2.10.3.- Comprobación a deformación

The stability of the foreshore is affected by major changes in wave penetration, storm magnitude and frequency, and also is a function of sediment erosion. In coastal vulnerability and impact assessments, dynamic controls that affect a particular coastal environment need to be studied. Hence some of the most important drivers in coastal research studies are:

Rate of relative sea-level rise (RSLR)

Historical rates of relative sea-level rise have always affected sections of the shoreline. Past sea levels have increased the amount of time the coast has been exposed to extreme storm surges and is therefore important in assessing its relative vulnerability to RSL (Zhang et al., 1997). As coasts do respond over time (centuries to millennia) these changes have nothing to do with current SLR trends, present shoreline patterns are better explained in terms of sea-level history. Impacts of sea-level rise are not only determined by the global trends (eustatic), but also regional and local variations and tectonic uplift or subsidence. The combination of sea-level rise and vertical land movements (isostatic changes) at a particular position at the coastline results in relative sea-level rise rate (PSMSL, 2010). See Figure 4.2.

Figure 4. 2 .Relative sea-level in mm/yr from 1900-2016 trends for Europe (not corrected for local subsidence). Source: Woodworth and Player, 2003; Permanent Service for Mean Sea Level (PSMSL, 2017; 'Tide

Gauge Data' (http://www.psmsl. org/products/trends).

Most relative sea-level changes, locally and regionally, are due to meteorological and oceanographic factors such as oceanic circulation, thermal expansion, wind and atmospheric pressure changes, variations in Earth’s gravity and vertical land movements and other minor factors such as river discharge changes (Nicholls et al., 2011). Relative sea-level rise effects will vary spatially causing permanent and/or gradual inundation depending on uplift-subsidence mainly (Carter et al., 2007; Meehl et al., 2007 in IPCC, 2007). The historical record of sea-level change combined with other variables is critical in coastal impact and vulnerability assessments (Gornitz, 1990; Gornitz et al., 1994; Thieler et al., 2000; Sharples, 2006; Pendleton et al., 2010; IPCC, 2014). A suitable relative sea level analysis is extremely valuable for projecting future local sea-level rise scenarios and for driving impact models of future extreme events (Warrick, 2009, 2007; Nicholls et al., 2011; Yin and Urich, 2013).

Changes in wave climate

Wave climate is of particular interest as the energy imparted to waves by winds in the offshore region is finally dissipated on the coastline and used to transport and distribute sediments. Transport of sediments at the coast mainly occurs during storms by the combinations of waves and tides, storm surges action, and these vary geographically. There are reports that the significant wave height has increased in North Atlantic mid- latitudes (WASA Project, 1995; Woolf et al., 2002; IPCC, 2014).

Future wave climate will be more threatening to our coasts. Larger sea-levels increase the average annual/significant wave energies and can result in more significant changes on the coast (Sharples, 2006; Kelm et al., 2004) reshaping tidal basins and estuaries and even producing the rotation of beaches (Pickering et al., 2012). Most of the beaches in the study area are so-called drift-aligned systems, so a change in wave climate may greatly affect the shoreline (Orford et al., 2002; Alegria- Arzaburu and Masselink, 2010). Small changes in wind patterns will also influence wave climate, and both will adjust coastal sediment and erosion processes (Dawson et al., 2009).

Annual mean significant wave height is an indicator of wave energy, which is indicative of the total average annual swell and storm wave energy received over time and overtopping discharge (Pendleton et al., 2010; Sierra et al., 2016) (Figure 4. 1). Wave direction and long period swell influence erosion rates and can produce damages to coastal structures and major flooding, particularly those with steep shelf or slopes (Semedo et al., 2011; Hoeke et al., 2013). Hence, wave direction has been used as proxy in many coastal vulnerability indices and also in this research (Gornitz, 1990; Gornitz et al., 1994; Thieler et al., 2000; Mclaughlin, 2001; Sharples, 2006; Dwarakish et al., 2009; Pendleton et al., 2010; Mclaughlin and Cooper, 2010).

E = 1/8 ρgHs2

Equation 4. 1. Energy density proportionality to significant wave height.

where E= energy density, Hs= significant wave height (the highest third of the waves (H1/3)); ρ =water density; and g = acceleration gravity (Pond & Pickard,1983).

Changes in storminess and extreme water levels

Storm-surges are associated with strong or prolonged winds, wave activity controlled by wind stress at the surface and low pressure systems moving at the same speed as the tidal wave in the open sea. The effect of wind on sea-level largely depends on the topography of the area as a storm surge entering shallow water (gentle continental self) also increases in height (Lowe, 2001). Also, a barometric pressure of 1mb below the average will result in an increase of 10mm of sea level (ECOPRO, 1996). Changes in frequency, direction and intensity of storms will expose different parts of the coast and influence its vulnerability, increasing the magnitude and frequency of extreme coastal flooding events (Flather and Smith, 1998; IPCC 2007; 2013). Stronger storm conditions will aggravate coastal morphological impacts, particularly around estuaries, lowering the beach and increasing wave erosion on newly exposed tills and soft cliffs (Devoy, 2000; Church et al., 2006; Wang et al., 2015). Sea-level rise and changes in storm tracks will reshape local bathymetry in European margins (Storch and Weisse, 2008). Recently, changes in mean-sea level rise and storm surge height have been detected in Western Europe instigating flooding and more changes are expected in the future (Nicholls and Cazenave, 2010; EEA, 2012; Weisse et al., 2014; Ferreira et al., 2017).

There is evidence that changes in extreme sea levels are consistent with changes of global mean sea level (GMSL) rather than weather patterns (Marcos et al., 2009; Haigh et al., 2010; Menendez and Woodworth, 2010; Losada et al., 2013) and that they will negatively impact coastal systems (IPCC, 2014). Hydrodynamic models forced by climate models for the Northeast Atlantic showed strong sensitivity to changes in GMSL and RCP’s scenarios (IPCC, 2013; Debenard and Roed, 2008; Wang et al., 2008; Sterl et al., 2009). Consequently, evaluating the exposure of coastal areas to potential extreme water levels exacerbated by sea-level rise, is very important in future coastal vulnerability analysis (Brown and Wolf, 2009; Mendoza & Jiménez, 2009; OPW, 2010; Bosom & Jiménez, 2011; Bonetti et al., 2012).

4.3.3. Non-Climatic drivers

Tides

High tides and waves combined with strong winds have a profound impact on modelling our coastal landscape. Tide raising forces generate a tidal wave of approximately 0.5m in large oceans. However, as it approaches the coast, the shallower water causes the tidal wave to shoal and increase in height. Sometimes it can also reach higher heights due to the existence of the shallow continental shelf and the funnel-shape of the estuary (ECOPRO, 1996). Surges in water level may take a number of days to disappear and for the tide to return to predicted levels. Some authors consider than microtidal regimes pose a higher threat to coastal systems than macro tides as water levels remain higher for longer periods in between high and low-tides (Mclaughlin and Copper, 2010; Pendleton et al., 2010).

In a warmer future, surges might be quite significant when higher water levels coincide with high spring tides. This could increase the risk of lowland coastal flooding and cause drastic changes to coastal geomorphology (Lowe, 2001; Brown et al., 2009). Despite the relatively small size of the study area, tidal regime variability was significant enough to be considered as a relevant indicator for this study, as it has been in large-scaled studies (Gornitz, 1990; Gornitz et al., 1994; Thieler et al., 2000; McLaughlin, 2001; McLaughlin and Cooper, 2010; Pendleton et al., 2010; Gutierrez et al., 2011).