This work assesses the impacts in reshaping coastlines as a result of sea level rise and changes in wave climate. The methodology proposed combines the SWAN and SWASH wave models to resolve the wave processes from deep waters up to the swash zone in two micro-tidal sandy beaches in Mallorca island, western Mediterranean. In a first step, the modelling approach has been validated with observations from wave gauges and from the shoreline inferred from video monitoring stations, showing a good agreement between them. Afterwards, the modelling set-up has been applied to the 21st century sea level and wave projections under two different climate scenarios, representative concentration pathways RCP45 and RCP85. Sea level projections have been retrieved from state-of-the-art regional estimates, while wave projections were obtained from regional climate models. Changes in the shoreline position have been explored under mean and extreme wave conditions. Our results indicate that the studied beaches would suffer a coastal retreat between 7 and up to 50 m, equivalent to half of the present-day aerial beach surface, under the climate scenarios considered.
Rising sea levels represent one of the major threats for coastal regions, causing submersion, erosion and increased vulnerability to extreme marine events, among other negative impacts (Nicholls and Cazenave, 2010). It is expected that such effects will be aggravated in the coming decades as sea level rise accelerates in response to global warming (Church et al., 2013) and coastal population and development grow (Hanson et al., 2011).
Several studies have related coastline retreat during the last decades with sea level rise (e.g. Feagin et al., 2005; FitzGerald et al., 2008), although other relevant processes have also been identified (Passeri et al., 2015). These include oceanic forcing by wave climate and storms, direct or indirect human actions (e.g. mining activities or fluid extraction), and local features such as coastal morphology (Cazenave and Le Cozannet, 2014). Coastline retreat has important environmental impacts but also socio-economic implications as it affects population, infrastructures and assets. The impact of sea level rise in the shoreline position has therefore become a subject of increasing concern, particularly in densely populated regions with high urban development. This is the case for many Mediterranean regions, whose economies, which constitute about 14 % of the total gross domestic product of the EU (Eurostat, 2011), largely rely on tourism based on beach and other seaside recreational activities. Thus, sea level rise and its potential impacts are key factors that must be incorporated in coastal risk management and climate change adaptation measures.
In this paper, we investigate the shoreline changes in two anthropized micro-tidal sandy beaches located in Mallorca (Balearic Islands, western Mediterranean Sea) are investigated. Here, the shoreline is defined as the water–land interface of the beach, i.e. the limit of the swash zone. The potential impacts of a shoreline retreat would increase the vulnerability of the nearshore infrastructures. In addition, both are typical tourism-oriented beaches in urban environments of the Mediterranean region, so their reduction or disappearance would be detrimental for the local economies.
The impact of sea level rise along sandy coastlines consists of two processes, namely inundation and erosion. Increased sea levels allow waves and surges to act at higher levels landward in the beach profile, increasing erosion rates (Zhang et al., 2004). However, in this study the beach erosion has not been considered, which means that our estimates of landward migration of the coastline could be biased low if erosion rates increase and sediments are carried offshore; in other words, what is assessed here is the minimum impact in beach shoreline retreat. This assumption is further discussed later. Some earlier studies have explored the potential impact of future sea level rise on shoreline changes, although without taking into account changes in the wave climate (see e.g. Wu et al., 2002; Stive, 2004; Poulter and Halpin, 2008; Le Cozannet et al., 2014). Others have addressed the impact of waves, including extreme events, erosion rates, morphological changes, flooding, and vulnerability of infrastructures but sometimes without including changes in sea level (see e.g. Ruju et al., 2012; Guimarães et al., 2015; Medellín et al., 2016). Here, in line with works in Villatoro et al. (2014), we address both effects. Furthermore, our study goes beyond the “bathtub” approach and takes into consideration the wave dynamic forces (as in, for example, Passeri et al., 2015; Plant et al., 2016; Gutierrez et al., 2011). To do so, we have used regional sea level changes retrieved from global sea level projections, with all the different contributions, in combination with regional wave projections over the western Mediterranean Sea up to the year 2100 under two different climate change scenarios. The paper is organized as follows. Section 2 is devoted to the description of the study areas, the characteristics of the wave climate, the data available and the numerical approach. The validation of the methodology, which includes the comparison between modelled and observed shallow water waves and coastline positions, is presented in Sect. 3. Section 4 describes the shoreline changes obtained under different climate change scenarios. Finally, a summary and some conclusions are presented in Sect. 5.
Cala Millor and Playa de Palma are two micro-tidal sandy beaches located in Mallorca island (Balearic Islands, western Mediterranean Sea; Fig. 1). Cala Millor is 1.7 km alongshore by 35–40 m cross-shore, with a rock bed and a small cliff at the southernmost sector of the beach, and it is exposed to offshore waves from the NE to ESE. Both beaches are reflective, with the Playa de Palma slope being slightly steeper than Cala Millor.
Mallorca island with Cala Millor and Playa de Palma beaches marked with orange squares. SIMAR grid points used to characterize the offshore wave climate and the Capdepera wave buoy are also marked. The inset map represents the western Mediterranean basin.
Playa de Palma and Cala Millor self-organizing maps (SOMs). SIMAR
databases are shown in 100 cells displaying the more representative deep
water sea conditions at the Playa de Palma
The wave regime in deep waters has a significant wave height (
These two beaches are considered urban beaches since they are backed by promenades and buildings; therefore, the beach responses to hydrodynamic changes are restricted by these features. Also, their aerial shape depends on the distribution of the sand that is carried out by the council workers according to the tourist comfortability. Playa de Palma and Cala Millor beaches have been part of the beach monitoring programme of the Balearic Islands Coastal Observing and Forecasting System (SOCIB) since 2011 (Tintoré et al., 2013). This programme includes periodic topography and bathymetry surveys, continuous video monitoring of the shoreline position and in situ measurements of nearshore waves and currents, among others. In addition, a dedicated field survey (RISKBEACH) was undertaken in Cala Millor in March–April 2014, during which higher resolution observations were obtained (Morales-Márquez et al., 2016). Specific data used in the present work are described in the following.
Bathymetry surveys were conducted using a single-beam echo sounder,
BioSonics DT/DE Series Digital Echosounder, in the Cala Millor beach and a
multi-beam echo sounder, R2Sonic2020, in Playa de Palma. The final
spatial resolution is 1 m cross-shore and 2 m alongshore in Cala Millor and
0.5 m
In Cala Millor, nearshore hydrodynamic data were obtained from three directional Acoustic Waves and Currents (AWACs) sensors located at 8, 12 and 25 m water depths; the AWACs were deployed as part of the RISKBEACH field survey, which covered 12 March to 14 April 2014. Offshore hourly hydrodynamic data have been recovered from Capdepera buoy, located 36.45 km northeast of Cala Millor at 48 m depth (see Fig. 1 for location). The buoy has been operative during the period 1989–2014 as part of Puertos del Estado (the Spanish holding of harbours) buoys network. On the other hand, in Playa de Palma, wave data came from a coastal buoy located at 23 m depth and an acoustic Doppler current profiler (ADCP) deployed at 17 m depth, both operating since January 2012 as part of the SOCIB beach monitoring programme.
Five and fourteen video cameras are used to measure the coastline position along Cala Millor and Playa de Palma beaches, respectively. These cameras are part of the video-based coastal zone monitoring system called SIRENA developed by SOCIB and IMEDEA (Mediterranean Institute of Advanced Studies). Departing from images taken at 7.5 Hz the SIRENA system generates statistical products that provide quantitative information of hydrodynamics and morphodynamics after specific post-processing (Nieto et al., 2010). Specifically, the coastline is routinely obtained from the time image consisting of the addition of all images captured during 10 min (a total of 4500 images) and applying a post-processing of cluster classification. After applying different corrections to overcome the coarser resolution of the far-field camera images as well as rectifying the perspective projection, the coastline is georeferenced in a world coordinate system.
The processing of camera images involves two types of errors related to
the intrinsic and extrinsic calibrations. After images have been optically
corrected, the extrinsic calibration relates pixel position with real-world
coordinates, and thus errors are associated with the georeferencing (Simarro
et al., 2017). Typically, resolution ranges between 0.5 and 2 pixels for Cala
Millor and from 0.5 to 5 pixels for Playa de Palma. Conversely, pixel resolution
decreases with distance, but higher resolution (
With the aim of simulating the shoreline changes under given offshore
conditions, the SWAN (Booij et al., 1999) and SWASH (Zijlema et al., 2011) models
have been combined to resolve the wave processes from deep waters up to the
swash zone. SWAN is a third-generation wave model that solves the spectral
action balance equation for the propagation of wave spectra (
SWAN and SWASH computational domains for the Cala Millor beach. Yellow line indicates the sector where the three ADCPs are located.
For the present study, SWAN simulations have been performed in a stationary
mode over two regular nested grids. In Cala Millor, the coarser grid covers
a domain of 21 km
SWAN and SWASH computational domains for Playa de Palma. Yellow dots indicate the locations of the shallow water wave buoy and ADCP.
SWASH simulations in Cala Millor have been performed on a 1.5 km
The initial wave conditions imposed at the eastern boundary in Cala Millor and at the southwestern boundary in Playa de Palma corresponded to the 2-D variance energy density spectrum field provided by the corresponding SWAN simulations.
The simulations of SWAN and SWASH were performed with the same over-land extent as the width of the beaches, that is, 35–40 m in Cala Millor and 30–50 m in Playa de Palma. The SWASH model requires a rectangular computational grid, so dummy values were used behind the measured topography in order to complete the computational grid, given that the beach width is not uniform.
The final output of the model combination consists of instantaneous water
level elevations in the whole domain and the position of the coastline at
each time step. The shoreline simulated is obtained as a mask of wet–dry
points on the computational grid, providing the limit of flooding at each
time step and mesh position. More precisely, the SWASH model obtains the
moving shoreline ensuring non-negative water depths for a one-dimensional
case (
Finally, the PETRA model is used to evaluate the changes in the beach profile under the different sea level and wave conditions, in order to assess the limitations of the assumption of the unchanged profile. PETRA is a cross-shore beach model that simulates the sediment transport along a single beach profile. It takes into account both the hydrodynamic conditions and the conservation of sand to study the response in 1-D shape. The wave conditions are computed as a phase-averaged model and the sediment transport is calculated using different formulations. The reader is referred to González et al. (2007) for detailed information of this model.
Input condition of the model set-up under climate change scenarios for the two beaches. See the text for details on their computation.
The SWAN–SWASH model set-up described in Sect. 2.4 has been run under present-day and future climate conditions in both domains. The first step aims at validating the model performance, for which the present-day runs, forced with realistic offshore waves, have been compared against measured nearshore wave parameters. In the present-day runs deep water conditions were retrieved from the SIMAR database (Pilar et al., 2008), which is a 58-year wave reanalysis generated with the WAM model (WAMDI GROUP, 1988). The reanalysis, which is freely distributed by Puertos del Estado, covers the western Mediterranean and provides 3-hourly wave data up to 2011 and hourly data since then. The two closest SIMAR grid points to each of the domains were selected to force the SWAN model for the periods of validation (as detailed later). Although this data set has already been evaluated against observations (Pilar et al., 2008; Martínez-Asensio et al., 2013, 2015), we have further compared the output with the offshore waves observed at Capdepera buoy in order to ensure the reliability of the forcing in the particular periods and locations studied here (Sect. 3.1).
The sea level rise is included simply by indicating the still water level corresponding to the sea level in the projections by 2100.
Once validated, the model set-up has been forced under future climate
conditions. To so do, projected sea level rise together with changes in the
wave climate have been run. A summary of the values used for sea level and waves
is presented in Table 1. Regarding sea level, projections by 2100 have been
estimated following Slangen et al. (2014), who provided the regional
distribution of the different contributors to sea level change under two
climate change scenarios, namely representative concentration pathway (RCP)45 and RCP85 (Moss et al., 2010).
These are representative of moderate and
large emission scenarios, respectively. Slangen et al. (2014) used an
ensemble of 21 atmosphere–ocean coupled general circulation models (AOGCMs)
from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive
to estimate changes in ocean circulation and heat uptake contribution,
atmospheric loading, land ice contribution (including all glaciers, ice caps
and ice sheets on Greenland and Antarctica), groundwater depletion and mass
load redistribution worldwide, together with the associated uncertainties
for each term. As the regional distribution of each component was provided,
we selected the Mediterranean region and averaged the sum of the components
as the input for projected sea level rise. The results lead to a regional
sea level rise of 48
Return periods in the A2 scenario for future projections (blue dashed line), control simulation (black dotted line) and hindcast (red line). Note that there are different time periods for the series as well as the overlapping of hindcast and control scenarios. The red line indicates the 1st day of hindcast time series.
Capdepera buoy observations (blue) and hindcasted SIMAR
(black) time series of
Changes in the wave climate during the 21st century have been obtained
from regional wave projections over the western Mediterranean (Puertos del
Estado et al., 2016). These projections were carried out using the WAM model
with a spatial resolution of
In summary, six wave simulations have been carried out for each site to
predict the shoreline changes under mean conditions: one for each of the two
sea level rise scenarios (RCP45 and RCP85) and one for their respective
upper and lower uncertainty limits (i.e. plus 1
Scatter plots of buoy observations vs. SIMAR hindcast for
As described above, the SIMAR wave reanalysis has been taken as
representative of the offshore wave conditions and used to force the
numerical model set-up. To illustrate its reliability, the time series at the
closest grid point in Cala Millor has been compared against observations
from the nearby Capdepera buoy. The time series and scatter plots of the
measured and modelled statistical wave parameters (
Despite the differences found in the wave direction, the advantages of using reanalysed data instead of observations for the input wave in SWAN are evident: first, the modelled time series are complete, while observations are often gappy; and second, the deep water waves can be propagated over large domains, thus providing values close to our two areas of study. Although the validation of the numerical hindcast is limited to a single grid point close to Cala Millor, previous assessments (e.g. Martínez-Asensio et al., 2013) also validated this hindcast, and it is therefore assumed that the reanalysis is equally valid for Playa de Palma.
Comparison between SWAN results and nearshore wave observations in the Cala Millor beach. The period spanned by the series is from 14 March to 14 April 2014.
SWAN vs. ADCP scatter plots of
Comparison between SWAN results and nearshore wave observations in Playa de Palma. The period spanned by the series is from 1 to 30 September 2015.
The output of the SWAN model has been validated against observations in the
two beaches. In Cala Millor the results of SWAN forced with SIMAR data were
compared with nearshore wave observations during the period from 14 March
to 14 April 2014 (i.e. a total of 755 h of simulation). The closest grid
points of the SWAN model to each of the three directional wave ADCPs were
selected. Resulting correlations, RMSEs and biases are listed in Table 2 for
the three ADCPs and for the three wave parameters. Overall, the statistical
parameters show good agreement between measurements and the model output,
with correlations over 0.9 for
SWAN vs. ADCP scatter plots of
In Playa de Palma, the simulated waves have been compared with the
observations from a buoy moored at 23 m depth and with an ADCP at 17 m
depth for the period from 1 to 30 September 2015 (i.e. a total of
720 h of simulation). The results are summarized in Table 3 and the time
series are plotted in Figs. 10 and 11. Like in Cala Millor, there is a
good agreement in
Dates and forcing conditions of the SWASH simulations and results of the validation against observed shoreline position in the Cala Millor beach.
Dates and forcing conditions of the SWASH simulations and results of the validation against observed shoreline position in Playa de Palma.
A total of four and three simulations have been carried out with the SWASH model for the Cala Millor and Playa de Palma beaches, respectively, in order to validate the model results with measurements of shoreline positions. The dates chosen for the validation correspond to dates in which the video monitoring provided good quality images, with them being also close to the dates when the bathymetry surveys were performed (they are listed in Tables 4 and 5). Wave makers were defined at the eastern boundary of the SWASH model domain in Cala Millor and at the southwestern boundary in Playa de Palma, in both cases with the SWAN wave conditions. These input wave conditions for the validation process are specified in Tables 4 and 5 for the indicated dates.
Observed and modelled shoreline changes for each case study have been
compared in Figs. 12 and 13 along the two beaches. Results show that the
modelled shorelines line up with observations in all cases. In Cala Millor
the agreement is better in the central part of the beach, while some
differences are found in the northern and southernmost sector. It is
important to remark that images obtained from the beach cameras are
increasingly uncertain with the distance from the cameras (Sect. 2.3 for
details). Therefore, part of the difference between the measured and simulated
shoreline at the ends may come from this error in measurements. In Playa de
Palma only the area between 39.51 and 39.53
Observed (black) and modelled by SWASH (red) shoreline positions in Cala Millor.
The RMSEs and biases between observations and model results have been calculated for each case and are listed in Tables 4 and 5. These statistics must be set in a proper context in order to evaluate how good the model performance is. To do so, the temporal variability of the shoreline position has been estimated as the standard deviation (cross-shore) at each alongshore position for which 10 coastlines measured from video monitoring have been used. In Cala Millor, higher variability is observed, calculated between April and May 2014, in the central part of the beach (mean value of 8.4 m) and lower towards the ends, with a mean value along the entire beach of 5.5 m. Figure 14 shows the shorelines simulated for the case studies (red lines), the corresponding measured shorelines (blue lines) and the variability of the shoreline (grey area), zoomed in around an area at the centre of the beach. In the case of Playa de Palma, the shoreline displays a cross-shore variability of 6 m in the area around the centre of the beach and lower at the extremes, with a mean value of 3 m, as calculated with observations between August and October 2014. The results are plotted in Fig. 15 in which again the central area has been zoomed in, in order to highlight the differences. Notably, the modelled shorelines are very similar to each other, because the forcing is also similar in the three case studies.
Observed (black) and modelled by SWASH (red) shoreline positions in Playa de Palma.
Modelled (red) and observed (blue) shorelines positions in Cala Millor with mean shoreline position (black line) and its standard deviation (grey shadow) zoomed in to the central sector.
Since the model performance for present-day climate conditions is considered
to be satisfactory, the same model set-up has been used to assess the
response of the shoreline under future climate change scenarios. Shoreline
changes were simulated for both mean conditions and extreme waves (the
latter being defined here as
Modelled (red) and observed (blue) shorelines positions in Playa de Palma with mean shoreline position (black line), its standard deviation (grey shadow) and the resolution of the pixels of the cameras (orange shadow).
Changes in the cross profile in Cala Millor
Future projected changes in shoreline have been evaluated assuming that the present-day beach profile remains constant. In order to check the limitations of this assumption, we have run a numerical one-dimensional model capable of estimating profile changes under different mean sea level conditions. The model used here is PETRA (González et al., 2007), and it has been run for the central profile of each beach under the conditions of no sea level rise and 0.5 and 0.9 m of sea level rise and wave mean regime. The results of the model are plotted in Fig. 16 for both beaches, zoomed in to the nearshore sector where the largest changes are expected. Profile changes are, at most, 20 cm under the highest sea level rise of 0.9 m; that is, in these environments profile changes due to sea level rise are of the order of sandbar formation and mostly eroding the berm. We therefore have considered the variations in the beach profile to be negligible and the assumption of constant beach profile to be reasonable in this context.
Loss of aerial beach (defined here as the landward migration of the shoreline averaged over the entire beach) for both the mean and extreme conditions expected under climate change scenarios in Cala Millor (in m). For the extreme conditions, the maximum loss is also quoted.
Present-day shoreline position (in black) and landward migration (in red) in the worst case scenario (mean sea level rise under RCP85 and extreme wave conditions) by the end of the 21st century in the Cala Millor beach.
Present-day shoreline position (in black) and landward migration (in red) in the worst case scenario (mean sea level rise under RCP85 and extreme wave conditions) by the end of the 21st century in Playa de Palma.
Loss of aerial beach (defined here as the landward migration of the shoreline averaged over the entire beach) for both the mean and extreme conditions expected under climate change scenarios in Playa de Palma (in m). For the extreme conditions, the maximum loss is also quoted.
A second assumption in our climate change simulations is that the beach
shape remains unchanged under future conditions. This means that we consider
a constant direction in the mean wave energy flux. Thus, any redistribution
in the alongshore sediments is neglected in front of the hydrodynamic
response to increased mean sea level. The present-day modelled coastline has
been used as a reference to assess the changes under climate change
scenarios. The loss of aerial beach, defined here as the landward migration
averaged over the entire beach, is indicated in Tables 6 and 7 for each
simulation and for the mean and extreme conditions expected under climate change
scenarios. For the extreme conditions, the maximum loss is also listed. In
addition, Figs. 17 and 18 illustrate the maximum change in the shoreline
position obtained for Cala Millor and Playa de Palma (corresponding to
extreme wave conditions under the RCP85
Since projected changes in
This paper has investigated the capabilities of state-of-the-art numerical models to reproduce the changes in the shoreline position in the Cala Millor and Playa de Palma beaches. These two case studies were selected for two main reasons. First, they are representative of many other anthropized beaches in the Balearic Islands (and of many other beaches of the Mediterranean Sea): they are beaches located in urbanized areas, backed by walls, and therefore with limited possible landward migration of the shoreline. Second, these two sites are part of the beach monitoring programme carried out by SOCIB, and, consequently, a wide and complete set of observations is available, allowing the validation of the numerical models against measurements. Furthermore, the two beaches are exposed to offshore wave conditions from different directions and different wave heights, with Playa de Palma being located inside a bay and Cala Millor facing the open sea.
Much effort has been devoted to the validation of the model set-up to ensure
that the chosen combination of SWAN–SWASH models is able to reproduce the
shoreline variability within a reasonable accuracy. In both cases, modelled
and observed
Regarding the projections of the shoreline changes under climate scenarios of sea level and wave climate, a major assumption of our study is that the morphology of the beach will not change in the future. That is, both the beach shape and the profile will be the same under the climate conditions at the end of the century. It is well known that beach profile evolves in response to storms, moderate wave conditions and sea level rise causing changes in the beach morphology (e.g. erosion followed by recovery episodes, see Short, 1996; Simeone et al., 2014; Smallegan et al., 2016; Davidson-Arnott et al., 2002). It has also been demonstrated that the changes in the beach profile play a smaller role in the shoreline retreat due to sea level rise and waves. On top of the above reasons, numerical approaches reproducing the long-term morphological response of the beach are still very limited (e.g. Ranasinghe et al., 2012).
Under the assumptions outlined above, we have found that the retreat in the future shoreline at both sites, Cala Millor and Playa de Palma, are primarily a consequence of waves acting onto a higher mean sea level. It must be mentioned that changes in the wave climate are small and the impact of extreme waves increases mostly because they are projected to occur concurrently with higher sea levels. The results indicate that the beach regression varies between 7 and 24 m along Cala Millor and between 7 and 21 m in Playa de Palma, depending on the climate change scenario considered. This loss is further exacerbated under moderate (return period of 10 years) storm conditions, which may induce a temporary flooding reaching over 49 m in Cala Millor and 30 m in Playa de Palma, thus likely overtopping the walls of the promenade. The Playa de Palma coastal retreat is lower than in Cala Millor due to the steeper slope of the beach profile. As pointed out above in the introduction, the approach proposed here does not consider beach erosion, which means that the above estimates are conservative and could be biased low if erosion acts by removing beach sediments and accelerating aerial beach loss (Brunel and Sabatier, 2009).
Playa de Palma and Cala Millor, like many other typical urban Mediterranean beaches, are subject to high touristic pressure, especially during the summer season, and thus concentrate valuable assets and infrastructures. Since tourism constitutes the main economic activity of a large fraction of the region, the social, environmental and economic impacts of future sea level rise are anticipated if no adaptation measures are implemented.
The data used to validate the methodology (observations from shorelines and buoys) are freely available through the SOCIB data repository. The bathymetries are provided by SOCIB upon request. The results of the present study will also be provided upon request to the corresponding author.
The authors declare that they have no conflict of interest.
This work is supported by the CLIMPACT (CGL2014-54246-C2-1-R) funded by the Spanish Ministry of Economy) and MORFINTRA (CTM2015-66225-C2-2-P). Alejandra R. Enríquez acknowledges an FPI grant associated with the CLIMPACT project. Marta Marcos acknowledges a “Ramón y Cajal” contract funded by the Spanish Government. We thank Puertos del Estado for providing deep water wave data from the SIMAR database. Topo-bathymetries and video-monitoring observations are part of the beach monitoring facility of SOCIB. The authors are grateful to Aimée Slangen for providing the data for the regional sea level rise scenarios. Edited by: Paolo Tarolli Reviewed by: three anonymous referees