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A ATLAS FOR THE UNITED STATES

Report prepared for the

Caribbean Coastal Ocean Observing System (CariCOOS)

University of

Mayaguez, P.R.

By

Jose Benitez

and

Aurelio Mercado Irizarry

(this report is based on the MS thesis of Mr. Jose Benitez, and some part of the report are taken verbatim from the thesis – this is just his thesis rewritten in another way to make it shorter – for a list of references, please see Benitez theses - AM)

March 2014

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INTRODUCTION

As part of its work in the Caribbean, the Caribbean Integrated Ocean Observing System (CariCOOS) prepared a hurricane storm surge atlas for the United Stated Virgin Islands (USVI) (see Figure 1). In this atlas the potentially storm surge floodable areas for St Thomas, St John, and St Croix are determined for category 1, 2, 3, 4, and 5 hurricanes according to the Saffir-Simpson scale. State-of-the-art computer simulations using the tightly coupled models ADCIRC and SWAN were used. ADCIRC (Advanced Circulation model) is an unstructured mesh circulation model that can be forced by several products, including an internal parametric hurricane wind model. SWAN (Simulating Waves Nearshore) is a wind wave model that also runs in the same unstructured mesh as ADCIRC, and has been coupled to ADCIRC in order to compute the effects of high- frequency wind waves in the overall development of the storm surge. The idea is that ADCIRC is forced by hurricane , estimating the pressure (anomalous rise in sea surface elevation due to the low pressure accompanying the hurricane) and wind (anomalous sea surface elevation due to the

Figure 1 – Map of the USVI. accumulation of seawater against the coastline whenever the wind blows with a component towards the coastline) setups. In an iterative way, the storm surge due to these two setups is fed to SWAN, which then estimates the radiation stresses due to the wind-forced waves. These radiation stresses are then fed back to ADCIRC, which computes gradients of the radiation stresses, and the gradients themselves generate and additional setup which is called wave setup. The combination of the three setups, pressure, wind, and wave, produce an anomalous sea level rise (stillwater elevation) which is the so-called storm surge. Wave setup can be a non-negligible component to the overall storm surge in islands with narrow, and deep, shelves.

MODELS

The ADCIRC model used is version 50_99, while the SWAN version is 40.91. Both models were fed the best available bathymetry, available in DEM format (USVI DEM) from the National Geophysical Data Center (NGDC)/NOAA, with a 1/3 arc seconds resolution (approximately 10 x 10meters). Originally, the topography also came from the USVI DEM, but it was later demonstrated that this topography was useless for coastal flood mapping since it was obtained from USGS SRTM satellite data, which is not bare 3

earth. Fortuitously, a recent (2007) Lidar-derived, bare-earth, topography was found in the Internet, data which was prepared by the US Corps of Engineers for FEMA flood mapping purposes. With this topography, all of the topography from the NGDC DEM was replaced and the atlas was prepared. As is standard in coastal flood mapping, the vertical datum is Mean High Water (MHW).

Outside of the area of coverage of the NGDC bathymetry, use was made of the GEBCO 30-arc seconds bathymetry.

METHODOLOGY

The basic philosophy behind the storm surge atlas is the following. Figure 2 shows color-coded (based on storm’s intensity) historical tracks in the USVI region. It can be seen that they come with several headings, including two recent ones that had a west to east component (Lenny and Omar). Based on that, the idea is to run, for each hurricane category, several straight line tracks, at different headings,

Figure 2 – Map of historical storm trajectories in the USVI region. (http://csc.noaa.gov/hurricanes/#app=6078&3e3d- selectedIndex=1).

so that they fully cover the area of interest. Figures 3 to 5 show the tracks for the three headings that were chosen: from the southeast (Heading of 290°) and east (Heading of 270°) – the most common – and from the southwest (Heading of 60°), to evaluate the effects of Lenny- and Omar-like hurricanes. The tracks are displaced parallel to each other by a distance that should not exceed the radius of Maximum Winds (RMW). The goal is to have winds of a certain category sweep all of the islands.

For each individual track the models output the Maximum Envelope of Waters (MEOW), which shows the maximum stillwater elevations attained at each computational node during the whole model run (typically several days of simulation 4

). This individual track information is per se useful since it allows emergency managers estimate what to expect at a given site in the case of the approach of a similar hurricane. Once the MEOW for each track is determined for all tracks with a given heading, they are then all combined to obtain the Maximum of the Maximums (MOM) for that given heading and hurricane intensity (category). The MOM allows emergency managers, and relevant government personnel, evaluate what can be expected for a given hurricane intensity irrespective of the actual track taken, but for a given heading.

Figure 3 – Set of storm tracks for a heading of 270°. Red symbols play the role of arrowheads.

Figure 4 – Set of storm tracks for a heading of 290°. Red symbols play the role of arrowheads. 5

Figure 5 – Set of storm tracks for a heading of 60°. Red symbols play the role of arrowheads.

Finally, for a given hurricane category we can combine the MOM’s for the different headings and obtain what we can call a SuperMOM (SMOM) for that category. This will show the worst that can happen for that hurricane category irrespective of the storm heading. All of this will be done for all five hurricane categories.

Table 1 shows the hurricane parameters assigned to each hurricane category during the production runs for the atlas. These parameters are repeated for each of the three hurricane headings: 60°, 270°, and 290°. For each Saffir-Simpson scale interval it was decided to use the values of wind speed and central pressure corresponding to the worst case in that scale. Since category 5 has no upper limit in wind speed and lower limit in central pressure, the values shown in the table were chosen based on historical worst case Caribbean values.

Table 1:

CATEGORY CENTRAL PRESSURE Vmax Forward Speed (mb) (mph) (mph) 1-min 1 980 94 17.3 2 965 109 17.3 3 945 129 17.3 4 920 154 17.3 5 900 173 17.3

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COMPUTATIONAL MESH

Figure 6 shows the computational mesh used for this study. Being an unstructured mesh it goes from very high resolution in the nearshore (- 30 m) to low resolution (- 20 km) near the mesh boundary in deep water. All in one single mesh, avoiding grid nesting that complicates things. Figure 7 shows a zoom of the mesh around St Croix. Figure 8 shows the same around St Thomas. And Figure 9 shows the same around St John. The mesh was created using the SMS computational package.

As an example of the versatility of the unstructured mesh in handling complex coastlines, Figure 10 shows a zoom centered on Charlotte Amalie, St Thomas. The mesh penetrates inland up to an elevation of 20 m under the assumption that no storm surge will ever reach that elevation. The mesh has higher resolution in shallow waters and it decreases as we move to deeper waters. This can be seen in Figures 11 to 15, which show filled contour plots of grid spacing.

Once the computational mesh is created the next step is to interpolate the available bathymetry and topography to the mesh nodes. Figures 16 to 20 show filled contour plots of the resulting bathymetry and topography as seen by the models. Bathymetry is given as positive values, while topography is assigned negative values.

Figure 6 - Computational mesh used for the ADCIRC+SWAN model simulations. 7

Figure 7 - Computational mesh used for the ADCIRC+SWAN model simulations in the region of St. Croix Island.

Figure 8 - Computational mesh used for the ADCIRC+SWAN model simulations in the region of St. Thomas Island.

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Figure 9 - Computational mesh used for the ADCIRC+SWAN model simulations in the region of St. John Island.

Figure 10 - Computational mesh used for the ADCIRC+SWAN model simulations in the region of Charlotte Amalie, St. Thomas Island. 9

Figure 11 - Plot of grid spacing distribution in the entire mesh used for the ADCIRC+SWAN model simulations. Solid black lines are shorelines.

Figure 12 - Plot of grid spacing distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of St. Croix Island. Solid black lines are shorelines. 10

Figure 13 - Plot of grid spacing distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of St. Thomas Island. Solid black lines are shorelines.

Figure 14 - Plot of grid spacing distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of St. John Island. Solid black lines are shorelines.

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Figure 15 - Plot of grid spacing distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of the US Virgin Islands. Solid black lines are shorelines.

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Figure 16 - Plot of bathymetry distribution in the entire mesh used for the ADCIRC+SWAN model simulations. Solid black lines are shorelines. Bathymetry is given as positive values, while topography is assigned negative values.

Figure 17 - Plot of bathymetry distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of St. Croix Island. Solid black lines are shorelines. Bathymetry is given as positive values, while topography is assigned negative values.

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Figure 18 - Plot of bathymetry distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of St. Thomas Island. Solid black lines are shorelines. Bathymetry is given as positive values, while topography is assigned negative values.

Figure 19 - Plot of bathymetry distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of St. John Island. Solid black lines are shorelines. Bathymetry is given as positive values, while topography is assigned negative values.

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Figure 20 - Plot of bathymetry distribution in the mesh used for the ADCIRC+SWAN model simulations in the region of US Virgin Islands. Solid black lines are shorelines. Bathymetry is given as positive values, while topography is assigned negative values.

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MANNING'S N ROUGHNESS COEFFICIENT

(the following on Manning’s coefficients is taken verbatim from Jose Benitez M.S. thesis)

Land Cover for USVI

Bottom friction is parameterized using a Manning’s n formulation, with spatially-variable values based on land classification. Manning’s n roughness coefficients, or simply Manning coefficients, are spatially assigned to the mesh nodes which lie inland using a data set of land cover for USVI. This data set was derived through NOAA's Coastal Change Analysis Program (C-CAP) in 2007. Figure 21, Figure 22, and Figure 23 show land cover distributions for the island St. Croix, St. Thomas and St. John. The effects of land cover on surge water flow are considered by introducing various Manning coefficients based on the National Land Cover Database (NLCD). A modified table of Manning coefficients, Table 2, corresponding to different land cover classes proposed by Mattocks and Forbes (2008) was employed in this study. Note that the land categories Developed High Intensity, Developed Medium Intensity, and Developed Low Intensity (not shown in Table 2) are reduced to Impervious.

USVI Benthic Zones

The term benthic refers to anything associated with or occurring on the bottom of a permanent body of water. In order to assign Manning's coefficients to those nodes in the USVI computational mesh which lie inside the USVI benthic zones near shore, a data set containing information on the region's coral reefs, seagrass beds, mangrove forests, and other important habitats within the benthic zones were used as shown in Figure 24 and Figure 25. The NOAA's National Ocean Service acquired aerial photographs for the nearshore waters of the U.S. Virgin Islands in 1999, thus, creating a benthic habitat map. In Table 3, a Manning coefficient is assigned to each one of the different benthic habitat listed. These values for Manning coefficient were derived from the United Stated Geological Survey (USGS), among other reference sources for hydraulic information.

Table 2: NLCD land cover classes with assigned values for the Manning coefficients.

NLCD Land Cover Class Manning Coefficient

Unclassified 0.025

Impervious 0.050

Open Space Developed 0.020

Cultivated Land 0.037

Pasture / Hay 0.033

Grassland / Herbaceous 0.034 16

Deciduous Forest 0.100

Evergreen Forest 0.110

Scrub / Shrub 0.050

Palustrine Forested Wetland 0.100

Palustrine Scrub Shrub Wetland 0.048

Palustrine Emergent Wetland 0.045

Estuarine Forested Wetland 0.100

Estuarine Scrub Shrub Wetland 0.048

Unconsolidated Shore 0.040

Barren Land (Rock/Sand/Clay) 0.090

Open Water 0.020

Palustrine Aquatic Bed 0.015

Rest of Computational Mesh

Apart from the nodes that lie inside the land cover and benthic zones discussed above, for the rest of the nodes in the USVI computational mesh, a default constant Manning coefficient of 0.024 was employed in the ADCIRC model. This is approximately equivalent to flow over unrippled sand or mud. With respect to the SWAN model, the bottom fiction used was the one based on the JONSWAP formulation (Hasselmann et al., 1973) with constant friction coefficient Cb = 0.067 m2 s−3.

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Figure 21 - 2007 C-CAP Land Cover for St. Croix Island. 18

Figure 22 - 2007 C-CAP Land Cover for St. Thomas Island. 19

Figure 23 - 2007 C-CAP Land Cover for St. John Island.

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Table 3: Benthic zones with assigned values for the Manning coefficients.

Benthic Habitat Manning Coefficient Sand 0.0260 Mud 0.0200 Linear Reef 0.0488 Spur and Groove Reef 0.0488 Patch Reef (Individual) 0.0488 Patch Reef(Aggregated) 0.0488 Scattered Coral/Rock in Unconsolidated Sediment 0.0260 Colonized Pavement 0.0900 Colonized Bedrock 0.0900

Colonized Pavement with Sand Channels 0.0900

Reef Rubble 0.0500

Uncolonized Pavement 0.0900

Uncolonized Bedrock 0.0900

Land 0.0240 Mangrove 0.0450 Artificial 0.0488 Unknown 0.0260

Seagrass -- Continuous 0.0150

Seagrass -- Patchy(70-<90%) 0.0150

Seagrass -- Patchy(50-<70%) 0.0150

Seagrass -- Patchy(30-<50%) 0.0150

Seagrass -- Patchy(10-<30%) 0.0150

Macroalgae -- Patchy(50-<90%) 0.0150

Macroalgae – Patchy(10-<50%) 0.0150

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Figure 24 - Benthic zones for St. Croix Island.

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Figure 25 - Benthic zones for St. Thomas and St. John Islands.

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MODEL SETUP

During all simulations, the ADCIRC model ran at a time step of two seconds instead of a time step of one second in order to reduce simulation time. The SWAN model ran at a time step of 900 seconds except for the validation simulations that ran at a time step of 600 seconds. The coupling time between ADCIRC and SWAN was 600 seconds, that is, data was shared between the models every 600 seconds. Wetting and drying was allowed so flooding could occur over inland nodes in the computational mesh. No run-up wave model was used; hence the could be underestimated at some locations. All time and spatial nonlinear terms of ADCIRC were activated. Bottom friction was activated using a Manning- type friction law. Refraction was also activated throughout all the mesh. In the case of the validation runs, new coordinates for the center of the hurricane were updated every 6 hours from the data provided by the HURDAT database.

ASTRONOMICAL TIDE VALIDATION

To validate the hydrodynamic performance of the ADCIRC model, tide-only simulations were executed for periods centered on the days of passage of (1995), (1996), (1998), (1999), (2008), (2010), and (2011). That is, ADCIRC (SWAN is not used in the astronomical tidal validations) is used to compare the ADCIRC-computed tides with the NOAA-predicted tides. This is an excellent way to test the bathymetry since discrepancies in tidal amplitudes, and especially tidal phases, will show up if the bathymetry is not good. It is important to understand that the comparisons do not include the ADCIRC+SWAN predicted, nor the NOAA tide gauge observed storm surges. That will come in a separate section titled Storm Surge Validation.

Although the total tide is composed of hundreds of known tidal constituents, most have very small amplitudes so only the largest eight are required to capture over 90% of the tidal signal for ocean modeling applications. The eight primary lunar and solar tidal harmonic constituents (K1, O1, P1, Q1, N2, M2, S2, K2) were designated at each open-water boundary node in the computational mesh. These tidal constituents were obtained from TOPEX/Poseidon Global Inverse Solution TPXO (Egbert et al., 1994). The nodal factor and equilibrium argument for boundary and interior domain forcing tidal constituents are determined based on the starting time of the simulation. The appropriate nodal factor and equilibrium arguments for each tidal validation simulation are shown in Table 4 to Table 10. For the simulations the ADCIRC model had a spin-up time of 18 days and a total length of simulation of 60 days. Only a few days of each simulation were taken into consideration for the comparisons.

The average seasonal cycle of mean sea level, caused by regular fluctuations in coastal temperatures, salinities, winds, atmospheric pressures, and ocean currents, is shown in Figures 26 to 29 along with each month's 95% confidence interval. Based on this an average seasonal cycle correction was made to the tide-only simulation solution by adding the seasonal height correction to the simulated tide elevation. This seasonal water expansion factor was also included in the section of storm surge validations where the ADCIRC+SWAN results are compared with tide gauge observations. 24

Table 4: Tidal constituents, nodal factors and equilibrium arguments used for Hurricane Marilyn simulation. Nodal factors and equilibrium arguments were calculated for a 60 day period starting on July 25, 1995. Equilibrium Argument Tidal Constituent Nodal Factor (in degrees) K1 0.90127 217.24 O1 0.83858 199.98 P1 1.00000 147.76 Q1 0.83858 9.89 N2 1.03292 229.83 M2 1.03292 59.92 S2 1.00000 0.00 K2 0.77822 253.68 Table 5: Tidal constituents, nodal factors and equilibrium arguments used for Hurricane Bertha simulation. Nodal factors and equilibrium arguments were calculated for a 60 day period starting on May 17, 1996. Equilibrium Argument Tidal Constituent Nodal Factor (in degrees) K1 0.88606 147.42 O1 0.81323 229.28 P1 1.00000 215.02 Q1 0.81323 118.90 N2 1.03672 267.68 M2 1.03672 18.07 S2 1.00000 0.00 K2 0.75385 114.38 Table 6: Tidal constituents, nodal factors and equilibrium arguments used for Hurricane Georges simulation. Nodal factors and equilibrium arguments were calculated for a 60 day period starting on July 30, 1998. Equilibrium Argument Tidal Constituent Nodal Factor (in degrees) K1 0.90085 212.48 O1 0.83789 4.00 P1 1.00000 142.56 Q1 0.83789 189.36 N2 1.03303 39.16 M2 1.03303 213.80 S2 1.00000 0.00 K2 0.77752 245.77 25

Table 7: Tidal constituents, nodal factors and equilibrium arguments used for Hurricane Lenny simulation. Nodal factors and equilibrium arguments were calculated for a 60 day period starting on September 25, 1999. Equilibrium Argument Tidal Constituent Nodal Factor (in degrees) K1 0.93671 265.76 O1 0.89698 102.27 P1 1.00000 86.62 Q1 0.89698 174.20 N2 1.02357 76.10 M2 1.02357 4.17 S2 1.00000 0.00 K2 0.84159 352.25 Table 8: Tidal constituents, nodal factors and equilibrium arguments used for Hurricane Omar simulation. Nodal factors and equilibrium arguments were calculated for a 60 day period starting on August 25, 2008. Equilibrium Argument Tidal Constituent Nodal Factor (in degrees) K1 1.08834 249.14 O1 1.14298 265.42 P1 1.00000 116.37 Q1 1.14298 264.67 N2 0.97338 156.06 M2 0.97338 156.81 S2 1.00000 0.00 K2 1.23198 318.83 Table 9: Tidal constituents, nodal factors and equilibrium arguments used for Hurricane Earl simulation. Nodal factors and equilibrium arguments were calculated for a 60 day period starting on July 08, 2010. Equilibrium Argument Tidal Constituent Nodal Factor (in degrees) K1 1.03407 204.28 O1 1.05487 241.27 P1 1.00000 164.16 Q1 1.05487 330.20 N2 0.99361 178.17 M2 0.99361 89.25 S2 1.00000 0.00 K2 1.06753 228.95 26

Table 10: Tidal constituents, nodal factors and equilibrium arguments used for Hurricane Irene simulation. Nodal factors and equilibrium arguments were calculated for a 60 day period starting on July 01, 2011. Equilibrium Argument Tidal Constituent Nodal Factor (in degrees) K1 0.99686 197.61 O1 0.99473 158.96 P1 1.00000 171.29 Q1 0.99473 250.62 N2 1.00589 92.33 M2 1.00589 0.67 S2 1.00000 0.00 K2 0.97161 215.20

Figure 26 - Average seasonal cycle of mean sea level for the Charlotte Amalie station. 27

Figure 26- Average seasonal cycle of mean sea level for the LimeTree Bay station.

Figure 27 - Average seasonal cycle of mean sea level for the Magueyes Island station.

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Figure 28 - Average seasonal cycle of mean sea level for the San Juan station.

A total of eight tide stations were selected for the tide comparisons. Table 11 lists some information about these tide stations such as their respective station ID numbers and locations. The data from these stations are available in the NOAA's Tides and Currents database available through the internet. The ADCIRC tide simulation results were compared to the harmonic tide predictions at these NOAA tide station in order to avoid any atmospheric influences and measurement errors. ADCIRC was able to predict the harmonic tides very well for each of the hurricanes used in this study.

Table 11: NOAA Tide Stations for tide and storm surge comparisons.

Station ID Station Location Location Coordinates 9759110 Magueyes Island, 17° 58.2' N, Puerto Rico 67° 2.7' W 9752235 Culebra Island, 18° 18.0' N, Puerto Rico 65° 18.1' W 9752695 Esperanza, Vieques Island, 18° 5.6' N, Puerto Rico 65° 28.2' W San Juan, 18° 27.5' N, 9755371 Puerto Rico 66° 6.9' W 9751364 Christiansted Harbor, 17° 45' N, St Croix, USVI 64° 42.3' W 9751401 Lime Tree Bay, 17° 41.6' N, St. Croix, USVI 64° 45.2' W 9751639 Charlotte Amalie, 18° 20.1' N, St. Thomas, USVI 64° 55.2' W 9751381 Lameshur Bay, 18° 19.0' N, St. John, USVI 64° 43.4' W

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Astronomical Tide Validation during the passage of Hurricane Marilyn (1995)

Hurricane Marilyn was the fifteenth tropical depression and thirteenth named storm of the 1995 season. Marilyn struck the on September 14, at category 1 strength, and made landfall in USVI on September 15, at category 2 strength. The following eight figures show the harmonic tides predicted by the ADCIRC model along with the ones predicted at NOAA tide stations during Hurricane Marilyn. The results agree very well.

Figure 29 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Charlotte Amalie station in St. Thomas Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

Figure 30 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Christiansted Harbor station in St. Croix Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

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Figure 31 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Culebra station in Culebra Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

Figure 32 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Esperanza station in Vieques Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

Figure 33 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lamehur Bay station in St. John Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

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Figure 345: Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lime Tree Bay station in St. Croix Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

Figure 36: Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Magueyes station in Magueyes Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

Figure 37: Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the San Juan station in Puerto Rico for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

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Astronomical Tide Validation during the Passage of Hurricane Georges (1998)

Hurricane Georges was the seventh tropical storm and fourth hurricane of the 1998 Atlantic hurricane season. Georges passed south of USVI on September 21, at category 2 strength. The following eight figures show the harmonic tides predicted by the ADCIRC model along with the ones predicted at NOAA tide stations for Hurricane Georges. The results agree very well.

Figure 38 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Charlotte Amalie station in St. Thomas Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

Figure 39 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Christiansted Harbor station in St. Croix Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

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Figure 40 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Culebra station in Culebra Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

Figure 41 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Esperanza station in Vieques Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

Figure 42 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lamehur Bay station in St. John Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

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Figure 43 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lime Tree Bay station in St. Croix Island for Hurricane Georges (1998).

Figure 35 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Magueyes station in Magueyes Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

Figure 36 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the San Juan station in Puerto Rico for Hurricane Georges (1998). Surface elevation is relative to MHW.

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Astronomical Tide Validation during the Passage of Hurricane Lenny (1999)

Hurricane Lenny was the twelfth tropical storm and eighth hurricane of the Atlantic hurricane season. Lenny formed on November 13 in the western and maintained an unprecedented west-to-east track for its entire duration. On November 17, it passed south of USVI, eventually dissipating on November 23 over the open Atlantic Ocean. The following eight figures show the harmonic tides predicted by ADCIRC along with the ones predicted at NOAA tide stations for Hurricane Lenny. The results agree very well.

Figure 46 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Charlotte Amalie station in St. Thomas Island for Hurricane Lenny (1999). Surface elevation is relative to MHW

Figure 47 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Christiansted Harbor station in St. Croix Island for Hurricane Lenny (1999). Surface elevation is relative to MHW. 36

Figure 48 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Culebra station in Culebra Island for Hurricane Lenny (1999). Surface elevation is relative to MHW.

Figure 37 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Esperanza station in Vieques Island for Hurricane Lenny (1999). Surface elevation is relative to MHW.

Figure 50 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lamehur Bay station in St. John Island for Hurricane Lenny (1999). Surface elevation is relative to MHW.

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Figure 381 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lime Tree Bay station in St. Croix Island for Hurricane Lenny (1999). Surface elevation is relative to MHW.

Figure 392 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Magueyes station in Magueyes Island for Hurricane Lenny(1999). Surface elevation is relative to MHW.

Figure 403 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the San Juan station in Puerto Rico for Hurricane Lenny (1999). Surface elevation is relative to MHW.

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Astronomical Tide Validation during the Passage of Hurricane Omar (2008)

Hurricane Omar was a strong hurricane that took an unusual southwest to northeast track through the eastern Caribbean Sea during October, 2008. Omar passed south of USVI on October 15. The following eight figures show the harmonic tides predicted by ADCIRC along with the ones predicted at NOAA tide stations for Hurricane Omar. The results agree very well.

Figure 414 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Charlotte Amalie station in St. Thomas Island for Hurricane Omar (2008). Surface elevation is relative to MHW.

Figure 42 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Christiansted Harbor station in St. Croix Island for Hurricane Omar (2008). Surface elevation is relative to MHW.

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Figure 436 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Culebra station in Culebra Island for Hurricane Omar (2008). Surface elevation is relative to MHW.

Figure 57 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Esperanza station in Vieques Island for Hurricane Omar (2008). Surface elevation is relative to MHW.

Figure 58 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lamehur Bay station in St. John Island for Hurricane Omar (2008). Surface elevation is relative to MHW.

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Figure 59 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lime Tree Bay station in St. Croix Island for Hurricane Omar (2008). Surface elevation is relative to MHW.

Figure 60 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Magueyes station in Magueyes Island for Hurricane Omar (2008). Surface elevation is relative to MHW.

Figure 61 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the San Juan station in Puerto Rico for Hurricane Omar (2008). Surface elevation is relative to MHW.

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Astronomical Tide Validation during the Passage of Hurricane Earl (2010)

Hurricane Earl was the fifth tropical storm of the Atlantic hurricane season. Earl passed northeast of the on August 30, causing moderate damage. The following eight figures show the harmonic tides predicted by ADCIRC along with the ones predicted at NOAA tide stations for Hurricane Earl. The results agree very well.

Figure 62 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Charlotte Amalie station in St. Thomas Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

Figure 4463 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Christiansted Harbor station in St. Croix Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

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Figure 64 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Culebra station in Culebra Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

Figure 6465 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Esperanza station in Vieques Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

Figure 45 6 6- Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lamehur Bay station in St. John Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

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Figure 67 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lime Tree Bay station in St. Croix Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

Figure 68 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Magueyes station in Magueyes Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

Figure 69 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the San Juan station in Puerto Rico for Hurricane Earl (2010). Surface elevation is relative to MHW.

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Astronomical Tide Validation during the Passage of Hurricane Irene (2011)

Hurricane Irene was the ninth tropical storm and first hurricane of the Atlantic hurricane season. the system was designated as Tropical Storm Irene on August 20. After intensifying, Irene made landfall in St. Croix, USVI, as a strong tropical storm later that day. The following eight figures show the harmonic tides predicted by ADCIRC along with the ones predicted at NOAA tide stations for Hurricane Irene. The results agree very well.

Figure 70 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Charlotte Amalie station in St. Thomas Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

Figure 71 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Christiansted Harbor station in St. Croix Island for Hurricane Irene (2011). Surface elevation is relative to MHW. 45

Figure 72 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Culebra station in Culebra Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

Figure 73 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Esperanza station in Vieques Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

Figure 74 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lamehur Bay station in St. John Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

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Figure 75 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Lime Tree Bay station in St. Croix Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

Figure 76 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the Magueyes station in Magueyes Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

Figure 77 - Surface elevation time series comparison between the NOAA and ADCIRC tide prediction at the San Juan station in Puerto Rico for Hurricane Irene (2011). Surface elevation is relative to MHW.

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STORM SURGE VALIDATION

Storm Surge, which in this report will include the astronomical tide plus the storm surge, is now validated by ADCIRC+SWAN at four of the eight stations as shown in Table 15. Four stations do not contain storm tide data. In the following subsections, for each hurricane four figures are given showing the validations of storm tide at the four stations for which there is storm surge data.

The models were forced with NOAA’s Automated Forecast (ATCF) winds, a product that has been available since 2003. These files contain forecast guidance, along with position and intensity estimates of Tropical and Subtropical Cyclones.

Storm Surge Validation for Hurricane Marilyn (1995) (see Figure 78)

Figure 78 – Hurricane Marilyn track.

Figure 79 show that ADCIRC+SWAN underestimated the storm tide compared against the data obtained from the tide station at Charlotte Amalie in St. Thomas. Figure 80 shows a good fit prior, and up to the peak in the storm surge at the tide station at Lime Tree Bay in St. Croix. No figures are shown for Magueyes Island and San Juan since there was no storm surge at these stations. 48

Figure 79 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Charlotte Amalie station in St. Thomas Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

Figure 80 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Lime Tree Bay station in St. Croix Island for Hurricane Marilyn (1995). Surface elevation is relative to MHW.

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Storm Surge Validation for Hurricane Bertha (1996) (see Figure 81)

Figure 81- Track for Hurricane Bertha.

For hurricane Bertha, ADCIRC+SWAN slightly underestimated the storm tide at Charlotte Amalie station, but the result is quite good (see Figure 82). For the stations at Lime Tree Bay, St Croix, at Magueyes Island, and San Juan, there was no surge signal, so results are not shown.

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Figure 82 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Charlotte Amalie station in St. Thomas Island for Hurricane Bertha (1996). Surface elevation is relative to MHW.

Storm Surge Validation for Hurricane Georges (1998) (see Figure 83)

Figure 83 – Track for Hurricane Georges. 51

In the case of Hurricane Georges, the ADCIRC+SWAN simulated very well the storm tide at the tide stations in Charlotte Amalie, as seen in Figure 84. At Lime Tree Bay, St John, there was a slight phase shift, as seen in Figure 85. Figure 86, for Magueyes Island, shows an underestimate compared with observations. Finally, Figure 87, for San Juan Bay, shows a near perfect agreement.

Figure 84 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Charlotte Amalie station in St. Thomas Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

Figure 85 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Lime Tree Bay station in St. Croix Island for Hurricane Georges (1998). Surface elevation is relative to MHW. 52

Figure 86 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Magueyes station in Magueyes Island for Hurricane Georges (1998). Surface elevation is relative to MHW.

Figure 87 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the San Juan station in Puerto Rico for Hurricane Georges (1998). Surface elevation is relative to MHW.

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Storm Tide Validation for Hurricane Lenny (1999) (see Figure 88)

Figure 88 – Track for Hurricane Lenny. It came from west to east.

For (Wrong-way) Lenny there was a small signal at Charlotte Amalie, St Thomas, which was well matched in amplitude, but out of phase (Figure 89). At Lime Tree Bay, St Croix, the models well over predicted the amplitude of the storm tide, as can be seen in Figure 90. At Magueyes Island, nor San Juan Bay, was there any signal.

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Figure 89 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Charlotte Amalie station in St. Thomas Island for Hurricane Lenny (1999). Surface elevation is relative to MHW.

Figure 90 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Lime Tree Bay station in St. Croix Island for Hurricane Lenny (1999). Surface elevation is relative to MHW.

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Storm Tide Validation for Hurricane Omar (2008) (see Figure 91)

Figure 91 – Track of Hurricane Omar. It moved from southwest to northeast.

A small storm tide signal for Hurricane Omar was observed at Lime Tree, St Croix, the closest of the USVI. Figure 92 shows the comparison.

Figure 92 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Lime Tree Bay station in St. Croix Island for Hurricane Omar (2008). Surface elevation is relative to MHW. 56

Storm Tide Validation for Hurricane Earl (2010) (see Figure 93)

Figure 93 – Track for Hurricane Earl.

For Hurricane Earl only two stations showed signals. Figure 94 shows the comparison for Charlotte Amalie, St Thomas, where the fit is good. Figure 95 shows the comparison for San Juan Bay.

Figure 94 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Charlotte Amalie station in St. Thomas Island for Hurricane Earl (2010). Surface elevation is relative to MHW.

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Figure 95 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the San Juan station in Puerto Rico for Hurricane Earl (2010). Surface elevation is relative to MHW.

Storm Tide Validation for Hurricane Irene (2011) (see Figure 96)

Figure 96 – Track for Hurricane Irene.

For Hurricane Irene the only two significant signals were at Charlotte Amalie, St Thomas (see Figure 97), and Lime Tree Bay, St Croix (see Figure 98). In both stations the models did well. 58

Figure 97 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Charlotte Amalie station in St. Thomas Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

Figure 98 - Time series comparison between storm tide observed by NOAA and the one predicted by ADCIRC+SWAN at the Lime Tree Bay station in St. Croix Island for Hurricane Irene (2011). Surface elevation is relative to MHW.

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CAVEATS

It is important to highlight the caveats involved in the preparation of hazard maps like these since it is important for the users to know what’s missing, especially if it might lead to an underestimation of the hazard. These are independent of model limitations and of input bathymetry and topography potential errors.

· It should be emphasized that the following coastal flood maps show what is called the stillwater elevations. This is what a tide gauge would measure, filtering the high-frequency (periods of, say, 20 seconds or smaller) waves. · Related with the above caveat, the maps do not show the flooding due to wave runup (the high- frequency waves propagating inland on top of the stillwater elevation and breaking nearshore, and inland, like a bore or a sheet of seawater. It is known that wave runup can make a significant contribution to coastal flooding by seawater, increasing even more the flooded areas shown in the maps. · The effect of infragravity waves is not included. These are low-frequency (periods of a few minutes), coastally-trapped waves that can temporarily increase the stillwater elevations when the wave crest is passing by. In some cases these can also be an important factor. · No rainfall flooding, nor ponding due to rainfall, is included. Nor the effect of flash floods moving water downslope to the coast. · The stillwater elevations are given relative to Mean High Water. That is, it is assumed that the storm surge occurs at high astronomical tide. · These maps show potentially floodable areas under the scenario of a given category hurricane passing through the most critical trajectory for any given coastal site. Any different hurricane track will tend to show, in general, smaller flooding depths for that site. · The maps are based on the best available topographic and bathymetric data as obtained in the early 2000’s, and used for tsunami flood mapping for NOAA. The DEM resolution is 1/3 arc seconds (approximately 10 meters), and it tries to be bare-earth. That is, vegetation and infrastructure have mostly been eliminated. Information about the actual topographic roughness conditions at a given location is supplied by the use of assigned Manning coefficients to each computational node. Since the topographic and bathymetric data was obtained by the use of the LiDAR technology, in places with turbid waters the signal is not capable of reaching the bottom. As a consequence, rivers are represented as an almost flat surface upriver from almost its river mouth. And this surface lies 0.1 to 0.5 m above Mean High Water (it is dry land). The same happens in inland water bodies like coastal lagoons (Lagunas San Jose and Torrecillas, part of the San Juan Bay Estuary). · The dynamic interaction between river discharge and storm surge is not contemplated. · The storm surge propagation upriver is not reliable due to the lack of riverine bathymetric data. · Sea level rise is not contemplated. · Coastal morphological changes (due to wave erosion) during the storm are not included. Nor are any changes happening between the dates of topographic and bathymetric acquisition and the present. 60

· Land use information and sea bottom features that are included as a computational attributes, and both necessary for friction parameterization, are based on data that might not be up to date. It will be up to a year that an update of that information will be available.

RESULTS

In this section we will show the resulting coastal flood figures by hurricane category. Figures will not be shown for each individual track since these are too many. We will only show, for each category, the SuperMOM . That will be a total of 5 figures for each of the three islands. These are shown in Figures 99 to 113. In Figures 114 to 124 the storm surge from this study has been merged with the FEMA Flood Insurance shapefiles for the USVI.

ACKNOWLEDGMENTS

The support of the CariCOOS program is greatly appreciated. Also of the following individuals: Julio Morell, Harry Justiniano, Jorge Capella, and Juan Gonzalez.

St. Thomas

SuperMOM CATEGORY 1 (flooded areas painted green)

Figure 99 – St Thomas, category 1.

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SuperMOM CATEGORY 2 (flooded areas painted olive)

Figure 100 – St Thomas, category 2.

SuperMOM CATEGORY 3 (flooded areas painted yellow)

Figure 101 – St Thomas, category 3. 62

SuperMOM CATEGORY 4 (flooded areas painted dark orange)

Figure 102 – St Thomas, category 4.

SuperMOM CATEGORY 5 (flooded areas painted red)

Figure 103 – St Thomas, category 5. 63

St. John

SuperMOM CATEGORY 1 (flooded areas painted green)

Figure 104 – St John, category 1.

SuperMOM CATEGORY 2 (flooded areas painted olive)

Figure 105 – St John, category 2.

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SuperMOM CATEGORY 3 (flooded areas painted yellow)

Figure 106 – St John, category 3.

SuperMOM CATEGORY 4 (flooded areas painted dark orange)

Figure 107 – St John, category 4.

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SuperMOM CATEGORY 5 (flooded areas painted red)

Figure 108 – St John, category 5. St. Croix

SuperMOM CATEGORY 1 (flooded areas painted green)

Figure 109 – St Croix, category 1.

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SuperMOM CATEGORY 2 (flooded areas painted olive)

Figure 110 – St Croix, category 2.

SuperMOM CATEGORY 3 (flooded areas painted yellow)

Figure 111 – St Croix, category 3.

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SuperMOM CATEGORY 4 (flooded areas painted dark orange)

Figure 112 – St Croix, category 4.

SuperMOM CATEGORY 5 (flooded areas painted red)

Figure 113 – St Croix, category 5.

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COMPARISON WITH FEMA

Figure 114 – Comparison with FEMA Flood Insurance Rate Maps. Category 1.

Figure 115 – Comparison with FEMA Flood Insurance Rate Maps. St Thomas. Category 2. 69

Figure 116 – Comparison with FEMA Flood Insurance Rate Maps. St Thomas. Category 3.

Figure 117 – Comparison with FEMA Flood Insurance Rate Maps. St Thomas. Category 4. 70

Figure 118 – Comparison with FEMA Flood Insurance Rate Maps. St Thomas. Category 5.

Figure 119 – Comparison with FEMA Flood Insurance Rate Maps. St John. Category 1. 71

Figure 120 – Comparison with FEMA Flood Insurance Rate Maps. St Croix. Category 1.

Figure 121 – Comparison with FEMA Flood Insurance Rate Maps. St Croix. Category 2. 72

Figure 122 – Comparison with FEMA Flood Insurance Rate Maps. St Croix. Category 3.

Figure 123 – Comparison with FEMA Flood Insurance Rate Maps. St Croix. Category 4. 73

Figure 124 – Comparison with FEMA Flood Insurance Rate Maps. St Croix. Category 5.