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The effect of tidal inlets on open coast storm surge hydrographs

Michael B. Salisbury a,1, Scott C. Hagen b,⁎

a Water Resources Staff Engineer, Ardaman and Associates, Inc., 8008 South Orange Avenue, Orlando, Florida, 32809, USAb University of Central Florida, Department of Civil and Environmental Engineering, 4000 Central Florida Blvd., Orlando, Florida, 32816–2450, USA

Received 25 January 2006; received in revised form 11 September 2006; accepted 12 October 2006Available online 29 November 2006

Abstract

Bridge scour modeling requires storm surge hydrographs as open ocean boundary conditions for coastal waters surrounding tidal inlets. Theseopen coast storm surge hydrographs are used to accurately determine both horizontal and vertical circulation patterns, and thus scour, within theinlet and bay for an extreme event. At present, very little information is available on the effect that tidal inlets have on these open coast storm surgehydrographs. Furthermore, current modeling practice enforces a single design hydrograph along the open coast boundary for bridge scour models.This study expands on these concepts and provides a more fundamental understanding on both of these modeling areas.

A numerical parameter study is undertaken to elucidate the influence of tidal inlets on open coast storm surge hydrographs. Four different inlet–bay configurations are developed based on a statistical analysis of existing tidal inlets along the Florida coast. The length and depth of the inlet areheld constant in each configuration, but the widths are modified to include the following four inlet profiles: 1) average Florida inlet width; 2) 100 minlet width; 3) 500 m inlet width; and 4) 1000 m inlet width. Results from these domains are compared to a control case that does not include anyinlet–bay system in the computational domain.

The Advanced Circulation, Two-Dimensional Depth-Integrated (ADCIRC-2DDI) numerical code is used to obtain water surface elevations forall studies performed herein. The code is driven by astronomic tides at the open ocean boundary, and wind velocities and atmospheric pressureprofiles over the surface of the computational domains. Model results clearly indicate that the four inlet–bay configurations do not have asignificant impact on the open coast storm surge hydrographs. Furthermore, a spatial variance amongst the storm surge hydrographs is recognizedfor open coast boundary locations extending seaward from the mouth of the inlet.

In addition, a storm surge study of Hurricane Ivan in the vicinity of Escambia Bay along the Panhandle of Florida is performed to assess thefindings of the numerical parameter study in a real-life scenario. The main conclusions from the numerical parameter study are verified in theHurricane Ivan study: 1) the Pensacola Pass–Escambia Bay system has a minimal effect on the open coast storm surge hydrographs; and 2) theopen coast storm surge hydrographs exhibit spatial dependence along typical open coast boundary locations. The results and conclusionspresented herein have implications toward future bridge scour modeling efforts.© 2006 Elsevier B.V. All rights reserved.

Keywords: Tidal inlets; Storm surge hydrographs; Bridge scour; Shallow water equations; Hurricane Ivan

1. Introduction

The design of coastal bridges is governed by a number offactors: wind, moving (vehicular), and hydrodynamic loads, toname a few. In particular, the coastal circulation patterns areimportant in determining the amount of scour that occurs duringextreme flow events (e.g. hurricane storm surge). At present,

local three-dimensional models are used to estimate bothhorizontal and vertical circulation patterns, and thus bridgescour, in the vicinity of coastal bridges. Typically, these modelsencompass the bay system where the bridge is located andextend seaward to shallow ocean regions beyond tidal inlets.

The magnitude for the design surge event (e.g. 50-yr, 100-yr,or 200-yr surge event) used to force a local bridge scour model(as used herein, the term bridge scour model refers to any highresolution, three-dimensional circulation model that can beapplied to compute bridge scour) for a particular area is quitevaried between government agencies (Sheppard and Miller,2003). As a result, it is necessary to elucidate the behavior of

Coastal Engineering 54 (2007) 377–391www.elsevier.com/locate/coastaleng

⁎ Corresponding author. Fax: +1 407 823 3315.E-mail addresses: msalisbury@ardaman.com (M.B. Salisbury),

shagen@mail.ucf.edu (S.C. Hagen).1 Fax: +1 407 859 8121.

0378-3839/$ - see front matter © 2006 Elsevier B.V. All rights reserved.doi:10.1016/j.coastaleng.2006.10.002

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hurricane storm surge hydrographs along the coast. These opencoast storm surge hydrographs will be generated by a large-scale ocean circulation model and used as ocean boundaryconditions for near-shore, high resolution models that includethe inlet and bay system. These local, three-dimensional modelswill use the boundary conditions to better compute the hori-zontal and vertical flow patterns within the bay system forprediction of bridge scour. In the future, it is hoped that bygenerating these open coast storm surge hydrographs, a moreaccurate depiction of the effect of storm surge on bridge scourcan be formulated.

Two issues, however, arise when generating these open coastboundary conditions. First, the detail of the coastline resolutionin the ocean circulation model becomes an issue. The Floridacoast is abundant with tidal inlets that allow for water to con-tinuously circulate through embayment systems. This hydraulicconnection provides a conduit for storm surge to enter the baysystem during a hurricane event. Incorporating all of the inletand bay systems along the Florida coast into the model domainis an arduous task at best and it significantly increases thecomputational nodes included in the model. Therefore, it isnecessary to elucidate the effect, if any, that tidal inlets have onthe open coast storm surge hydrographs. In order to accomplishthis, a numerical parameter study is performed by employingvarious idealized inlet profiles that are representative of Floridatidal inlets. Each idealized inlet mesh is forced with a syntheticwind field and pressure profile that is representative of Hur-ricane Ivan (September 2004) and the results of each simulationare compared to one another. Furthermore, the conclusions fromthe numerical parameter study are verified for Hurricane Ivannear Pensacola, Florida. By doing this, coastal modelers will beable to determine which inlets need to be included in the coastalcirculation model, such that accurate open coast storm surgehydrographs can be generated.

Second, proper application of the open coast storm surgehydrographs to a local circulation model is critical for the pre-diction of scour levels within the inlet and bay. Current modelingpractice enforces a single design hydrograph along the oceanboundary of local two- or three-dimensional circulation models.This methodology, however, is inherently flawed because thechange in bathymetry along the ocean boundary creates varyinglevels of surge along the coast. The use of a single designhydrograph does not incorporate this effect along the open coastboundary. In lieu of this, the spatial variance of the open coaststorm surge hydrographs is examined in both an idealized settingand a Hurricane Ivan storm surge study. The results andconclusions of this study have implications toward moreaccurate bridge scour modeling in coastal areas.

1.1. Coastal scour modeling

Coastal bridges are subjected to foundation scour as a result ofcirculation patterns found in the bay or estuary. Scour may occuras a result of density stratification, water salinity, freshwaterriverine inflow, or astronomic tidal currents (Richardson et al.,1999). Under design conditions, these circulation patterns areoften computed based on water elevation data during an extreme

flow event (e.g. hurricane storm surge). Typically, this waterelevation data is obtained either through a deterministichydrodynamic model or a stochastic formulation.

Traditionally, hydrodynamics within an estuary are computedusing local-scale, two- or three-dimensional models (Zevenber-gen et al., 1999). The response of the model near the bridge is afunction of the applied boundary conditions, which include opencoast storm surge hydrographs. The applied open coast stormsurge hydrographs are a function of peak water surfaceelevation, rising limb time, duration of peak, and falling limbtime. The sensitivity of water currents in the model to the changein open coast hydrograph parameters has been well documentedby Sheppard and Pritsivelis (1999). The results show that modelresponse is very sensitive to the peak water surface elevation andthe duration of peak, but less sensitive to the falling limb time.Hence, the accuracy of the model is heavily dependent on theapplied open coast boundary conditions.

In the past, peak water surface elevations were obtained fromsurgemodels developed by the Federal EmergencyManagementAgency (FEMA) and the National Oceanic and AtmosphericAdministration (NOAA). FEMA employed a two-dimensional,finite difference model (SURGE) to compute maximum surgeelevations along the coast. NOAA also employed a two-dimen-sional, finite difference model (SLOSH) that computes peaksurge levels based on each class of hurricane. In both cases, asignificant number of storm surge simulations are performedbased on varying degrees of hurricane intensity and hurricanetrack. The results lead to maximum envelopes of water (MEOW)along the coast for use by consultants and emergency managers(Zevenbergen et al., 1999).

In view of the fact that only peak values are provided in theMEOW, not the full storm surge hydrographs, Cialone et al.(1993) report a procedure for developing the full hydrographbased on maximum surge levels. The full storm surgehydrograph is computed as follows:

StotðtÞ ¼ Sp 1−e−jDT−tj

� �þ HtðtÞ ð1Þ

where, Sp=peak surge height, D=storm duration (defined asthe radius to maximum winds divided by the storm's forwardspeed), T=time to peak surge, t=time, and Ht(t)= the daily tidecomponent. If the daily astronomic tides are excluded from theequation, then the storm surge hydrograph is symmetric abouttime T. In the absence of more accurate computer generatedstorm surge hydrographs, this equation can be used to developthe open coast storm surge hydrographs used for boundaryconditions in bridge scour modeling.

Previous studies have applied this methodology (i.e. applyinga single, synthetic hydrograph along the open coast boundary) instudying the influence of boundary conditions on velocitiesthrough the inlet and near bridge piers (Edge et al., 1999;Sheppard and Pritsivelis, 1999; Zevenbergen et al., 1999). Thereare two drawbacks, however, to using this single hydrographapproach. First, Eq. (1) produces a simple hydrograph that doesnot consider the influence of wind over time. As the hurricanetraverses the coastline, the change in wind speed and directionmay cause a negative surge that is not predicted by Eq. (1)

378 M.B. Salisbury, S.C. Hagen / Coastal Engineering 54 (2007) 377–391

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(Zevenbergen et al., 1999). Second, the spatial variance of thestorm surge hydrographs along the open coast boundary is notconsidered. Previous studies have assumed that applying asingle design hydrograph is sufficient, but results presented inthis study clearly indicate that this is not a thoroughly accurateprocedure. Results presented herein show that the open coaststorm surge hydrographs are dependent upon the depth andlocation of the boundary node. This result potentially has sig-nificant implications for future bridge scour modeling studies.

1.2. Hurricane Ivan

Hurricane Ivan (September 2, 2004–September 24, 2004)was one of four devastating hurricanes that struck the Floridacoast in 2004, along with Hurricanes Charley, Frances, andJeanne. The damage caused by Ivan was estimated to be$14.2 billion (Stewart, 2004), ranking among the costliesthurricanes to ever impact the United States. Damage in Floridaalone totaled more than $4 billion, with an estimated$900 million in damage to the Pensacola Naval Air Station.The death toll of Ivan reached 92 fatalities, with 25 deaths in theUnited States. The maximum sustained winds at landfallreached 210 km/h, with the most intense winds located in thenortheast quadrant of the storm. The greatest storm surgeoccurred along the coast of eastern Alabama and westernFlorida, with peak surge reaching 3–4 m along the Panhandle ofFlorida. In the Escambia Bay region, the storm surge and windwaves were great enough to topple portions of the Interstate 10Bridge, causing a 400 m section of the roadway to collapse intothe bay.

2. Methodology

In order to properly describe the physics of meteorologicaltides (storm surge), a numerical model must resolve coastalfeatures that affect storm surge generation and propagation.Therefore, a model domain must describe complex coastalgeometries (bathymetry and topography), large gradients inbathymetry along the continental shelf, and permit reasonableboundary conditions (i.e. tidal harmonics and/or water surfaceelevations). A finite element based model is ideal for such atask, as its flexibility allows for large spatial scales to berepresented in the domain while allowing higher nodalresolution along the coastline (Blain et al., 1994).

2.1. Idealized domain

Previous research has shown that an idealized finite elementdomain provides an excellent means for isolating and examining

inlet parameters. Hench et al. (2002) applied several idealizedinlet configurations to examine momentum balances for shallowtidal inlets. Pandoe and Edge (2004) and Kubatko et al. (2005)utilized an idealized domain to study sediment transport throughan inlet channel. For all cases, the structure of the domainprovided a clear discernment of changes in model results tomodifications in model parameters. Furthermore, a planformprofile was used to represent the ocean basin and the baywith theinlet and bay dimensions assumed to be realistic (no supportingevidence was provided to verify this claim). Similarly, aplanform profile is used in this study; however, the inlet andbay dimensions are modified to represent a range of inlet–bayconfigurations found along the Florida coast.

2.1.1. Statistical analysisA thorough review of existing Florida tidal inlets is

performed in order to properly design the idealized finiteelement meshes used in the numerical parameter study. A totalof 74 tidal inlets are identified along the Florida coast, 26 on theeast coast and 48 on the west coast (Carr de Betts, 1999). Astatistical analysis is performed on the hydrodynamic measure-ments associated with each tidal inlet. The mean and standarddeviation of each parameter dataset is determined (Table 1).

From this analysis it is noted that the variability amongstFlorida tidal inlets is quite recognizable. For example, theaverage inlet length is 3142 m, while the standard deviation is6537 m. This implies that a large range of inlet lengths is presentin the dataset, which indicates that the mean values listed inTable 1 may not be representative of a typical Florida tidal inlet.In lieu of this, a z-score test is performed to remove thestatistical outliers as follows (Mendenhall and Sincich, 1995):

z ¼ y−lr

ð2Þ

where, y=data point value, μ=mean, and σ=standard devia-tion. The values for μ and σ are obtained from Table 1. Bydefinition, the z-score describes the location of the data pointrelative to the mean value. In order to determine whether a valueis considered an outlier, the computed z-score for each datapoint is compared to a tabulated value of z-scores. If thecomputed value from the dataset is greater than the tabulatedvalue, |z| N |ztable|, then the data point is considered to be anoutlier. For this study, the 0.05 significance level is used for thetabulated z-score values.

This process is repeated for each of the datasets, and theoutliers are removed. Next, another statistical analysis isperformed on the revised dataset to determine mean valuesthat are more representative of a typical Florida tidal inlet.Table 2 presents the results of this analysis.

Table 1Average hydrodynamic characteristics of Florida's tidal inlets

Parameter Unit Mean Standard deviation

Width [m] 557 822Depth [m] 4.7 3.5Length [m] 3142 6537

Table 2Modified statistics of Florida's tidal inlets with outliers removed

Parameter Unit Mean Standard deviation

Width [m] 388 337Depth [m] 3.7 2.0Length [m] 2257 1814

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2.1.2. Inlet–bay configurationFour different inlet width profiles are used in the numerical

parameter study: an average inlet width (corresponding to theaverage width identified in Table 2), a 100 m inlet width, a500 m inlet width, and a 1000 m inlet width. This range of inletwidths encompasses the majority of Florida's tidal inlets. Foreach inlet width configuration, the inlet length and depth areheld constant according to the average values determined inTable 2. In contrast, the bay surface area varies between eachinlet width configuration according to a tidal prism–inlet cross-sectional area relationship developed by Jarrett (1976). Con-verted to the System International unit system, the relationshipis expressed as follows:

Ac ¼ 2:09� 10−5X0:95 ð3Þwhere, Ac=minimum cross-sectional area of the inlet (m2) andΩ=tidal prism (m3). This equation relates the minimum cross-

sectional area of the inlet to the tidal prism for stable tidal inlets.As a comparison, the data of Florida tidal inlets are compared tothe solutions obtained from Eq. (3). Overall, Eq. (3) provides anexcellent fit to the raw data (Fig. 1). Thus, Jarrett's relationshipis deemed appropriate for Florida's tidal inlets.

Additionally, the tidal prism is related to the bay surface areathrough the following relationship (USACE, 2002):

X ¼ 2abAb ð4Þwhere, ab= the bay tide amplitude, and Ab= the bay surfacearea. The bay tide amplitude is defined as one half the tidalrange; thus, Eq. (4) relates the tidal prism to a product of thetidal range (2ab) and the bay surface area. Substituting thisrelationship into Eq. (3) yields the following solution:

Ac ¼ 2:09� 10−5 2abAbð Þ0:95: ð5ÞFurthermore, it's assumed that the tidal range (2ab) is 1 m,

which is archetypical of the tidal range along the coast ofFlorida [see Kojima (2005) for a detailed tidal analysis along theUnited States coast]. Substituting this assumption into Eq. (5),and rearranging for the bay surface area, leads to the followingequation:

Ab ¼ Ac

2:09� 10−5

� �1=0:95

: ð6Þ

This expression is used to develop the inlet–bay configura-tions in the finite element meshes of the numerical parameterstudy. A rectangular cross-sectional profile is assumed for theentire length of the inlet; thus, the inlet cross-sectional area (Ac)can easily be determined based on the desired inlet width

Fig. 1. Comparison of Jarrett's relationship to Florida tidal inlet data.

Fig. 2. Inlet–bay configurations for the idealized finite element meshes: a) average inlet width; b) 100 m inlet width; c) 500 m inlet width; and d) 1000 m inlet width.

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(average, 100 m, 500 m, and 1000 m) and the constant inletdepth (3.7 m). Following this procedure for each inlet widthyields a unique bay surface area for each inlet configuration.The result of this process leads to the following inlet–bayconfigurations (Fig. 2).

The node spacing ranges from 50m in the inlet to 100m in thebay for the average, 500 m, and 1000 m inlet width config-urations, and 25 m in the inlet to 50 m in the bay for the 100 minlet width configuration. This level of resolution ensures thatthe inlet is represented by at least 4 elements across its width for

Fig. 3. a) Finite element mesh for the idealized domain; b) bathymetry for the idealized domain. Thick dashed lines represent locations of open boundaries.

Fig. 4. a) Finite element discretization for the ocean-based domain; b) bathymetry for the ocean-based domain; c) finite element discretization near Escambia Bay; andd) bathymetry for coastal areas near Escambia Bay.

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all inlet–bay configurations. Furthermore, the domain measures150 km alongshore with the ocean boundary placed 100 kmseaward from the coastline. A depth of 73 m is set at the oceanboundary and a linear transition is applied to the bathymetryprofile between the ocean boundary and the coastline. Fig. 3ashows the finite element mesh for the idealized domain, andFig. 3b displays the associated bathymetry profile.

2.2. Escambia Bay domain

2.2.1. Study locationFor the Hurricane Ivan analysis, a large-scale, ocean-based

domain is employed with higher mesh resolution in theEscambia Bay region. The study area is located along thePanhandle of Florida in the northwestern portion of the state ofFlorida. The main focus of this study is an inlet–bay system thatwas devastated by storm surge from Hurricane Ivan inSeptember 2004. The system includes the Pensacola Pass,Pensacola Bay, Escambia Bay, Blackwater Bay and East Bay(Fig. 4). The system is connected to two adjacent bay systems viaa Gulf Intracoastal Waterway: Perdido Bay to the west andChoctawatchee Bay to the east.

Pensacola Pass is a relatively deep inlet that connects thePensacola Bay to the Gulf of Mexico. The inlet is part ofEscambia County, and is bordered by two low-lying, sandybarrier islands: Perdido Key to the west and Santa Rosa Islandto the east. The inlet became a federal navigation project in 1881and is regularly dredged to a depth of approximately 15 m toaccommodate U.S. Navy aircraft carriers (Carr de Betts, 1999).

2.2.2. Model domainAn ocean-based domain is used to simulate storm surge due

to Hurricane Ivan in the vicinity of Escambia Bay. The domainencapsulates portions of the Atlantic Ocean found west of the60° West Meridian, the Gulf of Mexico, and the Caribbean Sea.The mesh was developed by incorporating the Escambia Baycoastline features into an existing 52,774 node mesh for theWestern North Atlantic Tidal model domain [see Hagen et al.(in press) for verification of the existing mesh]. The new meshincludes 88,318 nodes and 165,137 elements, and covers ahorizontal surface area of approximately 8.347×106 km2.

Bathymetry for the Escambia Bay region was obtained via theNational Geophysical Data Center (NGDC) Coastal ReliefModel, volume 3. The database consists of a combination of 3-arc second digital elevation maps (via the United StatesGeological Survey) and hydrographic soundings (via the NationalOcean Service). For regions extending beyond the Escambia Bayand Pensacola Pass, the bathymetry was interpolated from anexisting high resolution Western North Atlantic mesh. Fig. 4athrough d presents the finite element discretization andbathymetry for the ocean-based domain with zoomed in viewsof the Escambia Bay and Pensacola Pass.

In addition, a second computational domain is used thatincludes the low-lying barrier islands as inundation areas. Thesame ocean and Escambia Bay coastline features are used fromthe previously described mesh, but Santa Rosa Island to the eastand Perdido Key to the west of Pensacola Pass are included as

inundation areas. Including the barrier islands into the modeldomain allows the storm surge to inundate the barrier islands,creating higher surge levels within the bay. Model results arecompared to historical data at a National Ocean Service (NOS)tide gauge located in Pensacola Bay (Fig. 4d).

2.3. Storm surge model

The water surface elevations and circulation patterns arecomputed by the Advanced Circulation model (ADCIRC) forshelves, coasts, and estuaries (Luettich et al., 1992). In this study,barotropic dynamics are predominant and density gradients areassumed to be relatively small, as these conditions are commonnear tidal inlets (Hench et al., 2002). These assumptions permitthe use of the fully nonlinear two-dimensional, depth-integratedoption of the model (ADCIRC-2DDI). Westerink et al. (1994)present the basic governing continuity Eq. (7) and momentumEqs. (8) and (9) that are used in the model:

AfAt

þ AUHAx

þ AVHAy

¼ 0 ð7Þ

AUAt

þ UAUAx

þ VAUAy

−f V ¼ −A

Axpsq0

þ gðf−agÞ� �

þ 1HMX þ sSX

q0H−s⁎U

ð8Þ

AVAt

þ UAVAx

þ VAVAy

þ fU ¼ −A

Aypsq0

þ gðf−agÞ� �

þ 1HMY þ sSY

q0H−s⁎V

ð9Þ

where, t= time; x,y=horizontal coordinates, aligned in the Eastand North directions respectively; ζ=free surface elevation,relative to the geoid; U=depth-averaged horizontal velocity, xdirection; V=depth-averaged horizontal velocity, y direction;H= total water column depth, h+ζ; h=bathymetric depthrelative to the geoid; f=2Ωsinφ=Coriolis parameter; Ω=angu-lar speed of the earth; φ=degrees latitude; ps=atmosphericpressure at the free surface; g=acceleration due to gravity;η=Newtonian equilibrium tide potential; α=earth elasticityfactor; ρ0= reference density of water; τSX=applied free surfacestress, x direction; τSY=applied free surface stress, y direction;

s⁎ ¼ Cf

ffiffiffiffiffiffiffiffiffiffiffiU2þV 2

pH =bottom stress; Cf =bottom friction coefficient;

MX= Eh2A2UHAx2 þ A2UH

Ay2

h i=depth-integrated momentum disper-

sion, x direction; MY=Eh2A2VHAx2 þ A2VH

Ay2

h i=depth-integrated mo-

mentum dispersion, y direction; and Eh2=horizontal eddyviscosity.

The governing equations are discretized in space by linearfinite elements and in time by a finite difference scheme(Luettich et al., 1992). The finite element solution to the shallowwater equations gives rise to spurious modes and numericalinstabilities. Hence, it becomes necessary to reformulate theequations into a form that provides a stable solution in its finiteelement representation. Therefore, ADCIRC-2DDI employs theGeneralized Wave Continuity Equation (GWCE), together with

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the momentum conservation equations, to eliminate thisproblem (Westerink et al., 1994). The result is a noise-freesolution that is used to solve for the deviation from the geoid (ζ)and the velocities in the x and y directions.

2.3.1. Hurricane Ivan wind field modelThe state-of-the-art wind data (Fig. 5) for the hurricane storm

surge simulations was provided using a tropical wind modeldeveloped by Cox and Cardone (2000). The model is aderivative of the TC96 model that was first implemented in theOcean Data Gathering Program. The TC96 model providessnapshots in time that are blended into a synoptic-scale windfield using the Interactive Objective Kinematic Analysisalgorithm (Cox et al., 1995) of the Wind Workstation. Usinga numerical integration technique, the model solves thevertically averaged equations of motion for a boundary layerunder horizontal and vertical stresses. Based on this principle,the numerical model provides a fairly thorough description ofthe time–space evolution of the wind speeds within theplanetary boundary layer (PBL) during a tropical cycloneevent (Thompson and Cardone, 1996).

The wind field model is driven by “snapshots” in time of thestorm's intensity and is based on the assumption that thestructure of the hurricane changes relatively slowly (Cox andCardone, 2000). In addition to the TC96 model, these snapshotsare also obtained from the Hurricane Research Division WindAnalysis System, a distributed system that uses real-time tropicalcyclone observations as input (Powell et al., 1998). The slowevolution of the storm's intensity is then interpolated from thesesnapshots. In addition, the model is also controlled by severalinput parameters: the storm's speed and direction, the geo-strophic flow of the ambient PBL pressure field, a pressureprofile parameter, and a scaling factor for the exponential radialpressure profile. The wind model is capable of simulating anytype of storm for any particular region, and has been verified andvalidated for a number of test cases (Cox and Cardone, 2002).

The wind speeds that are computed by the wind field modelare used as surface stress conditions in the ADCIRC-2DDI

model. In order to convert wind speed to wind stress, ADCIRCemploys a relationship developed by Garrett (1977). Further-more, the wind model also provides a pressure gradient toADCIRC. A conversion is then performed within ADCIRC toconvert the pressure gradient to an equivalent water columnheight through the transformation P /ρwg (Blain et al, 1994). Inthe end, the wind stress and the equivalent water column heightare linearly interpolated to each computational node of the finiteelement mesh used by ADCIRC.

2.3.2. Synthetic wind field modelFor the numerical parameter study, a synthetic hurricane

wind field model is used to force the ADCIRC-2DDI model.The wind field model is parameterized according to the forwardvelocity and pressure field of Hurricane Ivan, and simulates asimplified, circularly symmetric version of the storm. Com-pared to the wind field model used in the Hurricane Ivan study,the synthetic wind field model is much less sophisticated.However, the model does allow the user to specify the hurricaneparameters and path of the storm, which makes it ideal for anumerical study such as this.

In all cases presented herein, the wind field model isinitialized to represent a typical worst-case scenario for coastalstorm surge in the vicinity of the tidal inlet. First, the path of thestorm is setup to traverse the coastline in a perpendicularmanner. Additionally, the eye of the storm makes landfall at apoint 25 km left of the tidal inlet, placing the inlet in the upperright quadrant of the storm (Fig. 6).

2.3.3. Model parameters for idealized domainsFor the idealized study, the inlet–bay configurations are

isolated to examine their influence on the model results.Consequently, the model parameters are held constant for eachsimulation and are specified according to the following: Theequations are solved in the Cartesian coordinate system.Simulations are spun up from rest over a 2-day period via ahyperbolic ramp function. Total simulation time is 4 days, with a0.25 second time step used to ensure model stability. A hybridbottom friction formulation is employed with the followingspecifications: Cfmin=0.0025, Hbreak=10 m, θ=10, and λ=1/3.

Fig. 5. Hurricane Ivan wind field just before landfall.

Fig. 6. Synthetic wind field used in the numerical parameter study.

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The horizontal eddy viscosity coefficient is set to 5 m2/sec. Aconstant Coriolis parameter corresponding to 27.5°N (approxi-mately the middle latitude of Florida) is used. One harmonicforcing frequency corresponding to the M2 (principal lunar)constituent is applied to the system with an amplitude of 0.5 mand 0° phasing. This produces a tidal range of approximately 1 mnear the coastline, which is representative of the tidal rangecharacteristics along the Florida coast. Meteorological forcings(wind stress and surface pressure) are read into the simulationevery 30 min, with the eye of the synthetic hurricane makinglandfall approximately 3 days into the simulation.

2.3.4. Model output locations for idealized domainsIn lieu of the fact that previous bridge scour modeling efforts

have incorporated open coast boundaries at varying distancesfrom the mouth of the inlet, a wide range of semi-circular arcsare created with output stations located along each arc. Thesearcs have radii ranging from 1 km to 15 km from the mouth ofthe inlet, and are representative of typical open coast boundarylocations used in bridge scour modeling. Water surfaceelevations are recorded at each of these stations over the entireduration of the simulation at six minute intervals. Fig. 7 displaysthe semi-circular arcs with the output locations for the differentradii.

2.3.5. Model parameters for the Escambia Bay domainAstronomic tides are included in the Escambia Bay domain

simulations; however, the astronomic tides and storm surge arecomputed separately due to the differences in model parame-terization and simulation length. The total hydrograph is com-puted by superimposing the storm surge output with aresynthesis of the astronomic tides. The results are thencompared to historical National Ocean Service (NOS) gaugedata located within Pensacola Bay to verify the model.

The model parameters for the astronomic tidal simulationsare set as follows: The coordinate system is set to spherical.Total simulation length is 90 days with all runs begun from acold start. Seven harmonic forcings are applied simultaneouslyalong the ocean boundary (M2, K1, O1, N2, K2, Q1, and S2)

and are ramped over a 20-day period. The hybrid bottomfriction formulation is employed with the following settings:Cfmin=0.0025, Hbreak=1 m, θ=10, and λ=1 /3. The horizontaleddy viscosity coefficient is set at 5 m2/sec, and a time step of5 s is used to ensure model stability.

Similarly, the model parameters for the storm surge simu-lations are set as follows: A spherical coordinate system isapplied. Simulations are begun from a cold start, and are runover a ten day period (September 7, 2004 at 6 p.m. to Sep-tember 17, 2004 at 6 p.m.) with a 2.5-day ramp time. Meteo-rological forcings (wind stress and pressure) are read into themodel every 30 min. The wetting and drying of elements isemployed with the minimum depth set to 0.1 m. A 2.5 secondtime step is used for each model domain to ensure stability. Ahybrid bottom friction formulation is used with the followingsettings: Cfmin=0.001, Hbreak=10 m, θ=10, and λ=1 /3, andthe horizontal eddy viscosity coefficient is set to 5 m2/sec.

2.3.6. Model output locations for the Escambia Bay domainIn a similar manner to the idealized domain, semi-circular

arcs of varying radii are extended seaward from the mouth ofPensacola Pass. The arcs range from 1 km to 15 km in radialdistance. Fig. 8 shows the observation points along each semi-circular arc extending seaward from Pensacola Pass.

Observation points for locations due east and west from themouth of the inlet are not included as some of the points wouldeither be outside of the model boundaries or within the baysystem. In this case, seven output stations are located on eachsemi-circular arc: east–southeast (1), southeast (2), south–southeast (3), south (4), south–southwest (5), southwest (6), andwest–southwest (7). These output locations are used to comparethe effect that the Pensacola Pass has on the open coast stormsurge hydrographs and to examine the spatial variance of thehydrographs along each arc.

3. Simulation results

Primary focus is given to the effect that inlet–bay configura-tions have on the open coast storm surge hydrographs. Two

Fig. 7. Semi-circular arcs with output locations for idealized domain.

Fig. 8. Semi-circular arcs with output locations for Escambia Bay domain.

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different studies are presented in this section to illustrate theseresults: 1) a numerical parameter study, where the effect of fourdifferent inlet widths (average, 100 m, 500 m, and 1000 mwidths) on the open coast storm surge hydrographs are isolatedand compared; and 2) a storm surge study that focuses on theeffect of the Pensacola Pass and Escambia Bay system on theopen coast storm surge hydrographs produced from HurricaneIvan. Additional discussion is provided on the spatial variance ofthe open coast storm surge along the observation arcs.

3.1. Numerical parameter study results

3.1.1. Inlet comparisonUltimately, the results and conclusions from this study will

be used to determine whether an inlet and bay system (e.g. thePensacola Pass and Escambia Bay system) should be includedin a large-scale ocean circulation model (e.g. the Western NorthAtlantic Tidal model domain) for generating open coastboundary conditions for local bridge scour models. In order toaccomplish this, four inlet–bay configurations and a controlcase are developed in an idealized setting. The control meshdoes not include an inlet–bay system along the coastline and

provides a test case for better determining the influence of theinlet–bay system on the open coast storm surge hydrographs.

Model output is compared at each of the observation pointsfor all of the inlet–bay configurations. Figs. 9–11, show modelresults for each of the inlet–bay configurations at point 3(perpendicular to the coast) on the 1 km, 5 km, and 15 km radiiarcs, respectively.

It is evident from the plots that no appreciable differenceexists in the storm surge hydrographs between the inlet–bayconfigurations. A difference of 5 cm is noticed in Fig. 9 (1 kmradius) for the 1000 m inlet width, but the difference ispractically negligible at the 5 km radius (Fig. 10) and the 15 kmradius (Fig. 11). Similar results are obtained at all of the othermodel output locations, but are not included in the interest ofbrevity. It is apparent from this analysis that the flow througheach of the inlets (velocity=3.1 m/s) does not produce a largeenough velocity head to draw down the water surface elevationsalong the open coast when compared to one another.

Proper modeling practice dictates that the open coastboundary be placed far enough from the inlet to allow forappropriate circulation patterns to be generated within themodel (Militello et al., 2000). Thus, bridge scour modelingstudies would place the boundary farther than 1 km from theinlet to avoid momentum flux problems. At locations further

Fig. 9. Storm surge hydrographs at point 3 on the 1 km radius observation arc foreach of the inlet–bay configurations.

Fig. 10. Storm surge hydrographs at point 3 on the 5 km radius observation arcfor each of the inlet–bay configurations.

Fig. 11. Storm surge hydrographs at point 3 on the 15 km radius observation arcfor each of the inlet–bay configurations.

Fig. 12. Storm surge hydrographs along the 1 km radius observation arc.

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from the inlet, the open coast storm surge hydrographs arenearly identical. Hence, the inlet–bay configurations do notappear to create a significant difference in the open coast stormsurge hydrographs. Consequently, a large-scale model (e.g. theWNAT domain) would not need to include an inlet–bay systemalong the coastline when generating boundary conditions for alocal bridge scour model.

3.1.2. Spatial variancePrevious research has applied a single design hydrograph

along the open coast boundary for bridge scour modelingstudies. No consideration was given in these studies to thespatial variance of the open coast storm surge hydrographsalong the boundary location. This was most likely due to theunavailability of a large-scale model to produce boundaryconditions for a local, high resolution circulation model. Hence,stochastic formulations were developed for generating opencoast boundary conditions. The use of a large-scale model forgenerating coastal boundary conditions allows for the spatialvariance of storm surge hydrographs to be incorporated into thelocal circulation model.

Two different results are presented in this section: 1)hydrographs along both the 1 km radius and 5 km radius arcs;and 2) hydrographs for point 3 (perpendicular to the coast) on

each arc ranging from 1 km to 5 km (model results at the otheroutput locations show similar patterns, but are not included inthe interest of brevity). Water surface elevations are compared atthe same open coast boundary locations as previously describedfor the average inlet width. Analysis in the previous sectionindicates that all inlet profiles produce nearly identical results asthe average inlet width; therefore, the results and conclusionspresented in this section can be extended to other inlet profilesas well.

Fig. 12 shows computed sea stages along the 1 km radiusobservation arc for the average inlet profile. The highest peak(recorded at point 5) is 2.16 m above mean sea level (MSL),whereas the lowest (recorded at point 3) is 2.04 m above MSL, adifference of 0.12 m. The peaks reveal that the points (4 and 5)closest to the eye of the storm produce the greatest surge.Overall, the behavior of the storm surge hydrographs shows thata spatial variance exists along this observation arc during thesurge event. However, the hydrographs also show that theastronomic tide signals are identical prior to hurricane landfall(i.e. before day 2.75 of the simulation), thus indicating that thespatial variance is limited to the surge event.

Similarly, Fig. 13 presents computed water elevations alongthe 5 km radius observation arc. The highest peak (recorded atpoint 5) is 2.18 m above MSL, whereas the lowest (recorded at

Fig. 13. Storm surge hydrographs along the 5 km radius observation arc.

Fig. 14. Storm surge hydrographs at point #3 on radii extending from 1 km to5 km.

Fig. 15. Astronomic tide comparison at the NOS station in Pensacola Bay.

Fig. 16. Astronomic tide comparison along the 5 km radius observation arcextending seaward from the mouth of Pensacola Bay.

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point 3) is 1.66 m above MSL, a difference of 0.52 m. Com-pared to the 1 km radius, the difference between the highest andthe lowest peak values is much greater for the 5 km radius(0.52 m for the 5 km radius compared to 0.12 m for the 1 kmradius).

Furthermore, a difference in peak elevations is also recognizedbetween points that have the same depth. Comparing locations 2and 4 (depth of 6.2 m at each location) in Fig. 13 indicates a peaksurge of 1.73 m at point 2 and 1.81 m at point 4 (a difference of8 cm). A similar difference (10 cm) is also recognized betweenpoints 1 and 5 (at a depth of 3.7 m). Therefore, the variability inthe peak storm surge elevations is, in part, attributed to thehorizontal location along the open coast boundary.

Moreover, differences in peak surge levels are also recog-nized at the same point on different observation arcs. Resultsshow that the peak storm surge increases as the surge wavepropagates into shallower waters. Fig. 14 displays recordedwater elevations at point 3 (perpendicular to the coast) on the1 km and 5 km radius observation arcs. The highest peak waterelevation is 2.05 m at the 1 km radius arc, and the lowest peak

elevation is 1.66 m at the 5 km radius arc. The results clearlyindicate that the storm surge is dependent on the depth of thelocation.

The results presented thus far potentially have significantimplications for local bridge scour modeling. Previous research(Edge et al., 1999; Zevenbergen et al., 1999; Sheppard andPritsivelis, 1999) has applied a single design hydrograph at theopen coast boundary for bridge scour studies (distance of theocean boundaries from the inlet was not specified in each study,but they appeared to be within a few kilometers of the coast).Results presented herein show that the hydrographs vary spa-tially over this open coast boundary, thus indicating that indi-vidual hydrographs should be applied at each open boundarynode for proper bridge scour modeling.

3.2. Hurricane Ivan storm surge results

A Hurricane Ivan storm surge study is undertaken to deter-mine if conclusions from the numerical parameter study can beextrapolated to a real-life scenario. In contrast to the numerical

Fig. 17. Hurricane Ivan water elevations at the NOS station in Pensacola Bay forthe domain that treats the barrier islands as model boundaries.

Fig. 18. Maximum storm surge elevations within Pensacola Bay and EscambiaBay for the domain that treats the barrier islands as model boundaries.

Fig. 19. Comparison between model results for the domain that treats the barrierislands as inundation areas versus treating the barrier islands as modelboundaries.

Fig. 20. Maximum storm surge elevations within Pensacola Bay and EscambiaBay for the domain that treats the barrier islands as inundation areas.

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parameter study, historical water elevation data is available tocompare model results as a means of verification. First, anastronomic tide verification and a storm surge study of Hur-ricane Ivan are performed to validate the model domain in thecoastal region of Pensacola Pass and Escambia Bay. Next, theeffect of the Pensacola Pass–Escambia Bay system on the opencoast storm surge hydrographs and the spatial variance of thestorm surge hydrographs along the open coast are evaluated.The width (980 m) of Pensacola Pass and the size (6.8×108 m2)of the adjoining bay indicate that the domain is similar to theinlet–bay configuration with the 1000 m inlet width used in thenumerical parameter study.

3.2.1. Astronomic tide verificationFirst the model domain is verified through an astronomic tide

comparison. A National Ocean Service tide gauge locatedwithin Pensacola Bay (see Fig. 4) provides historical tidalconstituent data. A 14-day resynthesis of model results is com-pared to a resynthesis of historical constituents at the NOS tidegauge in Pensacola Bay (Fig. 15). The 14-day resynthesisperiod is chosen to allow for a complete spring–neap tide cycle.The results indicate that the model performs reasonably well atthis location. A slight discrepancy is recognized in phasingbetween days 8 and 14, as well as the troughs through most ofthe resynthesis. Overall, however, the model domain faithfullysimulates the tidal dynamicswithin the Pensacola Pass–EscambiaBay system.

In addition, the astronomic tide variance is examined alongthe open coast observation arcs extending seaward from themouth of Pensacola Pass. Similar to the tide verification at theNOS station in Pensacola Bay, a 14-day resynthesis is per-formed at each of the model output locations along the obser-vation arcs. Fig. 16 shows a resynthesis of the astronomic tidesignal along the 5 km radius observation arc.

The results indicate that the tide signal is nearly identical ateach of these locations. Similar results are obtained along theother semi-circular observation arcs, indicating that the astro-nomic tides do not display a spatial variance near the inlet. As aresult, the spatial variance recognized amongst the storm surge

hydrographs in the following sections is a result of the stormsurge phenomenon rather than the astronomic tides.

3.2.2. Historical comparisonBoth model domains (barrier islands as model boundaries

and barrier islands as inundation areas) are used to simulatestorm surge within Escambia Bay for a ten day period: Sep-tember 7, 2004 at 6 p.m. through September 17, 2004 at 6 p.m.Fig. 17 compares model results to historical gauge data at theNOS station for the domain that treats the barrier islands asmodel boundaries.

Two noticeable results are obtained from this figure. First,the NOS tide gauge appears to have stopped recording close tothe time of hurricane landfall. As a result, the peak surge leveland the set-down behavior at this location are not shown in thehistorical data, making a comparison throughout the entirehurricane event impossible. In lieu of this, it is difficult toaccurately compare model results to historical data; however,high water marks in Escambia Bay suggest a peak water level of3–4.5 m near the Interstate 10 Bridge in Escambia Bay(Douglass et al., 2004). A plot of the maximum surge elevationswithin the bay (Fig. 18) for the model results that treat thebarrier islands as model boundaries indicates that the modelproduces peak surge levels that are slightly less (2.5–3 m) thanthe high water marks near the bridge.

Second, a difference in the rising limb behavior is noticedbetween the model results and the historical data (between 9/14and 9/15). This difference can be attributed to several factorsthat are not included in this study. First, short-wave (windwaves) processes are not included in the modeling process.Typically, wind-induced waves travel ahead of the storm surge,creating water elevations to rise before the hurricane makeslandfall. In order to perform a true storm surge hindcast (whichis not the objective of this study), wind waves would have to beincluded in the modeling process.

Additionally, the difference may also be attributed to themodel parameter (bottom friction coefficient, wind drag co-efficient, and horizontal eddy viscosity) values used in thisstudy. However, the model parameter values used are con-sidered standard values and a sensitivity analysis is outside the

Fig. 21. Storm surge hydrographs at point #4 along the 5 km radius observationarc for the model domain that does not include the Pensacola Pass and the modeldomain that does include the Pensacola Pass.

Fig. 22. Storm surge hydrographs along the 1 km radius observation arcextending seaward from Pensacola Pass.

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realm of this study. Lastly, inaccuracies in the wind field andpressure field may have also led to errors in the storm surgeresults.

Furthermore, when the barrier islands are treated asinundation areas, the surge levels within the bay increase byalmost half a meter compared to treating the barrier islands asmodel boundaries. Fig. 19 compares the storm surge hydro-graphs between the two model domains (barrier islands asmodel boundaries and barrier islands as inundation areas) tohistorical data at the NOS tide gauge. The results clearlyindicate that allowing the storm surge to flood over the barrierislands creates greater water elevations within the bay. In thiscase, the highest surge value for treating the barrier islands asinundation areas is 2.12 m, whereas the highest surge value fortreating the barrier islands as model boundaries is 1.66 m, adifference of 0.46 m.

Similarly, comparing the maximum storm surge contourswithin Escambia Bay to high water marks (3–4.5 m) recordednear the Interstate 10 Bridge indicates that including the barrierislands as inundation areas creates maximum surge levels that aremore consistent with historical records (Fig. 20). The resultsshown in this figure (3–4 m near the bridge) compare morefavorably with the high water marks than the results shown inFig. 18 (barrier islands treated as model boundaries). Thus, in-cluding the barrier islands as inundation areas creates morerealistic surge levels within the bay than treating them as modelboundaries.

Model results still indicate a discrepancy when compared tothe historical data during the rising limb period. It's important tonote, however, that this is not a true storm surge hindcast study fortwo reasons: 1) wind–wave processes are not included in themodeling process; and 2) standard, not necessarily optimal,values for model parameters (i.e., bottom friction coefficient,wind drag coefficient, and horizontal eddy viscosity) were used.In order to identify optimal model parameter values a sensitivitystudywould be required, but that is outside the realm of this study.The important conclusion from the results presented thus far is themodel reproduces the overall long-wave behavior reasonablywell, which is paramount to the open coast storm surge hydro-graph analysis presented in the following sections.

3.2.3. Pensacola PassThe main conclusion from the numerical parameter study is

that the effect of tidal inlets on open coast storm surgehydrographs is negligible. The implication of this conclusion isthat a large-scale ocean circulationmodel does not need to includean inlet–bay system in the computational domain when gen-erating open coast boundary conditions for a local bridge scourmodel. This section verifies this conclusion for the case ofPensacola Pass during Hurricane Ivan.

Two computational domains are used in this analysis: 1) afinite element mesh of the Western North Atlantic Tidal modeldomain that does not include the Pensacola Pass–Escambia Baysystem; and 2) a finite element mesh of the same region that doesinclude the Pensacola Pass–Escambia Bay system (previouslydescribed). The domain that does not include the Pensacola Pass–Escambia Bay system has been optimized in previous research forstorm surge applications (Hagen et al., in press; Kojima, 2005),and is representative of a model domain that would be used togenerate open coast boundary conditions for a local bridge scourmodel if the inlet–bay system is not included in the domain. Incontrast, the domain that does include the Pensacola Pass–Escambia Bay system is typical of a model domain that would beused to generate the open coast boundary conditions if the inlet–bay system is included in the domain. Model output is generatedalong the semi-circular observation arcs extending seaward fromthe mouth of the inlet.

Fig. 21 shows sea stages at point 4 (due south) on the 5 kmradius observation arc. Model results for the domain that doesnot include the Pensacola Pass indicate a peak surge level of1.79 m; whereas model results for the domain that does includethe Pensacola Pass indicate a peak surge of 1.71 m (a differenceof 8 cm). Similar results are obtained at the other open coastobservation locations.

At this point, it is impossible to state that this difference wouldor would not have an appreciable effect on the performance of abridge scour model. However, clearly it is unlikely that a differ-ence of 8 cm (4.5% relative to the peak value) would significantlyalter the model's performance, especially since the rising andfalling limbs of the hydrographs are nearly identical. These resultsare consistent with the conclusions from the numerical parameter

Fig. 23. Storm surge hydrographs along the 5 km radius observation arcextending seaward from Pensacola Pass.

Fig. 24. Storm surge hydrographs at the same location (point 4, due south) oneach observation arc from 1 km to 5 km in radius.

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study, i.e. tidal inlets do not appear to have a significant influenceon the open coast storm surge hydrographs.

3.2.4. Spatial varianceThis section verifies the spatial variance results shown in the

numerical parameter study with a real-life scenario (e.g.Pensacola Pass). The 1 km radius and 5 km radius observationarcs are used to verify these findings. Fig. 22 displays the stormsurge hydrographs along the 1 km radius extending seawardfrom the mouth of Pensacola Pass. The plots indicate that aminimal difference exists between the hydrographs along thisobservation arc. The highest peak surge value is 1.87 m at point7 (west–southwest), whereas the lowest peak value is 1.83 m atpoint 3 (south–southeast), a difference of only 4 cm.

Fig. 23 shows the water elevation recordings along the 5 kmarc radius. In contrast to the 1 km radius, a noticeable spatialvariance is evident in the plots. The greatest peak surge value is1.94 m (point 7) and the lowest peak surge value is 1.65 m(point 3), a difference of 0.29 m. The spatial variance along the5 km radius is much greater than the spatial variance along the1 km radius, which is consistent with the results from thenumerical parameter study.

In addition, spatial variance is also recognized as the radiusof the observation arc is increased. Fig. 24 shows hydrographsat the same location (point 4, due south) along the 1 km and5 km observation arcs. Similar to the numerical parameter studyresults, the peak storm surge increases nearer to the coastline.

4. Conclusions

Presented herein is a numerical parameter study focusing onthe effect that tidal inlets have on open coast storm surgehydrographs. Four different inlet–bay configurations are con-structed based on a statistical analysis of existing Florida tidalinlets. The inlet–bay configurations allow for a number of testcases to elucidate the influence that tidal inlets have on opencoast boundary conditions. A secondary focus of this study isthe spatial variance of the storm surge hydrographs along near-inlet boundary locations. Results from the numerical parameterstudy are compared with results from a Hurricane Ivan stormsurge study in the vicinity of Escambia Bay. The conclusionsfrom this study have implications toward future bridge scourmodeling efforts.

4.1. Numerical parameter study conclusions

Two primary conclusions are drawn from the numericalparameter study: 1) the effect of tidal inlets on open coast stormsurge hydrographs is minimal; and 2) a noticeable spatial var-iance of storm surge hydrographs exists along the open coastboundary locations.

The effect of including inlet–bay systems on the open coaststorm surge hydrographs is negligible. Comparing model outputfor all four inlet–bay configurations to the control mesh indi-cates that including an inlet–bay system in the model domaindoes not significantly alter the open coast hydrographs. Takingthis into account, a large-scale model domain (e.g. the WNAT

model domain) would not need to include the inlet–bay systemin the computational domain to generate open coast boundaryconditions for a local inlet-based model (a significant time-saving benefit for coastal modelers).

Another significant finding in this study is the spatialvariance of the storm surge hydrographs along the open coastboundary locations. Nearer to the inlet, the spatial variance ofthe hydrographs is minimal; however, the spatial varianceincreases further from the inlet (i.e. going from the 1 km radiusto the 15 km radius). This suggests that it is more appropriate toapply spatially varying hydrographs along the open coastboundary, instead of the single design hydrograph method usedin previous bridge scour modeling studies (as a point ofreference, the open coast boundary in these studies appeared tobe several kilometers offshore). If the open ocean boundary isplaced close to the inlet so that a single hydrograph can be usedat each node, then momentum flux problems may arise from theboundary being placed near the area of interest. By placing theboundary further from the inlet and applying individualhydrographs at each node, the cross-basin hydrodynamics ofstorm surge propagation can be artificially incorporated into theinlet-based model. The results from this study imply that currentbridge scour modeling practices can be improved upon byincorporating spatially varying hydrographs along the opencoast boundary.

4.2. Hurricane Ivan conclusions

The primary focus of the Hurricane Ivan storm surge study isthe verification of the numerical parameter study conclusions ina real-life scenario. The effect that the Pensacola Pass–EscambiaBay system has on the open coast storm surge hydrographs wasexamined. The results are consistent with the conclusions fromthe numerical parameter study, such that including the PensacolaPass–Escambia Bay system in the model domain does not have asignificant impact on the open coast storm surge hydrographs.Furthermore, a spatial variance is also recognized along obser-vation arcs extending seaward from the mouth of PensacolaPass. Similar to the behavior recognized in the numerical pa-rameter study, the magnitude of the spatial variance increases asthe open coast boundary locations are extended farther from themouth of the inlet. Thus, it is apparent that applying a singledesign hydrograph along the open coast boundary is inappro-priate and may lead to erroneous results.

A corollary to this study is the significance that the low-lyingbarrier islands had on the storm surge within Escambia Bayduring Hurricane Ivan. In this case, the storm surge increased byhalf a meter in the bay when the barrier islands were treated asinundation areas compared to treating the barrier islands asmodel boundaries. This is an important conclusion for futurestorm surge studies in areas that have barrier islands prevalent inthe coastal system.

Acknowledgments

This study was funded in part by Award UFEIE-S0404029UCF as a subcontract from the Florida Department

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of Transportation (FDOT) via the University of Florida (UF);Award N00014–02–1-0150 from the National Oceanic andAtmospheric Administration (NOAA), U.S. Department ofCommerce; and by National Oceanographic PartnershipProgram (NOPP) Award No. N00014–02–1-0150 administeredby the Office of Naval Research (ONR). The views expressedherein are those of the authors and do not necessarily reflectthose of the FDOT, UF, NOAA, Department of Commerce,ONR, or NOPP and its affiliates. The authors also wish to thankVince Cardone and Andrew Cox of Oceanweather Inc. forproviding the wind field used in the Hurricane Ivan study, andDon Slinn at the University of Florida for providing thesynthetic wind field code used in the numerical parameter study.

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