New York City Panel on Climate Change 2015 Report Chapter 4: Dynamic Coastal Flood Modeling

4.1 Background 4.2 Methods 4.3 Results and discussion 4.4 Conclusions and recommendations Storm surge is an increase in water level caused by winds and low atmospheric pressure and combines with tides to form the total water elevation during a storm, also known as the storm tide or stillwater elevation. Storm tides are among the world's most costly and deadly hazards, bringing floodwaters and waves capable of damaging and disabling infrastructure, homes, and property, as well as threatening human life and health. Sea level rise in the New York metropolitan region has already been increasing the number of coastal flood events (see e.g., Colle et al., 2010; Sweet et al., 2013; Talke et al., 2014). Coastal flood heights are projected to increase and coastal flood zones to expand as sea levels continue to rise due to climate change, as documented in Chapters 2 and 3. Until now, the New York City Panel on Climate Change (NPCC) has utilized a static mapping approach to assess future costal flood hazards (see NPCC, 2010; 2013; 2015). One assumption of static mapping is that the flood elevation is spatially uniform over inland flood areas, although peak water elevation for a major hurricane can have strong spatial variations (Fig. 4.1), potentially violating this assumption. In this chapter, the second NPCC (NPCC2) advances these methods by testing the use of a dynamic model that explicitly accounts for more of the forces acting on the water and the resulting water movement. The NPCC2 has undertaken dynamic modeling of future coastal flooding based on the Federal Emergency Management Agency's (FEMA) flood-mapping framework, which includes the effects of tides, storm surge, and wave setup (see Chapter 3, Box 3.1, NPCC, 2015) on water elevations and maps overland flood areas. This chapter presents the methods for the dynamic modeling of coastal flooding and compares results from the static approach (discussed in more detail in Chapter 3, NPCC, 2015) and dynamic modeling approaches. The NPCC2's exploration of dynamic modeling was, in part, motivated by a desire to test whether there were considerable differences between dynamic modeling and static mapping outcomes. In addition, FEMA uses dynamic models for its flood-mapping studies (e.g., FEMA, 2014a), and the National Oceanic and Atmospheric Administration (NOAA) similarly uses dynamic models for forecasting neighborhood flooding during hurricanes. Further, prior studies of New York Harbor have shown that dynamic models can reproduce past storm-tide events with a typical accuracy of 0.5 ft (e.g., Colle et al., 2008; Orton et al., 2012; Georgas et al., 2014). In addition, under the Biggert-Waters Flood Insurance Reform Act of 2012, FEMA is required to convene a Technical Mapping Advisory Council to develop recommendations on “how to ensure that the Federal Emergency Management Agency uses the best available methodology to consider the impact of the rise in sea level.”1 New York City relies on FEMA's Flood Insurance Rate Maps (FIRMs) as the basis to understand current flood risk and to inform floodplain management regulations. Therefore New York City and the NPCC2 have an interest in developing methods for assessing future flood hazards that are consistent with FEMA's approach for mapping present-day flood zones. Here, we set out to inform this discussion by utilizing both static and dynamic methods of calculating the effects of sea level rise on FEMA stillwater elevation estimates and then comparing results. The broader goal of this work is to contribute to the methods by which New York City and other coastal cities can evaluate and address the future impacts of sea level rise on coastal flooding. As discussed in Chapter 2 (NPCC, 2015), both tropical cyclones (e.g., hurricanes) and extratropical cyclones (e.g., nor'easters) strike the New York metropolitan region and are important to defining flood zones and elevations for the “100-year” and “500-year” floods, known respectively as the 1% and 0.2% annual chance floods (FEMA, 2014a, Chapter 2). Currently almost 400,000 New Yorkers live within the new 100-year FEMA flood zone, as defined by FEMA's Preliminary FIRMs (City of New York, 2013a; FEMA, 2014a), and Hurricane Sandy flooded many of these neighborhoods (see Chapter 2, FEMA, 2014a). Hurricanes strike New York City infrequently but have produced the highest two flood events on record at the Battery at the southern tip of Manhattan—Hurricane Donna in 1960 (7.2 feet, NAVD88) and Hurricane Sandy in 2012 (11.3 feet, NAVD88). Extratropical cyclones such as nor'easters typically have small-to-moderate surges but occur more frequently. Their effects can be large because they can last for several days, leading to more extended periods with high storm surge. This makes it more likely for the storm surge to coincide with high tide, as occurred with the December 11–12, 1992 nor'easter (Colle et al., 2010). In Chapter 3 (NPCC, 2015), NPCC, 2010, and NPCC, 2013, static approaches were used to estimate the future impacts of sea level rise, adding sea level rise projections to FEMA's 100- and 500-year flood elevations, and to map flood zones with projected sea level rise (Horton et al., 2010; NPCC, 2010; 2013). The static approach was applied to FEMA flood elevations for 100- and 500-year floods, with the additional criterion that low-elevation land areas must have direct connectivity to the open water in order to flood. Whereas the first NPCC maps relied on older FEMA flood elevations from the 2007 FIRMs, the NPCC2 updates use newer, higher flood elevations from the recently released FEMA Preliminary FIRMs and coastal flood study (FEMA, 2014a). Dynamic flood modeling is a physics-based computer simulation technique that includes the effects of factors such as wind, atmospheric pressure, and friction in the calculation of flood elevations (this technique is also known as hydrodynamic modeling). A limited number of studies have compared static mapping and dynamic modeling to quantify the impact of sea level rise on coastal flooding. One study of low-lying populated regions around Miami found that dynamic modeling gave higher flood heights than static flood-mapping methods (Zhang et al., 2013). A study of the New York metropolitan region that did not include overland flooding found that simple superposition of sea level rise on top of storm tide (used in the static mapping technique) was an excellent approximation to dynamic modeling results (Lin et al., 2012). This NPCC2 study uses a hazard assessment framework, dynamically simulates water elevation (including the effects of tides, storm surge, and wave setup) and identifies overland flood areas. The overall strategy of the NPCC2 dynamic modeling is to incorporate sea level rise projections into the dynamic coastal flood-modeling procedure used in the recent FEMA Region II Coastal Storm Surge Study (FEMA, 2014a). The aim is to produce compatible future flood exceedance curves and flood zones (see Appendix IID for details). The NPCC2 baseline simulations used the same dynamic model, grid parameters (e.g., bottom friction, bathymetry/land elevation), storm sets, and forcing data input files (wind, atmospheric pressure, and tide). Statistical methods were also similar between the NPCC2 dynamic modeling and the FEMA study, although there are small discrepancies in results that suggest minor differences in computation. The study region for the NPCC2's dynamic coastal flood modeling is shown in Figure 4.1, with three areas that were highlighted for special focus: The Battery, Manhattan; the Midland Beach, Staten Island neighborhood; and the Howard Beach, Queens neighborhood. The flood maps and hazard assessment presented in this chapter include the surrounding parts of New Jersey around the New York Harbor. These interconnected areas are a crucial part of the New York metropolitan region's transportation, energy, and food distribution systems. The first step was to conduct a baseline reproduction of the FEMA (2014a) model simulations that do not include the effects of sea level rise. The ADCIRC (ADvanced CIRCulation)/SWAN (Simulating WAves Nearshore) (Booij et al., 1996; Luettich et al., 1992) computer model was used to conduct the storm-surge simulations. The NPCC2 baseline results were then compared to FEMA (2014a) results to test for consistency. The storm set developed by FEMA for use in the Region 2 Coastal Storm Surge Study includes the 30 strongest extratropical cyclones from the period 1950–2009, based on ranking storm surge heights from tide gauges in the region. Tropical cyclones are harder to characterize because they are rare, so FEMA defined a set of 159 synthetic tropical cyclones that span a wider range of possible storms (see e.g., Fig. 4.2). In the second step, the same modeling procedure was followed, incorporating NPCC2 sea level rise projections. Chapter 2 (NPCC, 2015) presents the NPCC2 sea level rise projections for the 10th, 25th, 75th and 90th percentiles for the 2020s, 2050s, 2080s and 2100. The NPCC2 dynamic coastal flood modeling used the 90th percentile sea level projections in order to focus on high-end risks. Time periods simulated were the 2020s, 2050s and 2080s (11, 31, and 58 inches of sea level rise, respectively2). Only a subset of the storms were simulated with sea level rise, focused on 100-year to 500-year events, but the final results take into account the full range of storms (see Appendix IID). Temporal maximum water elevation data (e.g., Fig. 4.2) at each location over the entire domain for each storm were utilized for statistical analysis. For each of the 188,390 grid points in the study area that covers the spatial extent shown in Figure 4.2, probability distributions of water elevation were built separately for tropical cyclones (TCs) and extratropical cyclones (ETCs). A detailed description of the statistical methods utilized for converting these distributions to flood exceedance curves (return period versus water elevation; Fig. 4.3) is given in Appendix IID. As a consistency check, statistical codes and ADCIRC modeling outputs closely reproduced FEMA flood exceedance curves, generally within 2 inches (e.g., Fig. 4.3). For dynamic flood maps of the baseline and future decades, the 100-year and 500-year stillwater elevation values were taken from the flood exceedance curves for each grid location. The resulting water elevation data were imported into ArcMAP and interpolated (inverse-distance weighting, IDW) to form a raster surface over the entire region (New York City and the New Jersey Harbor regions). The ADCIRC land surface elevation (essentially a coarse, 70-m-resolution digital elevation model) was also interpolated using IDW to the same cell size as the water elevation rasters. The land surface raster was subtracted from each water elevation raster to compute a map (raster) of flood depth, and the zero contour is the boundary of that event's floodplain. Static mapping methods were generally equivalent to those summarized in Chapter 3, but were performed using a 70-m-resolution digital elevation model (DEM) to enable equivalent comparison to the dynamic mapping results (see Appendix IID, NPCC, 2015 for details). This section presents the dynamic coastal flood modeling results and examines differences between the dynamic and static flood-mapping results. The sensitivity of the flood elevations to potential climate change–driven increases in the frequency of tropical cyclones is then analyzed. Finally, the section outlines and discusses some limitations of this study as well as how further research can address them. Contours for the 100-year (1% annual chance) flood zone, baseline versus the 2080s, are shown in Figure 4.4. The regions where sea level rise will cause the greatest change in the 100-year flood zone are in the broad flat land area (a floodplain in geographic terms) of southern Queens and eastern Brooklyn around Jamaica Bay. There are other increases in the flooding area across the entire region, including the southern Bronx (the Bronx and Hutchinson River floodplains), and northern Brooklyn (Newtown and Gowanus Creek floodplains). A comparison of the dynamic and static assessments of flood zone boundary contours in the 2050s is shown in Figures 4.5 and 4.6. The results are similar, especially when considering the entire region. Many New York City floodplain regions in Figure 4.6 show dynamic mapping results that are similar to static mapping results—in many cases the two are only inches higher or lower. Variations in these results arise due to factors such as wind direction (which can blow up higher sea levels in downwind areas) and friction (which initially reduces flood height for a shallow flow, then eventually has little effect as the flow becomes deeper). (For full details, see Appendix IID, NPCC, 2015.) Results of stillwater elevations for the three specific study locations are compared in Figure 4.3 and Table 4.1. At the Battery, the site of the New York City financial district and a historical tide gauge station off lower Manhattan, the results show dynamic stillwater elevations that are just below those calculated with the static method. At Howard Beach, a neighborhood in southern Queens with a slightly sloping floodplain on the north shore of Jamaica Bay, the dynamic results are equal to or a few inches higher than the static results. At Midland Beach, a neighborhood on the eastern shore of Staten Island that is only a few feet above normal high tides, the dynamic results for the 2050s are substantially higher (>0.5 ft) than the static results, but for the 2080s they are substantially lower (>1.0 ft; Table 4.1). Reasons for these results are discussed below. A spatial view of the difference between dynamic and static 100-year flood calculations is presented in Figure 4.6. Like the Battery, most other deep-water, estuarine, or open coastal locations show dynamic flood elevations equal to or a few inches lower than the static results. One exception is the Meadowlands in New Jersey, where dynamic modeling results are close to 1 foot lower than those of the static mapping approach. These differences are likely related to several as flood levels rise with sea level rise, the floodplain across which the flood is some of water is and inland of just as in a prior study of the area et al., the be related to between the tide and the storm surge or to to the of the tides (e.g., et al., the differences also be related to the effects of (e.g., and These and other to be There are also a small number of locations where the static methods future flood heights by more than 0.5 For Midland dynamic results for the 2050s are than the static results by more than 0.5 feet, for the and 2080s they are equal or in lower than the static results (the 2080s 500-year water 4.1). These dynamic modeling results for Midland are also found in FEMA's results for 100-year flood elevations, where the area of Midland has feet lower stillwater elevations than the surrounding more The results at Midland from two the of only extratropical in the FEMA and the of the low-lying neighborhood an land which makes the statistical of flood zones In the FEMA study, areas that are not flooded for a given storm are to as (FEMA, and the dynamic are for storms with water elevations from flooded areas a static flood-mapping The of these two factors to results in the assessment of the impact of sea level rise for Midland are in the broader New York metropolitan region. where the dynamic and static results by more than 0.5 feet are more in the of flooding from tropical cyclones only (Fig. The difference between these results for the flood assessment (Fig. because the extratropical 100-year flood height is higher than the tropical 100-year flood height in the FEMA study, and the extratropical cyclones more the The differences versus for tropical cyclones are likely by the strong winds during tropical cyclones that can up large sea level in shallow areas of flooding. and water which to inland of a storm surge (e.g., a hurricane and have effect on a storm surge (e.g., a also a These results that the static flood-mapping approach is not the on the of a high risk and leading to a more of the effect of sea level rise on flood studies use both dynamic and static methods in the of use of static mapping methods for to of dynamic modeling of flood hazards is the of the model for the of the climate A New York, dynamic modeling was used to test the effects of coastal such as storm-surge and (City of New York, The dynamic modeling on the of these flood and on how they be to address such as that do not over high at the of a but around the low-lying area the as with Storm are to the or of storms for a given Like sea level storm can periods for a given flood level (Lin et al., 2012). this already be due to both in and and atmospheric et al., 2013; see Chapter 2). et found a of tropical cyclones in with based on of historical tide gauge data in the and A sensitivity test was based on this where the annual of tropical cyclones were in the statistical analysis. For the same test change was for extratropical as there is on how climate change will storm surges in the New York metropolitan region 2, NPCC, 2013). The results were that the 100-year and 500-year flood for the Battery by and feet, under annual of tropical These are small increases compared to the increases by sea level rise because extratropical cyclones the impact of storm surge in the FEMA and NPCC2 For a discussion of this see the last three of the The use of NPCC2 high-end projections of sea level rise is for but the of a similar assessment using estimates of sea level rise is a of this The sea level rise projections are for the specific future that the projections are in the of projected sea level rise, there is also the it will take to at a given Sea level rise is to occur and to be due to already to the but the and are to (see Chapter 2 of et al., 2013). the of this chapter on the differences between dynamic and static coastal flooding calculation methods are of the in the at which the sea level rise This NPCC2 study relied on the FEMA hazard assessment which is an detailed study of the region's storms and the FEMA approach has One is that Hurricane Sandy is not in the storm set because the storm assessment was Sandy the New York metropolitan region. This the of how storm and storm surge have results. studies will to data for Hurricane Sandy as well as more recent storms to a more storm in are A further is that tropical cyclones in the New York metropolitan region take on extratropical (Colle et al., as was the with Sandy et al., 2013). The FEMA study utilized of tropical cyclones (e.g., Fig. that the more of extratropical study of between tropical and extratropical and methods for synthetic tropical wind and pressure will be for the accuracy of future hazard assessment The FEMA study found that the hazard assessment results for New York Harbor at the Battery for the flood elevations of 100- and 500-year storm tides are by the extratropical a recent study has storm tide data from the and has shown that the three highest storm tides from to the were tropical cyclones (the major storm of and Hurricane Donna in or storms et al., 2014). the storm surge within the period used by FEMA was an extratropical on at storm surge at the of low tide, and the storm tide was only the highest from to et al., 2014). the of extratropical tropical and storms for defining the region's flood hazards is an important for further in flood hazard assessment for the New York metropolitan region (e.g., defining the 100-year flood are and more research be on historical events and on hazard assessment methods to these The recent FEMA hazard assessment found substantially higher estimates of 100-year and 500-year storm tides for New York City for the River and Island than those of other studies or data For the FEMA (2014a) estimate of the 100-year flood elevation at the Battery tide gauge is feet a statistical by of storm tides from to results in a 100-year flood elevation of feet a difference of this into Hurricane Sandy produced an storm tide at the to the new FEMA study, FEMA's estimate for the 100-year flood elevation was to be feet based on Flood results in the (Horton et al., 2010). A recent study of tropical storm tides that the 100-year tropical storm tide is feet (Lin et al., compared with the FEMA 100-year tropical storm tide of feet (FEMA, 2014a). for 500-year storm tides are similarly further research is to understand and these large discrepancies and The static and dynamic flood-mapping methods for the effects of sea level rise on coastal flood elevations in the New York metropolitan region similar results for most within the flood zone produced from these two methods are In a small number of areas, the methods by more than 0.5 These are more in to flooding from tropical cyclones than from extratropical cyclones in flood hazard assessment for the New York metropolitan region (e.g., defining the 100-year flood and in the of future sea level rise are than differences between the dynamic and static flood-mapping studies assessing the present-day 100-year flood elevation for the Battery have substantially (a range of the range percentile the in NPCC2 sea level rise for the 2080s is research be on historical storm events and on hazard assessment methods to the in defining New York City flood The 100-year and 500-year flood heights from FEMA's (2014a) present-day hazard assessment are by the extratropical but new storm tide data from the that the three highest storm tides from to the from tropical dynamic modeling study a broader set of sea level dynamic modeling of storm surges for hazard assessment is and this the potential for many statistical or a of will be is to understand the and storm that cause some locations to have higher dynamic modeling flood heights than static flood-mapping Dynamic modeling some locations in the New York metropolitan region where results from static flood-mapping it is that dynamic modeling continue to be used static flooding assessments as of dynamic modeling of flood hazards is the to conduct such as testing locations for storm surge For more risk and studies in the of sea level rise and for important and coastal it be to consider the storm tide elevations for periods (e.g., to with a of This research was by FEMA Region II and the City of New York of Emergency Management and of and FEMA's Technical as well as by a National Oceanic and Atmospheric Administration (NOAA) and for Climate in the and by a Coastal Climate This research was also in part by a of computer from the City of New York under and to and at