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5 - STORM SURGES IN PUERTO RICO: San_Juan (Luis Muñoz Marín) Airport

Before starting with the detailed analysis for the LMM airport, it is important to mention the following issues:

• A very important issue is the following. Due to the fact that the Lidar signal used to obtain the topography and bathymetry in the early 2000s could not penetrate the water surface in the lagoons forming part of the San Juan Bay Estuary Program, the DEMs prepared by NGDC/NOAA (and used to prepare the computational mesh for ADCIRC+SWAN) have a flat lid over those lagoons, lying about 0.3 – 0.5 m above the datum of the DEMs (MHW). Therefore, caution should be used for areas (all around the island) that border these coastal lagoons. The same holds for the major island rivers. It is not known what the effect on the inland flooding this problem will cause.

• It is important to also mention that the topographic data used to prepare the computational grid was the 1/3 arc-seconds (approximately 10 m resolution) prepared for tsunami flood mapping by NGDC/NOAA, and freely available through the Internet. The resolution of the computational mesh at the airport location is shown in Figure 21 below. By using the GE ruler one can estimate the spacing between nodes composing the finite elements triangles to vary between 65 to 95 meters in the airport area. So we had data to go to higher resolution in the mesh, but this triangle size was required by both computer and time limitations. Given the importance of the airport for the island, a more detailed, and higher resolution, study might be warranted. And the same holds for other critical facilities in the island. See Technical Report for more details.

• Finally, it should be pointed out that the flood maps to be shown show the flooding potential for the hurricane whose trajectory is the most critical for the location of interest. For example, for the San Juan airport a hurricane making landfall in Cabo Rojo is not expected to generate the flooding shown in the images below. Among the collection of hurricane tracks shown in Figures 8-10 there is one, or a pair, that will produce the worst case scenario for the airport. The same holds for all other locations.

The following figure (Figure 1) shows a Google Earth (GE) image of the airport. It has the Atlantic Ocean to its north, the Torrecillas lagoon to its east (actually, the north runway protrudes into the lagoon), the San Jose Lagoon to its west, and several narrow channels lying closer all around it. According to the link https://www.airnav.com/airport/TJSJ, the northernmost runway (#8) lies at an elevation of 2.53 m (8.3 ft) above MSL. Figure 2 shows topographic information according to a 1/9 arc-seconds (approximately 3 m) resolution DEM prepared by NGDC/NOAA. Contour values are in meters above MHW. To bring the contour values to MSL add 0.132 to each value (according to NGDC/NOAA). Figure 3 shows the same Digital Elevation Model, but using the technique of shaded relief. Figure 4 shows the same image, but now based on the 2016 bare-earth DEM obtained from the US Corps of Engineers. Vertical positions were referenced to the (NAD83 NA11; MSL PRV02) ellipsoid, and provided in meters. Vertical position accuracy is ∀0.1 m RMSE. And Figure 5 shows a zoom of the area inside the red box in Figure 4. I am not concerned about absolute values of the elevations. What I am trying to show is that the figures tend to tend to give the impression that the northern runway seems to lie at a slightly lower elevation than its surroundings, both north and south. A word of caution about that interpretation! A closer look at the Figures 3, 4, and 5 show an irregular area along the seaward border of the north runway. Figures 6 and 7 show that irregular area to be vegetation that was not taken care off when trying to get bare-earth values. It is that vegetation that gives the impression that the airport’s north

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runway is like a canal, with higher ground both north and south of it. And the vegetation plays the role of a solid dyke protecting the northern runway from direct flooding from the sea. We know that’s not true along the runway’s northern side, but the computer model thinks that the runway is like a flat canal. As the storm surge increases in elevation, it starts flooding the runway along the Torrecillas lagoon side (since it cannot flood the runway by moving directly south), and for a certain hurricane category (specifically category 3) all of the runway is flooded from east to west. And one will see that the areas of the vegetation along its northern side are not flooded. This doesn’t mean that the runway will not be flooded on its entirety by a category 3, but the waters will spread north into the canal that runs along that side, and the final picture will be that the inundation might extend all the way to

Highway 187 which lies between the Carolina public beach and the runway. After a certain storm surge elevation that canalization effect will become less obvious. So a word of caution about the use of Lidar topographic information which has not been completely cleared of vegetation. On the other hand, the only reason we could notice this “canalization” effect is due to the relatively high resolution modeling that was carried out. The bottom line is that it is possible that we might be underestimating the flooding of the airport due to errors in the bare-earth data. The same holds by the non-presence of the narrow canals that run along the runways, which cannot be resolved at the resolution used. Although we tried to make it as high as possible, time and computer limitations did not allow to increase the resolution.

This highlights the need to prepare a better computational mesh if more accurate results are desired for the airport. With mode accurate topographic data.

Figure 1 - Google Earth image of the San Juan Luis Muñoz Marin International Airport.

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Figure 2 - Topography at the San Juan Luis Muñoz Marin International Airport. Source: NGDC/NOAA 1/9 arc-seconds (3 m) DEM. Elevations are relative to MHW.

Figure 3 - Topography at the San Juan Luis Muñoz Marin International Airport. Source: NGDC/NOAA 1/9 arc-seconds (3 m) DEM.

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Figure 4 - Topography at the San Juan Luis Muñoz Marin International Airport. Source: USCoE 1 m DEM (2016).

Figure 5 - Zoom inside the red box shown in Figure 4. Shaded relief and contour plot the topography inside the box. Elevations are in meters.

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Figure 6 – Google Earth image showing the area inside the red box in Figure 15. Note the row of dense vegetation running along the sea side of the northern runway.

Figure 7 - Google Earth image showing the area inside the red box in Figure 15. Note the row of dense vegetation running along the sea side of the northern runway.

Figure 8 shows the present FEMA map for the airport, and Figure 9 shows the accompanying Legend. The airport falls in four tiles, which we have tried to assemble into one in a crude way. This figure allows comparison of the PRSSA maps with the FEMA map for the airport. It can be seen that the south runway

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lies completely outside of the 500-year flood, and the north runway shows limited flooding by the 500-year event (less than 0.3 meters flood depth). One of the handicaps of the FEMA maps is that they don’t show where the flooding is by seawater and where by fresh water.

Figure 10 shows the bathtub-type flooding by +1.0 m rise in sea level based on the latest USCoE 1 meter resolution DEM (2016). The case for +0.5 m rise in sea level cannot be detected at the scale of this figure. So it is not shown. The red curve outlines the z = 0 m elevation contour, which symbolizes the shoreline (the DEM datum is MSL, PRV02). The blue curve shows the z = +1.0 m elevation contour, with hachures pointing downhill (i.e., towards smaller elevations). By bathtub-type flooding is meant the simplest way to show the inland flooding by sea level rise, in which if sea level rises to +1.0 m then one assumes that it floods all of the nearshore terrain that lies below, and up to, +1.0 m. Note that the flooding remains basically in the vegetated areas. But by this time the phreatic level would be creating havoc all over the airport. We can use Figure 10 to estimate the additional flooding generated by the storm surge for the case of an initial sea surface elevation of +1.0 m above MSL.

Figure 11 shows the density of computational nodes in the airport vicinity, with a small, white, cross located at the position of each computational node. At each of these crosses the models output a result, which can be the SWE relative to MHW, the SWE relative to the local terrain elevation, the Significant Wave Height, Hs, and the Peak Wave Period of the waves, Tp. [NOTE: The computational mesh used for ADCIRC+SWAN is an unstructured mesh, composed of small triangles with a computational node at the vertex of each triangle; the triangles size vary with position. In some places there is a higher density of triangles in order get more accurate results. The reader should remember that each computational node is assigned a Manning coefficient based on land use. See technical report for more details.]

Let’s now show the images for category 1 to 5 under present sea level conditions. Figures 12 to 16 show the Inundation Depths (also called Local Water Depths, both in meters) for Categories 1 to 5 hurricanes, under present sea level elevation (actually, the data was taken in the early 2000s). It is extremely important to understand that these are sillwater elevations (SWE) with no wave runup/overtopping included, as emphasized at the beginning. And please also remember the caveats involved in the project. The figures speak for themselves about the vulnerability of this very important airport. As in the FEMA map, the inundation potential is worst for the eastern end of the airport. The increase in seawater flooding in going from Category 1, or 2, to Category 3 is dramatic. All of the north runway becomes flooded by seawater starting with the Category 3 hurricanes, as if it were of lower elevation than its surroundings (recall the discussion above based on Figures 3-7). We show flow depth. It is possible that the inundation could be worse if the row of vegetation along the seaside of the north runway were not there since what the model sees is like a solid dyke lying there. Or if that row of vegetation were allowed to pass water from the sea side to the runway. Something which is much more realistic than allowing the vegetation to act as a solid, impermeable, barrier.

On the other hand, as far as wave propagation inland, the vegetation in reality should act as an energy dissipation barrier. Something more alike to the presence of a dyke. Although the models used (ADCIRC+SWAN) output the Significant Wave Heights (Hs) at each computational node, for the airport we will not show those results.

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Figure 8 – FEMA map for the San Juan Luis Muñoz Marin International Airport. FEMA tiles used 360J, 380J, 370J, and 390J.

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Figure 9 - Legend accompanying the FEMA maps.

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Figure 10 – Topographic map of the San Juan airport based on the 1 meter resolution USCoE 2016 DEM. Elevations are relative to MSL, PRV02. Red line shows the z = 0 m elevation (shoreline), while blue line shows the 1 m elevation contour (shown with hachure pointing downhill). All painted areas outlined by the blue curve would be flooded.

Figure 11 – GE image of the San Juan Luis Muñoz Marin International Airport showing the location (white crosses) of computational nodes of the computational mesh utilized. See Technical Report for more details.

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Figure 12 – Inundation Depth for Category 1 hurricane for SLR = 0 m. See metadata at the top for hurricane characteristics.

Figure 13- Inundation Depth for Category 2 hurricane for SLR = 0 m. See metadata at the top for hurricane characteristics

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Figure 14- Inundation Depth for Category 3 hurricane for SLR = 0 m. See metadata at the top for hurricane characteristics

Figure 15 - Inundation Depth for Category 4 hurricane for SLR = 0 m. See metadata at the top for hurricane characteristics

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Figure 16 - Inundation Depth for Category 5 hurricane for SLR = 0 m. See metadata at the top for hurricane characteristics

Next the results for a sea level rise of +0.5 m are shown in Figures 17 to 21. It should be mentioned that an initial elevation of +0.5 m is not so far into the future since in 2015 the monthly mean sea surface elevation measured at the San Juan tide gauge was slightly above 0.21 m for two months in a row (September and October, 2015). See the section on Sea Level Watch around Puerto Rico.

It is important to note that running a storm surge model on top of an initial sea surface elevation of Z meters does not necessarily gives the same results as adding Z meters to results obtained by running the model with Z = 0 m. That’s why of the need to re-run everything again, but now with initial water elevations of +0.5 and +1.0 m.

Figures 22 to 26 show the results for an initial sea surface elevation of +1.0 m. Now the storm surge finds itself with a base line flooding shown in Figure 10 by the areas inside the blue curve.

I think that we can conclude that the Luis Muñoz Marin is located in a vulnerable location and, at some moment in this century there will be no other choice than relocating it. And it should be recognized that problems will start appearing prior to the manifestation of water overtopping the runways. Even with no hurricane passing by.

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Figure 17 - Inundation Depth for Category 1 hurricane for SLR = +0.5 m. See metadata at the top for hurricane characteristics.

Figure 18- Inundation Depth for Category 2 hurricane for SLR = +0.5 m. See metadata at the top for hurricane characteristics.

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Figure 19- Inundation Depth for Category 3 hurricane for SLR = +0.5 m. See metadata at the top for hurricane characteristics.

Figure 20 - Inundation Depth for Category 4 hurricane for SLR = +0.5 m. See metadata at the top for hurricane characteristics.

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Figure 21 - Inundation Depth for Category 5 hurricane for SLR = +0.5 m. See metadata at the top for hurricane characteristics.

Figure 22 - Inundation Depth for Category 1 hurricane for SLR = +1.0 m. See metadata at the top for hurricane characteristics.

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Figure 23- Inundation Depth for Category 2 hurricane for SLR = +1.0 m. See metadata at the top for hurricane characteristics.

Figure 24 - Inundation Depth for Category 3 hurricane for SLR = +1.0 m. See metadata at the top for hurricane characteristics.

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Figure 25 - Inundation Depth for Category 4 hurricane for SLR = +1.0 m. See metadata at the top for hurricane characteristics.

Figure 26 - Inundation Depth for Category 5 hurricane for SLR = +1.0 m. See metadata at the top for hurricane characteristics.