Beach morphology and shoreline evolution: Monitoring and modelling medium-term responses (Portuguese NW coast study site)

Coastal Engineering 84 (2014) 23–37

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Beach morphology and shoreline evolution: Monitoring and modelling medium-term responses (Portuguese NW coast study site) P. Baptista a,⁎, C. Coelho b, C. Pereira c, C. Bernardes a, F. Veloso-Gomes d a

Departamento de Geociências, Centro de Estudos do Ambiente e do Mar (CESAM), Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal Departamento de Engenharia Civil, Centro de Estudos do Ambiente e do Mar (CESAM), Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal Departamento de Engenharia Civil, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal d Faculdade de Engenharia, Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR), Universidade do Porto, Rua Dr. Roberto Frias 4200-465, Portugal b c

a r t i c l e

i n f o

Article history: Received 18 September 2012 Received in revised form 1 November 2013 Accepted 6 November 2013 Available online 8 December 2013 Keywords: Sandy-shores Monitoring Modelling Shoreline-evolution

a b s t r a c t Numerical models for shoreline evolution have been used for coastal management planning for several decades. The model calibration is a start point to project shoreline scenarios and in this aim the use of data acquired within the scope of monitoring programmes provides the opportunity to assess the models' capabilities under real condition. This work applies calibration data (retrieved from field surveys) to numerical models to predict medium-term shoreline evolution using, as a case study, a beach stretch named AC, about 3.5 km long and located downdrift of a groin on the northwest Portuguese coast. A smaller stretch AB (2.4 km long), included in the total one, which exhibits a pronounced erosive tendency usually better reproduced in shoreline evolution models, was also analysed. Based on topographic surveys, associated wave climate conditions registered between 2003 and 2008 and typical wave conditions registered over a longer wave climate time period, this work compares the calibration of two different shoreline evolution models, Long-term Configuration (LTC) and GENESIS for this period. Then, considering the 2003 topographic conditions for the models' calibration, the results of both models are discussed with respect to simulation scenarios after 10, 15 and 20 years of evolution. The 10-year evolution projections of the models are also compared to the results of a survey performed in February 2012. For the wave data calibration period (2003–2008), the average shoreline retreat of the analysed coastal stretch was reproduced with small differences (around 1% and 10% for LTC and 15% and 14% for GENESIS, considering stretches AB or AC, respectively), though local differences along the AB coastal stretch represent root mean square errors reaching up to 52% and 88% for GENESIS and LTC, respectively, and were above 118% for both models along the AC coastal stretch. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Numerical models for shoreline evolution are useful tools in establishing trends and forecasting shoreline position scenarios for decadal temporal scales. Several shoreline evolution models have been proposed to describe changes in shoreline evolution based on analysis of the balance of sediment volumes over a certain period of time (e.g., Coelho et al., 2004; Hanson and Kraus, 1989; Pelnard-Considére, 1956; Steetzel et al., 2000). These models typically simulate shoreline evolution with limited resolution of the response on the intra-annual scale. The major difficulty in their application is establishing the boundary conditions, calibrating the coefficients and parameters associated with variables that represent the reality of the coastal system and correcting their contribution to the modelling process.

⁎ Corresponding author at: Universidade de Aveiro, Departamento de Geociencias, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal. Tel.: +351 234370200; fax: +351 234370985. E-mail address: [email protected] (P. Baptista). 0378-3839/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.coastaleng.2013.11.002

New survey methodologies involving aerial-based methods such as Airborne Laser Scanning (ALS) (Huising and Gomes Pereira, 1998; Saye et al., 2005; Woolard and Colby, 2002) or land-based Global Positioning System (GPS) applications (Baptista et al., 2008; Baptista et al., 2011b; Haxel and Holman, 2004) allow for the generation of highly accurate Digital Elevation Models (DEMs), with significant advantages in representing detailed beach morphology. From DEMs, several geo-referenced beach morphological variables can be extracted, for example, tidal datum shoreline indicators according to the Boak and Turner (2005) shoreline proxy classification. The establishment of monitoring programmes in sandy shores can be considered as a starting point to understand present-day shoreline evolution. Acquired topobathymetric data along several years, and the respective DEMs, in these monitoring programmes can provide accurate information for calibration and validation of numerical model for shoreline evolution. Within the scope of shoreline evolution models, the GENESIS (GENEralised model for SImulating Shoreline change) model developed by Hanson (1989) and Hanson and Kraus (1989) has been used since the end of the 1980s. More recently, the LTC (Long-term Configuration) shoreline evolution model was proposed. LTC was

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first presented by Coelho et al. (2004) and has since been improved (Coelho, 2005; Coelho et al., 2007; Silva et al., 2007). GENESIS and LTC were both developed to simulate long-term shoreline changes produced by spatial and temporal gradients in alongshore sand transport on an open coast and they do not describe cross-shore processes. The main difference between these two models is the manner in which they capture the bathymetric and topographic changes in each wave action time period. In the LTC model, in the vicinity of the Depth of Closure (DoC), the depth level is constrained by the angle of repose (Ф) in an accretion situation and by a user-defined minimum underwater bottom slope in an erosion situation. In the vicinity of the run-up limit, the controlling parameters are the user-defined minimum beach face slope and Ф for accretion and erosion, respectively (Silva et al., 2011). The objective of this study was to perform a comparative study of two numerical models for shoreline evolution calibrated with highly accurate survey data in which their performance in analysing seasonal behaviour and in predicting scenarios of shoreline behaviour would be compared. A monitoring programme was established to evaluate short- (time scales of seasons) and mid- (time scales of years) term scales of shoreline evolution in a coastal sector measuring about 3.5 km long and limited by two coastal defense structures (Portuguese Northwest coast). Some sandy shore stretches of this coast has severe problems related with shoreline retreat and in 1998 the Portuguese Coastal Management Plans (POOC, 1998) predicted the shoreline

position for 10- and 30-year horizons. Some of the worst predictions have since been made; therefore, it is required that the prediction capability be improved. This monitoring programme involved land-based GPS measurements performed in the subaerial beach to generate representative DEMs. The shorelines representative of the mean sea level (MSL) and extracted from these 3D surfaces were used to calibrate and validate two shoreline evolution models, GENESIS and LTC. Scenarios for mid-term shoreline evolution were established for 10, 15 and 20 years. 2. Study area 2.1. Geomorphology and wave climate The study area is located south of the Aveiro Lagoon entrance along the northwest Portuguese coast (Fig. 1). This coastal stretch is morphologically characterised by a sandy barrier extending in a NNE– SSW direction; this area is considered highly vulnerable to erosion due to the large streak of low-lying land with sandy sediments, which experiences severe wave conditions and large tidal amplitudes (Coelho et al., 2011). The sector considered, from Poço da Cruz to Mira Beaches is backed by a foredune ridge and laterally limited by groins, one in Poço da Cruz Beach (built in 2003) and two others in Mira Beach (built in the 1980s). Frontal dunes are very vulnerable to coastal erosion and some segments

Fig. 1. Study area: a) study area location; b) Poço da Cruz–Mira stretch with shoreline position scheme, based on surveys performed in 2003 and 2008; c) Poço da Cruz groin in 2003 during construction; and d) Poço da Cruz groin in 2009, 6 years after construction.

P. Baptista et al. / Coastal Engineering 84 (2014) 23–37

show large escarpments due to frontal dune undercut during high spring tides and storm events. In general, the beaches in this sector show pronounced seasonal behaviour, with a range of morphodynamic states. This variation reveals the important exchange of sediments between the upper and lower foreshore. During low-energy conditions, the beaches present a berm, characteristic of its reflective state, due to the onshore migration of intertidal bars. Under larger wave energies, these features disappear, the beaches flatten and a dissipative profile develops (Rey and Bernardes, 2004). In spite of this cross-shore transport, significant littoral drift causes major alongshore motion of sediments along the southward direction. The nearshore exhibits a permanent alongshore bar located 300 m offshore at a water depth of 4.5 m. Bathymetric profiles reveal a reduction in the bar height after the construction of the defence structures of Areão (built in 2002–2003 and located approximately 3.3 km north of Poço da Cruz) and Poço da Cruz Beach (Rey and Bernardes, 2004). The shore is entirely exposed to highly energetic waves. The coast is classified as swell-dominated and the main wave direction is WNW– NNW (Coelho and Veloso-Gomes, 2006). According to Vitorino et al. (2002) from June to September significant wave heights and mean periods are consistently less than 3 m and 8 s. During winter and transitions periods, the mean significant wave heights and periods exceed 3 m (most frequent values of 3–4 m) and 8 s (most frequent mean periods of 8–9 s), with frequent storms defined by a mean significant wave height greater than 5 m (often exceeding 7 m) and mean wave periods of approximately 13 s, which can reach 18 s (maximum peak periods) (Vitorino et al., 2002). Tides are semidiurnal and regular. The average values for the spring and neap tidal ranges are 2.8 m and 1.2 m, respectively. When storms are associated with high spring tides, they may induce the overwash of natural morphologies and artificial structures, causing coastal erosion hazards. Even during neap tides, storm-surge processes increase the mean water level, causing severe flooding. Extreme water level fluctuations recorded at the Aveiro tidal gauge (19 km away from the study area) between 1986 and 1988 usually exceeded 40 cm (Gama et al., 1994). Dias and Taborda (1992) reported a maximum vertical rise in the mean sea level of 1.2 m during storms in 1981. Littoral drift is the result of the dominant northwestern waves that induce a net southward sediment transport. The two main sources of sediments are the Douro River (75 km to the north) and coastal erosion (updrift beach stretches and frontal dune erosion). However, the latter currently constitutes the most significant sediment supplier in Portugal because the natural fluvial contribution has been critically diminished by dam construction, changes in land use and dredging. The presence of several cross-shore structures (jetties and groins) also contributes to changes in the sediment transport patterns. Oliveira et al. (1982) report values of 0.7 × 106 m3/year for sediment retained between 1950 and 1978 in the northern jetty at the Aveiro artificial inlet. In recent years, the retention of sediments in the external sand bank of the inlet has caused a reduction of 106 m3/year in the original net residue (Taborda, 1993). Currently, the Aveiro harbour northern jetty has been extended by about 200 m, which will affect the littoral drift and as a consequence is expected to have an increase of sediment retention in the inlet external bank. 2.2. Erosion trends The determination of the erosion rate depends on the analysed time period, the season of the year during which the measurements were registered, the methods used, the number of points or amount of coastal stretch extension considered, etc. The erosion processes should also not be confused with the seasonal changes of the beach profiles, such as beach ridges, beach cusps or ridge and runnels. Despite all constraints, erosion rates provide irreplaceable results in forecasting coastal evolution and were considered for model calibration in the Poço da Cruz case.

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Table 1 Erosion rates in the study area (negative value represent accretion). Coastal stretch Poço da Cruz — Mira (a)

Coastal stretch

Period of time

PC—M (*)

1980 — 1990

2.0

1958 — 1970

—1,7

Poço da Cruz — Mira (b)

PC—M (*)

Mira (c)

Urban front

Mira (d)

Urban front

Erosion rate (m/year)

1970 — 1998

0.6

1998 — 2006

1.5

2006 — 2010

5.2

1954 — 1984

1.5

1947 — 1958

0.4

1958 — 1973

2.9

1973 — 1978

2.4

1980 — 1990

1.2

(a) Dias et al. (1994); (b) Pooc (2012); (c) Sener (2011); (d) EUrosion (2006). (*) Poço da Cruz groin to North Mira groin (see Fig. 1b).

Table 1 shows the erosion rate characteristics of the study area over the last decades. This area was in an erosion situation before the construction of the Poço da Cruz groin. Since then, as shown in Fig. 1, there is an observed erosive tendency downdrift of the groin and an accretion trend updrift (Fig. 1b and c). Fig. 1a also shows the shorelines representative of the Mean Sea Level (MSL) obtained from the topographic surveys of 2003 and 2008. 3. Observations 3.1. Beach morphological data Within the scope of this work, two main types of data were considered: a general topo-bathymetric representation of the study site and a more detailed sub-aerial beach characterisation. Topo-bathymetric data used to model the study area were obtained from an offshore fishing chart of the Portuguese Hydrographic Institute (Instituto Hidrográfico Português), associated with topographic data available from an aero-photogrammetric survey. With that information, a database of 3D points (x, y, z) was created and mapped to the national planimetric (Datum Lisboa) and altimetric (Datum Cascais) data coordinate systems. From this database, a Digital Elevation Model (DEM) with a regular square grid with a resolution of 50.0 m was generated. The total modelled area is approximately 33.5 × 7.7 km2, going from approximately 30.0 km offshore (approximately 100 m deep) to 3.5 km inland. The shoreline corresponds to the set of points with an elevation of 0.0 m (i.e. MSL). In addition to this general DEM representation of the study site, detailed topographic surveys were performed in the sub-aerial beach, including the monitoring of changes in the most active area of the beach profile (surf-zone). These surveys were performed with a prototype system mounted on a four-wheel motor quad (Baptista et al., 2008; Baptista et al., 2011a). The measurements were carried out during low-tide conditions in a dense profile grid, which included alongshore and cross-shore transects. Global Positioning System (GPS) data were processed using Real-Time Kinematic RTK GPS software (Cunha, 2002) by means of an algorithm for kinematic ambiguity fixing in the two GPS L-bands frequencies L1/L2 (L1 = 1572.42 MHz; L2 = 1227.60 MHz) (Hofmann-Wellehof et al., 1992). The accuracy of the final Differential GPS (DGPS) positions is within 0.03 m horizontally (x and y) and 0.04 m vertically (z) (Baptista et al., 2011a). Ellipsoidal heights were also converted to the national MSL altimetric datum of the Cascais tide gauge. The Triangular Irregular Networks (TIN) method (Lee and Schachter, 1980) was also used to convert data point observations to a 3D surface represented by a detailed DEM contour map (1.0 m of resolution). The topographic surveys carried out between 2003 and 2012 include six campaigns carried out during winters. The first topographic survey was carried out immediately after the construction of the Poço da Cruz groin (10th November 2003) and the last survey was performed on 24th February 2012. Four surveys (two surveys per year) allowed

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for the study of the seasonal alongshore beach response to different wave conditions occurring during the 2006–07 (21st December 2006 to 09th March 2007) and 2007–08 (14th January 2008 to 12th March 2008) winters. During the 2006/07 winter, the time interval between data acquisition was 78 days (21th December to 9th March). During the 2007/08 winter, the time interval was 57 days (14th January to 12th March). The beach morphological variables under study were the tidal shoreline indicator (MSL contour line), the frontal dune toe and the beach width. The MSL contour line was considered the shoreline indicator for the GENESIS and LTC models, both for calibration and verifications. Slight adjustments were made to the general DEM representation of the study area (previously mentioned) to coincide with the 2003 shoreline. Throughout almost the entire study site, the frontal dune is exposed to wave attack, not only during storm events but also during the twice monthly spring tides, which makes this feature an important indicator of wave action. The presence of the two transversal engineering structures (groins) at the ends of the study sector results in pronounced effects in the frontal dunes of the adjacent southward and northward coastal segments (Fig. 2a and b, respectively). The monitoring of the frontal dune evolution effectively registers the effects of wave action on the frontal dune. The frontal dune toe displacement over time (which, in most cases corresponds to a retreat) is calculated by considering the distance between these toe reference lines in the two DEMs generated in each winter in 2006/07 and 2007/08 and also the distance between the first and last DEMs for the model calibration period (10th November 2003 and 14th January 2008). Finally, the frontal dune toe displacement was computed between the first and last DEMs (10th November 2003 and 24th February 2012). The same analysis was performed for the shoreline (MSL contour line). These measurements (for frontal dune toe and shoreline indicators) were taken in a direction perpendicular to the overall beach trend as reported in Baptista et al. (2011b).

The beach width is represented by the distance between the frontal dune toe (landward DEM limit) and the shoreline (MSL contour line). This distance was determined for each DEM by using an algorithm that generates a set of regularly spaced transects (1 m spaces in the alongshore component) perpendicular to the overall stretch trend and calculates the distance between the intersection of each transect with the frontal dune toe and the shoreline. 3.2. Wave data The nearest available recorded wave data were referenced from Leixões buoy, which is located approximately 80 km north of the study area. For a longer characterisation period of the wave climate, the data from Coelho (2005), which considers information between 1981 and 2003 for wave heights and from 1993 to 2003 for wave directions, were defined as the typical wave climate conditions of the study area (TYP wave climate). For simulations, TYP wave climate was randomly generated to represent the typical frequencies of each wave height and direction classes during five years and thus, does not represent any seasonality. The data recorded within the survey period (November, 2003 to March, 2008) are considered representative of the observed wave climate in the study site (OBS wave climate). OBS time series represents the seasonality of wave climate because it maintains the registered data sequence. During this survey period, two winters were defined according to the dates of the sub-aerial beach topographic surveys: Winter 7 (07 wave climate) between 21st December 2006 and 09th March 2007 and Winter 8 (08 wave climate) between 14th January 2008 and 12th March 2008. Table 2 presents the wave height and wave direction distribution for the different classes under four wave conditions. The observed wave climate (OBS) presents the major frequencies of wave occurrence in the lower wave height classes for the typical data (TYP). A greater number of waves from the west quadrants are also observed (WNW and W). The two winters feature the most energetic wave climates. Considering only the winter periods, there is a significant percentage of waves with heights above 2.5 m (60% for the 07 wave climate and 42% for the 08 wave climate), where WNW is the predominant wave direction. Comparing both climates, 07 shows higher waves and 08 shows a slightly higher number of waves from northern quadrants. 4. Model description and calibration

Fig. 2. Beach features (August 2011): a) erosion to the south of Poço da Cruz groin; b) Mira Beach to the north of the groin.

Wave action is the mechanism that produces alongshore sand transport. In GENESIS, spatial and temporal differences in the transport rate may be caused by a range of diverse factors such as wave focusing and spreading due to irregular bottom bathymetry, wave diffraction, boundary conditions, line sources and sinks of sand and constraints on transport (such as those produced by seawalls and groins), all of which are factors that are interrelated and may function in different combinations at different times. The modelling system is generalised to a wide variety of offshore wave inputs, initial beach plan shape configurations, coastal structures and beach fills (Hanson and Kraus, 1991). The LTC model is specially designed for open sandy beaches, where the main cause of coastline evolution is also alongshore gradients in alongshore sediment transport, which is dependent on the wave climate, water levels, sediment sources and sinks, sediment characteristics and boundary conditions. Moreover, different combinations of coastal interventions (groins, longshore revetments, artificial nourishments, etc.) may be considered (Coelho et al., 2009; Coelho et al., 2011; Roebeling et al., 2011). The model is able to uniformly distribute erosion or accretion resulting from gradients in alongshore transport along the active cross-shore profiles, between the depth of closure (DoC) and the wave run-up limit. Thus, the key difference between GENESIS and LTC is the LTC ability to update the active cross-shore profile along the calculations (Coelho et al., 2007; Silva et al., 2011), while GENESIS maintains

P. Baptista et al. / Coastal Engineering 84 (2014) 23–37

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Table 2 Wave height distribution (%) and wave direction distribution (%) recorded at Leixões buoy. Hs (m)

≤0.5

0.5–1.5

1.5–2.5

2.5–3.5

3.5–4.5

4.5–5.5

5.5–6.5

6.5–7.5

7.5–8.5

8.5–9.5

TYP (Coelho, 2005) OBS (11/2003–03/2008) W7 (12/2006–03/2007) W8 (01/2008–03/2008)

1 12.6 0 0

40.3 45.1 13 14.4

31.7 25.7 27 43.5

13.3 10.9 31.1 26.3

5.6 4 20.6 10

5.1 1.3 5.4 3.3

2.1 0.4 1.9 1.4

0.7 0.1 1 0.5

0.2 0 0 0.5

0.1 0 0 0

Direction

NNW

NW

WNW

W

WSW

SW

SSW

TYP (Coelho, 2005) OBS (11/2003–03/2008) W7 (12/2006–03/2007) W8 (01/2008–03/2008)

12.1 1.9 2.2 2.9

42.4 27.5 6 22

33.9 40.9 51.4 47.8

7.7 23 36.5 27.3

1.9 4.7 2.5 0

1.4 1.3 0 0

0.5 0.8 1.3 0

the cross-shore profile shape. Near cross-shore profile boundaries, LTC allows geometrical considerations related to slope angles that may be adopted to define profile evolution (Fig. 3). LTC has to consider a more streamlined wave propagation process since in each time step the bathymetry changes due to the sediment transport gradients. GENESIS uses wave information defined through STWAVE that is a half-plane model in the sense that it only includes spectral energy directed into the computational grid at the seaward boundary. For both models, the calibration approach that was applied consisted of reproducing the shoreline evolution for the time period between 2003 and 2008, using shoreline positions extracted from the DEMs generated for both campaigns and the OBS wave climate data. Thus, it was possible to define shoreline displacement rates during that time period. In addition to the shoreline position, both models require the DoC input. In GENESIS, DoC was introduced by the user and was assumed to be equal to 12 m, in accordance with Sena (2010). The LTC model performs the calculation of DoC in each time step of the simulation, according to Hallermeier's (1978) formulation. Both models allow using the CERC formula for sediment transport estimation, and that was the formula adopted in this study. There are other parameters essential to the simulation process, such as the sediment grain size, which was set to be 0.30 mm in both models (Silva et al., 2009); the angle of repose of sediment, set to be 15° in the LTC model (representing the maximum slope allowed for the cross-shore profiles, even underwater conditions); and the height of the beach berm, considered to be 4.0 m (according to the sub-aerial DEM berm height) in the GENESIS model. The adopted values for the parameters used in the simulations are presented in Table 3, according to the considered model.

According to Fig. 1b, two coastal domains can be observed due to different shoreline evolution tendencies during the period 2003–2008: domain AB, which exhibits a pronounced erosive tendency and domain BC, where some accretion was registered (more difficult to reproduce in the models). Due to this behaviour, additionally to the total stretch AC (3.5 km long) that allow a macro-scale analysis of the entire area, the stretch AB (2.4 km long) was also considered for analysis and comparison with the numerical models. The area located south of C point was not surveyed due to anthropisation of its profile and thus, was not analysed in the models. Different parameters were considered during calibration of GENESIS and LTC. The general topo-bathymetric DEM generated for the whole study site was the same at the beginning of all the simulations. The OBS wave climate was considered in both models, always in the same chronological wave climate sequence and thus, different runs of the same situation will give the same shoreline. Appropriate boundary conditions and the definition of the coastal defense works present in the study area, as well as the sediment size, cross-shore berm height, DoC and calibration coefficients, were tested. 5. Results According to the performed calibrations, the effect of the TYP wave climate was tested for the period between 2003 and 2008 and the specific behaviour during the 2006/07 and 2007/08 winters (07 and 08, respectively) was analysed. The effect of the natural introduction of sand into the sub-aerial beach due to frontal dune undercut during high spring tides and storm events were also tested. This frontal dune erosive process, particularly evident in the course of the monitoring

Fig. 3. Schematic representation of the differences between the GENESIS and LTC models.

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Table 3 Adopted values for the parameters considered by numerical models. GENESIS D50 — median sediment grain size (mm) Average berm height (m) Closure depth (m) Longshore sediment transport coefficient 1 Longshore sediment transport coefficient 2

0.3 4 12 0.1508 0.02

programme, introduces a certain amount of sediment onto the beach that was considered as natural beach nourishment. After those evaluations, the calibrated models were applied to a medium-term evolution extrapolated scenario (10, 15 and 20 years projections, considering 2003 as the reference year). In the case of these extrapolated scenarios, the time series of 5 years wave climate data (OBS and TYP) was repeated in the same sequence until complete the number of years required for the simulations.

LTC

5.1. Observed morphological changes

Seawater characteristics ROA — seawater density (kg/m) NIU — kinematic water viscosity coefficient (m/s) KB — wave breaking depth coefficient

1027 1.36 × 10−6 0.78

Sediment characteristics ROS — sediments density (kg/m) D50 — median sediment grain size (mm) N — sediments porosity K — adimensional coefficient

2650 0.3 0.4 0.039

The alongshore variations in shoreline and frontal dune toe from seasonal and annual perspectives for the six sub-aerial beach surveys considered in the present study are shown in Figs. 4 and 5, respectively. There is a high alongshore shoreline variability for the 2006/07 winter, which exhibits an alternating pattern of erosion and accretion (Fig. 4a). This pattern can be justified by the presence of rhythmic alongshore transverse bar and rip forms in which rip currents and

Fig. 4. Alongshore variations in shoreline and frontal dune toe, considering short-term behaviours — seasonal perspective during the winters of 2006/07 and 2007/2008. a) 21st December 2006 to 9th March 2007; b) 14th January 2008 to 12th March 2008. The points A, B and C indicate the limits of the study stretches AB and AC. Negative displacements represent accretion and positive displacements indicate retreat.

P. Baptista et al. / Coastal Engineering 84 (2014) 23–37

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Fig. 5. Alongshore variations in shoreline and frontal dune toe, considering medium-term behaviours during the period between 2003 and 2012. a) 10th November 2003 to 14th January 2008; b) 14th January 2008 to 24th February 2012; c) 10th November 2003 to 24th February 2012. The points A, B and C indicate the limits of the study stretches AB and AC. Negative displacements represent accretion and positive displacements indicate retreat.

transverse bars are disposed along the foreshore area. These forms can be considered as mega or giga cups according to their wavelength. In the study zone they have in general kilometric length. This behaviour contrasts with the smooth shoreline behaviour observed during the 2007/2008 winter (Fig. 4b). The frontal dune toe exhibits more groin-dependent behaviour, which is particularly evident for the Poço da Cruz downdrift sector during the 2007/2008 winter, between 500 and 1500 m, from Poço da Cruz groin in its alongshore distance (Fig. 4b). Between 2003 and 2008 (Fig. 5a), the average frontal dune retreat for the entire coastline was 17.41 m and the respective standard deviation is 16.08 m. The computed area of retreat in this period was computed to be 60,039 m2. Taking into account an average dune height of approximately 8 to 10 m, it is estimated that the eroded sedimentary volume falls between 480,000 and 600,000 m3. Shoreline differences for the beginning and the end of the model calibration period (2003–2008) and for the period from 2008 to the present show a general shoreline and frontal dune toe retreat downdrift of the Poço da Cruz groin (Fig. 5). Between 10th November 2003 and 14th January 2008, the mean shoreline retreat for the entire study sector was 34 m and the mean frontal dune toe retreat was 17 m (Fig. 5a). For the period 2008–2012, the shoreline retreat was not as pronounced,

with an average retreat of 11 m (14th January 2008 to 24th February 2012), but exhibited a similar frontal dune toe baseline retreat, with an average of 19 m (in the same period) (Fig. 5b). A shoreline rotation is particularly evident for the period between 10th November 2003 and 24th February 2012 (Fig. 5c). The detectable changes in beach width for each survey provide additional information about the alongshore beach behaviour (Fig. 6). Short-term behaviours can be observed for the 2006/07 and 2007/2008 winters. During the 2006/07 winter, the beach width exhibited high alongshore variability, which was mainly related to the alternating pattern of the previously mentioned shoreline behaviour (Fig. 6a). During the 2007/08 winter, the beach width changes with respect to the alongshore component were not as high as those during the previous winter (Fig. 6b). In general, the beach width increased along the study site from approximately 50 m downdrift of the Poço da Cruz groin (between 0 and 2500 m south of Poço da Cruz groin) to 150 m updrift of the Mira groin (between 2500 and 3500 m south of Poço da Cruz groin) during the 2006/07 winter. During the 2007/08 winter, although it exhibited a similar tendency, the beach presented a 50% shorter width. Middle-term behaviours indicate that the greatest changes in width occurred along 2 km south of the Poço da Cruz groin, revealing the

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Fig. 6. Beach width (BW) changes during survey period, considering short-term behaviours during the winters of 2006/07 and 2007/08 and medium-term behaviours during the period 2003–2012. a) 21st December 2006 and 9th March 2007; b) 14th January 2008 and 12th March2008; c) 10th November 2003, 14th January 2008 and 24th February 2012. BW is measured from the dune toe to the shoreline. The points A, B and C indicate the limits of the study stretches AB and AC. Negative displacements represent accretion and positive displacements indicate retreat.

downdrift space scale dependence on the Poço da Cruz groin. The changes in beach width along this 2-kilometre stretch are not homogeneous in time. Between 2003 and 2008, the decrease in beach width was related to the shoreline retreat, which was more significant than the frontal dune baseline retreat (Fig. 4: 10th November 2003 to 14th January 2008). Between 2008 and 2012, an increase in beach width was observed along this 2-kilometre stretch, which was related to a more significant frontal dune baseline retreat with respect to the corresponding shoreline displacement along this stretch. Across the rest of the study site, the beach width presented a similar pattern over all survey periods. 5.2. Model calibration — period between 2003 and 2008 The OBS (used in the calibration process) and TYP wave climate were used to simulate the time period between 10st November, 2003 and 12th March, 2008. By running the calibrated GENESIS and LTC models, a shoreline estimate for the year 2008 was obtained. Fig. 7 represents, the shorelines surveyed in 2003 and 2008 and the shorelines resulting from model simulation (qualitative approach). From a general point of view, LTC and GENESIS produced different behaviours, where GENESIS performed better in the northern part of the analysed stretch and LTC in the southern part. Immediately downdrift from the Poço da

Cruz groin (near A point), when considering the TYP wave climate, the results of GENESIS are very similar to those obtained for the shoreline during the surveys. For the southern stretch (near B point), considering the OBS wave climate, the GENESIS results are again better. For the downdrift B point, the LTC model performs slightly better for both wave climates. For the BC stretch, the LTC results show the same trend of accretion that was observed. GENESIS induced accretion in an area close to the area where accretion actually occurred, though south of the precise location. According to the results obtained, shoreline retreats along the points of the modelled grid were estimated in a quantitative approach, both for the AB and AC coastal stretches, representing the stretch under only erosion and the complete stretch with both erosion and accretion (Table 4). Differences between survey and models were quantified, considering the shoreline position for each point of the modelled grid (taking into account the effective distance of the model result in each grid point, independent of advance or retreat relative to the survey). Thus, Table 4 also shows the root mean square error of the differences between surveyed and modelled shoreline positions along the coast line. Regarding OBS wave climate calibration, it was verified that both models present reasonable performance along the entire stretch (AC), with differences of up to 15% in the average retreat (Table 4). For this stretch, considering the results of each point along the coast, the root

P. Baptista et al. / Coastal Engineering 84 (2014) 23–37

31

Fig. 7. Surveyed shorelines in 2003 and 2008 and LTC and GENESIS shoreline projections, considering OBS and TYP wave climates.

mean square error of the differences between models and survey are around 120%. LTC model presents slightly better results (difference of average retreat of 10% (27.73/25.20) and differences along the coast with a root mean square error of 30.12 m) than GENESIS (difference of average retreat of 14% (28.81/25.20) and differences along the coast with a root mean square error of 29.87 m). However, for the AB stretch, the average differences in GENESIS for the surveyed behaviour are approximately 52% (21.18/40.94) and those in the LTC model are approximately 88% (36.05/40.94). For this coastal stretch, the average retreat is well reproduced by both models, with GENESIS again exceeding the observed average retreat by 15% (47.18/40.94) and the LTC average retreat being only

approximately 1% lower than the surveyed results (40.67/40.94). The TYP wave climate was considered, in accordance with the wave height and wave direction frequencies presented in Table 2 and led in general to lower average retreats for the shoreline results of both models. It was verified that both models present lower performance along the entire coastal stretch AC, with differences of up to 74% (LTC = 70% (17.72/25.20) and GENESIS = 74% (18.61/25.20)) in the average retreat (for OBS wave climate the difference is up to 15%). However, considering the results of each point along the coast, the retreat difference between models and survey for the TYP wave climate are similar to the OBS wave climate. Again, along the AB coastal stretch it is also observed that there is a lower performance in the modelled

Table 4 Shoreline retreat for the 2003–2008 period according to LTC and GENESIS simulations, considering OBS and TYP wave climates. Stretch

Surveys average retreat (m)

AB

40.94

AC

25.20

OBS wave climate

TYP wave climate

Model

Modelled average retreat (m)

Root mean square error (m)

Modelled average retreat (m)

Root mean square error (m)

LTC GENESIS LTC GENESIS

40.67 47.18 27.73 28.81

36.05 21.18 30.12 29.87

29.15 27.83 17.72 18.61

35.44 23.10 29.53 29.33

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Table 5 Sediment transport rates (×103 m3/year) for the 2003–2008 period according to LTC and GENESIS simulations, considering OBS and TYP wave climates. Transport

Section

North to south

South to north

Gross

Net (north to south)

LTC

A B C Average A B C Average A B C Average A B C Average

GENESIS

OBS wave climate

TYP wave climate

OBS wave climate

TYP wave climate

436 887 954 759 145 292 443 227 581 1180 1197 986 291 595 711 532

780 1097 1205 1027 312 454 363 376 1092 1551 1568 1404 467 643 843 651

1138 1481 1466 1362 188 151 161 167 1326 1631 1627 1528 950 1330 1305 1195

1313 1499 1502 1438 1139 1100 1097 1112 2452 2600 2599 2550 173 399 406 326

in GENESIS is approximately 1.5 times higher than that in LTC (GENESIS with 1528 × 103 m3/year and LTC with 986 × 103 m3/year of average gross transport for OBS wave climate). For the TYP wave climate, all the sediment transport components increase, representing the more energetic wave climate (GENESIS with 2550 × 103 m3/year and LTC with 1404 × 103 m3/year of average gross sediment transport for OBS wave climate). However, the highest increase is in the south to north sediment transport obtained by GENESIS, representing a general reduction in the net sediment transport volumes compared to the OBS wave climate. For LTC, with the exception of section A, the average net transport volumes are nearly the same for both wave climates. 5.3. Beach nourishment due to dune erosion

averaged retreat for the TYP wave climate (LTC with 71% and GENESIS with 68%) when compared with the OBS wave climate (LTC with 1% and GENESIS with 15%), but similar root mean square errors in the differences between survey and models. In spite of the higher and more northern waves, both models are consistent in presenting less severe erosion. However, as expected, the sediment transport volumes are higher with these wave heights and directions (Table 5 presents the annual average sediment transport rates at cross-sections A, B and C). The shoreline position is not directly dependent of the sediment volumes transported alongshore but it is dependent on its gradients. Sediment transport is naturally predominant from north to south, slightly increasing as the distance from the Poço da Cruz groin increases. The boundary conditions imposed on the models at the northern border can induce the lower sediment transport rates obtained in cross-section A (those conditions are limited by the model options related to the fixed transport volumes or fixed points of the shoreline). The sediment transport volumes remain relatively constant over time. The GENESIS volumes of net sediment transport for the OBS wave climate are similar to the results reported in the literature. According to Andrade and Freitas (2002), the net sediment transport volumes from north to south in the Aveiro region are estimated to be between 1 and 2 million m3/year. The north to south sediment transport for OBS wave climate in LTC is twice in section C (approximately 1.0 × 10 6 m 3 /year) the sediment transport in section A (approximately 0.4 × 106 m3/year). The same relation is found for TYP wave climate in the LTC model (section A with approximately 0.7 × 106 m 3/year and section C with approximately 1.2 × 106 m3/year). For the OBS wave climate in GENESIS, there is also a clear predominance of north–south transport (approximately 1.2 × 106 m3/year for net transport), which is twice the LTC model result (0.5 × 106 m3/year), representing a sediment transport ratio along the north to south and south to north directions of approximately 3.3 in LTC and 8.2 in GENESIS. The gross transport

According to topographic survey analysis, between 2003 and 2008, the dune system at Poço da Cruz Beach, downdrift of the Poço da Cruz groin, was eroded by a volume of sediments estimated between 480,000 m3 and 600,000 m3, which is in agreement with the observations presented in Section 5.1. In fact, this volume has entered the sediment transport system and thus can be considered to represent natural beach nourishment. To improve the initial modelling results, the effect of 0.5 million m3 of beach nourishment, corresponding to the erosion of the dune system, was considered. The previous calibration conditions were maintained for both models and the OBS wave climate was adopted. Three nourishment tests were performed (N1, N2 and N3), which differed in the locations of nourishment areas and in the simulation periods of their occurrence. In test N1, nourishment was supplied to the BC stretch, corresponding to the location where accretion occurred. In test N2, the sediment supply was considered to be along the AB stretch, which corresponds to the main area of frontal dune erosion. Finally, test N3 corresponds to nourishment located along 1 km of the shoreline extension, centred at cross section B. In the first test, the nourishment was distributed throughout the entire simulation period, while in the other two cases it was distributed throughout the first year of simulation, allowing the models time to simulate the transport of the sediment downdrift (Table 6). No evidence of significantly better simulation performance was obtained from these tests due to the small significance of the nourishment contribution to the overall sediment transport capacity. The average absolute difference between the surveyed and modelled shoreline positions are relatively close to the values resulting from the simulation without nourishment. By comparing the root mean square error between the differences of survey and modelled shoreline positions in N1, N2 and N3 tests (indicated in Table 6) with the simulations without nourishment (indicated in Table 4) it can be observed close values for N1 and N3 tests, when OBS wave climate are considered. For the entire coastal stretch AC considering the results of each point along the coast in N1 test, the root mean square error of the retreat difference between models and survey is 32.98 m for LTC (30.12 m without sand nourishment) and is 30.67 m for GENESIS (29.87 m without sand nourishment). For the AB stretch in the same test, the root mean square error of the retreat difference between models and survey is of 36.31 m for LTC (36.05 m without sand nourishment) and is 21.14 m for GENESIS (21.18 m without sand nourishment).

Table 6 Shoreline retreat (m) for the 2003–2008 period according to LTC and GENESIS simulations, considering OBS wave climates and 3 nourishment tests (N1, N2 and N3). Stretch

AB AC

Model

LTC GENESIS LTC GENESIS

N1

N2

N3

Modelled average retreat (m)

Root mean square error (m)

Modelled average retreat (m)

Root mean square error (m)

Modelled average retreat (m)

Root mean square error (m)

42.03 42.66 19.15 18.16

36.31 21.14 32.98 30.67

34.97 1.19 23.60 9.73

33.49 44.38 28.06 43.55

42.68 41.31 28.36 20.71

35.76 20.09 30.71 27.93

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In N3 test, considering also the results of each point along the coast, the root mean square error is 30.71 m and is 35.76 m for LTC in AC and AB stretches, respectively; and is 27.93 m and 20.09 m for GENESIS in AC and AB stretches, respectively. Only test N2 presents higher differences for the GENESIS simulations with root mean square errors of 43.55 m and 44.38 m, respectively for AC and AB stretches. The average retreat obtained in both models for the AC stretch decreases for test N1 (modelled average retreat of 19.15 m in LTC and 18.16 m in GENESIS for N1 test) in relation to the modelled averaged retreat without nourishment (27.73 m in LTC and 28.81 m in GENESIS, according to Table 4), due to the location of the nourishment in BC. However, according to the LTC model, erosion increases to the north (42.03 m for N1 test in contrast with 40.67 m without sand nourishment); in contrast, GENESIS shows a decrease in erosion to the north (42.66 m for N1 test in contrast with 47.18 m without sand nourishment). The nourishment of the AB stretch during the first year of simulation (test N2) led to a decrease in the modelled average retreat over the entire AC stretch. In GENESIS, the resulting erosion is significantly lower (9.73 m for test N2 in contrast with 28.81 m without sand nourishment). LTC results were slightly improved in the root mean square error along the coastal stretch for N2 test, in contrast to what was observed with GENESIS. In test N3, the average retreat increases according to the LTC model (28.36 m for AC stretch and 42.68 m for AB stretch in contrast with 27.73 m and 40.67 m for AC and AB stretches, respectively, without sand nourishment) and decreases according to the GENESIS model (20.71 m for AC stretch and 41.31 m for AB stretch in contrast with 28.81 m and 47.18 m for AC and AB coastal stretches, respectively, without sand nourishment). Some of the differences in the models' behaviours and results for these tests are related to the different approaches used to treat sediment distribution during nourishment. GENESIS only allows beach nourishment distribution along the active cross shore profile, from the DoC to the berm. With LTC, the position of the sediments can be defined by the user and only a small width of approximately 200 m was considered, which was located between approximately 100 m and 300 m from the shoreline.

5.4. Seasonal behaviour — winters Based on the previous calibration, an analysis of the performance of the models for both winters (07 and 08) was performed (Table 7). The surveyed winters were not representative of the behaviour that is typically observed because primarily accretion was observed during those periods. Between 21st December, 2006 and 09th March, 2007, the study area (stretch AC) was mostly under accretion (− 1.08 m) and LTC reflects this trend, although with an average value much higher than that registered by the survey (− 12.72 m). However, erosion occurred in stretch AB (1.18 m), which was predicted by the GENESIS model (1.43 m). Between 14th January, 2008 and 12th March, 2008, greater accretion occurred in both of the considered stretches (− 7.03 m for AC stretch and − 6.68 m for AB stretch) and this behaviour was well represented by LTC in both sign and magnitude

Table 7 Shoreline retreat (m) according to LTC and GENESIS simulations during winters. Stretch

AB AC

Model

LTC GENESIS LTC GENESIS

07 (12/2006–03/2007)

08 (01/2008–03/2008)

Survey average retreat (m)

Modelled average retreat (m)

Survey average retreat (m)

Modelled average retreat (m)

−14.10 1.43 −12.72 1.91

−6.68

−9.42 0.17 −8.92 1.00

1.18 −1.08

−7.03

33

Table 8 Shoreline retreat (m) for the 2003–2012 period and expected shoreline retreat according to LTC and GENESIS simulations for a 10-year horizon scenario, considering OBS and TYP wave climates. Stretch Surveys Model average retreat (m)

AB

64.45

AC

41.67

OBS wave climate

TYP wave climate

Modelled Root mean Modelled Root mean average square average square retreat (m) error (m) retreat (m) error (m)

LTC 79.59 GENESIS 110.51 LTC 66.30 GENESIS 70.05

18.81 52.30 31.89 47.67

84.81 43.14 55.74 30.60

44.70 29.99 36.66 29.98

(Table 7) which shows accretion on both stretches (− 8.92 m for AC stretch and −9.42 m for AB stretch). Again, GENESIS does not represent any occurrence of accretion on either stretch (1.00 m for AC stretch and 0.17 m for AB stretch).

5.5. Model verification — 10-year projection compared with 2012 survey Considering the previous calibration of both models, a 10-year simulation, starting with the 2003 conditions, was performed to establish a comparison between the results obtained by the numerical models and the survey performed on 24th February, 2012. Both wave climates (OBS and TYP) were considered for these extrapolations. As previously mentioned the time series of 5 years of OBS and TYP wave data was repeated in the same sequence until the number of years required for the simulations is complete. For the OBS time series this procedure ensures the seasonality of the short term wave regimes and the inherent wave frequencies for the extrapolated data. The variations in shoreline position between 2003 and 2012 were estimated with the corresponding average retreats (which were compared to the average retreat obtained from the survey). These results are shown in Table 8 and the surveyed and modelled shorelines are shown in Fig. 8. Considering the field surveys carried out in the study area, approximately 60% of the total shoreline displacement between 2003 and 2012 occurred before 2008 (60% (25.20/41.67) for AC stretch and 64% (40.94/64.45) for AB stretch). With the OBS wave climate, modelling simulations predicted a higher average retreat of the shoreline than what actually occurred (LTC modelled average retreat of 66.30 m and 79.59 m for AC and AB stretches, respectively, in contrast with survey average retreats of 41.67 m and 64.45 m for AC and AB stretches, respectively); this was especially true for GENESIS (modelled average retreat of 70.05 m and 110.51 m for AC and AB stretches, respectively), which predicted erosion rates that were approximately 70% higher (68% for AC stretch (70.05/41.67) and 71% for AB stretch (110.51/64.45)) than the surveyed ones. Considering the TYP wave climate, the simulations provided by LTC represent 30% higher retreat rates than the surveyed ones (55.74/41.67 for stretch AB and 84.81/64.45 for stretch AC), while GENESIS on average predicted less erosion than what was actually observed (73% for AC stretch (30.60/41.67) and 66% for AB stretch (43.14/64.45)). Analysing the root mean square error between the surveyed and modelled results, LTC shows the smallest differences under OBS wave climate conditions, in contrast to GENESIS, which presents the highest differences. GENESIS presents better behaviour for TYP wave climate conditions. The root mean square error along the coast between the surveyed and the modelled shoreline projections is between approximately 29% (18.81/64.45 from Table 8 for LTC with OBS wave climate for stretch AB) and 114% (47.67/41.67 from Table 8 for GENESIS with OBS wave climate for stretch AC) of the actual retreat observed. Those values may represent the degree of uncertainty in the modelling projections, suggesting that this type of analysis should incorporate a range of shoreline positions instead of a single shoreline projection.

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Fig. 8. Surveyed shorelines in 2003 and 2012 and LTC and GENESIS shoreline projections, considering OBS and TYP wave climates.

As observed in Fig. 8, the best results are obtained for stretch BC, where the obtained shorelines for the TYP wave climate are very similar to those recorded by the survey. All other situations present some significant differences (Table 8). For the OBS wave climate in stretch AB, LTC presents good agreement with the surveyed shoreline in 2012, while GENESIS produces higher erosion rates. For the updrift and downdrift neighbourhoods of section B, GENESIS shows better performance, but when moving towards section C, none of the models represents the actual behaviour of the shoreline (LTC predicts too much erosion and GENESIS indicates accretion). For the TYP wave climate in stretch AB, the models do not reproduce the surveyed shoreline, particularly in the northern part of the stretch. LTC predicts too much

Table 9 Expected average shoreline retreat (m) based on LTC and GENESIS simulations, for 15- and 20-year horizon scenarios. Stretch

AB AC

Model

LTC GENESIS LTC GENESIS

15 years

20 years

OBS wave climate

TYP wave climate

OBS wave climate

TYP wave climate

127 157 115 106

100 53 68 40

190 214 166 150

109 59 80 45

erosion and GENESIS predicts less retreat than that observed for the surveyed shoreline. 5.6. Model projections — 15- and 20-year scenarios Considering 2003 as the reference year, an extrapolation of the shoreline evolution over 15- and 20-year horizons was performed based on typical trends and previous calibrations. Table 9 and Fig. 9 present the main results. Both models allow for the prediction of significant erosion for this coastal stretch, if the actual conditions remain the same (maintaining the existing coastal defence structures, not considering new structures or artificial nourishments). As can be observed in the qualitative approach presented in Fig. 9 erosion rates are higher near the Poço da Cruz groin because the average retreat in stretch AB is higher than that in stretch AC for any model or wave climate considered. Over time, results were similar for both models, with erosion increasing from the 15-year to 20-year simulations. The retreat rates show a decreasing tendency over time, mainly in the TYP wave climate, where 85% to 92% of the 20-year retreat was obtained in the first 15 years. For these simulations, the LTC and GENESIS results indicate higher retreats under OBS wave conditions (127 m and 115 m for LTC and 157 m and 106 m for GENESIS in AB and AC stretches, respectively) in comparison with TYP wave climate (100 m and 68 m for LTC and 53 and 40 m for GENESIS, in the same respective stretches) considering in

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35

Fig. 9. LTC and GENESIS shoreline projections for 15- and 20-year horizon scenarios, considering OBS and TYP wave climates.

both cases 15-year simulations, which is in accordance with the results obtained during the models' calibration. A significant dependence on the considered wave climate is highlighted by these simulation results. For the OBS wave climate, GENESIS shows a higher rotation of the shoreline (clockwise), inducing important retreats to the north and some accretion in the southern stretch as can be observed in the qualitative approach presented in Fig. 9. In this wave climate, the LTC erosion rates are more uniform along the entire stretch, representing mainly a translation of the shoreline position, with a small rotation. As indicated before, considering TYP wave conditions, the shoreline position after 15 years is similar to the position after 20 years and this is the same for both models. With TYP wave climate, the shoreline rotation is higher in the LTC model than in GENESIS (Fig. 9). 6. Discussion This work is intended to be a first approach in evaluating the performance of two shoreline evolution models calibrated and validated with real data acquired within the scope of a monitoring programme. The results obtained for the calibration period and verification test indicate some differences between the shoreline predictions and observed shoreline positions. One notable aspect is related to the conditions that are assumed in the calibration process and should have affected the obtained results. Another aspect is related to the evaluation of the differences between positions of the observed shoreline evolution and the modelled shoreline evolution. Concerning the monitoring variables, the shoreline indicator used for the calibration was the MSL contour line. This indicator, due to its high sensitivity to cross and alongshore sand transport reproduces with high precision the alongshore migration of the transversal sand

bars, in accord with progressive alongshore changes in the rip channel position, but could not be the best reference for the calibration of medium- to long-term shoreline evolution models due to its dependence on short-term wave parameters. Future work must be carried out to test other tidal datum shoreline indicators that are less sensitive to short-term beach changes. With respect to the GENESIS and LTC models, the boundary conditions of the modelled grid, where sediments in transport should be well known and controlled, cannot be well represented on open coasts. Models define a permanent situation over time (constant volumes going into or out of the study area, fixed points of the shore, etc.). This situation is difficult to exist under real conditions, in which an initial situation without sediment transport becomes into a situation with permanent and variable sediment transport rates over time. The presence of new transversal defence structures, as was observed in the presented case (new Poço da Cruz groin concluded in 2003), may represent, in the short term perspective (1–5 years), an obstacle to downdrift sediment transport but is not an obstacle to permanent sediment transport once by-passing begins. Trying to reduce the effect of this condition, the modelled grid was extended to the north of the study site, but some differences may arise from the volume of sediments that transpose the head of the groin over time and was not considered. The results clearly show some differences between the LTC and GENESIS models. The difference between the two models regarding the models' verification process reaches 50% in the worst scenario for the same wave climate variables and 25% (according to Table 8) between the LTC model projections and actual results surveyed along the shoreline (or 100% for GENESIS in the worst scenario). The differences between the models are justified by considering the models' capacity to integrate some variables as previously mentioned in

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Section 4 (Fig. 3). LTC varies the bathymetry in accord with geometric considerations, and topography in accord with real survey data, during calculations taken into account the slope conditions imposed by the user. GENESIS maintains the cross-shore profile over time. Because of this, wave propagation in LTC is processed step by step by considering bathymetric changes over time. GENESIS wave propagation is independent of the profile changes over time because the same profile shape is always maintained. The boundary conditions and the differences between the models reflect important aspects of the shoreline evolution study. These are related to the uncertainty of the future wave climate and the short-term changes in local forms of the beaches make it difficult to predict the shoreline position. Each of these factors contributes to the discrepancy between the real shoreline position and the modelled shoreline positions. With the actual available information and taking into account the previously mentioned medium- to long-term model limitations, differences of the same order of magnitude between the real data and model results in the model verification process are considered acceptable. Information regarding dune erosion, which was considered artificial sand nourishment, did not significantly improve the obtained results and due to that was not considered in the calibration process. GENESIS considers the variation in shoreline position during the calculations and thus should improve the results by adding the sediments to the system. LTC changes the topography during calculations; thus, the volumes of sediments that are eroded from the dune should automatically be considered in the simulation. However, these different approaches of the models and the nourishment considerations did not allow for such improvements. The difficulty in reproducing the coastal stretch behaviour for a short time period (winters) is also evident. This is mainly due to seasonal beach dynamics (due to the previous mentioned cross and alongshore sand transport and the inherent alongshore migration of the transversal sand bars) that are not represented by the models when applied to medium- to long-term shoreline evolution predictions. The winters of 2006–2007 and 2007–2008 presented some seasonal changes or a short-term evolution of the beach that did not correspond to shoreline evolution trends and thus are not well described, in some cases, by the shoreline evolution models. As an example, in 2006–2007 winter, which is the winter with higher alongshore shoreline variations, the mean shoreline retreat is − 1.0 m and the standard deviation of the shoreline retreat, that represents the seasonal shoreline variations, is 33.0 m. This means that the noise (shoreline variations) is much higher than the signal (shoreline retreat) and as can be observed in Table 7, LTC modelled average retreat in this case exceeds (factor 12) the survey average retreat (less than factor 2 for GENESIS in the same conditions). In order to reduce the influence of the short term shoreline variations, in model calibration process, and as consequence in the 2012 and 15- and 20-year projections, the present work model calibration only considers 2003 and 2008 shorelines (mean shoreline retreat of 34.0 m and standard deviation of 25.0 m). The medium term shoreline data, although it uses the same shoreline indicator, and has the inherent dependence on short-term wave parameters, is less sensitive to the short term variations. So, model projections for 2012 and 15- and 20 year scenarios are more influenced by the shoreline retreat signal than by the shoreline fluctuation noise (bars and other seasonal morphologic features). After calibration, the numerical models reproduce specific shoreline behaviours relatively well. For the calibration period, the average shoreline retreat of the analysed coastal stretch was reproduced with small differences (around 1% and 10% for LTC and 15% and 14% for GENESIS, considering the stretch with the more erosive tendency AB or the entire stretch AC, respectively), but looking at the root mean square error, the differences along the AB coastal stretch reached up to 52% (21.18/40.94) or 88% (36.05/40.94) for GENESIS and LTC, respectively, and were around 120% (30.12/25.20 and 29.87/25.20) for both models along AC

coastal stretch (Table 4). However, the extrapolation of those results over time needs to be carefully interpreted. The general average behaviour could be similar to the real stretch behaviour, although in specific locations the results may exhibit significant differences. It is difficult to simultaneously reproduce the shoreline retreat rates and the sediment transport volumes. According to Andrade and Freitas (2002) the net sediment transport rate (north to south) in the Portuguese west coast is situated between 1 and 2 × 103 m3/year. GENESIS presents sediment transport estimations closer to the reference values for Portuguese coast, while LTC underestimates the sediment transport reference values. On the other hand the 2012 predictive shoreline retreat values obtained under the simulations, for the entire coastal sector AC, when compared with the real shoreline retreat values, also for the entire sector, allow the observation that both models produce better results, when it is considered a TYP wave climate (Table 8). In this wave climate the LTC modelled average retreat is 33% higher that the surveyed average retreat and GENESIS retreat is 27% lower than the surveyed average retreat. The 15-year scenario (2017 horizon), with TYP wave climate, indicates a shoreline retreat of 4.5 m/year for LTC and 2.6 m/year for GENESIS (4.0 m/year for LTC and 2.25 m/year for GENESIS in the 20-year scenario that corresponds to 2022 horizon). These values when compared with the erosion rates, determined in the past for the entire study site by Dias et al. (1994) (2.0 m/year for the period 1980–1990) and more recently by POOC (2012) (0.6 m/year for the period 1970–1998 and 5.2 m/year for the period 2006–2010), allow the observation that LTC projections (2017 and 2022 horizon) follow the most recent observations (Table 1). The trends presented by both models show continued erosion in the future and the aggravation of this coastal stretch situation. However, the LTC and GENESIS models present some differences regarding the expected results. LTC results are closer to the most recent observed shoreline retreat values (POOC, 2012), mainly when it is considered the most erosive coastal stretch (AB). However, despite the differences between model results, in future studies, a range of possible shoreline positions instead of a unique final shoreline must be considered. 7. Conclusion The present work compares the performance of two numerical models (LTC and GENESIS) for forecast shoreline position scenarios for decadal temporal scales. In this study the models were calibrated with observed waves, recorded by a wave buoy, and real shorelines acquired in the scope of a monitoring programme for a coastal sector with a 5-kilometre extension and limited by two groins. The calibration period corresponds to five years of observed waves with two reference shorelines acquired in the beginning and at the end of this period (2003–2008). The simulation scenarios of shoreline behaviour were established for time horizon up to three times the calibration period (10-, 15- and 20-year projections that correspond to 2012, 2017 and 2022 time horizons). In the first simulation scenario the models' simulated shorelines are compared with the real surveyed shorelines. In this aim the use of non-observed wave data in models' simulations provides the opportunity to verify the accuracy of the predicted shorelines in the short term scenarios. The obtained results allow us to conclude that both models' (LTC and GENESIS) projections produce an accuracy degree that is highly sensitive to the adopted wave data. In general the errors in the models' shoreline projections are of the same order of magnitude of the observed shoreline results. LTC overestimate the retreat rates, which are 30% higher than the observed retreat, while GENESIS underestimates the retreat rates (70% lower retreats) considering in both cases wave data representative of the study site wave climate (TYP). The models' forecast scenarios for 2017 and 2022 time horizons must be analysed taking into account the uncertainty degree produced in model verification, although it must be pointed out that the decreasing tendency of predicted shoreline retreat over time suggests a lower model dependence from high frequency

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processes as is the case of the wave climate seasonality and the short term changes in local forms. Despite the differences between LTC and GENESIS in the shoreline evolution projections the presented composite approach that include monitorisation and modulation (whose quantitative evaluation can be checked and improved in future through long-term wave and morphological data in order to generate better estimates), can be considered as a first step towards an integrated coastal management plan. In this aim the progressive erosion trend observed along the last years in the study site considered in this work, in which the most important coastal protection forms (frontal dunes) have been destroyed, and the medium term shoreline evolution scenarios here presented provide strong arguments to the coastal management entities in order to define a more structured intervention plan. In the scope of the present strategy for integrated coastal zone management, the establishment of scenarios of shoreline evolution in sandy shores contributes to the final settings of management goals related with identification of sensitive areas and the associated problems (frontal dune overwash and inundation of inner zones) and the definition of temporal horizons for future interventions. Acknowledgements This work was been supported by FCT within the framework of the research project PTDC/AAC-CLI/100953/2008 — ADAPTARia: Climate Change Modelling on Ria de Aveiro Littoral — Adaptation Strategy for Coastal and Fluvial Flooding. Paulo Baptista was supported by the Fundação para a Ciência e a Tecnologia, grant reference SFRH/BPD/63141/2009. References Andrade, C.F., Freitas, M.C., 2002. Climate change in Portugal — scenarios, impacts and adaptation measures — SIAM Project. . Chapter 6 In: Santos, F.D., Forbes, K., e Moita, D. (Eds.), Coastal Zones. Gradiva, Lisbon (456 pp.). Baptista, P., Bastos, L., Bernardes, C., Cunha, T., Dias, J., 2008. Monitoring sandy shore morphologies by DGPS — a practical tool to generate digital elevation models. J. Coast. Res. 24 (6), 1516–1528. Baptista, P., Bernardes, C., Cunha, T.R., 2011a. The validation analysis of the INSHORE system — a precise and efficient coastal survey system. Environ. Monit. Assess. 179 (1–4), 589–604. Baptista, P., Cunha, T., Bernardes, C., Gama, C., Ferreira, Ó., Dias, J., 2011b. A precise and efficient methodology to analyse the shoreline displacement rate. J. Coast. Res. 27 (2), 223–232. Boak, E.H., Turner, I.L., 2005. Shoreline definition and detection: a review. J. Coast. Res. 21 (4), 688–703. Coelho, C., 2005. Riscos de exposição de frentes urbanas para diferentes intervenções de defesa costeira (Exposure risk of urban waterfronts, for different coastal defense interventions). . PhD thesis University of Aveiro, Portugal (404 pp. (Portuguese)). Coelho, C., Veloso-Gomes, F., 2006. Crosshore beach profile models — application to Aveiro coast. 8th International Coastal Symposium; Santa Catarina, Brasil. J. Coast. Res. SI 39, 345–350. Coelho, C., Taveira-Pinto, F., Veloso-Gomes, F., 2004. Coastal evolution and coastal works in the southern part of Aveiro lagoon inlet, Portugal. Proceedings of the 29th International Conference on Coastal Engineering, Lisboa, Portugal, 4, pp. 3914–3926. Coelho, C., Veloso-Gomes, F., Silva, R., 2007. Shoreline coastal evolution model: two Portuguese case studies. Coastal Engineering 2007. Proceedings of the 30th International Conference, 4, pp. 3430–3771. Coelho, C., Silva, R., Veloso-Gomes, F., Taveira-Pinto, F., 2009. Potential impacts of climate change on NW Portuguese coastal zones. ICES J. Mar. Sci. 66, 1497–1507. Coelho, C., Silva, R., Veloso-Gomes, F., Rodrigues, L., 2011. Artificial nourishment and sand by-passing in the Aveiro inlet, Portugal — numerical studies. Proceedings of the International Conference on Coastal Engineering, No. 32 (2010), Shanghai, China. Cunha, T., 2002. High precision navigation integrating satellite information — GPS — and inertial system data. Ph.D. Thesis Faculty of Engineering of the University of Porto, Portugal (223 pp.).

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