1. Introduction
Storm flooding is a destructive event that damages infrastructure, especially in coastal areas with low elevations. The state of Connecticut suffered around
$360 million in damages after Hurricane Sandy alone [
1]. Damages caused by increased water levels from historic storm surges and waves in low-lying areas can be used in order to estimate the potential for future damage from similar events. In addition, because rising sea-levels increase the frequency of storm-induced high water levels, an understanding of the effect of sea-level rise on risk trends is necessary for evaluating future storm and hurricane inundation risk [
2,
3,
4,
5]. O’Donnell [
6] emphasized that storm-related flood risks would increase as the sea-level rose. Therefore, storm-induced flooding risk assessments should include the effect of sea-level rise, and we use an upper bound of 50 cm sea-level rise by 2050 for Connecticut [
6].
The Federal Emergency Management Agency (FEMA) and the North Atlantic Coast Comprehensive Study (NACCS) [
7] evaluated the 1% annual chance of flood events in Long Island Sound (LIS). FEMA’s approach for estimating floodplain maps included a regional statistical approach applied to the New London, New Haven, and Bridgeport tide gauge stations to compute probability distributions of the data at the gauges. FEMA computed deep-water wave characteristics using empirical wind-wave growth equations that were applied to Tweed New Haven Regional Airport historical data and then calculated along an inland transect to compute the overland wave propagation using the model WHAFIS [
8]. One of the drawbacks of this approach is that storm surges are interpolated over only three stations, and calculated incident wave heights do not consider refraction, diffraction, or bottom dissipation effects.
The NACCS study used observations from extratropical storms using the method described by [
9], which was then applied to synthetic tropical storms using the LIS model and analyzed using an optimum sampling of the joint probability method [
10,
11,
12]. The deep-water wave boundary was obtained in 0.083-degree resolution and 0.25-degree wind resolution by solving the action-balance equation in the WAM model [
13], which produced nearshore steady-state wave model results using STWAVE [
14] and simulated surge and circulation results using ADCIRC [
15]. Even though the NACCS study was more sophisticated than the FEMA study, the storm surge model was of coarse resolution to simulate total water levels in the coastal floodplains of the Connecticut coasts [
16,
17]. Like FEMA, NACCS did not include the effect of sea-level rise on return intervals, which is essential for future risk planning at local scales [
18].
Understanding the probability of a flood event influences coastal policy and management. A down-scaled comprehensive understanding of total wave elevations can aid in assessing the risks, consequences of design costs, and environmental impacts of coastal plans [
19]. Furthermore, the return period analysis in LIS should be updated at a higher resolution. This study aims to provide storm surge and wave height probabilities to aid the engineers and planners in developing cost-effective design criteria for resiliency projects.
We calibrated and applied a coupled coastal circulation and wave model system to estimate the frequency of occurrences of extreme storms using hindcasts of historical storms with different return periods for each town along the LIS coast in Connecticut. Our work demonstrates a method and technique for enclosed sounds where circulation and wave modeling are challenging due to sparse data availability and unique geomorphologies. We also examined extreme events under both present and future sea-level conditions in order to understand the effect of sea-level rise on the generated wave characteristics.
Section 2 presents the study area, historical storm data, and data collected in Connecticut to build the circulation and wave model.
Section 3 describes the wave and circulation models and methodology to obtain statistically independent storm events, the peak-over-threshold method, and error analysis.
Section 4 presents our results by town and compares these with previous studies. Finally,
Section 5 discusses the results and presents our conclusions.
5. Conclusions
This paper is intended as a guide for decision-makers to identify risk probabilities for the coastal protection project design for the current environment, as well as considering local sea-level rise projections for 2050. This study provides modeled water levels and significant wave heights in LIS to improve probability estimates of the extreme surge and wave heights for Connecticut shorelines and municipalities, filling the gaps between very sparse coastal observations. We analyzed 68 years of data with POT to model the 44 highest-ranked storms. We then estimated 10-, 30-, 50-, and 100-year return period water levels and significant wave heights for all Connecticut coastal towns. It is worth noting that the Poisson-GPD distribution best fits the empirical distribution.
The model results show that the water levels for a given return period are higher along the western end of the Connecticut coast than the eastern end. Conversely, significant wave heights increase eastward. The results lie within the confidence interval of the previous NACCS study and show good agreement with tide gauge and buoy observations. The 1% annual exceedance probabilities of water levels in Bridgeport, New Haven, and New London is 2.78 m, 2.55 m, and 2.03 m, respectively, and the corresponding significant wave heights are 4.48 m, 3.98 m, and 4.91 m. The probability of the occurrence of extreme events increases when a 0.5 m local sea-level rise projection for 2050 is included in our calculations. When a 0.5 m sea-level rise is included, a 10% annual probability event (10-year return period) increases to a 50% annual probability (2-year return period) and a 1% annual probability event (100-year return period) increase to a 5% annual probability (20-year return period). Although this study presents annual probabilities for storm surges and significant wave heights of the next few decades, the potential for climate change to impact these probabilities must be considered in planning coastal projects. Since the degree of sea-level rise will significantly affect these results, we feel it is imperative to repeat coastal flood risk assessments as better predictions of sea level rise become available.