Morphological Evolution of the Sandspit at Tortugueros Beach, Mexico

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‘This is the peer reviewed version of the following article: Escudero, M., Silva, R., Hesp, P. A., & Mendoza, E. (2019). Morphological evolution of the sandspit at Tortugueros Beach, Mexico. Marine Geology, 407, 16–31. https:// doi.org/10.1016/j.margeo.2018.10.002 which has been published in final form at https://doi.org/10.1016/j.margeo.2018.10.002

Morphological evolution of the sandspit at Tortugueros Beach, Mexico

M. Escudero, R. Silva, P.A. Hesp, E. Mendoza

PII: S0025-3227(18)30333-5 DOI: doi:10.1016/j.margeo.2018.10.002 Reference: MARGO 5858 To appear in: Marine Geology Received date: 30 July 2018 Revised date: 25 September 2018 Accepted date: 8 October 2018

Please cite this article as: M. Escudero, R. Silva, P.A. Hesp, E. Mendoza , Morphological evolution of the sandspit at Tortugueros Beach, Mexico. Margo (2018), doi:10.1016/ j.margeo.2018.10.002

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Morphological evolution of the sandspit at Tortugueros Beach, Mexico

M. Escudero1, R. Silva1, P.A. Hesp2, E. Mendoza1

1Engineering Institute, National University of Mexico, Mexico City, Mexico [email protected]

[email protected] (Corresponding author)

[email protected]

2 Beach and Dune Systems (BEADS) Lab, College of Science and Engineering, Flinders

University, Bedford Park, South Australia 5042

[email protected]

ABSTRACT

Sand spits occur around the world with different shapes, dimensions and dynamics. While usually considered non-developable coastal features, development has taken place in several locations around the world, and because spits are often very dynamic, a better understanding of their behaviour and evolution is useful. Understanding their stability and morphological cycles can be used as a measure of the health of nearby beaches. The inter-annual and decadal morphological evolution of the beach spit at Tortugueros, on the Yucatan peninsula, Mexico, a re-entrant bay on the Isla del Carmen barrier system, is examined. Digitized information from satellite imagesACCEPTED and aerial photographs, MANUSCRIPT covering a 31 year period, was used to compare the shoreline evolution with numerical results. The method used consists of the estimation of the wave breaking conditions and the evaluation of the cross and longshore energy flux. The time-averaged wave energy flux allows the estimation of the evolution of those

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morphological features. The shoreline changes are very dramatic, with rates of accretion up to 160 m yr-1 and erosion up to 196 m yr-1. The results of the comparative analysis show that Tortugueros beach is a resilient system in dynamic equilibrium, governed by the combination of the short period local marine climate of the area and large-scale weather cycles related to the El Niño and La Niña phenomena. The analysis presented in this paper is valid to describe the functioning and resilience of dynamic beach systems elsewhere, where the wave climate is known, based on the wave energy flux of the breaking waves.

Keywords: Barrier spit, satellite images, cyclic behaviour, wave energy flux, Tortugueros beach processes, Mexico, Laguna de Terminos

1. Introduction

Successful coastal management requires knowledge of the underlying processes of shoreline variability in the medium term, and in inter-annual and decadal time scales (Camfield and

Morang, 1996; Oost et al., 2012). An analysis of the extremely dynamic morphology of sandy barriers or spits parallel with the shore and at various orientations to it is considered here. A spit is generally an elongated supratidal coastal barrier, composed of sand, gravel or mixed sediment; and spatially an extension or progradation from the mainland, or from an outcrop or island (Shepard,ACCEPTED 1952; Oertel, 1985; Otvos, MANUSCRIPT 2012; Randazzo et al., 2015). Spits mainly occur in areas with a relatively small tidal range and an abundance of siliceous-clastic sediments, according to Dean and Dalrymple (2004) and Davis and Fitzgerald (2004), but are also found in other tidal regimes (e.g. Taaouati et al., 2015; Kelley et al., 2015). Cross-

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shore and longshore sediment transport affects the evolution of spits, sometimes in a very complex manner (Nagarajan et al., 2015). They are common in areas dominated by oblique waves and longshore transport, and often display considerable variation alongshore in erosion/accretion trends, particularly where there is a limited sediment supply and the spit is eroding at the proximal end and accreting at the distal end (Zenkovich, 1967; Carter, 1988).

In form, spits can vary from a relatively simple, single arc to a highly complex, crenulated, irregular barrier. The former tend to prograde, or accrete, by the addition of recurved bars and beaches on the distal point (Zenkovich, 1967; Hequette and Ruz, 1991). The most dynamic spits may be made up of multiple, separated spits or spit segments (multiple fingers), which translate landwards and migrate or extend alongshore (see e.g. Figure 198, p.413, in

Zenkovich, 1967). As this type of spit migrates, breaching may occur (Carter, 1988) and the spit break up into islands, to later become beaches attached to the mainland. The spit investigated here, at Tortugueros beach, on the Gulf of Mexico, is this type of complex, dynamic spit.

Landforms found on spits may include overwash fans, flats and terraces (e.g. Canadian

Beaufort Sea; Hequette and Ruz, 1991; Skallingen, Denmarck, Nielsen and Nielsen, 2006;

Danube delta spits, Vespremeanu-Stroe and Preoteasa, 2015), wave built or storm beach ridges (Dungeness spit, Washington, USA), foredune and relict foredunes (also commonly termed beach ridges)ACCEPTED (e.g. El Rompido spit, MANUSCRIPT Spain, Ojeda Zujar and Vallejo Villalta, 1995;

Gallego-Fernandez et al., 2006; Arcay spit, France, Allard et al., 2008, Dehouck et al., 2013;

Feddet spit, Denmark, Kabuth and Kroon, 2014), or a variety of other dune types, foredune- blowout complexes, parabolic dunefields and transgressive dunefields (e.g. Farewell Spit,

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NZ, Tribe and Kennedy, 2010; the eastern shore spit of Qinghai Lake, China; the Ebro delta spits, Spain, Santalla et al., 2009; Ginst spit, west Wales, Thomas et al., 2014), or a combination of these (e.g. Vejers spit, Denmark, Nielsen et al., 1995; St Joseph Point spit,

USA, Bitton and Hesp, 2013).

Spit dynamics are strongly linked to wave energy and/or sediment supply. Hequette and Ruz

(1991) found that the highest retreat rates for spits in the Beaufort Sea correlated with those with the lowest sediment supply. Weidman et al. (1993), identified five cycles of accretion and breaching on a spit at South Beach, USA, forced by interrelated morphological, tidal and climatic factors. Spits may undergo significant changes in configuration when there is a change in the predominant or storm wave field (Watanabe et al., 2005; Thomas et al., 2011).

A mean spit retreat rate of 1.7 m yr-1 was found by Hequette and Ruz (1991). Longshore extension rates can be exceptional (e.g. 22 m yr-1 for the Arcay spit, France; Allard et al.,

2008; Dehouck et al., 2013).

From a review of the literature and examination of world coasts using Google Earth, it appears that research on spits has concentrated on simple spits, with very few, rather limited studies on dynamic, complex spits, to the authors’ knowledge. Similarly, there have been few studies on spit beach behaviour which combine numerical modelling and satellite and aerial imagery such as Allard et al. (2008) who used a dataset of more than 100 years of imagery and numericallyACCEPTED estimated wave climate to MANUSCRIPTunderstand the rhythmic development of Arçay

Spit in France, and Thomas et al. (2014) who studied the morphodynamic evolution of Ginst

Spit in West Wales from 63 years of imagery and wave models. In this paper, digitized information from satellite images and aerial photographs, covering a 31 year period, were

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used in order to compare the shoreline evolution of the spit at Tortugueros beach, Mexico, with numerical results. The method proposed in this paper consists of the estimation of the wave breaking conditions, the evaluation of the cross and longshore energy flux in this zone and, using the time-averaged wave energy flux, the evaluation of the evolution of the morphological features related to the spatial and temporal wave climate conditions.

2. Study area

Tortugueros beach, a re-entrant bay about 1 km long, is located in the middle of Isla del

Carmen, a barrier island, on the southern coast of the Gulf of Mexico (Jimenez-Orocio et al.,

2014; Fig. 1). It is an indentation formed at a point where the larger barrier system shifts significantly landward for a short distance. Several studies have reported the existence of serious erosion problems on the coast of Isla del Carmen (Marquez 2008, Torres et al., 2010,

Escudero et al., 2014) without examining the significant and rapid morphological changes experienced at this beach from 1985 to 2016, as shown in Fig. 2.

Figure 1. Location of the study area: (a) General location map; (b) Detailed study area; (c)

Aerial view of Tortugueros beach- photos taken on the beach on 29 April 2012.

Figure. 2. Morphological evolution of Tortugueros beach from 1985 to 2016. Very rapid changes in the ACCEPTEDposition and size of the bars andMANUSCRIPT spits occur over time with subsequent large- scale changes in the beach widths. The black dots mark the same reference points in all photographs.

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The coastal climate of the area is defined by three main seasons of the year (Yañez- Arancibia and Day, 2005): the ‘rainy’ season (from June to September), when tropical cyclones or hurricanes dominate; the ‘Nortes’ season (from October to February), which is the period when the storms locally known as ‘Nortes’ are produced (cold fronts, or strong winds from the northwest and north); and the ‘dry’ season (from March to May). Sediment characteristics, mean beach slope, and wave and surf zone parameters for typical calm, energetic and extremely energetic wave conditions are included in Table 1. Representative storm or non-storm wave conditions are defined in terms of the annual RMS wave height; energetic wave conditions are those produced by a typical ‘Norte’; and extreme storm conditions are the wave conditions originating from the passage of tropical cyclones or hurricanes. A dissipative surfzone-beach morphological state is observed for both low and most energetic wave conditions.

Table 1. Sediment characteristics, mean beach slope, and wave and surf zone parameters for typical calm, energetic and extremely energetic wave conditions.

Tortugueros beach is a wave dominated beach with typical Caribbean shore features of very fine to fine sands forming a beach profile of quite mild slope, with gentle wave breaking ACCEPTED MANUSCRIPT (mostly spilling). The sediment sources are longshore sediment transport and onshore sandbar migration, while sediment loss is due to long and crosshore (during storms) transport.

Waves and currents throughout the year show a dominant East-West direction, as does the sediment transport. This pattern is only modified by the winter storms (‘Nortes’) when the

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coastal hydrodynamics are North-South directed and cross-shore sediment transport occurs.

The region is micro-tidal with mean and maximum high tide levels of 0.18 m and 0.92 m above the mean sea level (amsl) and a difference between the mean high tide and mean low tide of 0.43 m (PDU, 2009). Small dunes extend longitudinally along the beach, with the vegetation behind being mainly mangrove forests. Tortugueros beach is at the midpoint of the relatively linear shore of Isla del Carmen. Escudero (2016) produced maps showing the existence of a connecting channel between the ocean and the lagoon, which was naturally closed towards the end of the 19th century. Thus, the sand that nowadays feeds the spit was part of a natural bypass system. Consequently, the spit can be considered a young coastal formation and hence has a highly dynamic character.

3. Methods

3.1. Spit coastline position

Aerial photographs and satellite images from 1985 to 2016 were used to identify annual and interannual morphological changes at Tortugueros beach. The aerial photograph (2-m, resolution) covered the period from 1985 to 2008 and the subsequent images, until 2016, were 0.5-m resolution satellite images provided by DigitalGlobe. The aerial photographs were geo-rectified to the Universal Transverse Mercator coordinate system (UTM 15N

WGS84), taking specific control points from the satellite images and the topographic points taken with GPSACCEPTED, in the field in April 2012 , MANUSCRIPTmainly along the edge of the highway crossing Isla del Carmen, which is the most visible permanent, rigid element appearing in all the images.

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16 shoreline positions (15 non-homogeneous time spans) were used from the digitization of the photographs and images into a Geographic Information System (GIS). The shoreline position was defined as the water line at the time of the photograph. The pixel size of the satellite images (0.5 m) and the aerial photographs (2 m) were small enough, compared to the coastline displacement rates, to obtain a feasible time series of coastline positions.

Fifteen transects, located every 50 m along the baseline and perpendicular to the mean orientation of the spit shoreline at the beginning of each time span, were defined to calculate the cross-shore and longshore wave energy. Two shoreline positions were considered representative for the initial coastline orientation of the spit for the 15 time periods (Fig. 3).

The beach profiles shown in Fig. 3a were used in time spans 1, 7, 9, 10, 12, 13 and 15; and the horizontal transects (Fig. 3b) within the other eight time periods. Fig. 3a also includes, as examples, the initial coastline position of the spit for the analysis in time spans 1 (Mar 1985

– Mar 1990), 9 (Feb 2008- Jul 2009), 10 (Jul 2009 – Jul 2011) and 12 (Apr 2012 – May

2012). On the other hand, Fig. 3b shows the initial coastline position of the spit in time spans

2 (Mar 1990 – Apr 1992), 5 (Jan 2002 – Feb 2005), 6 (Feb 2005 – Sep 2005) and 8 (Jan 2007

– Feb 2008).

Figure 3. Orientation of beach profiles selected for the evaluation of cross-shore and longshore evolutionACCEPTED of the spit: (a) Oblique MANUSCRIPTtransects; (b) Horizontal transects.

3.2. Offshore wave data & modelled wave breaking data

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Hindcast databases from two different sources, at points 60 km offshore from the beach (Fig.

1b), provided the 31 year (1985-2016) time series of wave data. The ATLAS source (Silva et al., 2008) supplied hourly sea states from a point at 24 m depth, from March 1985 to

February 2005 (time spans 1 to 5); and data from the WAVEWATCH III model (WW3)

(ftp://polar.ncep.noaa.gov/pub/history/waves/) provided sea states at 3 hourly intervals from a point at 22 m depth, covering the hydrodynamic forcing from February 2005 to 18 Feb

2016 (time spans 6 to 15).

Both sources of reanalysis data were compared to buoy data to analyse their validity and compatibility for the analysis, and to determine the most appropriate database in the common period of data (from 2005 to 2010). The buoy data, Station 42055 (Bay of Campeche) (Fig.

1a), were obtained from the National Data Buoy Center (http://www.ndbc.noaa.gov/).

The normalized root mean square error (NRMSE) obtained from the comparison of reanalysis and buoy data (ATLAS vs Buoy in Fig. 4a; WW3 vs Buoy in Fig. 4b) was lower for the WW3 database. Consequently, the WW3 reanalysis data were used in the period from

2005 to 2016.

Figure 4. Validation of reanalysis wave data (significant wave height Hs, peak period Tp and wave direction) against buoy data: (a) ATLAS vs Buoy; (b) WW3 vs Buoy. ACCEPTED MANUSCRIPT

The breaking wave conditions were calculated to estimate the wave energy flux capable of moving the beach sediment. After that, specific offshore wave characteristics were related to

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specific spatial distributions of the wave energy along the beach and to determined shoreline responses. The procedure followed was:

(a) Identification of storm episodes, considering a threshold of 2 m significant wave height, based on the application of threshold stability properties on extreme values (Gonzalez, 2014), and a minimum duration of two hours.

(b) Definition of the wave data between storms as non-storm wave episodes.

(c) Obtaining the representative wave characteristics for the storm and non-storm episodes by using the RMS wave height, the mean and maximum peak period and the resulting direction of the significant wave height. Series of monochromatic wave scenarios were defined by combining those parameters in a length equal to the duration of each wave episode.

(d) Extraction of 157 representative monochromatic wave scenarios for propagation, with four different bathymetries, near the shoreline (see section 3.3.2), which approximated the characteristics defined for every wave event. The wave periods selected for the numerical propagation were the mean value between the mean and maximum peak periods for non- storms episodes and the maximum peak period for the simulation of storms.

(e) Wave propagation using REFDIF (Kirby and Dalrymple, 1994) and WAPO (Silva et al., 2005) numericalACCEPTED models. REFDIF was used MANUSCRIPT to approximate the wave conditions from 15 to 8 m depth; and WAPO was applied to propagate waves from 8 m depth to the beach, on a more detailed grid to properly simulate the hydrodynamics that occur on the breaker and surf zones of the beach.

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(f) Extraction of the breaking wave height and breaking wave angle for each of the 15 beach profiles to subsequently calculate the wave energy flux.

3.3. Topography and Bathymetry

3.3.1. Topography

The configuration of the spit from the LiDAR data was compared to the digitalized coastline from the aerial photograph of February 2008 to assess the compatibility and quality of both data sources (Fig. 5). Five representative beach profiles along the spit were selected from the fifteen transects used in the analysis (p4, p7, p10, p13 and p15). The error was consistent along almost the full extension of the spit, with a maximum difference of 8 m between both coastlines (except for two very specific sections located around profiles 13 and 15, in the northern region where a difference of 20 m was found). The elevation of the spit ranges from

0.3 to 2 m above sea level, and the lagoon depth is less than 0.5 m.

Figure 5. Beach profiles along the barrier spit obtained from LiDAR (Light Detection and

Ranging) data (position of the beach from 2008). Compatibility of the aerial plot of

February 2008 (dashed line) and the LiDAR data.

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Bathymetric data from four dates between 1978 and 2014 were used to numerically propagate offshore wave conditions to the beach. Table 2 includes the year of each seabed dataset, the source of information and the imagery time spans to which they were applied. Concatenated

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grids of bathymetric data were created for the numerical wave propagation (see Fig. 6a and

6b), using two different detailed meshes (for WAPO numerical model application) to appropriately cover the range of simulated wave directions (solid line and dashed boxes, Fig.

6a and Fig. 6b).

Table 2. Bathymetric data used for the numerical propagation of waves

Figure 6. Sketch of concatenated bathymetric grids for numerical wave propagation: (a)

REFDIF + WAPO (1978 bathymetric data); (b) REFDIF + WAPO (2005 bathymetric data); (c) WAPO (2008 bathymetric data); (e) WAPO (2014 bathymetric data).

3.4. Wave energy flux for individual wave events

The wave energy flux was estimated considering linear wave theory and negligible energy dissipation before the break point, as defined by eq. (1) (Mil-Homens et al., 2013).

53 42 2 g 52 FECFHb gb; b b (1) 8  b where Eb is the wave energy per unit crest; Cgb is the group velocity at the breaker; Hb is the breaking wave;ACCEPTED γb is the breaker index (γb=0.78) MANUSCRIPT; g is the acceleration due to gravity; and ρ is the water density.

Considering obliquely incident waves, the longshore and cross-shore components of the incident wave energy flux per unit length of the shore are given by eqns. 2 and (3):

Alongshore wave energy flux 12

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53 42 2 g 52 FHbl  bcos  b sin  b (2) 8  b

Cross-shore wave energy flux

53 42 2 g 5 2 2 FHbc  bcos b (3) 8  b where αb is the wave angle at the breaking point.

3.5. Time-averaged wave energy flux for the duration of each time span

Equation 4 is proposed to obtain an averaged value of the wave energy flux (total and in its longshore and cross-shore components) at the location of each beach profile,

F dur F   bii episode (4) b _ Profiletime dur  episodei where F is the wave energy flux obtained for each wave event; dur is the duration of bi episodei each wave event.

In the following sections the validity of eq. 4 to represent the series of wave energy conditions within each time span was determined according to the duration and the wave characteristics per time span. The most important application of this parameter is the possibility of predicting which sections of the beach might advance or retreat as a consequence of the concentration of wave energy.

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Sea level variation due to astronomical tide and/or storm surge was not considered for the numerical wave propagation. However, as mentioned previously, the range of the astronomical tide is less than 1 m; and the numerical modelling of storm surges at the location

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of the reanalysis data also showed values of around 1 m for the most unfavourable storm conditions which were observed during the passage of Hurricane Roxanne (Oct 1995),

Hurricane Nate (Sep 2011) and Hurricane Ernesto (Aug 2012). This approximation is in agreement with the registered data of 0.5 m and 1.2 m, reported for Hurricane Roxanne by

Palacio-Aponte (2010).

4. Results

4.1. Shoreline behaviour

The limits of the study area are marked by black dots in Fig. 2, and were defined by the borders around which the most important beach changes occurred, with the northern end being a rocky headland. Three general spit positions were identified in the 31-year period of analysis (in dashed line, blue and black in Fig. 7a). The distance, measured perpendicular between the most extreme positions, was around 164 m, of which 90 m was the separation between the intermediate location and that closest to the mainland beach. The maximum rate of coastline advance, 44 cm/day, was observed from 3 May 2012 to 25 Nov 2012, and the maximum retreat, 54 cm/day, from 25 Nov 2012 to 23 Mar 2013. These are extremely rapid rates of change, equating to 160 m yr-1 and 196 m yr-1 respectively.

The identification of a similar position of the spit on different dates, as shown in Fig. 7b and

7c, and its evolution between the three general positions observed facilitated an understanding ACCEPTEDof the cycles of spit growth and MANUSCRIPT breaching. Those were produced on a seasonal basis with inlet-spits completing their entire growth within one season (i.e. the spit change from February 2005 to September 2005, in time span 6) or two seasons (i.e. the spit change from April 2012 to November 2012, in time span 12).

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Figure. 7. Identification of spit positions at various times: (a) Three general positions; (b)

Three positions farthest from the mainland; (c) Four intermediate positions: (d) Two coastlines with a progradated position in the north and an eroded position in the south, with respect to 19 Jan 2002 (intermediate position); (e) Three configurations with a similar position for their northern sections (intermediate position), and a more eroded spit on the southern stretches; (f) Three positions showing a more eroded spit, between the intermediate and the most landward form (Mar 1990).

4.2. Barrier spit changes induced by wave climate

Fig. 8 shows the distribution of total wave energy flux and its cross-shore component values within the time spans 1 to 3 (Fig. 8c and Fig. 8d, respectively), at the breaking point of the

15 transverse beach profiles, for the modelled storm and non-storm wave scenarios (defined by wave height, in Fig. 8a; and wave direction, in Fig. 8b). The sequence of wave energy determined by the series of wave scenarios was compared with the coastline evolution within the fifteen time periods from 1985 to 2016 (Fig. 8e) in order to determine the coastal dynamic drivers. Those results were analysed for the other time periods in Fig. 9 (times 4 to 5) and

Fig. 10 (times 6 to 15). ACCEPTED MANUSCRIPT

Figure 8. Wave energy distribution for the 15 beach profiles for the modelled wave scenarios within the time spans 1 to 3: (a) wave height; (b) wave direction; (c) magnitude of total wave

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energy flux; (d) magnitude of cross-shore wave energy flux; (e) coastline evolution within each of the time spans.

Figure 9. Wave energy distribution for the 15 beach profiles for the modelled wave scenarios within the time spans 4 to 5: (a) wave height; (b) wave direction; (c) magnitude of total wave energy flux; (d) magnitude of cross-shore wave energy flux; (e) coastline evolution within each of the time spans.

Figure 10. Wave energy distribution for the 15 beach profiles for the modelled wave scenarios within the time spans 6 to 15: (a) wave height; (b) wave direction; (c) magnitude of total wave energy flux; (d) magnitude of cross-shore wave energy flux; (e) coastline evolution within each of the time spans.

Seven categories of energy magnitude were established to visualize more clearly the wave energy distribution along the beach (Table 3).

Table 3. Categories defined for total wave energy flux values (Fb) and its cross (Fbc) and longshore componeACCEPTEDnts (Fbl). MANUSCRIPT

The wave energy distribution pattern for the beach was related to the coastal climate of the area. The most energetic wave conditions were observed during ‘Nortes’ storms (mainly from

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October to February) and tropical cyclones (in the ‘rainy’ season, from June to September).

In general, those storms produced high wave energy along virtually the entire beach. Table

4 includes the wave parameters, duration and maximum and mean values of the wave energy flux (total and in its cross-shore and longshore components) of the most energetic tropical cyclones identified in the period 1985 to 2016. The values higher than 56 kW/m are highlighted in black to show the most intense storms, which occurred in time periods 1, 4 and 5, with the maximum wave energy value, of up to 232 kW/m, observed during Hurricane

Isidore, in September 2002. The distribution of energy along the beach for those wave conditions can be seen in Fig. 8, Fig. 9 and Fig. 10.

Table 4. Wave parameters and energy for the most energetic tropical cyclones identified in the period 1985 to 2016.

Regarding ‘Nortes’ episodes, between one and six cold-fronts a year impact the site, lasting from a few hours to two days. The most frequent wave scenarios have a RMS wave height of 2 to 3 m, a maximum peak period of 8 to 11 s, and a mean wave direction coming from the North-West to North sectors. The maximum values of the total wave energy flux in

‘Nortes’ episodes in the different time periods ranges from 44 to 178 kW/m, with a mean wave energy fluACCEPTEDx of up to 112 kW/m. In particular, MANUSCRIPT the time periods 10 and 15 showed the highest frequency of intense and long-lasting ‘Nortes’ storms (Fig. 10); and the maximum energy value, of around 178 kW/m, was observed on some stretches of the beach during a

‘Norte’ event in January 2001 (time span 4).

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Although less intense than the storms described above, the analysis of non-storm episodes showed offshore wave conditions which need to be considered for their associated medium- high and/or high wave energy levels on certain sections of the beach (see Table 5), and which, again, occurred most frequently in the ‘Nortes’ season.

Table 5. Non-storm wave conditions that produce medium-high and/or high wave energy levels.

Regarding the direction of the total wave energy flux, an oblique orientation with predominant North to South longshore direction was observed for storm and non-storm episodes. However, for some conditions which occurred during the ‘Nortes’ season and hurricanes, a longshore component in the South to North direction occurred (see Table 6).

Table 6. Wave conditions that produce a South to North alongshore wave energy flux.

Moreover, and also associated with a greater frequency in the ‘Nortes’ season, several wave conditions were distinguished by a more important longshore (North-to-South direction) or cross-shore componentACCEPTED of the wave energy fluxMANUSCRIPT (see Table 7 and Table 8).

Table 7. Wave characteristics that produce a higher longshore (North-to-South direction) component of the wave energy flux.

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Table 8. Wave characteristics that produce a higher cross-shore component of the wave energy flux.

Analysis of the wave distribution along the beach, as a function of the wave characteristics and the bathymetric data, showed five general patterns of beach response. These are: for the entire beach, higher in the northern section, higher in the southern section, higher in the central section and lower in the central section (see Fig. 8-10). Lower wave energy along the entire beach usually occurred during non-storm wave episodes, in dry and rainy seasons. In

‘Nortes’ seasons a higher concentration of wave energy in the northern section of the beach and higher/lower wave energy in the central region was produced. The greatest distribution of energy in the southern section was observed either in ‘Nortes’, ‘rainy’ or ‘dry’ seasons

(Fig. 8- Fig. 10), though with a lower magnitude in ‘rainy’ and ‘dry’ periods.

The comparison of results from the four bathymetries available in the analysis period showed some differences, mainly related to the magnitude of the wave energy for specific non-storm episodes of waves coming from the North and North-East sectors. Some of those wave scenarios are included in Table 9. A similar pattern of wave energy distribution was observed for the most energetic conditions during ‘Nortes’ and tropical cyclones, with Medium-High, ACCEPTED MANUSCRIPT High or Very High wave energy for the majority of the episodes. The differences are mainly related to variations in the seabed slope of the breaker and surf zones of the beach in the four years (see Fig. 6), which determine the dissipation mode of the wave energy on the beach.

The most important changes were identified from the 2005 bathymetric data due to its steeper

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slope in comparison with the other three bathymetries. This produces a higher wave energy flux at the breaking point for the same wave conditions.

Table 9. Non-storm wave scenarios that produced a different wave energy distribution pattern.

4.3. Time-averaged wave energy flux

In general, the pattern of wave energy along the beach represented by the time-averaged wave energy flux was consistent with the evolution of the spit coastline in each period (see Fig. 11 in Annex). Six categories of energy magnitude were established covering the range of values associated with the modelled wave scenarios (Table 10). Retreat of the shoreline was identified for medium or higher energy classes in most of the time periods, with the exception of the behaviour in the longest period (time span 4, of 8 years).

The total magnitude of the time-averaged wave energy flux also identifies the sections of spit susceptible to breaching due to high energy gradients.

Table 10. Categories established for the time-averaged wave energy flux (Fb) and its cross

(Fbc) and longshoreACCEPTED components (Fbl). MANUSCRIPT

5. Discussion

5.1. Changes in the spit system

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In this section, the location of the spit farthest from land is called position 1, the intermediate location is position 2 and the most eroded position is position 3 (see Fig. 7a). The area between positions 1 and 2 is termed zone A, and zone B lies between positions 2 and 3. The wave conditions referred to as drivers correspond to modelled wave events, and they are obtained from the comparison of the beach response observed from the images and the wave energy distribution, at the break point, produced by each modelled wave episode.

In time 1 (Mar 1985-Mar 1990), the barrier spit evolved from position 2 to position 3. The general retreat is thought to have been produced by the high frequency of storms (several

‘Norte’ events and hurricanes) with a mainly Northwest to North-Northwest wave direction with, in some cases, a small angle (5°); and also due to waves of the non-storm class that produced a low-medium energy concentration (H: 0.6 m; T: 8 s; Dir: 14 – 65°) or medium- high energy (H: 0.8 m; T: 8 s; Dir: 35°) in the central section of the beach (see Fig. 8).

In times 2 (Mar 1990-Apr 1992) and 3 (Apr 1992-16 Mar 1994), the coastline moved from position 3 to zone B in the northern section, due to prevailing very low and low energy non- storm wave conditions coming from the first quadrant.

In time 4 (16 Mar 1994-19 Jan 2002), a general advance of the beach from zone B to position

2 occurred, which could be the result of predominantly low and low-medium wave energy conditions associated with the three last episodes of the time span (H: 0.4 m; T: 8 s; Dir: 51°;

‘Norte’ event- ACCEPTEDH: 2.4 m; T: 9 s; Dir: 8°/ H: 0.6MANUSCRIPT m; T: 8 s; Dir: 356°). The low-medium energy of that 'Norte’ storm, with a higher longshore wave energy component North-to-South in some sections of the beach was noticeable; and the wave energy pattern originated by the last wave episode, with lower cross-shore energy in the southern section (where the advance of

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the spit was produced) and a higher longshore (North-to-South) energy in some sections at the northern end. Other wave conditions in this time span also produced an important alongshore wave energy flux (North-to-South). Therefore, the response of the spit in this period was thought to be a consequence of both components of the wave energy flux.

In time 5 (19 Jan 2002-Feb 2005), frequent storms during the ‘Nortes’ season and medium wave energy in the non-storm class (H: 0.5 m; T: 8 s; Dir: 36°) produced the general retreat of the beach from position 2 to zone B, though this was a little more pronounced in the southern section of the beach.

In time 6 (Feb 2005-15 Sep 2005), non-storm wave conditions (H: 0.7 m; T: 8 s; Dir: 11°) produced medium wave energy in the southern region and medium-high (around twice the wave energy as the medium category) at specific sections of the northern end at the beginning of the period. After that wave episode a ‘Norte’ event (H: 2.2 m; T: 9 s; Dir: 332°) produced a similar gradient in the cross-shore component in the northern section to that of the southern end (high vs medium-high energy), but a greater increase of the longshore wave energy

(North-to-South direction) in some sections (very high category in Fig. 11d), which could have exceeded the critical width of the spit and caused its rupture. Hence, the twofold beach response was from zone B to position 1 in the northern section and to position 3 in the southern section.

In time 7 (15 SepACCEPTED 2005- 4 Jan 2007), the sequence MANUSCRIPT of wave scenarios (non-storm and ‘Norte’ events) characterized with significant longshore (North-to-South direction) and cross-shore wave energy flux is thought to have produced sediment redistribution along the spit. The spit had reached position 1 by the end of the time span.

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In time 8 (4 Jan 2007- 17 Feb 2008), the coastline retreated in the northern stretch of the beach from position 1 to position 2, which might have been produced by the ‘Norte’ events occurring at the end of the period. Those storms (H: 2-3 m; T: 10 s; Dir: 333-355°) caused high and very high oblique wave energy (North-to-South direction) at the northern and southern ends and a high energy gradient in central areas (high vs low-medium), which could also have caused the break in the spit at the southern end.

In time 9 (17-Feb 2008-31 Jul 2009), low wave energy was evident for a long period in the last episode (H: 0.6 m; T: 8 s; Dir: 53°), which corresponded to the ‘dry’ season, when seaward progradation moved the beach from positon 2 to position 1. An elongation of the spit from North to South occurred, consistent with the alongshore direction of the wave energy given by the most frequent wave episodes.

In time 10 (31 Jul 2009-20 Jul 2011), the frequency of intense and long-lasting ‘Nortes’ storms and very high energy non-storm conditions for a long time (H: 0.7 m; T: 7 s; Dir: 39°) caused a coastline shift from position 1 to zone B in the central and southern stretches and no significant movement at the northern end. The high longshore component of wave energy

(North-to-South), in particular during the long-lasting high energy non-storm event, is thought to have been the driver responsible for forcing the loss of sediment of the southern end.

In time 11 (20 ACCEPTEDJul 2011-15 Apr 2012), the beachMANUSCRIPT response was from position 1 to position 2 in the northern section, with more erosion in zone B, at the southern end. High wave energy conditions (‘Nortes’ events, H: 2-3 m; T: 10-11 s; Dir: 332-338°) and non-storm waves coming from the North-Northeast (H: 0.8 m; T: 8 s; Dir: 57°) drove a shoreline response of

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cross-shore retreat in the northern region and alongshore wave energy flux in a North-to-

South direction. The gradient in cross-shore and longshore wave energy in the northern section in respect to the southern end (medium-high vs low-medium) produced by ‘Norte’ events could have caused a breach in the central section of the spit.

In time 12 (15 Apr 2012-3 May 2012), the beach shifted from position 2 to zone B at the northern end and retreated a little more in the southern stretch. The coastline response was consistent with the wave energy distribution produced by the non-storm wave conditions at this time (H: 0.8 m; T: 8 s; Dir: 30°), which were characterized by a predominant alongshore component (north-to-south) and higher energy in the central section of the beach.

In time 13 (May 2012-Nov 2012), the prevailing low wave energy produced a seaward advance of the coastline along the entire beach, from zone B to position 1.

In time 14 (Nov 2012-Mar 2013), as in time 8, the higher concentration of wave energy in the northern stretch of the beach produced by ‘Norte’ storms induced a coastline retreat in that section, from position 1 to position 2. In this period, a breach of the spit in the southern stretch did not occur because of the lower magnitude of the wave energy produced by the

‘Norte’ events in this period. Moreover, the wave energy associated with the last non-storm episode (H: 0.8 m; T: 7 s; Dir: 20°) also caused a higher energy concentration (low-medium energy) in the northern section of the beach. ACCEPTED MANUSCRIPT In time 15 (Mar 2013-Feb 2016), the sequence of high wave energy episodes during the

‘Nortes’ season induced the retreat of the beach in the southern section, going from position

2 to zone B, similar to the behaviour observed in time 5 for this part of the beach.

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Given that a clear correlation between the dynamics of the spit and the local marine weather conditions is still difficult to obtain, a wider view of the phenomena involved in the morphological evolution of the spit is needed. For that purpose, the Oceanic Niño Index

(ONI) was retrieved (ggweather.com/enso/oni.htm) for the years when aerial or satellite images were available. These data was crossed with the morphological responses shown in

Fig. 2; the summary of which is shown in Table 11.

Table 11. Oceanic Niño Index (ONI) and morphological response for the years with imagery available for Tortugueros spit.

As can be seen in Table 11, in all the years with a Niña event, the spit moves landwards, while in all the years with a Niño event the spit moves seawards. This finding is in agreement with the well-known phenomena of overall energy and sea level increases in the Atlantic

Ocean during Niña events and vice versa. When the ONI is not clearly an El Niño or La Niña event, the response of the spit depends on the local marine weather conditions.

The above is true except for times 6 and 7. This divergence is due to the record number of storms in 2005, which explains the breaching of the spit into two parts (time 6) and its recovery (time 7). ACCEPTED MANUSCRIPT It is clear then, that the response observed in the spit is due to the combination of long period events and short period local conditions. These two precursors may serve as indicators of spit behaviour elsewhere. In accordance with other authors, the wave climate variations are seen to be the main factor controlling the morphological evolution of spits. Spit formation in areas 25

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with a relatively small tidal range (Dean and Dalrymple, 2004 and Davis and Fitzgerald,

2004) and dominated by oblique waves, where both cross-shore and longshore sediment transport are important (Nagarajan et al., 2015; Zenkovich, 1967; Carter, 1988), match with the case of Tortugueros spit.

The cycles of accretion and breaching on the spit identified in this analysis are in agreement with the finding of Weidman et al. (1993) at South Beach, USA. As reported by (Watanabe et al., 2005; Thomas et al., 2011), the changes in the configuration of spits are correlated to the predominant storm wave characteristics, i.e. by the occurrence of a hurricane in the study area.

Following the methodologies applied by Arrard et al. (2008) and Thomas et al. (2014), in this study, we used a combination of numerical modelling and satellite imagery to investigate the hydrodynamic causes of coastal evolution. The methodology used here also incorporates the wave energy flux of the breaking waves to determine the drivers responsible of a specific spit coastline evolution. The time-averaged wave energy was also suggested as a representative parameter to understand the wave forcing in a particular time period. Hence, it was consistent with the spit shoreline response at Tortugueros beach in the medium term and in inter-annual time scales (1 or 2 years), despite its simplicity in relation to the high variability and complex morphological behaviour of the spits. Therefore, it is thought that the methodologyACCEPTED proposed in this study is aMANUSCRIPTble to explain the multi-annual change of a spit and is therefore valid to describe the functioning of spit dynamics elsewhere.

6. Conclusions

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The methodology presented here is able to explain the multi-annual behaviour of a dynamic, complex barrier spit due to the variations in the cross-shore and longshore energy flux of the breaking waves.

The numerical modelling of representative storm and non-storm wave episodes and the associated wave energy flux at breaking conditions allowed the identification of drivers responsible for the particular evolutionary path of the spit shoreline at Tortugueros beach.

The pattern of energy distribution along the beach was related to the coastal climate of the area, which was characterized by three main seasons.The most important loss of sediment and/or coastline retreat were related to energetic episodes during storms and also to specific non-storm conditions; although, in general, mild weather favoured the advance of the shoreline spit. The breaching of the spit in a specific time span was related to gradients in wave energy in different sections of the spit. The predominant oblique orientation of the total wave energy flux (north-to-south direction) for the majority of the modelled wave scenarios also determined the importance of both cross and longshore components on the shoreline response of the spit.

In general, the time-averaged wave energy flux as a parameter to represent the wave energy that might drive the coastal evolution of the spit within a specific time span showed a consistent behaviour for all the time spans analysed, with the exception of time 4 (the longest time span). TheACCEPTED results suggest that cross -shoreMANUSCRIPT wave energy flux greater than 6 kW/m is more likely to produce the retreat of the spit.

The cycles of spit growth and breaching were observed on a seasonal basis, governed by the climatic variations in the frequency and intensity of storms. . Moreover, a clear influence of

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El Niño and La Niña phenomena was identified to explain the landward or seaward displacement of the spit, through the analysis of the Ocean Niño Index (ONI) for the years when aerial or satellite images were available.

The analyses conducted here also highlight the importance of the monitoring of spits as a means of detecting the effects of natural events and human interventions on the coast. This information can be key for coastal managers. Given that spits are highly dynamic and vulnerable, changes in their dynamics may allow stakeholders react in advance of significant coastal degradation.

Analysis of the position and morphology of the barrier spit system over time also demonstrates how very dynamic such systems are; being perhaps some of the most mobile and translatory of all shorelines. If one considers the fixed (black dot) point in Fig. 2, it is clear that any infrastructure built adjacent to such a shoreline must take into account the possibility of extreme shoreline changes along such a highly dynamic (and naturally functioning) coast.

Acknowledgements

The authors would also like to acknowledge the Mexican Secretaría de Marina (SEMAR) for the bathymetric information provided, which improved the quality of the research. This publication is one of the results of the Latin American Regional Network global collaborative project “EXCEEDACCEPTED SWINDON project–Excellence MANUSCRIPT Center for Development Cooperation–

Sustainable Water Management in Developing Countries”. Patrick Hesp thanks Flinders

University and UNAM for their support.

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Annex

Figure 11. Time-averaged wave energy flux for the 15 time periods (total and longshore and cross-shore components)

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Table 1. Sediment characteristics, mean beach slope, and wave and surf zone parameters for typical calm, energetic and extremely energetic wave conditions.

Parameter Non-storm wave conditions Storm wave conditions Extreme storm conditions

Beach gradient tanβ 0.0012 0.0012 0.0012

0.000137 0.000125 0.000074 Sediment size D50 (m) fine sand very fine sand very fine sand

-1 0.0154 0.0139 0.006 Sediment fall velocity ws (ms )

Wave forcing parameters

0.5 2 6 Breaking wave height Hb (m)

Wave period T (s) 3.2 11.5 9.5

Breaking wave angle α (°) 60 48 56

Morphodynamic indices

gT 2 16 206 141 Wave length (m) L  0 2

Surf similarity parameter 0.007 0.012 0.005

tan  spilling breaking spilling breaking spilling breaking b  HLb / 0

Battjes (1974)

Surf scaling parameter 136458 42264 185795

HT2/ 2 dissipative beach dissipative beach dissipative beach   b g  tan2 

Guza and Inman (1975)

Morphological classification C 13 23 112

0.67 erosive beach erosive beach erosive beach H 0.27 d 0 C tan    LL00

Sunamura (1974) Dimensionless fall velocityACCEPTED 10 MANUSCRIPT13 105 dissipative beach state reflective beach state dissipative beach state Hb  wTs 

Wright and Short (1984) where g gravity acceleration, L0 deep-water wavelength, H0/L0 wave steepness of offshore waves, d sediment diameter, tanβ beach gradient, Hb breaking wave height, ws sediment fall velocity, T wave period

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Table 2. Bathymetric data used for the numerical propagation of waves

Bathymetric Source Resolution/ Imagery time Period of time No. of wave scenarios data spans modelled Scale

1978 Mexican Nautical Chart, SEMAR: 1 to 2 Mar 1985 – Apr 25 1992 S.M. 840-1st Edition 1:250,000 S.M. 842.1- 1st Edition 1:60,000 2005 Mexican Nautical Chart, SEMAR: 3 to 7 Apr 1992 – Jan 57 2007 S.M. 840-4th Edition 1:250,000 S.M. 842.1- 2nd Edition 1:60,000 2008 IOC, IHO and BODC, 2003 30 arc-seconds 8 to 10 Jan 2007 – Jul 37 2011 2014 IOC, IHO and BODC, 2003 30 arc-seconds 11 to 15 Jul 2011 – Feb 38 2016

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Table 3. Categories defined for total wave energy flux values (Fb) and its cross (Fbc) and longshore components (Fbl).

Category Fb/Fbc/Fbl (W/m) Very Low (VL) 0 - 340 Low (L) 340 – 1,131 Low-Medium (LM) 1,131 – 2,828 Medium (M) 2,828 – 5,657 Medium-High (MH) 5,657– 28,930 High (H) 28,930-56,568 Very High (VH) 56,568– 232,010

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Table 4. Wave parameters and energy for the most energetic tropical cyclones identified in the period from 1985 to 2016.

Name Year Month Duration H (m) T (s) Dir (°) Fbmax Fbmean Fbcmax Fbcmean Fblmax Fblmax Time (h) (W/m) (W/m) (W/m) (W/m) N-S S-N span (W/m) (W/m) 1 Gilbert 1988 Sep 37 3.4 9 302 55,653 30,038 42,710 23,872 36,561 - 1 Jerry 1989 Oct 12 2.5 13 340 80,831 39,638 49,905 22,792 64,319 - 3 Gert 1993 Sep 23 2.4 7 343 31,317 27,646 31,311 26,277 14,855 6,195 4 Roxanne 1995 Oct 149 4.0 11 322 160,146 146,315 86,878 73,257 134,526 - 4 Dolly 1996 Aug 15 2.3 8 40 29,473 19,172 28,511 17,938 13,413 10,726 4 Mitch 1998 Nov 30 3.0 8 315 45,612 40,786 34,643 27,974 29,993 - 4 Keith 2000 Oct 14 2.6 7 336 45,612 40,786 34,643 27,974 29,993 - 5 Isidore 2002 Sep 83 4.0 12 302 232,010 183,990 146,428 109,014 186,767 - 8 Dean 2007 Aug 6 2.2 8 355 38,518 8,825 25,581 5,720 28,794 40

Note. The wave energy values in black correspond to the Category ‘Very High’.

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Table 5. Non-storm wave conditions that produce medium-high and/or high wave energy levels. H (m) T (s) Dir (°) Bathymetry Season Time span 0.6 8 14 1978 Nortes 1 0.7 7 39 2008 Rainy 10 0.7 7 340 2005 Nortes 4 0.8 8 35 1978 Nortes 1 0.9 8 9 2005/2008 Dry 7 1 8 340 2008 Nortes 10 1.3 9 348 2005 Nortes 7 1.7 7 335 2005 Nortes 4 1.6 7 6 2005 Rainy 3

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Table 6. Wave conditions that produce a South to North alongshore wave energy flux.

H (m) T (s) Dir (°) Bathymetric data Season or Time span storm 0.5 7 350 2005 Nortes 3 2.4 7 343 2005 Hurricane 3 2.2 8 40 2005 Hurricane 4 2.2 8 355 2005 Hurricane 8 2.6 7 336 2005 Norte storm 4 2.4 7 325 2005 Norte storm 3/4 2 7 331 2005 Norte storm 4 2 7 316 2005 Norte storm 4

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Table 7. Wave characteristics that produce a higher longshore (North-to-South direction) component of the wave energy flux. H (m) T (s) Dir (°) Bathymetric data Season Time span 0.6 8.0 57 2005 Rainy 7 0.7 7.0 39 2008 Rainy 10 0.8 8.0 30 2014 Dry 12 0.8 8.0 50 2005 Nortes 7 0.8 8.0 35 1978 Nortes 1 0.8 10.0 34 1978 Nortes 1 0.9 8.0 35 2008 Nortes 10 1.6 7.0 6 2005 Rainy 3 2.0 11.5 5 1978 Nortes 1 2.3 10.0 338 2005/2014 Nortes 7/14 2.5 13.0 340 1978 Nortes 1 3.0 11.0 332 2014 Nortes 11

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Table 8. Wave characteristics that produce a higher cross-shore component of the wave energy flux. H (m) T (s) Dir (°) Bathymetric data Storm Time span 2 7 316 2005 Norte 4 2 7 331 2005 Norte 4 2.2 8 40 2005 Hurricane 4

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Table 9. Non-storm wave scenarios that produced a different distribution pattern of wave energy depending on the bathymetric data.

H (m) T (s) Dir (°) Bathymetries 0.5 8 36 1978 vs 2005 0.6 8 53 1978 vs 2008 0.8 8 14 2005 vs 2008 0.8 8 30 2008 vs 2014 0.9 8 35 1978 vs 2008

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Table 10. Categories established for the time-averaged wave energy flux (Fb) and its cross (Fbc) and longshore components (Fbl).

Category Fb/Fbc/Fbl (W/m) Very Low (VL) 0 - 170 Low (L) 170 - 340 Low-Medium (LM) 340 – 1,200 Medium (M) 1,200 – 3,400 High (H) 3,400-7,200 Very High (VH) 7,200 – 18,000

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Table 11. Oceanic Niño Index (ONI) and morphological response for the years with imagery available for Tortugueros spit.

Time ONI Spit displacement 1 Strong Niña Landwards 2 Strong Niño Seawrds 3 Weak Niño None 4 Moderate Niño Seawards 5 Weak Niña Landwards 6 Weak Niña Broken spit: Seawards at the North, Landwards at the South 7 Strong Niña Seawards – Recovery 8 Strong Niña Landwards 9 Strong Niño Seawards 10 Strong Niña Landwards 11 None (less tan very weak effect) Landwards 12 None (less tan very weak effect) Landwards 13 None (less tan very weak effect) Seawards 14 Moderate Niña Landwards 15 Weak Niña Landwards

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Highlights

- Satellite images were used to analyse the shoreline evolution of a complex barrier spit.

- Breaking wave energy flux data defined the drivers of the specific coastal dynamics.

- The cycles of spit growth and breaching were observed on a seasonal basis.

- A predominant oblique orientation of the total wave energy flux was observed.

- The highly dynamic position and morphology of the barrier spit was analysed.

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Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11