Assessing storm surge hazard and impact of sea level rise in Lesser Antilles-Case study of Martinique
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Abstract. In the Lesser Antilles, coastal inundations from hurricane-induced storm surges cause great threats to lives, properties, and ecosystems. Assessing current and future storm surge hazard with sufficient spatial resolution is of primary interest to help coastal planners and decision makers develop mitigation and adaptation measures. Here, we use wave-current numerical models and statistical methods to investigate worst case scenarios and 100-year surge levels for the case study of Martinique, under present climate or considering a potential sea-level rise. Results confirm that the wave setup plays a major role in Lesser Antilles, where the narrow island shelf impedes the piling-up of large amounts of wind-driven water on the shoreline during extreme events. The radiation stress gradients thus contribute significantly to the total surge, up to 100 % in some cases. The non-linear interactions of sea level rise with bathymetry and topography are generally found to be relatively small in Martinique, but can reach several tens of centimeters in low-lying areas where the inundation extent is strongly enhanced compared to present conditions. These findings further emphasize the importance of waves for developing operational storm surge warning systems in the Lesser Antilles, and encourage caution when using static methods to assess the impact of sea level rise on storm surge hazard.Keywords:
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Surge hazards induced by tropical cyclones have caused substantial economic losses and casualties for coastal communities worldwide. Under projected sea level rise (SLR), it is not well understood how the probabilistic surge hazard may change. Coastal planning and engineering usually adopt the “bathtub” method to evaluate the surge‐SLR response, where surge with SLR is considered to be the exact summation of the two. This method has been shown by previous studies to be unreliable. Studies on surge‐SLR response either use a low‐fidelity model setup or rely on individual storm's surge to represent the probabilistic surge due to the high computational burden. Herein, we use high‐fidelity numerical models in the Tampa region, West Florida, consider 188 synthetic storms and four SLR scenarios, and investigate the surge‐SLR response and its physical drivers. Compared to the direct summation of present‐day surge and SLR amount, results show that the probabilistic surge with SLR can be 1.0 m larger, while different individual storm's surge with the same magnitude can be 1.5 m larger or 0.1 m smaller, indicating the importance of not relying on a limited number of surge events to assess the probabilistic surge response to SLR. Investigation of the physical drivers shows that distinct topographic features of the study area and storm forward speed notably affect the surge‐SLR response. When considering 1.3 m or larger SLR in the study area, complex topography, and large surge events, the effects of SLR on the probabilistic surge are hard to predict and should be investigated more carefully.
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Thuy, N.B.; Kim, S.; Chien, D.D.; Dang, V.H.; Cuong, H.D.; Wettre, C., and Hole, L.R., 2017. Assessment of storm surge along the coast of central Vietnam. In the present paper, the interaction of surge, wave, and tide along the coast of central Vietnam is assessed using a coupled model of surge, wave, and tide. A series of storm surge simulations for Typhoons Xangsane (2006), Ketsana (2009), and Nary (2013) are carried out, considering the effects of tides and waves that combines wave-dependent drag and wave-induced radiation stress to find a predominant factor in storm surge generation. The results indicate that the surge–wave interaction is crucial to the storm surge simulation in this area. In particular, the wave-dependent drag improves an accuracy of the storm surge level up to 30%. In addition, the radiation stress contributes up to 15%. However, the tide–surge interaction is negligible because there is less than 2% difference in results with and without the tide. A series of coupled surge and wave simulations for 49 historical typhoons in the period of 1951 to 2014 show that mean peak surge levels along the coast are 2.5 m. The highest peak surge level reached 4.1 m at Cuaviet in the Quangtri Province during Typhoon Harriet (1971).
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Kim, Y.H., 2020. Assessment of coastal inundation due to storm surge under future sea-level rise condition. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 845–849. Coconut Creek (Florida), ISSN 0749-0208.Coastal communities, transportation systems, and energy infrastructures will be at increasing risk of impact from the extreme events like storm surge. Coastal areas are at risk for worse inundation in the near future due to coupled effects of sea-level rise and surge under the future global climate change scenarios. In order to assess the impact of coastal inundation due to the combined effect of sea-level rise and tropical storms, Sea, Lake and Overland Surge from Hurricanes (SLOSH) model was implemented to coastal areas of Korea. SLOSH calculates water level from depth-integrated, quasi-linear, shallow-water equations. In this study, a new developed high-resolution hyperbolic mesh grid was applied to the Korean peninsula. The minimum and maximum grid size is 321 m in coastal regions and ∼18 km in offshore areas, respectively. A total of 60 representative potential storm tracks were developed based on preselected four historic storm tracks in the study area. Each storm tracks were assumed to be 2 different strength, implying each 50 and 100-yr return frequency level. Five different sea-level rise scenario were applied on the basis of the recent IPCC report: 0, 34.1, 65.0, 83.8, and 98.0 cm above the present sea level. Thus, a total of 600 scenarios (= 5 sea levels X 2 strength X 60 storm tracks) were simulated, and Maximum Envelop Of Water (MEOW) and Maximum Of Maximum (MOM) were calculated for each water level case. The results show that the rise of sea level induces higher storm surge and the increasing trend is not linear. For instance, the case with 98 cm sea-level rise above the current sea level show about 1.5-2.5 m increase of storm surge. Also, the results of storm surge (i.e., MOM) were applied to local topography data, which estimate inundation depth for each cell. As expected, the case of present sea level depicts lowest inundation and it increase with the range of sea level rise. Also, the area of inundation is smallest in the case of present sea level, and more sea level rise results in larger area of inundation.
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