Improving the Planning Process to Protect Infrastructure from Emerging Coastal Flood Hazards

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Infrastructure Protection Resources: Improving the Planning Process to Protect Infrastructure from Emerging Coastal Flood Hazards

Marathon and Key Largo in Monroe County, North Bay Village and North Miami in Miami-Dade County, and Dania Beach and Hollywood in Broward County

Part 1 (of 3)

Identifying and Ground-Truthing Tidal Flooding Hotspots in Six Pilot Communities

Page 1 of 91 Acknowledgements

Department of Economic Opportunity South Florida Regional Planning Council

Barbara Lenczewski, PhD AICP, Project Manager Isabel Cosio Carballo, Executive Director

Keren Bolter, PhD, Project Manager

Christina Miskis, Project Co-Manager

Vince Edwards, Analyst

This publication was funded by a Community Planning Technical Assistance grant, provided pursuant to section 163.3168, F.S., and Specific Appropriation 2220, Chapter 2016-66, Laws of Florida, to provide direct and/or indirect technical assistance to help Florida communities find creative solutions to fostering vibrant, healthy communities, while protecting the functions of important State resources and facilities.

Completed January 2017

Page 2 of 91 Executive Summary

The Fall King Tide flooding in South Florida adds approximately a foot of water to the region’s average daily high tide. The King Tide events allow for a glimpse of what a low-lying coastal community will look like in coming decades if no actions are taken. This coastal flood risk analysis reports two key results for 2016 Fall King Tide flooding in six South Florida communities. Presented here is documentation of in situ measurement and modelling of the extreme water levels, as well as maps of future tidal flood extent given one and two-foot sea-level rise scenarios. From September to November of 2016, the South Florida Regional Planning Council (SFRPC) worked to identify tidal flooding hot spots and to conduct in situ measurements during predicted extreme events. Results were used to identify and analyze discrepancies and gaps between actual observed flooding and flooding predicted by the National Oceanic and Atmospheric Administration (NOAA) Mean Higher High Water (MHHW) surface data. Comparing the predictions to observations allows for “ground-truthing” of modeled results, as well as applications to inform appropriate flood mitigation practices.

Moderate to severe levels of tidal flooding were documented in all six communities. Results show that predicting and quantifying tidal flooding requires a complex understanding of local factors, including geology, infrastructure, natural resources, and community structure. For example, several study areas within a community were predicted to have similar water level heights, but the impacts of these water levels differed dramatically. The areas inhabited by wetlands did not appear to be affected; wading birds were perched upon mangroves. Areas with recent infrastructure improvements such as backflow preventers were not impacted. The most dramatic and severe flooding was observed in areas where water overtopped the seawall or bulkhead, or where seawater travelled into the streets through a 2-way drainage system.

This report outlines the methods for the data collection and analysis, and presents the results as a series of maps for the six communities. The best available Light Detection and Ranging (LIDAR) surface elevation data was overlaid with observed extreme tide levels, Vertical Datum Transformation (VDATUM) MHHW tidal surfaces, and NOAA data for historical high water level data to identify tidal flooding hotspots and areas projected as susceptible to future flooding vulnerability due to extreme tides combined with one and two feet of permanent inundation. This analysis may be applied to validate modeled results or to make recommendations for improvements. Adjusting for real-time observations allows for a unique and in-depth perspective on how risk is spatially distributed within the pilot communities. Results may be used to inform decision-making and prioritization of resources.

Page 3 of 91 Table of Contents Executive Summary ...... 3 Table of Contents ...... 4 Infrastructure Protection Resources Project Description ...... 6 Background Information ...... 6 Tide Gauges Measurements and Variations ...... 7 The National Tidal Datum Epoch and Mean Higher High Water ...... 12 Ocean Currents ...... 13 Sea-Level Rise Predictions ...... 14 Descriptions of Pilot Communities ...... 16 North Bay Village...... 19 Hollywood ...... 19 Dania Beach ...... 19 Key Largo ...... 19 North Miami ...... 20 Islamorada ...... 20 King Tide Events Media Coverage ...... 20 Methods ...... 22 In-Situ Sampling ...... 22 Processing of Sample Data ...... 23 GIS Modeling Using NOAA Water Levels, MHHW, and LIDAR ...... 25 Results and Discussion ...... 27 In-Situ Measurement Data ...... 27 2016 High Tide Records ...... 30 Data Limitations ...... 33 Analysis Components ...... 33 MHHW Layer ...... 33 King Tide and Compound Flooding Maps ...... 38 Maps ...... 41 Hollywood and Dania Beach ...... 41 North Miami ...... 49 North Bay Village...... 55 Key Largo ...... 59 Islamorada ...... 65 Roads ...... 70 Flood Zones and Base Flood Elevation Maps ...... 70 Coastal Flood Threshold Inundation Extent ...... 74 Conclusion ...... 76 References ...... 77 Appendices ...... 80 A: VDATUM: 2016 Update for East Florida...... 80 B: Sea-Level Rise Data: NOAA Flood Frequency and Threshold Inundation Extent ...... 80 C: Harmonic Constituents for Tide Gauge 8723214, Virginia Key FL ...... 82 D: Data Specifications for Broward and Monroe County LIDAR...... 83 E: Miami Dade 2015 LIDAR Metadata ...... 84 F: FLORIDA MANGROVES - APRIL 2015 ...... 86 G: UF GeoPlan Center Infrastructure ...... 87 H: FLORIDA FLOOD INSURANCE RATE MAP (DFIRM) - MAY 2016 ...... 88 I: Utilities ...... 90 J: SLR Projections ...... 90 Page 4 of 91 Table of Figures

Figure 1: Map of tide gauge and pilot community locations...... 9 Figure 2: Virginia Key, Vaca Key, and Key West tide gauge stations...... 9 Figure 3: Classification of tide cycles based on daily tide peaks and magnitudes...... 11 Figure 4: Predicted and verified water levels at Vaca Key from 10/14/16 to 10/16/16. . 12 Figure 5: Seasonal high tide water levels at Virginia Key, FL ...... 13 Figure 6: SLR scenarios; projections shown developed by USACE and NOAA...... 14 Figure 7: Exceedance probabilities and mean water level elevations...... 15 Figure 8: Data points used in SLR projection curves...... 15 Figure 9: The six pilot communities in this study: Dania Beach, Hollywood, North Miami, North Bay Village, Key Largo, and Islamorada...... 16 Figure 10: Community growth rates, 1990-2016...... 17 Figure 11: Median household and per capita income. Source: 2015 5-year ACS estimates...... 18 Figure 12: Breakdown of housing tenure. Source: 2015 5-year ACE estimates...... 18 Figure 13: 2014 King Tide flooding in Miami Beach...... 20 Figure 14: 2016 King Tide flooding in Hollywood prompted local authorities to put out caution signs to warn drivers about flooded streets...... 21 Figure 15: Residents struggled to get around downtown Fort Lauderdale in nearly a foot of water during 2016...... 21 Figure 16: Driveway flooding in Dania Beach...... 22 Figure 17: Flooding in the neighborhood of Hollywood Lakes...... 22 Figure 18: Measuring water flood water levels...... 23 Figure 19: Using Google MyMaps to plot sampling sites for easily shareable visualizations...... 24 Figure 20: Southeast Florida MHHW values in feet referenced to NAVD88...... 25 Figure 21: MHHW values in Islamorada, referenced to NAVD88...... 26 Figure 22: MHHW levels relative to Virginia Key water levels...... 26 Figure 23: MHHW values adjusted for King Tide water levels...... 26 Figure 24: Verified water levels at Virginia Key during September 2015 King Tides. .... 31 Figure 25: Verified water levels at Virginia Key during September 2016 King Tides. .... 31 Figure 26: Winds at Virginia Key over a four-day period prior to October 2016 King Tides. Notice effects off offshore winds due to Hurricane Nicole...... 32 Figure 27: Winds at Virginia Key over a four-day period prior to September 2016 King Tides...... 32 Figure 28: Variation in MHHW along the Southeast Florida coastline; projected inland using VDATUM...... 34 Figure 29: Key to reading the maps on the following pages; red shows present flooding extent during extreme tides, yellow under an additional foot of sea-level rise and green under an additional two feet of sea-level rise...... 40 Figure 30: Projected number of discrete coastal flooding events and number of days per year flooding occurs at Virginia Key, Vaca Key, and Key West...... 74 Figure 31: Predicted flooding extent in Southeast Florida when the aforementioned flood thresholds are exceeded...... 75

Page 5 of 91 Infrastructure Protection Resources Project Description

This summary report is the first of three resources in a series of Infrastructure Protection Resources which are aimed at providing technical assistance to local governments wishing to increase resilience to coastal flooding, particularly during extreme events such as high tides and storm surge. The six specific local pilot communities for this project were selected because they have a high risk of inundation from coastal flooding and because the local governments are planning mitigation practices for existing and emerging tidal flooding conditions. The first part of the project documented here consists of data collection and analysis based on in situ measurement and modelling of current and projected Fall King Tide flooding. The next resource, set for completion in April 2017, is a summary report for a series of surveys given to local governments to document the extent of existing and emerging tidal flooding conditions and any planned mitigation. The final resource, set for completion in June 2017, focuses on one community, North Bay Village, to prepare and transmit comprehensive plan amendment(s) which address deficiencies in the Village’s response to Peril of Flood. This amendment will include best available data, including recently released storm surge data from the Sea, Lake, and Overland Surges from Hurricane (SLOSH) model to designate the Coastal High Hazard Area.1

Background Information

In order to plan for future sea level rise, modeling of projections is important. One way to then assist in authenticating these modeled projections is to examine how they align or diverge from flooding events that closely approximate future sea level conditions. This research seeks to identify predicted hot spots using MHHW and LIDAR data provided by NOAA, followed by ground-truthing these predictions during King Tide events. This will provide valuable insight into the accuracy of these modeled predictions, the efficacy of recent infrastructure improvements, and what the implications of future SLR might be.

The term nuisance flooding is often used to describe the periodic flooding that occurs during in South Florida, a phrase that tends to imply nothing more than simple inconvenience. However, local residents will frequently attest that what was once a simple inconvenience has been increasingly disruptive over the last several decades, from causing significant traffic slow-downs to more severe property damage (Boehrer, 2014; Robles and Alvarez, 2016; Clary, 2016).

1 http://sfregionalcouncil.org/swflslosh/

Page 6 of 91 The most common of this recurrent flooding is caused the by the seasonal cycle of extreme tides, often called King Tides. These are acute events that occur at regular intervals, the dates and times of which can be predicted with relatively high accuracy via tide charts and the orbit of the moon. While these tides are relatively short-lived at present, and considered only to be “nuisance” by some, both the length of this flooding and the extent of inundation are increasing. When coupled with projected increased in sea level, the impacts may be devastating. In several cases over the last ten years, high tides have also coincided with increased sea levels due to storm surge—this will be explored in greater depth in the sections that follow. As a result of the increased severity of this flooding, and the potentially additive nature of the inputs described, infrastructure improvements and coastal protection must be made a top priority.

Definitions Related to High Tide Events, Tidal Datums, and Measurement

 Local tides are related to astronomical considerations (related to the position of the Earth, sun and moon) and non-astronomical factors such as configuration of the coastline, local depth of the water, ocean-floor topography, and other hydrographic and meteorological influence.  Extreme water levels: extremely high or low water levels at coastal locations are an important public concern and a factor in coastal hazard assessment, navigational safety, and ecosystem management. Exceedance probability, the likelihood that water levels will exceed a given elevation, is based on a statistical analysis of historic values.  Perigean tides: refers to a tide that occurs when the moon is closest to the earth  Spring tides: occur twice each lunar month (during full or new moons), during which high tides are a little higher and low tides are a little lower.  Perigean spring tides are the largest astronomical tides, occurring when spring tides and perigean tides coincide. They occur at intervals that are slightly more than six months long, so each year they are later in the season than the preceding year. For this reason, we must refer to tables of predicted tides to know exactly when to expect these unusually high tides. These are colloquially referred to as “King Tides.”  Tide cycle: pattern of high and low tides that occur in a given basin or region of a basin due to reflections of the tidal bulge off of land masses as it progresses around the planet.

For more key terms and definitions, visit NOAA at http://tidesandcurrents.noaa.gov/restles2.html, http://www.nhc.noaa.gov/surge/, http://w1.weather.gov/glossary/.

Tide Gauges Measurements and Variations

The purpose of this section is to elucidate the complexity of tide gauge measurements as well as the spatial and temporal variability of these measurements throughout South Florida. This background information is important as it justifies the methods used to select tide gauges and datasets for this project.

It was determined that the best tide gauge to use for all pilot communities was Virginia Key. Different tide gauges are used for a variety of applications, and each method

Page 7 of 91 was considered and discussed with NOAA technical experts before this was decided. A detailed investigation was required for the researchers to understand how a range of measurements related to the sampling details for each pilot community. The results of this research is summarized in this section.

NOAA’s tide gauges are classified as either harmonic or subordinate. A subordinate station is inactive. Harmonic gauges are those where harmonic constants have been calculated—these are not necessarily still active, however. Within our study area, there exist only three active harmonic gauges: Virginia Key, Vaca Key, and Key West. These three gauges are the only three where both predicted water levels and verified water levels are reported. Harmonic constants are calculated from a variety of individual factors and cyclical variations that dictate the tides in a given location, largely based on the positioning of the Earth, moon, and sun. A sample of these constituents can be found in Table 1: A sampling of variables used to calculate tidal harmonic constants below; full details listing all 37 constituents can be found in the Appendix.

Harmonic Constituents for 8723214, Virginia Key FL

Constituent # Name Amplitude Phase Speed Description 1 M2 0.98 256 28.9841 Principal lunar semidiurnal constituent 2 S2 0.17 281.3 30 Principal solar semidiurnal constituent 3 N2 0.22 239.3 28.43973 Larger lunar elliptic semidiurnal constituent 4 K1 0.1 187.9 15.04107 Lunar diurnal constituent 5 M4 0.02 139.6 57.96821 Shallow water overtides of principal lunar constituent 6 O1 0.09 218.6 13.94304 Lunar diurnal constituent Table 1: A sampling of variables used to calculate tidal harmonic constants. Full table can be found in Appendix.

1. M2: Principal lunar semidiurnal constituent. This constituent represents the rotation of the Earth with respect to the Moon. Speed = 2T - 2s + 2h = 28.984,104,2° per solar hour. 2. S2: Principal solar semidiurnal constituent. This constituent represents the rotation of the Earth with respect to the Sun. Speed = 2T = 30.000,000,0° per solar hour. 3. N2: Larger lunar elliptic semi diurnal constituent. Speed = 2T- 3s + 2h + p = 28.439,729,5° per solar hour. 4. K1: Lunisolar diurnal constituent. This constituent, with O1, expresses the effect of the Moon's declination. They account for diurnal inequality and, at extremes, diurnal tides. With P1, it expresses the effect of the Sun's declination. Speed = T + h = 15.041,068,6° per solar hour. 5. M4: Shallow water overtides of the principal lunar constituent. Speed of M4 = 2M2 = 4T - 4s + 4h = 57.968,208,4° per solar hour. 6. O1: Lunar diurnal constituent. Speed = T - 2s + h = 13.943,035,6° per solar hour.

Figure 2 is a map showing the three active harmonic gauges in the region and the locations of the pilot communities in this study. Figure 2: Virginia Key, Vaca Key, and Key West tide gauge stations. shows what these tide gauge stations actually look like while. Tide predictions at a given time are made by summing the oscillating contributions of individual constituents that have calculated from long-term water level records. The time periods over which these averages are computed vary significantly; some cycles operate over a period of hours, some longer than a month (Parker, 2007).

Page 8 of 91 Figure 1: Map of tide gauge and pilot community locations.

Figure 2: Virginia Key, Vaca Key, and Key West tide gauge stations.

Page 9 of 91 A full list of tide gauges can be found using NOAA’s tide gauge map service2. Excluding the three gauges previously mentioned, the remainder are classified as either inactive harmonic stations or subordinate stations. A subordinate station is one where specific harmonic constants have not been calculated and active water levels are no longer being recorded. However, enough historic data exists at these gauges to determine the differences in time and water level of tides relative to one of the three active harmonic gauges. As such, each of the subordinate gauges is listed as “referenced to” one of those three. This relationship allows tide predictions to be made at these subordinate stations, despite the fact that they do not actively read water levels themselves. Inactive harmonic stations do not need to be referenced to active stations; enough data exists that predictions can be made without establishing this relationship, despite the fact that they are no longer recording data.

It’s important to note which active harmonic gauge a given subordinate gauge is referenced to, and why this relationship has been established. This depends less on spatial proximity and more on similarities in tides, which occur under different cycles depending on a variety of factors. If the Earth was perfectly spherical and contained no extremely large land masses, all coastlines would experience two nearly equivalent high and low tides every lunar day. However, this is not the case—continents block the procession of this otherwise relatively uniform tidal bulge around the globe, and complex patterns exist in the Earth’s ocean basins that produce three somewhat distinct tidal cycles (Sumich, 1996).

Semi-diurnal tide cycles are those with two distinct high tides and two distinct low tides, such as most areas along the East Coast of the US. Diurnal cycles are found in the Gulf of Mexico, where only one high and low tide are experienced each lunar day. The third common tidal cycle is mixed semidiurnal; this can be considered somewhat of a blend of the two. These are experienced across most of the West Coast of the US. Figure 3 below visually describes these three distinct cycles.

2 https://tidesandcurrents.noaa.gov/map/index.shtml?type=PreliminaryData®ion=Florida

Page 10 of 91 Figure 3: Classification of tide cycles based on daily tide peaks and magnitudes.

Because of the interface between the diurnal cycle of the Gulf of Mexico and semidiurnal cycle present along the Atlantic Coast, parts of the Florida Keys experience a cycle that doesn’t adequately conform to either one. While generally not considered to be categorized as a mixed-semidiurnal tide regime, water levels recorded at the Vaca Key tide gauge do share features with this type of cycle, shown in Figure 4 (He, 2002). The Florida Department of Natural Resources has stated that “the tides of the Keys are chiefly semidiurnal but generally are mixed with a diurnal phase. The tide amplitudes trend to dominantly semidiurnal nearest the neap tides and are most notably mixed nearest the spring tides” (Clark, 2000). As previously discussed, each of the subordinate tide gauges are referenced to one of the three active harmonic stations, and this is based upon similarities in tide cycle. For example, the subordinate Alligator Reef Lighthouse tide gauge, located southest off the coast of Islamorada, is referenced to the Virginia Key tide gauge, despite it’s geographic closeness to the harmonic gauge on Vaca Key. The is because, based on historic data collected at the lighthouse gauge, the tide cycle and other variations at this point more closely resemble the patterns present in Miami (even if water levels do not,

Page 11 of 91 Figure 4: Predicted and verified water levels at Vaca Key from 10/14/16 to 10/16/16. the patterns are related), rather than those present at the Vaca Key gauge. In fact, Vaca Key serves as a “stand-alone” active station—no subordinate stations are presently referenced back to this station because of the instability and irregularity of the tides at this location.

The National Tidal Datum Epoch and Mean Higher High Water

Tidal datums are another important concept to address when analyzing variations in sea level. This document frequently references Mean Higher High Water (MHHW), which is defined as the average of the highest daily tides over a given time period, the National Tidal Datum Epoch (NTDE). The present NTDE extends from 1983 to 2001. This temporal distinction exists because it averages out tidal variations that result from the moon’s precession, or change in rotational axis, over 18.6 years (Parker, 2007). This period is also called the lunar nodal cycle. The establishment of a set period is critical, as it allows measurements to be referenced to the same set of control points; this is also the principle that allows land elevations or horizontal positions to be referenced to the same model of the Earth.

Over the NTDE period, there is an overall cyclical fluctuation in the mean range of tide, which is the height between the lowest tide and the highest tide at a given location. Recent literature has suggested that there is cyclical contribution to water levels from peaks and troughs in the lunar nodal cycle. The median amplitude globally was found to be 2.2 centimeters, and there was found to be a trend in regional mean sea levels (Baart, 2011). Additionally, it’s suggested that sea-level rise projections based on tide gauge data

Page 12 of 91 extending longer than 60 years inherently accounts for this variation. While noteworthy, the magnitude of this variation and potential increase in tide height is generally dwarfed by other factors over short time periods, such as weather patterns, seasonal cycles, and other general hydrologic variability, however should be considered when using short datasets to project future sea-level rise (Woodworth, 2011). One such seasonal cycle, the seasonal variation in high tides, is shown below in Figure 5. The largest peak shown below occurs in the Fall, which coincides with the end of the wet season in South Florida as well. There is also a relatively smaller peak in annual mean sea level that occurs in the spring; these are commonly referred to as spring tides, however often go unnoticed in comparison to the much larger Fall tides.

Figure 5: Seasonal high tide water levels at Virginia Key, FL

Ocean Currents

Results from recent studies, synthesized in the Southeast Florida Regional Climate Compact’s Unified Sea Level Rise Projection, have suggested that relationships can be drawn between fluctuations in Atlantic Ocean currents and rates of sea-level rise on the Florida coastline (Southeast Florida Regional Climate Compact, 2015). In one study, models were developed to explain the correlation between a 30% weakening of the Gulf Stream in the 1960s with a sudden spike in sea levels (up to 10 centimeters over a few

Page 13 of 91 years)—similar relationships were found to have occurred more recently in 2009-2010 (Ezer, 2015). These findings were corroborated by two separate studies, both linking accelerated sea-level rise over the last decade with a decline in mean transport of the Gulf Stream along the Florida coast (Kirtman, 2012; Park 2015).

Sea-Level Rise Predictions

The following relative sea-level rise projections in Figure 6 were generated using the US Army Corps of Engineers’ (USACE) Sea Level Change Curve Calculator3. Zero levels have been set at 1992, the midpoint year for the current NTDE. Various estimates are shown, based on both NOAA and USACE rates of projected sea-level rise. All estimates are based on regional local mean sea level, and have been adjusted to reflect regional variations in vertical land motion due to subsidence (Zervas, Gill, & Sweet, 2013). This study employs projections made by USACE from Key West, rather than Virginia Key, simply because a longer dataset exists at this gauge. Longer datasets take into consideration a greater amount of variability, such as the lunar nodal cycle described above.

Figure 6: SLR scenarios; projections shown developed by USACE and NOAA.

3 For more information on the U.S. Army Corps of Engineers Sea Level Change Methods, see: http://www.corpsclimate.us/ccaceslcurves.cfm

Page 14 of 91

Figure 8 shows the data points that make up the curves presented on the previous page. This document does not serve to forecast which of these curves is most probable, but rather to present the full range of likely outcomes. Additionally, local increases vary from gauge to gauge— the predictions shown represent estimations for Key West; however, these differ from region to region.

Figure 8: Data points used in SLR projection curves.

Figure 7 shows the annual exceedance probabilities in relation to various tidal datums at the Key West tide gauge. Blue squares show water levels that are very likely to be reached; red diamonds are much higher, and less likely to be exceeded. Also note that current tide levels have increased from those averages used in the computation of the NTDE’s datums.

Figure 7: Exceedance probabilities and mean water level elevations.

Page 15 of 91 Descriptions of Pilot Communities

The six pilot communities, shown in Figure 9, are Dania Beach, Hollywood, North Miami, North Bay Village, Key Largo, and Islamorada. They were selected as sampling sites for this investigation, as they all frequently experience King Tide flooding and represent a rough cross-section of communities along the Southeast Florida coast. Each of these communities’ experience tidal flooding and have implemented various degrees of protection strategies in an attempt to mitigate this flooding.

Figure 9: The six pilot communities in this study: Dania Beach, Hollywood, North Miami, North Bay Village, Key Largo, and Islamorada.

Page 16 of 91 The most recent available population data for the six communities is shown in Table 2. Additional information on community growth rates, housing tenure, per capita income, and median household income are shown in Figure 10, Figure 12, and Figure 11.

Table 2: Populations and trends of pilot communities, 1990 to 2016.

Population Growth (%) 1990 2000 2010 2016 (April 1st) 1990-00 2000-10 2010-16 North Miami 50,001 59,880 58,912 63,731 19.8 -1.6 8.2 North Bay Village 5,383 6,733 7,137 8,949 25.1 6.0 25.4 Dania Beach 13,183 20,061 29,639 31,093 52.2 47.7 4.9 Hollywood 121,720 139,368 140,768 146,155 14.5 1.0 3.8 Islamorada - 6,846 6,119 6,202 - -10.6 1.4 Key Largo 11,336 11,886 10,433 10,496* 4.9 -12.2 0.6* *These figures use US Census Bureau 2015 ACS 5-year estimates. US Bureau of the Census and UF Bureau of Economic and Business Research. Prepared by the South Florida Regional Prosperity Institute

Community Growth Rates: 1990-2016

60.0

50.0

40.0

30.0

20.0

10.0

0.0 1990-00 2000-10 2010-16 -10.0

-20.0

North Miami North Bay Village Dania Beach Islamorada Hollywood Key Largo

Figure 10: Community growth rates, 1990-2016.

Page 17 of 91 Housing Tenure 120

100

0 Dania Beach Hollywood North Miami North Bay Village Key Largo Islamorada

Rent Own

Figure 11: Breakdown of housing tenure. Source: 2015 5-year ACE estimates.

Median Household and Per Capita Income 70000

60000

50000

40000

30000

20000

10000

0 Dania Beach Hollywood North Miami North Bay Village Key Largo Islamorada

Median Household Per Capita

Figure 12: Median household and per capita income. Source: 2015 5-year ACS estimates.

Page 18 of 91 North Bay Village

North Bay Village is made up of several islands located in northcentral Biscayne Bay in Miami-Dade County. The island is almost entirely manmade; dredging in the Bay began in 1940 and by the middle of the decade, the island had been further expanded to include Treasure and Harbor Island. North Bay Village was incorporated in 1945, and is made up of several neighborhoods of single-family homes, high rise condominiums, and a small downtown area of businesses and restaurants. While much of the island is protected by sea walls, upwelling via storm drains has been observed during King Tide events. The Village’s most recent Comprehensive Plan highlights the need to address sea- level rise from a planning perspective at least every five years, incorporating feedback and recommendations from local stakeholders. Strategies are encouraged to be drafted over relatively short 25-year periods, in addition to long-term planning on 100-year horizons. North Bay Village encourages educating homeowners about sea-level rise, the potential for property damage, and mitigation strategies.

Hollywood

Founded in 1925, Hollywood is a city located in southeastern Broward County halfway between Miami and Fort Lauderdale, and includes over six miles of Atlantic Ocean beaches. There are several vibrant downtown areas in the city, including the boardwalks along the beach and public parks surrounded by shops and restaurants. The area is served by the nearby Lauderdale-Hollywood International Airport to the north, as well as Port Everglades, a major hub for some of the world’s largest cruise liners. Hollywood also supports a significant healthcare industry network, which is a major employer in the region. Low-lying east Hollywood is especially at risk, where upwelling through storm drains in some neighborhoods is common and pumps attempt to reverse the process.

Dania Beach

Dania Beach, located just north of Hollywood, is also located in Broward County and shares a small strip of beach between the coastline with Hollywood. The area was incorporated in 1904. The geographic bounds of the city were established during a partial secession from Hollywood in 1926. Recreation, boating, tourism, and radio are major industries in the area.

Key Largo

Key Largo, an unincorporated area in Monroe County, is one of the uppermost islands in the Florida Keys archipelago, and also the largest at 33 miles long. It is bordered by Everglades National Park to the northwest and John Pennekamp Coral Reef State Park to the east, both of which attract boaters, divers, and ecotourists. Officials with Monroe County have conducted analyses on several major county roads to determine the

Page 19 of 91 feasibility of raising them to combat nuisance tidal flooding; while expensive, it may be their best option (Robles and Alvarez, 2016).

North Miami

North Miami, officially incorporated in 1926, is a suburban city located within Miami-Dade County right on Biscayne Bay. It composes the majority of the Arch Creek Basin, an area that has received considerable attention in recent years for its interest in increasing resilience due to repetitive losses from flooding. It may serve a model for surrounding areas as the region as a whole continues to push resiliency measures and adaptation strategies, including its designation as an Adaptation Action Area.

Islamorada

Islamorada is the southernmost community chosen to be included in this study, located in the middle Florida Keys. It’s composed of five inhabited islands, none wider than a mile, and several smaller islands that are important for local wildlife. In 2015, Islamorada conducted an intensive vulnerability assessment to outline measures intended to reduce the impact of sea-level rise. In this report, it was determined that nuisance flooding due to extreme tides was a top concern, impacting traffic and damaging property. At the time of publication, it was determined that Islamorada experiences this type of flooding an average of four times per year, a number that they projected to increase with sea-level rise (Catalysis, 2014).

King Tide Events Media Coverage

News coverage of King Tides in South Florida has been steadily on the rise over the last several years as nuisance flooding becomes increasingly problematic. Beginning in early October, media begins running stories about King Tide preparation, including preparing pumps, cleaning storm drains, and blocking off certain roadways that are particularly prone to inundation. In 2014, the Huffington Post ran a story describing the mitigation methods in place in Miami Beach, from hundreds of millions of dollars spent on pumps and hundreds of outflow valves, to the revitalization of dunes with sea oats and other soft infrastructure protection methods (Boehrer, 2014).

Figure 13: 2014 King Tide flooding in Miami Beach. Despite this, the city’s chief engineer at the

Page 20 of 91 time of publication was quoted as saying “[t]he technology is never as effective as it was when you first installed it,” and the City Manager at the time suggested it’s an uphill battle. Both of these sentiments exemplify the importance of better predicting flooding hotspots in order to more adequately defend against King Tide flooding and future sea-level rise.

The King Tides events in the fall of 2016 brought concerned residents from around the area to document damages, groups of students waded through knee-high water, and reporters interviewed locals and took pictures of the flooding. Often, homeowners in low-lying areas are unable to get their cars out of their driveways, and in some cases garages, and experience corrosion and other property damages resulting from Figure 14: 2016 King Tide flooding in Hollywood prompted local repeated salt-water inundation. authorities to put out caution signs to warn drivers about flooded streets. The New Times interviewed one resident, who had moved in over the summer only several months before, was upset that he had not been informed of the flooding prior to purchasing him home by the previous owner (Swanson, 2016). Another resident mentioned that she had recently noticed waters progressively getting higher, year after year.

Residents in Las Olas in Fort Lauderdale experience similar flooding every fall King Tide season. One resident interviewed by the Sun Sentinel noted that the flooding “isn’t the end of the world,” but can be a pain; he spoke with a reporter while piling sand bags around the base of Figure 15: Residents struggled to get around downtown Fort Lauderdale in nearly a foot of water during 2016. his driveway. Local business owners implemented the same strategy to protect their properties and inventories; several noted that the flooding puts a serious financial burden on the region

Page 21 of 91 during peak flooding days. In one neighborhood where the flooding reached a foot deep, a large “No Wake Zone” sign could be seen in the middle of what was usually a highly trafficked street (Clary, 2016). Coastal flood advisories were in effect in some areas that were particularly susceptible.

Methods

In-Situ Sampling

In the months leading up the projected King Tides of 2016, SFRPC staff spent time compiling maps and tabular information regarding projected flooding hotspots within the previously described pilot communities. This was done using GIS by projecting slight increases to the MHHW surface height, in accordance with previous King Tide heights, and comparing that to LIDAR elevation data. By estimating only relatively small increases in the MHHW surface, the investigators were able to pinpoint several proposed hotspots that would like likely flood first, and most dramatically, during the King Tide events. Hydrologic connectivity was accounted for, and results were found to be in close correlation with NOAA’s sea- Figure 16: Driveway flooding in Dania level rise and flooding visualization tools online. Beach.

Field sampling for this research took place in each of the six communities in September, October and November of 2016 during peak King Tide events, as predicted by NOAA. King Tide days and high tide times were determined by choosing the tide gauges geographically closest to the projected hotspots. For sites within all six communities, historic tide gauges were used as references, meaning while presently inactive, long enough data series exist from which tide Figure 17: Flooding in the neighborhood of Hollywood Lakes. estimates can be made.

Following the GIS assessment of potential flood locations, staff were tasked with investigating sites ahead of time to determine the suitability of the selected locations. Sites were required to have a hard, level surface within them, as LIDAR data collected

Page 22 of 91 over this type of groundcover suffers from minimal margins of error. Additionally, surfaces such as roads and sidewalks provided consistent points of reference over the time period the measurements were taken, whereas softer or more natural surfaces, such as sand or grass, may have been more subject to variability. Sites also needed to be verified as publically accessible or inaccessible private property—inaccessible areas were not immediately dismissed from the list of potential measurement sites. However, it was noted beforehand that exact measurements would likely be difficult to collect. In cases where these areas were still visible, investigators opted to use “flooding observed” or “not flood observed” distinctions, rather than specific depth measurements.

After determining peak King Tide days and times, as well as site suitability, arrangements were made for three SFRPC staff to conduct in-situ measurements in the pre-determined locations. There was considerable spatial and temporal variability in the predicted high tides which were extracted from the NOAA website. Travel routes and sampling order were carefully coordinated based upon local predicted high tide times, which, in some cases, varied by up to an hour over relatively small regions for the same high tide. In locations where flooding was in fact observed, inundation depths were measured above the hard surfaces, as previously described, using yardsticks. Depth and measurement time were recorded at each site, and specific location was determined using portable GPS devices. Additionally, photographs were taken of the water level against the yardsticks to ensure the original measurements could Figure 18: Measuring water flood water levels. be referred to later if necessary. Notes were also taken regarding hydroconnectivity and other information, such as blocked drainage infrastructure, cracked sea walls, and other relevant observations. Notes and data that were collected in the field were then compiled and transcribed into Excel tables. After transcription was complete for all sites, the information in the tables was re-validated using the coordinates and depths recorded by site specific geotagged photographs.

Processing of Sample Data

Following the data collection and conversion into Excel tables, the recorded points and attached information were imported into Google Maps using the MyMaps application, shown in Figure 19. This application also allows the user to attach photographs to each individual point. These maps are readily accessible via an internet browser and can be made publicly available. From this application, the points can be exported as a KMZ file,

Page 23 of 91 Figure 19: Using Google MyMaps to plot sampling sites for easily shareable visualizations. an XML-based extension that stores geographic data. The point locations and associated data can then be imported into ArcMap using the KMZ to Layer function. An additional point at Virginia Key was then added within ArcMap. The XY Coordinates tool was used to import the point coordinates into the point layer attribute table. The MHHW layer for the region, downloaded from NOAA, was then added, and the Extract Value to Point tool was used to assign the MHHW values at each of the points to the layer attribute table. The updated attribute table was then exported using the Table to Excel function.

Links to Google MyMaps:

Hollywood and Dania King Tide Measurements North Bay Village King Tide Measurements Key Largo King Tide Measurements North Miami King Tide Measurements

Page 24 of 91 GIS Modeling Using NOAA Water Levels, MHHW, and LIDAR

It is important to keep in mind that all of the tide levels and elevations used are referenced to the North American Vertical Datum of 1988 (NAVD88). To create a reference that relates the water levels at each site to Virginia Key, the MHHW relationships were used to compare relative high water levels to the observed water levels and the land elevations. For an example of how these relationships work, focus on the northernmost sampling point (yellow, in Dania Beach) indicated on the map in figure x. The MHHW value at this location is 0.50ft NAVD88, whereas this value is 0.25ft NAVD88 at Virginia Key. Therefore, to model how the water levels observed at Virginia Key translate to this particular point, the point must be referenced to the Virginia Key MHHW by taking the difference. Subtracting 0.25ft from 0.50ft gives a relative difference of +0.25ft, meaning that the modeled water level maximum at the sampling point is 0.25ft higher than the height recorded at Virginia Key, when referenced to NAVD88. This means that if 2.1ft NAVD88 was recorded Virginia Key (2.1ft is used because this was the highest recorded tide height over our sampling period— discussed in greater detail in subsequent sections), 2.35ft NAVD88 (2.1ft + 0.25ft) is the translated water level maximum at the sampling point. In this case, the water level maximum at the sampling point indicates that any land below 2.35ft NAVD88 would be inundated. With 1 and 2 feet of sea-level rise, the land below 3.35ft and 4.35ft respectfully, would be inundated. Figure 20 shows MHHW values in the region referenced to Figure 20: Southeast Florida MHHW values in feet referenced to NAVD88. NAVD88.

Page 25 of 91 While this example refers to one point, it can be applied to a continuous surface using the MHHW tidal raster layer and the LIDAR elevation raster layer. The series of layers are illustrated by zooming in on Islamorada. Figure 21 displays the MHHW values in Islamorada, relative to Virginia Key.

Since 0.25 is the value assigned to Virginia Key in the MHHW surface, the raster calculator was used to subtract .25 from the MHHW surface. This created a new surface with values relative to Virginia Key Figure 22. The relative value surface is simply the difference between the Virginia Key and each other point within the surface. Figure 23 displays the King Tide adjusted values in Islamorada. This surface Figure 21: MHHW values in Islamorada, referenced to NAVD88. was created by adding the value of 2.1 uniformly to the relative value surface.

Figure 22: MHHW levels relative to Virginia Key water levels.

Figure 23: MHHW values adjusted for King Tide water levels.

Page 26 of 91 In summary, adding the highest value observed at Virginia Key (2.1ft NAVD88) will adjust this maximum value to each sampling location, based on the difference between it and Virginia Key at the MHHW level. This King Tide Adjusted Layer (KTAL) is the surface which was used to create the maps for existing and emerging tidal flooding hotspots.

King Tide Continuous MHHW - .25 (Virginia Key MHHW) + 2.1 = Adjusted Layer

The LIDAR Elevation layer was subtracted from the KTAL surface to create an inundation layer. Wherever the inundation level is higher than the land, a tidal flooding hotspot emerges. Within this final layer, any negative values are dry, and positive values are wet during an extreme tide. For example, at a particular sampling point, imagine that the KTAL has a value of 2 feet and the LIDAR shows that point to be at an elevation of 3 feet. The subtraction of 2 – 3 = -1 shows the point to be dry. However, if these values were reversed, 3 – 2 = 1 indicates a foot of inundation.

King Tide - LIDAR Elevation = Inundation Adjusted Layer Layer Depth

The future sea-level rise layers were created by adding another foot to the KTAL for 1- foot SLR scenarios and 2 feet for 2-foot SLR scenarios. If a point’s KTAL has a value of 2 feet and the LIDAR shows that point to be at an elevation of 4 feet, that area will only become a tidal flooding hotspot in the 2 foot scenario maps.

Results and Discussion

In-Situ Measurement Data

The table on the following page shows results from the sampling that occurred during the October and November King Tide events in the six pilot communities. Addresses and geographic coordinates are provided for each sampling location, as well as information regarding the hydrologic connectivity and ground surface type. Areas shown as “0 feet” of inundation are points representing predicted hotspots where no flooding was observed at the time of investigation. The MHHW column gives the elevation, referenced to NAVD88, of the tidal surface at that location in feet—the relative column shows the adjusted value after converting the surface to a 0 height at Virginia Key.

Page 27 of 91 Location Lat. Long. Depth Oct16 Time Depth Nov15 Time Hydrologically Surface MHHW Adjusted Virginia Key 0.248 0 Dania Beach Eller Dr & Tracks - Not Observed 26.08248 -80.12952 0 8:45 Asphalt 0.499 0.251 Gulfstream & NW 2nd Pl 26.05704 -80.13153 9.5 9:09 4 9:36 Y Asphalt 0.349 0.101 Gulfstream & Alley 26.05655 -80.13152 11.5 9:12 10 9:39 Y Asphalt 0.257 0.009 Gulfstream & NE 2nd St 26.05615 -80.13152 4 9:15 3 9:36 Y Asphalt 0.219 -0.029 Hollywood A1a & Meade Street 26.04489 -80.11486 7.5 10:40 6 9:40 Y Concrete 0.257 0.009 Sheridan Park 26.03493 -80.11657 4 10:33 Y Asphalt 0.219 -0.029 A1a & Buchanan 26.01772 -80.11688 6.25 10:21 Y Asphalt 0.230 -0.018 N Southlake Drive 26.01029 -80.11869 11.25 10:04 6 10:04 Y Asphalt 0.217 -0.031 North Miami Trailer Park 7-10 Inches Of Water 25.90183 -80.15284 7 to 10 9:48 Asphalt 0.266 0.018 13105 Ixora Ct 25.89719 -80.15939 0.1 10:19 Asphalt 0.262 0.014 Marina 13000 Coronado Dr 25.89750 -80.15878 0.1 10:24 Asphalt 0.262 0.014 NE 135th St East From Bay Vista 25.90095 -80.14489 4 to 6 10:34 Y Asphalt 0.269 0.021 2603 NE 135th St 25.90076 -80.14737 2 10:41 Y Asphalt 0.269 0.021 Venice Park - Water At Ground Level 25.89934 -80.16196 0.1 10:47 Asphalt 0.262 0.014 Flood Control Structure 25.90044 -80.16247 0 11:09 Gravel Road 0.262 0.014 Flooding Predicted, Not Observed 25.89598 -80.16405 0 11:10 Asphalt 0.259 0.011 Flooding Predicted, Not Observed 25.88854 -80.15167 0 11:25 Asphalt 0.259 0.011 Flooding Predicted, Not Observed 25.88892 -80.14965 0 11:00 Asphalt 0.260 0.012 2190 NE 124th St 25.89024 -80.15300 0.1 11:07 Y Asphalt 0.259 0.011 Water Spilling Onto Property 25.89023 -80.15316 11:11 Asphalt 0.259 0.011 2225 NE 123rd St 25.88997 -80.15261 6.5 11:15 Y Asphalt 0.259 0.011 North Bay Village 1331 Bay Terrace 25.84421 -80.15872 2 12:05 Asphalt 0.285 0.037 1441 S Treasure Drive 25.84483 -80.15488 4 to 6.5 12:02 Asphalt 0.283 0.035 1471 S Treasure Drive 25.84525 -80.15482 5 to 7 12:06 Asphalt 0.282 0.034 1519 S Treasure Drive 25.84457 -80.15304 7 12:08 Asphalt 0.284 0.036 1541 S Treasure Drive 25.84460 -80.15281 6.75 to 7 12:10 Asphalt 0.283 0.035 1580 S Treasure Drive 25.84460 -80.15233 3.5 to 4.25 12:10 Asphalt 0.282 0.034 1601 S Treasure Drive 25.84460 -80.15223 4 12:11 Asphalt 0.282 0.034 7500 West Treasure Drive 25.84473 -80.15478 4 12:14 Asphalt 0.283 0.035 7504 West Treasure Drive 25.84474 -80.15487 12 to 13 12:17 Asphalt 0.283 0.035 7505 West Treasure Drive 25.84485 -80.15488 6.5 12:19 Asphalt 0.283 0.035 7556 South Treasure Drive 25.84714 -80.15492 7.5 12:15 Asphalt 0.282 0.034 Treasure And Bucaneer 25.84460 -80.15223 3 12:16 Asphalt 0.282 0.034 Key Largo North Blackwater Lane 25.15912 -80.38852 0.1 9:05 Asphalt -0.610 -0.858 Anchorage Resort And Yacht Club 25.18344 -80.38732 1 to 2 9:12 Asphalt -0.614 -0.862 Sexton And Blackwater Lane 25.15911 -80.38975 4 9:22 Asphalt -0.610 -0.858 8 Center Lane 25.15969 -80.39155 1-2 9:39 Asphalt -0.610 -0.858

Page 28 of 91 North Drive West Of Stillwright 25.16098 -80.39241 4 9:40 Asphalt -0.610 -0.858 Homeowners Park Marina 25.13026 -80.40399 6 9:51 Gravel Road -0.020 -0.268 Islamorada Flooding Predicted But Not Observed 24.96649 -80.56092 0 10:03 Asphalt 0.215 -0.033 Wetland Edge, Boat Storage Flooded 24.96279 -80.56392 0.1 10:10 Asphalt 0.249 0.001 Flooding Predicted, Not Observed 24.96493 -80.56828 0 10:21 Asphalt -0.525 -0.773 Flooding Predicted, Not Observed 24.96206 -80.57110 0 10:29 Asphalt -0.520 -0.768 Flooding Predicted, Not Observed 24.95505 -80.58409 0 10:36 Asphalt -0.260 -0.508 Flooding Predicted, Not Observed 24.95670 -80.58389 0 10:51 Asphalt -0.283 -0.531

Page 29 of 91 2016 High Tide Records

Verified tidal maximums for September to November 2016 in feet relative to NAVD88 are shown in Table 3 (highest measurement highlighted; these values are used for tidal extremes).

Table 3: Tidal maximums during 2016 King Tides.

September 17th/19th October 16th/17th November 15th/16th/17th Gauge Predicted Verified Predicted Verified Predicted Verified Location High Tide High Tide High Tide High Tide High Tide High Tide Virginia Key 0.923 1.050 0.966 2.110 .963 (16th) 1.811 Vaca Key -.061 0.016 0.016 0.768 .080 (17th) 1.030 Key West .454 (19th) 0.549 0.526 1.333 0.71 (15th) 1.500

Verified tidal maximums recorded by NOAA on the specific date of in-situ measurements relative to NAVD88 are shown in Table 4.

Table 4: Tidal maximums specifically on sampling days.

September 18th October 16th November 15th High Tide Time High Tide Time High Tide Time Gauge Location (feet) (EDT) (feet) (EDT) (feet) (EST) Virginia Key 0.860 11:06am 2.044 9:54am 1.768 9:24am Vaca Key 0.046 5:24pm 0.682 12:30pm 1.076 11:59pm Key West 2.222 12:24pm 1.33 10:36pm 1.500 10:12pm *Note: the Eastern Time Zone switched from Eastern Daylight Time (EDT) to Eastern Standard Time (EST) on November 6, 2016.

As shown in Figure 24 below, verified water levels at Virginia Key during the September King tide events align well with predicted levels; this is in stark contrast to 2015’s September King Tide event, shown in Figure 25, where verified levels were up to 0.6 feet higher than those predicted.

While a discussion of the full extent of factors influencing the differences shown above are beyond the scope of this report, NOAA provides basic atmospheric data alongside their tide and water predictions that may help explain a small portion of the variance. Barometric pressure reached lows of 1007 millibars on September 18th of 2015. During the peak King Tides of the same month in 2016, occurring roughly between the 17th and 19th, pressure reached lows of only 1014 millibars. A 1 millibar decrease in pressure is roughly equivalent to a 1 centimeter rise in sea level locally (Swedish Meteorological and Hydrological Institute, 2010). These measurements were taken at the Virginia Key tide gauge; however similar disparities were found to be present in the data at the other active gauges in the region over the same time period. While this is only one

Page 30 of 91 Figure 24: Verified water levels at Virginia Key during September 2015 King Tides.

Figure 25: Verified water levels at Virginia Key during September 2016 King Tides. contributor to local variations in sea level, it’s emblematic of various climatic conditions that can serve to increase or decrease the severity of tidal flooding.

It was also found that tide heights were far more significant in October than in September of 2016. This is at least in part likely due to increased surge from Hurricane Nicole. While this storm did not ever make landfall in the United States, the climatic effects were still felt as they coincided with October’s King Tide cycle. Shown below are wind data recorded four days prior to the King Tides measured in both September and October. While this alone is not robust enough to explain the differences in tide heights between the two months, it’s an additional factor that likely influenced the heights recorded in October. The vectors in the charts represent wind direction; based on the images, it would

Page 31 of 91 appear that winds partially attributable to Nicole were both stronger and more uniform in direction than those present the month prior in September. These conditions likely contributed to tide heights, creating a “piling” effect of water along the coastline, the process that is responsible for storm surge.

Figure 27: Winds at Virginia Key over a four-day period prior to September 2016 King Tides.

Figure 26: Winds at Virginia Key over a four-day period prior to October 2016 King Tides. Notice effects off offshore winds due to Hurricane Nicole.

Page 32 of 91 Data Limitations

There is some inherent uncertainty in both the LIDAR data and the MHHW surface. The vertical uncertainty in LIDAR collected elevation data is getting progressively smaller, however should still be considered (check metadata for margins of error). LIDAR data from early 2008 flights is used for Monroe County’s digital elevation model (DEM), and data collected in 2007 is used for Broward—both areas collected as part of a state-side multimillion-dollar collection project. Miami-Dade’s was updated more recently in 2015. Since then, some communities have implemented flood mitigation strategies such as sea walls or raised roads that have affected hydroconnectivity and flooding hotspots. This likely explains our identification of several predicted hotspots where no flooding was actually observed (due to the best available data being outdated). This occurred in several locations throughout Monroe County. An article published recently indicates that pilot projects were approved for work to begin raising select roads in anticipation of rising sea levels, and county commissioners ordered a comprehensive assessment of all 300 miles of county roads in the Florida Keys (CBS Miami, 2017). Additionally, LIDAR data used to generate elevation layers is only capable of capturing a snapshot of coastal morphology, and cannot account for natural processes such as barrier island migration, marsh transgression, or erosion. These factors have not been considered in the sea-level rise projections considered here. However, specifics of both implemented flood mitigation infrastructure and relevant natural processes will be investigated in the forthcoming components of this project by conducting community interviews and more in depth site surveys.

The MHHW surface is computed by interpolating high tide levels from tide gauge station to tide gauge station, which introduces uncertainty because additional variability may exist between stations that is not fully captured in the generated tidal surface. Changes in coastal geomorphology, as discussed above, can also impact coastal hydraulics, with in turn may affect the MHHW surface. Additionally, there is some uncertainty associated with interpolating this surface inland.

Analysis Components

MHHW Layer

Shown below are several maps depicting the tidal surface used in the analysis portion of this investigation. The first shows the elevation of this surface across our entire area of study; heights are in reference to NAVD88. As shown in the map, the height of this surface varies by roughly six inches along the Atlantic coast within our study area, increasing only slightly into Central Broward, and decreasing slightly in parts of Miami- Dade and into the Keys. It’s also worth noting that this surface is roughly a foot lower on the Florida Bay side of the Keys than on the Atlantic side. This is due to variations in hydrologic processes that occur in each of these ocean basins that effect tide heights. Figure 28 shows the locations of the pilot communities and the MHHW tidal surface for

Page 33 of 91 the region. The variability in the height of this surface, as referenced to NAVD88, is particularly large in the Florida Keys.

Figure 28: Variation in MHHW along the Southeast Florida coastline; projected inland using VDATUM. The following maps show the same tidal surface at a larger scale for each of the six pilot communities in this study. Again, while subtle, height variations in this surface do exist, and must be accounted for in the process of projecting both current hotspots and future inundation extents.

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Page 37 of 91 King Tide and Compound Flooding Maps

According to recently published research investigating the additive effects of storm surge and rainfall, compound flooding poses an increasingly significant risk to coastal communities worldwide (Wahl, 2015). Coastal tidal flooding is compounded in a variety of ways. Increased precipitation causes surface water to overtop, groundwater lifting limits the soil storage capacity, and other climatic factors such as wind and pressure, gulf stream velocity, and offshore storms can also serve as contributing factors to coastal flooding. Compound flooding occurs when these influences coincide; therefore, it is necessary to determine a methodology to isolate the contribution of King Tide levels from the other components of compound flooding.

While 2016 was the sampling year for this project, it is important to consider King Tide maximums in recent years. The tidal maximums since 2006 in Table 5 show an interesting variation. The notes column allows comparison with other relevant events which contributed to compound flooding. The range of water levels highlight the distinction between King Tide flooding and King Tides as a component of compound flooding. For October 2016, the King Tide was supplemented with amplified water levels from Tropical Storm Nicole. Tides were especially high in 2012 because of Hurricane Sandy. Relatively larger tides were also recorded in September of 2015, in part due to a super moon, which is a coincidence of either a new or full moon and the Moon’s closest position in its orbit of Earth.

Table 5: Maximum verified annual tidal heights at Virginia Key from 2006 to 2016.

Max Height (FT Year Day Notes NAVD88) 2006 6-Oct 1.41 2007 2-Oct 1.62 2008 26-Sept 1.93 2009 19-Sep 1.63 2010 7-Oct 1.75 2011 9-Nov 1.34 2012 28-Oct 2.12 Hurricane Sandy 2013 17-Oct 1.67 2014 7-Oct 1.51 2015 27-Sep 2.07 Super moon 2016 16-Oct 2.11 Hurricane Nicole

The frequency of compound flooding events in recent years shows that they are becoming more likely and need to be considered. It is important to map compound flooding water levels for current and future scenarios to consider extreme events. It was also important to do this in order to be able to model what was measured in 2016. Therefore, the results section which shows current, 1-foot, and 2-foot inundation uses a water level of 2.1ft NAVD88 as current. This is an average of recent Compound Flooding years (2012, 2015, and 2016).

Page 38 of 91 However, it is important to compare King Tide only versus King Tide and compound flooding. The maps shown below describe the potential flooding under two different scenarios: King Tide Only, and King Tide with additional compound flooding. Both of these estimated extents are for current sea levels. King Tide flooding is mapped at a water level of 1.6ft NAVD88, based on the average annual verified high tide reached at Virginia Key during the fall King Tide events from 2006 to 2014, excluding 2012, 2015, and 2016 (these are years where a major additional factor influenced those levels).

The compound flooding extents were developed the maximum tide heights over the same period, including those years where a secondary external event contributed to the height of the tides. It would be misleading to project flooding hotspots based solely on high tides from hurricane years, so the maps shown in the Results section make note of the difference. Furthermore, based on Table 5, it’s clear that additional factors have contributed to higher-than-normal tides on a number of occasions over the last ten years. In infrastructure protection planning, it’s important to consider the difference and accommodate the outliers.

Mangrove forests, as of 2015, are also displayed in the images below. These are important to highlight in flooding assessments because while they often show as flooding hotspots, they are naturally resilient to this type of event, and in many cases act as buffers with the ability to dampen waves, prevent erosion, and absorb flood waters. If the mangroves are not used to shade over the inundation layers, they stick out as hotspots when, in reality, they are protecting infrastructure (as long as they can accrete at a rate faster than the sea-level rise rate).

The diagram below serves as a guide to reading the maps presented over the next several pages. The top left shows hotspots identified in this analysis based on present King Tide heights and inundation extents. The top right shows the same flood extents during extreme tides with an added 1 foot of sea-level rise, the bottom left under 2 feet of sea-level rise, and the bottom right shows all three scenarios together. This make it easier to view scenarios simultaneously in order to visualize the increases in flooding extent under these projected sea-level rise estimates. It’s important to note that in the composite map in the bottom right, not only will the green areas be flooded in a 2-foot scenario, but the yellow and red will be as well—in this case, the green simply represents the increase in flood extent from a projected 1 to 2 feet of sea-level rise.

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Figure 29: Key to reading the maps on the following pages; red shows present flooding extent during extreme tides, yellow under an additional foot of sea-level rise and green under an additional two feet of sea-level rise. Page 40 of 91 Maps

Accompanying each of the SLR maps shown in this section is the associated King Tide and Compound Flood map. The King Tide and Compound Flood maps show the average extent of King Tide flooding since 2006 during years without additional influences, as well as the average for years where compound flooding occurred. Each set of maps will start with an overview map of the pilot community, and then zoom in to more specific locations within each.

Hollywood and Dania Beach

Maps on pages 42 to 48 show Hollywood and Dania Beach. Maps on the first page show the entire area of interest, and the pages following show large-scale maps of identified flooding hotspots within each of the communities. On pages 43 and 44 there are large areas shaded in red and cyan to indicate inundation; some of these areas however, marked in a floral pattern, are primarily mangroves or other classifications of wetlands. The distinction between flooded developed areas and flooded natural areas is an important one to make because of the vulnerability differential—developed areas are subject to significant losses when flooded, whereas wetlands can actually serve to reduce flooding, buffer wave action, and in many cases accrete to “keep up” with sea-level rise. Page 45 suggests rather devastating inundation for South Lake, even during present King Tides; however, this was not observed. While significant flooding did occur at the sampling site marked by the blue star, the vast majority of other streets in the community remained dry. This is likely is part due to an aggressive system of pumps that has been installed to counteract the seasonal flooding that would otherwise be extremely problematic in this region. This situation perfectly exemplifies the need to ground truth flood hotspot predictions. Not only is it important to be aware of this deviation for current planning purposes in this specific region, it’s also useful in assessing what strategies are effective and how those strategies may be implemented in other communities facing similar threats. Some maps in this series also contain infrastructure layers, including utilities, railroads, and bus routes. Evacuation routes are also identified. This part of the assessment will be discussed in greater detail in Part 2 of this project.

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Page 48 of 91 North Miami

Maps on pages 50 to 54 show North Miami. Maps on the first page show the entire area of interest, and the pages following show large-scale maps of identified flooding hotspots within the community. Once again, notice the large areas that are blocked out by the light green mangrove layer—these areas would otherwise show up as “hotspots” without the consideration of land cover type (mangrove cover symbology has been changed in this series to enhance the usability of these maps). There are also several locations where flooding was predicted to occur, but was not observed, shown in purple stars. An area of particular interest in North Miami is the trailer park shown on page 54. While just outside of the municipal bounds of North Miami, the flooding here was significant, and it was deemed to appropriate to include in this report because of its proximity. Areas like this should be given particular attention, because not only is the flooding significant, but the sensitivity of the residents and the homes on these parcels make inundation an even greater concern. Specifics of scenarios like this one will be assessed in greater detail in Part 2 of this project.

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Page 54 of 91 North Bay Village

The series of maps on pages 56 to 58 display observed and modeled results for North Bay Village. Maps on the first page show the entire area of interest, and the pages following show large-scale maps of identified flooding hotspots within each of the communities. The results presented in the maps in this section corroborate expectations. The primary recurrent flooding hotspot in North Bay Village is located along the southwest corner of Treasure Island (the more eastern of the two islands) northward along West Treasure Drive. This is likely due to the general downslope of the island from north to south. Flooding was observed at the north end of West Treasure Drive—nearby this location, water intruding through storm water infrastructure had managed to uplift a manhole cover. North Bay Village is serving as our primary pilot community in this project—the research and analyses presented in the first two reports of this project will culminate in the production of XXX

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Page 58 of 91 Key Largo

The series of maps on pages 60 to 64 display observed and modeled results for Key Largo. Maps on the first page show the entire area of interest, and the pages following show large-scale maps of identified flooding hotspots within each of the communities. It’s apparent from this analysis that the use of up-to-date land cover data is extremely valuable in assessing flooding hotspots, especially in areas with marsh ecosystems. Awareness of land cover ahead of time can save resource expenditure in resiliency planning and on-ground investigations because quite often natural areas, especially mangrove stands, are far more resilient than the built environment. Additionally, modeling where these areas are and the effects that may have on local flooding may be valuable as well; research suggests that the incorporation of soft infrastructure in coastal resilience planning can be extremely effective, especially when coupled with traditional infrastructure such as sea walls, bulkheads, and pumps (Phillips, 2006). Additional investigation into transportation infrastructure will be done in Part 2 of this project; several areas in the Keys will receive a closer look, as these some of communities have been proactive in raising roads over the last several years.

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