erosion methodology have beendiscussed, including the determination ofpost-storm beach and coast physiography,encounter period and probability, and anerosion damage potential scale.

ACKNOWLEDGEMENTS

Robert J. Hallermeier with Dewberryand Davis, Inc., Washington, D. C., identifiedseveral storm erosion events not included inearlier versions of this work, and reviewedthe manuscript. The review and comments ofWilliam A. Birkemeier, CERC, are gratefullyacknowledged.

An extensive and valuable review ofthe manuscript was conducted by the staffof the Florida Geological Survey. Thecontributions of Jon Arthur, Paulette Bond,Ken Campbell, Ed Lane, Jacqueline M. lloyd,Deborah Mekeel, Frank Rupert, Thomas M.Scott, and Walter Schmidt are gratefullyacknowledged.

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33

APPENDIX

Table 4 and Figure 15 of main text transformed to British Imperial Units of Measure

35

r

Amended SaffirlSimpson Hurricane Damage Potential Scale

PeakStorm

Centr.l1 WDIStorm Event rKie Average Maximum

e.te-Pressure Speed

rKie Forwardlise Erosion Erosion Damage

gory(Inches) (mph)

Bention SpeedTme Volume Volume Potential

.bove (mph) (yds31ft) (yds31ft)MSL (ft)

(Iv)

1 >28.94 74-95 4-5.5 31-55 2.5-4.5 1.2·3.3 2.5-7 Minimal(>980)"

2 28.50·28.9196-110 5.5-8.5 18-31 4.5-7.5 3.3-10 7-21 Moderate(965-979)

3 27.91·28.47 111-130 8.5-12.5 12-18 7.5-11 10·25 21-53 Extensive(945-964)

427.17-28.88

131-155 12.5-18 6.5·12 11-21 25-75 53·158 Extreme(920-944)

5 <27.17 >155 >18 <6.5 >21 >75 >158 Catastrophic(<920)

-Central pressure in parentheses are In millibars.

Peak Storm Tide Elevation (ft MSL)

: CATASTROPHIC.......~.* '!+*•••**+..~+-~+ ++~.+ +••

55

50

4S MINIMAL

40

35

30

25

20

15

12

10

2 ! 4 j 6 ~ 8 j 10 ~ 12 ~ 14 ~ 18 ~ 18 j 20

37

1

:2Q.

E'D11.ICb~

rIJ

'EIII

~o

LL­l:Cb>

W 6

Beach and coast erosion damage potential scale as a function of event forward speedand peak storm tide elevation, both at landfal. &osion volumes are based on peakstorm tide elevation classes of above table; results, however, apply to storm events asweI as hurricanes.