Beach modelling I: Beach erosion occurrence and causes. Adonis F. Velegrakis Dept Marine Sciences University of the Aegean. Synopsis. 1 Significance of beaches to other ecosystems and economic activity 2 Coastal erosion 3 Causes of beach erosion 4 Climate change: a short review
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Beach modelling I: Beach erosion occurrence and causes
Adonis F. Velegrakis
Dept Marine Sciences
University of the Aegean
1 Significance of beaches to other ecosystems and economic activity
2 Coastal erosion
3 Causes of beach erosion
4 Climate change: a short review
4.2 The mechanism
4.3 The future
4.4 What scenario
5. Erosion costs and adaptation
Beaches, i.e. the low lying coasts built on unconsolidated sediments, are valuable ecosystems by themselves; they also, front/protect various other important back-barrier environments/ecosystems
Beaches protect very important coastal economic assets/infrastructure and activities from marine inundation
Beaches are very important assets by themselves, being the focus of the very large and lucrative ‘sun and beach’ tourist industry; islands, in particular, depend on their beaches for most of their income.
Beaches are considered as particularly vulnerable to climate change, likely to bear the brunt of the adverse impacts of climate change, particularly through coastal retreat/erosion
Coastal (beach) erosion, i.e. the retreat of the coastline (which may or may not be accompanied by reduction in the beach sediment volume), is a global phenomenon
It can be differentiated into:
Both can be devastating
Major causes of beach erosion include:
One the most potent drivers of beach erosion are the climatic changes, i.e.
Note: Beach response to climatic changes is a non-linear process; it (mainly) depends on the magnitude/rate of sea level rise, beach slope and morphology, the impinging (and generated-infragravity) wave energy and the intensity, duration and frequency of storm surges and the nature of coastal sediments
Our knowledge on these processes is still incomplete and, thus, predictions are characterised by a large uncertainty
4.2 Mechanism: what are the processes involved?
Predictions of future changes are characterised by uncertainty and, thus, there is a large range of predictions,
Predictions depend on:
Few integrated, comprehensive studies on the ecological and socio-economic impacts of climate-change driven beach erosion
The best studies undertaken in the US, UK and the Netherlands
These studies highlight the huge socioeconomic and environmental costs of the ‘do nothing’ attitude and the large costs of the inevitable adaptation For example, it is predicted that in 2050 (at least) 124 million people and assets of 28 trillion US $ will be at risk of coastal inundation at the 136 coastal megacities
The evidence suggests that we have no other choice but to get prepared for a huge adaptation effort that will be based on sound science and engineering.
If beaches (and/or coastal defences) are breached, then large tracts of back-barrier ecosystems (e.g. wetlands and saltmarshes) are under a deadly threat
The Netherlands disaster case (Mollema, 2009).
Coastal housing destruction, following short-term (catastrophic) beach erosion
Fig. 2 S. Carolina (US) beach (c) before and (d) after a storm event in September 1996 (USGS, 1996)
Coastal transport infrastructure
Sochi, S. Russia
Fig. 3 The main railway line to Sochi in Black Sea will be in jeopardy, if the fronting beach would be eroded – which, will be (red line) under 1 m storm surge and offshore waves with height (H) = 4 m and period (T) = 7.9 sec.
Leont’ yev Model
Present normal conditions
Storm surge 1 m
US Gulf Coast inundation risk
Fig.4 (a) Flood risk at US Gulf coast under sea level rise of 0-6-1.2 m (MSL+storm surge); such rise could inundate > 2400 miles of roads, > 70% of the existing port facilities, 9% of the rail lines and 3 airports.
(b) In the case of a ~5.4-7 m rise (MSL+storm surge), > 50% of interstate and arterial roads, 98% of port facilities, 33% of railways and 22 airports could be affected (CCSP, 2008).
Fig. 5. Super Paradise (Mykonos). A pocket beach with very large economic potential. Economic value of Greek beaches min €1400/m/yr. This beach, €60000/m/yr.
Examples of beach erosion
Coastal erosion in Europe
Source: Eurosion, 2004
Coastal development planning/engineering time scales must take into consideration future climate
Potential length of service
Adapted from Savonis (2011)
Long-term beach erosion
Fig. 7 Beach erosion since the 1945 in Morris Island, S. Carolina, US (SEPM, 1996)
bunkers built in
Source J-P. Tastet
Fig. 9Nearshore bed cover and shoreline changes along Negril’s beaches (at the location of the 74 used beach profiles (RiVAMP, 2010)
Fig.10 Long-term and short-term (catastrophic beach erosion, Eressos beach E. Mediterranean
Fig.11 Trends in total annual stream flow into Perth dams 1911–2008. (Steffen, 2009)
Fig. 12 Coastal sediment supply in the Med has been reduced from 1012 x 106 σε 355 x106 tons/yr during the second half of the 20th century due to the presence of about 3500 dams, 84% of which have been constructed during this period (Poulos et al., 2002).
Fig. 13 (a) The damand the Eressos drainage basin/beach, (c) monthly time series (2004) of (potential) sediment load (in tons) of the Eresos basin (black) and the sub-basin of the dam (white), for steady and high intensity (simulated) rainfall for 2 soil cases (i) sand soil (K=0.03) and (ii) silt soil (K=0.52). The dam witholds 52-55% of the sediments produced in the drainage basin
Fig. 14 Eressos, Lesbos, E. Med 27-2-2004. The beach, the river and the dam, which
Fig. 15 Sea level rise at Pensacola (FL) 2.14 mm/yr, Grand Isle (LA)- 9.85 mm/yr, and Galveston (TX)- 6.5 mm/yr. These trendsshow the high rates of local subsidence in Louisiana and Texas relative to the morestable geology of Florida (Savonis et al., 2008)
Fig. 16 Schema showing the beach response to sea level rise. For a sea level increase α, sediments from the shoreface are eroded and transported to the submarine section of the beach, resulting to a coastal retreat s.
Fig. 17 Mean temperature rise 1880-2010. NASA Data (Rahmstorf, 2011).
Projections for 2100:
- Increase 0.5 - 4.0 oC, depending on the scenario (IPCC, 2007)
Fig.?? Global sea level changes 1860-2010 (Rahmstorf, 2011).
Projections for 2100:
- 0.20 - 0.59m(IPCC, 2007)
- > 1 m if the melt of Ice sheets is included (Rahmstorf, 2007)
above the mean sea level of 1980-1999
Fig 18. Long term climate-induced increase in sea level (accelerated sea level rise-ASLR) is caused by the thermal expansion of the oceans and the melting of continental ice sheets (IPCC, 2007). The relationship, however is complex, particularly at a regional level
Fig. 20 Annual mean trends (% per century) for 1901-2005 (Grey areas- insufficient data). Time series of annual precipitation (% of mean for 1961-1990) for the different Green bars (annual), black bars (decadal variations). After IPCC (2007).
Fig. 21 (a) The decrease of Arctic sea ice: minimum extent in September 1982 and September 2007 and projections for the future late summers (2010-2030, 2040-2060 and 2070-2090) (http://maps.grida.no/go/graphic/the-decrease-of-arctic-sea-ice-minimum-extent-in-1982-and-2007-and-climate-projections-norwegian). (b) Model results/observations of sea ice loss (Rahmstorf, 2011).
Current trends: More energetic extreme waves
Fig. 22Increases in the annualmean, winteraverages, mean of the highest annual waves and annualmaximasignificant wave heights at the NDBC #46005 platform (NE Pacific). The annual maximum significant wave height has increased 2.4 m! in the last 25 years. (Ruggieroetal., 2010).
Fig. 23 Predictions (estimates) showing an increase in the number of large storms (hurricanes) in the US coast (from M. Beniston, 2009).
Fig. 24 Observed and projected increasein hurricane intensity. If the increase is due to therelatively higher increase in the Atlantic SSTs relative to other oceans, then theintensity might relax to earlier levels as inter-oceanbasin SSTs equilibrate. Conversely, if the intensity is related to absolute SSTs, then evenmore intense cyclones are expected (Steffen, 2009).
Global temperature a result of energy balance
Heat = solar radiation - back radiation
Trends in GHG atmospheric concentration
Fig. 26Atmospheric CO2 concentration (in parts per million) during the last 11000 years (Rahmstorf, 2011) and the last 50 years. The concentrations of the CH4 and N2O (in ppb-parts ber billion) since 1978 are also shown (Richardson et al., 2009).
Climate change: Natural causes
Fig. 27. Astronomical (Milankovich) cycles that force periodic increases and decreases of incoming heat to the Earth system (Zachos and Berger, 2004).
Climate change: Natural causes
Fig.28.Relationship between temperature and CO2 concentration (from ice cores in the Antarctic, Petit et al., 1999) with the astronomical cycles
Climate change: Anthropogenic causes
Fig. 29Tempearture/CO2 concentration increase in the northern hemisphere in the last 1000 years. Note the large and accelerating increase since the industrial revolution (e.g. Mann and Jones, 2003; Zachos and Berger, 2004).
Climate change: Natural and anthropogenic
Diagnosis/prognosis from climatic models (Hadley Centre for Climate Prediction, UK) which show the combined natural/anthropogenic control on temperature; only combined forcing results in aggreemnt between moels and observations ((Mann and Jones, 2003).
Fig. 27 Temperature anomalies with respect to 1901-1950 for 6 oceanic regions for (a) 1906-2005 (black line) and as simulated by known forcings; and (b) as projected for 2001-2100 for the A1B scenario (orange envelope). The bars at the end of the orange envelope represent the range of projected changes for 2091-2100 for the B1 scenario (blue), the A1B scenario (orange) and the A2 scenario (red). Black line is dashed where observations are present for less than 50% of the area in the decade concerned.
Fig. 28 Global mean sea level (relative to the 1980-1999 mean) in the past and future (grey shading shows past uncertainty). The red line from tide gauges (red shading shows variation range). The green line shows global mean sea level observations from satellite altimetry. Blue shading represents the range of model projections for the 21st century, relative to the 1980-1999 mean. Emissions scenario?. More recent research (2008-2011) shows that we may have underestimated the trends by a factor of 2.5-3.
Table 1. IPCC 2007 socioeconomic scenarios (IPCC 2007)
Fig. 29 Scenario-dependent global warming (IPCC 2007)