NHESSNatural Hazards and Earth System SciencesNHESSNat. Hazards Earth Syst. Sci.1684-9981Copernicus PublicationsGöttingen, Germany10.5194/nhess-17-1559-2017Assessing storm surge hazard and impact of sea level rise in the Lesser
Antilles case study of MartiniqueKrienYannykrien@gmail.comhttps://orcid.org/0000-0002-6471-5801DudonBernardRogerJeanhttps://orcid.org/0000-0002-3078-9052ArnaudGaelhttps://orcid.org/0000-0002-0289-4103ZahiboNarcisseLARGE, Laboratoire de Recherche en Géosciences, Université des Antilles, Guadeloupe, FranceG-Mer Etudes Marines, Guadeloupe, FranceYann Krien (ykrien@gmail.com)18September20171791559157117April201725April201720July20173August2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://nhess.copernicus.org/articles/17/1559/2017/nhess-17-1559-2017.htmlThe full text article is available as a PDF file from https://nhess.copernicus.org/articles/17/1559/2017/nhess-17-1559-2017.pdf
In the Lesser Antilles, coastal inundations from
hurricane-induced
storm surges pose a great threat to lives, properties and
ecosystems. Assessing current and future storm surge hazards 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 the 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 nonlinear interactions of sea level
rise (SLR) 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.
Introduction
Coastal urbanization and industrialization in storm-surge-prone
areas pose great challenges for adaptation and mitigation. Human and economic
losses due to water extremes have considerably increased over the last
decades (WMO, 2014) and are expected to continue to do so in many areas
worldwide because of coastal population growth (Neumann et al., 2015) and
climate change impacts (sea level rise, SLR; deterioration of protected
marine ecosystems; potential increase in the frequency of extreme events;
etc.). It is therefore necessary to better assess current and future storm
surge hazards to help decision makers regulate land use in coastal areas and
develop mitigation strategies.
The Lesser Antilles are the first islands on the path of hurricanes
that originate off the west coasts of Africa and strengthen during
their travel across the warm waters of the tropical Atlantic
Ocean. They are therefore regularly exposed to extremely severe winds
and waves causing great human and economic losses. In the center of
the Lesser Antilles Archipelago lies Martinique, a French insular
overseas region which shares similar characteristics with neighboring
islands, such as a relatively narrow island shelf, fringing coral
reefs, mangrove forests, numerous bays and contrasted slope
morphologies.
Although Martinique has been relatively spared over the last decades
compared to other islands such as Dominica or Guadeloupe, it still
largely suffered from massive destruction in coastal areas due to
hurricanes passing nearby (Durand et al., 1997; Pagney and Leone,
1999; Saffache, 2000; Léone, 2007; Duvat, 2015). A recent example
is hurricane Dean (category 2), which struck the island in 2007,
causing severe damages, especially along the exposed east coast
(Barras et al., 2008).
About 15 years ago, the French national meteorological service
delivered a preliminary map of 100-year surge heights in Martinique
(Météo France, 2002). These early results were of great interest and
have been used extensively by coastal planners since then (Grau and Roudil,
2013). At the time, however, wave–current interactions were not taken into
account, although waves were already known to have a strong impact on surges
in coastal areas (e.g., Wolf et al., 2011; Brown et al., 2011). Water levels
were thus expected to be underestimated, especially in areas exposed to
waves.
Over the past few years, significant progress has been made in developing
wave–current coupled models (e.g., Dietrich et al., 2012; Roland et al.,
2012; Kumar et al., 2012; Qi et al., 2009; Bennis et al., 2011; Dutour
Sikiric et al., 2013), but no attempt has been made so far to improve storm
surge hazard assessment in Martinique. The preliminary results are thus still
largely used as a reference by decision makers, and recent works investigate
the impacts of historical events (e.g., Barras et al., 2008) or the ability
of numerical models to reproduce extreme water levels and inland flooding
(Nicolae Lerma et al., 2014).
The potential impacts of climate change have also received little attention.
Although the effect of a warmer climate remains relatively uncertain in terms
of hurricane activity in the North Atlantic (e.g., Knutson et al., 2010),
a significant increase in sea level is expected in the Lesser Antilles in the
coming decades (Palanisamy et al., 2012). Moreover, coastal ecosystems such
as mangroves, coral reefs or seagrass beds may not be able to adapt to
climate change (e.g., Waycott et al., 2009; Wong et al., 2014), which could
have large impacts on coastal flooding (e.g., Alongi, 2008; Wong et al.,
2014).
Here we investigate storm surge hazard in Martinique in greater detail and
derive more accurate 100-year surge heights and maximum surge levels, using
state-of-the-art numerical models and the statistical-deterministic approach
of Emanuel et al. (2006). We also conduct preliminary tests to investigate
the impact of sea level rise (SLR) in the following decades. The present
paper is organized as follows: after a short presentation of the study area
(Sect. 2), we describe the methodology (Sect. 3) and the numerical model
(Sect. 4). The results are shown in Sect. 5. The limitations of this study
and material for further research are given in Sect. 6. The main conclusions
can be found in Sect. 7.
Study area
Located in the center of the Lesser Antilles (Fig. 1a), Martinique is
a French mountainous island of about 390 000 inhabitants, with a remarkable
variety of coastal environments (mangroves, cliffs, sandy coves, coral reefs,
highly urbanized areas, etc.) and contrasted sea bottom morphologies. The
Atlantic coast is characterized by barrier and fringing coral reefs, as well
as a gently dipping dissipating shelf promoting relatively large storm
surges, whereas most of the Caribbean beaches are reflective, with waves
propagating onshore without significant attenuation, except in the Bay of
Fort-de-France (Fig. 1).
(a) Area of interest. The computational domain is
given in red. Dashed white lines represent the southernmost and
northernmost tracks considered for the “worst case scenarios” (Sect. 5.1).
(b) Focus on Martinique and the location of coral reef communities
(red), mangroves areas (green) and lagoons (cyan). Source of data: agence des
aires marines protégées. (c) Isobaths at 10 m
(white), 20 m (yellow), and 100 m (cyan), as well as location
of the bathymetric profiles displayed in (d).
A large part of the population has been living close to the shoreline
for centuries, for historical or economic reasons, such as military
defense or fishing activities (EPRI, 2012). This trend is being
accentuated with the development of tourism infrastructures since the
1960s (Desarthe, 2014). The number of tourists has tripled since
1995, even though the sector has undergone a deterioration recently
(Dehoorne et al., 2014). Coastal zones are now highly coveted and
densely populated areas (Garnier et al., 2015), which are prone to natural
hazards such as erosion, storm surges or tsunamis (e.g., Poisson and
Pedreros, 2007). The Bay of Fort-de-France has been identified as
a particularly vulnerable area by the French government services, in
the framework of the EU Floods Directive (PGRI, 2014). Indeed, this
relatively low-lying zone concentrates a great part of the industry,
services and transport infrastructures (highway, airport,
etc.). In addition, the mangrove forest of Lamentin (Fig. 1b) is one of the
largest remaining mangroves of the Caribbean and an important ecological
area supporting a great variety of animal species.
Martinique is regularly affected by severe storms: about one hurricane
every 10 years on average, according to the data provided by NOAA's
Office for Coastal Management (Fig. 2). Fortunately, it has been
relatively spared over the past decades compared to neighboring
islands such as Dominica or Guadeloupe, with only one hurricane making
landfall on the island since 1900 (Fig. 2). The main
historical hurricane event is probably the hurricane that hit Martinique in 1780,
resulting in about 9000 fatalities (Saffache et al., 2002). More
recently, Dean (a category 5 hurricane that passed Martinique as
a category 2 storm in 2007) caused very extensive damage to the urban
areas close to the coast as well as severe coastline erosion (Barras
et al., 2008). Significant destructions also arose in recent years
because of energetic swells generated by hurricanes traveling eastward
in the Caribbean Sea (e.g., Omar in 2008 or Lenny, 1999). The
reflective Caribbean coast is particularly exposed to this type of
event.
Tracks and intensities of historical hurricanes passing
within 65 nautical miles from Martinique, since 1900. (source:
NOAA's Office for Coastal Management,
https://coast.noaa.gov/hurricanes/).
Marine ecosystems such as coral reefs or mangroves are known to
provide substantial protection against waves and surges during
hurricanes (e.g., Ferrario et al., 2014). In Martinique, however,
mangrove forests have at least partially deteriorated due to
earthworks, water and soil pollution, or hurricanes (e.g., Imbert and
Migeot, 2009). The situation is even worse for coral reefs, for which
a dramatic decline due to eutrophication, anthropogenic disturbances
or extreme storms has been observed over the past 40 years (Bouchon
and Laborel, 1986; Legrand et al., 2008; Rousseau et al., 2010;
IFRECOR, 2016). The deterioration of these marine ecosystems because
of climate change is thus a cause of major concern for the coming
decades.
A warmer climate is also expected to induce a significant increase in
sea level in Martinique. Since the regional trends are very similar to
the global mean rate (Palanisamy et al., 2012), the mean sea level
might rise by several dozens of centimeters or more in the coming
decades. All these findings strongly encourage coastal planners and
scientists to better assess current and future storm surge hazard
along the coastline of Martinique in order to develop mitigation
strategies.
Methodology
To achieve this goal, we conducted numerical investigations using
a wave–current coupled model (Sect. 4). As a first step, we computed the
maximum surge obtained for a few synthetic severe (category 4–5) hurricanes.
The aim is to better understand the mechanisms responsible for generating
storm surges in Martinique and to crudely estimate the maximum surges that
could be reached along the coastline for extreme events. To do this, we
generated 13 synthetic hurricanes striking Martinique, with maximum velocity
Vmax=140kn (knot), radius of maximum winds
Rmax=20km, track angle of 10∘ with respect to
an east–west profile, and translation speed Vt=12kn.
These values represent typical characteristics of major hurricanes in
Martinique (Sansorgne, 2013). A few sensitivity tests were performed to
ensure that track angle and translation speed are of second order compared to
hurricane intensity and distance to the area of interest (Sansorgne, 2013).
The tracks parallel each other and are spaced 10 km apart to
take into account almost all the possible landfall locations. The
southernmost and northernmost tracks are displayed in Fig. 1.
In a second phase, we derived new 100-year surge levels. This step is
relatively complex for regions prone to cyclones because of the dearth of
events in historical records. Traditional extreme value analysis methods are
generally found to not be applicable in these areas, so more advanced
statistical approaches are needed to infer water level return periods. These
methods involve the generation of a large number of synthetic cyclones that
are in statistical agreement with observations. Several approaches have been
proposed so far, such as JPM-OS (Joint Probability Methods with Optimal
Sampling, e.g., Resio, 2007; Toro et al., 2010) or the
statistical-deterministic model of Emanuel et al. (2006). They have been used
successfully for storm surge assessment at local (Lin et al., 2010, 2012),
regional (Harper et al., 2009; Niedoroda et al., 2010) or even continental
(Haigh et al., 2014) scales. In the present paper, we use the
statistical-deterministic approach of Emanuel et al. (2006), which provided
good results for Guadeloupe in a previous study (Krien et al., 2015). This
method consists of four main steps (Emanuel et al., 2006):
The genesis locations of the new synthetic storms are obtained
by a random draw from a space–time probability density function derived from
historical genesis point data.
For each storm considered, synthetic time series of the zonal
and meridional wind components at 250 and 850 hPa are generated. They
are designed to conform to the climatologies derived from NCEP–NCAR
reanalysis between 1980 and 2011. In particular, the observed monthly means
and variances are respected, as well as most covariances. The wind time
series are regenerated if the initial vertical shear is too strong to be
conducive to a storm.
The storm track is then derived from a weighted mean of the 250 and
850 hPa flow plus a correction for beta drift (Emanuel et al., 2006). The
weight factor and beta-drift terms are chosen to optimize comparisons between
the synthesized and observed displacement statistics.
The intensity along the synthetic track is obtained using
a numerical model developed by Emanuel et al. (2004). The wind shear
is given by the synthetic time series of winds determined
previously. The monthly mean climatological upper-ocean thermal
structure is taken from Levitus (1982).
The full database developed for this study contains 3200
low-pressure events (tropical depressions, tropical storms and
hurricanes) passing within 100 km from Fort-de-France
(Fig. 3).
Examples of synthetic hurricanes generated for this
study, using the statistical-numerical approach of Emanuel
et al. (2006).
It represents about 8000 years of hurricane activity under the present
climate conditions in the immediate vicinity of Martinique. In practice,
however, we computed only the surges for the strongest events, as tropical
storms and depressions are not found to be able to generate water levels with
a 100-year return period. In all, 700 events were simulated on a 240-core
computational cluster.
In both cases, we also investigated the effect of a 1 m sea level rise.
Considering that the sea level trend in the Lesser Antilles is very similar
to the global mean rate (Palanisamy et al., 2012), this value of 1 m
roughly corresponds to the global projections of IPCC by 2100 in the case of
a high emission scenario (IPCC, 2013). Considering that coral reefs and
mangroves have already deteriorated, we assume here that they will not been
further damaged but that they cannot keep pace with SLR. In practice, this
amounts to a rise in the water level of 1 m, without changing the shape of
bathymetry or topography.
Numerical modelModel description
In this study we employed the wave–current coupled model ADCIRC+SWAN (Dietrich et al., 2012). ADCIRC (ADvanced CIRCulation Model,
Luettich et al., 1992; Westerink et al., 1994) is a finite-element
hydrodynamic model that solves the depth-averaged barotropic form of the
shallow water equations on unstructured grids. Water levels are obtained from
the solution of the generalized wave-continuity equation, whereas currents are
derived from the vertically integrated momentum equation. A wetting–drying
algorithm is also included to allow inland overflowing.
After several sensitivity tests to achieve stability of the model and results
while keeping reasonable computing time, a time step of 1 s was
chosen.
ADCIRC (v50) is coupled to the wave model SWAN (Simulating WAves
Nearshore, Booij et al., 1999), which predicts the evolution in time
and space of the wave action density spectrum and has been converted
recently to also run on unstructured meshes (Zijlema et al.,
2010). Computations are performed here using 36 directions and
36 frequency bins. Source terms include wind input (Cavaleri and
Malanotte-Rizzoli, 1981; Komen et al., 1984), quadruplet interactions
(Hasselmann et al., 1985), whitecapping (Komen et al., 1984), triads
(Eldeberky, 1996), bottom friction (Madsen et al., 1988) and wave
breaking (Battjes and Janssen, 1978).
SWAN is forced by the wind velocities, water levels and currents given
by ADCIRC and passes back the radiation stress gradients every
10 min (Dietrich et al., 2012). Bottom friction is computed in ADCIRC
using a Manning formulation. The coefficients are converted to
roughness length by SWAN. The Manning coefficient here depends on land
cover (European Union, 2006). The values can be found in Krien
et al. (2015) and are displayed in Fig. 4a. Note that we did not
consider a strong dissipation of energy at the bottom for coral reefs,
as they are known to be very eroded in Martinique (IFRECOR, 2016).
The model is forced by wind and pressure fields, calculated using the
gradient wind profiles of Emanuel and Rotunno (2011) and
Holland (1980) respectively (see Krien et al., 2015, for more details).
Topography and bathymetry in shallow waters (up to about 40 m depth)
are specified using high-resolution lidar data (Litto3D Program). On the
shelf, ship-based sounding data acquired by the French Naval Hydrographic and
Oceanographic Department (SHOM) are also included. GEBCO (General Bathymetric Chart of the Oceans) data with 30 arcsec
resolution are used for deep water areas.
The effect of tides are neglected here as their amplitude is very low
in Martinique (less than 35 cm).
The computational domain is displayed in Fig. 1. The resolution spans
from 10 km in the deep ocean to about 50 m on the
coastline and coral reefs (Fig. 4b).
(a) Spatial variation of the Manning coefficient
n, based on land cover data (European Union,
2006). (b) Spatial variation of the mesh resolution in the
vicinity of Martinique.
Model performance
This model has been used and validated for various storm events around
the world (e.g., Dietrich et al.,, 2011a, b, 2012; Hope et al., 2013;
Kennedy et al., 2011; Murty et al., 2016). It was also found to give
good results for several islands in the Lesser Antilles, such as
Guadeloupe and Martinique (Krien et al., 2015; Nicolae Lerma et al.,
2014).
In the course of the present study, we conducted a few more validation
tests, such as for hurricane Dean (2007). Results are consistent with
observations, but those are not sufficiently accurate and compelling
to really add relevant information regarding the ability of the model
to reproduce storm surges. As an example, the tide gauge located at Le
Robert recorded a surge peak (of about 20 cm according to our
estimates) on 17 August 2007, but this value is probably significantly
underestimated since only hourly data are available. Our model
predicts higher values (about 75 cm), which are more
consistent with observations made by witnesses, who reported that the
garden south of the city center (14.6753∘ N, 60.9387∘ W)
was partially under water. Similarly, only small surges (less than
20 cm) were recorded in Fort-de-France (Barras et al., 2008)
for hurricane Dean. This is again consistent with the model prediction
(15 cm), but not really satisfying in terms of validation for
extreme events. Similarly, in the most impacted areas, such as Le
Vauclin, only indirect information about the maximum water level is
available (e.g., Barras et al., 2008). Although they are again in
agreement with the predictions of the numerical model (about
1.5 m above mean sea level), systematic measurements of water
levels should be performed in the future to be able to better
assess the ability of the model to reproduce storm surges. Note that
preliminary validation tests were also performed for waves and give
satisfying results (Krien, 2013).
ResultsTest cases for a few synthetic hurricanes and maximum
surge levels
The results obtained for a few “worst case” (category 4–5) events
are displayed in Fig. 5 and Table 1. The water levels on the Caribbean
coast are found to be largest for hurricanes making landfall in the
northern part of Martinique. This was expected since in this case the
winds on the west coast are essentially onshore when hurricanes pass
over the island.
Maximum storm surges (in meters) predicted by the model for
the 13 worst case scenarios at four different locations:
Fort-de-France tide gauge, airport, Le Robert tide gauge, and Le
Vauclin. The distance of the hurricane track from Fort-de-France is
also given. (S) or (N) refers to a storm passing
south or north of Fort-de-France respectively. The maximum values
obtained for each location are shown in bold.
Water levels can exceed 4 m above mean sea level in the upper
part of the Bay of Fort-de-France for extreme events (Fig. 5a). In
that case, most of the surge is driven by the wind. The wave setup
only contributes a few tens of centimeters to the total water
levels (Fig. 5b). This component plays a crucial role on the
Atlantic coast, where it can reach 1 m. In some locations,
such as Le Vauclin, the wave setup accounts for
almost all the total surge.
On the eastern coast, the surge is maximum for hurricanes passing
south of Martinique. For category 4–5 hurricanes (such as the ones
modeled here), it can exceed 3 m locally (Fig. 5c). The wave
setup is still significant (up to about 1 m) in the shallow
waters between the coastline and the coral reefs on the Atlantic coast
(Fig. 5d). This contribution can amount to about 50 % of the total
surge along the southeastern coasts of Martinique in the test case
considered here.
Figure 5e and f show the results obtained when considering a sea level
rise of 1 m. The wave setup is found to be only slightly
modified, with a reduction of a few centimeters in general compared to
the case without sea level rise Fig. 5d. The wind-driven surge is
significantly attenuated near the shore (by a few tens of
centimeters), because wind stresses are less efficient in driving
water masses towards the coast when the water depth is higher
(comparison between Fig. 5c and Fig. 5e).
Maximum water levels (left) and wave setup (right) for
three worst case (category 4–5) hurricanes: northern track
and no sea level rise (a, b), southern track
and no sea level rise (c, d), and southern track with
1 m sea level rise (e, f). The dashed black lines represent
the track of the
cyclone for each scenario. “Wave setup” refers here to the
difference between the maximum water levels with and without
waves. Note that the wave setup “peaks” offshore the northwest
coast are probably due to small numerical instabilities in SWAN
in a region with strong lateral bathymetric
variations. Fortunately these errors are found to be very small
(1 cm maximum) and bear no consequences on the results
presented in this paper.
Maximum surges obtained by considering worst case
(category 4–5) hurricanes hitting Martinique, without (a)
and with (b) sea level rise.
The maximum water levels computed using the 13 synthetic category 4–5
hurricanes are presented in Fig. 6a. As mentioned above, the maximum
surges are obtained for the bay of Fort-de-France, where water levels
can exceed 4 m above mean sea level. The head of the bay,
where high environmental and transportation stakes are located
(e.g., airport, national roads, mangrove forest), is particularly
exposed.
The shallow waters of the eastern coast also promote significant
surges, which can reach about 3 m. On the other hand, the
steep slopes characterizing most of the western part of Martinique
impedes strong wind surges and are generally not directly exposed to
waves, so maximum water levels are considerably reduced. Note,
however, that the grid resolution (about 50 m) is probably not
sufficient to fully capture the wave setup in these areas, so the
maximum surge (about 1 m) might be somewhat underestimated.
A sea level rise of 1 m would have potentially major impacts,
for example, in the urban area of Fort-de-France (Fig. 6b) where many
buildings could be flooded in the case of a severe storm.
100-year surge levels for present climate and no SLR (a),
as well as difference between 100-year surge levels for present climate when
considering a 1 m sea level rise (b).
Statistical storm surge analysis
The 100-year surge levels obtained using the database described in
Sect. 3 are plotted in Fig. 7a. Since extreme hurricanes striking
Martinique are rather scarce, these levels are found to be
significantly smaller than the maximum surges estimated above, by
a factor of 2 or more. However, they still reach 1.5 m on the
Atlantic coast or in the Fort-de-France bay. These 100-year surge
heights are thus significantly higher than those computed in early
studies (Météo France, 2002), with discrepancies that can
reach 1 m – for example, in the southeast. Such differences are
certainly largely due to the wave-induced setup, which has been found
to contribute significantly to the water levels (Sect. 5.1) and was
not accounted for in the early 2000s.
The impact of a 1 m sea level rise on 100-year surge levels
is investigated in Fig. 7b. The nonlinear interactions between surge
and topography–bathymetry result in a decrease in water levels by
several centimeters in most coastal areas, especially between the
eastern shoreline and coral reefs, where the wave setup is reduced,
and in shallow waters where the wind is less efficient in generating
surges because of larger water depths. Conversely, the 100-year
surges are increased inland by a few tens of centimeters in low-lying
regions where the inundation extent is strongly enhanced by the sea
level rise. This is the case, for example, in the bay of Fort-de-France
or in the Les Salines laguna, where a 1 m sea level rise will
allow storm surges to inundate the low-lying areas beyond the sand
dune (Fig. 1d).
Discussion
These results constitute a significant step forward in assessing storm
surge hazard and impacts of SLR in Martinique. However, this study
still leaves room for improvement. In particular, more work will be
needed in the future to further investigate the impacts of climate
change, including the following:
Changes in hurricane activity. Although the effect of
a warmer climate remains uncertain, a number of studies seem to
reach the conclusion that the frequency of hurricanes will decrease
but that these events will be on average more intense (e.g., Knutson
et al., 2010). This might lead to changes in water levels for
a given return period, even if preliminary works suggest that the
impact could be very moderate compared to the effect of SLR
(e.g., Condon and Sheng, 2012).
Evolution of coastal ecosystems. Coral bleaching and
mortality are expected to increase over the next decades due to
ocean warming and acidification (e.g., Hoegh-Guldberg et al., 2007;
Baker et al., 2008; Wong et al., 2014). Although it is not clear
whether coral reefs will be able to keep up with the sea level rise
in Martinique, their dramatic decline due to eutrophication,
anthropogenic disturbances or hurricanes over the past
40 years (Bouchon and Laborel, 1986; Legrand et al., 2008;
Rousseau et al., 2010; IFRECOR, 2016) gives little reason for
optimism. This could have major consequences in terms of wave
impacts at coastlines, and possibly also for surges, although the
results presented here suggest that this effect might be moderate.
Similarly, mangrove forests have at least partially
deteriorated due to earthworks, water and soil pollution, or
hurricanes (e.g., Imbert and Migeot, 2009) and may have difficulty
adapting to climate change in some specific areas (Gilman et al.,
2008; IFRECOR, 2016). Seagrass beds already degraded by anthropic
pressure or patches of Sargassum (Thabard and Pouget-Cuvelier, 2014)
might experience the same fate (Waycott et al., 2009). As
a consequence, shorelines might be much more vulnerable to erosion
and storm surges in the following decades (e.g., Alongi, 2008; Wong
et al., 2014).
Evolution of the shoreline due to sediment transport, human activities or vertical motions. In Martinique, a few low
sandy coastlines are subject to erosion and might be more exposed to
relative sea level rise in the coming decades (Lemoigne et al.,
2013). This is the case for several coves, especially in the south
(e.g., Sainte-Anne, see Fig. 1). However, most low-lying coastal
areas are rather in accretion because of natural and/or anthropic
factors. This has been observed, in particular, for the bay of
Fort-de-France, where a coastline extension of about 100 m
was reported between 1951 and 2010 (Lemoigne et al., 2013) in the
mangrove area.
In addition, the numerical approach can be further improved, particularly
regarding the following:
The resolution. Due to high computational costs, it was
hardly possible to have a resolution better than 50 m at the
coastline and for coral reefs. To get an idea of the potential error
in water levels, we performed a few sensitivity tests with higher
resolutions (typically 20–30 m). The discrepancy was found
to only amount to a few centimeters in shallow areas, where most
of the stakes are exposed to storm surges. The coral reefs' geometry
seems to be satisfactorily captured by the mesh, probably because
the reefs are strongly eroded (so bathymetric gradients are
relatively mild) and also because we ensured that the minimum water
depths were correctly captured in these areas. However, a resolution
of 50 m is probably insufficient to properly assess the wave
setup component in areas where the slope is steep. For example, the results found are
thus expected to be somewhat underestimated in the northwestern
coast. Note, however, that these areas are generally not
really exposed to storm surges. They are more prone to wave
overtopping, which is not taken into account in this study and will
require further work in the future.
The phase-averaged model. Phase-averaged models suffer
from several limitations. In particular, they do not deal with
run-up, which might contribute significantly to shoreline inundation
(e.g Ford et al., 2013). This can be the case for
fringing coral reefs, for example, where the water level can be dominated by
large low-frequency (e.g., infragravity) waves. Indeed, during
extreme events, the spectral wave energy at reef crests shifts into
lower frequencies, which can be amplified due to resonance modes
(e.g., Roberts et al., 1992; Péquinet et al., 2009; Cheriton
et al., 2016). Even if (to our knowledge) large infragravity waves
were not reported in Martinique, we see no reason to rule them
out. In addition, climate change and sea level rise are expected to
change the hydrodynamics across the reefs and might further
increase the exposure of coastlines to these type of waves
(e.g., Merrifield et al., 2014). This issue has been receiving more
and more attention over the last years and will probably be a major
topic of research in the near future.
West-to-east tracks. A few hurricanes impacting
Martinique and traveling eastward have been reported recently
(e.g., Omar in 2008 or Lenny in 1999). Although several synthetic
events with similar characteristics are included in our database,
these events might be too infrequent to be properly represented from
a statistical point of view. Since the hurricanes generally pass far away from
Martinique, they are not expected to have large impacts on our
computed 100-year surges in low-lying (surge prone) areas. However,
larger errors can be expected for steep slopes on the western
coast.
Conclusions
Using coupled wave–current numerical models and a dataset of
synthetic hurricanes representing thousands of years of cyclonic activity in
the central part of the Lesser Antilles, we presented a detailed analysis of
storm surge hazard in Martinique for the present climate and started
investigating the potential changes expected for the next decades. The
100-year and extreme surge levels are found to be highest for the bay of
Fort-de-France and the Atlantic coast (south of La Trinité, see Fig. 1
for location), where they can reach up to 4–5 and 3 m respectively.
A very significant part of the surge (up to about 1 m on the eastern
coast) can be due to the wave setup. The contribution of radiation stress
gradients can even account for almost all the total surge in some special
cases – for example, for hurricanes making landfall in the northern part of
Martinique that will induce essentially cross shore or offshore winds (and
hence low wind setup) on the southeastern coast.
The nonlinear interactions of sea level rise with bathymetry and
topography are generally found to be relatively small, with
a reduction of surge by a few centimeters in many nearshore areas,
because the wave setup is reduced and the wind is less efficient in
driving water masses towards the shoreline with increasing water
depths. However, they can amount to several tens of centimeters in
specific low-lying areas (mangroves or lagoons for example) where the
inundation extent is strongly enhanced compared to present conditions,
due to SLR. These results provide further evidence that drawing
inundation maps for the future without considering the nonlinear effects
of sea level rise on water levels can lead to significant errors.
In the case of a large sea level rise in the coming decades, hurricanes
striking Martinique could have devastating impacts in the bay of
Fort-de-France, where most economical, historical and transportation
stakes are located. According to some of our worst case
scenarios, a large part of the Fort-de-France urban area could be
regularly flooded by hurricanes by the end of the 21st century. This
finding also applies to the airport, located on the waterfront, and
probably several major trunk roads.
The results presented in this paper can be further improved in terms
of resolution, or by taking infragravity waves into account. The other
impacts of climate change (evolution of coastal ecosystems and
hurricane activity, for example) could also be investigated in greater
detail. Some of those limitations are currently being addressed in
the framework of C3AF, a project funded by the ERDF (European Regional
Development Fund).
The methodology and results presented here should be of interest for
other islands in the Lesser Antilles, as they display similar
morphological features to Martinique, such as a relatively narrow
shelf, contrasted slope morphologies, the presence of coral reefs and/or
mangrove forests. This is confirmed, for instance, for the Guadeloupe
archipelago, where very similar results in terms of 100-year surge
levels (Krien et al., 2015), maximum water levels, or wave setup
contribution are found.
The 100-year surge data are freely available, provided that
an agreement is signed with the University of the French West Indies. Please
contact Professor Narcisse Zahibo (narcisse.zahibo@univ-ag.fr) for details.
The authors declare that they have no conflict of
interest.
Acknowledgements
This work was supported by the INTERREG IV/TSUNAHOULE and FEDER/C3AF projects
as well as by the Guadeloupe region. Many thanks to Kerry Emmanuel from the
Massachusetts Institute of Technology for providing the synthetic storm
datasets, as well as to Raphaël Pasquier, Jacques Laminie and Pascal
Poullet (University of the French West Indies) for the setup of the computing
cluster. We also express our gratitude to A. N. Lerma and another anonymous
reviewer for their helpful comments and suggestions, which have led to
a significantly improved manuscript.
Edited by: Thomas Glade
Reviewed by: Alexandre Nicolae Lerma and Michaela Spiske
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