NHESSNatural Hazards and Earth System SciencesNHESSNat. Hazards Earth Syst. Sci.1684-9981Copernicus PublicationsGöttingen, Germany10.5194/nhess-18-3211-2018Numerical and remote techniques for operational beach management under storm group forcingNumerical and remote techniquesMorales-MárquezVerónicaOrfilaAlejandroaorfila@imedea.uib-csic.eshttps://orcid.org/0000-0002-1016-8726SimarroGonzaloGómez-PujolLluísÁlvarez-EllacuríaAmayaContiDanielGalánÁlvarohttps://orcid.org/0000-0003-2966-3089OsorioAndrés F.MarcosMartahttps://orcid.org/0000-0001-9975-5013IMEDEA (UIB-CSIC), Mediterranean Institute of Advanced Studies, St. Miquel Marquès 21, 07190, Esporles, Balearic Islands, SpainICM, Institute of Marine Sciences, Passeig Marítim de la Barceloneta 37-49, 08003 Barcelona, Catalonia, SpainEarth Sciences Research Group, Department of Biology, University of the Balearic Islands, Ctra. Valldemossa, km 7.5, 07122 Palma, Balearic Islands, SpainETSI Caminos, Canales y Puertos, University of Castilla–La Mancha, Av. Camilo José Cela s/n, 13071 Ciudad Real, Castilla–La Mancha, SpainOCEANICOS Research Group, Universidad Nacional de Colombia
Cr. 80, 65-223 Medellín, ColombiaDepartment of Physics, University of the Balearic Islands, Ctra. Valldemossa km 7.5, 07122 Palma, Balearic Islands, SpainAlejandro Orfila (aorfila@imedea.uib-csic.es)3December201818123211322311June201810July201822October201818November2018This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/This article is available from https://nhess.copernicus.org/articles/18/3211/2018/nhess-18-3211-2018.htmlThe full text article is available as a PDF file from https://nhess.copernicus.org/articles/18/3211/2018/nhess-18-3211-2018.pdf
The morphodynamic response of a microtidal beach under a storm group is
analyzed, and the effects of each individual event are inferred from a numerical
model, in situ measurements and video imaging. The combination of these
approaches represents a multiplatform tool for beach management, especially
during adverse conditions. Here, the morphodynamic response is examined
during a period with a group of three storms. The first storm, with moderate
conditions (Hs∼1m during 6 h), eroded the aerial beach and
generated a submerged sandbar in the breaking zone. The bar was further
directed offshore during the more energetic second event (Hs=3.5m and 53 h). The third storm, similar to the first one, hardly
affected the beach morphology, which stresses the importance of the beach
configuration previous to a storm. The volume of sand mobilized during the
storm group is around 17.65m3m-1. During the following months,
which are characterized by mild wave conditions, the aerial beach recovered
half of the volume of sand that is transported offshore during the storm
group (∼9.27m3m-1). The analysis of beach evolution shows
two different characteristic timescales for the erosion and recovery
processes associated with the storm and mild conditions, respectively.
In addition, the response depends largely on the previous beach morphological
state. The work also stresses the importance of using different tools
(video monitoring, modeling, and field campaign) to analyze beach
morphodynamics.
Introduction
Evolution of sandy coasts at temporal scales (from minutes to years) has been
a topic of wide interest over the past decades since sandy beaches and dune
systems are the first natural lines of coastal defense against flooding and
erosion hazards while at the same time
being
attractive environments in terms of leisure activities and tourism economy
e.g., . The maintenance of these
areas is crucial for coastal defense and, at the same time, coastal
tourism seems to be one main target for beach erosion management
. For instance, in Spain, beaches represent only 0.01 % of the land surface, producing up to 10 % of its gross
domestic product . Beach management tends to be reactive
rather than proactive, solving the problems as they appear and without long-term planning.
Mitigation of coastal erosion and preservation of coastal areas represent
essential aspects of the Protocol on Integrated Coastal Zone Management in
the Mediterranean and are included in the objectives of most countries'
national regulations and policies in Europe . It
is already known that decisions concerning coastal management actions should
be made using the best available science, and new tools that take
into account physical, natural and socioeconomic characteristics of beaches
should be developed (; ). This makes it necessary to transfer the
knowledge from scientists to managers in an effective way, which is
a challenge today.
For coastal management it is crucial to have continuous measurements of waves
and shoreline .
One of the main issues in coastal erosion is the response of coastlines to
both individual storms and storm groups since the behaviors are quite
different (i.e., ; ; ; ;
;
; ). Single storms can result in significant beach erosion
within a few hours, whereas a sequence of storms can have a large and complex
impact on beach morphology, the final effects of which remain difficult to quantify
and to predict .
Storm waves and their associated water-level conditions are key drivers in shoreline dynamics. Shoreline response to successive storms can be
dependent on storm energy thresholds as well as on the feedback mechanisms
associated with the beach morphology and the presence or absence of former
impacts . There are many examples that have shown that
shorelines can recover relatively well from erosion triggered by storms and
that this recovery can be quick, from a few days or weeks to a couple of months . Therefore, the
resilience of beaches, understood as their capacity to recover from a major
storm, is related to the combination of sediment reservoirs, arrangement of
three-dimensional beach morphology (i.e., sand bar type and location, beach
slope) and the beach memory .
Study site location (a) and major features of Cala Millor.
(b, c) White dashed lines correspond to the bathymetric survey (isoline equal distance of 2 m); the yellow frame covers the bathymetry
area obtained by means of XBeach, and red lines correspond to the beach profile described in text. The bottom orthophoto is provided by the
Govern de les Illes Balears-SITIBSA (June 2008). Panel (b) shows the combination of multibeam bathymetric survey (green points)
and RTK–GPS survey for dry beach and very shallow submerged beach (red points). (c) Bottom type at Cala Millor.
Recent works, such as the study by , have shown that the observed
morphological change during consecutive storms has a strong dependence on the
initial beach morphology. These authors, departing from field experiments in
southern Portugal, stated that beach recovery did not maintain pace with
storm frequency and that storms can have a dramatic impact on erosion if
they occur in groups. In addition, other works dealing with storm impact on
shoreline dynamics in the Bay of Biscay (SE France) have suggested that
energetic events are probably not the only drivers of erosion processes
since significant beach erosion has been characterized under very calm
conditions following energetic events . In a similar way,
observations from a detailed field campaign involving daily beach surveys at
Truc Vert beach (Bordeaux, France) during a sequence of storms demonstrated
that a sequence of extreme storms does not necessarily result in cumulative
erosion, possibly because of the interplay among water levels, the angle of
wave approach and the preexisting beach face conditions .
The goal of this contribution is to study the effect of a storm group on the
morphology of a beach system and to advance a multiplatform methodology for effective decision-making regarding beach erosion management according to
the available data and numerical models. Here, we present the explanation of
temporal patterns of beach accretion and erosion under consecutive storm
events at an intermediate microtidal carbonate beach by using the dataset
available on the studied beach, high-frequency data on shoreline positions
and cross-shore profiles extracted from coastal video monitoring techniques,
real-time kinematic (RTK) and echo sounding surveys, concurrent hydrodynamic
measurements, and the use of numerical models widely validated in order to
fill gaps in the dataset.
Study area
Cala Millor is a semi-embayed beach 1.7km in length and ranging
between 15 and 30m in beach width. It is located on the
northeastern coast of Mallorca (western Mediterranean Sea, Fig. ). Sediments are mainly composed of well-sorted medium to coarse
biogenic carbonate sand with a grain diameter D50 between 0.3 and
0.6mm changing along the cross-shore distance, according to the
depth . The beach area is around 1.4km2 with a
bottom colonized by the endemic Posidonia oceanica meadow at depths
from 6 to 35m. This meadow increases bottom
roughness, reducing near-bed velocity and thus modifying the sediment transport
and increasing wave attenuation
.
From a morphodynamic point of view, Cala Millor is an intermediate beach with
a highly dynamic configuration of longitudinal sinuous-parallel bars and
troughs, presenting intense variations in the bathymetry related to sandbar
movement .
Tides are negligible (the tidal amplitude is less than 0.25m)
although other surge components such as those induced by wind or atmospheric
pressure can increase the sea level by up to 1m.
The beach is open to the east and, due to the semi-enclosed configuration, is
well exposed to waves from the NNE to the SE .
Significant wave height (Hs) at deep waters is usually below 0.9m with a peak period (Tp) between
4 and 7s,
although frequent storms account for 2% of time increase Hs up to 5m
with a Tp higher than 10s, with a return period of 1.5
years .
Cala Millor is one of the most important tourist resorts created on the
eastern coast of Mallorca – more than 60000 visitors during the summer
period – and has a long history of sand nourishment and coastal management
approaches .
Since November 2010 the Balearic Islands Coastal Observing and Forecasting
System (SOCIB) has been monitoring Cala Millor by means of coastal video
monitoring, moored instruments and a periodic program of beach profile and
sediment characterization . Along Cala Millor beach, over
short temporal scales, shoreline position changes are not always homogeneous
(Fig. a) and it is possible to appreciate some different
behaviors and responses to the wave climate. Cala Millor has experienced at
least 19 events with significant wave height at 25m in depth of over
2m between November 2010 and January 2017 (Fig. b). Some of these events are isolated storms (e.g., April 2013), while others
act in groups (e.g., January 2015). Figure a shows the
alongshore anomaly of shoreline distances for the period between November 2010 and January 2017. The correlation between beach face response and sea
conditions is not clear: there are storms that, even though Cala Millor is
not a pocket beach, give rise to apparent temporary rotation, whereas
others appear as a general shoreline advance or retreat. Nevertheless, from
the averaged alongshore shoreline width anomaly (Fig. c) a clear change in beach behavior since April 2014, just
after a group of storm events that will be analyzed below, can be inferred. Despite that the beach
eventually recovers the former alongshore width, a net
shoreline recession is observed.
In March 2014, just a few days before the storm group event, a field
experiment was carried out in Cala Millor in order to characterize the beach
morphology. This experiment produced detailed bathymetries, and beach profiles
were measured before the storms and wave recorders were also installed at
different depths. Later, in June 2014, another detailed
beach survey and bathymetry belonging to the SOCIB's periodic beach
monitoring program were carried out . Unfortunately, even though the April 2014 storm group seems to be critical for the beach width evolution, there
are no bathymetric data available immediately after the storms. Nevertheless,
the number of available data before and after the storm group impacts makes
this an opportunity to validate and generate numerical proxies that
contribute to unraveling the beach response to the storm group.
(a) Alongshore shoreline width anomaly at Cala Millor from November 2010 to January 2017.
Red colors indicate shoreline advance, whereas blue ones indicate shoreline recession. The dashed
black lines show the sea storm events larger than 2 m. (b) Wave significant height from a wave recorder
located at -17 m in the middle of the Cala Millor embayment. (c) Alongshore averaged shoreline width anomaly
at Cala Millor. The red arrows highlight the storm group event at April 2014.
Data and methods
This paper partially deals with datasets produced during the Riskbeach
experiment, performed by the SOCIB, the Mediterranean Institute for Advanced
Studies (IMEDEA) and the Institute of Marine Sciences (ICM-CSIC) in Cala
Millor from 17 to 26 March 2014. This
experiment was designed to study the response and recovery of an intermediate
beach to usual (1-year return period) storm conditions and the related
sediment transport processes and morphological changes. During the
experiment,
some instruments, detailed in Fig. , were installed in a central
section of the beach to obtain high-resolution sediment and hydrodynamical
data. In this paper we employ the wave and current recorder data (acoustic
wave and current meter, AWAC) moored at 25m in depth. Measurements are
completed with bathymetric surveys, sediment samples and video monitoring
products. After the experiment (just from 26 March) large waves
resulted in a significant morphological change of the beach, once the field
survey was finished and the echo sounding equipment was dismantled. To assess
the effects of these storms we combine numerical modeling with
video monitoring techniques to infer the beach profiles that help us to
understand the changes in the beach morphology before and after the storm
group.
Figures and summarize the approach developed in
this study, showing which data are from different instrumental approaches
(i.e., direct measurements from bathymetric and differential GPS–real-time kinematic (DGPS–RTK) surveys) and which
ones are inferred from numerical modeling and video images (indirect
measurements). According to Fig. 3, field wave, sediment and beach morphology
data, before the storm event, are required in order to start up numerical model
tools. The obtained results when field campaign data are available have to
be validated with field bathymetric data. The numerical model validation
ensures that the results obtained during the storm period are
accurate. In addition, the product acquired by video monitoring, once the
cameras have been calibrated with field bathymetric data, will provide the
“proxy” of the measured data. Results will be organized in two sections:
first, profiles obtained by direct methods and, second, the results related
to the use of these data sources for unraveling the beach erosion and
recovery timescales.
We have wave mooring data that we use, through statistical analyses, in order
to describe the wave climate and the storms that occurred in Cala Millor. We
also have bathymetric data, obtained with DGPS–RTK and echo sounding beach
surveys. With the wave climate parameters, the bathymetric initial data of
the beach and the grain size distribution (taken with sediment sampling), we
can simulate the situation of the Cala Millor beach in the XBeach model. The
obtained results must be validated with field bathymetric data during the
period of time that we can recollect them. When the field campaign is
impossible, we will be able to know the conditions of the beach thanks to the
simulation of XBeach (once it has been validated). In addition, we can
have another source of data, the video monitoring. Through image analysis
we can obtain the beach profile. Once this tool is calibrated and
validated against the model and field data, it will act as an independent technique in
order to know the state of the beach.
(a) Workflow of the approach followed in the study. (b) Calendar showing the date for
the samples used in the study.
In this way, we can obtain an approximation of the sediment mass balance and
the erosion and recovery timescales of the beach.
Wave conditions
Offshore wave conditions (significant wave height, Hs, peak period,
Tp,
and wave direction at 50 m in depth every 3 h) are obtained from a
reanalysis of a 60-year wave model output produced by the Spanish Harbor
Authority (http://www.puertos.es/es-es/oceanografia/Paginas/portus.aspx, last access: 29 November 2018). The
mean Hs for the period of study is 0.9m with a mean peak period
(Tp) of 6s. During the experiment (17 to 26 March 2014), wave conditions were measured with an AWAC system
moored at deep waters (25m in depth) in the central part of the beach.
Deep water wave conditions show three storms during the period of study
(Fig. ). Here we define storm as sustained wave conditions
during at least 6 h with Hs>1m. suggested
this threshold as the condition required to generate a significant impact
along beach morphology and sediment properties. When such an event is not
isolated but becomes a succession of events, we refer to it as a group of
storms. These episodes can cause larger damage on the beach with smaller
wave heights since the beach does not have enough time to recover its
initial morphodynamic state. The experiment started on 17 March
after a period of moderate conditions with Hs close to 1 m that did not
result in significant morphological changes. The first storm, S1 (see Fig. a), occurred on 26 March, just after the
instruments were moved away, with a maximum significant wave height
Hs=1.5m and Tp=9.9s from the SE (Fig. c)
and a duration of 7 h. The second storm, S2, beginning on 28 March, lasted 53 h and peaked during the evening of 29 March
with a maximum Hs of 3.4 m and Tp of 10.4 s. The
estimated return period for the S2 storm is around 1.2 years. Nevertheless, the
return period just refers to the significant wave height threshold, despite
that
the storm duration and persistence of wave height was 38 h with Hs>2m, which
is unusual. Wave conditions started to build up again on 2 April 2014 after a short period of relatively small waves
(Hs<1m). The third storm, S3, from 2 to 3 April, peaked 4 days after the former storm with maximum
Hs of 1.3m and Tp
of 7.8s (Fig. a and b) during 48 h. The following 2 months were characterized by mild conditions, which
will be used to study the beach recovery after the storm groups.
Beach morphology
The topographic surveys were performed from 17 to 26 March
using a DGPS–RTK with submetrical resolution (having a
horizontal accuracy of around 8 mm and a vertical accuracy of around 15 mm) for
both the aerial (the area located over the mean sea level) and the submerged
beach (from deep waters up to 1m in depth). Additionally, for
submerged beach, bathymetric data were obtained using a Biosonics DE-4000
echo sounder with a DGPS, which allowed dense mapping from 0.5 to 10.m in depth. On 17 March, an initial bathymetry was
acquired. In addition, nine cross-shore profiles were taken daily between
18 and 26 March (see Fig. ). An
additional bathymetry was performed on 12 June for control
purposes. Elevations were referenced to the Balearic Islands ordinance survey
mean sea level and the horizontal position referenced to the UTM coordinate
system . These data cover the area between the boulevard
sea wall and the lower shoreface (ca. 8 m in depth).
(a)Hs (m) at 25m in Cala Millor between
15 March and 14 April 2014. (b)Tp (s). (c) Wave direction. The blue shading
shows the period corresponding to the storms. Vertical red dotted lines indicate the initial bathymetry
obtained while dashed dotted lines indicate the dates when cross-shore profiles were measured. Vertical
green dotted lines state the day when the model was validated using the corresponding shore profiles.
Vertical red lines show the date when bathymetry inferred from XBeach was used for comparison among storms.
Sediment characteristics
Sediment samples were collected from aerial beach (+2m) to 6m in depth at one of the central cross-shore transects (profile 07,
Fig. ). Sediments in the aerial beach and up to 1m in depth
were collected by dragging a plastic bag inserted in an oval
metallic frame on the bottom with a vertical penetration of about 2–4 cm, and for
greater depths we threw a clamshell bucket from a boat. The weight of
samples ranged from 200 to 500g. After collection, samples
were
soaked in fresh water for 4 h and drained before being dried for 24 h. Sediment was analyzed using a laser granulometer and grain size
obtained through the method described by using GRADISTAT
software .
(a) Time stack image for 19 March at 09:00 UTC + 1 for the central camera. The abscissa
corresponds to the cross-shore direction and the ordinate for the time. (b) Reconstruction for the same
date assuming a constant wave height using the Fourier mode of the detected period (i.e.,
cos(ϕ(x,fw)-2πfw)).
Video monitoring
Coastal monitoring using video images is a practical and widely used
technique since the advent of Argus . Since then, several
systems (Cam-era, Horus, Cosmos, Beachkeeper, Ulises, etc.) mimic the Argus
philosophy with the objective of providing continuous measurements of coastal
processes in an unsupervised and autonomous procedure. Here, we use one
such approach, SIRENA/Ulises , which has been
operating since 2009 in Cala Millor. The system is composed of five
charge-coupled device (CCD) cameras connected to a server acquiring daily
images . The five cameras encompass an alongshore distance
of around 1.7km, largely including the monitored area. We use the
time stacks, consisting of pseudo-images built with all pixel observation
taken at 7.5Hz at a predefined cross-shore transect during the
first 10 min of each hour, to infer the beach profile with the
inversion of the wave dispersion relationship. The underlying idea in the
inversion method is that the wave speed for progressive waves can be measured
from its visible signature at consecutive snapshots to estimate the
bathymetry using linear wave theory at the observed cross-shore transect
.
Adopting the linear wave theory, the wave celerity c for shallow water
waves (kh<π/10, where k is the wave number and h the local water
depth) is
c2=g⋅h,
where g is the gravitational acceleration.
Time stack images (Fig. a) are preprocessed to convert the RGB
data to a tractable intensity matrix. First, original time stacks, with
spatial and temporal dimensions (nx,nt)=(650,4500), are resampled by
removing pixels at the aerial beach as well as at the outer domain
(intermediate waters) where each pixel corresponds to large distances that
are
not useful for measuring hydrodynamic processes. Final images have spatial and
temporal dimensions of (n^x,nt)=(460,4500). A quadratic filter
with a time window of 3s is applied to smooth the intensity
timewise, and for each cross-shore position the temporal mean is subtracted.
From the intensity matrix I(x,t), the wave frequency is obtained as the
main component of the fast Fourier transform (FFT) in the time domain, which is constant along the
cross-shore dimension. A FFT is performed for each of the 460 cross-shore
time series and the wave frequency, f, found as the mode of all resulting
peaks (Fig. b).
Once f is known, the spatial component of the wave phase function (Fig. b) is evaluated following as
ϕ=arctanIm(I(x,ω))Re(I(x,ω),
and the wave
celerity is obtained as
c=2πf∂ϕ/∂x.
The beach profile is finally obtained from Eq. ().
Numerical modeling
Morphological evolution is assessed using the XBeach (eXtreme Beach behavior)
model , which resolves the hydrodynamic processes of both
the short waves (refraction, shoaling and breaking) and the long waves
(generation, propagation and dissipation). We use version 4920 for 64
bits. The model has been extensively validated with
laboratory data as well as with field observations to study the morphological
response of beach and sandy dunes, mostly under storm conditions. Here, we
apply the model to analyze the storm group period with the surf beat mode that
resolves the 2-D averaged equations.
The initial bathymetry (of 17 March) is discretized in an
orthogonal rectangular grid evenly spaced with a resolution of Δx=7.44m in the cross-shore direction and with Δy=15.86m in the alongshore direction. Hourly JONSWAP spectra, generated
through the measured data with the AWAC at 25m in depth, are
propagated from the seaward boundary to the coast for the period of 17 March
to 8 April, after S3 (summing up 528 runs of 1 h of real time). The seaward boundary is imposed as the absorbing–generating
(weakly reflective) boundary condition and the lateral boundaries as
Neumann type, for which the alongshore gradients are set to zero. The incoming wave
directions in almost all simulations come from the east perpendicular to the
shoreline (Fig. c).
Sediment characteristics measured before the experiment (D50 and
D90) are interpolated along the sampled profile and then they are
extrapolated alongshore according to the depth of each grid point. The
dimensionless porosity of the sediment is set to 30% and the density
considered to be 2650 kg m-3.
Results and discussionBathymetry extraction from model and video images
The analyses based on XBeach and on time stacks are used to obtain the
bathymetry and beach profiles to address changes in sediment mass balance.
The initial bathymetry was measured before the storms (17 March).
The numerical model is run for the period between 7 March and
8 April, as stated. For each day a model-derived bathymetry is
obtained and nine profiles are extracted at the same locations of the measured
cross-shore profiles. Table shows the error parameters between
measured profiles and the XBeach modeled profiles from 17
to 26 March. The computed error parameters are the correlation
coefficient (R2), the scatter index (SCI) normalized with the maximum of
the RMS of the data and the absolute value of the mean of the data, and the
relative bias (RB) normalized in the same way as the scatter index, used in
:
R2=Cov(m,c)σmσc,SCI=rmsc-mmax(rmsm,|〈m〉|),RB=〈c-m〉max(rmsm,|〈m〉|),
where m is the field data and c the modeled results.
Error statistics for the simulated profiles by XBeach
compared with the measured profiles during Riskbeach.
The profiles derived from the model compare well with the measured ones from
the aerial beach (h=2m) to the depth of closure (h=-7m,
according to the , formulation). The minimum R2 is
99.31%, the maximum SCI is 0.11 and the maximum RB is 0.03 in the
central profile. Therefore the modeled bathymetries (XBeach) can be
considered an efficient and reliable tool for unraveling the beach storm
effects.
As an additional source of data, a cross-shore seabed profile in the
SIRENA/Ulises central camera (Fig. ) is obtained following the
above-described methodology. Table compares the cross-shore
profiles derived from time stacks against the instrumental measured profiles
for the period between 19 March and 26 April (there
are not time stacks available for 17 and 18 March).
Since the time stack is defined in a cross-shore transect located between
profiles 07 and 09, in situ measurements are interpolated daily to the
time stack transect for comparison purposes. Error parameters from in situ
measurements and from video images are shown in Table , with a
R2 value of 97.95%, SCI of 0.14 and RB of 0.04. The largest
differences tend to be located at deep profile positions where the model is
known to perform worse since the accepted assumption on Eq. () is only
valid for shallow waters. In general, there is a good agreement between
both sets of data.
(a) Cross-shore transect defined for the time stack image on camera no. 3. The figure shows the
original image in the (u,v) ≡ pixel coordinate system. (b) The same after rectification in
the (x,y) ≡ UTM coordinate system. (c) Resulting time stack for 19 March at 10:00 UTC + 1.
Error statistics for the estimated profile from time stacks
compared with the measured profiles during Riskbeach.
R2 (%)SCIRelative bias97.95±1.40.14±0.070.04±0.06
Both comparisons, XBeach vs. instrumental and time stack vs. instrumental,
present the same order of magnitude as that obtained in .
This allows us to compare beach sediment mass balance before and after the
storm group as well as during the longer period of calm after the storms
using different datasets and different techniques. This would allow a correct
management of the beach, avoiding unnecessary engineering works between
tourist seasons.
Beach morphological response to storms and recovery
Although the individual storms are not exceptional in terms of intensity,
their occurrence as a storm group has a significant imprint on the beach
morphology. The initial bathymetry, performed before the storm group (on
17 March 2014), shows a sinuous-parallel and patchy bar at
-1m and a cross-shore profile with attenuated secondary forms with
a mean slope of 2.6 %, whereas the bathymetry obtained for 8 April 2014 from XBeach shows a marked dissipative configuration.
This is consistent with the obtained timex images through the SIRENA video monitoring
station (see Fig. ). The seabed variation after the storm group
(S1, S2 and S3, in Fig. a) is presented in Fig. a. This morphological change is obtained as the difference
between the bathymetry obtained with XBeach after storm S3 (8 April) and the initial bathymetry. The effect of consecutive storms is to
mainly erode the aerial beach, mobilizing the sediment from the berm to
depths of
between -1 and -5m, forming a bar (around 100m
from the shoreline, Fig. a). The sediment mobilized to the bar
is around 2.69×104m3 and comes from the aerial
beach, where the volume loss is estimated as 3.01×104m3. This approximation of the sediment transport is calculated as
the variation in depth at each spatial grid point between the initial
bathymetry on 17 March and the simulated bathymetry for 8 April. All grid points are finally summed to obtain an approximated
value of the sediment transport. The same methodology is applied to determine
the sediment volume during the recovery period, but in this case the initial
bathymetry is simulated by XBeach on 8 April and the final one
is the one measured during 12 June. The redistribution can also be
examined by analyzing the profile at the center of the beach using
video images. Figure a shows the beach profile change using
video images from 19 March (the selection of 19 March is
made since no images are available for the previous days) to 8 April
(after S3).
Timex images with dates referred to in each image. Notice the intermediate configuration
with a sinuous parallel bar along the coast (ca. 180 m) for 17 and 27 March
and the dissipative scenario without a bar for 8 April.
Depth variation estimated from XBeach and from measurements. (a) Bottom variation during the storm
group (17 March to 8 April). (b) Bottom variation for the period of calms
(8 April to 12 June).
We analyze the
differences between the initial bathymetry (17 March 2014,
preceding S1) and the bathymetries after storms S1, S2 and S3 (28 March, 1 and 8 April, respectively) obtained
from XBeach. Figure shows the differences, i.e., the impact of
each of the storms. The first storm, S1, with moderate Hs and short
duration, produces erosion at the beach face (volume loss of 1.18×104m3), accumulating large volumes of sand between -1 and -2m (not shown in Fig. ). During the
second storm, S2, which is the most energetic, the beach face suffers a new
episode of intense erosion, with depth variations between 1 and
1.5m and movement of the bar offshore (Fig. b). The gain
in volume in the bar zone is around 1.51×104m3.
Finally, the third storm (S3), with moderate wave heights but with long
duration, continues eroding the aerial beach with little change in the
submerged beach (Fig. c). This indicates that a sequence of
storms does not necessarily result in cumulative erosion, supporting previous
findings by and . The eroded sediment that
is transported offshore but not lost has the capacity to modify the
cross-shore morphology and promote the wave attenuation contributing to the
sediment transport feedback.
The three-dimensional beach response to three successive storms highlights
the importance of the storm duration in the sedimentary budget. This has been
recently addressed in different studies among others and particularly for the Mediterranean by
. This scenario fits with the usual “storm–post storm”
behavior model and highlights the need for
more research, especially in the physical description and numerical modeling,
in order to improve our knowledge of the characterization of the temporal
scales associated with the beach sedimentary budget. Here, we found evidence
that recovery times, jointly with antecedent morphology, play a crucial role
in shoreline and beach dynamics as stated by or
.
After the S3 storm the beach experienced relatively calm conditions. A new
bathymetry was performed on 12 June 2014, allowing us to address the
behavior of the beach during this period. Figure b shows the
differences between the bathymetry on 12 June and the post-storm
bathymetry obtained with numerical modeling for 8 April 2014.
As can be seen, 2 months after the storm group, there is an opposite scenario. The
sand reservoir below feeds up the shoreface again but also redistributes
sediment along the beach at different depths. The sand volume recovered at
the aerial beach during this period is 1.58×104m3,
which
is half of the volume lost during the storm period. This behavior is
confirmed from the analysis of the beach cross-shore profile obtained from
the time stack video image. Figure b shows the difference between
the summer profile (12 June 2014) and the beach profile after
S3 (8 April 2014), supporting a recovery of the upper part of
the beach.
The proposed approach aims to be a tool to assist in beach management,
especially during adverse conditions when field surveys are not possible.
The combination of numerical models, video monitoring and in situ data
provides alternatives for the lack of data, especially during adverse
conditions. This approach follows the change in the paradigm in ocean studies
in which multiplatform approaches are being developed across the globe in order
to fill spatial and temporal gaps in the measured time series.
On the studied beach, the results show that the beach is able to recover the
lost sediment on a larger scale than the erosion and that it is crucial to know
the beach configuration at any time in order to know its evolution in front-specific wave climate episodes.
Depth variation estimated from bathymetry inversion of the time stack during storm conditions;
(a) between 8 April and 20 March (storm conditions); (b) between 12 June and 8 April (calm conditions).
Depth variation estimated from XBeach and from measurements. (a) Bottom variation
between 17 and 28 March (storm S1). (b) Depth variation between
28 March and 1 April (storm S2). (c) Depth variation between
1 and 8 April (storm S3).
Conclusions
The response of a low-energy microtidal beach in front of storm groups on timescales related to processes of beach erosion and accretion is studied. For
this purpose, different techniques and approaches including DGPS–RTK and
bathymetry surveys, modeling, and video monitoring are combined. The
observations confirm that the previous morphological conditions are crucial
for controlling the sediment exchange and the morphological response of the
beach.
Focusing on the effect of individual storms, the first storm mobilizes sand
mostly from the aerial area, generating a parallel bar at depths of ∼1m and modifying the beach profile from near reflective to more dissipative.
The effect of S2, lasting for more than 30 h, is to mobilize a large
volume of sediment, redistributing the profile along the whole beach and
generating a large submerged sandbar at depths of ∼-2.5m (∼100m from the shoreline). This profile is very efficient
in protecting the beach from the third storm, which has a duration of 48 h, with the sediment mobilized during this event being almost negligible. The
largest changes in sediment mobilization occur in the transition from the
reflective to the dissipative states, when the beach adjusts its profile to
the incoming wave conditions. The combined effects of this storm group
confirm that in low-energy systems such as the one analyzed here, it is necessary
to know the previous morphological state in order to properly assess the new
beach conditions.
Results highlight the different well-known temporal scales for erosion
and accretion in low-energy systems. While offshore sand migration is
produced at storm timescales, the onshore sediment transport has a much
slower characteristic timescale. In particular, a group of relatively
energetic storms has the capacity to generate significant erosion in 3
days. Despite the moderate conditions and the lack of storms during the next
2 months, only half of the sediment is recovered. In this study the recovery
of the beach is not documented, either in sediment mass balance or in
shoreline width. Nevertheless, from Fig. a it can be seen
that the aerial beach remains relatively stable and the
beach width slightly increases at the end of 2014. Then in December 2014 and early January
2015, a new set of storm group events affect the beach, and since then the
beach shoreline width has not recovered to former conditions, despite some advance in shoreline position.
Time recovery after storms is a key issue for local beach managers who are
pressed by tourism stakeholders to nourish the beach after energetic
processes in order to reach the quality standards required by beach users. The
combined use of remote-sensing data, in situ observations and numerical
models should already be integrated into management tools to make short-term
decisions, such as those concerning beach nourishment, based on reliable physical data.
All data are accessible from http://apps.socib.es/beamon/ () and
http://thredds.socib.es/thredds/catalog/mooring/waves_recorder/mobims_playadepalma/L1/2014/catalog.html ().
AO conceived the idea of the study with the support of VM, LGP, GS and MM;
AO, GS and VM developed the methodology with the support of AA and DC; VM
produced the results with the support of AO and DC; AA, GS and LGP
analyzed the results with the support of AO and VM. All authors contributed to
writing the paper.
Alejandro Orfila is a member of the editorial board of Ocean Dynamics
and Frontiers in Marine Sciences. Marta Marcos is a member of the editorial board of
Frontiers in Marine Sciences.
Acknowledgements
This work has been possible thanks to the IMEDEA–SOCIB collaboration. Authors
acknowledge financial support from MINECO/FEDER through projects
MORFINTRA/MUSA (CTM2015-66225-C2-2-P) and CLIMPACT (CGL2014-54246-C2-1-R). Verónica Morales-Márquez is supported by an FPI grant from the Ministerio de
Economía, Industria y Competitividad of the Spanish government associated
with MORFINTRA/MUSA. Daniel Conti is supported by a PhD fellowship (FPI/1543/2013)
granted by the Conselleria d'Educació, Cultura i Universitats from the
Government of the Balearic Islands co-financed by the European Social Fund.
The authors thank the four anonymous referees for their valuable support. Edited by: Maria Ana Baptista
Reviewed by: four anonymous referees
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