Journal of Coastal Research 31 5 1078–1083 Coconut Creek, Florida September 2015 Future Flood Frequency under Sea-Level Rise Scenarios David L. Kriebel†, Joseph D. Geiman†, and Gina R. Henderson‡* †Department of Naval Architecture and Ocean Engineering ‡Department of Oceanography United States Naval Academy United States Naval Academy Annapolis, MD 21401, U.S.A. Annapolis, MD 21401, U.S.A. ABSTRACT Kriebel, D.L.; Geiman, J.D., and Henderson, G.R., 2015. Future flood frequency under sea-level rise scenarios. Journal of Coastal Research, 31(5), 1078–1083. Coconut Creek (Florida), ISSN 0749-0208. The effect of sea-level rise (SLR) on exceedance probabilities for annual flooding at coastal locations is explored in this paper. We assess four future SLR scenarios given by the U.S. Army Corps of Engineers and how these SLR scenarios affect monthly flooding statistics. Focusing on one case site, Annapolis, Maryland, we fit the probability density function of the monthly maximum tide gauge record with a Pareto-tail distribution. Random sampling from this distribution is then performed on top of the various future SLR scenarios. Exceedance probabilities for a storm tide to exceed the coastal flood stage, the elevation of which has already been established in a previous paper, are then calculated from the interpolated Pareto cumulative distribution. We illustrate that even mild increases in mean sea level acceleration lead to drastically higher exceedance probabilities of coastal flooding. ADDITIONAL INDEX WORDS: Sea-level rise acceleration, storm surge, statistics. INTRODUCTION the maxima of the gauge time series, they showed that MSL While the increase in mean sea level (MSL) has been well rise is the major reason for the rise in extreme high water at documented (Church et al., 2004; IPCC, 2007; Rahmstorf, 2007; most stations. USACE, 2011; Woodworth, 2006), determining the value of In this paper, we wish to expand upon earlier work (Kriebel mean sea-level rise (SLR) acceleration has been much debated and Geiman, 2013), where a ‘‘coastal flood stage’’ was proposed (Houston and Dean, 2011; Rahmstorf and Vermeer, 2011). A for all historical tide gauge sites. A major flood stage, defined by mean sea-level elevation that is accelerating has enormous the National Weather Service (NOAA, 2013) as flooding that implications for the onset and severity of future flooding causes serious widespread damage to roads and buildings, is events. Indeed, tidal fluctuations, storm surge, and other defined with respect to a fixed tidal datum, such as NAVD88. In sources (usually climatological) of local fluctuating sea levels, the previous paper (Kriebel and Geiman, 2013), this elevation when superimposed on this background relative MSL rise, was shown to be correlated at over 29 U.S. East Coast sites with would cause increasingly severe coastal flooding (Nicholls and the statistical stage of l þ 3r, where l is the mean value of the Cazenave, 2010), even if there is no increase in major storm detrended (with respect to the MSL) monthly extreme water severity or frequency (Zhang, Douglas, and Leatherman, 2000). tide, and r is the standard deviation of the monthly extreme Therefore, assessing the relative impact of MSL acceleration on high tide. In some sense, the major flood stage is an elevation flooding frequency is of prime importance. that separates outlier flood events from the ‘‘common’’ monthly high water levels and appears to work for a wide range of The combined effect of sea-level rise and storm tides has been locations on the U.S. East Coast. considered recently in several studies. Since historical data of We wish to use the major flood stage in Annapolis, Maryland, extremes are correlated with the rise in mean sea level, and to assess frequency of past flooding of this threshold, as well as assuming this trend holds into the future, Obeysekera and project future flooding probabilities using SLR scenarios Park (2013) calculated future return periods of extreme sea (IPCC, 2007; USACE, 2011), along with the probabilities of levels from MSL acceleration scenarios and storm tide the monthly maximum high tide. Several authors, including statistics. This included a temporal variation of the return Menendez and Woodworth (2010), Bernardara, Andreewsky, period with time. They then applied this method to a few U.S. and Benoit (2011), and Obeysekera and Park (2013), have coastal locations. In Menendez and Woodworth (2010), they modeled the extreme water levels with the generalized extreme calculated statistics of a global network of historical tide value distribution (GEV). Here, we compare the fitted GEV gauges, including statistics of the peak storms or maxima of the distribution with a two-population distribution in which the gauge time series. They concluded that there has been an bulk of the distribution is defined empirically, but the extreme increase in extreme high water levels worldwide since 1970. tail is fit with a Pareto tail. After assessing the goodness of fit of Furthermore, by removing the annual median sea level from the data to these two different distributions, we then simulate storm tides taken from a random sample of the chosen DOI: 10.2112/JCOASTRES-D-13-00190.1 received 15 October 2013; distribution on top of mean sea-level rise scenarios proposed accepted in revision 2 August 2014; corrected proofs received 1 December 2014; published pre-print online 22 January 2015. by the U.S. Army Corps of Engineers (USACE, 2011, 2014). We *Corresponding author: [email protected] then project monthly exceedance probabilities for major ÓCoastal Education and Research Foundation, Inc. 2015 flooding in Annapolis, Maryland, into the future. Assessment of Future Sea-Level Scenarios 1079 METHODS Sea-Level Rise Scenarios Four future sea-level rise scenarios are considered here. The first, which will be denoted NRC-0, is a continuation of the existing linear trend without SLR acceleration. The second, third, and fourth are scenarios for accelerated SLR included in USACE (2009) based on recommendations from National Research Council (NRC), here termed NRC-I, NRC-II, and NRC-III. In these NRC cases, the historic linear rate of relative SLR in Annapolis was augmented with an acceleration term following methods outlined in USACE (2009) as a scenario- based assessment of future SLR. This method can be stated explicitly. First, the linear trend in relative mean SLR ml(t) is calculated ml À mp ¼ sðt À tpÞð1Þ Figure 1. Plot of the past monthly mean sea level (MSL) and future MSL scenarios proposed by the U.S. Army Corps of Engineers. Scenario 0 is a where mp and tp are the values of the mean sea-level trend and continuation of the existing linear MSL trend with a slope of s ¼ 3.5 6 0.3 time at the end of the last tidal epoch, 1992. Here, s is the slope mm/y. Scenarios I–III are quadratic in time and given by Equation (4). Also of the linear trend, which includes both eustatic SLR as well as shown is the extreme high water elevation (EHW) for each month (black line). A mean EHW of 0.54 6 0.16 m is indicated by the spread of the local ground subsidence. The global eustatic sea-level trend, distribution. (Color for this figure is available in the online version of this me, is given by paper.) me À mp ¼ seðt À tpÞð2Þ correlates well to flooding of roadways and some buildings in and following USACE (2011), a value of se ¼ 1.7 6 0.5 mm/y is adopted for the eustatic slope in SLR. This is then compared to Annapolis. It is noted from the historical record (see Figure 1) ml, and the SLR trend due to local land subsidence is computed that nine storms exceeded this coastal flood stage and resulted via in flooding of local infrastructure. Two events led to major flood damage—one hurricane in 1933, and Hurricane Isabel in 2003. ms ¼ ml À me ¼ðs À seÞðt À tpÞð3Þ Other events were ‘‘nuisance’’ flooding events controlled by This added land subsidence is then added into any of the four sand bags. scenarios (0, I, II, III). These scenarios can be written succinctly The monthly relative MSL trend up to the current tidal epoch as is s ¼ 3.5 6 0.3 mm/y, with the error giving the 95% confidence interval. The trend in monthly maxima, denoted by EHW in 2 mJ À ms ¼ seðt À tpÞþaJðt À tpÞ J ¼ 0; I; II; III ð4Þ Figure 1, is roughly 3.6 6 0.4 mm/y. While this value is slightly higher than the value for MSL rise, it is certainly within the where a ¼(a , a , a , a )¼(0, 2.71, 7.0, 11.3)310À5 mm/y2 are J 0 I II III error limits of the mean SLR and is supported by the findings of the acceleration values of SLR considered by USACE (2011). Menendez and Woodworth (2010), and so we assume that the NRC-III obviously represents the most extreme SLR acceler- linear trend in monthly maxima is attributable to mean SLR. A ation scenario, while NRC-0 once again represents a continu- climatological study (Zhang, Douglas, and Leatherman, 2000) ation of the historic linear SLR scenario. We note that m is r speculates that there has been no increase in the frequency of added to the acceleration scenario, since an increase in land extreme events on the U.S. East Coast in the twentieth subsidence increases the relative MSL. century, even though mean SLR may be contributing to an Annapolis Monthly Tidal Data increase in the flooding severity from extreme events. Con- In this section, we focus on the monthly sea-level time series versely, a study in the U.S.